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Abstract Traditional Proportional-Integral-Derivative (PID) control systems often encounter challenges related to nonlinearity and time-variability. Original dung beetle optimizer (DBO) offers fast convergence and strong local exploitation capabilities. However, they are limited by poor exploration capabilities, imbalance between exploration and exploitation phases, and insufficient precision in global search. This paper proposes a novel adaptive PID control algorithm based on enhanced dung beetle optimizer (EDBO) and back propagation neural network (BPNN). Firstly, the diversity of exploration is increased by incorporating a merit-oriented mechanism into the rolling behavior. Then, a sine learning factor is introduced to balance the global exploration and local exploitation capabilities. Additionally, a dynamic spiral search strategy and adaptive $$t$$ -distribution disturbance are presented to enhance search precision and global search capability. The BPNN is employed to fine-tune both PID and network parameters, leveraging its powerful generalization and learning ability to model nonlinear system dynamics. In the simplified motor experiments, the proposed controller achieved the lowest overshoot (0.5%) and the shortest response time (0.012 s), with a settling time of 0.02 s and a steady-state error of just 0.0010. In another set of experiments, the proposed controller recorded an overshoot and response time of 0.7% and 0.0010 s, across five DC motor tests. These results demonstrate the proposed adaptive PID control algorithm has superior performance in optimizing control system parameters, as well as improving system robustness and stability.

Highlights A novel gradient-layered architecture based on single-pore hollow lignin nanospheres (HLNPs)-intercalated MXene layers was created to fabricate highly stretchable (600%) and durable (1000 cycling) supercapacitor electrodes. The architecture reduced the overstacking of MXene, and the micro-chamber structure of HLNPs better utilized lignin’s pseudocapacitive property to improve ion and electron accessibility (specific capacitance reached 1273 mF cm−2). HLNPs enhanced mechanical durability and capacitive stability of the integrated wrinkled electrodes during the stretch-release cycling.

Abstract Although aberrant splicing events of genes are closely related to the development and progression of colorectal cancer (CRC), the mapping of abnormal splicing events, especially alternative splicing (AS) event types and the underlying effects, remain investigational. In the present study, we analyzed a public RNA-seq database (GSE138202) and identified 14,314 significant AS events in CRC patients compared to healthy individuals. Most of the key genes such as oncogenes involved in the development of CRC have different AS event types. Moreover, the results demonstrate that certain AS events may play a significant role in the functioning of key genes involved in splicing factors and microRNAs. Furthermore, we observed that the oncogene CDK4 in CRC tends to undergo exon 2 skipping AS events, resulting in a stronger tendency for protein expression to form complexes with CCND1, thereby inhibiting the cell cycle and weakening cell proliferation, while enhancing cell migration capability. These findings not only provide new insights into the mechanism of AS in regulating CRC, but also offers a theoretical basis for targeted splicing therapy in CRC.

ObjectiveThis paper aims to analyzes the shock response characteristics of a large-scale floating shock platform (LFSP) subjected to underwater explosion. MethodsThe acoustic-solid coupling approach is used as the basis for the numerical simulation. The validity of the calculation method used in this paper is verified by comparing the experimental data with simulation, and the shock response characteristics of the location of interest in the LFSP's inner bottm plating is investigated in terms of its longitudinal section distribution as well as the effects of changes in the horizontal distance to the blast source on the whole shock environment of LFSP's inner bottom structure, thereby the LFSP's shock response prediction formula is obtained by fitting method.ResultsThe results indicate that the shock response characteristics of the locations (i.e. outer and inner plates, longitudinal section in centre plane) distributed along the longitudinal section of the inner bottom structure are basically the same. The shock response amplitude of the front and back sides of the floating platform are small, while that of the middle is large. The shock responses of the outer and inner plates differ, and the spectral velocity of the inner plate is greater than that of the outer plate, while the spectral displacement of the outer plate is greater than that of the inner plate.ConclusionsThe measurement points within the inner bottom plating are excited so spikes appear in the shock spectral lines, resulting in the spectral velocity of the inner plate is higher than that of the outer plate. The horizontal distance of bottom plate to the blast source is smaller so the shock response is stronger, bringing about a greater spectral displacement of the outer plate than that of the inner plate.

Abstract Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

The wide performance variation and inability for destructive testing make accurately determining ancient brick mechanical properties crucial for assessing structural safety in ancient masonry. This paper uses multiscale modeling with microscopic finite element analysis to quantitatively assess ancient brick macroscopic stress–strain relationship and compressive strength based on microstructural characteristics. The basic parameters such as porosity, pore size distribution, mineral composition and volume ratio, and microstructure characteristics of ancient bricks were obtained by corresponding methods. The Mori-Tanaka homogenization theory was applied to derive a three-phase equivalent brick matrix using elastic moduli and Poisson’s ratios of quartz, kaolinite, and montmorillonite at the microscale. The Representative Volume Element model with pores was created based on this matrix and pores, integrating Drucker-Prager plastic damage for finite element analysis of ancient brick mechanical behavior. The results indicate that stress–strain curves from the multi-scale micromechanics model resemble macroscopic experimental curves and maintain consistent peak strength. This shows that combining microscopic testing with finite element simulation for analyzing the mechanical properties of ancient bricks is feasible, providing a new non-destructive means of obtaining these properties.

Abstract The effects of moisture and drying shrinkage can lead to uneven settlement, cracking, and other diseases in loess subgrade. The objective of this study was to investigate the effects of amide polymer (AP) on the permeability, mechanical properties and crack resistance of loess by orthogonal experiments. The basic properties of AP and the permeability, mechanical properties, and dry–wet variation properties of polymer-modified loess were tested, and a scale model verification and simulation analysis were conducted. In this paper, water migration in subgrade is regulated by improving the water sensitivity of loess. By reducing the variation range of subgrade water content, the stress accumulation in subgrade caused by water is weakened. The results show that the curing time and mechanical properties of AP are directly affected by the oxidant and reducing agent, and the mechanical properties of AP are compatible with the characteristics of loess. AP filled the grain gap and reduced the permeability of loess by 34.05–280.83%. The ductility of polymer-modified loess is significantly increased, and the strain of peak strength is increased by 17.21–126.36%. AP can regulate moisture change, reduce the surface tension between particles, and reduce stress concentration. The strength loss rate was reduced by 19.98–51.21% by enhancing the cracking resistance and weakening the strength loss caused by dry and wet cycling. The increase of upper layer moisture content in the scale model of polymer-modified loess subgrade is reduced by 31.38–36.11%.

