Search

Abstract Reducing interface nonradiative recombination is important for realizing highly efficient perovskite solar cells. In this work, we develop a synergistic bimolecular interlayer (SBI) strategy via 4-methoxyphenylphosphonic acid (MPA) and 2-phenylethylammonium iodide (PEAI) to functionalize the perovskite interface. MPA induces an in-situ chemical reaction at the perovskite surface via forming strong P-O-Pb covalent bonds that diminish the surface defect density and upshift the surface Fermi level. PEAI further creates an additional negative surface dipole so that a more n-type perovskite surface is constructed, which enhances electron extraction at the top interface. With this cooperative surface treatment, we greatly minimize interface nonradiative recombination through both enhanced defect passivation and improved energetics. The resulting p-i-n device achieves a stabilized power conversion efficiency of 25.53% and one of the smallest nonradiative recombination induced V oc loss of only 59 mV reported to date. We also obtain a certified efficiency of 25.05%. This work sheds light on the synergistic interface engineering for further improvement of perovskite solar cells.

Abstract Bitter gourd, being perishable, requires timely harvesting. Delayed harvesting can result in a substantial reduction in fruit quality. while premature harvesting leads to underdeveloped fruit and decreased yields, the continuous flowering pattern in bitter gourd underscores the significance of accurately assessing fruit growth and ensuring timely harvesting for subsequent fruit setting and development. The current reliance on the experience of production personnel represents a substantial inefficiency. We present an improved real-time instance segmentation model based on YOLOv5-seg. The utilization of dynamic snake convolution enables the extraction of morphological features from the curved and elongated structure of bitter gourd. Diverse branch blocks enhance feature space diversity without inflating model size and inference time, contributing to improved recognition of expansion stages during bitter gourd growth. Additionally, the introduction of Focal-EIOU loss accurately locates the boundary box and mask, addressing sample imbalances in the L2 stage. Experimental results showcase remarkable accuracy rates of 99.3%, 93.8%, and 98.3% for L1, L2, and L3 stages using mAP@0.5. In comparison, our model outperforms other case segmentation models, excelling in both detection accuracy and inference speed. The improved YOLOv5-seg model demonstrates strong performance in fine-grained recognition of bitter gourd during the expansion stage. It efficiently segments bitter gourd in real-time under varying lighting and occlusion conditions, providing crucial maturity information. This model offers reliable insights for agricultural workers, facilitating precise harvesting decisions.

Abstract The thermal runaway issue represents a long‐standing obstacle that retards large‐scale applications of lithium metal batteries. Various approaches to inhibit thermal runaway suffer from some intrinsic drawbacks, either being irreversible or delayed thermal protection. Herein, this work has explored thermo‐responsive lower critical solution temperature (LCST) ionic liquid‐based electrolytes, which provides reversible overheating protection for batteries with warning and shut‐down stages, well corresponding to an initial stage of thermal runaway process. The batteries could function stably below 70 °C as a working mode, while demonstrating a warning mode above 80 °C with a noticeable reduction in specific capacitance to delay temperature increase of batteries. In terms of 110 °C as a critically dangerous temperature, a shut‐down mode is designed to minimize the thermal energy releasing as the batteries are barely chargeable and dischargeable. Dynamically growing polymeric particles above LCST contributed to such an intelligent and mild control on specific capacitance. Larger size will occupy larger surfaces of electrodes and close more pores of separators, enabling a gradual suppressing of Li+ transfer and reactions. The present work demonstrated a scientific design of thermoresponsive LCST electrolytes with a superiorly precise and intelligent control of electrochemical performances to achieve self‐adapted overheating protections.

BackgroundAdalimumab induces the production of anti-drug antibodies (ADA) that may lead to reduced drug concentration and loss-of-response, posing significant clinical challenges. However, traditional immunoassays have limitations in terms of sensitivity and drug-tolerance, hindering the insights of ADA response.MethodsHerein, we developed an integrated immunoassay platform combining the electrochemiluminescence immunoassay with immunomagnetic separation strategy. A longitudinal cohort study involving 49 patients with ankylosing spondylitis was carried out to analyze the dynamic profiles of ADA and to investigate the impact of ADA on adalimumab pharmacokinetics using a population pharmacokinetic model. Additionally, cross-sectional data from 12 patients were collected to validate the correlation between ADA levels and disease relapse.ResultsThe ADA assay demonstrated high sensitivity (0.4 ng/mL) and drug-tolerance (100 μg/mL), while the neutralizing antibodies (NAB) assay showed a sensitivity of 100 ng/mL and drug-tolerance of 20 μg/mL. Analysis of the longitudinal cohort revealed that a majority of patients (44/49, 90%) developed persistent ADA within the first 24 weeks of treatment. ADA levels tended to plateau over time after an initial increase during the early immune response phase. Further, nearly all of the tested patients (26/27, 96%) were classified as NAB positive, with a strong correlation between ADA levels and neutralization capacity (R2 = 0.83, P < 0.001). Population pharmacokinetic modeling revealed a significant positive association between model-estimated individual clearance and observed ADA levels. Higher ADA levels were associated with adalimumab clearance and disease relapse in a cross-sectional cohort, suggesting a promising ADA threshold of 10 for potential clinical application. Moreover, the IgG class was the primary contributor to ADA against adalimumab and the apparent affinity exhibited an increasing trend over time, indicating a T-cell dependent mechanism for ADA elicitation by adalimumab.ConclusionIn summary, this integrated immunoassay platform shows promise for in-depth analysis of ADA against biologics, offering fresh insights into immunogenicity and its clinical implications.

17q12 deletion syndrome is a chromosomal abnormality, where there is a small missing piece (deletion) of genetic material on the long arm (q) of chromosome 17. Sign and symptoms can vary widely among different patients. Recently, a patient was diagnosed with 17q12 deletion syndrome in our hospital, and the clinical characteristics presented as absence of the right kidney, compensatory hypertrophy of the left kidney, multiple small cysts in the left kidney, pancreatic atrophy, hypomagnesemia, bowed uterus, multiple follicular cysts in both lobes of the thyroid gland, and maturity-onset diabetes of the young type 5 (MODY-5). A 1.5-Mb deletion with haploinsufficiency for 20 genes within the 17q12 region was found through copy number variation (CNV) analysis based on metagenomic next-generation sequencing (mNGS) technology. In addition to HNF1B absence, the LIM-class homeobox 1 transcription factor (LHX1) and GGNBP2 absence was also involved in regulation of kidney development and the reproductive system through bioinformatics analysis. The inheriting risk of 17q12 deletion syndrome is about 50%, and it is recommended to provide genetic counseling to all patients who are suspected or diagnosed with the syndrome.

