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1. Crystallization Kinetics of Precipitating Calcium from Yellow Phosphorus Slag Lixivium

Author: Li, G. -B., Luo, D. M., Lai, H.-P., Su, Y., and Du, M.-M.
Subjects: Crystallization kinetics, yellow phosphorus slag lixivium, calcium sulphate, precipitation, Chemistry, QD1-999
Abstract: The crystallization dynamic parameters of calcium sulphate were determined in the course of the precipitation conversion process of calcium in lixivium. The crystallization dynamic equations of calcium sulphate were achieved by multiple linear regression. The study results indicate that CaSO4 · 2 H2O crystal nucleation-growth kinetics equation in nitric acid leaching liquid of yellow phosphorus slag at room temperature is expressed by B0 = 2.904 · 1011 · G0.83 · MT 0.167.
Published: 2014
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2. Identification of Long Noncoding RNAs Expression Profiles Between Gallstone and Gallbladder Cancer Using Next-Generation Sequencing Analysis

Author: Wang Q, Bi P, Luo D, Cao P, Chen W, and Yang B
Subjects: gallstone, gallbladder cancer, long non-coding rna, next-generation sequencing analysis, computational biology, Medicine (General), R5-920
Abstract: Qiang Wang,&ast; Pinduan Bi,&ast; Ding Luo, Pingli Cao, Weihong Chen, Bin Yang Department of Hepatobiliary Surgery, the First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Bin Yang, Department of Hepatobiliary Surgery, the First Affiliated Hospital of Kunming Medical University, No. 295, Xichang Road, Wuhua District, Kunming, People’s Republic of China, Tel +86 013987642890, Email yangbin@kmmu.edu.cnBackground: Gallstone disease (GS) is an important risk factor for Gallbladder cancer (GBC). However, the mechanisms of the progression of GS to GBC remain unclear. Long non-coding RNA (lncRNA), modulates DNA/RNA/proteins at epigenetic, pre-transcriptional, transcriptional and posttranscriptional levels, and plays a potential therapeutic role in various diseases. This study aims to identify lncRNAs that have a potential impact on GS-promoted GBC progression.Methods and Results: Six GBC patients without GS, six normal gallbladder tissues, nine gallstones and nine GBC patients with GS were admitted to our hospital. The next-generation RNA-sequencing was performed to analyze differentially expressed (DE) lncRNA and messenger RNA (mRNA) in four groups. Then overlapping and specific molecular signatures were analyzed. We identified 29 co-DEGs and 500 co-DElncRNAs related to gallstone or GBC. The intersection and concatenation of co-DEGs and co-DElncRNA functionally involved in focal adhesion, Transcriptional misregulation in cancers, Protein digestion and absorption, and ECM-receptor interaction signaling pathways may contribute to the development of gallbladder cancer. Further exploration is necessary for early diagnosis and the potential treatment of GBC. FXYD2, MPZL1 and PAH were observed in both co-DEGs and co-DElncRNA and validated by qRT-PCR.Conclusion: Our data identified a series of DEGs and DElncRNAs, which were involved in the progression of GBC and GS-related metabolism pathways. Compared to GBC, the GS profile was more similar to para-tumor tissues in transcriptome level and lower risk of cancer. Further exploration is necessary from GBC patients with different periods of follow-up gallstone.Keywords: gallstone, gallbladder cancer, long non-coding RNA, next-generation sequencing analysis, computational biology
Published: 2024

3. Lessons to Learn About the Misdiagnosis of a Rare Case in China: Bart Syndrome or Carmi Syndrome?

Author: Wei XQ, Zhang JY, Mei YW, Li EQ, Dai QL, Yang XL, Luo D, Li B, Hua P, Cai J, Lai H, Qi DF, Lai S, Qin M, and Lin YH
Subjects: carmi syndrome, bart syndrome，epidermolysis bullosa，eb，junctional epidermolysis bullosa, jeb, congenital pyloric atresia, cpa, aplasia cutis congenita, acc, congenital localized absence of skin, clas, pyloric atresia, pa, epidermolysis bullosa with pyloric atresia, eb-pa, multidisciplinary teams, mdt., Medicine (General), R5-920
Abstract: Xiaoqing Wei,1,&ast; Junying Zhang,2,&ast; Youwen Mei,3 Eqiong Li,4 Qianling Dai,1 Xiaoli Yang,1 Dan Luo,5 Biao Li,6 Ping Hua,7 Jian Cai,7 Hua Lai,8 Dongfeng Qi,9 Sha Lai,10 Mi Qin,11 Yonghong Lin4 1Department of Cervical Disease and Cervical Cancer Prevention and Treatment, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 2Clinical Laboratory Department, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 3Department of Reproduction and Infertility, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 4Department of Gynecology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 5Department of Obstetrics, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 6Department of Neonatal Intensive Care Unit, Chengdu Women’ and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 7Department of Pathology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 8Department of Radiation and Interventional Therapy, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 9Department of Ultrasonics, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 10Dermatology Department, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China; 11Department of Pediatric Surgery, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yonghong Lin; Xiaoqing Wei, Email linyhcd2011@163.com; xqcherry@163.comObjective: We report a case of Carmi Syndrome in a neonate.Aim: To share our lessons in diagnosis of the case of Carmi Syndrome.Case Report: Carmi Syndrome is an extremely rare autosomal recessive genetic disorder characterized the coexistence of pyloric atresia and junctional epidermolysis bullosa, and with aplasia cutis congenita in approximately 28% patients. In this case, a full-term male neonate was born to a G4P2+1L1 multipara through cesarean section delivery in hospital in a non-consanguineous marriage with 4000mL of II°meconium-stained amniotic fluid. He was found extensive skin loss over lower legs and other parts, with scattered blisters and bilateral microtia. Plain abdominal X-ray revealed a large gastric air bubble with no gas distally. The mother had an intrauterine fetal loss previously for reasons unknown. The dermatologist diagnosed the newborn with Bart Syndrome, while the pediatric surgeon diagnosed congenital pyloric atresia(CPA). The parents refused further treatment and the neonate passed away about 30 hours after birth.Outcome: The neonate passed away about 30 hours after birth.Conclusion: Lessons from this case:①.Rule out Carmi Syndrome in patients with PA, and differentiate Bart syndrome and Carmi Syndrome in patients with abnormal skin manifestations. ②. For rare and/or severe diseases, multidisciplinary teams(MDTs) should be establish. ③. Genetic counseling and prenatal diagnosis are necessary prior to subsequent childbearings. ④.Termination of pregnancy might be contemplated if certain indicators are revealed.Keywords: Carmi syndrome, bart syndrome, epidermolysis bullosa, EB, junctional epidermolysis bullosa, JEB, congenital pyloric atresia, CPA, aplasia cutis congenita, ACC, congenital localized absence of skin, CLAS, pyloric atresia, PA, epidermolysis bullosa with pyloric atresia, EB-PA, multidisciplinary teams, MDT
Published: 2024

4. Performance assessment of helicon wave heating and current drive in EXL-50 spherical torus plasmas

Author: Qiao, G. J., Luo, D., Song, S. D., Dong, J. Q., Shi, Y. J., Li, J. C., Du, D., Peng, Y. K. Martin, Liu, M. S., and team, EXL-50
Subjects: Physics - Plasma Physics
Abstract: Analysis of helicon wave heating and current drive capability in EXL-50 spherical torus plasmas has been conducted. It is found that the driven current increases with the launched parallel refractive index $n_{||}$ and peaks around $n_{||} = 4.0$ when the frequency of the helicon wave is between 300~MHz and 380~MHz. The helicon wave current drive efficiency shows a relatively stable upward trend with increasing plasma temperature. Moreover, the driven current decreases as the plasma density increases. We also analyzed the current drive with helicon waves of 150~MHz and 170~MHz and found that the driven current at a lower frequency was lower than that at a higher frequency. A positive proportional relationship exists between the driven current and $n_{||}$. Besides, as $n_{||}$ increases, the profile of the driven current becomes wider. Finally, the effect of the scrape-off layer (SOL) region on the helicon wave current drive was also investigated.
Published: 2022

5. Plasma SMOC2 Predicts Prognosis in Patients with Heart Failure: A Prospective Cohort

Author: Chen X, Zhong X, Luo D, Lei Y, and Huang R
Subjects: smoc2, heart failure, ischemia cardiomyopathy, readmission rate, myocardial fibrosis, Medicine (General), R5-920
Abstract: Xin Chen,1– 3,&ast; Xing Zhong,1,4,&ast; Dan Luo,1– 3,&ast; Yuhua Lei,1– 3 Rui Huang1– 3 1Cardiovascular Disease Center, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei Province, People’s Republic of China; 2Hubei Selenium and Human Health Institute, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshii, Hubei Province, People’s Republic of China; 3Hubei Provincial Key Laboratory of Selenium Resources and Bio applications, Enshii, Hubei Province, People’s Republic of China; 4Department of Medicine, Hubei Minzu University, Enshi, Hubei Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuhua Lei; Rui Huang, Email yuhualei0319@163.com; henry0923@whu.edu.cnBackground: Heart failure (HF) is a chronic disease with a poor prognosis, making it extremely important to assess the prognosis of patients with HF for accurate treatment. Secreted modular calcium-binding protein 2 (SMOC2) is a cysteine-rich acidic secreted protein that plays a pathophysiological role in many diseases, including regulation of vascular growth factor activity. It has previously been found that SMOC2 plays an essential role in cardiac fibrosis in our previous preclinical study, but whether it can be used as a clinical marker in heart failure patients remains unclear. The purpose of this research was to evaluate the correlation between plasma levels of SMOC2 and the prognosis for individuals with HF.Methods: HF patients diagnosed with ischemic cardiomyopathy were enrolled from January to December 2021. Baseline plasma levels of SMOC2 were measured after demographic and clinical features were collected. Linear and nonlinear multivariate Cox regression models were used to determine the association between plasma SMOC2 and patient outcomes during follow-up. All analysis was performed using SPSS, EmpowerStats, and R software.Results: The study included 188 patients, and the average follow-up time was 489.5± 88.3 days. The plasma SMOC2 concentrations were positively correlated with N-terminal pro-B-type Natriuretic Peptide (NT-proBNP), left ventricular end-diastolic diameter (LVEDd), and length of hospital stay and were negatively correlated with left ventricular ejection fraction (LVEF) at baseline. A total of 53 patients (28.2%) were rehospitalized due to cardiac deterioration, 14 (7.4%) died, and 37 (19.7%) developed malignant arrhythmias. A fully adjusted multivariate COX regression model showed that SMOC2 is associated with readmission (HR = 1.02, 95% CI:1.012– 1.655). A significant increase in rehospitalization risk was observed in group Q2 (HR =1.064, 95% CI: 1.037, 3.662, p=0.005) and group Q3 (HR =1.085, 95% CI:1.086, 3.792, p=0.009) in comparison with group Q1. The p for trend also shows a linear correlation across the three models (P < 0.001). SMOC2 was associated with the severity of HF in patients, but not with all-cause deaths and arrhythmias during follow-up.Conclusion: Plasma SMOC2 is associated with the severity of HF and readmission rate, and is a good predictor of the risk of readmission in patients.Keywords: SMOC2, heart failure, ischemic cardiomyopathy, readmission rate, myocardial fibrosis
Published: 2024

