In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD...In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.展开更多
With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medici...With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.展开更多
Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effect...Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.展开更多
The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor depositio...The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.展开更多
Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordina...Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the...Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.展开更多
Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factor...Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.展开更多
This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic hea...The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic heat.However,its longterm changes in subduction rate and volume in response to shifting climate conditions are unclear.In this study,we investigated the long-term trend of the subduction rate and volume of the South Pacific–SAMW(SPSAMW)using Simple Ocean Data Assimilation outputs during 1980–2017.The results show the overall increasing trend of the subduction rate of the SPSAMW.The increased subduction of the SPSAMW directly contributes to the volume variation in the SPSAMW.The increased subduction in the South Pacific reached(0.28±0.16)Sv-1 per year,which explains nearly 68%of the volume increase in the SPSAMW.This variability in the SPSAMW reflects alterations in the overlying atmosphere.The positive to negative phase change of the Interdecadal Pacific Oscillation(IPO)in 1980–2017 deepened the Amundsen Sea Low(ASL)via atmospheric teleconnections over the South Pacific.Further analysis reveals that the increased westerly winds during the deepening of ASL resulted in more cold water transport from the south,which deepened the winter mixed layer and thus increased subduction and volume within the SPSAMW subduction region.This finding suggests the association of the long-term trends of SPSAMW subduction and volume with the phase change of the IPO.展开更多
The spatial organization of urban-rural systems is fundamentally shaped by the agglomeration and diffusion effects inherent in human-Earth processes,giving rise to distinct gradient-based and hierarchical structures.U...The spatial organization of urban-rural systems is fundamentally shaped by the agglomeration and diffusion effects inherent in human-Earth processes,giving rise to distinct gradient-based and hierarchical structures.Understanding the complexity of these interactions and their multidimensional drivers is essential for deciphering the mechanisms of integrated urban-rural development.Here,we apply a novel hierarchical spatial system framework based on the human-Earth system,combining social network analysis and multi-level modeling,to examine the evolution of the socio-spatial structure in the Beijing-Tianjin-Hebei region from 2000 to 2020.We developed a comprehensive evaluation system spanning economic,social,environmental,and infrastructural dimensions to characterize spatial patterns across multiple network levels,including city clusters,metropolitan areas,municipal-counties,towns,and villages.Our analysis reveals three key findings:First,the density of foundational network connections increased significantly,reflecting a trend toward spatial concentration driven by policy-led regional integration.Second,network structures at the city-cluster and metropolitan scales exhibited a pattern of“initial expansion followed by convergence”,accompanied by notable shifts in their spatial centers of gravity.In parallel,differentiated patterns of agglomeration and expansion were evident in the township-and village-level networks of Baoding,Tangshan,and Handan,while village-level networks in Anxin,Quyang,and other locations demonstrated distinct developmental trends.Third,community structures demonstrated strong functional homophily and interactive cohesion across multiple dimensions,with metropolitan and township communities undergoing restructuring that reflects a reconfiguration of cross-level influence and functional coupling.Spatially,the system manifests as a gradient structure of interwoven point,line,and area networks,establishing a mechanism for functional differentiation and transmission from rural to urban areas.This study provides theoretical foundations and methodological support for understanding the spatial organization logic of integrated urban-rural development,offering practical reference value for advancing regional coordination and rural revitalization in a scientifically informed manner.展开更多
Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combin...Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.展开更多
In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-pin...In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.展开更多
In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction...In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.展开更多
Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluatio...Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.展开更多
The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then t...The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.展开更多
Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc es...Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.展开更多
With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental qua...With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.展开更多
Security is an important component in the process of developing healthcare web applications.We need to ensure security maintenance;therefore the analysis of healthcare web application’s security risk is of utmost imp...Security is an important component in the process of developing healthcare web applications.We need to ensure security maintenance;therefore the analysis of healthcare web application’s security risk is of utmost importance.Properties must be considered to minimise the security risk.Additionally,security risk management activities are revised,prepared,implemented,tracked,and regularly set up efficiently to design the security of healthcare web applications.Managing the security risk of a healthcare web application must be considered as the key component.Security is,in specific,seen as an add-on during the development process of healthcare web applications,but not as the key problem.Researchers must ensure that security is taken into account right from the earlier developmental stages of the healthcare web application.In this row,the authors of this study have used the hesitant fuzzy-based AHP-TOPSIS technique to estimate the risks of various healthcare web applications for improving security-durability.This approach would help to design and incorporate security features in healthcare web applications that would be able to battle threats on their own,and not depend solely on the external security of healthcare web applications.Furthermore,in terms of healthcare web application’s security-durability,the security risk variable is measured,and vice versa.Hence,the findings of our study will also be useful in improving the durability of several web applications in healthcare.展开更多
文摘In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.
