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Abstract In areas where loess is distributed, landslides represent a significant geohazard with severe implications. Among these events, loess-mudstone landslides are particularly prevalent, posing substantial risks to the safety and property of local residents, and moisture plays a pivotal role as a key factor in causing these disasters. In this study, the hydraulic properties of the soils along the longitudinal section of an ongoing loess-mudstone landslide are investigated through the variation of soil water characteristic curves, which are subsequently fitted by utilizing van Genuchten model. Moreover, a comprehensive experimental investigation was conducted on the loess, mudstone, and loess-mudstone mixtures to facilitate analysis, including X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM) observation, particle size distribution (PSD) analysis, along with fundamental geotechnical tests for parameter determination. It is found that mudstone and loess have distinct SWCC distribution. The SWCC of loess at various depths exhibits a similar distribution pattern due to the occurrence of landslide. The SWCC distribution of loess-mudstone mixture displays a transitional trend between the SWCC of mudstone and that of loess, and the water retention capacity increases as the mudstone content increases. The experimental findings have demonstrated notable agreement between each other and exhibited a satisfactory level of concurrence with the observed phenomena in geological surveys.

In the context of the Fashion Apparel Industry 4.0, a transformative evolution is directed towards the Online Apparel Mass Customization (OAMC) strategy, which provides efficient and personalized apparel product solutions to consumers. A critical challenge within this customization process is the determination of sizes. While existing research addresses comfort evaluation in relation to wearer and garment fit, little attention has been given to how garment fit influences the wearer’s body image, which is also an important purchase consideration. This study investigates the impact of garment fit on the wearer’s body scale perception using quantitative research design. A digital dataset of avatars, clothed in varying sizes of T-shirts, were created for the body scale perception experiment, and an Artificial Neural Network (ANN) model was developed to predict the effect of T-shirt fit on body image. With only a small number of garments and body measurements as inputs, the ANN model can accurately predict the body scales of the clothed persons. It was found that the effect of apparel fit on body image varies depending on the wearer’s gender, body size, and shape. This model can be applied to enhance the online garment shopping experience with respect to personalized body image enhancement.

BackgroundHepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) is a syn-drome with a high short-term mortality rate, and its prognosis is critical in clinical management. This study aimed to investigate the clinical significance of glutathione peroxidase 4 (GPX4) in the occurrence and development of HBV-ACLF and its prognostic value for 90-day mortality.MethodsThe expression levels of GPX4, oxidative stress-related molecules and inflammatory cytokines in serum or peripheral blood mononuclear cells (PBMCs) of 289 participants were determined by RT-qPCR or ELISA, and the methylation level of GPX4 promoter in PBMCs was determined by MethyLight.ResultsThe expression levels of GPX4 in the PBMCs and serum of HBV-ACLF patients were lower than those in non-HBV-associated acute-on-chronic liver failure (non-HBV ACLF) patients, patients with chronic hepatitis B (CHB) and healthy control (HC) individuals, while the methylation level of the GPX4 promoter was greater. In HBV-ACLF patients, the methylation level of the GPX4 promoter is correlated with oxidative stress, inflammation-related molecules, and some clinicopathological indicators. The methylation level of the GPX4 promoter was identified as an independent risk factor for 90-day mortality in HBV-ACLF patients and yielded a larger area under the receiver operating characteristic curve (AUROC) than the model for end-stage liver disease (MELD) score in predicting 90-day mortality.ConclusionThe GPX4 promoter methylation level has promising potential as a predictor of 90-day mortality in patients with HBV-ACLF.

Abstract Surface modification is frequently used to solve the problems of low combustion properties and agglomeration for aluminum‐based fuels. However, due to the intrinsic incompatibility between the aluminum powder and the organic modifiers, the surface coating is usually uneven and disordered, which significantly deteriorates the uniformity and performances of the Al‐based fuels. Herein, a new approach of monolayer nano‐vesicular self‐assembly is proposed to prepare high‐performance Al fuels. Triblock copolymer G‐F‐G is produced by glycidyl azide polymer (GAP) and 2,2′‐(2,2,3,3,4,5,5‐Octafluorohexane‐1,6‐diyl) bis (oxirane) (fluoride) ring‐open addition reaction. By utilizing G‐F‐G vesicular self‐assembly in a special solvent, the nano‐sized vesicles are firmly adhered to the surface of Al powder through the long‐range attraction between the fluorine segments and Al. Meanwhile, the electrostatic repulsion between vesicles ensures an extremely thin coating thickness (≈15 nm), maintaining the monolayer coating structure. Nice ignition, combustion, anti‐agglomeration, and water‐proof properties of Al@G‐F‐G(DMF) are achieved, which are superior among the existing Al‐based fuels. The derived Al‐based fuel has excellent comprehensive properties, which can not only inspire the development of new‐generation energetic materials but also provide facile but exquisite strategies for exquisite surface nanostructure construction via ordered self‐assembly for many other applications.

