In order to facilitate spare parts management,an integrated approach of BP neural network and supportability analysis(SA)was proposed to evaluate the criticality of spare parts as well as to prioritize spare parts.Inf...In order to facilitate spare parts management,an integrated approach of BP neural network and supportability analysis(SA)was proposed to evaluate the criticality of spare parts as well as to prioritize spare parts.Influential factors of prioritizing spare parts were detailedly analyzed.Framework of the integrated method was established.The modelling process based on BP neural network was presented.As the input of the neural network,the values of influential factors were determined by supportability analysis data.Based on the presented method,spare parts could be automatically prioritized after supportability analysis for a new system.A case study results showed that the new method was applicable and effective.展开更多
To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing...To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing system was used to conduct rock damage tests on sandstone with different support timing and strength paths.Based on the acoustic emission monitoring system,the spatial and temporal evolution characteristics of the whole process of rock body loaded instability under two stress paths were studied,and the mechanism of the reinforcing effect of stress support on the unloaded rock mass was analyzed.The results show that,within the scope of this study,both earlier applications of shoring and an increase in shoring strength can effectively improve the ultimate bearing capacity of the unloaded rock,which increases the ultimate bearing capacity of the unloaded rock mass by 60.31% and 54.96%,respectively;There is a phenomenon of rebound deformation of the rock mass during sudden changes in stress(single-sided unloading,stress support),which shows opposite expansion and compression platforms on the stress−strain curve;The crack evolution of unloaded rock under different stress support conditions shows the state law of"initial crack activation→middle steady state expansion→late main crack penetration",and the lagging support significantly accelerates the crack evolution from local activation to main penetration;The single-sided unloading and stress-supporting stages have less influence on the unloading deformationsσ_(1u),σ_(2u) and support deformationsσ_(1) t,σ_(2t) in theσ_(1) andσ_(2)directions,while they show significant response characteristics toσ_(3u),σ_(vu) and σ_(3) t,σ_(vt),and with the increase of the support strength,the stress-supporting stagesσ_(3) t,σ_(vt) gradually increase and exceed the deformations generated by the unloading stagesσ_(3u),σ_(vu);The increase of support strength can effectively compensate for the rock stress loss caused by unloading,which makes the maximum,minimum,and volumetric strain support coefficients during the loading and unloading of the rock body increase gradually while the effect on the intermediate principal strain support coefficient is small;During loading,the support strength of rock masses seeks a new bearing area by regulating stress equilibrium states.This process primarily manifests as a shift in the locations of the crushing zone and the main bearing area,accompanied by a corresponding transformation in failure patterns.Consequently,the rock mass transitions from asymmetric three-zone damage under no or weak support to approximate symmetric three-zone damage under strong support.Simultaneously,the main load-bearing area of the rock mass shifts from deep bearing in the unsupported to middle bearing under strong support as the support strength increases.展开更多
This paper proposes a practical and framework-based approach to design an architecture transformation strategy and roadmap aiming to transform or modernize critical legacy enterprise systems.The approach is business v...This paper proposes a practical and framework-based approach to design an architecture transformation strategy and roadmap aiming to transform or modernize critical legacy enterprise systems.The approach is business value driven with IT supportability in terms of lower application operational and support costs,higher business value and shorter time to market of application delivery.The approach introduces a robust enterprise application architecture assessment framework with an emphasis on technical(internal)and strategic(external)perspectives to guide the application assessment and also a finance selfsupport transformation strategy to aid its transformation roadmap design.The approach was applied in multiple large enterprises successfully and received endorsements and positive feedback from the sponsors.The paper also presents a case study detailing the successful application of the approach to modernize an enterprise logistics transportation management system.展开更多
The testing of large structures is limited by high costs and long cycles, making scaling methods an attractive solution. However, the scaling process of elastic rings introduces complexities in multi-parameter geometr...The testing of large structures is limited by high costs and long cycles, making scaling methods an attractive solution. However, the scaling process of elastic rings introduces complexities in multi-parameter geometric distortions, leading to a diminution in the predictive accuracy of the distorted similitude. To address this challenge, this study formulates a novel set of scaling laws, tailored to account for the intricate geometric distortions associated with elastic rings. The proposed scaling laws are formulated based on the intrinsic deformation characteristics of elastic rings, rather than the traditional systemic governing equations. Numerical and experimental cases are conducted to assess the efficacy and precision of the proposed scaling laws, and the obtained results are compared with those achieved by traditional methods. The outcomes demonstrate that the scaling laws put forth by this study significantly enhance the predictive capabilities for deformations of elastic rings.展开更多
