In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.展开更多
A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the ...A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.展开更多
In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjuste...In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjusted with the CMYK printing ink volume variation of the single,double and triple channels in the given 280%total ink limit conditions.A larger number of color vision normal observers were organized to carry out the color preference evaluation experiment,and the selected preferred skin colors were analyzed.The distribution range of the chromaticity values for skin color images were obtained and the results indicated that there are three regions for printing skin color preferences,and the observers have a memory preference for brighter,fairer skin colors in young female and a reddish skin colors in girl,which can provide the guidance for color adjustment of printed skin color images.展开更多
By using the Chinese stock market data from 2018 to 2024,the weak association between structural trends stocks and market index under investors’preference effect in trading cause the market is lack of liquidity and m...By using the Chinese stock market data from 2018 to 2024,the weak association between structural trends stocks and market index under investors’preference effect in trading cause the market is lack of liquidity and more likely to be dominated by structural trends,as in this market,the willingness to engage in passive trading exceeds that for active trading and investors’preference easy to reverse toward market volatility.The lack of incremental capital in the market often leads to sector-specific rallies rather than broad-based increases,which is one of the key reasons why the Chinese stock market has struggled to achieve overall growth over the long-term period.展开更多
Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivat...Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies.Methods A discrete choice experiment was conducted in nine provinces across China.Seven key attributes were identified to analyze the job preferences of CDC workers.Mixed logit models,latent class models,and policy simulation tools were used.Results A valid sample of 5,944 cases was included in the analysis.All seven attributes significantly influenced the job choices of CDC workers.Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility.Income-prioritizers were concerned with income and opportunities for career development,whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits.The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives.Conclusion Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers.Heterogeneity in job preferences was also identified.Based on the preference characteristics of different subgroups,policy content should be skewed to differentiate the importance of incentives.展开更多
The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeogr...The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeographic studies(Wagner and Liebherr 1992;Peeters and Ito 2001;Helms 2018).展开更多
Two widespread bird species in Sri Lanka’s dry zone,Pycnonotus cafer(Red-vented Bulbul,RVBB)and Pycnonotus luteolus(White-browed Bulbul,WBBB),were studied to understand their foraging dynamics and ecology.The researc...Two widespread bird species in Sri Lanka’s dry zone,Pycnonotus cafer(Red-vented Bulbul,RVBB)and Pycnonotus luteolus(White-browed Bulbul,WBBB),were studied to understand their foraging dynamics and ecology.The research was conducted from October 2022 to February 2023 in Mihintale Sanctuary(80.30′11.24″E,8.21′04.63″N)and the Faculty of Applied Sciences,Rajarata University of Sri Lanka(80.502206″E,8.353090″N).Data were obtained through focal sampling,opportunistic observations,and mist netting.Both species predominantly foraged on twigs,using gleaning as the dominant food-handling technique.RVBB foraged mostly at the canopy level,while WBBB foraged primarily at the sub-canopy level.Fruits constituted the major food type for both species.RVBB and WBBB utilized 10 and 7 plant species,respectively,with Grewia helicterifolia being the primary foraging plant.Minimal foraging was observed on Croton sp.(RVBB)and Hugonia mistax(WBBB).The correlation between nutritional components and the consumption of both species revealed a preference for foods with lower protein,higher fat,and ash content.There was no linear correlation between gape width and fruit size(r=-0.21,P=0.69)for both species.The standardized dietary niche breadth indicated both species are specialists,with a high pairwise dietary niche overlap(0.9854).These findings highlight the niche-specific foraging adaptations of RVBB and WBBB within Mihintale,emphasizing their distinct strategies in utilizing plant species,fruit sizes,and foraging heights.Understanding such ecological dynamics is essential for habitat conservation efforts and ensuring the availability of key foraging resources for these species in the dry zone.展开更多