Abstract Background Hepatitis B virus (HBV) infection is a public health problem that seriously threatens human health. This study aimed to investigate the clinical significance of glutathione peroxidase 4(GPX4) in the occurrence and development of chronic hepatitis B (CHB). Methods A total of 169 participants including 137 patients with CHB and 32 healthy controls (HCs) were recruited. We detected the expression of GPX4 and stimulator of interferon genes (STING) in peripheral blood mononuclear cells (PBMCs) by real-time quantitative polymerase chain reaction (RT-qPCR). The methylation level of GPX4 gene promoter in PBMCs was detected by TaqMan probe-based quantitative methylation-specific PCR (MethyLight). Enzyme-linked immunosorbent assay (ELISA) was performed to detect the serum levels of GPX4, IFN-β, oxidative stress (OS) related molecules, and pro-inflammatory cytokines. Results The expression levels of GPX4 in PBMCs and serum of CHB patients were lower than those of HCs, but the methylation levels of GPX4 promoter were higher than those of HCs, especially in patients at the immune tolerance phase. STING mRNA expression levels in PBMCs and serum IFN-β levels of patients at the immune activation phase and reactivation phase of CHB were higher than those at other clinical phases of CHB and HCs. GPX4 mRNA expression level and methylation level in PBMCs from patients with CHB had a certain correlation with STING and IFN-β expression levels. In addition, the methylation level of the GPX4 promoter in PBMCs from patients with CHB was correlated with molecules associated with OS and inflammation. Conclusions GPX4 may play an important role in the pathogenesis and immune tolerance of CHB, which may provide new ideas for the functional cure of CHB.

Abstract Extreme heat events caused by continuous anthropogenic climate change have been increasing. Establishing public cooling environments (PCEs) is imperative for protecting public health and enhancing productivity. Yet, disparities in access to PCEs based on race, travel behavior, and income status can undermine their role in helping communities cope with extreme heat. This study investigates the varied access to three types of PCEs across 40 U.S. counties. Our findings reveal that White people enjoy greater access to PCEs than other groups, especially to tree-covered green spaces (TCGSs), outperforming Black people approximately three times. Driving can disproportionately narrow the racial/ethnic inequality gap compared to walking. Non-expense-required public environments (NERPEs) and expense-required public environments (ERPEs) are less accessible to high-income groups. Our research underscores the ongoing challenges in achieving environmental justice through equitable PCE access and stresses the importance of further studies and policy actions to eliminate disparities.

Population migration has become a dominant force in shaping local demographic changes in the United States, surpassing natural growth rates. However, whether the migration pattern and the influential factor have distinctive disparities between hierarchical county pairs is still elusive. This study delves into the spatial diversity and driving forces behind migration patterns at the county level, with a particular focus on the disparities through an examination of migration levels and scales. We utilize county-pair-level migration data from the U.S. Census Bureau's American Community Survey to unveil the intricate network structure of population movement. Our findings reveal a pronounced spatial diversity in migration patterns, while cities witness a net influx of population, and in contrast to rural areas, majority of population inflow of cities primarily stems from metro areas. We employ Hierarchical Linear Models to analyze the impact of social connectedness, local wealthiness, and racial diversity on migration flows. The results highlight that cities with robust social networks, higher economic status, and balanced racial diversity are more attractive to migrants. Notably, the influence of racial diversity differences between origin and destination counties is found to be more significant in attracting migration compared to per capita income disparities. The findings offer valuable insights for policymakers and urban planners in managing demographic changes and addressing the challenges associated with migration-driven population redistribution. The study underscores the importance of considering social, economic, and racial factors in understanding and shaping migration patterns, with implications for regional development and social cohesion.

Microwave annealing, an emerging annealing method known for its efficiency and low thermal budget, has established a foundational research base in the annealing of molybdenum disulfide (MoS2) devices. Typically, to obtain high-quality MoS2 devices, mechanical exfoliation is commonly employed. This method’s challenge lies in achieving uniform film thickness, which limits the use of extensive data for studying the effects of microwave annealing on the MoS2 devices. In this experiment, we utilized a neural network approach based on the HSV (hue, saturation, value) color space to assist in distinguishing film thickness for the fabrication of numerous MoS2 devices with enhanced uniformity and consistency. This method allowed us to precisely assess the impact of microwave annealing on device performance. We discovered a relationship between the device’s electrical performance and the annealing power. By analyzing the statistical data of these electrical parameters, we identified the optimal annealing power for MoS2 devices as 700 W, providing insights and guidance for the microwave annealing process of two-dimensional materials.

