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Abstract This paper focuses on the online anti-epidemic resource allocation between demanders and suppliers considering the epidemic spatial spread. The spatial crowdsourcing with sharing platform is an effective way for anti-epidemic resource allocation, and a reasonable online matching strategy can improve the efficiency of resource utilization. The paper proposes online matching heuristic strategy (HSTRF-LRLUF strategy) and designs an online batch bilateral matching algorithm for anti-epidemic resources, which considers the impact of grid spatial aggregation and diffusion risk of emerging infectious diseases. The population distribution within grids and the commuting patterns between grids can provide decision support for selecting online matching strategies of anti-epidemic resources. A larger matching time window focusing on the spatial transmission risk (TR) of the epidemic can obtain better matching results. However, with a smaller matching time window, the decision makers can focus on spatial agglomeration risk (OR) or spatial diffusion risk (IR). The paper effectively combines the spatial crowdsourcing model with the anti-epidemic resource allocation to achieve the allocation of emergency resources to individuals. A combined anti-epidemic resource online matching heuristic strategies is designed from the spatial agglomeration risk and the spatial diffusion risk. Decision makers can dynamically adjust the online matching strategies of anti-epidemic resources by evaluating the spatial agglomeration risk, the spatial diffusion risk, and the overall spatial transmission risk based on the real-time spread of the epidemic and the supply of anti-epidemic resources.

Abstract Aims The value of the systemic immune‐inflammatory index (SII) in assessing adverse outcomes in various cardiovascular diseases has been extensively discussed. This study aims to evaluate the predictive value and risk stratification ability of SII for 30 day mortality in patients with acute decompensated heart failure (ADHF). Methods This analysis included 1452 patients hospitalized for ADHF, all the participants being part of the China Jiangxi‐acute decompensated heart failure1 project. The risk stratification capability of the SII in patients with ADHF, as well as its correlation with the 30 day mortality risk among ADHF patients, was evaluated utilizing Kaplan–Meier survival analysis and multivariable Cox regression models. A restricted cubic spline was employed to model the dose–response relationship between the two, and the receiver operating characteristic curve was utilized to assess the predictive ability of SII for 30 day mortality. Results The Kaplan–Meier analysis revealed that the risk of mortality in the high SII group (SII ≥ 980 × 109/L) was significantly greater than that in the low SII group (SII

Abstract Influenza virus infection remains a major global health problem and requires a universal vaccine with broad protection against different subtypes as well as a rapid-response vaccine to provide immediate protection in the event of an epidemic outbreak. Here, we show that intranasal administration of probiotic Escherichia coli Nissle 1917 activates innate immunity in the respiratory tract and provides immediate protection against influenza virus infection within 1 day. Based on this vehicle, a recombinant strain is engineered to express and secret five tandem repeats of the extracellular domain of matrix protein 2 from different influenza virus subtypes. Intranasal vaccination with this strain induces durable humoral and mucosal responses in the respiratory tract, and provides broad protection against the lethal challenge of divergent influenza viruses in female BALB/c mice. Our findings highlight a promising delivery platform for developing mucosal vaccines that provide immediate and sustained protection against respiratory pathogens.

The Qingkou landslide in Wulong, Chongqing, has developed on an inclined thick abrupt cliff, with a large area of goaf formed due to hundreds of years of coal mining below. Based on the analysis of the geological conditions, current goaf situation, and deformation characteristics of the mountain, it is identified that the landslide exhibits both bending-tension and sideslip deformations, suggesting a bending-sideslip failure mode. The deformation history of the mountain is examined, and the deformation characteristics of the landslide are analyzed in two stages: bending deformation and sideslipping deformation. Change in the rock surface occurrence are studied accordingly. Considering the combination relationship between bedding and the free face, the mountain failure is divided into bending-tension failure, wedge failure and plane-sliding failure. Criteria for each failure stage are established, revealing the evolution rules and formation mechanism of the bending-sideslip landslide. This study provides a scientific basis for the disaster prevention and mitigation of such landslides.

Objective: Presentation of a novel case of a patient with Hb Bart's hydrops fetalis, which was accurately identified by SMRT sequencing leading to expand the mutation spectrum of α-thalassemia. Case report: A 26-year-old pregnant woman and her husband underwent molecular analysis of thalassemia due to abnormal hematological results. The molecular analysis showed that the pregnant woman carried -α3.7/--SEA, while her husband exhibited a negative result. Accordingly, the pregnant woman continued the pregnancy until the 19-week gestational age. She was subsequently referred to our department for genetic counseling due to abnormal ultrasound findings in the fetus. A novel deletional α-thal mutation was detected for the husband by MLPA, and the precise location of the mutation was determined through SMRT sequencing, which revealed a 45.2 kb deletion. Later, an interventional umbilical cord blood puncture was offered for the pregnant woman. The cord blood was subjected to capillary electrophoresis, which revealed apparent Hb Bart's and Hb Portland peaks associated with Hb Bart's hydrops fetalis syndrome. Conclusion: It is imperative that Hb Bart's hydrops fetalis syndrome be diagnosed with the utmost expediency. If results of molecular analysis are not consistent with the clinical hematological findings, the presence of a novel thalassemia could be suspected. To identify the novel genotype, the SMRT sequencing represents an effective method for achieving an accurate diagnosis.

Study region: The Ganjiang River Basin, China Study focus: Parameter calibration is crucial for the accurate and reliable operation of hydrological models. Traditional methods face challenges in calibrating spatially heterogeneous parameters of distributed hydrological models, and existing multi-variable calibration strategies often fall short in comprehensively improving model performance, particularly in streamflow simulations. To address these challenges, this study proposes a multi-objective calibration framework that integrates observed streamflow data and satellite-based evapotranspiration (ET) data. The spatiotemporal information of the merged ET is utilized to calibrate six hydrological parameters of the Variable Infiltration Capacity (VIC) model at the grid scale, enhancing hydrological simulations for the Ganjiang River basin. New hydrological insights: Compared to the benchmark scheme based solely on streamflow, the proposed calibration framework improves simulations of area-average ET at the sub-basin scale and soil moisture content in the Ganjiang River basin, without compromising the accuracy of daily streamflow simulations. Additionally, notable enhancements are observed in monthly streamflow simulations. This study provides a promising and comprehensive calibration framework using satellite-based data to constrain parameters and enhance the performance of distributed hydrological models.

Mycoplasma gallisepticum (MG) is a pathogen that induces chronic respiratory illnesses in chickens, leading to tracheal and lung injury, and eliciting immune reactions that support sustained colonization. Baicalin, a compound found in scutellaria baicalensis, exhibits anti-inflammatory, antioxidant, and antibacterial properties. This study aimed to investigate the potential of baicalin in alleviating lung and cell damage caused by MG by restoring imbalances in M1/M2 and Th1/Th2 differentiation and to explore its underlying mechanism. In this research, a model for M1/M2 polarization induced by MG was initially developed. Specifically, infection with MG at a multiplicity of infection (MOI) of 400 for 6 h represented the M1 model, while infection for 10 h represented the M2 model. The polarization markers were subsequently validated using qRT-PCR, ELISA, and Western blot analysis. Baicalin disrupts the activation of M1 cells induced by MG and has the potential to restore the balance between M1 and M2 cells, thereby mitigating the inflammatory damage resulting from MG. Subsequent studies on MG-infected chickens detected imbalances in M1/M2 and Th1/Th2 differentiation in alveolar lavage fluid, as well as imbalances in macrophages and Th cells in the lung. The M1/Th1 model was exposed to MG for 5 d, while the M2/Th2 model was infected with MG for 7 d. The utilization of both light and electron transmission microscopes revealed that the administration of baicalin resulted in a reduction in the number of M1 cells, a decrease in cytoplasmic vacuoles, restoration of mitochondrial swelling and chromatin agglutination, as well as alleviation of alveolar rupture and inflammatory cell infiltration. Furthermore, baicalin restored MG-induced M1/M2 and Th1/Th2 imbalances and inhibited the phosphorylation of p38 and p65 proteins, thereby hindering the activation of the TLR4-p38 MAPK/NF-κB pathway. This study provides insights into the potential long-term effects of baicalin in MG infection and offers a theoretical basis for practical applications.