With the increasing complexity of hotel selection,traditional decision-making models often struggle to account for uncertainty and interrelated criteria.Multi-criteria decision-making(MCDM)techniques,particularly thos...With the increasing complexity of hotel selection,traditional decision-making models often struggle to account for uncertainty and interrelated criteria.Multi-criteria decision-making(MCDM)techniques,particularly those based on fuzzy logic,provide a robust framework for handling such challenges.This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets(C-IFS)by combining three distinct methodologies:Weighted Aggregated Sum Product Assessment(WASPAS),an Alternative Ranking Order Method Accounting for Two-Step Normalization(AROMAN),and the CRITIC method(Criteria Importance Through Inter-criteria Correlation).To address the dynamic nature of traveler preferences in hotel selection,the study employs a comprehensive set of criteria encompassing aspects such as location proximity,amenities,pricing,customer reviews,environmental impact,safety,booking flexibility,and cultural experiences.The CRITIC method is used to determine the importance of each criterion by assessing intercriteria correlations.AROMAN is employed for the systematic evaluation of alternatives,considering their additive relationships and providing a weighted assessment.WASPAS further analyzes the results obtained from AROMAN,incorporating both positive and negative aspects for a comprehensive evaluation.The integration of C-IFS enhances the model’s ability to manage uncertainty and imprecision in the decision-making process.Through a case study,we demonstrate the effectiveness of this integrated approach,offering decision-makers valuable insights for selecting the most suitable hotel option in alignment with the diverse preferences of contemporary travelers.This research contributes to the evolving field of decision science by showcasing the practical applicability of these methodologies within a C-IFS framework for complex decision scenarios.展开更多
Objective Although dietary preferences influence chronic diseases,few studies have linked dietary preferences to mortality risk,particularly in large cohorts.To investigate the relationship between dietary preferences...Objective Although dietary preferences influence chronic diseases,few studies have linked dietary preferences to mortality risk,particularly in large cohorts.To investigate the relationship between dietary preferences and mortality risk(all-cause,cancer,and cardiovascular disease[CVD])in a large adult cohort.Methods A cohort of 1,160,312 adults(mean age 62.48±9.55)from the Shenzhen Healthcare Big Data Cohort(SHBDC)was analyzed.Hazard ratios(HRs)for mortality were estimated using the Cox proportional hazards model.Results The study identified 12,308 all-cause deaths,of which 3,865(31.4%)were cancer-related and 3,576(29.1%)were attributed to CVD.Compared with a mixed diet of meat and vegetables,a mainly meat-based diet(hazard ratio[HR]=1.13;95%confidence interval[CI]:1.02,1.27)associated with a higher risk of all-cause mortality,while mainly vegetarian(HR=0.87;95%CI:0.78,0.97)was linked to a reduced risk.Furthermore,there was a stronger correlation between mortality risk and dietary preference in the>65 age range.Conclusion A meat-based diet was associated with an increased risk of all-cause mortality,whereas a mainly vegetarian diet was linked to a reduced risk.展开更多
Plant roots interact with diverse fungi that are essential for maintaining the productivity and sustainability of pasture ecosystems,but how these root-associated fungi(RAF)differ between forage species and how they r...Plant roots interact with diverse fungi that are essential for maintaining the productivity and sustainability of pasture ecosystems,but how these root-associated fungi(RAF)differ between forage species and how they respond to nutrient enrichment and fungicide application are not well understood.Here,we constructed an 11-year experiment involving fungicide application(with or without)nested within four levels of experimental nitrogen(N)addition treatments in an alpine pasture,and the RAF communities,root traits,tissue nutrients,and shoot biomass of two dominant forage species(Carex capillifolia and Elymus nutans)were analyzed.The RAF community composition showed striking differences between the plant species and was strongly affected by both N addition level and fungicide applications.Fungicide,but not N application,dramatically reduced the RAF richness of all functional guilds in both plant species,and fungicide also simplified the co-occurrence network of the RAF for C.capillifolia.The RAF community correlated strongly with root traits,whereas their relationships became weakened or even vanished at the level of the individual plant species.The importance of RAF to plant nutrients and productivity varied between plant species,with significant contributions in C.capillifolia but not in E.nutans.This is the first report elucidating the long-term effect of fungicides on RAF in alpine pastures,and our findings emphasize the host-specific responses of RAF community structure and function to anthropogenic disturbances.展开更多