Modern data centers provide the foundational infrastructure of cloud computing. Workload generation, which involves simulating or constructing tasks and transactions to replicate the actual resource usage patterns of real-world systems or applications, plays essential role for efficient resource management in these centers. Data center traces, rich in information about workload execution and resource utilization, are thus ideal data for workload generation. Traditional traces provide detailed temporal resource usage data to enable fine-grained workload generation. However, modern data centers tend to favor tracing statistical metrics to reduce overhead. Therefore the accurate reconstruction of temporal resource consumption without detailed, temporized trace information become a major challenge for trace-based workload generation. To address this challenge, we propose STWGEN, a novel method that leverages statistical trace data for workload generation. STWGEN is specifically designed to generate the batch task workloads based on Alibaba trace. STWGEN contains two key components: a suite of C program-based flexible workload building blocks and a heuristic strategy to assemble building blocks for workload generation. Both components are carefully designed to reproduce synthetic batch tasks that closely replicate the observed resource usage patterns in a representative data center. Experimental results demonstrate that STWGEN outperforms state-of-the-art workload generation methods as it emulates workload-level and machine-level resource usage in much higher accuracy.

The unloading effect by excavation may cause irreversible and severe damage to the surrounding rock masses in underground engineering. In this paper, both conventional triaxial compression (CTC) tests and triaxial unloading confining pressure (TUCP) tests were conducted on fine-grained granite to study its triaxial compression failure processes due to unloading. Based on the crack volumetric strain (CVS) method, the crack axial strain (CAS) method and crack radial area strain (CRAS) method were proposed to identify the failure precursor information (including stress thresholds and axial strain at the initiation point of crack connectivity stage) during the rock failure processes. The results of the CTC tests show that the stable crack development stress σsd, unstable crack development stress σusd, and crack connectivity stress σct identified by the CAS method are 6%, 74%–84%, and 86%–97% of the peak stress, respectively. For the TUCP cases, as the confining pressure increases, the stress thresholds, axial pressure at failure and axial strain at the start of the crack connectivity stage increase, while the time ratio of the crack connectivity stage to the entire unloading stage decreases. This indicates that fine-grained granite is prone to generate more cracks and leads to fail suddenly under high confining pressure. Furthermore, this new method demonstrates that the point at which the derivative of the radial crack area strain transitions from stable to a sudden increase or decrease is defined as the precursor point of rock failure. The results of axial strain at the starting point of the crack connectivity stage are very close to those predicted by the AE method, with β1 no more than 11%.

Elastic spherical polishing tools effectively conform to the polishing surface and exhibit high efficiency in the removal of materials, so they are extensively used in the sub-aperture polishing stages of optical components. However, their processing is often accompanied by significant mid-spatial frequency (MSF) errors, which critically degrade the performance of optical systems. To suppress the MSF errors generated during polishing with spherical tools, this study investigates the influence factor of MSF errors during the polishing process through an analysis of the convolution effect in material removal. A material removal profile model is established, and a uniform removal simulation is conducted to assess the influence of different shape material removal profiles on MSF errors. Simulation and experimental results show that a Gaussian-like shape material removal profile is more effective in suppressing the MSF errors during polishing compared to the “W” and trapezoidal shape material removal profiles. In addition, based on the characteristics of the RMS decreasing in a serrated trend with the decrease in path spacing, a path spacing optimization method considering the polishing efficiency is proposed to improve the polishing efficiency while controlling the MSF errors, and the effectiveness of the path spacing optimization method is verified by comparing the MSF error at the maximum theoretical path spacing and the path spacing that is less than this. Finally, the path spacing optimization method is used to polish single-crystal silicon to further illustrate its practicality.

The BeiDou Navigation Satellite System (BDS) has developed rapidly, and the combination of BDS Phase II (BDS-2) and BDS Phase III (BDS-3) has attracted wide attention. It is found that there are code ISBs between BDS-2 and BDS-3, which may have a certain impact on the BDS-2 and BDS-3 combined positioning. This paper focuses on the performance of BDS-2/BDS-3 combined B1I single-frequency pseudorange positioning and investigates the positioning performance with and without code ISBs correction for different types of receivers, include geodetic GNSS receivers and low-cost receivers. The results show the following: (1) For geodetic GNSS receivers, the code ISBs of each receiver is about −0.3 m to −0.8 m, and the position deviation is reduced by 7% after correcting code ISBs. The code ISBs in the baseline with homogeneous receivers has a little influence on the positioning result, which can be ignored. The code ISBs in the baseline with heterogeneous receivers is about −0.5 m, and the position deviation is reduced by 4% after correcting code ISBs. (2) The code ISBs in the low-cost receivers are significantly larger than those in the geodetic GNSS receivers, and the impact on the positioning performance of the low-cost receivers is significantly greater than that on the geodetic GNSS receivers. After correcting the code ISBs, the position deviation of low-cost receivers can be reduced by around 12% for both undifferenced and differenced modes. (3) For low-cost receivers, correcting the code ISBs can increase the number of epochs successfully solved, which effectively improves the low-cost navigation and positioning performance. (4) The carrier-phase-smoothing method can effectively reduce the distribution dispersion of code ISBs and make the estimation of ISBs more accurate. The STD values of estimated code ISBs in geodetic GNSS receivers are reduced by about 40% after carrier-phase smoothing, while the corresponding values are reduced by about 7% in low-cost receivers due to their poor carrier-phase observation quality.