6. Predicting COVID-19 Re-Positive Cases in Malnourished Older Adults: A Clinical Model Development and Validation

Author: Chen J, Luo D, Sun C, Sun X, Dai C, Hu X, Wu L, Lei H, Ding F, Chen W, and Li X
Subjects: malnutrition, covid-19, re-positive, clinical prediction model, Geriatrics, RC952-954.6
Abstract: Jiao Chen, Danmei Luo, Chengxia Sun, Xiaolan Sun, Changmao Dai, Xiaohong Hu, Liangqing Wu, Haiyan Lei, Fang Ding, Wei Chen, Xueping Li Geriatric Department, Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of ChinaCorrespondence: Xueping Li, Chengdu University of Traditional Chinese Medicine, No. 37, Shier Bridge Road, Chengdu, Sichuan, People’s Republic of China, Tel +86-18380251086, Email 3173907@qq.comPurpose: Building and validating a clinical prediction model for novel coronavirus (COVID-19) re-positive cases in malnourished older adults.Patients and Methods: Malnourished older adults from January to May 2023 were retrospectively collected from the Department of Geriatrics of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine. They were divided into a “non-re-positive” group and a “re-positive” group based on the number of COVID-19 infections, and into a training set and a validation set at a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify predictive factors for COVID-19 re-positivity in malnourished older adults, and a nomogram was constructed. Independent influencing factors were screened by multivariate logistic regression. The model’s goodness-of-fit, discrimination, calibration, and clinical impact were assessed by Hosmer-Lemeshow test, area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CIC), respectively.Results: We included 347 cases, 243 in the training set, and 104 in the validation set. We screened 10 variables as factors influencing the outcome. By multivariate logistic regression analysis, preliminary identified protective factors, risk factors, and independent influencing factors that affect the re-positive outcome. We constructed a clinical prediction model for COVID-19 re-positivity in malnourished older adults. The Hosmer-Lemeshow test yielded χ2 =5.916, P =0.657; the AUC was 0.881; when the threshold probability was > 8%, using this model to predict whether malnourished older adults were re-positive for COVID-19 was more beneficial than implementing intervention programs for all patients; when the threshold was > 80%, the positive estimated value was closer to the actual number of cases.Conclusion: This model can help identify the risk of COVID-19 re-positivity in malnourished older adults early, facilitate early clinical decision-making and intervention, and have important implications for improving patient outcomes. We also expect more large-scale, multicenter studies to further validate, refine, and update this model.Keywords: malnutrition, COVID-19, re-positive, clinical prediction model
Published: 2024

7. Multi-scale time-resolved electron diffraction: A case study in moir\'e materials

Author: Duncan, C. J. R., Kaemingk, M., Li, W. H., Andorf, M. B., Bartnik, A. C., Galdi, A., Gordon, M., Pennington, C. A., Bazarov, I. V., Zeng, H. J., Liu, F., Luo, D., Sood, A., Lindenberg, A. M., Tate, M. W., Muller, D. A., Thom-Levy, J., Gruner, S. M., and Maxson, J. M.
Subjects: Physics - Instrumentation and Detectors, Condensed Matter - Materials Science
Abstract: Ultrafast-optical-pump -- structural-probe measurements, including ultrafast electron and x-ray scattering, provide direct experimental access to the fundamental timescales of atomic motion, and are thus foundational techniques for studying matter out of equilibrium. High-performance detectors are needed in scattering experiments to obtain maximum scientific value from every probe particle. We deploy a hybrid pixel array direct electron detector to perform ultrafast electron diffraction experiments on a WSe$_2$/MoSe$_2$ 2D heterobilayer, resolving the weak features of diffuse scattering and moir\'e superlattice structure without saturating the zero order peak. Enabled by the detector's high frame rate, we show that a chopping technique provides diffraction difference images with signal-to-noise at the shot noise limit. Finally, we demonstrate that a fast detector frame rate coupled with a high repetition rate probe can provide continuous time resolution from femtoseconds to seconds, enabling us to perform a scanning ultrafast electron diffraction experiment that maps thermal transport in WSe$_2$/MoSe$_2$ and resolves distinct diffusion mechanisms in space and time., Comment: Submitted manuscript, 22 pages, 5 figures
Published: 2022

8. Investigation of the effectiveness of non-inductive `multi-harmonic' electron cyclotron current drive through modeling multi-pass absorptions in the EXL-50 spherical tokamak

Author: Banerjee, D., Song, S. D., Xie, H. S., Liu, B., Wang, M. Y., Liu, W. J., Chen, B., Han, L., Luo, D., Song, Y. Y., Petrov, Yu. V., Song, X. M., Liu, M. S., Harvey, R. W., Shi, Y. J., Peng, Y. K. M., and team, the EXL50
Subjects: Physics - Plasma Physics
Abstract: The effectiveness of multiple electron cyclotron resonance (ECR) harmonics has been thoroughly investigated in context of high current drive efficiency, generally observed in fully non-inductive operation of the low aspect ratio EXL-50 spherical tokamak (ST) powered by electron cyclotron (EC) waves. The Fokker-Plank equation is numerically solved to obtain electron distribution function, under steady state of the relativistic nonlinear Coulomb collision and quasi-linear diffusion operators, for calculating plasma current driven by the injected EC wave. For the extra-ordinary EC wave, simulation results unfold a mechanism by which electrons moving around the cold second harmonic ECR layer strongly resonate with higher harmonics via the relativistic Doppler shifted resonance condition. This feature is in fact evident above a certain value of input EC wave power in simulation, indicating it to be a non-linear phenomenon. Similar to the experimental observation, high efficiency in current drive (over 1 A/W) has indeed been found in simulation for a typical low density ($\sim 1\times10^{18}~m^{-3}$), low temperature ($\lesssim 100$ eV) plasma of EXL-50 by taking into account multi-pass absorptions in our simulation model. However, such characteristic is not found in the ordinary EC-wave study for both single-pass and multi-pass simulations, suggesting it as inefficient in driving current on our ST device., Comment: 22 pages, 15 figures. Submitted to the Nuclear Fusion journal
Published: 2021

9. Rehybridization dynamics into the pericyclic minimum of an electrocyclic reaction imaged in real-time

Author: Liu, Y., Sanchez, D. M., Ware, M. R., Champenois, E. G., Yang, J., Nunes, J. P. F., Attar, A., Centurion, M., Cryan, J. P., Forbes, R., Hegazy, K., Hoffmann, M. C., Ji, F., Lin, M.-F., Luo, D., Saha, S. K., Shen, X., Wang, X. J., Martínez, T. J., and Wolf, T. J. A.
Published: 2023
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10. Conformer-specific Chemistry Imaged in Real Space and Time

Author: Champenois, E. G., Sanchez, D. M., Yang, J., Nunes, J. P. F., Attar, A., Centurion, M., Forbes, R., Gühr, M., Hegazy, K., Ji, F., Saha, S. K., Liu, Y., Lin, M. -F., Luo, D., Moore, B., Shen, X., Ware, M. R., Wang, X. J., Martínez, T. J., and Wolf, T. J. A.
Subjects: Physics - Chemical Physics
Abstract: Conformational isomers or conformers of molecules play a decisive role in chemistry and biology. However, experimental methods to investigate chemical reaction dynamics are typically not conformer-sensitive. Here, we report on a gas-phase megaelectronvolt ultrafast electron diffraction investigation of {\alpha}-phellandrene undergoing an electrocyclic ring-opening reaction. We directly image the evolution of a specific set of {\alpha}-phellandrene conformers into the product isomer predicted by the Woodward-Hoffmann rules in real space and time. Our experimental results are in quantitative agreement with nonadiabatic quantum molecular dynamics simulations, which provide unprecedented detail of how conformation influences time scale and quantum efficiency of photoinduced ring-opening reactions. Due to the prevalence of large numbers of conformers in organic chemistry, our findings impact our general understanding of reaction dynamics in chemistry and biology.
Published: 2021
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11. Untargeted Metabolomics of Feces Reveals Diagnostic and Prognostic Biomarkers for Active Tuberculosis and Latent Tuberculosis Infection: Potential Application for Precise and Non-Invasive Identification

Author: Luo D, Yang BY, Qin K, Shi CY, Wei NS, Li H, Qin YX, Liu G, Qin XL, Chen SY, Guo XJ, Gan L, Xu RL, Dong BQ, and Li J
Subjects: feces, latent tuberculosis infection, active tuberculosis, biomarkers, progression, metabolomics, Infectious and parasitic diseases, RC109-216
Abstract: Dan Luo,1,2,&ast; Bo-Yi Yang,3,&ast; Kai Qin,4 Chong-Yu Shi,3 Nian-Sa Wei,4 Hai Li,1 Yi-Xiang Qin,1 Gang Liu,1 Xiao-Ling Qin,1 Shi-Yi Chen,1 Xiao-Jing Guo,1 Li Gan,1 Ruo-Lan Xu,1 Bai-Qing Dong,1 Jing Li5 1Department of Biostatistics, School of Public Health and Management of Guangxi University of Chinese Medicine, Nanning, Guangxi, People’s Republic of China; 2Guangxi Key Laboratory of Translational Medicine for Treating High-Incidence Infectious Diseases with Integrative Medicine, Guangxi University of Chinese Medicine, Nanning, Guangxi, People’s Republic of China; 3The First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 4The Second Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 5Deparment of Physiology, School of Basic Medical Sciences of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Bai-Qing Dong, Guangxi University of Chinese Medicine, 13 Wuhe Road, Nanning, Guangxi, 530200, People’s Republic of China, Tel/Fax +86-771-4928360, Email 764937318@qq.com Jing Li, Guangxi Medical University, 22 Shuangyong Road, Nanning, Guangxi, 530021, People’s Republic of China, Tel/Fax +86-771-5358212, Email lijing@gxmu.edu.cnPurpose: Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) is important to control the prevalence of tuberculosis; however, there is currently no effective method. The aim of this study was to discover specific metabolites through fecal untargeted metabolomics to discriminate ATB, individuals with LTBI, and healthy controls (HC) and to probe the metabolic perturbation associated with the progression of tuberculosis.Patients and Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to comprehensively detect compounds in fecal samples from HC, LTBI, and ATB patients. Differential metabolites between the two groups were screened, and their underlying biological functions were explored. Candidate metabolites were selected and enrolled in LASSO regression analysis to construct diagnostic signatures for discriminating between HC, LTBI, and ATB. A receiver operating characteristic (ROC) curve was applied to evaluate diagnostic value. A nomogram was constructed to predict the risk of progression of LTBI.Results: A total of 35 metabolites were found to exist differentially in HC, LTBI, and ATB, and eight biomarkers were selected. Three diagnostic signatures based on the eight biomarkers were constructed to distinguish between HC, LTBI, and ATB, demonstrating excellent discrimination performance in ROC analysis. A nomogram was successfully constructed to evaluate the risk of progression of LTBI to ATB. Moreover, 3,4-dimethylbenzoic acid has been shown to distinguish ATB patients with different responses to etiological tests.Conclusion: This study constructed diagnostic signatures based on fecal metabolic biomarkers that effectively discriminated HC, LTBI, and ATB, and established a predictive model to evaluate the risk of progression of LTBI to ATB. The results provide scientific evidence for establishing an accurate, sensitive, and noninvasive differential diagnosis scheme for tuberculosis.Keywords: feces, latent tuberculosis infection, active tuberculosis, biomarkers, progression, metabolomics
Published: 2023