Photocatalytic nitrogen fixation (PNF) is a promising alternative to the Haber-Bosch process.It achieves green ammonia production by utilizing solar energy for nitrogen fixation under mild conditions.While nanoscale p...Photocatalytic nitrogen fixation (PNF) is a promising alternative to the Haber-Bosch process.It achieves green ammonia production by utilizing solar energy for nitrogen fixation under mild conditions.While nanoscale photocatalysts offer enhanced performance due to their high surface area and abundant active sites,their small size makes them difficult to recover and prone to agglomeration.These bottlenecks severely limit industrial application.A promising solution is to immobilize the catalysts onto support surfaces.This paper provides a systematic review of recent advances in the design of immobilized photocatalysts for ammonia synthesis.It begins by outlining the key benefits of immobilization strategies,particularly in improving catalyst stability,recyclability,and overall photocatalytic performance.The working mechanisms and features of various immobilization techniques are then categorized and explained,covering physical adsorption/deposition,chemical bonding,in situ growth,and hybrid physico-chemical methods.Supported materials and common substrate types are also summarized.Furthermore,the widely used configurations of photoreactors suitable for immobilized systems are introduced.Finally,the review identifies current research limitations and challenges,and offers perspectives on future developments in the field of immobilized photocatalysis.展开更多
Significant diurnal temperature variations in mountainous rack railways cause stiffness mismatches between the rack structure and simply supported bridges,leading to critical failures like bolt loosening and rack frac...Significant diurnal temperature variations in mountainous rack railways cause stiffness mismatches between the rack structure and simply supported bridges,leading to critical failures like bolt loosening and rack fractures.This study develops a dynamic model of the vehicle-rack-bridge system based on train-track-bridge interaction theory,integrating gear-rack meshing and wheel-rail contact mechanisms.The model analyzes the dynamic response of bridges with varying spans under combined thermal and dynamic loading.Numerical simulations,conducted using finite element analysis,reveal peak vibration accelerations of 1.3 m/s^(2)for the rack,3.0 m/s^(2)for the rail,1.2 m/s^(2)for the sleeper,and 0.1 m/s^(2)for the bridge,with maximum stresses of 3 MPa in the rack,8 MPa in the rail,and 25 MPa in connecting bolts.The results show significant span-dependent amplification of stress and strain in the rack system under thermo-mechanical loading,exceeding material strength limits at 60-meter spans.An innovative elastic connection method is proposed to mitigate stress concentrations effectively,en-hancing system durability.This study introduces a novel approach to modeling complex thermo-mechanical interactions in rack railway systems,validated through extensive simulations,and provides a practical solution for improving structural resilience,offering theoretical guidance for optimizing rack-bridge system design to ensure operational safety in extreme environmental conditions.展开更多
The neutral surface of a concave thin mirror is too close to the mirror surface,which makes it difficult to effectively mount the flexible structure and increases the mirror surface shape error.To address this problem...The neutral surface of a concave thin mirror is too close to the mirror surface,which makes it difficult to effectively mount the flexible structure and increases the mirror surface shape error.To address this problem,we design a flexible support structure including connectors,a support plate,and flexible structures,and construct an equivalent mirror by installing connectors and a support plate on the back of the mirror.While ensuring that the neutral surface of the equivalent mirror is moved away from the mirror surface,we optimize the support structure so that the rotary center of the flexible structure is located on the neutral surface of the equivalent mirror,avoiding the tilting moment.Following design and modeling of the structure,we analyze the static and dynamic characteristics using a finite element simulation,finding a root-mean-square(RMS)value for the surface shape error of 9.28 nm under the coupled effects of 1g gravity load,4℃ temperature rise,and 0.005 mm unevenness assembly error,with a fundamental frequency of 170.75 Hz,which all meet the design requirements.Finally,we carry out a surface shape error test of the mirror assembly,confirming it to meet the design index requirement of the mirror assembly.Simulation and test results verify the reliability and effectiveness of our proposed support structure.展开更多