Abstract Background The prevalence of diabetes and obesity has been continuously rising worldwide over the last three decades, particularly in China. The prevalence varies widely among different ethnicities. In this study, we investigated the prevalence of diabetes and obesity, as well as the associated factors for diabetes in Kazakh adults in Xinjiang to improve diabetes screening. Methods We collected data from the Xinjiang physical examination in 2018, including a total sample of 118,505 Kazakh adults in Altay District. Data on demographic characteristics, medical history, physical examination, fasting plasma glucose (FPG) and serum lipid profiles were collected. The chi-square test was used to examine the differences between multiple variables. Multivariate logistic regression was performed to identify the factors associated with diabetes. Results The mean age was 43. 66 years (SD 14.14). 49.3% of the population were women and 75.5% were rural residents. The mean FPG was 5.33 mmol/L (SD 1.22). The prevalence of diabetes was 6.3% and 4.1% received a new diagnosis by FPG. 26.6% were diagnosed with impaired fasting glucose (IFG). The mean body mass index (BMI) was 26.29 kg/m2 (SD 14.14) and the mean waist circumference was 87.69 cm (SD 12.74). 33.2% of the population were overweight, and 33.0% were obese. The prevalence of central obesity was 51.4%. Diabetes was mostly positively associated with hypertension (OR = 3.821, P

Background: Head and neck cancer is the sixth most common malignancy worldwide, and oral squamous cell carcinoma (OSCC) is the most common head and neck cancer, being one of the leading causes of cancer morbidity and mortality worldwide. CC Chemokine receptor 7(CCR7) is a multifunctional G protein-coupled trans-membrane chemokine that affects immune cell chemotaxis, migration, and cancer progression through its interaction with its ligands C-C motif chemokine ligand 19(CCL19) and C-C motif chemokine ligand 21(CCL21). Numerous studies have demonstrated the involvement of CCR7 in the malignant progression of a variety of cancers, reflecting the pro-cancer properties of CCR7. The Cancer Genome Atlas data suggests CCR7 has elevated expression in oral cancer. Specifically, CCR7 expression in tumor microenvironment (TME) may regulate the ability of some immune cells to engage in anti-tumor immune responses. Since CD8+ T cells have become a key immunotherapeutic target, the role of CCR7 in antitumor immune response of naïve CD8+ T cells in TME has not been thoroughly investigated. Methods: A CCR7 knockout mouse model was constructed, and the mechanism of ccr7 on the regulation of tumor microenvironment by naïve CD8+ T cells was verified under the guidance of single-cell RNA sequencing combined with in vivo animal experiments and in vitro cell experiments. Results: CCR7 is knocked out with impaired tumor growth and altered CD8+ T cell profiles, revealing the importance of this protein in OSCC. Conclusions: Inhibition of CCR7 enhances CD8+ T cell activation, proliferation, and anti-tumor function, suggesting its potential as a therapeutic target.

Abstract Valine is an essential amino acid and a type of branched-chain amino acid. Due to the involvement of branched-chain amino acids in various metabolic pathways, there has been a surge of interests in valine nutrition and its role in animal physiology. In pigs, the interactions between valine and other branched-chain amino acids or aromatic amino acids are complex. In this review, we delve into the interaction mechanism, metabolic pathways, and biological functions of valine. Appropriate valine supplementation not only enhances growth and reproductive performances, but also modulates gut microbiota and immune functions. Based on past observations and interpretations, we provide recommended feed levels of valine for weaned piglets, growing pigs, gilts, lactating sows, barrows and entire males. The summarized valine nutrient requirements for pigs at different stages offer valuable insights for future research and practical applications in animal husbandry.

Using computer vision technology to estimate pig live weight is an important method to realize pig welfare. But there are two key issues that affect pigs’ weight estimation: one is the uneven illumination, which leads to unclear contour extraction of pigs, and the other is the bending of the pig body, which leads to incorrect pig body information. For the first one, Mask R-CNN was used to extract the contour of the pig, and the obtained mask image was converted into a binary image from which we were able to obtain a more accurate contour image. For the second one, the body length, hip width and the distance from the camera to the pig back were corrected by XGBoost and actual measured information. Then we analyzed the rationality of the extracted features. Three feature combination strategies were used to predict pig weight. In total, 1505 back images of 39 pigs obtained using Azure kinect DK were used in the numerical experiments. The highest prediction accuracy is XGBoost, with an MAE of 0.389, RMSE of 0.576, MAPE of 0.318% and R2 of 0.995. We also recommend using the Mask R-CNN + RFR method because it has fairly high precision in each strategy. The experimental results show that our proposed method has excellent performance in live weight estimation of pigs.

Although PPP(Public-private partnership) mode has been applied for a long time in infrastructural project, the success rate is not very high. The sustainability of PPP projects is still influenced by many factors. In order to examine the evolutionary stable strategies (ESSs) of social capital, government, and paying consumers, a tripartite evolutionary game model is established in this work. In order to further promote consumer participation, it is necessary to make the assumption that customer oversight and review can have an impact on service prices. The results show: i)The strategy choice of consumer depends on the comparison between supervision cost of consumer and price coefficient for consumer to social capital. ii)Consumer supervision can promote the provision of high-quality services by social capital. iii)The difference between high-quality cost and low-quality cost, subsidy coefficient, price coefficient and supervision cost of consumer are critical factors influencing both evolutionary results and trajectories. This paper also puts forward policy implications for the three stakeholders to promote social capital's high-quality strategy so as to maintain the sustainability of PPP projects.

Background: Reconstruction of large scalp defects after tumor resection is common and challenging. Free skin grafting or free flap transfer is always performed. However, these techniques can result in poor functional and cosmetic outcomes. Methods: In the Second Affiliated Hospital of Soochow University and the Second Affiliated Hospital of Chengdu Medical College, 35 patients underwent jigsaw puzzle flap procedures based on a free-style perforator to repair large scalp defects after tumor resection from May 2013 to November 2022. The key to this procedure was to divide a large defect into several smaller parts that correspond to adjacent free-style perforators around the scalp defect. The free-style perforator flaps were designed in different ways, such as propeller flaps, rotation flaps, and V-Y advancement flaps, which were pedicled with free-style perforators. All of the small flaps were then mobilized to the defect and sutured to each other to create a new, large jigsaw puzzle-like flap to cover the large scalp defect. Finally, all the donor sites were closed directly. Results: Overall, 35 patients were treated. The average defect size was 72 ​cm2 (range, 25–91 ​cm2). All flaps had a satisfactory appearance after follow-up periods of 6 months–10 years. Local tumor recurrence occurred in one case. Conclusion: The application of a jigsaw puzzle flap based on a free-style perforator is a suitable option for the reconstruction of large scalp defects after resection, yielding satisfactory functional and cosmetic results.

Abstract Most cancer immunotherapy approaches aim to stimulate cytotoxic CD8+ T lymphocytes to reject tumor cells. Due to the tumor-mediated suppressive micro-environment, of which the major contributor is regulatory T cells (Tregs), promising preclinical approaches were disappointing in clinical settings. Our recent study demonstrated that transient interruption of Tregs could induce CD8+ T cell responses to reject tumors in an animal model. The long-term tumor protective effect has yet not to be investigated. In this study, mice with Treg depletion rejected tumors and were rechallenged to study anti-tumor memory immune responses. The effects of major immune cell subsets on tumor protection were explored. Finally, we demonstrate that transient depletion of Tregs during primary tumor challenge can result in long-lasting protection against the tumor rechallenge. Skin-resident memory T cells (sTRM) were major factors in rejecting rechallenged tumors even when peripheral T cells were deficient. These findings highlight a promising strategy for empowering tissue-resident memory T cells for cancer prevention and immunotherapy in humans by interrupting Tregs.

Carbon dioxide (CO2) is currently the most harmful greenhouse gas in the atmosphere. Obtaining long-term, high-resolution atmospheric column CO2 concentration (XCO2) datasets is of great practical significance for mitigating the greenhouse effect, identifying and controlling carbon emission sources, and achieving carbon cycle management. However, mainstream satellite observations provide XCO2 datasets with coarse spatial resolution, which is insufficient to support the needs of higher-precision research. To address this gap, in this study, we integrate spatial information with the extreme random trees model and develop a new machine learning model called spatial extreme random trees (SExtraTrees) to reconstruct a 1 km spatial resolution XCO2 dataset for China from 2016 to 2020. The results indicate that the predictive ability of spatial extreme random trees is more stable and has higher fitting accuracy compared to other methods. Overall, XCO2 in China shows an increasing trend year by year, with the spatial distribution revealing significantly higher XCO2 levels in eastern coastal regions compared to western inland areas. The contributions of this study are primarily in the following areas: (1) Considering the spatial heterogeneity of XCO2 and combining spatial features with the advantages of machine learning, we construct the spatial extreme random trees model, which is verified to have high predictive accuracy. (2) Using the spatial extreme random trees model, we reconstruct high-resolution XCO2 datasets for China from 2016 to 2020, providing data support for carbon emission reduction and related decision making. (3) Based on the generated dataset, we analyze the spatiotemporal distribution patterns of XCO2 in China, thereby improving emission reduction policies and sustainable development measures.