Objective:To investigate the preference characteristics and relative importance of each core factor in the teaching program for undergraduate nursing students during clinical practice,and to provide empirical support ...Objective:To investigate the preference characteristics and relative importance of each core factor in the teaching program for undergraduate nursing students during clinical practice,and to provide empirical support for the creation of a student-centered,formalized clinical teaching system that meets the actual needs of nursing students.Methods:The quantitative research method of discrete choice experiment was adopted,and the questionnaire was designed based on the random utility theory.Through a systematic literature review,semi-structured interviews,and two rounds of Delphi expert consultations,six core attributes of the instructor,namely educational qualifications,teaching methods,frequency of individualized guidance,operational practice opportunities,feedback timeliness,and instructor title,and their corresponding levels were determined.The study period was from January 2024 to January 2025,and 158 undergraduate nursing students who chose to intern at Deyang People’s Hospital were selected as the research subjects.A survey tool with 12 choice sets was created using Ngene software,and then statistical analysis was performed on the obtained data using the conditional Logit model to measure the impact of each attribute on the choice behavior of nursing students.Results:The results showed that the conditional Logit model fitted well(likelihood ratio chi-square=85.32,p<0.001).The analysis results indicated that the most important teaching attributes for undergraduate nursing students were,in order:the academic qualifications of the teaching instructor(master vs.Junior college,β=0.42,p<0.01),individualized guidance frequency(daily vs.Weekly,β=0.38,p<0.01),operational practice opportunities(more vs.less,β=0.31,p<0.05),and the timeliness of feedback(timely versus delayed,β=0.29,p<0.05).The influence of the title of the instructor was not statistically significant(p>0.05).Conclusion:Undergraduate nursing students show a clear and systematic preference structure for clinical teaching,with a high expectation of frequent personalized guidance from highly educated teachers,as well as sufficient operational opportunities and timely teaching feedback.展开更多
Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a fr...Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.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
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.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
In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternati...In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.展开更多
In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web page...In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web pages in accordance with user preferences is proposed.PWPR assigns the initial weights based on user interests and creates the virtual links and hubs according to user interests.By measuring user click streams,PWPR incrementally reflects users’ favors for the personalized ranking.To improve the accuracy of ranking, PWPR also takes collaborative filtering into consideration when the query with similar is submitted by users who have similar user interests. Detailed simulation results and comparison with other algorithms prove that the proposed PWPR can adaptively provide personalized ranking and truly relevant information to user preferences.展开更多
Many agricultural landscapes have been formed through the interaction and co-evolution of nature and people, and represent the living landscapes shaped over time through intensive and continuous human cultivation. Ter...Many agricultural landscapes have been formed through the interaction and co-evolution of nature and people, and represent the living landscapes shaped over time through intensive and continuous human cultivation. Terraced paddy fields are being re-evaluated to take into account the multiple functions they fill beyond only rice cultivation, particularly their contribution to the national biodiversity strategy of Japan. Since the 1990 s, terraced paddy fields have been considered a representative cultural landscape of Japan and, at the same time, multi-stakeholder conservation activities have been conducted throughout Japan to reverse the increasing abandonment of terraces. Shiroyone Senmaida is an outstanding cultural landscape and a major tourist attraction in Noto Peninsula, Ishikawa Prefecture, which was designated through an initiative by the Food and Agriculture Organization(FAO) as a Globally Important Agricultural Heritage Systems(GIAHS) pilot site in 2011. It is important to clarify tourist preference for terraced paddy field landscapes to contribute to future policy making toward improved agricultural landscape conservation. A key finding of this study is that tourists visiting toenjoy the agricultural landscape are also concerned on the sustainability of the farming methods and preferred to maintain the naturalness of the landscape. Respondents with higher educational levels and greater concern for the biological and traditional farming knowledge aspects of the rice terraces were also more inclined to favor sustainable farming practices. Tourists preferred to maintain the naturalness and rurality of the agricultural landscape, and indicated that construction of excessive tourist facilities would cause the landscape to deteriorate. It was suggested that the local community and surroundings, including rural settlements, hills, and forests, should also be conserved together with the scenic terrace.展开更多