Objective:To explore the clinical effect of personalized nutritional support in elderly women with gestational diabetes(GDM),and explore its impact on the incidence of maternal complications and pregnancy outcomes.Met...Objective:To explore the clinical effect of personalized nutritional support in elderly women with gestational diabetes(GDM),and explore its impact on the incidence of maternal complications and pregnancy outcomes.Methods:A total of 90 elderly pregnant women with gestational diabetes who were delivered in our hospital from January 2023 to January 2024 were selected as the research objects.They were randomly divided into an observation group and a control group,with 45 cases in each group.The control group only received routine pregnancy care and basic nutrition guidance,while the observation group received personalized nutrition support on this basis.Compare the blood glucose control,incidence of pregnancy complications,pregnancy outcomes,and neonatal outcomes between two groups of parturient.Result:After intervention,the fasting blood glucose(FPG),2-hour postprandial blood glucose(2hPG),and glycated hemoglobin(HbA1c)of the observation group were significantly lower than those of the control group,and the differences were statistically significant(p<0.05);The incidence of complications such as gestational hypertension syndrome,polyhydramnios,premature rupture of membranes,and postpartum hemorrhage in the observation group was significantly lower than that in the control group,and the difference was statistically significant(p<0.05);The cesarean section rate in the observation group was significantly lower than that in the control group,and the incidence of adverse neonatal outcomes such as fetal distress,macrosomia,neonatal asphyxia,and neonatal hypoglycemia in the observation group was significantly lower than that in the control group,with statistical significance(p<0.05).Conclusion:Individualized nutritional support for elderly women with gestational diabetes can effectively improve the level of maternal blood sugar control,reduce the incidence of complications during pregnancy,and improve the outcome of pregnancy and neonatal outcomes,which is of high clinical value.展开更多
YOU CANNOT SUCCUMB TO CHOLERA,unless the sewage system breaks down-likewise deaths from violence vanish,as long as emotional support networks are working properly.Gut hygiene eliminates the one,societal hygiene the ot...YOU CANNOT SUCCUMB TO CHOLERA,unless the sewage system breaks down-likewise deaths from violence vanish,as long as emotional support networks are working properly.Gut hygiene eliminates the one,societal hygiene the other.Cholera was an inexorable plague-until Germ Theory was accepted and implemented.Violence too,will persist-until we agree and accept its equivalent in Societal Theory.The scientific method,especially Quantum Physics,sabotages philosophy-it cannot cope with the living fact that the elephant in the room is alive.Quantum Mechanics describes itself as being(1)more incomprehensible,(2)weirder,and(3)more uncertain than anything we’ve met before.But that’s chickenfeed,compared to what you find in clinical medicine,which though portrayed as being intrinsically woolly and subjective,wilfully aims to enhance life,whatever that might be.展开更多
Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural netwo...Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural networks learn new classes sequentially,they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes.This challenge,which lies at the core of class-incremental learning,severely limits the deployment of continual learning systems in real-world applications with streaming data.Existing approaches,including rehearsalbased methods and knowledge distillation techniques,have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features under limited memory constraints.To overcome these limitations,we propose a support vector-guided framework for class-incremental learning.The framework integrates an enhanced feature extractor with a Support Vector Machine classifier,which generates boundary-critical support vectors to guide both replay and distillation.Building on this architecture,we design a joint feature retention strategy that combines boundary proximity with feature diversity,and a Support Vector Distillation Loss that enforces dual alignment in decision and semantic spaces.In addition,triple attention modules are incorporated into the feature extractor to enhance representation power.Extensive experiments on CIFAR-100 and Tiny-ImageNet demonstrate effective improvements.On CIFAR-100 and Tiny-ImageNet with 5 tasks,our method achieves 71.68%and 58.61%average accuracy,outperforming strong baselines by 3.34%and 2.05%.These advantages are consistently observed across different task splits,highlighting the robustness and generalization of the proposed approach.Beyond benchmark evaluations,the framework also shows potential in few-shot and resource-constrained applications such as edge computing and mobile robotics.展开更多
In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative...In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative spam detection method utilizing the Horse Herd Optimization Algorithm(HHOA),designed for binary classification within multi⁃objective framework.The method proficiently identifies essential features,minimizing redundancy and improving classification precision.The suggested HHOA attained an impressive accuracy of 97.21%on the Kaggle email dataset,with precision of 94.30%,recall of 90.50%,and F1⁃score of 92.80%.Compared to conventional techniques,such as Support Vector Machine(93.89%accuracy),Random Forest(96.14%accuracy),and K⁃Nearest Neighbours(92.08%accuracy),HHOA exhibited enhanced performance with reduced computing complexity.The suggested method demonstrated enhanced feature selection efficiency,decreasing the number of selected features while maintaining high classification accuracy.The results underscore the efficacy of HHOA in spam identification and indicate its potential for further applications in practical email filtering systems.展开更多
