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Prior studies suggested that patients with autoimmune liver diseases (AiLDs) had an increased risk of cancer, whereas the causal effect remained unclear.Meta-analyses concerning the relationship between AiLD and cancer risk were performed to calculate the pooled relative risk (RR) and corresponding 95% confidence intervals (CIs). Then, the associations with a p value of.05 were further validated by two-sample Mendelian randomization studies.A total of 37 cohort studies covering more than 34 558 patients were included, and we observed an increased risk of overall cancers (pooled RR = 3.64, 95% CI: 2.64-5.03, p .001) and cancer-related death (pooled RR = 2.48, 95% CI: 1.73-3.53, p .001) for patients with AiLD. Besides, overall and several site-specific cancers risk were found in patients with primary biliary cholangitis (PBC), autoimmune hepatitis (AIH), and primary sclerosing cholangitis (PSC) (p .05). However, associations between genetically predisposed AIH, PBC, and PSC and the risk of specific cancers did not reach a significant level, except for PBC and gastric cancer (OR = 0.96, 95% CI: 0.93-0.99; p = .02).In addition to hepatobiliary cancer, results from the meta-analyses suggest that patients with AiLD might have an increased risk of several extrahepatobiliary cancers. However, the causal role of AiLD in cancer development needs to be further investigated.

Programming by Demonstration(PBD) applies in the industry as a method of human-robot collaboration for assembly, such as placing, inserting, and screwing; however, PBD has not received much attention in commercial electronic product assembly. There is little work on integrating a strategy to optimize trajectory planning, which is an initial step of PBD. Most recent related works improving PBD performance focus on taking care of numerous demonstration samples from motion-sensing devices under time consumption, distance, and other related criteria. However, it is necessary to integrate a strategy to optimize the performance of precise assembly tasks. We proposed a framework with two custom algorithms to pre-process and classify contactless demonstration performance in this research work. It verified that these algorithms could more effectively generate optimal motion paths in criteria of distance, smoothness, and trajectory variance than canonical methods. Machine learning methods, including the Convolutional neural network(CNN), Artificial Neural Network(ANN), and Support Vector Machine(SVM), are feasible to predict the further performance that the best motion path with accuracy ranging from 80% to 85% accuracy. Also, CNN performs better than ANN and SVM. Among CNN methods, the DarkNet yields the highest accuracy rate of 85%. Future work includes the hybrid CNN/ANN algorithm, which may yield higher accuracy in prediction. Also, the proposed algorithms may apply to robots with dual assembly arms which mimic human arms.

This study aimed to evaluate the effectiveness of vitrectomy without using perfluorocarbon liquid (PFCL) for the treatment of complicated retinal detachment (RD).The utilisation of PFCL was calculated in four hospitals in 2020 and in one hospital every year from 2012 to 2020. A case series of 320 RD eyes treated with vitrectomy without the use of perfluorocarbon liquid (VWTPL) was followed up for 1-26 months. The rate of retinal reattachment (RR) and postoperative visual acuity (VA, LogMAR) was evaluated. Furthermore, factors influencing RR and VA were analysed.The overall utilisation of PFCL was 43.87% (42.74%, 45.83%, 62.39% and 4.5%). The annual utilisation was 46.94%, 20.43%, 46.73%, 47.41%, 20%, 17.24%, 7.60%, 10.67% and 4.49% from 2012 to 2020. The VA of 320 eyes improved from 1.96 ± 1.07 preoperatively to 1.43 ± 0.92 (LogMAR, p 0.001) 1 week post-operation. In the follow-up of 1-26 months (median: 9 months), the primary and final RR was 87.37% and 95.56%, respectively. Age, uveitis, recurrent RD, the number of detached retinal quadrants, aPVR and preoperative VA were considered as the factors influencing postoperative VA. Moreover, preoperative VA and preoperative intraocular pressure were the factors influencing RR.The utilisation of PFCL varies amongst hospitals with a highest percentage of 62.39%. VWTPL is safe and effective, thereby saving costs and preventing complications related to PFCL.ChiCTR-ORC-17014225.