As a physical model, the cellular automata （CA） model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees＇ walk preferences nor psychological status, and the...As a physical model, the cellular automata （CA） model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees＇ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees＇ walk preference and how evacuee＇s psychology influences their behaviors are introduced into this model. Evacuees＇ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants.展开更多
Case-based reasoning(CBR) is one of the best methods for generating an effective solution in an emergency. In recent years, some methods for generating emergency alternatives have been included in practical CBR applic...Case-based reasoning(CBR) is one of the best methods for generating an effective solution in an emergency. In recent years, some methods for generating emergency alternatives have been included in practical CBR applications, but there have been no in-depth studies of these processes. In this study,we propose a new method for dynamic case retrieval with subjective preferences and objective information, which considers the personal preferences of the decision makers and changes in the attributes of the emergency as the situation develops. First,we present a formula for calculating the case similarity and changing trends in the case considered, where similar cases are obtained. Next, we describe a method for measuring the overall assessment value with respect to similar historical cases, which is obtained by aggregating the case similarity, the utility case similarity, the first response time, and the implementation effect.The subjective preferences and objective information are also integrated in the decision-making process. Finally, we present a case study based on the emergency response to a fire in a highrise building, which illustrates the applicability and feasibility of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
基金supported by the National Natural Science Foundation of China (60904059 60975049)+1 种基金the Philosophy and Social Science Foundation of Hunan Province (2010YBA104)the National High Technology Research and Development Program of China (863 Program)(2009AA04Z107)
文摘A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.
文摘In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjusted with the CMYK printing ink volume variation of the single,double and triple channels in the given 280%total ink limit conditions.A larger number of color vision normal observers were organized to carry out the color preference evaluation experiment,and the selected preferred skin colors were analyzed.The distribution range of the chromaticity values for skin color images were obtained and the results indicated that there are three regions for printing skin color preferences,and the observers have a memory preference for brighter,fairer skin colors in young female and a reddish skin colors in girl,which can provide the guidance for color adjustment of printed skin color images.
文摘By using the Chinese stock market data from 2018 to 2024,the weak association between structural trends stocks and market index under investors’preference effect in trading cause the market is lack of liquidity and more likely to be dominated by structural trends,as in this market,the willingness to engage in passive trading exceeds that for active trading and investors’preference easy to reverse toward market volatility.The lack of incremental capital in the market often leads to sector-specific rallies rather than broad-based increases,which is one of the key reasons why the Chinese stock market has struggled to achieve overall growth over the long-term period.
基金supported by the Major Program of the National Social Science Foundation of China(no.2022YFC3600801)the Operation of Public Health Emergency Response Mechanisms of the Chinese Center for Disease Control and Prevention(no.102393220020010000017)。
文摘Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies.Methods A discrete choice experiment was conducted in nine provinces across China.Seven key attributes were identified to analyze the job preferences of CDC workers.Mixed logit models,latent class models,and policy simulation tools were used.Results A valid sample of 5,944 cases was included in the analysis.All seven attributes significantly influenced the job choices of CDC workers.Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility.Income-prioritizers were concerned with income and opportunities for career development,whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits.The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives.Conclusion Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers.Heterogeneity in job preferences was also identified.Based on the preference characteristics of different subgroups,policy content should be skewed to differentiate the importance of incentives.
基金funded by the“Departments of Excellence”program of the Italian Ministry for University and Research(MIUR,2018-2022 and MUR,2023-2027).
文摘The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeographic studies(Wagner and Liebherr 1992;Peeters and Ito 2001;Helms 2018).