Global navigation satellite system (GNSS) provides users with all-weather, continuous, high-precision positioning, navigation, and timing (PNT) services. In the operation and use of GNSS, the influence of the space environment is a factor that must be considered. For example, during geomagnetic storms, a series of changes in the Earth’s magnetosphere, ionosphere, and upper atmosphere affect GNSS’s positioning performance. To investigate the positioning performance of global satellite navigation systems during geomagnetic storms, this study selected three geomagnetic storm events that occurred from September to December 2023. Utilizing the global positioning system (GPS)/Beidou navigation satellite system (BDS) dual-system, kinematic precise point positioning (PPP) experiments were conducted, and the raw observational data from 100 stations worldwide was analyzed. The experimental results show that the positioning accuracy of some stations in high-latitude areas decreases significantly when using the conventional Geometry Free (GF) cycle-slip detection threshold during geomagnetic storms, which means that the GF is no longer applicable to high-precision positioning services. Meanwhile, there is no significant change in the satellite signal strengths received at the stations during the period of the decrease in positioning accuracy. Analyzing the cycle-slip rates for stations where abnormal accuracy occurred, it was observed that stations experiencing a significant decline in positioning accuracy exhibited serious cycle-slip misjudgments. To improve the kinematic PPP accuracy during magnetic storms, this paper proposes an adaptive threshold for cycle-slip detection and designs five experimental strategies. After using the GF adaptive threshold, the station positioning accuracy improved significantly. It achieved the accuracy level of the quiet period, while the cycle-slip incidence reached the average level. During magnetic storms, the ionosphere changes rapidly, and the use of the traditional GF constant threshold will cause serious cycle-slip misjudgments, which makes the dynamic accuracy in high latitude areas and some mid-latitude areas uncommon, while the use of the GF adaptive threshold can alleviate this phenomenon and improve the positioning accuracy in the high-latitude regions and some of the affected mid-latitude areas during the magnetic storms.

Fish-aggregating devices play a significant role in tuna purse fisheries. The severe marine environment and the large number of non-biodegradable fish-aggregating devices impact structural safety and cause marine litter. Therefore, hydrodynamic performance and the use of biodegradable materials are crucial issues for ensuring the sustainability of fish-aggregating devices. In this study, a type of virtual biodegradable drifting fish-aggregating device (Bio-DFAD) was designed. Numerical simulations were conducted to investigate the motion responses and relative velocities of Bio-DFADs in regular waves (first- and fifth-order waves). The numerical model was applied based on unsteady Reynolds-averaged Navier–Stokes equations with the realizable k–ε model. For different scenarios of modeling, various conditions were modeled, including the relative length, wave steepness, and diameter of the balsa wood, to analyze their effects on the hydrodynamic response of the Bio-DFADs. The results indicated that the increased relative length, wave steepness, and diameter of balsa wood had a significant influence on the motion response amplitude operators (RAOs) and relative velocity of Bio-DFADs. The results suggested that a relative length (LF/B = 1.5) and smaller diameter (DF = 30 mm) were recommended for fewer motion responses and relative velocity. The obtained results provide insight for practical engineering applications of the hydrodynamic design of Bio-DFADs.

The surface of molybdenum disulfide (MoS2) underwent oxygen plasma treatment to enhance its machinability and mitigate the tearing effects commonly associated with mechanical forces on 2D materials. This treatment led to the oxidation of the atoms on the top 1–3 layers of MoS2, resulting in the formation of MoO3 on the surface. During mechanical scanning probe lithography (m-SPL), only the surface oxide layer was uniformly removed, with material accumulation occurring predominantly on one side of the machined area. The resolution of the machining process was significantly enhanced via dynamic lithography while maintaining atomic-level smoothness in the machined area. Importantly, these techniques only removed the surface oxide layer, preserving the integrity of the underlying MoS2 surface, which was pivotal in avoiding damage to the original material structure. This study provided valuable insights and practical guidance for the nanofabrication of transition metal dichalcogenides (TMDCs) nanodevices, demonstrating a method to finely tune the machining of these materials.