The pollution and damage caused by antibiotics in water have aroused serious concern. Metal–organic frameworks (MOF), which have been hotly investigated as a novel kind of sensing materials, have been tentatively applied to the detection of antibiotics in recent years. In this work, four new Zn(II)/Cd(II) coordination polymers, [Cd(opda)(mbib)(H2O)] (1), [Cd(opda)(pbib)(H2O)] (2), [Cd(ppda)(mbib)] (3), and [Zn2(mpda)2(mbib)2]·2H2O (4), (H2opda = 1,2-phenylenediacetic acid, H2mpda = 1,3-phenylenediacetic acid, H2ppda = 1,4-phenylenediacetic acid, mbib = 1,3-bis(imidazolyl)benzene, pbib = 1,4-bis(imidazolyl)benzene), have been synthesized using bis(imidazole) and phenylenediacetate isomers under hydrothermal conditions. The flexible pda and bib ligands in 1–3 afford 2D (4,4)-connected layers, which are further stacked in an offset fashion with an ABAB sequence to propagate into a 3D supramolecular architecture through strong C–H⋯π and C–H⋯O interactions. In contrast, the flexible cis-conformation mpda and mbib ligands in 4 can be seen as “V”-type building blocks, linking Zn(II) atoms to form a 1D loop chain. The structural diversity of these complexes is mainly attributed to the different coordination modes and isomer conformations of the flexible phenylenediacetic acid and bis(imidazole) ligands. The application of the fluorescence properties of the four complexes for detecting the antibiotics cefixime (CEF) and tetracycline (TEC) and the related mechanisms have been researched. Complexes 1–4 exhibit high quenching percentages in low-concentration aqueous solutions, with values of 94.9%, 97.8%, 95.5%, and 97.2% (toward CEF) and 97.7%, 96.7%, 96.4%, and 97.4% (toward TEC), respectively. Compared with 1–3, complex 4 has a higher quenching percentage, which may be because 4 is a 3D porous supramolecular network. The detection limits of complexes 1–4 have been measured to be 0.278 μM, 0.379 μM, 0.52 μM, and 0.171 μM (for CEF) and 0.384 μM, 0.189 μM, 0.421 μM, and 0.137 μM (for TEC), which surpass/approach those of most of the reported MOF-based fluorescent sensing materials. Systematic analysis of the sensing mechanism reveals that photoinduced electron transfer and the inner filter effect contribute to the realization of the sensing process.

Purpose This paper studies the characteristics of the seedling regeneration, stand structures, undergrowth biomasses, litter amounts and soil water contents of planted forests of Pinus tabuliformis in the Liaoheyuan Nature Reserve after a fire disturbance in 2014 and analyzes the significant factors affecting seedling regeneration to offer a scientific basis for the ecological restoration of vegetation in burned areas. Methods Plots of forest stands that experienced different fire severities (high severity, moderate severity, low severity) and control sample plots were used to study the significance of differences in seedling regeneration, stand structure, undergrowth biomass, litter amount and soil water content characteristics among stands under the effects of different fire severities by using single element variance analysis. The major factors affecting seedling regeneration characteristics were also analyzed here by using correlation and principal component analyses. Results (1) There was no significant difference in the density and growth characteristics (base diameter, plant height and crown diameter) of regenerated seedlings of Pinus tabuliformis under the different fire severities (P ​> ​0.05), and the spatial distribution of regenerated seedlings fit the aggregated distribution pattern. (2) There was no significant difference in diameter at breast height (DBH), plant height or crown diameter of Pinus tabuliformis under different fire severities (P ​> ​0.05), but there were highly significant differences in scorch height, biomass of undergrowth woody plants, biomass of undergrowth herbs, undecomposed litter amount, semidecomposed litter amount and soil water content under different the fire severities (P ​ Conclusion In the 5th year after a fire disturbance, the seedling regeneration of Pinus tabuliformis in a burned area was influenced by factors such as the stand structure, undergrowth plants, litter and soil. Low- and moderate-severity fires promote the natural regeneration of stands and are conducive to the stable balance of ecosystems.

BackgroundPrevious studies have suggested associations between addictive behavior and gallstone disease (GSD) risk, yet conflicting results exist. It also remains unclear whether this association is causal or due to confounding or reverse associations. The present study aims to systematically analyze the epidemiological evidence for these associations, as well as estimate the potential causal relationships using Mendelian randomization (MR).MethodsWe analyzed four common addictive behaviors, including cigarette smoking, alcohol intake, coffee, and tea consumption (N = 126,906–4,584,729 participants) in this meta-analysis based on longitudinal studies. The two-sample MR was conducted using summary data from genome-wide associations with European ancestry (up to 1.2 million individuals).ResultsAn observational association of GSD risk was identified for smoking [RR: 1.17 (95% CI: 1.06–1.29)], drinking alcohol [0.84 (0.78–0.91)], consuming coffee [0.86 (0.79–0.93)], and tea [1.08 (1.04–1.12)]. Also, there was a linear relationship between smoking (pack-years), alcohol drinking (days per week), coffee consumption (cups per day), and GSD risk. Our MRs supported a causality of GSD incidence with lifetime smoking [1.008 (1.003–1.013), P = 0.001], current smoking [1.007 (1.002–1.011), P = 0.004], problematic alcohol use (PAU) [1.014 (1.001–1.026), P = 0.029], decaffeinated coffee intake (1.127 [1.043–1.217], P = 0.002), as well as caffeine-metabolism [0.997 (0.995–0.999), P = 0.013], and tea consumption [0.990 (0.982–0.997), P = 0.008], respectively.ConclusionOur study suggests cigarette smoking, alcohol abuse, and decaffeinated coffee are causal risk factors for GSD, whereas tea consumption can decrease the risk of gallstones due to the effect of caffeine metabolism or polyphenol intake.