With the global expansion of protected areas(PAs)and increasing involvement of indigenous communities,understanding their impacts on indigenous peoples is crucial.This study evaluates the extent to which China’s nati...With the global expansion of protected areas(PAs)and increasing involvement of indigenous communities,understanding their impacts on indigenous peoples is crucial.This study evaluates the extent to which China’s national cultural ecological protection areas(CEPAs)safeguard indigenous culture,using land-use disturbance as a key metric to assess impacts on cultural keystone species(CKS).We employ a multi-step evaluation framework that reclassifies land use,identifies environment-dependent CKS,and analyzes land-use dynamics by comparing disturbances before and after CEPAs establishment.Our results reveal that,despite overall improvements in land conditions,over 36%of CEPAs are in land disturbance threat or warning status.All of these sites are indigenous CEPAs,indicating a disproportionate disturbance burden on indigenous communities.Notably,traditional medicinal practices are particularly vulnerable.These findings underscore the urgent need for policies aligning ecological diversity with cultural diversity to support the global commitment to expand PAs to over 30%of Earth’s land and oceans by 2030.展开更多
The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc...The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.展开更多
Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving re...Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.展开更多
This study investigated the effects of parental involvement,parenting stress,and social support on the social skills of school-aged children(6-18 years old)with intellectual disabilities(ID).Data were collected from 2...This study investigated the effects of parental involvement,parenting stress,and social support on the social skills of school-aged children(6-18 years old)with intellectual disabilities(ID).Data were collected from 280 Chinese parents(mothers=70.0%,fathers=30.0%)of children with ID through purposive sampling and analyzed using partial least squares structural equation modeling(PLS-SEM).The results indicated that parental involvement not only directly enhanced children’s social skills but also indirectly improved them by alleviating parenting stress,which acted as a partial mediator.Contrary to the stress-buffering hypothesis,social support did not moderate the negative impact of parenting stress on social skills.Theoretically,this study contributes by validating ecological systems theory through a shift in focus from individual deficits to family systems,while also challenging the conventional view of stress-buffering theory.Accordingly,parent-support programs should integrate practical involvement training with systematic stress reduction and provide tailored assistance such as behavior-management training and respite care.展开更多
On New Year’s Eve,Chinese President Xi Jinping delivered his 2026 New Year message via China Media Group and online platforms.The address signals China’s continued support for the aspirations of the Global South,off...On New Year’s Eve,Chinese President Xi Jinping delivered his 2026 New Year message via China Media Group and online platforms.The address signals China’s continued support for the aspirations of the Global South,offering political and moral backing at a time of heightened global uncertainty.展开更多
Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudi...Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.展开更多
In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory mode...In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.展开更多
Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,B...Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,Bukyiende Subcounty in Uganda where he has been cultivating plantain,coffee and Irish potatoes for the past 16 years.展开更多
Under the condition of frequent replacement of wind tunnel models,multiple types of wind tunnel models are fixed by a slender support sting with low stiffness damping.When excited by wind load,various models produce r...Under the condition of frequent replacement of wind tunnel models,multiple types of wind tunnel models are fixed by a slender support sting with low stiffness damping.When excited by wind load,various models produce random multi-dimensional vibration with different characteristics,which makes it impossible to obtain accurate and efficient aerodynamic data.Therefore,in order to ensure the reliable and efficient conduction of wind tunnel test,a wind-tunnel-modeladaptive vibration control method is proposed in this paper.First,the split type adaptive vibration suppression structure is designed.Second,the multi-dimensional vibration characteristic characterization method is derived and the vibration characteristic identification method of the system is designed.Then,a vibration state estimation model is established according to the identification results of vibration characteristics,and a multi-actuator cooperative control method based on vibration state estimation is constructed.Finally,a model-adaptive vibration control system is built,and vibration characteristics identification and hammer experiments are carried out for two types of typical models.The results show that the proposed model-adaptive vibration control method increases the equivalent damping ratio of pitch and yaw dimensions of the high-aspect-ratio class model by 8.19 times and 48.81 times,respectively.The equivalent damping ratio of pitch and yaw dimensions of the highslenderness-ratio class model is increased by 16.44 and 5.43 times,respectively.It provides a strong guarantee for the reliable and efficient development of multi-type wind tunnel test tasks.展开更多
文摘In order to facilitate spare parts management,an integrated approach of BP neural network and supportability analysis(SA)was proposed to evaluate the criticality of spare parts as well as to prioritize spare parts.Influential factors of prioritizing spare parts were detailedly analyzed.Framework of the integrated method was established.The modelling process based on BP neural network was presented.As the input of the neural network,the values of influential factors were determined by supportability analysis data.Based on the presented method,spare parts could be automatically prioritized after supportability analysis for a new system.A case study results showed that the new method was applicable and effective.