文摘Two widespread bird species in Sri Lanka’s dry zone,Pycnonotus cafer(Red-vented Bulbul,RVBB)and Pycnonotus luteolus(White-browed Bulbul,WBBB),were studied to understand their foraging dynamics and ecology.The research was conducted from October 2022 to February 2023 in Mihintale Sanctuary(80.30′11.24″E,8.21′04.63″N)and the Faculty of Applied Sciences,Rajarata University of Sri Lanka(80.502206″E,8.353090″N).Data were obtained through focal sampling,opportunistic observations,and mist netting.Both species predominantly foraged on twigs,using gleaning as the dominant food-handling technique.RVBB foraged mostly at the canopy level,while WBBB foraged primarily at the sub-canopy level.Fruits constituted the major food type for both species.RVBB and WBBB utilized 10 and 7 plant species,respectively,with Grewia helicterifolia being the primary foraging plant.Minimal foraging was observed on Croton sp.(RVBB)and Hugonia mistax(WBBB).The correlation between nutritional components and the consumption of both species revealed a preference for foods with lower protein,higher fat,and ash content.There was no linear correlation between gape width and fruit size(r=-0.21,P=0.69)for both species.The standardized dietary niche breadth indicated both species are specialists,with a high pairwise dietary niche overlap(0.9854).These findings highlight the niche-specific foraging adaptations of RVBB and WBBB within Mihintale,emphasizing their distinct strategies in utilizing plant species,fruit sizes,and foraging heights.Understanding such ecological dynamics is essential for habitat conservation efforts and ensuring the availability of key foraging resources for these species in the dry zone.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2025R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia+1 种基金supported by the Researchers Supporting Project Number(UM-DSR-IG-2023-07)Almaarefa University,Riyadh,Saudi Arabia.
文摘With the increasing complexity of hotel selection,traditional decision-making models often struggle to account for uncertainty and interrelated criteria.Multi-criteria decision-making(MCDM)techniques,particularly those based on fuzzy logic,provide a robust framework for handling such challenges.This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets(C-IFS)by combining three distinct methodologies:Weighted Aggregated Sum Product Assessment(WASPAS),an Alternative Ranking Order Method Accounting for Two-Step Normalization(AROMAN),and the CRITIC method(Criteria Importance Through Inter-criteria Correlation).To address the dynamic nature of traveler preferences in hotel selection,the study employs a comprehensive set of criteria encompassing aspects such as location proximity,amenities,pricing,customer reviews,environmental impact,safety,booking flexibility,and cultural experiences.The CRITIC method is used to determine the importance of each criterion by assessing intercriteria correlations.AROMAN is employed for the systematic evaluation of alternatives,considering their additive relationships and providing a weighted assessment.WASPAS further analyzes the results obtained from AROMAN,incorporating both positive and negative aspects for a comprehensive evaluation.The integration of C-IFS enhances the model’s ability to manage uncertainty and imprecision in the decision-making process.Through a case study,we demonstrate the effectiveness of this integrated approach,offering decision-makers valuable insights for selecting the most suitable hotel option in alignment with the diverse preferences of contemporary travelers.This research contributes to the evolving field of decision science by showcasing the practical applicability of these methodologies within a C-IFS framework for complex decision scenarios.
基金supported by the National Natural Science Foundation of China(No.82425052).
文摘Objective Although dietary preferences influence chronic diseases,few studies have linked dietary preferences to mortality risk,particularly in large cohorts.To investigate the relationship between dietary preferences and mortality risk(all-cause,cancer,and cardiovascular disease[CVD])in a large adult cohort.Methods A cohort of 1,160,312 adults(mean age 62.48±9.55)from the Shenzhen Healthcare Big Data Cohort(SHBDC)was analyzed.Hazard ratios(HRs)for mortality were estimated using the Cox proportional hazards model.Results The study identified 12,308 all-cause deaths,of which 3,865(31.4%)were cancer-related and 3,576(29.1%)were attributed to CVD.Compared with a mixed diet of meat and vegetables,a mainly meat-based diet(hazard ratio[HR]=1.13;95%confidence interval[CI]:1.02,1.27)associated with a higher risk of all-cause mortality,while mainly vegetarian(HR=0.87;95%CI:0.78,0.97)was linked to a reduced risk.Furthermore,there was a stronger correlation between mortality risk and dietary preference in the>65 age range.Conclusion A meat-based diet was associated with an increased risk of all-cause mortality,whereas a mainly vegetarian diet was linked to a reduced risk.