Abstract Objectives This study aims to develop and validate a virtual biopsy model to predict microsatellite instability (MSI) status in preoperative gastric cancer (GC) patients based on clinical information and the radiomics of deep learning algorithms. Methods A total of 223 GC patients with MSI status detected by postoperative immunohistochemical staining (IHC) were retrospectively recruited and randomly assigned to the training (n = 167) and testing (n = 56) sets in a 3:1 ratio. In the training set, 982 high-throughput radiomic features were extracted from preoperative abdominal dynamic contrast-enhanced CT (CECT) and screened. According to the deep learning multilayer perceptron (MLP), 15 optimal features were optimized to establish the radiomic feature score (Rad-score), and LASSO regression was used to screen out clinically independent predictors. Based on logistic regression, the Rad-score and clinically independent predictors were integrated to build the clinical radiomics model and visualized as a nomogram and independently verified in the testing set. The performance and clinical applicability of hybrid model in identifying MSI status were evaluated by the area under the receiver operating characteristic (AUC) curve, calibration curve, and decision curve (DCA). Results The AUCs of the clinical image model in training set and testing set were 0.883 [95% CI: 0.822–0.945] and 0.802 [95% CI: 0.666–0.937], respectively. This hybrid model showed good consistency in the calibration curve and clinical applicability in the DCA curve, respectively. Conclusions Using preoperative imaging and clinical information, we developed a deep-learning-based radiomics model for the non-invasive evaluation of MSI in GC patients. This model maybe can potentially support clinical treatment decision making for GC patients. Graphical abstract

Abstract Type 2 diabetes mellitus (T2DM) with hypertension (DH) is the most common diabetic comorbidity. Patients with DH have significantly higher rates of cardiovascular disease morbidity and mortality. The objective of this study was to develop and validate a nomogram model for the prediction of an individual's risk of developing DH. A total of 706 T2DM patients who met the criteria were selected and divided into a training set (n = 521) and a validation set (n = 185) according to the discharge time of patients. By using multivariate logistic regression analysis and stepwise regression, the DH nomogram prediction model was created. Calibration curves were used to evaluate the model's accuracy, while decision curve analysis (DCA) and receiver operating characteristic (ROC) curves were used to evaluate the model's clinical applicability and discriminatory power. Age, body mass index (BMI), diabetic nephropathy (DN), and diabetic retinopathy (DR) were all independent risk factors for DH (P

The high pressure structural evolution of cubic Yb2O3 has been studied using in situ synchrotron angle dispersive x-ray diffraction in combination with diamond anvil cell techniques up to 44.1 GPa. The XRD measurements revealed an irreversible reconstructive phase transition from cubic to monoclinic Yb2O3 at 11.2 GPa and extending up to 28.1 GPa with ∼8.1% volume collapse and a subsequent reversible displacive transition from monoclinic to hexagonal phase starting at 22.7 GPa. The monoclinic phase coexists with the hexagonal phase up to 44.1 GPa. After pressure releases, the hexagonal Yb2O3 reverts to the monoclinic structure. The second-order Birch–Murnaghan equation of state fit to the pressure–volume data yields a bulk modulus of 201 (4), 187 (6), and 200 (4) GPa for the cubic, monoclinic, and hexagonal phases, respectively. Furthermore, the effects of the hydrostatic pressure state on the diffraction patterns, bulk modulus, and onset transition pressure of Yb2O3 under high pressure have been discussed. It is concluded that the bulk modulus of the cubic Ln2O3 phase increases with decreasing cation radius due to lanthanide contraction. Another important work in this study is the determination of the enthalpies of the cubic to monoclinic and monoclinic to hexagonal phase transitions of Yb2O3 of 37.0 and 17.4 kJ/mol, respectively, based on the basic thermodynamic equations and using the onset transition pressures and corresponding volume changes obtained from high pressure XRD experiments.

Bovine viral diarrhoea virus (BVDV) is the etiologic agent of bovine viral diarrhea-mucosal disease, one of the most important viral diseases in cattle, with inflammatory diarrhea, enteritis, and mucosa necrosis as the major clinical manifestations. NF-κB is an important transcription complex that regulates the expression of genes involved in inflammation and immune responses. NLRP3 inflammasome plays a key role in the development of inflammatory diseases. However, whether the activation of NF-κB is crucial for BVDV infection-induced inflammatory responses remains unclear. The results of our present study showed that BVDV infection significantly activated the NF-κB pathway and promoted the expression of NLRP3 inflammasome components (NLRP3, ASC, pro-caspase 1) as well inflammatory cytokine pro-IL-1β in BVDV-infected bovine cells, resulting in the cleavage of pro-caspase 1 and pro-IL-1β into active form caspase 1 and IL-1β. However, the levels of the NLRP3 inflammasome components and inflammatory cytokines were obviously inhibited, as well the cleavage of pro-caspase 1 and pro-IL-1β in the pre-treated bovine cells with NF-κB-specific inhibitors after BVDV infection. Further, cytopathic biotype BVDV (cpBVDV) Erns and NS5A proteins with their key functional domains contributed to BVDV-induced inflammatory responses via activating the NF-κB pathway were confirmed experimentally. Especially, the NS5A can promote cholesterol synthesis and accelerate its augmentation, further activating the NF-κB signalling pathway. Conclusively, our data elucidate that the activation of NF-κB signaling pathway plays a crucial role in cpBVDV infection-induced inflammatory responses.

Feline viral diseases, such as feline panleukopenia, feline infectious peritonitis, and feline coronaviral enteritis, seriously endanger the health of cats, and restrict the development of pet industry. Meanwhile, there is a current lack of effective vaccines to protect against feline viral diseases. Thus, effective therapeutic agents are highly desirable. Interferons (IFNs) are important mediators of the antiviral host defense in animals, particularly type I IFNs. In this study, a novel feline IFN omega (feIFN-ω) gene was extracted from the cat stimulated with feline parvovirus (FPV) combined with poly(I:C), and following codon optimization encoding the feIFN-ω, the desired gene (feIFN-ω’) fragment was inserted into plasmid pPICZαA, and transformed into Pichia pastoris GS115, generating a recombinant P. pastoris GS115 strain expressing the feIFN-ω’. After induction, we found that the expression level of the feIFN-ω’ was two times more than that of feIFN-ω (p