基金Projects(2023 YFC 2907602,2022 YFF 1303302)supported by the National Key Research and Development Project of ChinaProject(52342404)supported by the National Natural Science Foundation of China+2 种基金Project(GXXT-2021-075)supported by the University Synergy Innovation Program of Anhui Province,ChinaProject(2022AH010053)supported by Excellent Scientific Research and Innovation Team of Universities in Anhui Province,ChinaProject(2022xscx080)supported by Anhui Provincial Department of Education Graduate Student Academic Innovation Fund,China。
文摘To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing system was used to conduct rock damage tests on sandstone with different support timing and strength paths.Based on the acoustic emission monitoring system,the spatial and temporal evolution characteristics of the whole process of rock body loaded instability under two stress paths were studied,and the mechanism of the reinforcing effect of stress support on the unloaded rock mass was analyzed.The results show that,within the scope of this study,both earlier applications of shoring and an increase in shoring strength can effectively improve the ultimate bearing capacity of the unloaded rock,which increases the ultimate bearing capacity of the unloaded rock mass by 60.31% and 54.96%,respectively;There is a phenomenon of rebound deformation of the rock mass during sudden changes in stress(single-sided unloading,stress support),which shows opposite expansion and compression platforms on the stress−strain curve;The crack evolution of unloaded rock under different stress support conditions shows the state law of"initial crack activation→middle steady state expansion→late main crack penetration",and the lagging support significantly accelerates the crack evolution from local activation to main penetration;The single-sided unloading and stress-supporting stages have less influence on the unloading deformationsσ_(1u),σ_(2u) and support deformationsσ_(1) t,σ_(2t) in theσ_(1) andσ_(2)directions,while they show significant response characteristics toσ_(3u),σ_(vu) and σ_(3) t,σ_(vt),and with the increase of the support strength,the stress-supporting stagesσ_(3) t,σ_(vt) gradually increase and exceed the deformations generated by the unloading stagesσ_(3u),σ_(vu);The increase of support strength can effectively compensate for the rock stress loss caused by unloading,which makes the maximum,minimum,and volumetric strain support coefficients during the loading and unloading of the rock body increase gradually while the effect on the intermediate principal strain support coefficient is small;During loading,the support strength of rock masses seeks a new bearing area by regulating stress equilibrium states.This process primarily manifests as a shift in the locations of the crushing zone and the main bearing area,accompanied by a corresponding transformation in failure patterns.Consequently,the rock mass transitions from asymmetric three-zone damage under no or weak support to approximate symmetric three-zone damage under strong support.Simultaneously,the main load-bearing area of the rock mass shifts from deep bearing in the unsupported to middle bearing under strong support as the support strength increases.
文摘This paper proposes a practical and framework-based approach to design an architecture transformation strategy and roadmap aiming to transform or modernize critical legacy enterprise systems.The approach is business value driven with IT supportability in terms of lower application operational and support costs,higher business value and shorter time to market of application delivery.The approach introduces a robust enterprise application architecture assessment framework with an emphasis on technical(internal)and strategic(external)perspectives to guide the application assessment and also a finance selfsupport transformation strategy to aid its transformation roadmap design.The approach was applied in multiple large enterprises successfully and received endorsements and positive feedback from the sponsors.The paper also presents a case study detailing the successful application of the approach to modernize an enterprise logistics transportation management system.
基金Project supported by the National Natural Science Foundation of China(Nos.52405095,12272089,and 92360305)the Guangdong Basic and Applied Basic Research Foundation of China(No.2023A1515110557)+4 种基金the Natural Science Foundation of Liaoning Province of China(No.2023-BSBA-102)the Open Fund of National Key Laboratory of Particle Transport and Separation Technology of China(No.WZKF-2024-6)the Open Project of Guangxi Key Laboratory of Automobile Components and Vehicle Technology of China(Nos.2024GKLACVTKF07 and 2024GKLACVTKF06)the Basic Research Projects of Liaoning Provincial Department of Education of China(No.JYTQN2023162)the Fundamental Research Funds for the Central Universities of China(No.N2403022)。
文摘The testing of large structures is limited by high costs and long cycles, making scaling methods an attractive solution. However, the scaling process of elastic rings introduces complexities in multi-parameter geometric distortions, leading to a diminution in the predictive accuracy of the distorted similitude. To address this challenge, this study formulates a novel set of scaling laws, tailored to account for the intricate geometric distortions associated with elastic rings. The proposed scaling laws are formulated based on the intrinsic deformation characteristics of elastic rings, rather than the traditional systemic governing equations. Numerical and experimental cases are conducted to assess the efficacy and precision of the proposed scaling laws, and the obtained results are compared with those achieved by traditional methods. The outcomes demonstrate that the scaling laws put forth by this study significantly enhance the predictive capabilities for deformations of elastic rings.