Squall lines often produce extremely disastrous gales and play a crucial role in the safety of hytropower stations.This article explores a squall line event over the lower reaches of Jinsha River on June 4， 2016， which brought 13-level wind at the canyon of Baihetan Hytropower Station.This research detect the formation mechanism of this squall line from environmental conditions and medium-scale meteorology.The following conclusions are obtained： （1） Before the squall line arrived， the ground pressure dropped steadily by 9 hPa because of the low pressure， and the temperature of the canyon rises up above 14 ℃.As the squall line arrived， the pressure rises sharply with thunderstorm high pressure， and the temperature dropped more than 10 ℃.At the same time， the relative humidity reached as higher as 70%， accompanied by short-term precipitation.After the squall line left， the aforementioned meteorological elements restored to their original values.（2） Analysis on the synoptic scale circulation， we finds that Baihetan hytropower station located in the south of southwest vortex， which induced a wind convergence background at the low level.Meanwhile， the station lied in right side of the jet stream inlet at upper level， and strong vertical motion formed by the wind shear.As a result， the squall line to come into being.Furthermore， in the troposphere before the squall line， the atmospheric circulation displayed a dry-cold advection in the middle-upper level superimposed over a warm-wet advection and higher ground temperature in the lower levels， increasing the temperature lapse rate.t As a result， the strong static instability and convection accumulated， and the conditions were favorable for the squall line to live a long time.The analyses from vertical wind speed showed that the subsidence movement made the momentum spread down， and promoted the uplift in the front side of line， and a positive feedback effect developed， promoting a stable mechanism for the strong storm.（3） Radar of Zhaotong detection indicates that echo cell that greater than 30 dBZ aggregated costly into a band and embed with the strong echo cores of greater than 50 dBZ， as a cylindrical convective cloud of higher than 10 km.On the radical velocity field， the meso-scale convergence line coinciding with the banded strong echo， as well as MARC （Mid-Altitude Radial Convergence） characteristics of the mid-altitude radial convergence， were the trigger mechanism for the squall line.As the cloud structure of the storm， strong upward movement in front of the squall line leaded to the dome.As the squall line arrived， the echo core dropped rapidly， and the extreme gale of downburst formed， resulted the new convective monomers come in being along the canyon.

Plums (Prunus salicina and Prunus domestica) are prevalent in southwestern China, and have attracted interest owing to their delectable taste and exceptional nutritional properties. Therefore, this study aimed to investigate the nutritional and flavor properties of plum to improve its nutritional utilization. Specifically, we determined the soluble sugars, organic acids, and phenolic components in 86 accessions using high-performance liquid chromatography. Notably, glucose, fructose, malic, and quinic acids were the predominant sweetness and acidity in plums, with sucrose contributing more to the sweetness of the flesh than the peel. Moreover, The peel contains 5.5 fold more phenolics than flesh, epicatechin, gallic acid, and proanthocyanidins C1 and B2 were the primary sources of astringency. Correlation and principal component analyses showed eight core factors for plum flavor rating, and a specific rating criterion was established. Conclusively, these findings provide information on the integrated flavor evaluation criteria and for enhancing optimal breeding of plums.

The outbreak of COVID-19 causes a serious threat to human health and life around the world and puts enormous pressure on the healthcare system. The lockdown policy has effectively reduced the number of cases and suppressed the spread of the COVID-19 epidemic, but it also requires high social and economic costs. In this paper, we aim to use feedback control to help decision-makers establish lockdown policies, which can effectively constrain the spread of the COVID-19 pandemic with minimal financial loss. The time-dependent susceptible-infected-removed (SIR) model is used for the dynamics of the COVID-19 pandemic. The feedback control is based on a modified nonlinear active disturbance rejection controller (ADRC) that includes modified nonlinear extended state and nonlinear state error feedback with parameters tuned by particle swarm optimization, and the performances are compared with a well-known proportional-–integral–-derivative (PID) controller. The final simulation results show that the modified nonlinear ADRC has better performances and is more robust against uncertainties in the parameters of the epidemiological model.

ABSTRACTMeningococcal vaccination strategies in China are intricate, including multiple vaccines targeting different serogroups. The current National Immunization Program (NIP) includes two polysaccharide vaccines for serogroups A and C (MPV-A and MPV-AC), covering limited serogroups and requiring adaptation. This study aims to evaluate the cost-effectiveness of replacing the current strategy with alternative strategies utilizing non-NIP vaccines to inform policy decisions. From a societal perspective, a decision tree-Markov model was constructed to simulate the economic and health consequences of meningococcal disease in a 2019 birth cohort with four vaccination strategies. Epidemiology, vaccine efficacy, cost, and other parameters were derived from previous studies. We conducted sensitivity analyses to assess the robustness of the findings and explored prices for non-NIP vaccines that enable cost-effective strategies. Compared to the current strategy, alternative strategies using quadrivalent polysaccharide vaccine (MPV-4), bivalent conjugate vaccine (MCV-AC), and quadrivalent conjugate vaccine (MCV-4) could avoid 91, 286, and 455 more meningococcal cases. The ICERs were estimated at approximately $250 thousand/QALY, $450 thousand/QALY, and $1.5 million/QALY, all exceeding the threshold of three times GDP per capita. The alternative strategies were not cost-effective. However, if vaccine prices were reduced to $3.9 for MPV-4, $9.9 for MCV-AC, and $12 for MCV-4, the corresponding strategy would be cost-effective. The current meningococcal vaccination strategy in China could effectively prevent the disease at a low cost, but with limited serogroup coverage. Strategies using MPV-4, MCV-AC, or MCV-4 could increase health benefits at a substantial cost, and might become cost-effective if vaccine prices decrease.

Background: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy individuals, ignoring adding information from multiple sources and the changes in brain aging patterns after mild traumatic brain injury (mTBI) were still unclear. Methods: Here, we leveraged the structural data from a large, heterogeneous dataset (N = 1464) to implement an interpretable 3D combined CNN model for brain-age prediction. In addition, we also built an atlas-based occlusion analysis scheme with a fine-grained human Brainnetome Atlas to reveal the age-sstratified contributed brain regions for brain-age prediction in healthy controls (HCs) and mTBI patients. The correlations between brain predicted age gaps (brain-PAG) following mTBI and individual's cognitive impairment, as well as the level of plasma neurofilament light were also examined. Results: Our model utilized multiple 3D features derived from T1w data as inputs, and reduced the mean absolute error (MAE) of age prediction to 3.08 years and improved Pearson's r to 0.97 on 154 HCs. The strong generalizability of our model was also validated across different centers. Regions contributing the most significantly to brain age prediction were the caudate and thalamus for HCs and patients with mTBI, and the contributive regions were mostly located in the subcortical areas throughout the adult lifespan. The left hemisphere was confirmed to contribute more in brain age prediction throughout the adult lifespan. Our research showed that brain-PAG in mTBI patients was significantly higher than that in HCs in both acute and chronic phases. The increased brain-PAG in mTBI patients was also highly correlated with cognitive impairment and a higher level of plasma neurofilament light, a marker of neurodegeneration. The higher brain-PAG and its correlation with severe cognitive impairment showed a longitudinal and persistent nature in patients with follow-up examinations. Conclusion: We proposed an interpretable deep learning framework on a relatively large dataset to accurately predict brain age in both healthy individuals and mTBI patients. The interpretable analysis revealed that the caudate and thalamus became the most contributive role across the adult lifespan in both HCs and patients with mTBI. The left hemisphere contributed significantly to brain age prediction may enlighten us to be concerned about the lateralization of brain abnormality in neurological diseases in the future. The proposed interpretable deep learning framework might also provide hope for testing the performance of related drugs and treatments in the future.