Abstract Purpose This study aimed to investigate the impact of CC chemokine receptor 7 (CCR7) on the recruitment and polarization of tumor-associated macrophages (TAMs) in oral squamous cell carcinoma (OSCC). Methods We analyzed CCR7 expression pattern, clinicopathological significance, and its association with M2 macrophage infiltration in OSCC by bioinformatic methods. Small interfering RNA (siRNA) was utilized to silence CCR7 in OSCC cells. Conditioned media (CM) was harvested from transfected OSCC cells to establish a co-culture model of THP-1 derived macrophages and OSCC cells. Transwell assay and cell adhesion assay were performed to examine the effect of CCR7 on macrophages recruitment and adhesion. Cytoskeleton was labelled by phalloidin to observe macrophage morphological changes. Moreover, phenotypic alteration of macrophages was measured using quantitative real-time PCR (qRT-PCR), flow cytometry, and immunofluorescence (IF) staining. Ultimately, recombinant human CCL19 and CCL21 were added into the medium of THP-1 derived macrophages to explore their effects on polarization in vitro. Results In OSCC patients, the overexpression of CCR7 positively correlated with lymph node metastasis and M2 macrophage infiltration. Macrophage not only exhibited enhanced migration, invasion and adhesion abilities, but also appeared more spindle and branched in vitro when treated with CM from OSCC cells. However, these phenomena were abrogated with knockdown of CCR7. We also discovered that inhibition of CCR7 in OSCC cells suppressed TAMs polarization to an M2 phenotype. In addition, recombinant human CCL19 and CCL21 promoted macrophage M2-polarization in vitro. Conclusion CCR7 in OSCC cells promoted recruitment and M2-polarization of THP-1 derived macrophages in vitro by regulating production of CCL19 and CCL21.

Pressure-induced phase transitions in cubic Eu2O3 subjected to non-hydrostatic conditions have been studied by in situ high-pressure synchrotron angle dispersive x-ray diffraction and Raman scattering measurements up to 30.1 and 43.8 GPa, respectively. Both x-ray diffraction and Raman spectroscopy results indicate that the pressure-induced transition routines of cubic Eu2O3 depend on the nature of stress loading. In contrast to our previous high-pressure studies of cubic Eu2O3 under hydrostatic pressure, where cubic Eu2O3 transforms directly into a hexagonal structure, the x-ray diffraction data show that cubic Eu2O3 begins to transform into the monoclinic phase at a non-hydrostatic pressure of about 4.3 GPa, while the monoclinic to hexagonal phase transition is initiated at about 6.4 GPa. These phase transitions have also been confirmed by Raman spectroscopy; the hexagonal phase is stable up to at least 43.8 GPa; and the material decompressed from high pressures is composed of a monoclinic phase, showing that the cubic Eu2O3 to monoclinic phase transition is irreversible due to the constructive nature. Pressure coefficients of Raman peaks and Grüneisen mode parameters of cubic, monoclinic, and hexagonal phases followed under pressure were determined. Furthermore, this study provides evidence for the shear stress-induced cubic to monoclinic phase transition in cubic Eu2O3 and the corresponding mechanism.

Ulva prolifera (U. prolifera), a global eco-environmental issue, has been recurring annually in the Yellow Sea of China since 2007, leading to significant impacts on the coastal ecosystem and the economies of coastal cities. To enhance the frequency of daily monitoring for U. prolifera and to advance the multi-source remote sensing monitoring system, a combination of the Sentinel-1 SAR remote sensing satellite and the Sentinel-3 OLCI and NPP VIIRS optical remote sensing satellites was employed. This comprehensive analysis encompassed the examination of Sentinel-1 C band characteristics, the range of influence of U. prolifera, and the migration trajectory of its enrichment zones. On 6 June 2021, three satellite images depicted the northwest drift of U. prolifera, followed by a southward movement after making contact with the coast of Qingdao, China, on 12 June. The most extensive impact area caused by U. prolifera was observed on 18 June. Subsequently, the images revealed a contraction and enrichment of U. prolifera in an eas–-west direction. The amalgamation of radar and optical remote sensing satellites in a multi-frequency monitoring approach allows for a continuous all-weather surveillance mechanism for U. prolifera. This mechanism serves to provide timely alerts for the prevention and management of U. prolifera outbreaks.

Objective: To investigate the protective effect of bexarotene in radiation-induced skin injury and elucidate underlying mechanism. Methods: Irradiated cellular and animal models were established using an X-ray linear accelerator. Cell viability and apoptosis were evaluated by CCK8 and flow cytometry. In vivo protective effect of bexarotene was measured in irradiated SD rats. The antioxidant capacity of bexarotene was validated by DCF-DA method. The signaling pathways involved in bexarotene-mediated skin repair were enriched by RNA sequencing. Results: Bexarotene could significantly restore the proliferation and inhibit the apoptosis of WS1 cells with radiation damage (P ​

Magnetic droplets are a type of non-topological magnetic soliton, which are stabilised and sustained by spin-transfer torques for instance. Without this, they would collapse. Here Ahlberg et al show that by decreasing the applied magnetic field, droplets can be frozen, forming a static nanobubble

The COVID-19 disease caused by infection with SARS-CoV-2 and its variants is devastating to the global public health and economy. To date, over a hundred COVID-19 vaccines are known to be under development, and the few that have been approved to fight the disease are using the spike protein as the primary target antigen. Although virus-neutralizing epitopes are mainly located within the RBD of the spike protein, the presence of T cell epitopes, particularly the CTL epitopes that are likely to be needed for killing infected cells, has received comparatively little attention. This study predicted several potential T cell epitopes with web-based analytic tools and narrowed them down from several potential MHC–I and MHC–II epitopes by ELIspot and cytolytic assays to a conserved MHC–I epitope. The epitope is highly conserved in current viral variants and compatible with a presentation by most HLA alleles worldwide. In conclusion, we identified a CTL epitope suitable for evaluating the CD8+ T cell-mediated cellular response and potentially for addition into future COVID-19 vaccine candidates to maximize CTL responses against SARS-CoV-2.

Blood samples are easily damaged in traditional bloodstain detection and identification. In complex scenes with interfering objects, bloodstain identification may be inaccurate, with low detection rates and false-positive results. In order to meet these challenges, we propose a bloodstain detection and identification method based on hyperspectral imaging and mixed convolutional neural networks, which enables fast and efficient non-destructive identification of bloodstains. In this study, we apply visible/near-infrared reflectance hyperspectral imaging in the 380–1000 nm spectral region to analyze the shape, structure, and biochemical characteristics of bloodstains. Hyperspectral images of bloodstains on different substrates and six bloodstain analogs are experimentally obtained. The acquired spectral pixels are pre-processed by Principal Component Analysis (PCA). For bloodstains and different bloodstain analogs, regions of interest are selected from each substance to obtain pixels, which are further used in convolutional neural network (CNN) modeling. After the mixed CNN modeling is completed, pixels are selected from the hyperspectral images as a test set for bloodstains and bloodstain analogs. Finally, the bloodstain recognition ability of the mixed 2D-3D CNN model is evaluated by analyzing the kappa coefficient and classification accuracy. The experimental results show that the accuracy of the constructed CNN bloodstain identification model reaches 95.4%. Compared with other methods, the bloodstain identification method proposed in this study has higher efficiency and accuracy in complex scenes. The results of this study will provide a reference for the future development of the bloodstain online detection system.