ABSTRACT: Dietary Macleaya cordata extract (MCE) can improve the meat quality of poultry. However, the specific mechanism by which MCE regulates the meat quality has not been clarified yet. Sanguinarine (SAN) is one of the important natural active components in MCE. Our study aims to explore the regulatory mechanism of dietary SAN supplementation on meat quality through transcriptomic and gut microbiome analysis, thereby providing a basis for regularing meat quality with MCE. 240 1-day-old broilers were divided into 4 groups according to different doses of SAN (0, 0.225, 0.75, and 2.25 mg/kg). The results indicated that SAN significantly improve the physicochemical quality indicators of breast and thigh muscle in broilers, improved the serum biochemical indexes. Through transcriptome sequencing analysis of the liver and ileum tissues of broilers, we found that the differentially expressed genes induced by SAN were mainly enriched in lipid metabolism, which were related to the peroxisome proliferator-activated receptor (PPAR) pathway. It reconfirmed that SAN can regulate lipid metabolism in the body by promoting the expression of genes related to cholesterol metabolism, fatty acid transport and oxidation by RT-PCR, this ultimately affects the physicochemical quality of muscle. Additionally, through 16S rRNA sequencing analysis, we found that dietary addition of SAN increased the relative abundance of Bacteroides, Lactobacillus and unclassified_f_Lachnospiraceae, while decreased the relative abundance of Alistipes in ceca. To further investigate the impact of gut microbiota on lipid metabolism, we conducted a correlation analysis of PPAR pathway factor expression in cecum tissue and microflora structure. The results showed that Bacteroides exhibited a positive correlation with the expression of most genes in the PPAR signaling pathway. Unclassified_f__Lachnospiraceae is positively correlated with PPARγ, Cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and Acyl-CoA synthetase long-chain family member 5 (ACSL5). In conclusion, dietary addition of SAN can promote the genes expression of the PPAR pathway, target the regulation of intestinal microflora structure and abundance and regulate lipid metabolism, thereby improving meat quality of broilers.

Background: Male breast cancer (MBC) is a rare disease. Although several large-scale studies have investigated MBC patients in other countries, the features of MBC patients in China have not been fully explored. This study aims to explore the features of Chinese MBC patients comprehensively. Methods: We retrospectively collected data of MBC patients from 36 centers in China. Overall survival (OS) was evaluated by the Kaplan-Meier method, log-rank test, and Cox regression analyses. Multivariate Cox analyses were used to identify independent prognostic factors of the patients. Results: In total, 1119 patients were included. The mean age at diagnosis was 60.9 years, and a significant extension over time was observed (P

ABSTRACT: Mycoplasma gallisepticum (MG) can cause chronic respiratory disease (CRD) in chickens, which has a significant negative economic impact on the global poultry sector. Respiratory flora is the guardian of respiratory health, and its disorder is closely related to respiratory immunity and respiratory diseases. As a common probiotic in the chicken respiratory tract, Lactobacillus salivarius (L. salivarius) has potential antioxidant, growth performance enhancing, and anti-immunosuppressive properties. However, the specific mechanism through which L. salivarius protects against MG infection has not yet been thoroughly examined. This study intends to investigate whether L. salivarius could reduce MG-induced tracheal inflammation by modulating the respiratory microbiota and metabolites. The results indicated that L. salivarius reduced MG colonization significantly and alleviated the anomalous morphological changes by using the MG-infection model. L. salivarius also reduced the level of Th1 cell cytokines, increased the level of Th2 cell cytokines, and ameliorated immune imbalance during MG infection. In addition, L. salivarius improved the mucosal barrier, heightened immune function, and suppressed the Janus kinase/Signal transducer, and activator of transcription (JAK/STAT) signaling pathway. Notably, MG infection changed the composition of the respiratory microbiota and metabolites, and L. salivarius therapy partially reversed the aberrant respiratory microbiota and metabolite composition. Our results highlighted that these findings demonstrated that L. salivarius played a role in MG-mediated inflammatory damage and demonstrated that L. salivarius, by altering the respiratory microbiota and metabolites, could successfully prevent MG-induced inflammatory injury in chicken trachea.

An efficient method was discovered for catalyzing the esterification under air using Novozym 435 to obtain pyridine esters. The following conditions were found to be optimal: 60 mg of Novozyme 435, 5.0 mL of n-hexane, a molar ratio of 2:1 for nicotinic acids (0.4 mmol) to alcohols (0.2 mmol), 0.25 g of molecular sieve 3A, a revolution speed of 150 rpm, a reaction temperature of 50 °C, and reaction time of 48 h. Under nine cycles of Novozym 435, the 80 % yield was consistently obtained. Optimum conditions were used to synthesize 23 pyridine esters, including five novel compounds. Among them, gas chromatography-mass spectrometry-olfactometry (GC-MS-O) showed phenethyl nicotinate (3g), (E)-hex-4-en-1-yl nicotinate (3m), and octyl nicotinate (3n) possessed strong aromas. Thermogravimetric analysis (TG) revealed that the compounds 3g, 3m and 3n exhibited stability at the specified temperature. This finding provides theoretical support for adding pyridine esters fragrance to high-temperature processed food.

Objectives: We aimed to investigate the continuous changes in respiratory virus epidemics in hospitalized children with lower respiratory tract infections (LRTIs) persisting from January 2019 to December 2022 in Wuhan, China. Methods: We retrospectively enrolled children with LRTIs admitted to the Wuhan Children's Hospital. Specimens were nasopharyngeal aspirates which had been collected and detected the following microorganisms with direct immunofluorescence: influenza virus types A and B, respiratory syncytial virus, parainfluenza virus types 1-3, and adenovirus. We also analyzed demographic data and laboratory test results. Results: A total of 22,660 patients were enrolled. The total virus detection rate in 2019, 2021, and 2022 significantly declined gradually (36.96% vs 29.47% vs 22.62%, P value < 0.001). All the detected viruses did not follow previously observed seasonal patterns during the COVID-19 pandemic. Children hospitalized for LRTIs were older during the COVID-19 pandemic in contrast to the pre-period, particularly notable in cases attributed to respiratory syncytial virus and parainfluenza virus type 3 infections. Conclusions: This work adds to our knowledge of the epidemiology characteristics of respiratory viruses spanning the COVID-19 pandemic among children with LRTIs. The circulation of respiratory viruses changed consistently, and active LRTI surveillance in children remains critical for defining the healthcare burden of respiratory viruses.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder with pathological features of β-amyloid (Aβ) and hyperphosphorylated tau protein accumulation in the brain, often accompanied by cognitive decline. So far, our understanding of the extent and role of adaptive immune responses in AD has been quite limited. T cells, as essential members of the adaptive immune system, exhibit quantitative and functional abnormalities in the brains of AD patients. Dysfunction of the blood-brain barrier (BBB) in AD is considered one of the factors leading to T cell infiltration. Moreover, the degree of neuronal loss in AD is correlated with the quantity of T cells. We first describe the differentiation and subset functions of peripheral T cells in AD patients and provide an overview of the key findings related to BBB dysfunction and how T cells infiltrate the brain parenchyma through the BBB. Furthermore, we emphasize the risk factors associated with AD, including Aβ, Tau protein, microglial cells, apolipoprotein E (ApoE), and neuroinflammation. We discuss their regulation of T cell activation and proliferation, as well as the connection between T cells, neurodegeneration, and cognitive decline. Understanding the innate immune response is crucial for providing comprehensive personalized therapeutic strategies for AD.