Nano zero-valent iron (nZVI) acting as a high-cost disposable material in soil Cr(VI) remediation faces significant challenges due to its easily oxidizable nature and biological toxicity. In addressing this issue, the present study undertook the synthesis of a series of modified nZVI and combined the selected material with Cr(VI)-resistant filamentous fungus Penicillium oxalicum SL2 for real-site chromium pollution remediation. Adsorption experiments demonstrated that the inclusion of carboxymethyl cellulose (CMC) significantly enhanced the adsorption capacity of nZVI for Cr(VI) by 19.3% (from 73.25 to 87.4 mg/L), surpassing both biochar (37.42 mg/L) and bentonite modified nZVI (48.03 mg/L). Characterization results validated the successful synthesis of the nano composite material. Besides, oxidative stress analysis explained the unique detoxification effects of CMC on SL2, acting as a free radical scavenger and isolating layer. In real-sites soil remediation experiments, a low dosage (0.4% w/w) of nZVI/CMC@SL2 (CMC modified nZVI combined with SL2) exhibited an impressive reduction of over 99.5% in TCLP-Cr(VI) and completely transformed 18% of unstable Cr to stable forms. Notably, nZVI/CMC demonstrated its capability to facilitate SL2 colonization in highly contaminated soil and modulate the microbial community structure, enriching chromium-removing microorganisms. In summary, the synergistic system of nZVI/CMC@SL2 merges as a cost-effective and efficient approach for Cr(VI) reduction, providing meaningful insights for its application in the remediating contaminated site soils.

Abstract Eucalyptus was one of the most cultivated hardwood species worldwide, with rapid growth, good wood properties and a wide range of adaptability. Eucalyptus stem undergoes primary growth (longitudinal growth) followed by secondary growth (radial growth), which produces biomass that is an important source of energy worldwide. In order to better understand the genetic regulation of secondary growth in Eucalyptus grandis, Transcriptome analyses in stem segments along a developmental gradient from the third internode to the eleventh internode of E. grandis that spanned primary to secondary growth were carried out. 5,149 genes that were differentially expressed during stem development were identified. Combining the trend analysis by the Mfuzz method and the module-trait correlation analysis by the Weighted Gene Co-expression Network Analysis method, a total of 70 differentially expressed genes (DEGs) selected from 868 DEGs with high connectivity were found to be closely correlated with secondary growth. Results revealed that the differential expression of these DEGs suggests that they may involve in the primary growth or secondary growth. AP1, YAB2 TFs and EXP genes are highly expressed in the IN3, whereas NAC, MYB TFs are likely to be important for secondary growth. These results will expand our understanding of the complex molecular and cellular events of secondary growth and provide a foundation for future studies on wood formation in Eucalyptus.

Abstract Colorectal cancer (CRC) is a common malignancy worldwide. Angiogenesis and metastasis are the critical hallmarks of malignant tumor. Runt-related transcription factor 1 (RUNX1), an efficient transcription factor, facilitates CRC proliferation, metastasis and chemotherapy resistance. We aimed to investigate the RUNX1 mediated crosstalk between tumor cells and M2 polarized tumor associated macrophages (TAMs) in CRC, as well as its relationship with neoplastic angiogenesis. We found that RUNX1 recruited macrophages and induced M2 polarized TAMs in CRC by promoting the production of chemokine 2 (CCL2) and the activation of Hedgehog pathway. In addition, we found that the M2 macrophage-specific generated cytokine, platelet-derived growth factor (PDGF)-BB, promoted vessel formation both in vitro and vivo. PDGF-BB was also found to enhance the expression of RUNX1 in CRC cell lines, and promote its migration and invasion in vitro. A positive feedback loop of RUNX1 and PDGF-BB was thus formed. In conclusion, our data suggest that RUNX1 promotes CRC angiogenesis by regulating M2 macrophages during the complex crosstalk between tumor cells and TAMs. This observation provides a potential combined therapy strategy targeting RUNX1 and TAMs-related PDGF-BB in CRC.

With the increasing penetration of wind and solar energies, the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems. A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations. Multiple types of system components, including demand response service entities, converter stations, DC transmission systems, cascade hydropower stations, and other traditional components, have been extensively modeled. Moreover, energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence. Demand-response service entities from the load side are used to reduce and move the demand during peak load periods. The uncertainties in wind, solar energy, and loads were simulated using stochastic programming. Finally, the effectiveness of the proposed model is verified through numerical simulations.

Wireless hierarchical federated learning (WHFL) is an implementation of wireless federated Learning (WFL) on a cloud–edge–client hierarchical architecture that accelerates model training and achieves more favorable trade-offs between communication and computation. However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. In this paper, we propose a secure finite block-length (FBL) approach for the multi-antenna URLLC-WHFL, and characterize the relationship between privacy, utility, and PLS of the proposed scheme. Simulation results show that when the eavesdropper’s CSI is perfectly known by the edge server, our proposed FBL approach not only almost achieves perfect secrecy but also does not affect learning performance, and further shows the robustness of our schemes against imperfect CSI of the eavesdropper’s channel. This paper provides a new method for the URLLC-WHFL in the presence of PLS.

The inverse model based multi-objective evolutionary algorithm (IM-MOEA) generates offspring by establishing probabilistic models and sampling by the model, which is a new computing schema to replace crossover in MOEAs. In this paper, an active learning Gaussian modeling based multi-objective evolutionary algorithm using population guided weight vector evolution strategy (ALGM-MOEA) is proposed. To properly cope with multi-objective problems with different shapes of Pareto front (PF), a novel population guided weight vector evolution strategy is proposed to dynamically adjust search directions according to the distribution of generated PF. Moreover, in order to enhance the search efficiency and prediction accuracy, an active learning based training sample selection method is designed to build Gaussian process based inverse models, which chooses individuals with the maximum amount of information to effectively enhance the prediction accuracy of the inverse model. The experimental results demonstrate the competitiveness of the proposed ALGM-MOEA on benchmark problems with various shapes of Pareto front.

Abstract Bacterial σI factors of the σ70-family are widespread in Bacilli and Clostridia and are involved in the heat shock response, iron metabolism, virulence, and carbohydrate sensing. A multiplicity of σI paralogues in some cellulolytic bacteria have been shown to be responsible for the regulation of the cellulosome, a multienzyme complex that mediates efficient cellulose degradation. Here, we report two structures at 3.0 Å and 3.3 Å of two transcription open complexes formed by two σI factors, SigI1 and SigI6, respectively, from the thermophilic, cellulolytic bacterium, Clostridium thermocellum. These structures reveal a unique, hitherto-unknown recognition mode of bacterial transcriptional promoters, both with respect to domain organization and binding to promoter DNA. The key characteristics that determine the specificities of the σI paralogues were further revealed by comparison of the two structures. Consequently, the σI factors represent a distinct set of the σ70-family σ factors, thus highlighting the diversity of bacterial transcription.