12. Influencing Factors of Treatment Outcomes Among Patients with Pulmonary Tuberculosis: A Structural Equation Model Approach

Author: Liu K, Zhang M, Luo D, Zheng Y, Shen Z, Chen B, and Jiang J
Subjects: pulmonary tuberculosis, structural equation model, treatment outcome, depression, Psychology, BF1-990, Industrial psychology, HF5548.7-5548.85
Abstract: Kui Liu,1,&ast; Mengdie Zhang,2,&ast; Dan Luo,3 Yan Zheng,4 Zhenye Shen,4 Bin Chen,1 Jianmin Jiang1,5 1Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China; 2Department of Social Medicine of School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China; 3Department of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang Province, People’s Republic of China; 4Department of Tuberculosis Control and Prevention, Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang Province, People’s Republic of China; 5Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Bin Chen; Jianmin Jiang, Email Bchen@cdc.zj.cn; Jmjiang@cdc.zj.cnBackground: Pulmonary tuberculosis (PTB) is a serious infectious disease, and the factors and pathways that influence final treatment outcomes are unclear. Here, we aimed to assess the factors that influence treatment outcomes in patients with PTB using a structural equation model.Methods: Participants completed a questionnaire covering demographics, understanding of PTB, psychological status, and history of medical treatment. Exploratory factor analysis and reliability testing were performed, and a structural equation model was constructed using the SPSS and Amos software.Results: A total of 251 participants were enrolled. Symptoms of depression were observed in 94.4% of participants, whereas 6% showed mild or greater anxiety. Through factor rotation, four common factors were extracted with a total variation of 66.15%. The structural equation model indicated that regular tuberculosis-related follow-up behaviour had a direct and positive effect on the final treatment outcome, with a path coefficient value of 0.20; the level of PTB understanding had a direct positive effect on the testing behaviour for PTB, with a path coefficient of 0.26; patients’ psychological characteristics had a direct negative impact on regular testing behaviour, with a path coefficient of − 0.13. The psychological characteristics and level of disease understanding of patients exerted indirect effects on the treatment outcome by affecting the way patients approached tuberculosis detection behaviour.Conclusion: Interventions aimed at improving the treatment outcomes of patients with PTB should mainly focus on financial support and improvements in psychological status in addition to a greater understanding and knowledge of PTB. Furthermore, patients should be encouraged to undergo regular PTB testing during the follow up period, as this mediates the effect of other factors on treatment outcomes and also helps in achieving favourable treatment outcomes.Keywords: pulmonary tuberculosis, structural equation model, treatment outcome, depression
Published: 2023

13. Whole Genomic Analysis Revealed High Genetic Diversity and Drug-Resistant Characteristics of Mycobacterium tuberculosis in Guangxi, China

Author: Liang D, Song Z, Liang X, Qin H, Huang L, Ye J, Lan R, Luo D, Zhao Y, and Lin M
Subjects: tuberculosis, mycobacterium tuberculosis, drug-resistance, genetic diversity, whole genome sequencing, Infectious and parasitic diseases, RC109-216
Abstract: Dabin Liang,1,2,&ast; Zexuan Song,3,&ast; Xiaoyan Liang,1,2,&ast; Huifang Qin,1,2 Liwen Huang,1,2 Jing Ye,1,2 Rushu Lan,4 Dan Luo,5 Yanlin Zhao,3 Mei Lin1,2 1Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China; 2Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China; 3National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China; 4Department of Clinical Laboratory, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, People’s Republic of China; 5School of Public Health and Management, Guangxi University of Chinese Medicine, Nanning, Guangxi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yanlin Zhao, National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People’s Republic of China, Email zhaoyl@chinacdc.cn Mei Lin, Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530023, People’s Republic of China, Email gxlinmei@126.comBackground: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a major public health issue in China. Nevertheless, the prevalence and drug resistance characteristics of isolates vary in different regions and provinces. In this study, we investigated the population structure, transmission dynamics and drug-resistant profiles of Mtb in Guangxi, located on the border of China.Methods: From February 2016 to April 2017, 462 clinical M. tuberculosis isolates were selected from 5 locations in Guangxi. Drug-susceptibility testing was performed using 6 common anti-tuberculosis drugs. The genotypic drug resistance and transmission dynamics were analyzed by the whole genome sequence.Results: Our data showed that the Mtb in Guangxi has high genetic diversity including Lineage 1 to Lineage 4, and mostly belong to Lineage 2 and Lineage 4. Novelty, 9.6% of Lineage 2 isolates were proto-Beijing genotype (L2.1), which is rare in China. About 12.6% of isolates were phylogenetically clustered and formed into 28 transmission clusters. We observed that the isolates with the high resistant rate of isoniazid (INH, 21.2%), followed by rifampicin (RIF, 13.2%), and 6.7%, 12.1%, 6.7% and 1.9% isolates were resistant to ethambutol (EMB), streptomycin (SM), ofloxacin (OFL) and kanamycin (KAN), respectively. Among these, 6.5% and 3.3% of isolates belong to MDR-TB and Pre-XDR, respectively, with a high drug-resistant burden. Genetic analysis identified the most frequently encountered mutations of INH, RIF, EMB, SM, OFL and KAN were katG_Ser315Thr (62.2%), rpoB_Ser450Leu (42.6%), embB_Met306Vol (45.2%), rpsL_Lys43Arg (53.6%), gyrA_Asp94Gly (29.0%) and rrs_A1401G (66.7%), respectively. Additionally, we discovered that isolates from border cities are more likely to be drug-resistant than isolates from non-border cities.Conclusion: Our findings provide a deep analysis of the genomic population characteristics and drug-resistant of M. tuberculosis in Guangxi, which could contribute to developing effective TB prevention and control strategies.Keywords: tuberculosis, Mycobacterium tuberculosis, drug-resistance, genetic diversity, whole genome sequencing
Published: 2023

14. Onset and Irreversibility of Granulation of Bose-Einstein condensates under Feshbach Resonance Management

Author: Lode, A. U. J., Tsatsos, M. C., Kevrekidis, P. G., Telles, G. D., Luo, D., Hulet, R. G., and Bagnato, V. S.
Subjects: Condensed Matter - Quantum Gases, Quantum Physics
Abstract: Granulation of quantum matter -- the formation of persistent small-scale patterns -- is realized in the images of quasi-one-dimensional Bose-Einstein condensates perturbed by a periodically modulated interaction. Our present analysis of a mean-field approximation suggests that granulation is caused by the gradual transformation of phase undulations into density undulations. This is achieved by a suitably large modulation frequency, while for low enough frequencies the system exhibits a quasi-adiabatic regime. We show that the persistence of granulation is a result of the irregular evolution of the phase of the wavefunction representing an irreversible process. Our model predictions agree with numerical solutions of the Schr\"odinger equation and experimental observations. The numerical computations reveal the emergent many-body correlations behind these phenomena via the multi-configurational time-dependent Hartree theory for bosons (MCTDHB)., Comment: 7 pages, 2 figures + 9 pages, 2 figures, software available at http://ultracold.org
Published: 2021

15. Transcriptome Profiling Analysis of Breast Cancer Cell MCF-7 Treated by Sesamol

Author: Wu J, Luo D, and Xu J
Subjects: breast cancer cells, sesamol, transcriptome, differentially expressed genes, go and kegg pathway analyses, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Jiafa Wu,1 Dongping Luo,2 Jiayun Xu2 1School of Food and Bioengineering, Henan University of Science and Technology, Luoyang, People’s Republic of China; 2The First Affiliated Hospital, Henan University of Science and Technology, Luoyang, People’s Republic of ChinaCorrespondence: Jiafa Wu, School of Food and Bioengineering, Henan University of Science and Technology, Kaiyuan Avenue 263, Luoyang, People’s Republic of China, Email wujiafa@haust.edu.cn Jiayun Xu, The First Affiliated Hospital, Henan University of Science and Technology, Guanlin Avenue 636, Luoyang, People’s Republic of China, Email xujy_haust@163.comBackground: Breast cancer is a highly malignant tumor that affects a large number of women worldwide. Sesamol, a natural compound, has been shown to exhibit inhibitory effects on various tumors, including breast cancer. However, the underlying mechanism of its action has not been fully explored. In this study, we aimed to investigate the effect of sesamol on the transcriptome of MCF-7 breast cancer cells, in order to better understand its potential as an anti-cancer agent.Methods: The transcriptome profiles of MCF-7 breast cancer cells treated with sesamol were analyzed using Illumina deep-sequencing. The differentially expressed genes (DEGs) between the control and sesamol-treated groups were identified, and GO and KEGG pathway analyses of these DEGs were conducted using ClueGO. Protein–protein interaction (PPI) network of DEGs was mapped on STRING database and visualized by Cytoscape software. Hub genes in the network were screened by Cytohubba plugin of Cytoscape. Prognostic values of hub genes were analyses by the online Kaplan–Meier plotter and validated by qRT-PCR in MCF-7 cells.Results: The results of the study showed that sesamol treatment had a significant effect on the transcriptome of MCF-7 cells, with a total of 351 DEGs identified. Functional enrichment analyses of DEGs revealed their involvement in extracellular matrix (ECM) remodeling, fatty acid metabolism and monocyte chemotaxis. The protein–protein interaction (PPI) network analysis of DEGs resulted in the identification of 10 hub genes, namely IGF2, MMP1, MSLN, CXCL10, WT1, ITGAL, PLD1, MME, TWIST1, and FOXA2. Survival analysis showed that MMP1 and ITGAL were significantly associated with overall survival (OS) and recovery-free survival (RFS) in breast cancer patients.Conclusion: Sesamol may play important roles in extracellular matrix (ECM) remodeling, fatty acid metabolism and cell cycle of MCF-7.Keywords: breast cancer cells, sesamol, transcriptome, differentially expressed genes, GO and KEGG pathway analyses
Published: 2023

16. Scene recognition based on DNN and game theory with its applications in human-robot interaction

Author: Wang, R. Q., Wang, W. Z., Zhao, D. Z., Chen, G. H., and Luo, D. S.
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Scene recognition model based on the DNN and game theory with its applications in human-robot interaction is proposed in this paper. The use of deep learning methods in the field of scene recognition is still in its infancy, but has become an important trend in the future. As the innovative idea of the paper, we propose the following novelties. (1) In this paper, the image registration problem is transformed into a problem of minimum energy in Markov Random Field to finalize the image pre-processing task. Game theory is used to find the optimal. (2) We select neighboring homogeneous sample features and the neighboring heterogeneous sample features for the extracted sample features to build a triple and modify the traditional neural network to propose the novel DNN for scene understanding. (3) The robot control is well combined to guide the robot vision for multiple tasks. The experiment is then conducted to validate the overall performance.
Published: 2019

17. Neutrophil Extracellular Traps Induce Alveolar Macrophage Pyroptosis by Regulating NLRP3 Deubiquitination, Aggravating the Development of Septic Lung Injury