Summary: Directed self-assembly (DSA) lithography has demonstrated significant potential in fabricating integrated circuits. However, DSA encounters limited processing windows due to the requirement for precise matching between the period of block copolymers (BCPs) and graphoepitaxy templates. We propose a binary BCP/homopolymer blending strategy to manipulate the self-assembly behavior and the processing window of graphoepitaxy DSA in contact hole shrinking. By carefully tailoring the blending rates of poly(methyl methacrylate) (PMMA) with different molecular weights in cylindrical polystyrene-b-poly(methyl methacrylate) (PS-b-PMMA), we manipulate the period and morphology of BCP/homopolymer self-assembly. Specifically, we employ BCP/homopolymer blending to fine-tune the critical dimension (CD) of contact holes with PS-affined topographical templates. Subsequent pattern transferring is achieved by selectively etching defect-free shrinkable cylinders as hard masks. Furthermore, self-consistent field theory (SCFT) simulation was employed to explore the self-assembly of BCP/homopolymer blending in confined cylindrical space and the results were in good consistency with the experimental results.

Background: Primary insomnia (PI) refers to syndromes of difficulty falling asleep, poor sleep quality, early awakening, and difficulty falling asleep after waking up. Although there have been numerous studies, the specific etiology and pathogenesis of PI are still misunderstanding. In recent years, the gut microbiota has been proved to be involved in the metabolism of many mental disorders. But the specific mechanisms of its involvement in PI have not been fully elucidated. This study aims to explore the relationship between the gut microbiota and the symptoms, cognitive function changes in PI. Methods: In this study, the gut microbiota of PI patients and healthy controls was profiled by performing stool 16s rRNA gene sequencing. The co-occurrence network was constructed by using Weight Gene Co-expression Network Analysis (WGCNA) algorithm. The correlation between gut microbiota associated pathways and traits in PI were predicted. Results: WGCNA results demonstrated several Operational Taxonomic Units (OTU) modules are correlated to symptoms. By using PICRUSt2 software, we predicted the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of microbiota in modules. For instance, sleep efficiency may be correlated with the presence of Insulin signaling pathway, Flavonoid biosynthesis, Ascorbate and aldarate metabolism, Nitrotoluene degradation, Biotin metabolism, RNA polymerase and Chlorocyclohexane and chlorobenzene degradation. Total sleep time may be correlated with the presence of Tyrosine metabolism, Propanoate metabolism, Carbon fixation pathways in prokaryotes, Carotenoid biosynthesis, Systemic lupus erythematosus, Nitrotoluene degradation and Biosynthesis of unsaturated fatty acids. The severity of insomnia may be correlated with Insulin signaling pathway, Flavonoid biosynthesis, Ascorbate and aldarate metabolism, Nitrotoluene degradation, Biotin metabolism and RNA polymerase. Change of name score in Montreal Cognitive Assessment (MoCA) may be correlated with Tyrosine metabolism, Propanoate metabolism, Carbon fixation pathways in prokaryotes, Carotenoid biosynthesis, Systemic lupus erythematosus, Nitrotoluene degradation, Biosynthesis of unsaturated fatty acids, Apoptosis, Steroid hormone biosynthesis, Geraniol degradation, Protein digestion and absorption and Bisphenol degradation in Gut Microbiota (GM). Conclusion: This study revealed the potential relationships between gut microbiota and PI. By using pathway prediction and enrichment analysis, we concluded many metabolic pathways may associated with some important traits of insomnia patients, including sleep efficiency, severe insomnia, total sleep time and change of name score in MoCA. The metabolic pathways include Insulin signaling pathway, Flavonoid biosynthesis, Ascorbate and aldarate metabolism, Nitrotoluene degradation, Biotin metabolism, RNA polymerase and Chlorocyclohexane, chlorobenzene degradation, Tyrosine metabolism, Propanoate metabolism, Carbon fixation pathways in prokaryotes, Carotenoid biosynthesis, Systemic lupus erythematosus, Biosynthesis of unsaturated fatty acids, Apoptosis, Steroid hormone biosynthesis, Geraniol degradation, Protein digestion and absorption and Bisphenol degradation.Our study demonstrated that PI patients demonstrate significant changes in gut microbiota, which will help delineate the relationship between gut microbiota and syndromes of PI.

Due to the excellent results achieved by transformers in computer vision, more and more scholars have introduced transformers into the field of medical image segmentation. However, the use of transformers will make the model’s parameters very large, which occupies a large amount of the computer’s resources, making them very time-consuming during training. In order to alleviate this disadvantage, this paper explores a flexible and efficient search strategy that can find the best subnet from a continuous transformer network. The method is based on a learnable and uniform L1 sparsity constraint, which contains factors that reflect the global importance of the continuous search space in different dimensions, while the search process is simple and efficient, containing a single round of training. At the same time, in order to compensate for the loss of accuracy caused by the search, a pixel classification module is introduced into the model to compensate for the loss of accuracy in the model search process. Our experiments show that the model in this paper compresses 30% of the parameters and FLOPs used, while also showing a slight increase in the accuracy of the model on the Automatic Cardiac Diagnosis Challenge (ACDC) dataset.

Droughts present substantial challenges to agriculture, food security, and water resources. Employing a drought index based on soil moisture dynamics is a common and effective approach for agricultural drought monitoring. However, the precision of a drought index heavily relies on accurate soil moisture and soil hydraulic parameters. This study leverages remote sensing soil moisture data from the Climate Change Initiative (CCI) series products and model-generated soil moisture data from the Variable Infiltration Capacity (VIC) model. The extended triple collocation (ETC) method was applied to merge these datasets from 1992 to 2018, resulting in enhanced accuracy by 28% and 15% compared to the CCI and VIC soil moisture, respectively. Furthermore, this research establishes field capacity and a wilting point map using multiple soil datasets and pedotransfer functions, facilitating the development of an enhanced Soil Water Deficit Index (SWDI) based on merged soil moisture, field capacity, and wilting points. The findings reveal that the proposed enhanced SWDI achieves a higher accuracy in detecting agricultural drought events (probability of detection = 0.98) and quantifying their severity (matching index = 0.33) compared to an SWDI based on other soil moisture products. Moreover, the enhanced SWDI exhibits superior performance in representing drought-affected crop areas (correlation coefficient = 0.88), outperforming traditional drought indexes such as the Standardized Precipitation Index (correlation coefficient = 0.51), the Soil Moisture Anomaly Percent Index (correlation coefficient = 0.81), and the Soil Moisture Index (correlation coefficient = 0.83). The enhanced SWDI effectively captures the spatiotemporal dynamics of a drought, supporting more accurate agricultural drought monitoring and management strategies.