To reveal the mechanism of rainfall- and irrigation-induced landslides in loess slopes within cold regions, a series of tests on loess samples subjected to different permeability durations were conducted, and the effects of rainfall on several performance indicators, including the permeability coefficient, composition, microstructure, soil–water characteristic curve, and the shear strength of the loess, were investigated. The results show that the permeability coefficient of the loess decreased by 68% after permeability testing. With increased permeability duration, there is a marked decrease in total dissolved solids, sand particles, and clay particles, contrasted with an increase in silt particles. This dynamic alters the original soil structure and impacts the soil–water characteristic curve of the loess. Additionally, rainwater infiltration heightens the effective saturation of the loess, in turn diminishing the shear strength of the loess as effective saturation increases. This reduction in shear strength is further intensified with extended infiltration time (or rainfall duration). A landslide is triggered once the shear strength diminishes to the level of the geostatic stress of the loess slope, and the influence of the rainfall-induced loss of soil shear strength should be taken into account during slope stability analysis. This study enhances the understanding of the initiation mechanisms of rainfall-induced landslides in loess slopes.

In the era of big data, unsupervised learning algorithms such as clustering are particularly prominent. In recent years, there have been significant advancements in clustering algorithm research. The Clustering by Density Peaks algorithm is known as Clustering by Fast Search and Find of Density Peaks (density peak clustering). This clustering algorithm, proposed in Science in 2014, automatically finds cluster centers. It is simple, efficient, does not require iterative computation, and is suitable for large-scale and high-dimensional data. However, DPC and most of its refinements have several drawbacks. The method primarily considers the overall structure of the data, often resulting in the oversight of many clusters. The choice of truncation distance affects the calculation of local density values, and varying dataset sizes may necessitate different computational methods, impacting the quality of clustering results. In addition, the initial assignment of labels can cause a ‘chain reaction’, i.e., if one data point is incorrectly labeled, it may lead to more subsequent data points being incorrectly labeled. In this paper, we propose an improved density peak clustering method, DPC-MS, which uses the mean-shift algorithm to find local density extremes, making the accuracy of the algorithm independent of the parameter dc. After finding the local density extreme points, the allocation strategy of the DPC algorithm is employed to assign the remaining points to appropriate local density extreme points, forming the final clusters. The robustness of this method in handling uncertain dataset sizes adds some application value, and several experiments were conducted on synthetic and real datasets to evaluate the performance of the proposed method. The results show that the proposed method outperforms some of the more recent methods in most cases.

The presence of nucleus-shaped anomalous regions in the power spectrum image of the electric field VLF frequency band has been discovered in previous studies. To detect and analyze these nucleus-shaped abnormal areas and improve the recognition rate of nucleus-shaped abnormal areas, this paper proposes a new nucleus-shaped abnormal area detection model ODM_Unet (Omni-dimensional Dynamic Mobile U-net) based on U-net network. Firstly, the power spectrum image data used for training is created and labeled to form a dataset of nucleus-shaped anomalous regions; Secondly, the ODConv (Omni-dimensional Dynamic Convolution) module with embedded attention mechanism was introduced to improve the encoder, extracting nucleus-shaped anomaly region information from four dimensions and focusing on the features of different input data; An SDI (Semantics and Detail Infusion) module is introduced between the encoder and decoder to solve the problem of detail semantic loss in high-level images caused by the reduction of downsampling image size; In the decoder stage, the SCSE (Spatial and Channel Squeeze-and-Excitation) attention module is introduced to more finely adjust the feature maps output through the SDI module. The experimental results show that compared with the current popular semantic segmentation algorithms, the ODM_Unet model has the best detection performance in nucleus-shaped anomaly areas. Using this model to detect data from November 2021 to October 2022, it was found that the frequency of nucleus-shaped anomaly areas is mostly between 0 and 12.5KHz, with geographic spatial distribution ranging from 40° to 70° south and north latitudes, and magnetic latitude spatial distribution ranging from 58° to 80° south and north latitudes. This method has reference significance for detecting other types of spatial electromagnetic field disturbances. [ABSTRACT FROM AUTHOR]