Author: Cui Y, Yang Y, Tao W, Peng W, Luo D, Zhao N, Li S, Qian K, and Liu F
Subjects: sepsis, neutrophil extracellular traps, macrophage pyroptosis, nlrp3 inflammasomes, ubiquitination, oxidative stress, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Yamei Cui,&ast; Ying Yang,&ast; Wenqiang Tao, Wei Peng, Deqiang Luo, Ning Zhao, Shuangyan Li, Kejian Qian, Fen Liu Department of Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Fen Liu, Department of Critical Care Medicine, The First Affiliated Hospital of Nanchang University, No. 17 Yongwaizheng Street, Dong Lake District, Nanchang, 330000, People’s Republic of China, Tel +86 0791 88692533, Email liufen9934@163.comBackground: Uncontrolled inflammation is a typical feature of sepsis-related lung injury. The key event in the progression of lung injury is Caspase-1-dependent alveolar macrophage (AM) pyroptosis. Similarly, neutrophils are stimulated to release neutrophil extracellular traps (NETs) to participate in the innate immune response. This study aims to illustrate the specific mechanisms by which NETs activate AM at the post-translational level and maintain lung inflammation.Methods: We established a septic lung injury model by caecal ligation and puncture. We found elevated NETs and interleukin-1b (IL-1β) levels in the lung tissues of septic mice. Western blot and immunofluorescence analyses was utilized to determine whether NETs promote AM pyroptosis and whether degrading NETs or targeting the NLRP3 inflammasome had protective effects on AM pyroptosis and lung injury. Flow cytometric and co-immunoprecipitation analyses verified intracellular reactive oxygen species (ROS) levels and the binding of NLRP3 and ubiquitin (UB) molecules, respectively.Results: Increased NETs production and IL-1β release in septic mice were correlated with the degree of lung injury. NETs upregulated the level of NLRP3, followed by NLRP3 inflammasome assembly and caspase-1 activation, leading to AM pyroptosis executed by the activated fragment of full-length gasdermin D (FH-GSDMD). However, the opposite effect was observed in the context of NETs degradation. Furthermore, NETs markedly elicited an increase in ROS, which facilitated the activation of NLRP3 deubiquitination and the subsequent pyroptosis pathway in AM. Removal of ROS could promote the binding of NLRP3 and ubiquitin, inhibit NLRP3 binding to apoptosis-associated spotted proteins (ASC) and further alleviate the inflammatory changes in the lungs.Conclusion: In summary, these findings indicate that NETs prime ROS generation, which promotes NLRP3 inflammasome activation at the post-translational level to mediate AM pyroptosis and sustain lung injury in septic mice.Keywords: sepsis, neutrophil extracellular traps, macrophage pyroptosis, NLRP3 inflammasomes, ubiquitination, oxidative stress
Published: 2023

18. Recovery of antimony and bismuth from arsenic-containing waste streams from the copper electrorefining circuit: An example of promoting critical metals circularity from secondary resources

Author: Luo, D., Fernández de Labastida, M., Cortina, J.L., and Lopez, J.
Published: 2023
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19. Simultaneous measurement of beta-delayed proton and gamma emission of $^{26}$P for $^{25}$Al($p,\gamma$)$^{26}$Si reaction rate

Author: Liang, P. F., Sun, L. J., Lee, J., Hou, S. Q., Xu, X. X., Lin, C. J., Yuan, C. X., He, J. J., Li, Z. H., Wang, J. S., Wang, D. X., Wu, H. Y., Yang, Y. Y., Lam, Y. H., Ma, P., Duan, F. F., Gao, Z. H., Hu, Q., Bai, Z., Ma, J. B., Wang, J. G., Zhong, F. P., Wu, C. G., Luo, D. W., Jiang, Y., Liu, Y., Hou, D. S., Li, R., Ma, N. R., Ma, W. H., Shi, G. Z., Yu, G. M., Patel, D., Jin, S. Y., Wang, Y. F., Yu, Y. C., Zhou, Q. W., Wang, P., Hu, L. Y., Wang, X., Zang, H. L., Li, P. J., Zhao, Q. Q., Yang, L., Wen, P. W., Yang, F., Jia, H. M., Zhang, G. L., Pan, M., Wang, X. Y., Sun, H. H., Hu, Z. G., Chen, R. F., Liu, M. L., Yang, W. Q., and Zhao, Y. M.
Subjects: Nuclear Experiment
Abstract: $\beta$ decay of $^{26}$P was used to populate the astrophysically important $E_x=$5929.4(8) keV $J^{\pi}=3{^+}$ state of $^{26}$Si. Both $\beta$-delayed proton at 418(8) keV and gamma ray at 1742(2) keV emitted from this state were measured simultaneously for the first time with corresponding absolute intensities of 11.1(12)\% and 0.59(44)\%, respectively. Besides, shell model calculations with weakly bound effects were performed to investigate the decay properties of other resonant states and a spin-parity of $4^+$ rather than $0^+$ was favored for the $E_x=$5945.9(40) keV state. Combining the experimental results and theoretical calculations, $^{25}$Al($p,\gamma$)$^{26}$Si reaction rate in explosive hydrogen burning environments was calculated and compared with previous studies.
Published: 2019
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20. Nitrogen Contamination Causes High Field Q-Slope (HFQS) in Buffered Chemical Polished SRF Cavities

Author: Luo, D., Saito, K., and Shanab, S.
Subjects: Physics - Accelerator Physics
Abstract: Buffered Chemical Polishing (BCP) was the most conventional polishing method for superconducting radio frequency (SRF) Niobium (Nb) cavity surface preparation before the discovery of Electropolishing (EP), which is superior to BCP in high gradient performance. The High Field Q-slope (HFQS) is perfectly eliminated by taking the low temperature bake (LTB) post EP, which guarantees high gradient performance in EP'ed cavities. The mechanism of the HFQS is well understood for EP'ed cavities. On the other hand, there is no common consensus on the HFQS with BCP, since even BCP with LTB does not always resolve the HFQS. BCP is much easier to apply and still an important preparation technology for very complicated SRF structures like low beta cavities. Therefore, overcoming the issue of HFQS with BCP is highly beneficial to the SRF community. This paper mines a large number of available data sets on BCP'ed cavity performance with fine grain, large grain, and even single crystal niobium materials under different experimental settings. We found that all existing explanations for HFQS with BCP are inconsistent with some experimental results, and propounded nitrogen contamination as a new model. We checked that nitrogen contamination agrees with all existing data and nicely explains unresolved phenomena. Combining these evidence, we deduce that nitrogen contamination is the cause of HFQS in BCP.
Published: 2019

21. Experimental Upper Bound and Theoretical Expectations for Parity-Violating Neutron Spin Rotation in 4He

Author: Swanson, H. E., Bass, C. D., Bass, T. D., Crawford, B. E., Dawkins, J. M., Gan, K., Heckel, B. R., Horton, J. C., Huffer, C., Luo, D., Markoff, D. M., Micherdzinska, A. M., Mumm, H. P., Nico, J. S., Sarsour, M., Sharapov, E. I., Snow, W. M., Walbridge, S. B., and Zhumabekova, V.
Subjects: Nuclear Experiment
Abstract: Neutron spin rotation is expected from quark-quark weak interactions in the Standard Model, which induce weak interactions among nucleons that violate parity. We present the results from an experiment searching for the effect of parity violation via the spin rotation of polarized neutrons in a liquid $^{4}$He medium. The value for the neutron spin rotation angle per unit length in $^{4}$He, $d\phi/dz =(+2.1 \pm 8.3 (stat.) \pm 2.9 (sys.))\times10^{-7}$ rad/m, is consistent with zero. The result agrees with the best current theoretical estimates of the size of nucleon-nucleon weak amplitudes from other experiments and with the expectations from recent theoretical approaches to weak nucleon-nucleon interactions. In this paper we review the theoretical status of parity violation in the $\vec{n}+^{4}$He system and discuss details of the data analysis leading to the quoted result. Analysis tools are presented that quantify systematic uncertainties in this measurement and that are expected to be essential for future measurements., Comment: 15 pages, 7 figures
Published: 2019
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22. Low-Dimensional Contact Layers for Enhanced Perovskite Photodiodes

Author: Luo, D, Zou, T, Yang, W, Xiang, B, Yang, X, Wang, Y, Su, R, Zhao, L, Zhu, R, Zhou, H, Russell, TP, Yu, H, and Lu, ZH
Subjects: Physical Sciences, Chemical Sciences, Engineering, Materials
Abstract: Controlling defects and energy-band alignments are of paramount importance to the development of high-performance perovskite-based photodiodes. Yet, concurrent improvements in interfacial contacts and defect reduction simply by tailoring bottom contacts have not been investigated. An effective strategy is reported that can simultaneously improve energy-band alignments and structural defects by introducing low-dimensional contact (LDC) layers at the bottom interface. It is found that LDC-based perovskites considerably suppress undesirable structural defects induced by microstrains, resulting in reduced nonradiative recombination centers and improved carrier lifetimes. Additionally, the resulting LDC-based interface structures help block minority carrier injection from the electrodes by forming built-in electric fields. As a consequence, LDC-based perovskite photodiodes showed improved light detection capabilities. The result opens an avenue to yield highly efficient photodiodes.
Published: 2020

23. Increasing the circularity of the copper metallurgical industry: Recovery of Sb(III) and Bi(III) from hydrochloric solutions by integration of solvating organophosphorous extractants and selective precipitation

Author: Benabdallah, N., Luo, D., Hadj Youcef, M., Lopez, J., Fernández de Labastida, M., Sastre, A.M., Valderrama, C.A., and Cortina, J.L.
Published: 2023
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24. Ovo Like Zinc Finger 2 (OVOL2) Suppresses Breast Cancer Stem Cell Traits and Correlates with Immune Cells Infiltration

Author: Wu J, Luo D, and Li S
Subjects: ovol2, gene ontology, kegg pathway, bcscs, immune cell infiltration, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Jiafa Wu,1 Dongping Luo,2 Shengnan Li3 1School of Food and Bioengineering, Henan University of Science and Technology, Luoyang, People’s Republic of China; 2The First Affiliated Hospital, Henan University of Science and Technology, Luoyang, People’s Republic of China; 3School of Medicine, Henan Polytechnic University, Jiaozuo, People’s Republic of ChinaCorrespondence: Jiafa Wu, School of Food and Bioengineering, Henan University of Science and Technology, Kaiyuan Avenue 263, Luoyang, People’s Republic of China, Email wujiafa@haust.edu.cnBackground: Breast cancer stem cells (BCSCs) are associated with tumor initiation, invasion, metastasis and drug resistance. It is known that many proteins and signaling pathways are involved in the regulation of BCSCs, however, much more efforts are needed to understand BCSCs comprehensively. Tumor-infiltrating immune cells are important in cancer treatment efficacy and patient prognosis. We tried to identify potential suppressor of BCSCs and analyze its correlation with various immune cells infiltration by bioinformatic and experimental methods.Methods: Expression level and methylation state of OVOL2 were analyzed by tools from bc-GenExMiner v4.8 and UALCAN databases. The Kaplan–Meier plotter was applied to evaluate the prognostic values of OVOL2. Gene expression datasets (GSE7515, GSE15192) were selected to analyze differentially expressed genes (DEGs) related to BCSCs. GO and KEGG pathway analyses of DEGs were conducted. MCODE app plugin of Cytoscape was used to screen modules in PPI network of downregulated DEGs. Correlation of OVOL2 expression with infiltrating immune cells was evaluated by TIMER 2.0. Experiments were conducted to verify whether OVOL2 could inhibit stemness traits of breast cancer cell MDA-MB-231.Results: The expression level of OVOL2 in basal/TNBC was significantly lower than that of other subtypes. Survival analyses indicated that high expression of OVOL2 was associated with favorable prognosis. GO and KEGG pathway analyses for upregulated and downregulated DEGs were conducted. The top three clusters of downregulated DEGs showed that tight junction and chemokines may play important roles in BCSCs. OVOL2 is one module of clusters. OVOL2 expression is correlated with various immune cells infiltration. Experiments showed that OVOL2 suppresses CD44+/CD24− ratio and mammospheres formation of MDA-MB-231.Conclusion: OVOL2 may play an important role in the regulation of breast cancer stemness and immune cell infiltration, and is likely to be a target for the treatment of breast cancer.Keywords: OVOL2, gene ontology, KEGG pathway, BCSCs, immune cell infiltration
Published: 2022