Abstract Despite that in-sensor processing has been proposed to remove the latency and energy consumption during the inevitable data transfer between spatial-separated sensors, memories and processors in traditional computer vision, its hardware implementation for artificial neural networks (ANNs) with all-in-one device arrays remains a challenge, especially for organic-based ANNs. With the advantages of biocompatibility, low cost, easy fabrication and flexibility, here we implement a self-powered in-sensor ANN using molecular ferroelectric (MF)-based photomemristor arrays. Tunable ferroelectric depolarization was intentionally introduced into the ANN, which enables reconfigurable conductance and photoresponse. Treating photoresponsivity as synaptic weight, the MF-based in-sensor ANN can operate analog convolutional computation, and successfully conduct perception and recognition of white-light letter images in experiments, with low processing energy consumption. Handwritten Chinese digits are also recognized and regressed by a large-scale array, demonstrating its scalability and potential for low-power processing and the applications in MF-based in-situ artificial retina.

Abstract Plasmaspheric hiss waves are important to shape the Earth’s electron radiation belt. These waves are commonly envisioned to have a long lifetime which allows them to permeate the global plasmasphere from a spatially restricted source. However, this hypothesis has not been experimentally confirmed yet, because of the challenging observational requirements in terms of location and timing. With wave and particle measurements from five magnetospheric satellites and detailed modeling, we present the first report of long lifetime (∼42 s) hiss rays in the substorm‐disturbed plasmasphere. The low‐frequency hiss waves are found to originate from the middle piece of the plasmaspheric plume, bounce between two hemispheres, and eventually drift into the plasmaspheric core. These hiss rays can travel through ∼3 hr magnetic local time and ∼4 magnetic shell. Such a long‐time and large‐scale permeation of hiss rays could benefit from the ducting process by plasmaspheric field‐aligned density irregularities.

Abstract Martian mini‐magnetospheres contain whistler‐mode chorus waves potentially contributing to atmospheric escape, analogous to the Earth's inner magnetosphere. At Earth, the chorus waves have been found to originate from the near‐equatorial region spanning approximately 2% of the entire magnetic field line length. However, because of the lack of wave Poynting flux measurements, the Martian chorus source region remains unclear. By comparing the frequency dependence between observed wave power and modeled linear growth rates, we present the first attempt to explore the chorus wave source distribution along the Martian mini‐magnetospheric field lines. Our data‐to‐model comparisons support that these waves are not generated by a single source tightly confined near the magnetic strength minimal location but by intermittent or continuous sources spanning up to 40% of the entire field line length. These results imply that the Martian mini‐magnetospheres could have more active energy transfer processes mediated by whistler‐mode chorus waves than the expectation.

Introduction: Early predictive pathological complete response (pCR) is beneficial for optimizing neoadjuvant chemotherapy (NAC) strategies for breast cancer. The hematoxylin and eosin (HE)-stained slices of biopsy tissues contain a large amount of information on tumor epithelial cells and stromal. The fusion of pathological image features and clinicopathological features is expected to build a model to predict pCR of NAC in breast cancer.Methods: We retrospectively collected a total of 440 breast cancer patients from three hospitals who underwent NAC. HE-stained slices of biopsy tissues were scanned to form whole-slide images (WSIs), and pathological images of representative regions of interest (ROI) of each WSI were selected at different magnifications. Based on several different deep learning models, we propose a novel feature extraction method on pathological images with different magnifications. Further, fused with clinicopathological features, a multimodal breast cancer NAC pCR prediction model based on a support vector machine (SVM) classifier was developed and validated with two additional validation cohorts (VCs).Results: Through experimental validation of several different deep learning models, we found that the breast cancer pCR prediction model based on the SVM classifier, which uses the VGG16 model for feature extraction of pathological images at ×20 magnification, has the best prediction efficacy. The area under the curve (AUC) of deep learning pathological model (DPM) were 0.79, 0.73, and 0.71 for TC, VC1, and VC2, respectively, all of which exceeded 0.70. The AUCs of clinical model (CM), a clinical prediction model established by using clinicopathological features, were 0.79 for TC, 0.73 for VC1, and 0.71 for VC2, respectively. The multimodal deep learning clinicopathological model (DPCM) established by fusing pathological images and clinicopathological features improved the AUC of TC from 0.79 to 0.84. The AUC of VC2 improved from 0.71 to 0.78.Conclusion: Our study reveals that pathological images of HE-stained slices of pre-NAC biopsy tissues can be used to build a pCR prediction model. Combining pathological images and clinicopathological features can further enhance the predictive efficacy of the model.

Block copolymer (BCP) self-assembly has tremendous potential applications in next-generation nanolithography. It offers significant advantages, including high resolution and cost-effectiveness, effectively overcoming the limitations associated with conventional optical lithography. In this work, we demonstrate a focused solar annealing (FSA) technique that is facile, eco-friendly, and energy-efficient for fast self-assembly of polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) thin films. The FSA principle involves utilizing a common biconvex lens to converge incident solar radiation into a high-temperature spot, which is directly used to drive the microphase separation of PS-b-PMMA thin films. As a result, PS-b-PMMA undergoes self-assembly, forming ordered nanostructures in a vertical orientation at seconds timescales on silicon substrates with a neutral layer. In addition, the FSA technique can be employed for grafting neutral polymer brushes onto the silicon substrate. Furthermore, the FSA's compatibility with graphoepitaxy-directed self-assembly (DSA) of BCP is also demonstrated in the patterning of contact holes. The results of contact hole shrinking show that contact hole prepatterns of ∼60.4 nm could be uniformly shrunk to ∼20.5 nm DSA hole patterns with a hole open yield (HOY) of 100 %. For contact hole multiplication, doublet DSA holes were successfully generated on elliptical templates, revealing an average DSA hole size of ∼21.3 nm. Most importantly, due to the direct use of solar energy, the FSA technique provides many significant advantages such as simplicity, environmental friendliness, solvent-free, low cost, and net-zero carbon emissions, and will open up a new direction for BCP lithography that is sustainable, pollution-free, and carbon-neutral.

The Mars Orbiter MAGnetometer (MOMAG) is a scientific instrument onboard the orbiter of China’s first mission for Mars — Tianwen-1. Since November 13, 2021, it has been recording magnetic field data from the solar wind to the magnetic pile-up region surrounding Mars. Here we present its in-flight performance and first science results, based on its first one and one-half months’ data. Comparing these early MOMAG observations to the magnetic field data in the solar wind from NASA’s Mars Atmosphere and Volatile EvolutioN (MAVEN) mission, we report that the MOMAG magnetic field data are at the same level in magnitude, and describe the same magnetic structures with similar variations in three components. We recognize 158 clear bow shock (BS) crossings in these MOMAG data; their locations match well statistically with the modeled average BS. We also identify and compare five pairs of datasets collected when Tianwen-1’s orbiter and the MAVEN probe made simultaneous BS crossings. These BS crossings confirm the global shape of modeled BS, as well as the south-north asymmetry of the Martian BS. Two cases presented in this paper suggest that the BS is probably more dynamic at flank than near the nose. So far, MOMAG performs well, and provides accurate magnetic field vectors. MOMAG is continuously scanning the magnetic field surrounding Mars. Data from MOMAG’s measurements complement data from MAVEN and will undoubt edly advance our understanding of the plasma environment of Mars.