Background: The prognostic value of carbohydrate antigen 19-9 (CA19-9) is known to be affected by elevated bilirubin levels in patients with gallbladder carcinoma (GBC). The clinical significance of changes in the ratio of CA19-9 levels to total bilirubin (TB) levels in patients with GBC after curative-intent resection remains unknown. The aim of this study was to determine the prognostic value of changes in preoperative and postoperative CA19-9/TB ratio in these patients. Methods: Prospectively collected data on consecutive patients who underwent curative-intent resection for GBC between January 2015 and December 2020 stored in a multicenter database from 10 hospitals were analyzed in this retrospective cohort study. Based on the adjusted CA19-9 defined as the ratio of CA19-9 to TB, and using 2 × 103 U/µmol as the upper normal value, patients were divided into a normal group (with normal preoperative and postoperative adjusted CA19-9), a normalization group (with abnormal preoperative but normal postoperative adjusted CA19-9), and a non-normalization group (with abnormal postoperative adjusted CA19-9). The primary outcomes were overall survival (OS) and recurrence-free survival (RFS). The log-rank test was used to compare OS and RFS among the groups. The Cox regression model was used to determine factors independently associated with OS and RFS. Results: The normal group (n= 179 patients) and the normalization group (n= 73 patients) had better OS and RFS than the nonnormalization group (n =65 patients) (the 3-year OS rates 72.0%, 58.4% and 24.2%, respectively; the RFS rates 54.5%, 25.5% and 11.8%, respectively; both P<0.001). There were no significant differences between the normal and the normalization groups in OS and RFS (OS, P =0.255; RFS, P =0.130). Cox regression analysis confirmed that the non-normalization group was independently associated with worse OS and RFS. Subgroup analysis revealed that the non-normalization group of patients who received adjuvant therapy had significantly improved OS and RFS as compared to those who did not receive adjuvant therapy (OS, P =0.025; RFS, P =0.003). Conclusions: Patients with GBC who underwent curative-intent surgical resection with postoperative abnormal levels of adjusted CA19-9 (the CA19-9/TB ratio) were associated with poorer long-term survival outcomes. Adjuvant therapy after surgery improved the long-term outcomes of these patients. [ABSTRACT FROM AUTHOR]

Abstract Alkaline hydrogen evolution reaction (HER) for scalable hydrogen production largely hinges on addressing the sluggish bubble‐involved kinetics on the traditional Ni‐based electrode, especially for ampere‐level current densities and beyond. Herein, 3D‐printed Ni‐based sulfide (3DPNS) electrodes with varying scaffolds are designed and fabricated. In situ observations at microscopic levels demonstrate that the bubble escape velocity increases with the number of hole sides (HS) in the scaffolds. Subsequently, we conduct multiphysics field simulations to illustrate that as the hole shapes transition from square, pentagon, and hexagon to circle, where a noticeable reduction in the bubble‐attached HS length and the pressure balance time around the bubbles results in a decrease in bubble size and an acceleration in the rate of bubble escape. Ultimately, the 3DPNS electrode with circular hole configurations exhibits the most favorable HER performance with an overpotential of 297 mV at the current density of up to 1000 mA cm−2 for 120 h. The present study highlights a scalable and effective electrode scaffold design that promotes low‐cost and low‐energy green hydrogen production through the ampere‐level alkaline HER.

Abstract Harmonic resonance is caused by harmonic source matching resonance frequency and presents the characteristics of decentralization and whole network in modern grids. The current resonance suppression methods mainly focus on reducing the harmonic source, and are suitable for single‐site and small‐scale grids. This paper presents a new method for suppressing parallel resonance at system level. The holistic harmonic resonance is suppressed by reducing the harmonic impedance. In addition, new resonances are prevented by weakening the coupling between resonance and non‐resonance frequencies. The resonance modal analysis and resonance frequency shift (RFS) are employed to optimize harmonic impedance. Simulation results indicate that the capacitance parameter has higher sensitivity and is theoretically more suitable for RFS. Considering the accuracy of modal frequency sensitivity, a variable‐limit genetic algorithm for iteration is proposed. The validity of the proposed method was verified using an IEEE 14‐bus test network.

Abstract Conducting polymer hydrogel can address the challenges of stricken biocompatibility and durability. Nevertheless, conventional conducting polymer hydrogels are often brittle and weak due to the intrinsic quality of the material, which exhibits viscoelasticity. This property may cause a delay in sensor response time due to hysteresis. To overcome these limitations, we have designed a wrinkle morphology three‐dimensional (3D) substrate using digital light processing technology and then followed by in situ polymerization to form interpenetrating polymer network hydrogels. This novel design results in a wrinkle morphology conducting polymer hydrogel elastomer with high precision and geometric freedom, as the size of the wrinkles can be controlled by adjusting the treating time. The wrinkle morphology on the conducting polymer hydrogel effectively reduces its viscoelasticity, leading to samples with quick response time, low hysteresis, stable cyclic performance, and remarkable resistance change. Simultaneously, the 3D gradient structure augmented the sensor's sensitivity under minimal stress while exhibiting consistent sensing performance. These properties indicate the potential of the conducting polymer hydrogel as a flexible sensor.