Spinal cord injury (SCI) is a severe neurological disorder and the molecular mechanisms leading to its poor prognosis remain to be elucidated. S100A1, a mediator of Ca2+ handling of sarcoplasmic reticulum and mitochondrial function, operates as an endogenous danger signal (alarmin) associated with inflammatory response and tissue injury. The aim of the present study was to investigate the expression and biological effects of S100A1 in SCI. A rat model of SCI and a PC12 cell model of lipopolysaccharide (LPS)‑induced inflammation were established to examine S100A1 expression at the mRNA and protein levels. The inflammation level, which was mediated by S100A1, was determined based on inflammatory factor (IL‑1β, IL‑6 and TNF‑α) and anti‑inflammatory factor (IL‑10) expression. The effects of S100A1 on cellular oxidation and anti‑oxidation levels were observed by detecting the levels of reactive oxygen species, superoxide dismutase, catalase activities and nuclear factor erythroid 2‑related factor 2 expression. The protein levels of Bax, Bcl2 and cleaved caspase‑3 were used for the evaluation of the effects of S100A1 on apoptosis. Phosphorylated (p‑)ERK1/2 expression was used to evaluate the effects of S100A1 on ERK signaling. The results revealed that S100A1 expression was significantly upregulated

In order to explore the efficacy of using artificial intelligence (AI) algorithm-based ultrasound images to diagnose iliac vein compression syndrome (IVCS) and assist clinicians in the diagnosis of diseases, the characteristics of vein imaging in patients with IVCS were summarized. After ultrasound image acquisition, the image data were preprocessed to construct a deep learning model to realize the position detection of venous compression and the recognition of benign and malignant lesions. In addition, a dataset was built for model evaluation. The data came from patients with thrombotic chronic venous disease (CVD) and deep vein thrombosis (DVT) in hospital. The image feature group of IVCS extracted by cavity convolution was the artificial intelligence algorithm imaging group, and the ultrasound images were directly taken as the control group without processing. Digital subtraction angiography (DSA) was performed to check the patient’s veins one week in advance. Then, the patients were rolled into the AI algorithm imaging group and control group, and the correlation between May–Thurner syndrome (MTS) and AI algorithm imaging was analyzed based on DSA and ultrasound results. Satisfaction of intestinal venous stenosis (or occlusion) or formation of collateral circulation was used as a diagnostic index for MTS. Ultrasound showed that the AI algorithm imaging group had a higher percentage of good treatment effects than that of the control group. The call-up rate of the DMRF-convolutional neural network (CNN), precision, and accuracy were all superior to those of the control group. In addition, the degree of venous swelling of patients in the artificial intelligence algorithm imaging group was weak, the degree of pain relief was high after treatment, and the difference between the artificial intelligence algorithm imaging group and control group was statistically considerable ( p < 0.005 ). Through grouped experiments, it was found that the construction of the AI imaging model was effective for the detection and recognition of lower extremity vein lesions in ultrasound images. To sum up, the ultrasound image evaluation and analysis using AI algorithm during MTS treatment was accurate and efficient, which laid a good foundation for future research, diagnosis, and treatment.

Traditional x-ray sources used today for multiple applications, such as medical imaging (computed tomography, radiography, mammography, and interventional radiology) or industrial inspection, are vacuum based electron beam devices that include several key components, such as electron emitters, electron guns/cathodes, and anodes/targets. The associated electronics for electron beam generation, focusing and control, and beam acceleration are located outside the vacuum chamber. The general topology of these tubes has been directionally unchanged for more than 100 years; however, tube design remains a long, inefficient, tedious, and complex process; blind design of experiments do not necessarily make the process more efficient. As a case study, in this paper, we introduce the differential evolution (DE), an artificial intelligence-based optimization algorithm, for the design optimization of x-ray source beam optics. Using a small-scale design problem, we demonstrate that DE can be an effective optimization method for x-ray source beam optics design.

BackgroundObservational studies suggested that systemic lupus erythematosus (SLE) might be associated with increased cancer incidence and cancer-related death, however, the results are inconsistent. We aim to comprehensively estimate the causal relationships between SLE and cancer morbidity and mortality using a meta-analysis of cohort studies and Mendelian randomization.MethodsA systematic search was conducted using PubMed to identify cohort studies published before January 21, 2021. Meta-analysis was performed to calculate relative risk (RR) and corresponding 95% confidence intervals (CI). In addition, we further evaluated the potentially causal relationships identified by cohort studies using two-sample Mendelian randomization.ResultsA total of 48 cohort studies involving 247,575 patients were included. We performed 31 main meta-analysis to assess the cancer risk and three meta-analyses to evaluate cancer mortality in SLE patients. Through meta-analyses, we observed an increased risk of overall cancer (RR=1.62, 95%CI, 1.47-1.79, PPP=0.0035).ConclusionsFindings from our study suggest an important role of SLE in carcinogenesis, especially for lymphoma.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, CRD42021243635.