Cancer is a major public health threat, and researchers are constantly looking for new ways to develop effective treatments. One approach is the use of cancer vaccines, which work by boosting the body’s immune system to fight cancer. The goal of this study was to develop an effective cancer vaccine using rendered-inactive tumor cells. A CMS5 fibrosarcoma tumor model in BALB/c mice and an E.G7 lymphoma tumor model in C57BL/6 mice were used to evaluate how mitomycin C-inactivated tumor cells mediated tumor protection. The results showed that immunization with inactivated CMS5 cells significantly improved tumor suppression after a challenge with live CMS5 tumor cells, but no effect was observed using the E.G7 tumor model. The results suggested that DC (dendritic cell) responses to tumor antigens are critical. The maturation and activation of DCs were effectively promoted by mitomycin C-treated CMS5 cells, as well as enhanced phagocytosis ability in vitro. The tumor-protective effects established by the vaccination of inactivated CMS5 cells were CD8+ T cell-dependent, as the antitumor responses disappeared after eliminating CD8+ T cells. It was found that the tumor-prevention efficacy was dramatically increased by combining inactivated CM55 tumor cells with anti-CD25 antibodies to temporarily deplete Treg cells (regulatory T cells). This strategy could also significantly induce the rejection against E.G7 tumors. In addition, vaccination with anti-CD25 antibodies plus inactivated CMS5 cells elicited antitumor responses against heterologous tumors. According to the findings of this study, combining the immunization of inactivated tumor cells with an anti-CD25 antibody may be an effective method for cancer prevention.

Fruit maturity is a crucial index for determining the optimal harvesting period of open-field loofah. Given the plant’s continuous flowering and fruiting patterns, fruits often reach maturity at different times, making precise maturity detection essential for high-quality and high-yield loofah production. Despite its importance, little research has been conducted in China on open-field young fruits and vegetables and a dearth of standards and techniques for accurate and non-destructive monitoring of loofah fruit maturity exists. This study introduces a real-time detection and maturity classification method for loofah, comprising two components: LuffaInst, a one-stage instance segmentation model, and a machine learning-based maturity classification model. LuffaInst employs a lightweight EdgeNeXt as the backbone and an enhanced pyramid attention-based feature pyramid network (PAFPN). To cater to the unique characteristics of elongated loofah fruits and the challenge of small target detection, we incorporated a novel attention module, the efficient strip attention module (ESA), which utilizes long and narrow convolutional kernels for strip pooling, a strategy more suitable for loofah fruit detection than traditional spatial pooling. Experimental results on the loofah dataset reveal that these improvements equip our LuffaInst with lower parameter weights and higher accuracy than other prevalent instance segmentation models. The mean average precision (mAP) on the loofah image dataset improved by at least 3.2% and the FPS increased by at least 10.13 f/s compared with Mask R-CNN, Mask Scoring R-CNN, YOLACT++, and SOLOv2, thereby satisfying the real-time detection requirement. Additionally, a random forest model, relying on color and texture features, was developed for three maturity classifications of loofah fruit instances (M1: fruit setting stage, M2: fruit enlargement stage, M3: fruit maturation stage). The application of a pruning strategy helped attain the random forest model with the highest accuracy (91.47% for M1, 90.13% for M2, and 92.96% for M3), culminating in an overall accuracy of 91.12%. This study offers promising results for loofah fruit maturity detection, providing technical support for the automated intelligent harvesting of loofah.

Abstract Merkel cell carcinoma (MCC) is a rare but aggressive skin cancer with a high mortality rate, while Merkel cell polyomavirus (MCV) has been pointed as the causative agent of MCC. A better prognosis of MCC associated with a high level of antibodies against the capsid protein VP1 suggests that anti-VP1 immune response might be essential against MCC growth. In the current study, we developed a VP1-target vaccine formulated with CRA. Using a tumorigenic CMS5-VP1 tumor model, the vaccine-induced a potent antitumor efficacy in a dose-dependent manner was evidently demonstrated and mainly mediated by both VP1-specific CD4+ and CD8+ T-cell responses against the growth of CMS5-VP1 tumors in vaccinated BALB/c mice since the depletion of CD4+ and CD8+ T cells reverse the antitumor effects. Thus, immunotherapy with this vaccine represents a novel approach for the clinical treatment of aggressive MCV-related MCC in humans.

Abstract Owing to programmable nonlinear dynamics, magnetic domain wall (DW)‐based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy‐efficient, CMOS compatible, reliable, and tunable spintronic neurons to emulate brain‐inspired processes has been a key research goal for decades. Here, a new type of DW device is reported with biological neuron characteristics driven by the synergistic interaction between spin‐orbit torque and built‐in field (Hbuilt‐in) in magnetic tunnel junctions, enabling time‐ and energy‐efficient leaky‐integrate‐and‐fire and self‐reset neuromorphic implementations. A tilted magnetic anisotropic free layer is proposed and further executed to mitigate the DW retrograde motion by suppressing the Walker breakdown. Complementary experiments and micromagnetic co‐simulation results show that the integrating/leaking time of the developed spintronic neuron can be tuned to 12/15 ns with an integrating power consumption of 65 µW, which is 36× and 1.84× time and energy efficient than the state‐of‐the‐art alternatives, respectively. Moreover, the spatial distribution of Hbuilt‐in can be modulated by adjusting the width and compensation of the reference layer, facilitating tunable activation function generator exploration. Such architecture demonstrates great potential in both fundamental research and new trajectories of technology advancement for spintronic neuron hardware applications.

Abstract Perovskite solar cells (PSCs) suffer from significant nonradiative recombination at perovskite/charge transport layer heterojunction, seriously limiting their power conversion efficiencies. Herein, solution‐processed chromium multioxide (CrOx) is judiciously selected to construct a MAPbI3/CrOx/Spiro‐OMeTAD hole‐selective heterojunction. It is demonstrated that the inserted CrOx not only effectively reduces defect sites via redox shuttle at perovskite contact, but also decreases valence band maximum (VBM)‐HOMO offset between perovskite and Spiro‐OMeTAD. This will diminish thermionic losses for collecting holes and thus promote charge transport across the heterojunction, suppressing both defect‐assisted recombination and interface carrier recombination. As a result, a remarkable improvement of 21.21% efficiency with excellent device stability is achieved compared to 18.46% of the control device, which is among the highest efficiencies for polycrystalline MAPbI3 based n–i–p planar PSCs reported to date. These findings of this work provide new insights into novel charge‐selective heterojunctions for further enhancing efficiency and stability of PSCs.

Abstract Metallization has recently garnered significant interest due to its ability to greatly facilitate chemical reactions and dramatically change the properties of materials. Materials displaying metallization under low pressure are highly desired for understanding their potential properties. In this work, the effects of the pressure on the structural and electronic properties of lead‐free halide double perovskite (NH4)2PtI6 are investigated systematically. Remarkably, an unprecedented bandgap narrowing down to the Shockley–Queisser limit is observed at a very low pressure of 0.12 GPa, showing great promise in optoelectronic applications. More interestingly, the metallization of (NH4)2PtI6 is initiated at 14.2 GPa, the lowest metallization pressure ever reported in halide perovskites, which is related to the continuous increase in the overlap between the valence and conduction band of I 5p orbital. Its structural evolution upon compression before the metallic transition is also tracked, from cubic Fm‐3m to tetragonal P4/mnc and then to monoclinic C2/c phase, which is mainly associated with the rotation and distortions within the [PtI6]2– octahedra. These findings represent a significant step toward revealing the structure–property relationships of (NH4)2PtI6, and also prove that high‐pressure technique is an efficient tool to design and realize superior optoelectronic materials.