25. Beta-decay spectroscopy of $^{27}$S

Author: Sun, L. J., Xu, X. X., Hou, S. Q., Lin, C. J., José, J., Lee, J., He, J. J., Li, Z. H., Wang, J. S., Yuan, C. X., Wang, D. X., Wu, H. Y., Liang, P. F., Yang, Y. Y., Lam, Y. H., Ma, P., Duan, F. F., Gao, Z. H., Hu, Q., Bai, Z., Ma, J. B., Wang, J. G., Zhong, F. P., Wu, C. G., Luo, D. W., Jiang, Y., Liu, Y., Hou, D. S., Li, R., Ma, N. R., Ma, W. H., Shi, G. Z., Yu, G. M., Patel, D., Jin, S. Y., Wang, Y. F., Yu, Y. C., Zhou, Q. W., Wang, P., Hu, L. Y., Wang, X., Zang, H. L., Li, P. J., Zhao, Q. Q., Yang, L., Wen, P. W., Yang, F., Jia, H. M., Zhang, G. L., Pan, M., Wang, X. Y., Sun, H. H., Hu, Z. G., Chen, R. F., Liu, M. L., Yang, W. Q., Zhao, Y. M., and Zhang, H. Q.
Subjects: Nuclear Experiment
Abstract: Background: Beta-decay spectroscopy provides valuable nuclear physics input for thermonuclear reaction rates of astrophysical interest and stringent test for shell-model theories far from the stability line. Purpose: The available decay properties of proton drip-line nucleus $^{27}$S is insufficient to constrain the properties of the key resonance in $^{26}$Si$(p,\gamma)^{27}$P reaction rate and probe the possible isospin asymmetry. The decay scheme of $^{27}$S is complicated and far from being understood, which has motivated but also presented challenges for our experiment. Method: The $^{27}$S ions were implanted into a double-sided silicon strip detector array surrounded by the high-purity germanium detectors, where the $\beta$-delayed protons and $\gamma$ rays were measured simultaneously. Results: The improved spectroscopic properties including the precise half-life of $^{27}$S, the excitation energies, $\beta$-decay branching ratios, log~$ft$ values, and $B$(GT) values for the states of $^{27}$P populated in the $\beta$ decay of $^{27}$S were measured and compared to the $^{27}$Mg mirror states and the shell-model calculations. The present work has expanded greatly on the previously established decay scheme of $^{27}$S. Conclusions: The precise proton-separation energy of $^{27}$P, the energy and the ratio between $\gamma$ and proton partial widths of the $3/2^+$ resonance were obtained, thereby determining the $^{26}$Si$(p,\gamma)^{27}$P reaction rate based mainly on experimental constraints. The first evidence for the observation of a large isospin asymmetry for the mirror decays of $^{27}$S and $^{27}$Na is also provided. The experimental spectroscopic information can be reproduced by the shell-model calculation taking the weakly bound effect of the proton $1s_{1/2}$ orbit into account.
Published: 2018
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26. Experimentally well-constrained masses of $^{27}$P and $^{27}$S: Implications for studies of explosive binary systems

Author: Sun, L. J., Xu, X. X., Hou, S. Q., Lin, C. J., José, J., Lee, J., He, J. J., Li, Z. H., Wang, J. S., Yuan, C. X., Herwig, F., Keegans, J., Budner, T., Wang, D. X., Wu, H. Y., Liang, P. F., Yang, Y. Y., Lam, Y. H., Ma, P., Duan, F. F., Gao, Z. H., Hu, Q., Bai, Z., Ma, J. B., Wang, J. G., Zhong, F. P., Wu, C. G., Luo, D. W., Jiang, Y., Liu, Y., Hou, D. S., Li, R., Ma, N. R., Ma, W. H., Shi, G. Z., Yu, G. M., Patel, D., Jin, S. Y., Wang, Y. F., Yu, Y. C., Zhou, Q. W., Wang, P., Hu, L. Y., Wang, X., Zang, H. L., Li, P. J., Zhao, Q. Q., Yang, L., Wen, P. W., Yang, F., Jia, H. M., Zhang, G. L., Pan, M., Wang, X. Y., Sun, H. H., Hu, Z. G., Chen, R. F., Liu, M. L., Yang, W. Q., Zhao, Y. M., and Zhang, H. Q.
Subjects: Nuclear Experiment
Abstract: The mass of $^{27}$P was predicted to impact the X-ray burst (XRB) model predictions of burst light curves and the composition of the burst ashes. To address the uncertainties and inconsistencies in the reported $^{27}$P masses in literature, a wealth of information has been extracted from the $\beta$-decay spectroscopy of the drip-line nucleus $^{27}$S. We determine the most precise mass excess of $^{27}$P to date to be $-659(9)$~keV, which is 63~keV (2.3$\sigma$) higher than the AME2016 recommended value of $-722(26)$~keV. The experimentally unknown mass excess of $^{27}$S was estimated to be 17030(400)~keV in AME2016, and we constrain this mass to be 17678(77)~keV based on the measured $\beta$-delayed two-proton energy. In the temperature region of $(0.06-0.3)$~GK, the $^{26}$Si$(p,\gamma)^{27}$P reaction rate determined in this work is significantly lower than the rate recommended in the reaction rate libraries, up to two orders of magnitude around 0.1~GK. The impact of these newly determined masses and well-constrained rate on the modeling of the explosive astrophysical scenarios has been explored by hydrodynamic nova and post-processing XRB models. No substantial change was found in the nova contribution to the synthesis of galactic $^{26}$Al or in the XRB energy generation rate, but we found that the calculated abundances of $^{26}$Al and $^{26}$Si at the last stage of XRB are increased by a factor of 2.4. We also conclude that $^{27}$S is not a significant waiting point in the rapid proton capture process.
Published: 2018
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27. A review of net zero energy buildings in hot and humid climates: Experience learned from 34 case study buildings

Author: Feng, W, Zhang, Q, Ji, H, Wang, R, Zhou, N, Ye, Q, Hao, B, Li, Y, Luo, D, and Lau, SSY
Subjects: Net zero energy buildings, Hot and humid climates, Renewable energy, Energy efficiency, Case study, Energy, Engineering
Abstract: Sustainable development in the building sector requires the integration of energy efficiency and renewable energy utilization in buildings. In recent years, the concept of net zero energy buildings (NZEBs) has become a potential plausible solution to improve efficiency and reduce energy consumption in buildings. To achieve an NZEB goal, building systems and design strategies must be integrated and optimized based on local climatic conditions. This paper provides a comprehensive review of NZEBs and their current development in hot and humid regions. Through investigating 34 NZEB cases around the world, this study summarized NZEB key design strategies, technology choices and energy performance. The study found that passive design and technologies such as daylighting and natural ventilation are often adopted for NZEBs in hot and humid climates, together with other energy efficient and renewable energy technologies. Most NZEB cases demonstrated site annual energy consumption intensity less than 100 kW-hours (kWh) per square meter of floor space, and some buildings even achieved “net-positive energy” (that is, they generate more energy locally than they consume). However, the analysis also shows that not all NZEBs are energy efficient buildings, and buildings with ample renewable energy adoption can still achieve NZEB status even with high energy use intensity. This paper provides in-depth case-study-driven analysis to evaluate NZEB energy performance and summarize best practices for high performance NZEBs. This review provides critical technical information as well as policy recommendations for net zero energy building development in hot and humid climates.
Published: 2019

28. Parametric Excitation of a Bose-Einstein Condensate: From Faraday Waves to Granulation

Author: Nguyen, J. H. V., Tsatsos, M. C., Luo, D., Lode, A. U. J., Telles, G. D., Bagnato, V. S., and Hulet, R. G.
Subjects: Condensed Matter - Quantum Gases
Abstract: We explore, both experimentally and theoretically, the response of an elongated Bose-Einstein condensate to modulated interactions. We identify two distinct regimes differing in modulation frequency and modulation strength. Longitudinal surface waves are generated either resonantly or parametrically for modulation frequencies near the radial trap frequency or twice the trap frequency, respectively. The dispersion of these waves, the latter being a Faraday wave, is well-reproduced by a mean-field theory that accounts for the 3D nature of the elongated condensate. In contrast, in the regime of lower modulation frequencies we find that no clear resonances occur, but with increased modulation strength, the condensate forms an irregular granulated distribution that is outside the scope of a mean-field approach. We find that the granulated condensate is characterized by large quantum fluctuations and correlations, which are well-described with single-shot simulations obtained from wavefunctions computed by a beyond mean-field theory at zero temperature, the multiconfigurational time-dependent Hartree for bosons method., Comment: To be published in PRX (2019)
Published: 2017
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29. Magnetic nanoparticle-based solid phase peptide synthesis and the synchronous detection of their biological activity

Author: Luo, D., Wang, P., Zheng, Q., Han, R., Shi, C., Wang, L., Hong, Y., Liu, Y., and Sha, Y.
Published: 2021
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30. Analysis of Risk Factors for Changes in the Renal Two-Dimensional Image in Gout Patients

Author: Dang W, Xu X, Luo D, Luo H, Hu J, Zhou J, Liu J, and You L
Subjects: gout, two-dimensional ultrasound, renal medulla, renal cortex, kidney stones, Medicine (General), R5-920
Abstract: Wantai Dang,1,&ast; Xiaohui Xu,2,&ast; Danling Luo,2 Hui Luo,2 Jin Hu,2 Jingguo Zhou,1 Jian Liu,2 Lanlan You2 1Department of Rheumatism and Immunity, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, 610500, People’s Republic of China; 2Department of Ultrasound, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, 610500, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Lanlan You Email 17027279@qq.comObjective: To explore the effects of different blood uric acid levels in gout patients on the two-dimensional image of the kidney and the risk factors for gout-related kidney damage for providing clinical evidence to enable early prevention and treatment of gout-related kidney damage.Methods: We obtained information of 227 patients with primary gout and estimated the association between two-dimensional kidney images and clinical indicators using binary logistic regression.Results: Our study showed that different uric acid levels, age, disease course, cystatin C (CysC) level, and γ-glutamyl transpeptidase level were correlated with echo of the renal medulla (P < 0.05). CysC level was correlated with the renal cortex thickness and kidney stones in different uric acid-level groups (P < 0.05). Disease course, aspartate transaminase (AST) level, creatinine (CREA) level, and tophi were risk factors for renal cortex thinning in gout patients (P = 0.045, 0.026, 0.004, 0.006, respectively). The disease course, platelet (PLT) count, and high-density lipoprotein (HDL-C) level were risk factors for kidney stone formation in gout patients (P = 0.037, 0.022, 0.023, respectively), while CysC level and C-reactive protein (CRP) level were risk factors for increased renal medulla echo in these patients (P = 0.022, 0.028, respectively).Conclusion: Our study revealed disease course, AST level, CREA level, tophi, PLT count, HDL-C level, CysC level and CRP level may be important predictors of renal image changes.Keywords: gout, two-dimensional ultrasound, renal medulla, renal cortex, kidney stones
Published: 2021