Direct seawater electrolysis is a promising technology within the carbon-neutral energy framework, leveraging renewable resources such as solar, tidal, and wind energy to generate hydrogen and oxygen without competing with the demand for pure water. High-selectivity, high-efficiency, and corrosion-resistant multifunctional electrocatalysts are essential for practical applications, yet producing stable and efficient catalysts under harsh conditions remains a significant challenge. This review systematically summarizes recent advancements in advanced electrocatalysts for seawater splitting, focusing on their multifunctional designs for selectivity and chlorine corrosion resistance. We analyze the fundamental principles and mechanisms of seawater electrocatalytic reactions, discuss the challenges, and provide a detailed overview of the progress in nanostructures, alloys, multi-metallic systems, atomic dispersion, interface engineering, and functional modifications. Continuous research and innovation aim to develop efficient, eco-friendly seawater electrolysis systems, promoting hydrogen energy application, addressing efficiency and stability challenges, reducing costs, and achieving commercial viability.

Relay channels capture the essence of several important communication scenarios such as sensor network and satellite communication. In this paper, first, we propose an efficient coding scheme for an additive white Gaussian noise (AWGN) relay channel in the presence of AWGN feedback, which generalizes the conventional scheme for the AWGN relay channel with noiseless feedback by introducing a lattice-based strategy to eliminate the impact of the feedback channel noise on the performance of the original scheme. Next, we further extend the proposed scheme to the multi-input single-output (MISO) fading relay channel (FRC) with noisy feedback. The key to this extension is to use a pre-coding strategy to transform the MISO channel into a single-input single-output (SISO) channel and applying a two-dimensional lattice coding strategy to deal with the feedback fading channel noise. Finally, we analyze the security performance of our proposed scheme in several cases, and the results of this paper are further illustrated by numerical examples.

Wild ungulates play crucial roles in maintaining the structure and function of local ecosystems. The alpine musk deer (Moschus chrysogaste), white-lipped deer (Przewalskium albirostris), and red serow (Capricornis rubidus) are widely distributed throughout the Nyenchen Tanglha Mountains of Tibet. However, research on the mechanisms underlying their coexistence in the same habitat remains lacking. This study aimed to investigate the mechanisms underlying the coexistence of these species based on their dietary preferences through DNA barcoding using the fecal samples of these animals collected from the study area. These species consume a wide variety of food types. Alpine musk deer, white-lipped deer, and red serow consume plants belonging to 74 families and 114 genera, 62 families and 122 genera, and 63 families and 113 genera, respectively. Furthermore, significant differences were observed in the nutritional ecological niche among these species, primarily manifested in the differentiation of food types and selection of food at the genus level. Owing to differences in social behavior, body size, and habitat selection, these three species further expand their differentiation in resource selection, thereby making more efficient use of environmental resources. Our findings indicate these factors are the primary reasons for the stable coexistence of these species.

Understanding the biodiversity–productivity relationship (BPR) is crucial for biodiversity conservation and ecosystem management. While it is known that diversity enhances forest productivity, the underlying mechanisms at the local neighborhood level remain poorly understood. We established a 9.6 ha dynamic forest plot to study how neighborhood diversity, intraspecific competition, and interspecific competition influence tree growth across spatial scales using linear mixed-effects models. Our analysis reveals a significant positive correlation between neighborhood species richness (NSR) and relative growth rate (RGR). Notably, intraspecific competition, measured by conspecific neighborhood density and resource competition, negatively impacts RGR at finer scales, indicating intense competition among conspecifics for limited resources. In contrast, interspecific competition, measured by heterospecific density and resource competition, has a negligible impact on RGR. The relative importance of diversity and intra/interspecific competition in influencing tree growth varies with scale. At fine scales, intraspecific competition dominates negatively, while at larger scales, the positive effect of NSR on RGR increases, contributing to a positive BPR. These findings highlight the intricate interplay between local interactions and spatial scale in modulating tree growth, emphasizing the importance of considering biotic interactions and spatial variability in studying BPR.

The recently introduced coati optimization algorithm suffers from drawbacks such as slow search velocity and weak optimization precision. An enhanced coati optimization algorithm called CMRLCCOA is proposed. Firstly, the Sine chaotic mapping function is used to initialize the CMRLCCOA as a way to obtain better-quality coati populations and increase the diversity of the population. Secondly, the generated candidate solutions are updated again using the convex lens imaging reverse learning strategy to expand the search range. Thirdly, the Lévy flight strategy increases the search step size, expands the search range, and avoids the phenomenon of convergence too early. Finally, utilizing the crossover strategy can effectively reduce the search blind spots, making the search particles constantly close to the global optimum solution. The four strategies work together to enhance the efficiency of COA and to boost the precision and steadiness. The performance of CMRLCCOA is evaluated on CEC2017 and CEC2019. The superiority of CMRLCCOA is comprehensively demonstrated by comparing the output of CMRLCCOA with the previously submitted algorithms. Besides the results of iterative convergence curves, boxplots and a nonparametric statistical analysis illustrate that the CMRLCCOA is competitive, significantly improves the convergence accuracy, and well avoids local optimal solutions. Finally, the performance and usefulness of CMRLCCOA are proven through three engineering application problems. A mathematical model of the hypersonic vehicle cruise trajectory optimization problem is developed. The result of CMRLCCOA is less than other comparative algorithms and the shortest path length for this problem is obtained.

In this paper, a series of low-temperature CVN (Charpy V-notch impact test) and DWTT (drop-weight tear test) experiments were carried out to deal with the intensifying contradiction of strength and toughness of ultra-high-strength pipeline steel. The fracture behavior and toughening mechanisms of ultra-high-strength pipeline steel were investigated using scanning electron microscopy, transmission electron microscopy and backscattered electron diffraction systems. The results show that DWTT fractures in ultra-high-strength pipeline steel had a variety of unconventional morphological features compared to CVN fractures, including ridge protrusion in ductile fracture conditions and a large-size fracture platform in brittle fracture conditions. Therefore, DWTT fractures contained more information about the material fracturing process, and could better reflect the actual process of material fracturing. In ultra-high-strength pipeline steel, fine-grained granular bainite caused cracks to undergo large deflections or frequent small transitions, which consumed additional energy and improved toughness. In contrast, large-sized granular bainite, which consisted of low-angle grain boundaries, did not effectively prevent crack propagation when it encountered cracks, which was not conducive to improved toughness. Moreover, the M/A constituents in large-sized granular bainite aggregated, cracked, or fell off, which could easily lead to the formation of microcracks and was also detrimental to toughening.