Background: This study aims to assess the sex disparities in clinical characteristics and synchronous distant metastasis occurrence at diagnosis, as well as the subsequent prognosis in non-sex-specific cancers. Methods: The study included details from patients diagnosed with non-sex-specific cancers, during the period from 2010 to 2016, in the Surveillance, Epidemiology, and End Results (SEER) program. The distant metastasis prevalence and subsequent survival time were summarized in the total population and the population with specific cancers of different systems. The multivariable logistic and the Cox proportional hazards regressions were applied to evaluate the sex effect on distant metastasis occurrence and prognosis. The results were combined using meta-analysis. Results: Across all non-sex-specific cancers, the pooled prevalence of distant metastasis was 15.2% (95% CI: 14.7-15.7%) and 7.1% (95% CI: 6.8-7.3%) for males and females, respectively. The pooled median survival time was 8.40 months (95% CI: 7.99-8.81) for male patients and 9.40 months (95% CI: 8.84-10.02) for female patients. After combining all non-sex-specific cancers, male patients displayed a higher distant metastasis occurrence than females (pooled OR=1.06, 95% CI: 1.04-1.08; P

Six new Co(II)/Ni(II) coordination polymers, [Ni3(opda)3(mbib)4(H2O)4]·2H2O (1), [Ni(mpda)(mbib)]·H2O (2), [Ni(ppda)(mbib)]·H2O (3), [Co(opda)(pbib)(H2O)] (4), [Co(mpda)(pbib)1.5] (5), and [Co(ppda)(pbib)(H2O)2]·2H2O (6) (H2opda = 1,2-phenylenediacetic acid, H2mpda = 1,3-phenylenediacetic acid, H2ppda = 1,4-phenylenediacetic acid, mbib = 1,3-bis(1-imidazoly)benzene, and pbib = 1,4-bis(1-imidazoly)benzene), were synthesized using Co(II)/Ni(II) salts and the bis(imidazole) ligand in the presence of three different flexible phenylenediacetate isomers under hydrothermal conditions. In 1, the opda2− ligand exhibits a trans-conformation and acts as a bridging building block extending a 1D loop-containing (Ni–mbib) polymer chain into a 2D network. In 2 and 3, mpda2− and ppda2− ligands possess a cis-conformation and can be seen as a “V”-type building block, linking Ni(II) atoms to form a 1D loop-containing chain together with the mbib ligand. Utilizing the isomer bridging ligand pbib and a different metal ion, Co(II), instead of the mbib ligand and Ni(II) ion, 2D (4), 1D (5), and 2D (6) coordination polymers were obtained. The structural diversity of these complexes is mainly attributed to the different coordination modes and isomer conformations of flexible phenylenediacetic acids and the bis(imidazole) ligand. Furthermore, six Co(II)/Ni(II) coordination polymers could accelerate the degradation rate of methylene blue (MB) under visible light irradiation, especially complex 4. Complex 2 exhibited a high performance in the oxygen evolution reaction (OER). Results will provide an effective way to develop coordination polymers towards electrochemical applications.

Background Brain metastasis (BM) causes high morbidity and mortality rates in lung cancer (LC) patients. The present study aims to develop models for predicting the development and prognosis of BM using a large LC cohort. Methods A total of 266,522 LC cases diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program cohort. Risk factors for developing BM and prognosis were calculated by univariable and multivariable logistic and Cox regression analysis, respectively, and nomograms were constructed based on risk factors. Nomogram performance was evaluated with receiver operating characteristics (ROC) curve, or C-index and calibration curve. Results The prevalence of BM was 13.33%. Associated factors for developing BM include: advanced age; Asian or Pacific Islander race; uninsured status; primary tumor site; higher T stage; higher N stage; poorly differentiated grade; the presence of lung, liver, and bone metastases; and adenocarcinoma histology. Median overall survival (OS) was 4 months; associated prognosis factors were similar to risk factors plus female gender, unmarried status, and surgery. The calibration curve showed good agreement between predicted and actual probability, and the AUC/C-index was 73.1% (95% CI: 72.6–73.6%) and 0.88 (95% CI: 0.87–0.89) for risk and prognosis predictive models, respectively. Conclusions BM was highly developed in LC patients, and homogeneous and heterogeneous factors were found between risk and prognosis for BM. The nomogram showed good performance in predicting BM development and prognosis.

A closed loop two-phase thermosiphon is supposed as an effective heat transfer unit for improving the heat transfer in the latent heat storage devices, which has a simple structure and natural circulation. An experimental study and theoretical analysis were conducted to evaluate the heat transfer performance. The effects of height difference, filling ratio, and condenser temperature were investigated relative to changes in pressure and evaporator temperature. The results indicate that heat transfer performance is improved with an increase in height difference and a decrease in condenser temperature. Meanwhile, a closed loop thermosiphon with medium filling ratios of 44.5% and 49.9% shows the best heat transfer performance. Furthermore, the subcooling phenomenon occurs at large filling ratios of 68.1% and 67.1% and the superheating phenomenon occurs at small filling ratios of 27.3% and 31.1%.

This paper examines whether there are differences in the nature of the price discovery process across established versus emerging stock markets using a twenty-country sample. Daily returns are analysed for traces of predictability or non-randomness using variance ratio tests, Granger-Causality models and runs tests. The findings pin-point at predictabilities which seem inconsistent with market efficiency, and they suggest that the inherent cause of predictability differs across groups. Whilst the pricing process in emerging markets may be hindered by delayed adjustments, in case of established markets it seems that there is a higher tendency for price reversals which could be due to prior over-reactions., peer-reviewed

Existing literature has produced broadly inconclusive evidence about the asset pricing model which best fits partially integrated markets. This paper examines whether industry and country factors are independent factors helping to determine returns in emerging stock markets, or are derived from the stocks’ risk-return characteristics. We link the country-industry decomposition framework to the local and the Global CAPM in a new and more direct way. The results show that country factors are additional independent sources of cross-sectional variation in stock returns before 1996 particularly under the Global CAPM. After 1996, the results suggest partial integration: industry and country factors are both additional independent determinants of cross-sectional variations in stock returns. .