31. Construction of a Ferroptosis-Related Gene Signature for Predicting Survival and Immune Microenvironment in Melanoma Patients

Author: Zeng N, Ma L, Cheng Y, Xia Q, Li Y, Chen Y, Lu Z, Lu Q, Jiang F, and Luo D
Subjects: skin cutaneous melanoma, skcm, ferroptosis, immune microenvironment, immune checkpoint., Medicine (General), R5-920
Abstract: Ni Zeng,1,2 Liwen Ma,3 Yuxin Cheng,1 Qingyue Xia,1 Yueyue Li,1 Yihe Chen,1 Zhiyu Lu,1 Qian Lu,1 Feng Jiang,4 Dan Luo1 1Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People’s Republic of China; 2Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, People’s Republic of China; 3Department of Dermatology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210000, People’s Republic of China; 4Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, 200011, People’s Republic of ChinaCorrespondence: Dan LuoDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210000, People’s Republic of ChinaEmail daniluo2005@163.comFeng JiangDepartment of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, No. 419, Fangxie Road, Shanghai, 200011, People’s Republic of ChinaEmail dxyjiang@163.comObjective: In this research, we studied the genes associated with ferroptosis to develop a prognostic model and find out an association with tumor immune microenvironment in skin cutaneous melanoma (SKCM) patients.Methods: To find SKCM-related ferroptosis genes, we used Cox regression and LASSO approach on 60 genes related to ferroptosis and SKCM-related RNA-seq. Following that, a ferroptosis-related gene signature was created. Time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its capability of prediction. Besides, several assessments were used to evaluate overall survival (OS), accompanied by the creation of a nomogram for the clinicopathologic factors and the ferroptosis-related gene signature we established. We also investigated the relationship between ferroptosis-related gene signature with three immune checkpoints and immune cell infiltration.Results: Our prognostic model included two genes (ALOX5, CHAC1). In both TCGA and GEO cohorts, OS was lower in high-risk category. Using our gene signature, we can reliably predict OS. Additionally, our gene signature can predict immune cell infiltration and SKCM immunotherapy response.Conclusion: Our gene signature has shown to be a reliable predictor of OS, reflect the immune microenvironment, and predict the effectiveness of immunotherapy for SKCM patients.Keywords: skin cutaneous melanoma, SKCM, ferroptosis, immune microenvironment, immune checkpoint
Published: 2021

32. Explore the Value of Adding Induction Chemotherapy to Concurrent Chemoradiotherapy in T3-4N0M0 Nasopharyngeal Carcinoma Patients: A Retrospective Study

Author: Li P, Zhang Q, Luo D, Jiang F, Jin Q, Hua Y, Jin T, and Chen X
Subjects: nasopharyngeal carcinoma, chemotherapy, intensity-modulated radiation therapy., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Peijing Li,1,2,&ast; Qun Zhang,3,&ast; Donghua Luo,4– 6 Feng Jiang,1,2 Qifeng Jin,1,2 Yonghong Hua,1,2 Ting Jin,1,2 Xiaozhong Chen1,2 1Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310000, People’s Republic of China; 2Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, 310000, People’s Republic of China; 3Department of Radiation Oncology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510060, People’s Republic of China; 4Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China; 5State Key Laboratory of Oncology in South China, Guangzhou, 510060, People’s Republic of China; 6Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiaozhong Chen; Ting JinDepartment of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, 310022 Email chenxiaozhong2016@163.com; jinting22222@163.comPurpose: Patients with T3-4N0M0 nasopharyngeal carcinoma (NPC) are a unique subgroup of locoregional advanced NPC, which generally have a better prognosis than others and are often excluded in most randomized controlled clinical trials focusing on locoregional advanced NPC. The management of this population is still controversial. This study aims to evaluate the outcomes of T3-4N0M0 NPC patients treated with sequential induction chemotherapy and concurrent chemoradiotherapy (IC+CCRT) or chemoradiotherapy (CCRT) alone.Patients and Methods: We included 362 patients diagnosed with T3-4N0M0 NPC from two hospitals between December 2005 and December 2014. All patients were received IC + CCRT (n=146) or CCRT (n=216). Locoregional failure-free survival (LRFFS), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were retrospectively estimated.Results: The median follow-up was 95 (range: 11– 168) months. Univariable analyses have shown that 5-year LRFFS, DFS and OS in the IC+CCRT group and the CCRT group were 87.4% vs 93.4% (P = 0.035), 80.4% vs 87.0% (P = 0.047) and 86.3% vs 93.0% (P = 0.040). Multivariate analyses demonstrated that only the T stage was the independent prognostic factor for LRFFS, DFS, and OS in the entire group analysis. Subgroup analysis revealed that patients with T3 tumors who received IC+CCRT had significantly lower LRFFS, DFS, and OS than those treated with CCRT. For T4 patients, the outcomes had no significant difference between the two groups.Conclusion: This retrospective study showed that T3N0M0 patients who received CCRT had better prognosis than those treated with IC+CCRT. In terms of T4N0M0 disease, treatment outcomes are similar in both treatment groups. However, these results require further confirmation of large sample size, prospectively, randomized controlled trials.Keywords: nasopharyngeal carcinoma, chemotherapy, intensity-modulated radiation therapy
Published: 2021

33. Curvature of the spectral energy distribution, the dominant process for inverse Compton component and other jet properties in Fermi 2LAC blazars

Author: Xue, R., Luo, D., Du, L. M., Wang, Z. R., Xie, Z. H., Yi, T. F., Xiong, D. R., Xu, Y. B., Liu, W. G., and Yu, X. L.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We fit the spectral energy distributions (SEDs) of members of a large sample of Fermi 2LAC blazars to synchrotron and inverse Compton (IC) models. Our main results are as follows. (i) As suggested by previous works, the correlation between peak frequency and curvature can be explained by statistical or stochastic particle acceleration mechanisms. For BL Lacs, we find a linear correlation between synchrotron peak frequency and its curvature. The slope of the correlation is consistent with the stochastic acceleration mechanisms and confirm previous studies. For FSRQs, we also find a linear correlation, but its slope cannot be explained by previous theoretical models. (ii) We find a significant correlation between IC luminosity and synchrotron luminosity. The slope of the correlation of FSRQs is consistent with the EC process. And the slope of the correlation of BL Lac is consistent with the SSC process. (iii) We find several significant correlations between IC curvature and several basic parameters of blazars (black hole mass, broad line luminosity, the Lorentz factor of jet). We also find significant correlations between bolometric luminosity and these basic parameters of blazars which suggest that the origin of jet is a mixture of the mechanisms proposed by Blandford $\&$ Znajek and by Blandford $\&$ Payne., Comment: 17 pages, 9 figures, 5 tables. Accepted for publication in the Monthly Notices of the Royal Astronomical Society
Published: 2016
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34. Current Advances of Nanocarrier Technology-Based Active Cosmetic Ingredients for Beauty Applications

Author: Zhou H, Luo D, Chen D, Tan X, Bai X, Liu Z, Yang X, and Liu W
Subjects: nanocarrier technology, functional cosmetics, active cosmetic ingredients, skin penetration and positioning, efficacy evaluation, codelivery nanocarriers, Dermatology, RL1-803
Abstract: Hong Zhou,1 Dan Luo,2 Dan Chen,2 Xi Tan,1 Xichen Bai,1 Zhi Liu,1 Xiangliang Yang,1,2 Wei Liu1,2 1College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, People’s Republic of China; 2National Engineering Research Center for Nanomedicine, Huazhong University of Science and Technology, Wuhan, 430075, Hubei, People’s Republic of ChinaCorrespondence: Wei LiuCollege of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430075, Hubei, People’s Republic of ChinaTel/Fax +86 27 8779 2147Email wliu@hust.edu.cnAbstract: Nanocarrier technology has been effectively applied to the development of drug delivery systems to overcome the limitations of traditional preparation. Its application has been extended to various pharmaceutical fields from injection preparation to oral preparation and external preparation, and now it has appeared in the field of cosmetics for beauty applications. The widespread influence of nanocarrier in the cosmetics industry is due to the fact that nanocarrier can effectively promote the percutaneous penetration and significantly increase skin retention of active components in functional cosmetics. Meanwhile, nanocarrier can effectively improve the water dispersion of insoluble active cosmetic ingredients, enhance the stability of efficacy components and achieve the codelivery of diverse cosmetics active ingredients. In this review, we summarized the current progress of nanocarrier technology in the functional cosmetics, including the types and the routes of dermal/transdermal drug delivery nanocarriers used in the functional cosmetics, the mechanism of nanocarriers promoting the percutaneous penetration of active cosmetic ingredients, the application and efficacy evaluation of different active cosmetic ingredients in nanocarriers and discussing the potential risks to human. This will provide a useful reference for the further development of nanocarriers in the field of functional cosmetics.Keywords: nanocarrier technology, functional cosmetics, active cosmetic ingredients, skin penetration and positioning, efficacy evaluation, codelivery nanocarriers
Published: 2021

35. Prevalence of Human Papillomavirus and Genotype Distribution in Pregnant and Non-Pregnant Women in China

Author: Luo D, Peng M, Wei X, Pan D, Xue H, Xu Y, and Dong B
Subjects: human papillomavirus, genotype, squamous intraepithelial lesions, cervical cytology, china, pregnant, Public aspects of medicine, RA1-1270
Abstract: Dandan Luo,1 Meilian Peng,2 Xizhen Wei,1 Diling Pan,3 Huifeng Xue,4 Yuying Xu,1 Binhua Dong2 1Department of Obstetrics, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China; 2Department of Gynecology, Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China; 3Department of Pathology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China; 4Fujian Provincial Cervical Disease Diagnosis and Treatment Health Center, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of ChinaCorrespondence: Binhua DongDepartment of Gynecology, Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, 18 Daoshan Road, Fuzhou, Fujian, People’s Republic of ChinaTel +86-591-87558732Fax +86-591- 87551247Email dbh18-jy@126.comYuying XuDepartment of Obstetrics, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, 18 Daoshan Road, Fuzhou, Fujian, People’s Republic of ChinaTel +86-591-87279515Fax +86-591-87551247Email yyxu703@163.comPurpose: The status of human papillomavirus (HPV) infection in pregnant and non-pregnant women in China remains unclear. This study aimed to compare the prevalence and genotype distributions of HPV between pregnant and non-pregnant women in China.Patients and Methods: A case-control study was conducted of pregnant women during the second trimester and age-matched non-pregnant women attending the Fujian Maternity and Child Health Hospital between January 1, 2017 and December 31, 2018. Participants underwent cervical cytology testing and HPV genotyping. The genotyping test was able to identify 14 high-risk HPV (HR-HPV), four possible HR-HPV, and five low-risk HPV (LR-HPV) types. Further colposcopy and a cervical biopsy were performed if indicated. The primary outcomes were HPV prevalence and genotype distribution.Results: In total, 1077 pregnant and 1077 non-pregnant women were enrolled. Compared with non-pregnant women, pregnant women had a higher prevalence of HPV (24.2% vs 14.8%), HR-HPV (20.2% vs 11.7%), and LR-HPV (8% vs 4.5%) infection. In pregnant women, the most prevalent HPV genotypes were HPV-52 (6.0%), -16 (3.5%), -58 (2.6%), -53 (2.5%), and -51 (2.5%), while in non-pregnant women the most prevalent genotypes were HPV-52 (3.6%), -81 (1.9%), -51 (1.8%), -68 (1.4%), and -16 (1.3%). In women aged ≥ 35 years, HR-HPV (P=0.002) and LR-HPV (P=0.001) prevalence were significantly higher in pregnant women. However, in women aged < 35 years, only HR-HPV prevalence was higher in pregnant women. Pregnant and non-pregnant women with HPV-16 and HPV-58 infection had a high prevalence of high-grade squamous intra-epithelial lesions (HSIL) (HPV-16: P< 0.001 and P=0.005, HPV-58: P=0.043 and P=0.005); but with other HR-HPV genotypes, only non-pregnant women had an increased HSIL prevalence.Conclusion: In China, the HPV prevalence is higher in pregnant women than that in non-pregnant women and is also age- and genotype-dependent. HPV-infected pregnant women aged ≥ 35 years and those with HPV-16 should be closely monitored to enable rapid clinical intervention.Keywords: human papillomavirus, genotype, squamous intraepithelial lesions, cervical cytology, China, pregnant
Published: 2021