The resolution of conventional optical microscopy is restricted by the diffraction limit. Light waves containing higher-frequency information about the sample are bound to the sample surface and cannot be collected by far-field optical microscopy. To break the resolution limit, researchers have proposed various far-field super-resolution (SR) microscopy imaging methods using evanescent waves to transfer the high-frequency information of samples to the low-frequency passband of optical microscopy. Optimization algorithms are developed to reconstruct a SR image of the sample by utilizing the high-frequency information. These techniques can be collectively referred to as spatial-frequency-shift (SFS) SR microscopy. This review aims to summarize the basic principle of SR microscopy using evanescent illumination and introduce the advances in this research area. Some current challenges and possible directions are also discussed.

Objective: In this experiment, polysaccharides from cortex periplocae (CPP) were isolated and purified, and their monosaccharide composition and antioxidant activity were investigated, so as to provide a reference for the development and application of CPP in the food industry. Methods: The crude polysaccharides were obtained by aqueous extraction, alcoholic precipitation and protein removal by Sevag method, and four polysaccharide fractions CPP0, CPP1, CPP2 and CPP3 were separated and purified by DEAE-52 cellulose column. The chemical composition, molecular weight, monosaccharide composition, infrared spectrum and antioxidant activity were analyzed. Results: The sugar contents of these four polysaccharides were 82.20%, 77.13%, 75.23% and 72.85%, respectively, and all of them contained glyoxylate. The relative molecular weights were 685, 477, 411 and 572 kDa, respectively. The four polysaccharides were all heteropolysaccharides composed of mannose, rhamnose, galacturonic acid, glucose, galactose and arabinose in different molar ratios. The infrared spectra showed that four polysaccharides contained β-glycosidic bonds and with furan rings. The antioxidant experiments showed that all four polysaccharides had certain antioxidant properties, and the overall antioxidant capacity was in the following order: CPP0>CPP3>CPP1>CPP2. Conclusion: The four acidic polysaccharides extracted from cortex periplocae have high sugar content, high relative molecular weight, and antioxidant activity, among which CPP0 fraction has the best antioxidant activity.

Abstract Conventional deadbeat predictive current control (DBPCC) based on space vector modulation (SVM) shows quick dynamic responses and a good steady‐state performance in induction motor (IM) drives. However, the motor parameters change during operation due to temperature and saturation changes, leading to inaccurate reference voltage vectors and a degraded performance. Furthermore, conventional DBPCC uses a fixed vector sequence of 0127 over the entire speed range, which results in large current harmonics at high modulation indices. To address the above issues, this paper proposes a robust deadbeat predictive current control (RDBPCC) for IM drives. Based on an ultra‐local model, the proposed method updates the input voltage gain and unknown system components online according to the voltage and current of the previous two control cycles. Because the final control expression contains only the measured stator current and voltage values, the model shows a strong robustness. The steady‐state performance is significantly improved by selecting the optimal vector sequence according to the modulation index based on the principle of current harmonic minimization. The experimental results confirm that, compared with conventional vector control and conventional DBPCC, the proposed method achieves a strong parameter robustness and reduces the current total harmonic distortion (THD) by more than 10% and 20% at high‐modulation indices.

BackgroundThyroglobulin antibody (TgAb) has been found to be associated with the occurrence and development of differentiated thyroid cancer (DTC) for several years, but there is still controversy over whether thyroid peroxidase antibody (TPOAb) is related to differentiated thyroid cancer.MethodsWe scrutinized relevant studies published up to July 2023 across four major databases including PubMed, Embase, Cochrane Library, and Web of Science, to examine the association between TPOAb and DTC. Clinical outcome measures include the incidence of DTC, tumor size, extrathyroidal invasion, lymph node metastasis, multifocality, recurrence and bilaterality.Results12 original studies were included, involving a total of 20,330 subjects. Our analysis of the included studies revealed that TPOAb+ individuals exhibited a higher risk of developing DTC (OR=1.57 [95% CI: 1.00–2.45], p=0.049) than TPOAb– individuals. Furthermore, TPOAb+ DTC patients were more prone to present with bilateral (OR=1.40 [95% CI: 1.21–1.62], p

The structure of plant communities at local scales depends on both the spatial heterogeneity of abiotic environmental factors and the biotic interactions within the community. However, although environmental filtering due to microtopographic heterogeneity and resource competition among plants caused by spatial variation in tree density and size are considered to be very important in explaining the mechanisms of community assembly, their effects on the processes of individual mortality and recruitment in natural forest regeneration, as well as their relative contributions, are still poorly understood. To address this, we established a 12-ha permanent plot in a subtropical evergreen broad-leaved forest area and measured microtopographic variables such as elevation, slope, aspect, and terrain position index (TPI) using a total station. We monitored the individual mortality and recruitment in forest natural regeneration through repeated surveys at 5-year intervals. We fitted spatial covariance models to jointly use multiple factors from three groups of variables (microtopographic effect, neighborhood density effects, neighborhood size effects) as explanatory variables to analyze their roles in driving the mortality and recruitment of all individual and 12 dominant species in forest natural regeneration at the neighborhood scale. Our results show that: (1) In the crucial early stages of secondary forest restoration, natural regeneration is influenced by a synergy of environmental filtering, due to microtopographic heterogeneity, and resource competition among plants. (2) For distinct species responses, evergreen dominant species’ mortality is largely explained by neighborhood effects, while deciduous species are more affected by topographic factors. Furthermore, the adverse effects of larger conspecific trees on younger trees indicate a pattern of competitive pressure leading to mortality among regenerating trees, such pattern emphasis the influence of parent trees on natural regeneration. (3) As trees grow, their interaction with these stressors evolves, suggesting a shift in their resource acquisition strategies and response to neighborhood effects and environmental factors. Despite these changes, the relative importance of topographic factors in determining survival and recruitment success remains constant. This research highlights the importance of considering both environmental and neighborhood effects in forest management, particularly in early secondary forest restoration.

ObjectiveTo examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer.MaterialsIn this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups.ResultsAPT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax).ConclusionAPTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.

Inflammatory bowel disease (IBD), characterized primarily by gastrointestinal inflammation, predominantly manifests as Crohn’s disease (CD) and ulcerative colitis (UC). It is acknowledged that Inflammation plays a significant role in cancer development and patients with IBD have an increased risk of various cancers. The progression from inflammation to carcinogenesis in IBD is a result of the interplay between immune cells, gut microbiota, and carcinogenic signaling pathways in epithelial cells. Long-term chronic inflammation can lead to the accumulation of mutations in epithelial cells and the abnormal activation of carcinogenic signaling pathways. Furthermore, Immune cells play a pivotal role in both the acute and chronic phases of IBD, contributing to the transformation from inflammation to tumorigenesis. And patients with IBD frequently exhibit dysbiosis of the intestinal microbiome. Disruption of the gut microbiota and subsequent immune dysregulation are central to the pathogenesis of both IBD and colitis associated colorectal cancer (CAC). The proactive management of inflammation combined with regular endoscopic and tumor screenings represents the most direct and effective strategy to prevent the IBD-associated cancer.