Nowadays, there is a serious lack of information about the value-added apoptosis of sarcoma cells in China. Especially in clinical medicine, exploring the effect of ibuprofen on the growth and apoptosis of fibrosarcoma cells under the PI3K/Akt/mTOR signaling pathway can not only effectively prevent us in advance, but also be a great way to break through this field. The main purpose of this study was to investigate the effects of ibuprofen on the proliferation, cell cycle and apoptosis of fibrosarcoma cells through the PI3K/Akt/mTOR signaling pathway. We divided the HTl080 cell line into zero control group, control group and experimental group. The withering group was not inoculated with any cells, while the control group was only added with the same amount of culture medium, while the experimental group was added with 5,10,15,20 concentrations respectively. We found that the apoptosis rate of sarcoma cells in the control group increased from 5.66% to 7.12%, while the apoptosis rate of sarcoma cells in the experimental group increased significantly faster than that in the control group, with an overall increase of 7.16%, from 4.56% to 11.72%. Therefore, we can be surer that ibuprofen has a very good inhibitory effect on the proliferation, cell cycle and apoptosis of fibrosarcoma cells under the PI3K/Akt/mTOR signaling pathway. Therefore, when ibuprofen was injected into the body, it could not only observe the sarcoma cells well but also reflect the good inhibitory effect of ibuprofen on other substances in vivo under the PI3K/Akt/mTOR signaling pathway.

We aimed to perform a pan-metastatic cancer analysis on survival and prognostic factors and to create a prognosis-based classification system. We selected distant metastasis patients from the Surveillance, Epidemiology, and End Results (SEER) database. The associations between the characteristics of the patients at admission and overall survival were determined. A prognosis-based metastatic cancer classification was established based on the identified prognostic factors. The differences in prognosis among these categories were tested. The survival rate and prognostic factors were not consistent across cancers. Three metastatic cancer categories were generated, each with different prognoses. The prognostic differences among the categories were satisfactorily validated. Different metastatic cancer types had homogeneous and heterogeneous survival rates and prognostic factors. A prognosis-based classification system for synchronous distant metastasis cancer patients at admission was created. This classification system reflects the grade of malignancy in metastatic cancers and may guide the prediction of survival and individualized treatment. Moreover, it may have important implications for the management of synchronous metastatic cancers and aid clinicians in properly allocating medical resources to metastatic patients.

Focusing solenoids for accelerators and other charged particle beam applications usually have general requirements: focusing strength, stray field, eddy current losses and specific requirements. For industrial applications discussed in the paper, conventional resistive solenoids can be used, which have specific requirements include maximum operation current, minimum inductance or impedance. For high energy applications, superconducting focusing solenoids have been used widely [(T. Yang et al ., 2016), (G. Davis et al. , 2007)], which will have different design requirements. In contrast to a single quadrupole magnet, solenoid magnets can provide simultaneous focusing in both x- and y-directions. However, the focusing strength of solenoids is relatively low compared to quadrupoles due to the second order field effects (E. Muro et al. , 1990). But for low energy industrial application, solenoid magnets will be one of the cost-effective solutions. This paper proposes several design options to improve the performance of conventional resistive focusing solenoids. These design options include adding bucking coils to limit the stray fields, splitting the main coil to reduce the total impedance of the coils and implementing passive shielding layers to minimize the stray field and the effects of external disturbances simultaneously. Simulation results and experimental test data will be presented.

Thermal rectification is an attractive phenomenon for thermal management, which refers to a specific behavior in a heat transfer system where heat flow in one direction is stronger than that in the opposite direction under the same conditions. Two-dimensional monolayer molybdenum disulfide (MoS2) synthesized by chemical vapor deposition (CVD) has exhibited exceptional thermal, optical, and electrical properties due to its special structure; however, the thermal rectification in monolayer MoS2 is still not achieved by experimental measurement. Here, we successfully transferred monolayer MoS2 samples with three geometrical morphologies to the suspended microelectrodes by the PMMA approach. Through further heating the suspended microelectrodes with AC power in the opposite directions of these three monolayer MoS2 samples, we experimentally measured the thermal conductivity and first obtained the thermal rectification of monolayer MoS2. The rectification coefficients of monolayer MoS2 with three different geometrical morphologies are 10-13, 11-4, and 69-70%. Moreover, a theoretical model was also applied to discuss the dependence of thermal rectification on the geometrical asymmetry (angle and spacing). The results demonstrate that the monolayer MoS2 has an obvious thermal rectification phenomenon owing to the asymmetric structure, and it would have great potentials in the application of thermal energy control and management.