基金support for carrying out this work was provided by the Doctoral Research Foundation of Weifang University(2024BS20)Science and Technology Development Plan Foundation of Weifang(2024GX017).
文摘Photocatalytic nitrogen fixation (PNF) is a promising alternative to the Haber-Bosch process.It achieves green ammonia production by utilizing solar energy for nitrogen fixation under mild conditions.While nanoscale photocatalysts offer enhanced performance due to their high surface area and abundant active sites,their small size makes them difficult to recover and prone to agglomeration.These bottlenecks severely limit industrial application.A promising solution is to immobilize the catalysts onto support surfaces.This paper provides a systematic review of recent advances in the design of immobilized photocatalysts for ammonia synthesis.It begins by outlining the key benefits of immobilization strategies,particularly in improving catalyst stability,recyclability,and overall photocatalytic performance.The working mechanisms and features of various immobilization techniques are then categorized and explained,covering physical adsorption/deposition,chemical bonding,in situ growth,and hybrid physico-chemical methods.Supported materials and common substrate types are also summarized.Furthermore,the widely used configurations of photoreactors suitable for immobilized systems are introduced.Finally,the review identifies current research limitations and challenges,and offers perspectives on future developments in the field of immobilized photocatalysis.
基金Supported by the Sichuan Science and Technology Program(Grant Nos.2021YFD0211,2023ZDZX0011).
文摘Significant diurnal temperature variations in mountainous rack railways cause stiffness mismatches between the rack structure and simply supported bridges,leading to critical failures like bolt loosening and rack fractures.This study develops a dynamic model of the vehicle-rack-bridge system based on train-track-bridge interaction theory,integrating gear-rack meshing and wheel-rail contact mechanisms.The model analyzes the dynamic response of bridges with varying spans under combined thermal and dynamic loading.Numerical simulations,conducted using finite element analysis,reveal peak vibration accelerations of 1.3 m/s^(2)for the rack,3.0 m/s^(2)for the rail,1.2 m/s^(2)for the sleeper,and 0.1 m/s^(2)for the bridge,with maximum stresses of 3 MPa in the rack,8 MPa in the rail,and 25 MPa in connecting bolts.The results show significant span-dependent amplification of stress and strain in the rack system under thermo-mechanical loading,exceeding material strength limits at 60-meter spans.An innovative elastic connection method is proposed to mitigate stress concentrations effectively,en-hancing system durability.This study introduces a novel approach to modeling complex thermo-mechanical interactions in rack railway systems,validated through extensive simulations,and provides a practical solution for improving structural resilience,offering theoretical guidance for optimizing rack-bridge system design to ensure operational safety in extreme environmental conditions.
基金supported by the National Natural Science Foundation of China(12473085).
文摘The neutral surface of a concave thin mirror is too close to the mirror surface,which makes it difficult to effectively mount the flexible structure and increases the mirror surface shape error.To address this problem,we design a flexible support structure including connectors,a support plate,and flexible structures,and construct an equivalent mirror by installing connectors and a support plate on the back of the mirror.While ensuring that the neutral surface of the equivalent mirror is moved away from the mirror surface,we optimize the support structure so that the rotary center of the flexible structure is located on the neutral surface of the equivalent mirror,avoiding the tilting moment.Following design and modeling of the structure,we analyze the static and dynamic characteristics using a finite element simulation,finding a root-mean-square(RMS)value for the surface shape error of 9.28 nm under the coupled effects of 1g gravity load,4℃ temperature rise,and 0.005 mm unevenness assembly error,with a fundamental frequency of 170.75 Hz,which all meet the design requirements.Finally,we carry out a surface shape error test of the mirror assembly,confirming it to meet the design index requirement of the mirror assembly.Simulation and test results verify the reliability and effectiveness of our proposed support structure.