Abstract Background Cognitive frailty (CF) is currently a significant issue, and most of the associated factors discovered in current studies are not modifiable. Therefore, it is crucial to identify modifiable risk factors that can be targeted for interventions in patients with chronic heart failure (CHF). This study aimed to investigate the prevalence and modifiable risk factors of CF in CHF patients in China. Methods In this cross-sectional study, we sequentially enrolled patients diagnosed with CHF. CF served as the dependent variable, assessed through the Montreal Cognitive Assessment (MoCA) Scale and the FRAIL Scale. The independent variable questionnaire encompassed various components, including general demographic information, the Social Support Rating Scale (SSRS), the Simplified Nutrition Appetite Questionnaire (SNAQ), the Hamilton Depression Scale (HAMD), the Hamilton Anxiety Scale (HAMA), and the Minnesota Living with Heart Failure Questionnaire (MLHFQ). Logistic regression analysis was employed to identify independent factors contributing to CF. Results A total of 271 patients with CHF were included in the study. The overall prevalence of CF was found to be 49.4%, with 28.8% of patients exhibiting potentially reversible cognitive frailty and 20.7% showing reversible cognitive frailty. Among middle-young CHF patients, 10.7% had reversible cognitive frailty and 6.4% had potentially reversible cognitive frailty, with a prevalence of CF at 17.1%. Logistic regression analysis revealed that body mass index (OR = 0.826, 95%CI = 0.726–0.938), blood pressure level (OR = 2.323, 95%CI = 1.105–4.882), nutrition status (OR = 0.820, 95%CI = 0.671–0.979), and social support (OR = 0.745, 95%CI = 0.659–0.842) were independent factors associated with CF (p

Neonicotinoids (NEOs), a large class of organic compounds, are a type of commonly used pesticide for crop protection. Their uptake and accumulation in plants are prerequisites for their intra- and intercellular movements, transformation, and function. Understanding the molecular mechanisms that underpin NEO uptake by plants is crucial for effective application, which remains elusive. Here, we demonstrate that NEOs enter plant cells primarily through the transmembrane symplastic pathway and accumulate mainly in the cytosol. Two plasma membrane intrinsic proteins discovered in Brassica rapa, BraPIP1;1 and BraPIP2;1, were found to encode aquaporins (AQPs) that are highly permeable to NEOs in different plant species and facilitate NEO subcellular diffusion and accumulation. Their conserved transport function was further demonstrated in Xenopus laevis oocyte and yeast assays. BraPIP1;1 and BraPIP2;1 gene knockouts and interaction assays suggested that their proteins can form functional heterotetramers. Assessment of the potential of mean force indicated a negative correlation between NEO uptake and the energy barrier of BraPIP1;1 channels. This study shows that AQPs transport organic compounds with greater osmolarity than previously thought, providing new insight into the molecular mechanisms of organic compound uptake and facilitating innovations in systemic pesticides.

Abstract Thermophotovoltaic (TPV) technology converts heat into electricity using thermal radiation. Increasing operating temperature is a highly effective approach to improving the efficiency of TPV systems. However, most reported TPV selective emitters degrade rapidly via. oxidation as operating temperatures increase. To address this issue, replacing nanostructured oxide‐metal films with oxide–oxide films is a promising way to greatly limit oxidation, even under high‐temperature conditions. This study introduces new all‐oxide photonic crystal designs for high‐temperature stable TPV systems, overcoming limitations of metal phases and offering promising material choices. The designs utilize both yttria‐stabilized zirconia (YSZ)/MgO and CeO2/MgO combinations with a multilayer structure and stable high‐quality growth. Both designsexhibit positive optical dielectric constants with tunable reflectivity, measured via optical characterization. Thermal stability testing using in situ heating X‐ray diffraction (XRD) suggests high‐temperature stability (up to 1000 °C) of both YSZ/MgO and CeO2/MgO systems. The results demonstrate a new and promising approach to improve the high‐temperature stability of TPV systems, which can be extended to a wide range of material selection and potential designs.

Chronic non-specific neck pain (CNNP) poses a substantial health and economic burden in China. This study introduces a gamified motion-sensing health application framework to address the limitations of existing health applications. The gamified cervical spine somatic exercise application employs motion capture technology alongside the smartphone’s built-in sensors to simulate accurate somatic interactions. Controlled experiments and data analyses demonstrated that the application significantly outperformed traditional text and video interventions in relieving participants’ neck pain by increasing their average daily activity and compliance with the cervical spine exercise routine. The neck pain level of the participants is quantified by the Neck Disability Index (NDI). The results from the controlled experiments demonstrate that this gamified approach significantly decreases the Neck Disability Index (NDI) score from 1.54 to 1.24, highlighting its ability to alleviate neck pain and increase user compliance.