36. Real-time monitoring for the next core-collapse supernova in JUNO

Author: Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de André, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Morton-Blake, I, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chatrabhuti, A, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chin, Y, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Corso, F, Dalager, O, Datta, J, Taille, C, Deng, Z, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Göttel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jafar, A, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Labit, L, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lu, X, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhöfer, D, Miramonti, L, Mohan, N, Montuschi, M, Müller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Qu, M, Qu, Z, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rientong, K, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sangka, A, Sava, G, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Šimkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Šrámek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Venettacci, C, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, F, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, X, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, F, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, L, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Züfle, J, Null, N, Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Morton-Blake, Iwan, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Lorenzo, Selma Conforti Di, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, Taille, Christophe De La, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, 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Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, ZHANG, Lei, Zhang, Mohan, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, 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Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Lorenzo, Selma Conforti Di, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, Taille, Christophe De La, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, ZHANG, Lei, Zhang, Mohan, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, Züfle, Jan, and null, null
Abstract: The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector currently under construction in South China. The real-time monitoring system is designed to ensure both prompt alert speed and comprehensive coverage of progenitor stars. It incorporates prompt monitors on the electronic board as well as online monitors at the data acquisition stage. Assuming a false alert rate of 1 per year, this monitoring system exhibits sensitivity to pre-SN neutrinos up to a distance of approximately 1.6 (0.9) kiloparsecs and SN neutrinos up to about 370 (360) kiloparsecs for a progenitor mass of 30 solar masses, considering both normal and inverted mass ordering scenarios. The pointing ability of the CCSN is evaluated by analyzing the accumulated event anisotropy of inverse beta decay interactions from pre-SN or SN neutrinos. This, along with the early alert, can play a crucial role in facilitating follow-up multi-messenger observations of the next galactic or nearby extragalactic CCSN.
Published: 2024

37. A self-powered smart wave energy converter for sustainable sea

Author: Li, Hailong, Wu, J., Shi, Xiaodan, Kong, L., Kong, W., Zhang, Z., Pan, Y., Luo, D., Yan, Jinyue, Li, Hailong, Wu, J., Shi, Xiaodan, Kong, L., Kong, W., Zhang, Z., Pan, Y., Luo, D., and Yan, Jinyue
Abstract: Self-powered smart buoys are widely used in sustainable sea, such as marine environmental monitoring. The article designs a self-powered and self-sensing point-absorber wave energy converter based on the two-arm mechanism. The system consists of the wave energy capture module, the power take-off module, the generator module and the energy storage module. As the core component of the wave energy converter, the power take-off module is mainly composed of a two-arm mechanism, which can convert the oscillation heave motion into unidirectional rotary motion. To evaluate the power generation performance of the system, the kinematic and dynamic models of the wave energy converter with the flywheel are established, and the disengagement and engagement phenomena of the flywheel are analyzed. The effectiveness of the prototype in capturing wave energy is verified through dry experiments in lab and field tests. The dry experiment reveals that the maximum output power of the system is 5.67 W, and the maximum and average mechanical efficiency are 66.63 % and 48.35 %, respectively. Additionally, the field test demonstrates that the peak output power can reach 92 W. Meanwhile, the generated electrical signals can be processed by deep learning algorithms to accurately identify different wave states. This high performance confirms that the proposed wave energy converter can meet its own energy needs by capturing wave energy in the marine environment, while also achieving self-sensing for wave condition monitoring. The system has great potential for promoting the development of intelligent sustainable sea in the future.
Published: 2024
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38. Flexible sensors for food monitoring. Part I: Principle

Author: Luo, D., primary, Nikitina, M. A., additional, and Xiao, X., additional
Published: 2024
Full Text: View/download PDF

39. Initiation And Persistence With Antiplatelet Agents Among The Patients With Acute Coronary Syndromes: A Retrospective, Observational Database Study In China

Author: Liu X, He X, Wu J, and Luo D
Subjects: acute coronary syndromes, antiplatelet agents, initiation, persistence, china, Medicine (General), R5-920
Abstract: Xin Liu,1 Xiaoning He,1 Jing Wu,1 Da Luo1,2 1School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, People’s Republic of China; 2Tianjin Health Development Research Center, Tianjin, People’s Republic of ChinaCorrespondence: Jing WuSchool of Pharmaceutical Science and Technology, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, People’s Republic of ChinaTel +862227405176Fax +862287401830Email jingwu@tju.edu.cnDa LuoSchool of Pharmaceutical Science and Technology, Tianjin University, Tianjin, People’s Republic of ChinaEmail vividvigorous@163.comObjectives: To investigate the initiation and persistence of antiplatelet agents and the associated factors for patients with acute coronary syndromes (ACS) in Tianjin, China.Methods: Data were obtained from Tianjin Urban Employee Basic Medical Insurance database (2011–2015). Adult patients who were discharged alive after the first ACS-related hospitalization (index hospitalization) between January 2012 and December 2014 were included. Patients who initiated with antiplatelet therapy, including aspirin monotherapy, clopidogrel monotherapy, or dual antiplatelet with aspirin and clopidogrel at discharge or within the initial 30-day follow-up after discharge were further identified. Patients with no gaps of ≥30 days in antiplatelet therapy were deemed persistent. The logistic model and Cox model were used to explore the associated factors of initiation and persistence with antiplatelet agents, respectively.Results: In total, 21,450 patients (64.6±10.7 years; 46.0% female) were included. Only 70.3% (N=15,071) of them initiated with antiplatelet agents within the initial 30-day follow-up; 85.0% (N=12,809) of the initial users discontinued their antiplatelet therapy, and the average time to discontinuation was 117.4±119.7 days. The patients who had prior antiplatelet agents utilization (Odds ratio [95% CI]=1.93 [1.78–2.09]; hazard ratio [95% CI]=0.78 [0.74–0.81]), received percutaneous coronary intervention (PCI) during the baseline period (OR=1.47 [1.26–1.73]; HR=0.91 [0.84–0.97]) or index hospitalization (OR=22.40 [18.63–26.92]; HR=0.51 [0.49–0.53]) were more likely to initiate and persist with antiplatelet agents, while the female (OR=0.75 [0.70–0.81]; HR=1.22 [1.88–1.27]) patients were less likely to initiate and persist with antiplatelet agents.Conclusion: The initiation and persistence with antiplatelet agents are poor among the ACS patients in Tianjin. Females are associated with poorer initiation and persistence, while prior antiplatelet agents use and receiving PCI during baseline period or index hospitalization are associated with better initial use and better persistence.Keywords: acute coronary syndromes, antiplatelet agents, initiation, persistence, China
Published: 2019

40. Explore the Value of Adding Induction Chemotherapy to Concurrent Chemoradiotherapy in T3-4N0M0 Nasopharyngeal Carcinoma Patients: A Retrospective Study [Corrigendum]

Author: Li P, Zhang Q, Luo D, Jiang F, Jin Q, Hua Y, Jin T, and Chen X
Subjects: nasopharyngeal carcinoma, chemotherapy, intensity-modulated radiation therapy., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Li P, Zhang Q, Luo D, et al. Cancer Manag Res. 2021;13:7067–7076. The authors have advised the affiliation list on page 7067 is incorrect. The correct author list and affiliations are as follows. Peijing Li1,2,*Qun Zhang3,*Donghua Luo4–6Feng Jiang2Qifeng Jin2Yonghong Hua2Ting Jin2Xiaozhong Chen2 1Department of Radiotherapy and Oncology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, People’s Republic of China; 2Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital) and Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, 310000, People’s Republic of China; 3Department of Radiation Oncology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510060, People’s Republic of China; 4Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China; 5State Key Laboratory of Oncology in South China, Guangzhou, 510060, People’s Republic of China; 6Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, People’s Republic of China Read the original article
Published: 2022

41. JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo

Author: Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Bergnoli, A, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callegari, R, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chan, C, Chang, J, Chang, Y, Chen, G, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Di Lorenzo, S, Corti, D, Corso, F, Dalager, O, De La Taille, C, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dusini, S, Dvorak, M, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, D, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Ford, R, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Joutsenvaara, J, Kalousis, L, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Pelliccia, N, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Raper, N, Rasheed, R, Re, A, Rebber, H, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sanfilippo, S, Sangka, A, Sawangwit, U, Sawatzki, J, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settanta, G, Settimo, M, Shao, Z, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Sirignano, C, Siripak, J, Sisti, M, Slupecki, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Stefanik, D, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Treskov, K, Triossi, A, Troni, G, Trzaska, W, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, Volpe, C, Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Weng, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wong, S, Wonsak, B, Wu, D, Wu, Q, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, W, Yan, X, Yan, Y, Yang, C, Yang, H, Yang, J, Yang, L, Yang, X, Yang, Y, Yeng, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, G, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, F, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Bergnoli A., Birkenfeld T., Blin S., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callegari R., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Chan C., Chang J., Chang Y., Chen G., Chen P., Chen P. -A., Chen S., Chen X., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Di Lorenzo S. C., Corti D., Corso F. D., Dalager O., De La Taille C., Deng Z., Depnering W., Diaz M., Ding X., Ding Y., Dirgantara B., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dusini S., Dvorak M., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan D., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Ford R., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo J., Guo W., Guo X., Guo Y., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Joutsenvaara J., Kalousis L., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kutovskiy N., Kuusiniemi P., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Lippi I., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. 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Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, 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C. -F., Wonsak B., Wu D., Wu Q., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan W., Yan X., Yan Y., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yeng Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang G., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., and Zwickel S.
Abstract: We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande.
Published: 2023