文摘Objective:To explore the clinical effect of personalized nutritional support in elderly women with gestational diabetes(GDM),and explore its impact on the incidence of maternal complications and pregnancy outcomes.Methods:A total of 90 elderly pregnant women with gestational diabetes who were delivered in our hospital from January 2023 to January 2024 were selected as the research objects.They were randomly divided into an observation group and a control group,with 45 cases in each group.The control group only received routine pregnancy care and basic nutrition guidance,while the observation group received personalized nutrition support on this basis.Compare the blood glucose control,incidence of pregnancy complications,pregnancy outcomes,and neonatal outcomes between two groups of parturient.Result:After intervention,the fasting blood glucose(FPG),2-hour postprandial blood glucose(2hPG),and glycated hemoglobin(HbA1c)of the observation group were significantly lower than those of the control group,and the differences were statistically significant(p<0.05);The incidence of complications such as gestational hypertension syndrome,polyhydramnios,premature rupture of membranes,and postpartum hemorrhage in the observation group was significantly lower than that in the control group,and the difference was statistically significant(p<0.05);The cesarean section rate in the observation group was significantly lower than that in the control group,and the incidence of adverse neonatal outcomes such as fetal distress,macrosomia,neonatal asphyxia,and neonatal hypoglycemia in the observation group was significantly lower than that in the control group,with statistical significance(p<0.05).Conclusion:Individualized nutritional support for elderly women with gestational diabetes can effectively improve the level of maternal blood sugar control,reduce the incidence of complications during pregnancy,and improve the outcome of pregnancy and neonatal outcomes,which is of high clinical value.
文摘YOU CANNOT SUCCUMB TO CHOLERA,unless the sewage system breaks down-likewise deaths from violence vanish,as long as emotional support networks are working properly.Gut hygiene eliminates the one,societal hygiene the other.Cholera was an inexorable plague-until Germ Theory was accepted and implemented.Violence too,will persist-until we agree and accept its equivalent in Societal Theory.The scientific method,especially Quantum Physics,sabotages philosophy-it cannot cope with the living fact that the elephant in the room is alive.Quantum Mechanics describes itself as being(1)more incomprehensible,(2)weirder,and(3)more uncertain than anything we’ve met before.But that’s chickenfeed,compared to what you find in clinical medicine,which though portrayed as being intrinsically woolly and subjective,wilfully aims to enhance life,whatever that might be.
基金supported by the Gansu Provincial Natural Science Foundation(grant number 25JRRA074)the Gansu Provincial Key R&D Science and Technology Program(grant number 24YFGA060)the National Natural Science Foundation of China(grant number 62161019).
文摘Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural networks learn new classes sequentially,they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes.This challenge,which lies at the core of class-incremental learning,severely limits the deployment of continual learning systems in real-world applications with streaming data.Existing approaches,including rehearsalbased methods and knowledge distillation techniques,have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features under limited memory constraints.To overcome these limitations,we propose a support vector-guided framework for class-incremental learning.The framework integrates an enhanced feature extractor with a Support Vector Machine classifier,which generates boundary-critical support vectors to guide both replay and distillation.Building on this architecture,we design a joint feature retention strategy that combines boundary proximity with feature diversity,and a Support Vector Distillation Loss that enforces dual alignment in decision and semantic spaces.In addition,triple attention modules are incorporated into the feature extractor to enhance representation power.Extensive experiments on CIFAR-100 and Tiny-ImageNet demonstrate effective improvements.On CIFAR-100 and Tiny-ImageNet with 5 tasks,our method achieves 71.68%and 58.61%average accuracy,outperforming strong baselines by 3.34%and 2.05%.These advantages are consistently observed across different task splits,highlighting the robustness and generalization of the proposed approach.Beyond benchmark evaluations,the framework also shows potential in few-shot and resource-constrained applications such as edge computing and mobile robotics.
文摘In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative spam detection method utilizing the Horse Herd Optimization Algorithm(HHOA),designed for binary classification within multi⁃objective framework.The method proficiently identifies essential features,minimizing redundancy and improving classification precision.The suggested HHOA attained an impressive accuracy of 97.21%on the Kaggle email dataset,with precision of 94.30%,recall of 90.50%,and F1⁃score of 92.80%.Compared to conventional techniques,such as Support Vector Machine(93.89%accuracy),Random Forest(96.14%accuracy),and K⁃Nearest Neighbours(92.08%accuracy),HHOA exhibited enhanced performance with reduced computing complexity.The suggested method demonstrated enhanced feature selection efficiency,decreasing the number of selected features while maintaining high classification accuracy.The results underscore the efficacy of HHOA in spam identification and indicate its potential for further applications in practical email filtering systems.