基金supported by the National Natural Science Foundation of China(Grant 62293545)Shenzhen Science and Technology Program(Grant ZDSYS20220323112000001).
文摘With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.Ashit Kumar Dutta would like to thank AlMaarefa University for supporting this research under project number MHIRSP2025017.
文摘Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3608602)the National Natural Science Foundation of China(Grant Nos.62404215 and 62574199)Instrument and Equipment Development Project of CAS(Grant No.PTYQ2024TD0003)。
文摘The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.
基金supported by the National Natural Science Foundation of China(Grants 42374215,42230209,42374199,42304183,42422406,42174185,72061147004 and 72342001)the Science and Technology Development Fund,Macao SAR(File no.0042/2024/RIA1 and 0008/2024/AKP)+1 种基金the Natural Science Foundation of Hunan Province(Grant 2023JJ20038)the Research Project of Science and Technology of Hunan Province(2025JJ10009,2022RC4025,2025QK1004,2023JJ50312,2023JJ50010 and 2024RC9012).
文摘Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number-ber 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Admin-istration Climate Change Special Program[grant number QBZ202303]。
文摘Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.
基金the funding provided by the China Scholarship Council(Grant No.201804910634)the Ecology Fund of the Royal Netherlands Academy of Arts and Sciences(KNAWWF/807/19039)to Deyi Wang.
文摘Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金supported by the National Natural Science Foundation of China(Nos.42406256,42376034,and 42430402)the Qingdao Postdoctoral Application Research Project(No.QDBSH20220202152)+1 种基金the National Key R&D Program of China(No.2018YFA0605701)the Chinese Arctic and Antarctic Administration(No.IRASCC2020-2022-02-01-03)。
文摘The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic heat.However,its longterm changes in subduction rate and volume in response to shifting climate conditions are unclear.In this study,we investigated the long-term trend of the subduction rate and volume of the South Pacific–SAMW(SPSAMW)using Simple Ocean Data Assimilation outputs during 1980–2017.The results show the overall increasing trend of the subduction rate of the SPSAMW.The increased subduction of the SPSAMW directly contributes to the volume variation in the SPSAMW.The increased subduction in the South Pacific reached(0.28±0.16)Sv-1 per year,which explains nearly 68%of the volume increase in the SPSAMW.This variability in the SPSAMW reflects alterations in the overlying atmosphere.The positive to negative phase change of the Interdecadal Pacific Oscillation(IPO)in 1980–2017 deepened the Amundsen Sea Low(ASL)via atmospheric teleconnections over the South Pacific.Further analysis reveals that the increased westerly winds during the deepening of ASL resulted in more cold water transport from the south,which deepened the winter mixed layer and thus increased subduction and volume within the SPSAMW subduction region.This finding suggests the association of the long-term trends of SPSAMW subduction and volume with the phase change of the IPO.
基金supported by the National Natural Science Foundation of China(Grant Nos.42293270,42530712)the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.42401334).