As the energy density and efficiency requirements of air compressors continue to increase, gas foil thrust bearings face a high risk of thermal failure due to their elevated speed and limited cooling space. This paper proposes a novel structure for gas foil thrust bearings with enhanced thermal characteristics. A thermo-elastic–hydrodynamic model is developed using a thermal-fluid–solid interaction approach to investigate aerodynamic and thermal performance. The load capacity and thermal characteristics of nine different boundary angles are analyzed. The model is validated, and the actual characteristics of gas foil bearings with various boundary angles are examined using a test rig. The results indicate that, compared to conventional gas foil thrust bearings with a boundary angle of 0°, the new structure with a boundary angle ranging from −10° to −5° not only maintains the load carrying capacity but also improves thermal characteristics. Furthermore, this improvement becomes more pronounced with higher rotational speeds. Therefore, the proposed optimization is advantageous in reducing the risk of thermal failure.

Objective: This study aimed to provide clinical evidence for lineage replacement and genetic changes of High-Risk Human Papillomavirus (HR-HPV) during the period of vaccine coverage and characterize those changes in eastern China. Methods: This study consisted of two stages. A total of 90,583 patients visiting the Obstetrics and Gynecology Hospital of Fudan University from March 2018 to March 2022 were included in the HPV typing analysis. Another 1076 patients who tested positive for HPV31, 33, 52, or 58 from November 2020 to August 2023 were further included for HPV sequencing. Vaccination records, especially vaccine types and the third dose administration time, medical history, and cervical cytology samples were collected. Viral DNA sequencing was then conducted, followed by phylogenetic analysis and sequence alignment. Results: The overall proportion of HPV31 and 58 infections increased by 1.23% and 0.51%, respectively, while infection by HPV33 and 52 decreased by 0.42% and 1.43%, respectively, within the four-year vaccination coverage period. The proportion of HPV31 C lineage infections showed a 22.17% increase in the vaccinated group, while that of the HPV58 A2 sublineage showed a 12.96% increase. T267A and T274N in the F-G loop of HPV31 L1 protein, L150F in the D-E loop, and T375N in the H-I loop of HPV58 L1 protein were identified as high-frequency escape-related mutations. Conclusions: Differences in epidemic lineage changes and dominant mutation accumulation may result in a proportional difference in trends of HPV infection. New epidemic lineages and high-frequency escape-related mutations should be noted during the vaccine coverage period, and regional epidemic variants should be considered during the development of next-generation vaccines.

In this paper, the design of an atmospheric turbulence simulation system for free-space optical (FSO) communication is proposed. The system can accurately simulate repeatable atmospheric turbulent fading channels. It has a dynamic execution range of 30 dB with an execution rate of 1 MHz. The execution accuracy of the system is higher than 0.1 dB. In addition, the reliable TCP/IP protocol is used for communication, which ensures the convenience and versatility of the system. Experiments are carried out to investigate the performance of the system, and the results prove its superiority. Hence, the atmospheric turbulence simulation system can effectively simulate the influence of atmospheric turbulence channels on FSO communication systems.

Abstract An arc fault is the most common cause of charging pile fire. The series arc fault current is usually lower than the short‐circuit fault current and is challenging to detect, resulting in the inaction of the circuit breaker. Therefore, a method for detecting series arc faults of charging piles based on generalized Stockwell transform (GST) is proposed in this paper. First, an real time digital simulation system (RTDS)‐based charging pile arc experimental platform is constructed, and the point contact and the carbonization path arc fault current are measured. Then, the fault information is extracted using GST, and the 250‐Hz component is selected as the arc fault identification feature. On this basis, an improved sampling point selection method is proposed. Finally, multiple feature quantities are constructed as feature vectors, and the trained particle swarm optimization _support vector machine (PSO_SVM) is used for arc fault detection. The experimental results show that the accuracy rate reaches 98.75%; thus, the scheme proposed by this paper could detect the series arc fault current accurately and avoid the incorrect action of the circuit breaker.

Abstract The Martian bow shock stands as the first defense against the solar wind and shapes the Martian magnetosphere. Previous studies showed the correlation between the Martian bow shock location and solar wind parameters. Here we present direct evidence of solar wind effects on the Martian bow shock by analyzing Tianwen‐1 and MAVEN data. We examined three cases where Tianwen‐1 data show rapid oscillations of the bow shock, while MAVEN data record changes in solar wind plasma and magnetic field. The results indicate that the bow shock is rapidly compressed and then expanded during the dynamic pressure pulse in the solar wind, and is also oscillated during the IMF rotation. The superposition of variations in multiple solar wind parameters leads to more intensive bow shock oscillation. This study emphasizes the importance of joint observations by Tianwen‐1 and MAVEN for studying the real‐time response of the Martian magnetosphere to the solar wind.

The environment of the roadbed and pavement often has a significant impact on its dynamic performance. The stability of the strata in the Hilly Area is poor, and long-term complex environmental impacts will cause significant damage to the pavement. This article tests the dynamic response characteristics of semi rigid and inverted asphalt pavement through road load tests, and measures the humidity data of the roadbed during on-site rainfall. In addition, the variation of pore water pressure in the transition layer under the coupling effect of humidity and dynamic load was analyzed, revealing the influence of seasonal factors on the dynamic response of the pavement and roadbed. The test results indicate that the humidity inside the roadbed is greatly influenced by seasonal factors, and the humidity conditions of the roadbed and pavement vary significantly due to differences in measurement point depth, season, and rainfall. Graded crushed stone cushion is beneficial for improving the humidity conditions of the roadbed. The pore water pressure of the graded crushed stone transition layer did not show significant pore water reabsorption throughout the entire loading process. Meanwhile, the thickness of the surface layer and the magnitude of the load have a significant impact on the measurement of pore water pressure in the transition layer. The measured values of the dynamic response indicators of the pavement are greatly influenced by seasonal factors. The research in this article will provide theoretical and guiding significance for the dynamic response characteristics of pavement under the influence of multiple factors in the southwestern hilly area.

Abstract Magnetosonic waves inside and outside the plasmasphere differ statistically in occurrence rate, frequency, and intensity. How the density interface separates magnetosonic waves inside and outside the plasmasphere remains not fully understood. Here we report an experimental test made with the Van Allen Probes mission from the plasmaspheric plume through the low‐density channel to the plasmaspheric core. Our linear instability analysis and two‐dimensional full‐wave modeling support that the magnetosonic waves propagate from elsewhere to the channel, undergo reflection and transmission at the flanking plasmaspheric density interfaces and eventually exhibit drastic differences in intensity and frequency coverage between neighboring regions. Such a mesoscale (tens of wavelength wide) interface with a strong refractive index gradient allows the transformation of incident waves to surface waves and consequently filters waves in both frequency and orientation. This unexpected filtering pattern could commonly occur at the plasmaspheric boundary and eventually affect the global distribution of magnetosonic waves.

Agriculture generates ~83% of total US ammonia (NH3) emissions, potentially adversely impacting sensitive ecosystems through wet and dry deposition. Regions with intense livestock production, such as the dairy region of south-central Idaho, generate hotspots of NH3 emissions. Our objective was to measure the spatial and temporal variability of NH3 across this region and estimate its dry deposition. Ambient NH3 was measured using diffusive passive samplers at 8 sites in two transects across the region from 2018–2020. NH3 fluxes were estimated using the Surface Tiled Aerosol and Gaseous Exchange (STAGE) model. Peak NH3 concentrations were 4–5 times greater at a high-density dairy site compared to mixed agriculture/dairy or agricultural sites, and 26 times greater than non-agricultural sites with prominent seasonal trends driven by temperature. Annual estimated dry deposition rates in areas of intensive dairy production can approach 45 kg N ha−1 y−1, compared to −1 y−1 in natural landscapes. Our results suggest that the natural sagebrush steppe landscapes interspersed within and surrounding agricultural areas in southern Idaho receive NH3 dry deposition rates within and above the range of nitrogen critical loads for North American deserts. Finally, our results highlight a need for improved understanding of the role of soil processes in NH3 dry deposition to arid and sparsely vegetated natural ecosystems across the western US.