Cell fate is precisely modulated by complex but well-tuned molecular signaling networks, whose spatial and temporal dysregulation commonly leads to hazardous diseases. Biomolecular condensates (BCs), as a newly emerging type of biophysical assemblies, decipher the molecular codes bridging molecular behaviors, signaling axes, and clinical prognosis. Particularly, physical traits of BCs play an important role; however, a panoramic view from this perspective toward clinical practices remains lacking. In this review, we describe the most typical five physical traits of BCs, and comprehensively summarize their roles in molecular signaling axes and corresponding major determinants. Moreover, establishing the recent observed contribution of condensate physics on clinical therapeutics, we illustrate next-generation medical strategies by targeting condensate physics. Finally, the challenges and opportunities for future medical development along with the rapid scientific and technological advances are highlighted.

Maritime hazardous chemical transportation accidents have the characteristics of strong suddenness, wide influence, and great harm. To analyze the ability of a maritime hazardous chemical transportation system (MHCTS) to cope with sudden disturbance events, “resilience” is introduced into MHCTS safety research. The key to studying resilience is modeling its evolutionary process. Based on the dissipative structure theory, this study analyzes the entropy flow mechanism of MHCTS safety resilience evolution. Through a statistical analysis of 197 investigation reports on maritime hazardous chemical transportation accidents, the factors influencing the safety resilience of the MHCTS were determined. The entropy value and weight of each influencing factor were calculated using the entropy method and entropy weight method, respectively. Based on this, an entropy model of the safety resilience evolution of the MHCTS was established. The evolution process falls under four categories of disturbance strengths, which were simulated using the system dynamics method. The degree of contribution of absorptive, adaptive, and restorative capacities to the improvement of system safety resilience under four disturbance conditions and the sensitivity of each influencing factor to the absorptive, adaptive, and restorative capacities were analyzed. Based on the analyses, targeted resilience improvement strategies are proposed. The research results provide a theoretical reference for the study of safety resilience mechanisms and resilience management in the MHCTS.

The presence of nucleus-shaped anomalous regions in the power spectrum image of the electric field VLF frequency band has been discovered in previous studies. To detect and analyze these nucleus-shaped abnormal areas and improve the recognition rate of nucleus-shaped abnormal areas, this paper proposes a new nucleus-shaped abnormal area detection model ODM_Unet (Omni-dimensional Dynamic Mobile U-net) based on U-net network. Firstly, the power spectrum image data used for training is created and labeled to form a dataset of nucleus-shaped anomalous regions; Secondly, the ODConv (Omni-dimensional Dynamic Convolution) module with embedded attention mechanism was introduced to improve the encoder, extracting nucleus-shaped anomaly region information from four dimensions and focusing on the features of different input data; An SDI (Semantics and Detail Infusion) module is introduced between the encoder and decoder to solve the problem of detail semantic loss in high-level images caused by the reduction of downsampling image size; In the decoder stage, the SCSE (Spatial and Channel Squeeze-and-Excitation) attention module is introduced to more finely adjust the feature maps output through the SDI module. The experimental results show that compared with the current popular semantic segmentation algorithms, the ODM_Unet model has the best detection performance in nucleus-shaped anomaly areas. Using this model to detect data from November 2021 to October 2022, it was found that the frequency of nucleus-shaped anomaly areas is mostly between 0 and 12.5KHz, with geographic spatial distribution ranging from 40° to 70° south and north latitudes, and magnetic latitude spatial distribution ranging from 58° to 80° south and north latitudes. This method has reference significance for detecting other types of spatial electromagnetic field disturbances.

Objective: To investigate the clinical and genetic characteristics of a male carrier of exceptional complex chromosome rearrangement (CCR) and the outcome of preimplantation genetic testing for chromosomal structural rearrangement (PGT-SR)., Methods: Using the modified high resolution G banding technique and whole-genome low-coverage sequencing (WGLCS), we analyzed the cellular karyotype and molecular karyotype of a male carrier of CCR, performed an analysis of the single-sperm chromosome copy number and conducted PGT-SR for the patient by next-generation sequencing (NGS). In addition, we reviewed the literature on reported male carriers of CCRs and summarized their normal/balanced sperm ratios and PGT-SR outcomes., Results: The karyotype of the patient was 46,XY,der(5)inv(5)(q14.3q23.2)t(5;14;11) (q23.2;q31.1;q21),der(11)t(5;14;11);der(14)t(5;14;11), with the translocation breakpoints located in the intergenic region. Single-sperm sequencing revealed 20.0%（7/35）of normal haploids in the male's spermatozoa， and the results PGT-SR showed a proportion of 25.0%（4/16）of normal/balanced embryos. After thawing and transferring of 2 euploid blastocysts, a healthy male infant was successfully delivered., Conclusion: The proportion of normal haploids in the spermatozoa of male CCR carriers may be higher than theoretically predicted, and PGT-SR can effectively improve the pregnancy outcome in male CCR carriers and provide valuable data for genetic counseling.