基金supported by the 2023 Key Project of Guizhou Philosophy and Social Science Planning(Grant No.23GZZD22).
文摘With the global expansion of protected areas(PAs)and increasing involvement of indigenous communities,understanding their impacts on indigenous peoples is crucial.This study evaluates the extent to which China’s national cultural ecological protection areas(CEPAs)safeguard indigenous culture,using land-use disturbance as a key metric to assess impacts on cultural keystone species(CKS).We employ a multi-step evaluation framework that reclassifies land use,identifies environment-dependent CKS,and analyzes land-use dynamics by comparing disturbances before and after CEPAs establishment.Our results reveal that,despite overall improvements in land conditions,over 36%of CEPAs are in land disturbance threat or warning status.All of these sites are indigenous CEPAs,indicating a disproportionate disturbance burden on indigenous communities.Notably,traditional medicinal practices are particularly vulnerable.These findings underscore the urgent need for policies aligning ecological diversity with cultural diversity to support the global commitment to expand PAs to over 30%of Earth’s land and oceans by 2030.
基金supported by the China Agriculture Research System of MOF and MARAthe National Natural Science Foundation of China (31872337 and 31501919)the Agricultural Science and Technology Innovation Project,China (ASTIP-IAS02)。
文摘The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.
基金Da Nang University of Medical Technology and PharmacyDa Nang C Hospital for the invaluable support they provided in facilitating this research。
文摘Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.
文摘This study investigated the effects of parental involvement,parenting stress,and social support on the social skills of school-aged children(6-18 years old)with intellectual disabilities(ID).Data were collected from 280 Chinese parents(mothers=70.0%,fathers=30.0%)of children with ID through purposive sampling and analyzed using partial least squares structural equation modeling(PLS-SEM).The results indicated that parental involvement not only directly enhanced children’s social skills but also indirectly improved them by alleviating parenting stress,which acted as a partial mediator.Contrary to the stress-buffering hypothesis,social support did not moderate the negative impact of parenting stress on social skills.Theoretically,this study contributes by validating ecological systems theory through a shift in focus from individual deficits to family systems,while also challenging the conventional view of stress-buffering theory.Accordingly,parent-support programs should integrate practical involvement training with systematic stress reduction and provide tailored assistance such as behavior-management training and respite care.
文摘On New Year’s Eve,Chinese President Xi Jinping delivered his 2026 New Year message via China Media Group and online platforms.The address signals China’s continued support for the aspirations of the Global South,offering political and moral backing at a time of heightened global uncertainty.
文摘Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.
基金funded by the National Key R&D Program of China,China(No.2024YFF0507903)the National Key Research and Development Program of China(Grant No.2024YFF0507904)the National Natural Science Foundation of China,China(Grant No.52379114).These supports are gratefully acknowledged.
文摘In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.
文摘Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,Bukyiende Subcounty in Uganda where he has been cultivating plantain,coffee and Irish potatoes for the past 16 years.
基金supported in part by the National Natural Science Foundation of China(Nos.52475550,52305095)in part by the Key R&D Project of Liaoning Province,China(No.2023JH2/101800026)。
文摘Under the condition of frequent replacement of wind tunnel models,multiple types of wind tunnel models are fixed by a slender support sting with low stiffness damping.When excited by wind load,various models produce random multi-dimensional vibration with different characteristics,which makes it impossible to obtain accurate and efficient aerodynamic data.Therefore,in order to ensure the reliable and efficient conduction of wind tunnel test,a wind-tunnel-modeladaptive vibration control method is proposed in this paper.First,the split type adaptive vibration suppression structure is designed.Second,the multi-dimensional vibration characteristic characterization method is derived and the vibration characteristic identification method of the system is designed.Then,a vibration state estimation model is established according to the identification results of vibration characteristics,and a multi-actuator cooperative control method based on vibration state estimation is constructed.Finally,a model-adaptive vibration control system is built,and vibration characteristics identification and hammer experiments are carried out for two types of typical models.The results show that the proposed model-adaptive vibration control method increases the equivalent damping ratio of pitch and yaw dimensions of the high-aspect-ratio class model by 8.19 times and 48.81 times,respectively.The equivalent damping ratio of pitch and yaw dimensions of the highslenderness-ratio class model is increased by 16.44 and 5.43 times,respectively.It provides a strong guarantee for the reliable and efficient development of multi-type wind tunnel test tasks.