Plasmasphere is an upward extension of the ionosphere at low and middle latitudes along the closed magnetic field lines rooted in the Earth, where the trapped whistler-mode waves in the frequency range from tens to thousands of Hertz are named as plasmaspheric hiss. Since its discovery, plasmaspheric hiss has been considered an important plasma wave to drive the precipitation loss of the Van Allen radiation belt electrons. However, the origin of plasmaspheric hiss has long been under debate. There have been two classes of sources proposed for the plasmaspheric hiss: (1) background plasma noises inside the plasmasphere and (2) other plasma waves outside the plasmasphere. In 2012, the Van Allen Probes mission capable of measuring an enormous range of particles, fields and waves was launched, providing an unprecedented opportunity to investigate the origin of plasmaspheric hiss. Here we briefly review the progress on the internal sources of plasmaspheric hiss during the recent five years. It has been suggested the background plasma noises can be amplified to the plasmaspheric hiss by a combination of linear and nonlinear instabilities of energetic electrons. During geomagnetically active times, energetic electrons are transported from the magnetotail into the plasmaspheric body and plume. The linear growth rate of whistler-mode waves destabilized by these energetic electrons exhibits an analogous frequency-dependence to the observed hiss power spectral density. When the seed wave amplitude exceeds a threshold, the nonlinear instability can act and then amplify the seed wave to the observable level. Such internal sources could exist over a broad range of magnetic local times, radial distances, and other structures of the plasmasphere.

Aims: Gap junction intercellular communication (GJIC) in osteocytes is impaired by oxidative stress, which is associated with age-related bone loss. Ageing is accompanied by the accumulation of advanced oxidation protein products (AOPPs). However, it is still unknown whether AOPP accumulation is involved in the impairment of osteocytes’ GJIC. This study aims to investigate the effect of AOPP accumulation on osteocytes’ GJIC in aged male mice and its mechanism. Methods: Changes in AOPP levels, expression of connexin43 (Cx43), osteocyte network, and bone mass were detected in 18-month-old and three-month-old male mice. Cx43 expression, GJIC function, mitochondria membrane potential, reactive oxygen species (ROS) levels, and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation were detected in murine osteocyte-like cells (MLOY4 cells) treated with AOPPs. The Cx43 expression, osteocyte network, bone mass, and mechanical properties were detected in three-month-old mice treated with AOPPs for 12 weeks. Results: The AOPP levels were increased in aged mice and correlated with degeneration of osteocyte network, loss of bone mass, and decreased Cx43 expression. AOPP intervention induced NADPH oxidase activation and mitochondrial dysfunction, triggered ROS generation, reduced Cx43 expression, and ultimately impaired osteocytes’ GJIC, which were ameliorated by NADPH oxidase inhibitor apocynin, mitochondria-targeted superoxide dismutase mimetic (mito-TEMPO), and ROS scavenger N-acetyl cysteine. Chronic AOPP loading accelerated the degradation of osteocyte networks and decreased Cx43 expression, resulting in deterioration of bone mass and mechanical properties in vivo. Conclusion: Our study suggests that AOPP accumulation contributes to age-related impairment of GJIC in osteocytes of male mice, which may be part of the pathogenic mechanism responsible for bone loss during ageing. Cite this article: Bone Joint Res 2022;11(7):413–425.

Summary: Background: Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential for determining appropriate surgery strategy and guiding resection extent in breast cancer. However, a non-invasive tool to predict pCR accurately is lacking. Our study aims to develop ensemble learning models using longitudinal multiparametric MRI to predict pCR in breast cancer. Methods: From July 2015 to December 2021, we collected pre-NAC and post-NAC multiparametric MRI sequences per patient. We then extracted 14,676 radiomics and 4096 deep learning features and calculated additional delta-value features. In the primary cohort (n = 409), the inter-class correlation coefficient test, U-test, Boruta and the least absolute shrinkage and selection operator regression were used to select the most significant features for each subtype of breast cancer. Five machine learning classifiers were then developed to predict pCR accurately for each subtype. The ensemble learning strategy was used to integrate the single-modality models. The diagnostic performances of models were evaluated in the three external cohorts (n = 343, 170 and 340, respectively). Findings: A total of 1262 patients with breast cancer from four centers were enrolled in this study, and pCR rates were 10.6% (52/491), 54.3% (323/595) and 37.5% (66/176) in HR+/HER2−, HER2+ and TNBC subtype, respectively. Finally, 20, 15 and 13 features were selected to construct the machine learning models in HR+/HER2−, HER2+ and TNBC subtypes, respectively. The multi-Layer Perception (MLP) yields the best diagnostic performances in all subtypes. For the three subtypes, the stacking model integrating pre-, post- and delta-models yielded the highest AUCs of 0.959, 0.974 and 0.958 in the primary cohort, and AUCs of 0.882–0.908, 0.896–0.929 and 0.837–0.901 in the external validation cohorts, respectively. The stacking model had accuracies of 85.0%–88.9%, sensitivities of 80.0%–86.3%, and specificities of 87.4%–91.5% in the external validation cohorts. Interpretation: Our study established a novel tool to predict the responses of breast cancer to NAC and achieve excellent performance. The models could help to determine post-NAC surgery strategy for breast cancer. Funding: This study is supported by grants from the National Natural Science Foundation of China (82171898, 82103093), the Deng Feng project of high-level hospital construction (DFJHBF202109), the Guangdong Basic and Applied Basic Research Foundation (grant number, 2020A1515010346, 2022A1515012277), the Science and Technology Planning Project of Guangzhou City (202002030236), the Beijing Medical Award Foundation (YXJL-2020-0941-0758), and the Beijing Science and Technology Innovation Medical Development Foundation (KC2022-ZZ-0091-5). Funding sources were not involved in the study design, data collection, analysis and interpretation, writing of the report, or decision to submit the article for publication.

Study region: Yangtze River Basin, China Study focus: As agricultural drought originates from meteorological drought, exploring the propagation from meteorological to agricultural drought is an important step in providing early warning of agricultural drought. In this study, Standardized Precipitation Index (SPI) and Improved Soil Moisture Anomaly Percentage Index (ISMAPI) were adopted to indicate meteorological and agricultural droughts, respectively. The propagation time from meteorological drought to agricultural drought was identified, and probabilistic linkages between the two types of drought were investigated using the copula function and Bayesian network. New hydrological insights: The average propagation time from meteorological to agricultural drought in the Yangtze River Basin (YRB) is 48 d. The propagation times in the summer and autumn are shorter than those in the spring and winter. The occurrence probability of more serious agricultural drought gradually increases with meteorological drought intensity. Agricultural and meteorological drought events were matched using the proposed drought event-matching method. In the YRB, approximately 72.4% of meteorological drought events may translate into agricultural drought events. Generally, an agricultural drought event that has the same drought category as that of the given meteorological drought event is most likely to occur. Regional differences in drought propagation time and occurrence probability of agricultural drought may be related to variations in climatic conditions across regions.