文摘The spatial organization of urban-rural systems is fundamentally shaped by the agglomeration and diffusion effects inherent in human-Earth processes,giving rise to distinct gradient-based and hierarchical structures.Understanding the complexity of these interactions and their multidimensional drivers is essential for deciphering the mechanisms of integrated urban-rural development.Here,we apply a novel hierarchical spatial system framework based on the human-Earth system,combining social network analysis and multi-level modeling,to examine the evolution of the socio-spatial structure in the Beijing-Tianjin-Hebei region from 2000 to 2020.We developed a comprehensive evaluation system spanning economic,social,environmental,and infrastructural dimensions to characterize spatial patterns across multiple network levels,including city clusters,metropolitan areas,municipal-counties,towns,and villages.Our analysis reveals three key findings:First,the density of foundational network connections increased significantly,reflecting a trend toward spatial concentration driven by policy-led regional integration.Second,network structures at the city-cluster and metropolitan scales exhibited a pattern of“initial expansion followed by convergence”,accompanied by notable shifts in their spatial centers of gravity.In parallel,differentiated patterns of agglomeration and expansion were evident in the township-and village-level networks of Baoding,Tangshan,and Handan,while village-level networks in Anxin,Quyang,and other locations demonstrated distinct developmental trends.Third,community structures demonstrated strong functional homophily and interactive cohesion across multiple dimensions,with metropolitan and township communities undergoing restructuring that reflects a reconfiguration of cross-level influence and functional coupling.Spatially,the system manifests as a gradient structure of interwoven point,line,and area networks,establishing a mechanism for functional differentiation and transmission from rural to urban areas.This study provides theoretical foundations and methodological support for understanding the spatial organization logic of integrated urban-rural development,offering practical reference value for advancing regional coordination and rural revitalization in a scientifically informed manner.
基金supported by the Zhenjiang Key R&D Plan(GY2021009)Lianyungang City Major Technology Breakthrough(CGJBGS2104)+2 种基金National Natural Science Foundation of China under Grant(12302456)National Key Laboratory Foundation of Science and Technology on Materials under Shock and Impact under Grant(6142902241601)China Postdoctoral Science Foundation under Grants(2025M774217)。
文摘Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.
基金funded by the National Natural Science Foundation of China,grant number U24A20135Inner Mongolia Natural Science Foundation major project,grant number 2023ZD12+7 种基金Inner Mongolia Autonomous Region key research and development and achievement transformation plan project,grant number 2023YFHH0090Natural Science Foundation of Inner Mongolia,grant number 2022MS05006Inner Mongolia Autonomous Region Talent Development FundUniversity basic research business expenses,grant number 2023RCTD012University basic research business expenses,grant number 2023QNJS075Postgraduate Research Innovation Program and of Inner Mongolia Autonomous Region,grant number KC2024053BUniversity basic research business expenses,grant number 2024YXXS012National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology,grant number GZ2023KF012.
文摘In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.
基金The Planning Program of Science and Technology of Ministry of Housing and Urban-Rural Development of China (No. 2010-K5-16)
文摘In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.
基金Supported by the Science and Technology Support Key Project of Jiangsu Province (DE2008365)~~
文摘Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.
文摘Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.
基金Shanghai Leading Academic Discipline Project (T0502)Shanghai Municipal Educational Commission Project (05EZ32).
文摘With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.
基金Funding for this study was received from the Ministry of Education and Deanship of Scientific Research at King Abdulaziz University,Kingdom of Saudi Arabia under Grant No.IFPHI-286-611-2020.
文摘Security is an important component in the process of developing healthcare web applications.We need to ensure security maintenance;therefore the analysis of healthcare web application’s security risk is of utmost importance.Properties must be considered to minimise the security risk.Additionally,security risk management activities are revised,prepared,implemented,tracked,and regularly set up efficiently to design the security of healthcare web applications.Managing the security risk of a healthcare web application must be considered as the key component.Security is,in specific,seen as an add-on during the development process of healthcare web applications,but not as the key problem.Researchers must ensure that security is taken into account right from the earlier developmental stages of the healthcare web application.In this row,the authors of this study have used the hesitant fuzzy-based AHP-TOPSIS technique to estimate the risks of various healthcare web applications for improving security-durability.This approach would help to design and incorporate security features in healthcare web applications that would be able to battle threats on their own,and not depend solely on the external security of healthcare web applications.Furthermore,in terms of healthcare web application’s security-durability,the security risk variable is measured,and vice versa.Hence,the findings of our study will also be useful in improving the durability of several web applications in healthcare.