Objective To analyze the clinical characteristics and controllable risk factors of osteoporosis in elderly men with type‐2 diabetes mellitus (T2DM). Methods A total of 250 elderly OP patients with T2DM were included in the present study. Patients with one or more common chronic diseases (including hypertension, coronary heart disease, heart failure, chronic bronchitis, chronic nephrosis, and cirrhosis), and a course of more than 3 years were defined as complicated with chronic diseases. Blood glucose, cholesterol, triglyceride, low‐density lipoprotein, high‐density lipoprotein, calcium, phosphorus, glycosylated hemoglobin, urea nitrogen, creatinine, fasting insulin, liver function, and 25‐hydroxy vitamin D3 levels were measured. Bone mineral density was also measured. Results A total of 16 patients (6.4%) had severe osteoporosis. Furthermore, 66 patients (26.4%) had blood glucose control that reached the standard, while 176 patients (70.4%) used more than two anti‐diabetic drugs. The serum testosterone level was lower than the median in 87 patients (34.8%) and in 56 smokers (22.4%). Furthermore, 138 patients (55.2%) were overweight and obese, six patients (2.4%) were underweight, 197 patients (78.8%) had chronic diseases, 88 patients (35.2%) were sticking to exercise, and 117 patients (46.8%) had less exercise. In addition, 92 patients (36.8%) were treated with osteotrophy‐protective agents, and 24 patients (9.6%) received anti‐osteoporosis therapy. Smoking, poor glycemic control, low testosterone levels, less exercise, and complications with chronic diseases were the most relevant controllable risk factors. Conclusion For elderly male osteoporosis patients with type‐2 diabetes, smoking cessation, blood sugar control up to the standard, regular exercise, active prevention and treatment of complications, and appropriate testosterone supplementation are necessary for preventing and curing osteoporosis.

Elucidation of the molecular mechanisms involving the initiation and progression of radiation-induced esophageal injury (RIEI) is important for prevention and treatment. Despite ongoing advances, the underlying mechanisms controlling RIEI remain largely unknown. In the present study, RNA-seq was performed to characterize mRNA profiles of the irradiated rat esophagus exposed to 0, 25, or 35 Gy irradiation. Bioinformatics analyses including dose-dependent differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) pathway, protein-protein interaction (PPI) network, and immune infiltration were performed. 134 DEGs were screened out with a dose-dependent manner (35 Gy > 25 Gy > control, or 35 Gy < 25 Gy < control). GO and KEGG analyses showed that the most significant mechanism was IL-17 signaling-mediated inflammatory response. 5 hub genes, Ccl11, Cxcl3, Il17a, S100a8, and S100a9, were identified through the intersection of the DEGs involved in inflammatory response, IL-17 pathway, and PPI network. Additionally, immune infiltration analysis showed the activation of macrophages, monocytes, T cells, NKT cells, and neutrophils, among which macrophages, monocytes, and neutrophils might be the main sources of S100a8 and S100a9. Thus, these findings further our understanding on the molecular biology of RIEI and may help develop more effective therapeutic strategies.

American ginseng (Panax quinquefolius L.) has been cultivated in many locations in China, and we have noticed that its phenological performance and quality characteristics varied from location to location. However, the exogenous factors driving this process are still poorly understood, and this reduces the successful introduction of American ginseng for quality ensuring. Here, we conducted field and cabinet experiments to explore the relationship among environmental factors, phenological development, and ginsenoside accumulation in American ginseng. In the field experiments, we found that American ginseng from different original locations showed different phenological rhythms and different ginsenoside accumulation. Especially, those from higher latitude locations (e.g., Wuchang, 44.55°N) presented delayed spring phenology and advanced autumn phenology, but higher ginsenoside contents along with higher gene expression levels of ginsenoside biosynthesis than those from lower latitude locations (e.g., Wendeng, 37.23°N). Data analysis indicated that the phenological rhythm of American ginseng is closely related to the seasonal change in environmental factors, especially winter chilling duration, spring warming, and autumn day-length shortening. In the cabinet experiments, results further proved that temperature interaction with photoperiod plays a decisive role in the phenological development and ginsenoside accumulation of American ginseng in the absence of water and nutrient limitation. Both field and cabinet experiments indicated that sufficient winter cold exposure coupled with spring long day-length photoperiod is a beneficial environmental factor for normal spring phenology development, while shortening autumn day-length coupled with autumn cooling is a beneficial environmental factor for normal autumn phenology development of American ginseng. Results also indicated that insufficient cold exposure and unsuitable day-length photoperiod are detrimental factors to both spring and autumn phenology, and are not good for ginsenoside accumulation in American ginseng. An understanding of the environmental factors influencing phenological development along with ginsenoside accumulation can provide guidance for predicting suitable cultivation locations and improving planting techniques for high yield and good quality of American ginseng.

Abstract Background This study aims to explore the insulin requirement profiles, and analyze the related factors of type-2 diabetes mellitus (T2DM) with different C-peptide levels on insulin pump therapy. Methods A retrospective study was conducted on 271 T2DM patients treated with insulin pumps from 2016 to 2018. These patients were divided into groups according to the ratio of C-peptide at 2 h after meals to fasting C-peptide (C2h/C0), and the dosage of insulin and influencing factors were analyzed. Results In comparing group A (C2h/C0

Summary Oral squamous cell carcinoma (OSCC) become a heavy burden of public health, with approximately 300 000 newly diagnosed cases and 145 000 deaths worldwide per year. Nucleotide metabolism fuel DNA replication and RNA synthesis, which is indispensable for cell proliferation. But how tumor cells orchestrate nucleotide metabolic enzymes to support their rapid growth is largely unknown. Here we show that expression of pyrimidine metabolic enzyme dihydroorotate dehydrogenase (DHODH) is upregulated in OSCC tissues, compared to non-cancerous adjacent tissues. Enhanced expression of DHODH is correlated with a shortened patient survival time. Inhibition of DHODH by either shRNA or selective inhibitors impairs proliferation of OSCC cells and growth of tumor xenograft. Further, loss of functional DHODH imped de novo pyrimidine synthesis, and disrupt mitochondrial respiration probably through destabilizing the MICOS complex. Mechanistic study shows that transcriptional factor SOX2 plays an important role in the upregulation of DHODH in OSCC. Our findings add to the knowledge of how cancer cells co-opt nucleotide metabolism to support their rapid growth, and thereby highlight DHODH as a potential prognostic and therapeutic target for OSCC treatment.

The structural, electronic, optical, mechanical, lattice dynamics, and electronic transport properties of SrCu2O2 crystals were studied using first-principles calculations. The calculated band gap of SrCu2O2 using the HSE hybrid functional is about 3.33 eV, which is well consistent with the experimental value. The calculated optical parameters show a relatively strong response to the visible light region for SrCu2O2. The calculated elastic constants and phonon dispersion indicate that SrCu2O2 has strong stability in mechanical and lattice dynamics. The deep analysis of calculated mobilities of electrons and holes with their effective masses proves the high separation and low recombination efficiency of photoinduced carriers in SrCu2O2.

The harm of nonalcoholic fatty liver disease to human health is increasing, which calls for urgent prevention and treatment of the disease. Isoorientin is an effective ingredient of Chinese herbal medicine with anti-inflammatory and antioxidant effects. However, the effect of isoorientin in nonalcoholic fatty liver disease is still unclear. In this study, combined in vivo and in vitro experiments, through pathological observation, flow cytometry, immunofluorescence and western blot analysis to explore the role of isoorientin in steatosis and reveal its molecular mechanism. The results demonstrated that oleic acid treatment significantly increased the content of ROS and lipid droplets in rat hepatocytes, and promoted the expression of γH2AX, HO-1, PPARγ, SREBP-1c, FAS. The ROS content in the cells of co-treated with isoorientin and oleic acid was significantly reduced compared to the oleic acid group, and the expression of γH2AX, HO-1, PPARγ, SREBP-1c, FAS, and the nuclear translocation of NF-κB p65 were also significantly inhibited. Our data showed that oleic acid induce oxidative damage and steatosis in hepatocytes both in vitro and in vivo, and activate the PPARγ/NF-κB p65 signal pathway. Moreover, isoorientin can significantly reduce oleic acid -induced oxidative damage and steatosis by regulating the PPARγ/NF-kB p65 signal pathway.