Background: Glucose transporter 10 (GLUT10) is encoded by the SLC2A10 gene. Our recent investigations have shown that GLUT10 is not only involved in glucose metabolism but also involved in the body’s immune response to cancer cells. However, the role of GLUT10 in tumor prognosis and in tumor immunity has not been reported. Methods: We knocked down SLC2A10 and performed transcriptome sequencing to analyse the biological function of GLUT10 and found that GLUT10 may be involved in immune signaling. Then, we studied the expression level of SLC2A10 in cancers by the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. We also evaluated the prognostic potential of SLC2A10 in different cancers using the Kaplan‒Meier plotter database and PrognoScan online software. The correlations between SLC2A10 expression and immune infiltrates were analysed by TIMER. In addition, correlations between SLC2A10 expression and gene marker sets of immune infiltrates were analysed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). Immunofluorescence staining of cyclooxygenase-2 (COX-2) and GLUT10 in lung cancer tissue and adjacent tissue was performed to confirm our findings from the database research. Results: Knocking down SLC2A10 widely activated immune and inflammatory signaling. SLC2A10 was abnormally expressed in several tumors. The expression level of SLC2A10 was closely correlated with cancer prognosis. Low SLC2A10 expression was related to poorer prognosis and increased malignancy of lung cancer. Lung cancer patients with low expression of SLC2A10 have a much shorter median survival time than patients with high expression of SLC2A10. SLC2A10 expression is closely related to the infiltration of different types of immune cells, particularly macrophages. Both database research and lung cancer sample research revealed that GLUT10 might modulate immune cell infiltration via the COX-2 pathway. Conclusions: By transcriptome experiments, database studies, and human sample studies, we found that GLUT10 is a new immune signaling molecule involved in tumor immunity, especially in the immune cell infiltration of lung adenocarcinoma (LUAD). GLUT10 may modulate the immune cell infiltration of LUAD via the COX-2 pathway.

Abstract Background Despite significant survival improvement in human epidermal growth factor receptor 2 (HER2) blockade for HER2-positive breast cancer, resistance to anti-HER2 remains inevitable. Subsequent anti-HER2 with continuing trastuzumab beyond progression is acceptable with limited efficacy when other anti-HER2 treatment is unavailable. This single-arm, phase II study (SYSUCC-005) aimed to explore the efficacy of switching mode for HER2-positive refractory metastatic breast cancer. Methods Patients with HER2-positive metastatic breast cancer rapidly progressing during pre-trastuzumab from six hospitals in China were designed to switch to lapatinib 1,250 mg orally once per day continuously plus capecitabine (1,000 mg/m2 orally twice per day on days 1–14) or vinorelbine (25 mg/m2 intravenously once per day on days 1 and 8) of each 21-day cycle. The primary endpoint was progression-free survival (PFS). Results Between January 5, 2015 and May 31, 2020, 159 patients were eligible in this study. The median follow-up was 33.1 months, a median PFS of 8.5 months was achieved. Brain metastases (hazard ratio [HR] = 1.582, 95% confidence interval [CI] 1.019- 2.453, P = 0.041) and ≥ 2 metastatic sites (HR = 1.679, 95% CI 1.151–2.450, P = 0.007) were independent prognostic factors for PFS. The most common grade ≥ 3 adverse events were diarrhea (3.8%) and hand-foot syndrome (9.4%). Conclusion The switching mode showed predominant efficacy, which might be a prior therapeutic option over continuing mode in subsequent anti-HER2 therapy for patients with HER2-positive refractory metastatic breast cancer. Trial registration This trial was registered on ClinicalTrials.gov ( NCT02362958 ) on 13/02/2015.

This study focuses on thick top foil bearings (TTFBs), which can prevent top foil from sagging and significantly reduce the load capacity of gas foil bearings (GFBs). However, the limited research on the dynamic responses of TTFB-rotor systems has hindered their wide application of TTFBs with high load capacity. To address this, an integrated nonlinear dynamic model is developed to analyze the linear dynamic responses of a rigid rotor supported on TTFBs. The model incorporates time domain orbit simulation, considering unsteady Reynolds equations, foil deformation equations, thick top foil motion equations, and rotor motion equations. A symmetrical test rig is used to validate the model, and three types of TTFBs with different bump foil stiffness are tested, with experimental results aligning with the model predictions. This study also investigates the effects of nominal clearance, static load, and unbalance on TTFB-rotor systems. The results indicate that unbalance has minimal impact on subsynchronous vibrations. However, larger bump foil stiffness, increased normal clearance, and higher static load contribute to improved stability and higher maximum stable speed of the TTFB-rotor system. Moreover, other relevant parameters reducing the bearing attitude angle can further enhance the system’s stability.

In the ever-evolving fields of optoelectronics and photonics, the introduction of carefully designed micro-/nanostructures enables personalized customization of the electrical and optical properties of optoelectronic and photonic devices [...]

The performance of gas foil thrust bearings is critical to the successful design and operation of the high axial load rotatory machines that employ gas foil bearings. However, our understanding of gas foil thrust bearings remains incomplete. To enhance our understanding and predict the performance of gas foil thrust bearings, we have established a detailed three-dimensional thermo-elastic-hydrodynamic model of a gas foil thrust bearing based on a fluid-thermal-structure interaction approach in this study. To validate the accuracy of our model, a gas foil thrust bearing test rig was developed. Moreover, we present a numerical investigation of the influence of bump foil configurations on gas foil thrust bearing performance. The results show that the gas foil thrust bearing that fixes the bump foil at the trailing edge and splits the bump foil into several strips exhibits a 36.4% increase in load capacity compared to the gas foil thrust bearing that fixes a whole piece of bump foil at the leading edge. Fixing the bump foil at the trailing edge and splitting it into several strips effectively decreases power loss and reduces the risk of bearing thermal failure.

There is often obvious particle breakage for silica sand under high-stress, which will lead to the bearing capacity reduction and excessive settlement of the foundation. This paper focuses on the particle breakage characteristics of marine silica sand from the East China Sea under high-stress conditions. A series of conventional triaxial tests for silica sand, including consolidated drained (CD) and consolidated undrained (CU) shear tests, were conducted under the confining pressures in the range of 2–8 MPa to investigate the breakage rule during the shearing process. The developments of particle breakage index Br with axial strain ε1 and volumetric strain εv present hyperbolic and linear trends, respectively. A hyperbolic model was adopted to describe the relationship of Br and ε1 and the corresponding model parameters were obtained. The particle breakage index also has a good correlation with the input work per unit volume under various average stresses, regardless of the stress history. Furthermore, the relationship between the fractal dimension and the particle breakage was studied based on the particle size distribution curve. It is concluded that the fractal dimension increases in an up–convex hyperbolic trend with the increase of particle breakage index. The dividing radius for whether the silica sand particles exhibit the fractal features is determined as approximately 0.4 mm. This is anticipated to provide reference and supplementary test data for analyzing sand constitutive models/environments regarding particle crushing.

Droughts can lead to drought disasters, which have become one of the main natural disasters affecting the development of social economies and ecological environments around the world. Timely and effective drought process simulation and prediction based on atmospheric–hydrological coupling is crucial for drought prevention and resistance. The initial condition (IC) is one source causing uncertainty in drought process simulation and prediction, and the impacts are different with drought duration, basin size and region. Therefore, a quantitative method that measures the uncertainty caused by ICs on the drought process simulation in different climate zones is proposed in this study. In this study, the VIC (Variable Infiltration Capacity) model at a resolution of 0.05°, which is proven as an ideal model to reflect drought processes, was used as the hydrological model to obtain soil moisture. By analyzing the Soil Moisture Anomaly Percentage Index (SMAPI) error characteristics that were simulated based on different ICs, an uncertainty index for drought process simulation was constructed in different climate zones. It was found that with the development of a drought process, the uncertainty converges, and it decreases to within 10% after a drought occurs for 5 to 6 months, while it is less than 5% in the particular basin in a humid region. In climate transition zones, both the uncertainty and its decrease rate are greater than those in humid regions. Climate characteristics, as well as soil types and vegetation types, are fundamental factors that cause differences in drought process simulation and uncertainty changes. The precipitation and temperature distribution more obviously vary spatially and temporally, a greater uncertainty is caused by ICs. This quantitative method reveals the impact of ICs on drought process simulation in different climate regions and provides a basis for the further improvement of drought simulation and prediction based on atmospheric–hydrological coupling.