A series of 21 novel compounds containing a thiosemicarbazone moiety were designed and synthesised based on hit compound 1 from our in-house compound library screening. Most compounds showed potent antifungal activity in vitro against seven common pathogenic fungi. Notably, all compounds showed high potency against Candida glabrata 537 (MIC = ≤0.0156-2 µg/mL). Of note, compounds 5j and 5r displayed excellent antifungal activity against Candida krusei 4946 and Candida auris 922. Additionally, compounds 5j and 5r also showed high potency against 15 C. glabrata isolates with MIC values ranging from 0.0625 µg/mL to 4 µg/mL, with compound 5r being slightly superior to 5j. Moreover, compound 5r has certain effect against biofilm formation of C. glabrata. Furthermore, compound 5r has minimal cytotoxicity against HUVECs with an IC50 value of 15.89 µg/mL and no haemolysis at 64 µg/mL. Taken together, these results suggest that promising lead compound 5r deserves further investigation.

Abstract Cryo-electron tomography (cryo-ET) is widely used to explore the 3D density of biomacromolecules. However, the heavy noise and missing wedge effect prevent directly visualizing and analyzing the 3D reconstructions. Here, we introduced REST, a deep learning strategy-based method to establish the relationship between low-quality and high-quality density and transfer the knowledge to restore signals in cryo-ET. Test results on the simulated and real cryo-ET datasets show that REST performs well in denoising and compensating the missing wedge information. The application in dynamic nucleosomes, presenting either in the form of individual particles or in the context of cryo-FIB nuclei section, indicates that REST has the capability to reveal different conformations of target macromolecules without subtomogram averaging. Moreover, REST noticeably improves the reliability of particle picking. These advantages enable REST to be a powerful tool for the straightforward interpretation of target macromolecules by visual inspection of the density and of a broad range of other applications in cryo-ET, such as segmentation, particle picking, and subtomogram averaging.

Both pandemic and seasonal influenza are major health concerns, causing significant mortality and morbidity. Current influenza drugs primarily target viral neuraminidase and RNA polymerase, which are prone to drug resistance. Polyoxometalates (POMs) are metal cation clusters bridged by oxide anions. They have exhibited potent anti-tumor, antiviral, and antibacterial effects. They have remarkable activity against various DNA and RNA viruses, including human immunodeficiency virus, herpes simplex virus, hepatitis B and C viruses, dengue virus, and influenza virus. In this study, we have identified sodium polyoxotungstate (POM-1) from an ion channel inhibitor library. In vitro, POM-1 has been demonstrated to have potent antiviral activity against H1N1, H3N2, and oseltamivir-resistant H1N1 strains. POM-1 can cause virion aggregation during adsorption, as well as endocytosis. However, the aggregation is reversible; it does not interfere with virus adsorption and endocytosis. Our results suggest that POM-1 exerts its antiviral activity by inhibiting the nuclear import of viral ribonucleoprotein (vRNP). This distinct mechanism of action, combined with its wide range of efficacy, positions POM-1 as a promising therapeutic candidate for influenza treatment and warrants further investigation.

Group recommender systems aim to provide recommendations to a group of users as a whole rather than to individual users. Nonetheless, prevailing methodologies predominantly aggregate user preferences without adequately accounting for the unique individual intents influencing item selection. This oversight becomes particularly problematic in the context of ephemeral groups formed by users with limited shared historical interactions, which exacerbates the data sparsity challenge. In this paper, we introduce a novel Disentangled Self-Attention Group Recommendation framework with auto-regressive contrastive learning method, termed DAGA. This framework not only employs disentangled neural architectures to reconstruct the multi-head self-attention network but also incorporates modules for mutual information optimization via auto-regressive contrastive learning to better leverage the context information of user–item and group–item historical interactions, obtaining group representations and further executing recommendations. Specifically, we develop a disentangled model comprising multiple components to individually assess and interpret the diverse intents of users and their impacts on collective group preferences towards items. Building upon this model, we apply the principle of contrastive mutual information maximization to train our framework, aligning the group representations with the corresponding user representations derived from each factor of the disentangled model, thereby enriching the contextual understanding required to effectively address the challenges posed by ephemeral groups. Empirical evaluations conducted on three real-world benchmark datasets substantiate the superior performance of our proposed framework over existing state-of-the-art group recommendation approaches.

An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of clutter due to the radar configuration. To solve these problems, this paper proposes a joint implementation method based on sub-aperture processing to achieve clutter suppression and coherent maneuvering target detection. Specifically, clutter Doppler compensation and sliding window processing are carried out to realize sub-aperture space–time processing, removing the clutter non-stationarity resulting from the bistatic geometric configuration. Thus, the output matrix of clutter suppression in the sub-aperture could be obtained. Then, the elements with the same phase of this matrix are superimposed and rearranged to achieve the reconstructed 2-D range-pluse echo matrix. Next, the aperture division with respect to slow time is conducted and the RCM correction based on modified location rotation transform (MLRT) and coherent integration (CI) are realized within each sub-aperture. Finally, the matched filtering process (MFP) is applied to compensate for the RCM/DM among different sub-apertures to coherently integrate the maneuvering target energy of all sub-apertures. The simulation and measured data processing results prove the validity of the proposed method.

The purposes of this research is to analyzed the impact of various policies on household incomes and to obtain the influential factors according to their importance. Utilizing a survey data of poor households supported by poverty improvement policies, for individual income, this research implements the traditional random forest method. To analyze the influence of strategies on the overall household earnings, we propose a novel splitting method centered on copula entropy and construct a novel choice tree. Finally, we conclude that the policies are generally effective but that levels of effectiveness are varied for people with different levels of income. We also identified the policy arrangement that has the greatest impact on household income.

The saline, alkaline environment of arid soils is conducive to the diffusion of the metalloid arsenic (As). Desert plants in this area are of great ecological importance and practical value. However, there are few studies on the mechanism of arsenic action in desert plants. Therefore, in this study, Eremostachys moluccelloides Bunge was treated with different concentrations of As2O5 [As(V)] to analyze the physiological, biochemical, and transcriptomic changes of its roots and leaves and to explore the molecular mechanism of its response to As(Ⅴ) stress. The activities of catalase, superoxidase, peroxidase, and the contents of malondialdehyde and proline in roots and leaves first increased and then decreased under the As(Ⅴ) stress of different concentrations. The content of As was higher in roots than in leaves, and the As content was positively correlated with As(Ⅴ) stress concentration. In the differentially expressed gene analysis, the key enzymes of the oxidative stress response in roots and leaves were significantly enriched in the GO classification. In the KEGG pathway, genes related to the abscisic acid signal transduction pathway were co-enriched and up-regulated in roots and leaves. The related genes in the phenylpropanoid biosynthesis pathway were significantly enriched and down-regulated only in roots. In addition, the transcription factors NAC, HB-HD-ZIP, and NF-Y were up-regulated in roots and leaves. These results suggest that the higher the As(V) stress concentration, the more As is taken up by roots and leaves of E. molucelloides Bunge. In addition to causing greater oxidative damage, this may interfere with the production of secondary metabolites. Moreover, it may improve As(V) tolerance by regulating abscisic acid and transcription factors. The results will deepen our understanding of the molecular mechanism of As(Ⅴ) response in E. moluccelloides Bunge, lay the foundation for developing and applying desert plants, and provide new ideas for the phytoremediation of As pollution in arid areas.