To investigate the injury effects of bike share programs and the helmet usage status in bike share programs. We conducted a systematic review of peer reviewed scientific literature. Searches were conducted in three databases (Pubmed, Scopus, and Web of Science) on March 1 2020 to identify all articles on the injury incidence related to bike share programs and the helmet usage status in bike share programs. Titles, abstracts, and full-text articles were screened to identify all articles relevant to the themes by two authors independently, and discrepancies were resolved after discussion with the third author. Standardised data extraction and quality assessment (The Newcastle-Ottawa Scale) were implemented. A sum of 491 records after removing duplicates was identified, 181 fulltext articles were screened, and 13 studies were included in the review. The primary outcome are injuries of bike share users and unhelmeted rate among bike share users as well as the unhelmeted rate among personal bike users. Two studies evaluated the injuries related to bike share users, but have inconclusive results. A total of 11 studies reported the unhelmeted rates in bike share programs ranging from 36.0 to 88.9%. There is a significant change in bike injuries with the implementation of bike share programs. Moreover, the unhelmeted rate of bike share users was generally higher than that of personal bike users, which may result from helmets' accessibility and users' safety perception.

BackgroundGenetic studies have linked polymorphisms in the interleukin 6 receptor (IL6R) gene to the risk of multiple human diseases and phenotypes, yet have reported inconsistent results. We aimed to synthesize current knowledge of variants in the IL6R gene on the risk of diseases and phenotypes.MethodsWe searched the Medline and Embase databases to identify relevant publications. Meta-analysis was performed utilizing DerSimonian and Laird random-effects model. We also graded cumulative evidence for significant associations. Furthermore, phenome-wide analyses and functional annotations were performed for variants with strong evidence.ResultsWe included 155 studies for evaluating the associations between 80 polymorphisms in the IL6R gene and the risk of 102 human diseases and 98 phenotypes. We conducted 58 main meta-analyses, and 41 significant associations were identified. Strong evidence was assigned to 29 associations that investigated ten variants (rs2228145, rs4129267, rs7529229, rs4537545, rs7518199, rs4845625, rs4553185, rs4845618, rs4845371, and rs6667434) related to the risk of four cardiovascular diseases (coronary heart disease, coronary artery disease, atherosclerosis, and abdominal aortic aneurysms), four inflammatory diseases (rheumatoid arthritis, Crohn’s disease, dermatitis, and asthma), and concentration of four phenotypes (C-reactive protein, fibrinogen, IL-6, and sIL-6R). Furthermore, phenome-wide analysis verified that rs2228145 associated with asthma and dermatitis risk. Functional analyses indicated that these polymorphisms fall within exon, enhancer regions.ConclusionsOur study comprehensively summarizes current data on the genetic architecture of the IL6R gene and highlights the pharmacological targeting potential of IL-6R on cardiovascular and inflammatory diseases.

The nonlinear dynamic characteristics of human brain cognition and music stimulation are introduced based on the negative emotions of college students to explore the influence of music stimulation on human brain cognition activities and analyze the nonlinear dynamic characteristics of electroencephalogram (EEG) signals. First, the correlation between EEG signals and human brain cognition, as well as the nonlinear dynamics of cognition, are explained. The average correlation dimension and the maximum value of the Lyapunov exponent are selected to characterize the nonlinear dynamic characteristics of EEG signals. Second, the power spectrum and EEG coherence are considered, and an emotion assessment algorithm is proposed. Finally, music stimulation is introduced, and its role in adjusting college students’ negative emotions is discussed. Results demonstrate significant differences in the average correlation dimension and the maximum value of the Lyapunov component of the participants in different cognition states under normal physiological conditions. The cognition function state shows chaotic behaviors, explaining the nonlinear dynamic characteristics of EEG signals. After music stimulation, a significant increase in EEG relative power is mostly located in the frontal and temporal regions of the brain. The EEG coherence in the same brain region shows growth changes. After the intervention of music stimulation, the emotion assessment scores of the self-rating anxiety scale, the positive and negative affect schedule, and the self-rating depression scale are reduced, and the entire changing process presents statistical significance. In conclusion, music stimulation intervention can affect human brain cognition activity, playing a positive role in emotion regulation.

Volcanic rocks are unconventional oil and gas reservoirs, and the pore structure of the rock is relatively complex. In this study, we selected samples from CS105 well and DS9 well from Yingcheng Formation volcanic reservoirs in the southern Songliao Basin to study the pore structure. First, we performed experiments on two rock samples using computed tomography (CT), and then measured the porosity and density of the two rock samples using mercury intrusion porosimetry (MIP). According to the data obtained by micron computed tomography (Micro-CT), Avizo 2019.1 software was used to perform three-dimensional (3D) reconstruction on the micron level of the two wellhead samples. Analyze the microscopic pore structure of the rock sample and compare it with the porosity of the sample obtained by the mercury injection method. Compared with MIP, Micro-CT more accurately characterizes the pore structure and porosity of volcanic rocks.