Genetic optimization of Nucleic Acid immunogens is important for potentially improving their immune potency. A COVID-19 DNA vaccine is in phase III clinical trial which is based on a promising highly developable technology platform. Here, we show optimization in mice generating a pGX-9501 DNA vaccine encoding full-length spike protein, which results in induction of potent humoral and cellular immune responses, including neutralizing antibodies, that block hACE2-RBD binding of live CoV2 virus in vitro. Optimization resulted in improved induction of cellular immunity by pGX-9501 as demonstrated by increased IFN-γ expression in both CD8+ and CD4 + T cells and this was associated with more robust antiviral CTL responses compared to unoptimized constructs. Vaccination with pGX-9501 induced subsequent protection against virus challenge in a rigorous hACE2 transgenic mouse model. Overall, pGX-9501 is a promising optimized COVID-19 DNA vaccine candidate inducing humoral and cellular immunity contributing to the vaccine’s protective effects.

Through animal models, particularly non-obesity diabetes model (NOD), pathological understandings of human autoimmune diabetes have been gained. However, features of those mouse models and the human disease are not sufficiently analogous; it is therefore not unexpected that interventions based on the mouse data fail at an alarming rate in clinical settings. An improvised model that maximally resembles the real pathological course is highly desirable. Here we devised a ‘double-hit’ strategy, pancreas was first hit by chemical damage (streptozotocin, STZ) to unleash auto-antigens, then hit second time by transient immune-inflammation (regulatory T cell depletion). Comparing to NOD model, this strategy not only induced classical diabetic symptoms, but also depicted the crucial pathogenic features absent in conventional models, such as CD8+ T cell dominant infiltrates, strong ketoacidosis and epitope-specific T cell responses. In addition, this model allowed synchronized control of disease onset, permitting more refined temporal analysis of disease progression. We believe that this model would yield research outcomes with clinically relevant prediction power unattainable previously.

Background: Ginsenosides accumulation responses to temperature are critical to quality formation in cold-dependent American ginseng. However, the studies on cold requirement mechanism relevant to ginsenosides have been limited in this species. Methods: Two experiments were carried out: one was a multivariate linear regression analysis between the ginsenosides accumulation and the environmental conditions of American ginseng from different sites of China and the other was a synchronous determination of ginsenosides accumulation, overall DNA methylation, and relative gene expression in different tissues during different developmental stages of American ginseng after experiencing different cold exposure duration treatments. Results: Results showed that the variation of the contents as well as the yields of total and individual ginsenosides Rg1, Re, and Rb1 in the roots were closely associated with environmental temperature conditions which implied that the cold environment plays a decisive role in the ginsenoside accumulation of American ginseng. Further results showed that there is a cyclically reversible dynamism between methylation and demethylation of DNA in the perennial American ginseng in response to temperature seasonality. And sufficient cold exposure duration in winter caused sufficient DNA demethylation in tender leaves in early spring and then accompanied the high expression of flowering gene PqFT in flowering stages and ginsenosides biosynthesis gene PqDDS in green berry stages successively, and finally, maximum ginsenosides accumulation occurred in the roots of American ginseng. Conclusion: We, therefore, hypothesized that cold-induced DNA methylation changes might regulate relative gene expression involving both plant development and plant secondary metabolites in such cold-dependent perennial plant species.

Abstract Background Inflammation is one of a main reason for colon cancer progression and poor prognosis. The high-mobility group box-1 (HMGB1) and glutathione peroxidase 4 (GPX4) are responsible for inflammation, but the relationship between HMGB1 and GPX4 remains unknown about inflammation in colon cancer. Methods RT-qPCR was carried out to investigate the expression of IL1β, IL6 and TNFα in colon cancer cells stimulated with LPS or siHMGB1. To observe the relationship between HMGB1, GPX4 and inflammation or ROS, Western blot assays were adopted. Pull-down, CoIP and immunohistochemistry assays were performed to further investigate the molecular mechanisms of HMGB1 and GPX4 in colon cancer. Results We report that HMGB1 mediates lipopolysaccharide (LPS)-induced inflammation in colon cancer cells. Mechanistically, acetylated HMGB1 interacts with GPX4, negatively regulating GPX4 activity. Furthermore, by utilizing siHMGB1 and its inhibitor, our discoveries demonstrate that HMGB1 knockdown can inhibit inflammation and reactive oxygen species (ROS) accumulation via NF-kB. Conclusion Collectively, our findings first demonstrate that acetylated HMGB1 can interact with GPX4, leading to inflammation, and providing therapeutic strategies targeting HMGB1 and GPX4 for colon cancer.

Both turbo Hadamard codes and concatenated zigzag Hadamard codes are ultimate-Shannonlimit-approaching channel codes. The former one requires the use of Bahl-Cocke-Jelinek-Raviv (BCJR) in the iterative decoding process, making the decoder structure more complex and limiting its throughput. The latter one, however, does not involve BCJR decoding. Hence its decoder structure can be much simpler and can potentially operate at a much higher throughput. In this paper, we investigate the hardware design of a concatenated zigzag Hadamard encoder/decoder system and implement it onto an FPGA board. We design a decoder capable of decoding multiple codewords at the same time, and the proposed system can operate with a throughput of 1.44 Gbps - an increase of 50% compared with the turbo Hadamard encoder/decoder system. As for the error performance, the encoder/decoder system with a 6-bit quantization achieves a bit error rate of 2 × 10-5 at Eb/N0 = -0.2 dB.

In the application of X-ray industrial flaw detection, the exposure parameters directly affect the image quality. The voltage of the tube is the most important factor, which is difficult to be accurately calculated. Especially in the detection of a workpiece composed of both high absorption coefficient and low absorption coefficient materials, the improper symmetric balance of the tube voltage would lead to an overexposure or underexposure phenomenon. In this paper, based on the X-ray absorption model, combined with the performance of the X-ray imaging detector, and taking the optimal symmetry and contrast as the model constraint condition, the key factors of high absorption ratio material imaging are decomposed. Through expansion and iteration, the calculation process is simplified, the optimal imaging convergence surface is found, and then the optimal energy input conditions of high absorptivity materials are obtained and symmetrically balanced. As a result, this paper solves the problem of fast selection and symmetric factor chosen of the optimal tube voltage when imaging materials with high absorption ratios. It reduces the subsequent complications of the X-ray image enhancement process and obtains a better image quality. Through experimental simulation and measurement verification, the error between the theoretical calculation results and the measured data was better than 5%.

Slope failures lead to large casualties and catastrophic societal and economic consequences, thus potentially threatening access to sustainable development. Slope stability assessment, offering potential long-term benefits for sustainable development, remains a challenge for the practitioner and researcher. In this study, for the first time, an automated machine learning (AutoML) approach was proposed for model development and slope stability assessments of circular mode failure. An updated database with 627 cases consisting of the unit weight, cohesion, and friction angle of the slope materials; slope angle and height; pore pressure ratio; and corresponding stability status has been established. The stacked ensemble of the best 1000 models was automatically selected as the top model from 8208 trained models using the H2O-AutoML platform, which requires little expert knowledge or manual tuning. The top-performing model outperformed the traditional manually tuned and metaheuristic-optimized models, with an area under the receiver operating characteristic curve (AUC) of 0.970 and accuracy (ACC) of 0.904 based on the testing dataset and achieving a maximum lift of 2.1. The results clearly indicate that AutoML can provide an effective automated solution for machine learning (ML) model development and slope stability classification of circular mode failure based on extensive combinations of algorithm selection and hyperparameter tuning (CASHs), thereby reducing human efforts in model development. The proposed AutoML approach has the potential for short-term severity mitigation of geohazard and achieving long-term sustainable development goals.