Summary: The organization and dynamics of chromatin fiber play crucial roles in regulating DNA accessibility for gene expression. Here we combine cryoelectron tomography (cryo-ET), sub-volume averaging, and 3D segmentation to visualize the in vitro and in vivo chromatin fibers folding by linker histone. We discover that an increased nucleosome repeat length and prolonged fiber length do not change the two-start helical architecture in reconstituted chromatin of homogeneous composition. Additionally, an isolated chromatin fiber with heterogeneous composition was observed, which includes short-range regions compatible with two-start helix. In vivo, sub-volume averaging reveals similar subunits of two-start helical architecture in transcriptionally inactive chromatin in frog erythrocyte nuclei. Strikingly, unambiguous DNA trajectories that displayed a zigzag pattern universally between alternate N/N+2 nucleosomes were further determined by cryo-ET with voltage phase plate. Therefore, these structural similarities suggest a general folding mode of chromatin induced by linker histone, and heterogeneous compositions mainly affect local conformation rather than changing the overall architecture.

In order to solve the problem of poor grid connected consumption capacity of renewable energy in power system, a multi-source coordinated optimal scheduling method of wind-PV-hydro-thermal-nuclear-storage is proposed in this paper. The optimal scheduling method comprehensively considers the constraints of system power balance, capacity and climbing rate of various power generation modes, establishes the objective function based on the system power purchase cost and renewable energy consumption, obtains the weight relationship between the objective functions by analytic hierarchy process. An adaptive improved genetic algorithm is proposed, and the objective function is solved and the results are compared by this algorithm and three algorithms such as adaptive improved particle swarm algorithm, respectively. The results show that the improved genetic algorithm can eliminate the local optimum phenomenon by normalizing the crossover and combining variances, and is more suitable for the multi-source coordinated optimization scheduling model compared with the other algorithms. After the multi-source coordination and optimal dispatch, the system renewable energy disposal is reduced from 657MWh to 208MWh, and the power purchase cost of the system load is reduced from ${\$}$ 30.077 to ${\$}$ 30.052M. It can be seen that the selected optimization method can enhance the system’s renewable energy consumption capacity while reducing the system’s power purchase cost, which reflects the effectiveness of the optimization method used in this paper. By changing the scaling parameters of the hierarchical analysis method, the scheduling scheme can be flexibly selected for different regions, reflecting the universal applicability of the optimization method used in this paper. To provide an efficient and accurate solution for multi-energy dispatching problems in power systems.

Introduction: In recent years, with the rapid development of renewable energy generation, the stability of the power grid has been greatly reduced. In response to this problem, integrating the user side transferable load into the power market has become the key to the development of future power grid. At present, large transferable loads have entered the electricity market in some pilot areas of China, but the relevant research on small and medium-sized transferable users entering the electricity market is still few.Methods: This paper proposes the concept of generation load aggregators. A two-stage generation load aggregator robust optimization model is developed to obtain the scheduling scheme with the lowest operating cost under the worst scenario. The model consists of distributed renewable power, transferable load, self-provided power, energy storage, etc. Uncertainties of renewable energy and load are introduced in the model. By using the column constraint generation algorithm and strong pairwise theory, the original problem is decomposed into the main problem and sub-problems to be solved alternately, so as to obtain the scheduling scheme with the lowest operating cost in the worst scenario under different conservatism.Results: The solved results are compared with those without the generation load aggregator, illustrating the role of the generation load aggregator in relieving peak and valley pressure on the grid from the load side, reducing the cost of electricity for loads, and promoting the consumption of renewable energy. The comparison with the deterministic optimization algorithm shows a significant decrease in the total cost and validates the performance of the selected solution algorithm. The boundary conditions for the use of energy storage by generation load aggregators for peak and valley reduction under the time-sharing tariff mechanism are also derived.Discussion: This study can provide reference for the investors of generation load aggregators when planning whether to install energy storage or the scale of energy storage, and also help the power market management department to design a reasonable incentive mechanism.

A dual-band electrochromic supercapacitor device (DESCD) can be driven by an external power supply to modulate solar radiation, which is a promising energy-saving strategy and has broad application prospects in smart windows. However, traditional power supplies, such as batteries, supercapacitors, etc., usually face limited lifetimes and potential environmental issues. Hence, we propose a self-powered DESCD based on TiO2/WO3 dual-band electrochromic material and a ternary dielectric rotating triboelectric nanogenerator (TDR-TENG). The TDR-TENG can convert mechanical energy from the environment into electrical energy to obtain a high output of 840 V, 23.9 µA, and 327 nC. The as-prepared TDR-TENG can drive the TiO2/WO3 film to store energy with a high dual-band modulation amplitude of 41.6% in the visible (VIS) region and 84% in the near-infrared (NIR) region, decreasing the indoor–outdoor light–heat interaction and thereby reducing the building energy consumption. The self-powered DESCD demonstrated in this study has multiple functions of energy harvesting, energy storage, and energy saving, providing a promising strategy for the development of self-powered smart windows.

Performance-based seismic design methods for bridges are advancing, yet limited research has explored the damage mechanisms of bridges subjected to extreme seismic effects, such as those near or across faults. To investigate the damage mechanisms under bedrock dislocation and bridge rupture resistance, providing essential insights for the standardized design and construction of bridges in close proximity to seismic rupture sites, we developed a large-scale device to model bridges in the immediate vicinity of tilted-slip strong seismic rupture sites. This included a synchronous bedrock dislocation loading system. Four sets of typical sandy soil modeling tests were concurrently conducted. The results indicate: (1) The overall shear deformation zone of the foundation and surface uneven deformation primarily concentrate the overburdened soil body along the fault dip. The damaged area under the low-dip reverse fault is lighter on the surface and inside the soil body compared to the high-dip-positive fault. (2) The presence of bridges reduces the width of the main rupture zone and avoidance distance to some extent. However, this reduction is not as significant as anticipated. The damage to the bridge pile foundation along the fault dislocation tendency notably leads to the bending damage of the bridge deck. (3) Input parameters for fracture-resistant bridge design (surface rupture zone location, extent, maximum deformation, etc.) can be deduced from the free site. Within the rupture zone, a “fuse” design can be implemented using simply supported girders. Additionally, combining the “fuse” design with simple supported girders on both sides and utilizing simple support beams for “fuse” design within the rupture zone, along with structural “disconnection”, allows for reinforcing measures on the bridge structure’s foundation platform and pile in the soil body.