42. JUNO sensitivity to 7Be, pep, and CNO solar neutrinos

Author: Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Di Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Dal Corso, F, Dalager, O, Datta, J, De La Taille, C, Deng, Z, Depnering, W, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhofer, D, Miramonti, L, Mohan, N, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sanfilippo, S, Sangka, A, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zufle, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Beretta M., Bergnoli A., Bick D., Bieger L., Biktemerova S., Birkenfeld T., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callier S., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Cerrone V., Chan C., Chang J., Chang Y., Chen C., Chen G., Chen P., Chen S., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chepurnov A., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Molla M. C., Di Lorenzo S. C., Coppi A., Corti D., Csakli S., Dal Corso F., Dalager O., Datta J., De La Taille C., Deng Z., Depnering W., Ding X., Ding Y., Dirgantara B., Dittrich C., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dugas K., Dusini S., Duyang H., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo W., Guo X., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang J., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Imbert L., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang C., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khan A., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kuleshov S., Kutovskiy N., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li J., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Ling X., Lippi I., Liu C., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Liu Z., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo J., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martini A., Mayer M., Mayilyan D., Mednieks I., Meng Y., Meraviglia A., Meregaglia A., Meroni E., Meyhofer D., Miramonti L., Mohan N., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Nikolaev A., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qi X., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Rasheed R., Re A., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sandanayake D., Sanfilippo S., Sangka A., Sawangwit U., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settimo M., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Singhal A., Sirignano C., Siripak J., Sisti M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Takenaka A., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Tortorici F., Treskov K., Triossi A., Triozzi R., Trzaska W., Tung Y. -C., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., von Sturm K., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wirth R., Wonsak B., Wu D., Wu Q., Wu Y., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan X., Yan Y., Yang C., Yang J., Yang L., Yang X., Yang Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu G., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zufle J., Zwickel S., Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Di Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Dal Corso, F, Dalager, O, Datta, J, De La Taille, C, Deng, Z, Depnering, W, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhofer, D, Miramonti, L, Mohan, N, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sanfilippo, S, Sangka, A, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zufle, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Beretta M., Bergnoli A., Bick D., Bieger L., Biktemerova S., Birkenfeld T., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callier S., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Cerrone V., Chan C., Chang J., Chang Y., Chen C., Chen G., Chen P., Chen S., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chepurnov A., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Molla M. C., Di Lorenzo S. C., Coppi A., Corti D., Csakli S., Dal Corso F., Dalager O., Datta J., De La Taille C., Deng Z., Depnering W., Ding X., Ding Y., Dirgantara B., Dittrich C., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dugas K., Dusini S., Duyang H., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo W., Guo X., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang J., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Imbert L., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang C., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khan A., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kuleshov S., Kutovskiy N., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li J., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Ling X., Lippi I., Liu C., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Liu Z., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo J., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martini A., Mayer M., Mayilyan D., Mednieks I., Meng Y., Meraviglia A., Meregaglia A., Meroni E., Meyhofer D., Miramonti L., Mohan N., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Nikolaev A., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qi X., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Rasheed R., Re A., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sandanayake D., Sanfilippo S., Sangka A., Sawangwit U., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settimo M., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Singhal A., Sirignano C., Siripak J., Sisti M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Takenaka A., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Tortorici F., Treskov K., Triossi A., Triozzi R., Trzaska W., Tung Y. -C., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., von Sturm K., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wirth R., Wonsak B., Wu D., Wu Q., Wu Y., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan X., Yan Y., Yang C., Yang J., Yang L., Yang X., Yang Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu G., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zufle J., and Zwickel S.
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), the first multi-kton liquid scintillator detector, which is under construction in China, will have a unique potential to perform a real-time measurement of solar neutrinos well below the few MeV threshold typical of Water Cherenkov detectors. JUNO’s large target mass and excellent energy resolution are prerequisites for reaching unprecedented levels of precision. In this paper, we provide estimation of the JUNO sensitivity to 7Be, pep, and CNO solar neutrinos that can be obtained via a spectral analysis above the 0.45 MeV threshold. This study is performed assuming different scenarios of the liquid scintillator radiopurity, ranging from the most optimistic one corresponding to the radiopurity levels obtained by the Borexino experiment, up to the minimum requirements needed to perform the neutrino mass ordering determination with reactor antineutrinos — the main goal of JUNO. Our study shows that in most scenarios, JUNO will be able to improve the current best measurements on 7Be, pep, and CNO solar neutrino fluxes. We also perform a study on the JUNO capability to detect periodical time variations in the solar neutrino flux, such as the day-night modulation induced by neutrino flavor regeneration in Earth, and the modulations induced by temperature changes driven by helioseismic waves.
Published: 2023

43. AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

Author: Karlinsky, L, Michaeli, T, Nishino, K, Yang, R, Timofte, R, Li, X, Zhang, Q, Zhang, L, Liu, F, He, D, Li, F, Zheng, H, Yuan, W, Ostyakov, P, Vyal, D, Zhussip, M, Zou, X, Yan, Y, Li, L, Tang, J, Chen, M, Zhao, S, Zhu, Y, Qin, X, Li, C, Leng, C, Cheng, J, Rota, C, Buzzelli, M, Bianco, S, Schettini, R, Zhang, D, Huang, F, Liu, S, Wang, X, Jin, Z, Li, B, Li, M, Liu, D, Zou, W, Dong, P, Ye, T, Zhang, Y, Tan, M, Niu, X, Ayazoglu, M, Conde, M, Choi, U, Jia, Z, Xu, T, Ye, M, Luo, D, Pan, X, Peng, L, Yang R., Timofte R., Li X., Zhang Q., Zhang L., Liu F., He D., Li F., Zheng H., Yuan W., Ostyakov P., Vyal D., Zhussip M., Zou X., Yan Y., Li L., Tang J., Chen M., Zhao S., Zhu Y., Qin X., Li C., Leng C., Cheng J., Rota C., Buzzelli M., Bianco S., Schettini R., Zhang D., Huang F., Liu S., Wang X., Jin Z., Li B., Li M., Liu D., Zou W., Dong P., Ye T., Zhang Y., Tan M., Niu X., Ayazoglu M., Conde M., Choi U. J., Jia Z., Xu T., Ye M., Luo D., Pan X., Peng L., Karlinsky, L, Michaeli, T, Nishino, K, Yang, R, Timofte, R, Li, X, Zhang, Q, Zhang, L, Liu, F, He, D, Li, F, Zheng, H, Yuan, W, Ostyakov, P, Vyal, D, Zhussip, M, Zou, X, Yan, Y, Li, L, Tang, J, Chen, M, Zhao, S, Zhu, Y, Qin, X, Li, C, Leng, C, Cheng, J, Rota, C, Buzzelli, M, Bianco, S, Schettini, R, Zhang, D, Huang, F, Liu, S, Wang, X, Jin, Z, Li, B, Li, M, Liu, D, Zou, W, Dong, P, Ye, T, Zhang, Y, Tan, M, Niu, X, Ayazoglu, M, Conde, M, Choi, U, Jia, Z, Xu, T, Ye, M, Luo, D, Pan, X, Peng, L, Yang R., Timofte R., Li X., Zhang Q., Zhang L., Liu F., He D., Li F., Zheng H., Yuan W., Ostyakov P., Vyal D., Zhussip M., Zou X., Yan Y., Li L., Tang J., Chen M., Zhao S., Zhu Y., Qin X., Li C., Leng C., Cheng J., Rota C., Buzzelli M., Bianco S., Schettini R., Zhang D., Huang F., Liu S., Wang X., Jin Z., Li B., Li M., Liu D., Zou W., Dong P., Ye T., Zhang Y., Tan M., Niu X., Ayazoglu M., Conde M., Choi U. J., Jia Z., Xu T., Ye M., Luo D., Pan X., and Peng L.
Abstract: This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track 2 targets the super-resolution of compressed video. In Track 1, we use the popular dataset DIV2K as the training, validation and test sets. In Track 2, we propose the LDV 3.0 dataset, which contains 365 videos, including the LDV 2.0 dataset (335 videos) and 30 additional videos. In this challenge, there are 12 teams and 2 teams that submitted the final results to Track 1 and Track 2, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution on compressed image and video. The proposed LDV 3.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge is at https://github.com/RenYang-home/AIM22_CompressSR.
Published: 2023

44. Cohort study to evaluate efficacy, safety and acceptability of a two-rod contraceptive implant during third, fourth and fifth year of product use in China

Author: Che, Y, Taylor, D, Luo, D, Maldonado, LY, Wang, M, Wevill, S, Vahdat, H, Han, X, Halpern, V, Dorflinger, L, and Steiner, MJ
Published: 2019
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45. A liquid helium target system for a measurement of parity violation in neutron spin rotation

Author: Bass, C. D., Bass, T. D., Heckel, B. R., Huffer, C. R., Luo, D., Markoff, D. M., Micherdzinska, A. M., Snow, W. M., Swanson, H. E., and Walbridge, S. C.
Subjects: Nuclear Experiment
Abstract: A liquid helium target system was designed and built to perform a precision measurement of the parity-violating neutron spin rotation in helium due to the nucleon-nucleon weak interaction. The measurement employed a beam of low energy neutrons that passed through a crossed neutron polarizer--analyzer pair with the liquid helium target system located between them. Changes between the target states generated differences in the beam transmission through the polarizer--analyzer pair. The amount of parity-violating spin rotation was determined from the measured beam transmission asymmetries. The expected parity-violating spin rotation of order $10^{-6}$ rad placed severe constraints on the target design. In particular, isolation of the parity-odd component of the spin rotation from a much larger background rotation caused by magnetic fields required that a nonmagnetic cryostat and target system be supported inside the magnetic shielding, while allowing nonmagnetic motion of liquid helium between separated target chambers. This paper provides a detailed description of the design, function, and performance of the liquid helium target system., Comment: V2: 29 pages, 14 figues, submitted to Nucl. Instrum. Meth. B. Revised to address reviewer comments
Published: 2009
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46. HYDROXYAPATITE/HYALURONIC ACID COMPOSITE HYDROGEL AS AN INJECTABLE BULKING AGENT TO TREAT STRESS URINARY INCONTINENCE

Author: Liu, M, primary, Peng, L, additional, Xiao, Y, additional, and Luo, D, additional
Published: 2023
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47. SINGLE-CELL TRANSCRIPTOMICS REVEAL THE REMODELING LANDSCAPE AND DYSFUNCTION OF FIBROBLASTS AND MACROPHAGES IN OBSTRUCTION-INDUCED DETRUSOR UNDERACTIVITY

Author: Chen, J, primary, Peng, L, additional, Shen, H, additional, and Luo, D, additional
Published: 2023
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48. THE EFFICACY AND SAFETY OF ORAL MEDICATIONS, ONABOTULINUMTOXINA (THREE DOSES) AND TRANSCUTANEOUS TIBIAL NERVE STIMULATION (TTNS) AS NON OR MINIMALLY INVASIVE TREATMENT FOR THE MANAGEMENT OF NEUROGENIC DETRUSOR OVERACTIVITY (NDO) IN ADULTS: A SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS

Author: Chen, Y, primary, Peng, L, additional, Luo, D, additional, and Shen, H, additional
Published: 2023
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49. LARGE SCALE SOCIAL MEDIA ANALYTICS ON URINARY INCONTINENCE: INSIGHTS FROM CHINESE ONLINE USER GENERATED CONTENTS

Author: Fan, Y, primary, Huang, W, additional, Dong, Q, additional, and Luo, D, additional
Published: 2023
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50. OUTCOMES OF SIMULTANEOUS MODIFIED POSTERIOR COLPORRHAPHY AFTER MID-URETHRAL SLING ON THE SEXUAL FUNCTION OF PATIENTS WITH STRESS URINARY INCONTINENCE AND VAGINAL RELAXATION

Author: Shen, S, primary, Chen, J, additional, Liu, M, additional, Peng, L, additional, Luo, D, additional, and Shen, H, additional
Published: 2023
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