The main purpose of the interbank market is to redistribute liquidity in the financial system. However, the smoothing functioning of the market can be hampered by uncertainty during market distress, accentuated by the complexity of financial linkages. This chapter is inspired by the fact that interbank markets in their early stage of development are noticeably understudied. Using a unique daily transaction-level data set, spanning between 2003 and 2012, the chapter shows that Kenya's interbank market has become more closely interconnected with increasing network size and connectedness from 2006 to late 2009. This has coincided with a series of liquidity shocks that have affected liquidity demand in Kenya's banking sector. During liquidity shocks, large, foreign and listed banks have not only increased their importance in the network as borrowers but also formed a higher density of connections in the direct neighbourhood as borrowers. Consistent with the literature, this study suggests that with increased uncertainty and heightened asymmetric information, it is easier for more reputable banks to satisfy credit profiling by other banks and get access to liquidity. Such an incomplete interbank market structure, coupled with a high degree of interconnectedness, can facilitate the spread of liquidity shocks. Indeed, the regression models used in this chapter capture important heterogeneous relationships between topological measures and bank liquidity access during different liquidity shocks.

Background Observational studies suggested that systemic lupus erythematosus (SLE) was associated with an increased risk of cancer, however, the causal effect remains unclear. We aim to determine the causality between SLE and cancer using a meta-analysis and Mendelian randomization (MR) approach. Methods A systematic search was conducted using PubMed to identify cohort studies published before January 21, 2021. Meta-analysis was performed to calculate relative risk (RR) and corresponding 95% confidence intervals (CI), and the potentially causal relationships identified by observational studies were further validated using two-sample Mendelian randomization. Results Through meta-analysis of 43 cohort studies involving 231,499 patients, we observed an increased overall cancer risk among SLE patients (RR = 1.62, 95% CI, 1.47–1.79). Site-specific analysis suggested that SLE patients were associated with an increased risk of 17 cancers. Mendelian randomization analysis indicated that genetically predisposed SLE was causally associated with an increased risk of lymphoma (odds ratio = 1.0004, 95% CI, 1.0001–1.0007, P = 0.0035), whereas a decreased risk of bladder cancer (odds ratio = 0.9996, 95% CI, 0.9994–0.9998, P = 0.00004) in European ancestry. However, no relationship was observed between genetically predisposed SLE and risk of colon, pancreatic, lung, cervical and Non-melanoma skin cancer in European ancestry, liver cancer and lung cancer in Asian ancestry. Conclusions Findings from meta-analysis and Mendelian randomization analysis suggested that SLE might be causally associated with an increased risk of lymphoma. However, inconsistent results were observed between SLE and risk of bladder cancer.

A language model (LM) is an important part of a speech recognition system. The performance of an LM is affected when the domains of training data and test data are different. Language model adaptation is to compensate for this mismatch. However, there is no public dataset in Chinese for evaluating language model adaptation. In this paper, we present a public Chinese dataset called CLMAD for language model adaptation. The dataset consists of four domains: sport, stock, fashion, and finance. The differences in these four domains are evaluated. We present baselines for two commonly used adaptation techniques: interpolation for n-gram, and fine-tuning for recurrent neural network language models (RNNLMs). For n-gram interpolation, when the source domain and target domain are relatively similar, the adapted model can be improved. But interpolating LMs of very different domains does not obtain improvement. For RNNLMs, fine-tuning whole network achieves the largest improvement over only fine-tuning softmax layer or embedding layer. When the domain difference is large, the improvement of the adapted RNNLM is significant. We also provide speech recognition results on AISHELL-1 with the LMs trained on CLMAD. CLMAD can be freely downloaded at http://www.openslr.org/55/ .

Closed loop two-phase thermosyphon is an effective heat transfer device, of which the research is necessary to clarify the heat transfer and fluid flow mechanism. Numerical analysis was carried out in the article with one-dimensional model. The model was based on mass, momentum and energy conversation equations, solved by iterative method. Single-phase and two-phase flow were simulated, besides supercritical flow. Experimental data was used in the validation of the model with the error less than ±10%. The axial evolution of several parameters, namely pressure, enthalpy, void fraction, vapor quality and heat transfer coefficient in the loop, were presented firstly. Then the effects of pipe diameter, filling ratio, height difference, heat load, cold bath temperature and fluid type on the closed loop two-phase thermosyphon were investigated. Large pipe diameter and medium filling ratio led to low thermal resistance. The thermal resistance decreased with the increase of height difference firstly, and then increased at large height differences. Larger heat load led to higher mass flux, as well as larger subcooled or superheated region. Vapor quality at the outlet of evaporator increased with the increase in cold bath temperature, leading to low thermal resistance. Fluids with low viscosity and large density difference between liquid and vapor phase were suggested for favorable heat transfer performance. It was also concluded that thermal resistance increased sharply when supercritical phenomenon occurred due to the disappearance of two-phase region.