In China, the population of wild musk deer, belonging to the family Moschidae, has drastically decreased in recent years owing to human activities and environmental changes. During the 1990s, artificial breeding of Alpine musk deer was conducted in Xinglong Mountain, Gansu Province, China, and their ex situ conservation was explored for over a decade. Ex situ protection is beneficial for expanding the population of animals and maintaining their genetic diversity; however, it can also induce metabolic diseases and parasitic infections and reduce reproductive capacity. The gut microbiota of animals has a considerable impact on host energy metabolism and immune regulation, thereby playing a crucial role in the overall health and reproductive success of the host. In this study, by comparing the differences in the intestinal microbiome of the musk deer according to their place of origin and migration, the changes in their gut microbiota and the influencing factors were explored to provide a theoretical basis for monitoring the health status of the musk deer. We used 16S rRNA high-throughput sequencing technology to analyze the structure and diversity of the gut microbiota of Alpine musk deer in Gansu (G, place of origin) and Sichuan (S, place of migration). The results showed that the dominant bacteria and genera in the intestinal microbiome of captive musk deer were similar in the places of origin and migration, but significant differences were observed in their relative abundance (p < 0.05). Regarding Firmicutes and Actinobacteria, which are related to plant cellulose digestion, the relative abundance in group G was higher than that in group S; regarding Proteobacteria and Verrucomicrobia, which are related to fat and starch intake, the relative abundance in group S was higher than that in group G; the relative abundance of Bacillus and Clostridium sensu stricto, which are related to fiber digestibility, was higher in group G than in group S; the relative abundance of conditional pathogens Acinetobacter and Escherichia–Shigella was higher in group S than in group G. The results of α and β diversity analysis also showed significant differences between the two groups (p < 0.05). The ACE and Shannon indices of musk deer in group G were considerably higher than those in group S, and the Simpson index of musk deer in group S was greater than that in group G, indicating that the abundance and diversity of intestinal microbiome were higher in musk deer of Gansu than those of Sichuan. Comparison of the changes in the intestinal microbiome of the musk deer according to the place of origin and migration showed that the plant cellulose content in the food of the musk deer, the fat content in the concentrated feed, and changes in the feeding environment have an impact on the intestinal microbiome. Effective monitoring of the health and immunity of the musk deer is crucial for ensuring their overall health, which in turn will aid in formulating a scientific and reasonable management plan for their conservation.

Ultrathin flexible encapsulation (UFE) using multilayered films has prospects for practical applications, such as implantable and wearable electronics. However, existing investigations of the effect of mechanical bending strains on electrical properties after the encapsulation procedure provide insufficient information for improving the electrical stability of ultrathin silicon nanomembrane (Si NM)-based metal oxide semiconductor capacitors (MOSCAPs). Here, we used atomic layer deposition and molecular layer deposition to generate 3.5 dyads of alternating 11 nm Al2O3 and 3.5 nm aluminum alkoxide (alucone) nanolaminates on flexible Si NM-based MOSCAPs. Moreover, we bent the MOSCAPs inwardly to radii of 85 and 110.5 mm and outwardly to radii of 77.5 and 38.5 mm. Subsequently, we tested the unbent and bent MOSCAPs to determine the effect of strain on various electrical parameters, namely the maximum capacitance, minimum capacitance, gate leakage current density, hysteresis voltage, effective oxide charge, oxide trapped charge, interface trap density, and frequency dispersion. The comparison of encapsulated and unencapsulated MOSCAPs on these critical parameters at bending strains indicated that Al2O3/alucone nanolaminates stabilized the electrical and interfacial characteristics of the Si NM-based MOSCAPs. These results highlight that ultrathin Al2O3/alucone nanolaminates are promising encapsulation materials for prolonging the operational lifetimes of flexible Si NM-based metal oxide semiconductor field-effect transistors.

Abstract Background The critical role of thioredoxin-interacting protein (TXNIP) in cellular sulfhydryl redox homeostasis and inflammasome activation is already widely known, however, no pan-cancer analysis is currently available. Methods We thus first explored the potential roles of TXNIP across thirty-three tumors mainly based on The Cancer Genome Atlas and Gene Expression Omnibus datasets. Results TXNIP is lowly expressed in most cancers, and distinct associations exist between TXNIP expression and the prognosis of tumor patients. TXNIP expression was associated with tumor mutational burden, microsatellite instability, mismatch repair genes, tumor infiltrating immune cell abundance as well as cancer-associated fibroblasts. Moreover, ubiquitin mediated proteolysis, protein post-translational modification and other related pathways were involved in the functional mechanisms of TXNIP. Conclusions Our first pan-cancer study comprehensively revealed the carcinostatic role of TXNIP across different tumors. And this molecule may be considered as a potential immunological and prognostic biomarker.

The triboelectric nanogenerator (TENG) is an emerging technology proven to have great potential in rainwater energy harvesting. However, most studies have focused only on single-position droplets, and there needs to be more research on multi-position, large-scale rainwater energy. In this work, we develop a multi-position and multi-layered triboelectric nanogenerator (MM-TENG) for large-scale raindrop energy harvesting. The multi-position structure can harvest multiple droplets in the horizontal direction. The water reservoir with multiple holes can convert a large amount of water into droplets, ensuring the output performance of the TENG. The multi-layered structure improves the efficiency of space utilization, as demonstrated by the current integration calculation, where a double-layered structure increases the output by 15.27% and a three-layered structure increases the output by 38.2% at the same height. Finally, we successfully lit up 50 LEDs and drove a commercial calculator with the power generated by the MM-TENG. This work provides a practical guide for collecting large-scale raindrop energy and self-driven sensing of the rainwater environment.

BackgroundCongenital birth defects (CBDs) are a major public health issue. This study aims to assess trends in the burden of CBDs between 1990 and 2019 across China based on the Global Burden of Disease Study 2019 (GBD 2019).MethodsIndicators of the burden of CBDs included incidence, mortality, and disability-adjusted life years (DALYs). Metrics included number, rate, and age-standardized rate with 95% uncertainty intervals (UIs). Data were stratified by region [China, global, high-, middle-, low-socio-demographic index (SDI)], age, sex, and type of CBD. Average annual percentage changes (AAPC) and trends were evaluated.ResultsIn China, between 1990 and 2019, the age-standardized incidence rate for CBDs showed an increasing trend, with an AAPC of 0.26% (0.11% to 0.41%), reaching 148.12 per 105 person-years (124.03 to 176.33) in 2019. Most CBDs were congenital heart anomalies, with an AAPC of 0.12% (−0.08% to 0.32%). The age-standardized mortality rate for CBDs showed a decreasing trend, with an AAPC of −4.57% (−4.97% to −4.17%), reaching 4.62 per 105 person-years (3.88 to 5.57) in 2019. Most mortality was associated with congenital heart anomalies, with an AAPC of −3.77% (−4.35% to −3.19%). The age-standardized DALYs rate for CBDs showed a decreasing trend, with an AAPC of −3.74% (−3.95% to −3.52%), reaching 480.95 per 105 person-years (407.69 to 570.04) in 2019.ConclusionsMorbidity associated with CBDs increased in China between 1990 and 2019, accelerated by the adoption of the two-child policy, and ranked high globally. These findings emphasize the need for prenatal screening and primary and secondary prevention strategies.