Abstract Pulse diagnosis is an irreplaceable part of traditional Chinese medical science. However, application of the traditional pulse monitoring method was restricted in the modernization of Chinese medical science since it was difficult to capture real signals and integrate obscure feelings with a modern data platform. Herein, a novel multichannel pulse monitoring platform based on traditional Chinese medical science pulse theory and wearable electronics was proposed. The pulse sensing platform simultaneously detected pulse conditions at three pulse positions (Chi, Cun, and Guan). These signals were fitted to smooth surfaces to enable 3-dimensional pulse mapping, which vividly revealed the shape of the pulse length and width and compensated for the shortcomings of traditional single-point pulse sensors. Moreover, the pulse sensing system could measure the pulse signals from different individuals with different conditions and distinguish the differences in pulse signals. In addition, this system could provide full information on the temporal and spatial dimensions of a person’s pulse waveform, which is similar to the true feelings of doctors’ fingertips. This innovative, cost-effective, easily designed pulse monitoring platform based on flexible pressure sensor arrays may provide novel applications in modernization of Chinese medical science or intelligent health care.

Ship detection in synthetic aperture radar (SAR) images is an important and challenging work in the field of image processing. Traditional detection algorithms usually rely on handmade features or predefined thresholds, the different performance is obtained with varying degrees of prior knowledge, and it is difficult to take advantage of big data. Recently, deep learning algorithms have found wide applications in ship detection from SAR images. However, due to the complex backgrounds and multiscale ships, it is hard for deep networks to extract representative target features, which limits the ship detection performance to a certain extent. In order to tackle the above problems, we propose an improved YOLOv4 (ImYOLOv4) based on attention mechanism. Firstly, to achieve the best trade-off between detection accuracy and speed, we adopt the off-the-shelf YOLOv4 as our basic framework because of its fast detection speed. Secondly, a thresholding attention module (TAM) is introduced to suppress the adverse effect of complex backgrounds and noises. Besides, we embed channel attention module (CAM) into improved BiFPN as the feature pyramid network (FPN) to better enhance the discrimination of the multiscale target features. Finally, the decoupled head with two parallel branches improves the performance of classification and regression. The proposed method is evaluated on public SAR dataset and the experimental results demonstrate that it has higher efficiency and feasibility than other mainstream methods, yielding the accuracy of 94.16% at intersection over union of 0.5 and 58.19% at intersection over union of 0.75.

We present two multipoint interplanetary coronal mass ejections (ICMEs) detected by the Tianwen-1 and Mars Atmosphere and Volatile Evolution spacecraft at Mars and the BepiColombo (0.56 au ∼0.67 au) upstream of Mars from 2021 December 5 to 31. This is the first time that BepiColombo is used as an upstream solar wind monitor ahead of Mars and that Tianwen-1 is used to investigate the magnetic field characteristics of ICMEs at Mars. The Heliospheric Upwind Extrapolation time model was used to connect the multiple in situ observations and the coronagraph observations from STEREO/SECCHI and SOHO/LASCO. The first fast coronal mass ejection event (∼761.2 km s ^−1 ), which erupted on December 4, impacted Mars centrally and grazed BepiColombo by its western flank. The ambient slow solar wind decelerated the west flank of the ICME, implying that the ICME event was significantly distorted by the solar wind structure. The second slow ICME event (∼390.7 km s ^−1 ) underwent an acceleration from its eruption to a distance within 0.69 au and then traveled with the constant velocity of the ambient solar wind. These findings highlight the importance of background solar wind in determining the interplanetary evolution and global morphology of ICMEs up to Mars distance. Observations from multiple locations are invaluable for space weather studies at Mars and merit more exploration in the future.

Planetary bow shocks noncollisionally dissipate the incident bulk flow energy of solar wind into some other forms. To what extent and how solar wind disturbances affect the energy dissipation processes at the bow shocks on different planets remain unclear. With the Chinese Tianwen-1 and American Mars Atmosphere and Volatile EvolutioN missions, we present the first observation of significant modifications by a solar wind stream interaction region to the Martian foreshock waves, which are an important energy dissipation product of the bow shock. After the stream interface hitting Mars, an unusual band of foreshock waves emerged, with a central frequency of ∼0.4 Hz and frequency width of ∼0.2 Hz. These waves exhibited highly distorted waveforms, with peak-to-peak amplitudes of 10–25 nT in contrast to a background magnetic field of 6–9 nT. They were approximately elliptically polarized with respect to the wavevector and propagated highly obliquely to the background magnetic field. These waves reported here differed greatly from the commonly known Martian foreshock “30 s waves” and “1 Hz waves,” but resembled, to some extent, the less frequently occurring terrestrial foreshock “3 s waves.” Our present findings may imply an unexpected energy dissipation pattern of the Martian bow shock to the disturbed solar wind, which needs further observational, theoretical, and numerical investigations.

The underlying surface parameters in the Budyko framework (such as parameter n in the Choudhury–Yang equation) are crucial for studying the relationship between precipitation, evapotranspiration, and runoff. It is important to accurately quantify the influence of climate and human activities on the evolution of underlying surface characteristic parameters. However, due to the spatiotemporal heterogeneity of underlying surface parameters, it is often difficult to accurately quantify these relationships. In this study, taking the Kuye River Basin located in the northern Loess Plateau as the research object, we first used trend analysis and non-linear regression methods to estimate the evolution characteristics of runoff and underlying surface parameter n. We then determined the contribution of runoff changes by using the elasticity coefficient method under the 9-year moving average window. The results showed that: 1) the Kuye River Basin runoff underwent a sudden change in 1997, and the complex human activities are the main reasons for the sharp runoff decrease. 2) In addition to precipitation and potential evapotranspiration, temperature changes will alter the basin’s underlying surface parameters, ultimately changing the runoff. Moreover, climate change first inhibited and then promoted the runoff reduction trend. 3) Human activities, represented by changes in vegetation coverage and coal mining, considerably influenced runoff evolution in Kuye River Basin. More importantly, the change of runoff in the Kuye River Basin caused by coal mining is approximately four times that of the normalized vegetation index. This study can improve the applicability of the Budyko framework in the Loess Plateau sub-basin and provide scientific guidance for water resource management.

Abstract Background Since December 2019, coronavirus disease 2019 (COVID‐19) has emerged as an international pandemic. COVID‐19 patients with myocardial injury might need special attention. However, an understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID‐19 patients. Methods This retrospective, single‐center study finally included 304 hospitalized COVID‐19 cases confirmed by real‐time reverse‐transcriptase polymerase chain reaction from January 11 to March 25, 2020. Myocardial injury was determined by serum high‐sensitivity troponin I (Hs‐TnI). The primary endpoint was COVID‐19‐associated mortality. Results Of 304 COVID‐19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID‐19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C‐reactive protein (CRP; median, 84.9 vs. 28.5 mg/L; p