The non-uniformity of the readout circuit response in the infrared focal plane array unit detector can result in fixed pattern noise with stripe, which seriously affects the quality of the infrared images. Considering the problems of existing non-uniformity correction, such as the loss of image detail and edge blurring, a multi-scale residual network with attention mechanism is proposed for single infrared image stripe noise removal. A multi-scale feature representation module is designed to decompose the original image into varying scales to obtain more image information. The product of the direction structure similarity parameter and the Gaussian weighted Mahalanobis distance is used as the similarity metric; a channel spatial attention mechanism based on similarity (CSAS) ensures the extraction of a more discriminative channel and spatial feature. The method is employed to eliminate the stripe noise in the vertical and horizontal directions, respectively, while preserving the edge texture information of the image. The experimental results show that the proposed method outperforms four state-of-the-art methods by a large margin in terms of the qualitative and quantitative assessments. One hundred infrared images with different simulated noise intensities are applied to verify the performance of our method, and the result shows that the average peak signal-to-noise ratio and average structural similarity of the corrected image exceed 40.08 dB and 0.98, respectively.

Geohazard prevention and mitigation are highly complex and remain challenges for researchers and practitioners. Artificial intelligence (AI) has become an effective tool for addressing these challenges. Therefore, for decades, an increasing number of researchers have begun to conduct AI research in the field of geohazards leading to rapid growth in the number of related papers. This has made it difficult for researchers and practitioners to grasp information on cutting-edge developments in the field, thus necessitating a comprehensive review and analysis of the current state of development in the field. In this study, a comprehensive scientometric analysis appraising the state-of-the-art research for geohazard was performed based on 9226 scientometric records from the Web of Science core collection database. Multiple types of scientometric techniques, including coauthor analysis, co-citation analysis, and cluster analysis were employed to identify the most productive researchers, institutions, and hot research topics. The results show that research related to the application of AI in the field of geohazards experienced a period of rapid growth after 2000, with major developments in the field occurring in China, the United States, and Italy. The hot research topics in this field are ground motion, deep learning (DL), and landslides. The commonly used AI algorithms include DL, support vector machine (SVM), and decision tree (DT). The obtained visualization on research networks offers valuable insights and an in-depth understanding of the key researchers, institutions, fundamental articles, and salient topics through animated maps. We believe that this scientometric review offers useful reference points for early-stage researchers and provides valuable in-depth information to experienced researchers and practitioners in the field of geohazard research. This scientometric analysis and visualization are promising for reflecting the global picture of AI-based geohazard research comprehensively and possess potential for the visualization of the emerging trends in other research fields.

The purpose of this study was to investigate the effects of dietary Selenohomolanthionine (SeHLan) on antioxidant status and immune response in canine parvovirus (CPV) vaccinated puppies. In this study, 30 weaned puppies were randomly divided into six groups: control group (–Se/–Vacc), immunization group (–Se/+Vacc), supplementation of sodium selenite group (SS/+Vacc, 0.35 mg/kg DM), low-dose SeHLan group (SeHLan-L/+Vacc, 0.35 mg/kg DM), mid-dose SeHLan group (SeHLan-M/+Vacc, 1.0 mg/kg DM), and high-dose SeHLan group (SeHLan-H/+Vacc, 2.0 mg/kg DM). The puppies were fed for 42 days and vaccinated with Vanguard Plus 5 on day 0 and day 21. Blood samples were collected on 7, 14, 21, 28, 35, 42 days post-immunization (PI) for determination of antioxidant indicators, lymphocyte proliferation index, serum cytokine concentration (IL-2, IL-4), canine polymorphonuclear neutrophils (PMN) phagocytic function, and the level of CPV antibody titers. The results showed that SeHLan supplementation raised the serum Se concentration and glutathione peroxidase (GSH-Px) activity in a dose-dependent manner (P < 0.05). It also increased the activity of serum superoxide dismutase (SOD) and decreased serum malondialdehyde (MDA) content, especially in SeHLan-M/+Vacc group (1.0 mg/kg DM) (P < 0.01). SeHLan supplementation significantly increased lymphocyte proliferation, IL-2, and IL-4 levels in canine serum, and enhanced phagocytosis of PMN in vaccinated puppies (P < 0.05). Moreover, SeHLan supplementation shortened the CPV antibody production time and increased the CPV antibody titers (P < 0.05). Of note, the beneficial effects of SeHLan were superior to those of SS. In conclusion, dietary SeHLan supplementation improved antioxidant activity, increased CPV antibody titers, and enhanced immune function in puppies after weaning. An appropriate dosage of SeHLan (1~2 mg/kg DM) may confer nutritional benefits in puppies.

Blood perfusion is an important index for the function of the cardiovascular system and it can be indicated by the blood flow distribution in the vascular tree. As the blood flow in a vascular tree varies in a large range of scales and fractal analysis owns the ability to describe multi-scale properties, it is reasonable to apply fractal analysis to depict the blood flow distribution. The objective of this study is to establish fractal methods for analyzing the blood flow distribution which can be applied to real vascular trees. For this purpose, the modified methods in fractal geometry were applied and a special strategy was raised to make sure that these methods are applicable to an arbitrary vascular tree. The validation of the proposed methods on real arterial trees verified the ability of the produced parameters (fractal dimension and multifractal spectrum) in distinguishing the blood flow distribution under different physiological states. Furthermore, the physiological significance of the fractal parameters was investigated in two situations. For the first situation, the vascular tree was set as a perfect binary tree and the blood flow distribution was adjusted by the split ratio. As the split ratio of the vascular tree decreases, the fractal dimension decreases and the multifractal spectrum expands. The results indicate that both fractal parameters can quantify the degree of blood flow heterogeneity. While for the second situation, artificial vascular trees with different structures were constructed and the hemodynamics in these vascular trees was simulated. The results suggest that both the vascular structure and the blood flow distribution affect the fractal parameters for blood flow. The fractal dimension declares the integrated information about the heterogeneity of vascular structure and blood flow distribution. In contrast, the multifractal spectrum identifies the heterogeneity features in blood flow distribution or vascular structure by its width and height. The results verified that the proposed methods are capable of depicting the multi-scale features of the blood flow distribution in the vascular tree and further are potential for investigating vascular physiology.

AIM: To investigate the activation of autophagy in rat retina after optic nerve crush (ONC) and evaluate its relationship with apoptosis of retinal ganglion cells (RGCs). METHODS: The ONC model was established. Western blots were performed to investigate expression of p62, LC3 and Beclin-1. Transmission electron microscopy was performed to discover the autophagosomes in the retina after ONC. Immunohistochemistry was used to confirm the distribution of LC3. TUNEL was performed to confirm the relationship between autophagy and RGC apoptosis. RESULTS: p62/Beclin-1 ratio was declined shortly after ONC until to day 7 after ONC and then restored to a normal level at day 21. There was an opposite change in the LC3-II/LC3I ratio in the retina compared to the p62/Beclin-1 ratio. Increased autophagosomes were found after ONC using transmission electron microscopy, and most of the LC3-stained cells were colocalized with RGCs and Müller cells. More LC3-immunoreactive cells and apoptotic RGCs were found on day 7 following ONC. CONCLUSION: Possible activation of autophagy in RGCs after ONC; autophagy mainly occurred in RGCs and Müller cells, and the apoptosis of RGCs after ONC may be partly associated with autophagic activation.