This study examines the connections between stock prices and key macroeconomic indicators: inflation, industrial production, interest rates, money supply and select interactions between the latter group of variables. Such links are evaluated through vectorautoregressions (VARs) on monthly data spanning over the period 1999-2017, for Belgium, France, Germany, Netherlands and Portugal. We check whether such relations are confirmed across different sub-periods and also adopt a non-parametric approach by using a Pesaran-Timmermann test. We find different contemporaneous and lead-lag relationships between stock prices and the selected variables, although there are variations across countries. VAR models indicate that stock prices significantly lead inflation across all countries during the sample period and in most cases this relationship was positive. In addition, stock prices significantly lead industrial production in four of the sampled countries and these relationships were positive as well. Contrary to long-established finance theories, we did not find numerous significant links between interest rates and stock indices; however the interaction between interest rates and money supply was a leading indicator of stock prices in France, Germany and Portugal., peer-reviewed

The acoustic model trained using the knowledge from the shared hidden layer (SHL) model outperforms the model trained only by using the target language, especially under low resource conditions. However, the shared features may contain some unnecessary language dependent information. It will degrade the performance of the target model. Therefore, this paper proposes language-adversarial transfer learning to alleviate this problem. Adversarial learning is used to ensure that the shared layers of the SHL-model can learn more language invariant features. Experiments are conducted on IARPA Babel datasets. The results show that the target model trained using the knowledge transferred from the adversarial SHL-model achieves up to 10.1% relative word error rate reduction when compared with the target model trained using the knowledge transferred from the SHL-model.

In order to determine the heat transfer performance and the mechanisms of separate heat pipe (SHP) under various operating conditions covering two-phase states and transcritical states, experimental investigation was carried out in this study. The effect of charging mass, cold bath temperature, heat load and height between evaporator and condenser on heat pipe was analyzed and the thermal resistance was calculated to characterize the heat transfer performance. Results showed that the increase of head load, the decrease of height difference and the increase of condenser temperature led to increases in thermal resistance. Appropriate charging mass was seen to be the most important factor in terms of optimum heat transfer performance, whereas too much or too little charging mass led to the subcooling or superheating in the evaporator, which was found to have a direct impact on heat transfer performance.

Attention-based models have recently shown powerful representation learning ability in speaker recognition. However, most of the attention mechanism based models primarily focus on pooling layers. In this work, we present an end-to-end speaker verification system which leverage time-frequency and channel features hierarchically. To further improve system performance, we employ Large Margin Cosine Loss to optimize the model to determine the optimal loss function. We carry out experiments on the VoxCeleb1 datasets to evaluate the effectiveness of our methods. The results suggest that our best system outperforms the i-vector + PLDA and x-vector system by 53.3% and 7.6%, respectively.

Transducer-based models, such as RNN-Transducer and transformer-transducer, have achieved great success in speech recognition. A typical transducer model decodes the output sequence conditioned on the current acoustic state and previously predicted tokens step by step. Statistically, The number of blank tokens in the prediction results accounts for nearly 90\% of all tokens. It takes a lot of computation and time to predict the blank tokens, but only the non-blank tokens will appear in the final output sequence. Therefore, we propose a method named fast-skip regularization, which tries to align the blank position predicted by a transducer with that predicted by a CTC model. During the inference, the transducer model can predict the blank tokens in advance by a simple CTC project layer without many complicated forward calculations of the transducer decoder and then skip them, which will reduce the computation and improve the inference speed greatly. All experiments are conducted on a public Chinese mandarin dataset AISHELL-1. The results show that the fast-skip regularization can indeed help the transducer model learn the blank position alignments. Besides, the inference with fast-skip can be speeded up nearly 4 times with only a little performance degradation., Comment: Submitted to INTERSPEECH2021

Fake audio attack becomes a major threat to the speaker verification system. Although current detection approaches have achieved promising results on dataset-specific scenarios, they encounter difficulties on unseen spoofing data. Fine-tuning and retraining from scratch have been applied to incorporate new data. However, fine-tuning leads to performance degradation on previous data. Retraining takes a lot of time and computation resources. Besides, previous data are unavailable due to privacy in some situations. To solve the above problems, this paper proposes detecting fake without forgetting, a continual-learning-based method, to make the model learn new spoofing attacks incrementally. A knowledge distillation loss is introduced to loss function to preserve the memory of original model. Supposing the distribution of genuine voice is consistent among different scenarios, an extra embedding similarity loss is used as another constraint to further do a positive sample alignment. Experiments are conducted on the ASVspoof2019 dataset. The results show that our proposed method outperforms fine-tuning by the relative reduction of average equal error rate up to 81.62%., Comment: 5 pages, conference

Although attention based end-to-end models have achieved promising performance in speech recognition, the multi-pass forward computation in beam-search increases inference time cost, which limits their practical applications. To address this issue, we propose a non-autoregressive end-to-end speech recognition system called LASO (listen attentively, and spell once). Because of the non-autoregressive property, LASO predicts a textual token in the sequence without the dependence on other tokens. Without beam-search, the one-pass propagation much reduces inference time cost of LASO. And because the model is based on the attention based feedforward structure, the computation can be implemented in parallel efficiently. We conduct experiments on publicly available Chinese dataset AISHELL-1. LASO achieves a character error rate of 6.4%, which outperforms the state-of-the-art autoregressive transformer model (6.7%). The average inference latency is 21 ms, which is 1/50 of the autoregressive transformer model., Comment: accepted by INTERSPEECH2020

Three-fold interpenetrating Zn(ii) MOF with the dense π-stacking of flexible ligands exhibit long-lived phosphorescence emission up to 91 ms at room temperature. Photoelectric measurements show efficient electro-hole separation based on the long lifetime of triplet state exciton.