基金supported by the National Key Research and Development Program of China(2023YFF0805602)the National Natural Science Foundation of China(U21A20186,32171579,32371592 and 32471674)the Natural Science Foundation of Gansu Province,China(23JRRA1029 and 23JRRA1034)。
文摘Plant roots interact with diverse fungi that are essential for maintaining the productivity and sustainability of pasture ecosystems,but how these root-associated fungi(RAF)differ between forage species and how they respond to nutrient enrichment and fungicide application are not well understood.Here,we constructed an 11-year experiment involving fungicide application(with or without)nested within four levels of experimental nitrogen(N)addition treatments in an alpine pasture,and the RAF communities,root traits,tissue nutrients,and shoot biomass of two dominant forage species(Carex capillifolia and Elymus nutans)were analyzed.The RAF community composition showed striking differences between the plant species and was strongly affected by both N addition level and fungicide applications.Fungicide,but not N application,dramatically reduced the RAF richness of all functional guilds in both plant species,and fungicide also simplified the co-occurrence network of the RAF for C.capillifolia.The RAF community correlated strongly with root traits,whereas their relationships became weakened or even vanished at the level of the individual plant species.The importance of RAF to plant nutrients and productivity varied between plant species,with significant contributions in C.capillifolia but not in E.nutans.This is the first report elucidating the long-term effect of fungicides on RAF in alpine pastures,and our findings emphasize the host-specific responses of RAF community structure and function to anthropogenic disturbances.
基金Teaching Reform Research Project at Southwest Medical University(Project No.:JG2023jdyb034)Humanities and Social Sciences Research Project at Sichuan Vocational College of Nursing(Project No.:2022RWSY45)。
文摘Objective:To investigate the preference characteristics and relative importance of each core factor in the teaching program for undergraduate nursing students during clinical practice,and to provide empirical support for the creation of a student-centered,formalized clinical teaching system that meets the actual needs of nursing students.Methods:The quantitative research method of discrete choice experiment was adopted,and the questionnaire was designed based on the random utility theory.Through a systematic literature review,semi-structured interviews,and two rounds of Delphi expert consultations,six core attributes of the instructor,namely educational qualifications,teaching methods,frequency of individualized guidance,operational practice opportunities,feedback timeliness,and instructor title,and their corresponding levels were determined.The study period was from January 2024 to January 2025,and 158 undergraduate nursing students who chose to intern at Deyang People’s Hospital were selected as the research subjects.A survey tool with 12 choice sets was created using Ngene software,and then statistical analysis was performed on the obtained data using the conditional Logit model to measure the impact of each attribute on the choice behavior of nursing students.Results:The results showed that the conditional Logit model fitted well(likelihood ratio chi-square=85.32,p<0.001).The analysis results indicated that the most important teaching attributes for undergraduate nursing students were,in order:the academic qualifications of the teaching instructor(master vs.Junior college,β=0.42,p<0.01),individualized guidance frequency(daily vs.Weekly,β=0.38,p<0.01),operational practice opportunities(more vs.less,β=0.31,p<0.05),and the timeliness of feedback(timely versus delayed,β=0.29,p<0.05).The influence of the title of the instructor was not statistically significant(p>0.05).Conclusion:Undergraduate nursing students show a clear and systematic preference structure for clinical teaching,with a high expectation of frequent personalized guidance from highly educated teachers,as well as sufficient operational opportunities and timely teaching feedback.
文摘Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.
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support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
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.
文摘In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.
基金The Natural Science Foundation of South-Central University for Nationalities(No.YZZ07006)
文摘In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web pages in accordance with user preferences is proposed.PWPR assigns the initial weights based on user interests and creates the virtual links and hubs according to user interests.By measuring user click streams,PWPR incrementally reflects users’ favors for the personalized ranking.To improve the accuracy of ranking, PWPR also takes collaborative filtering into consideration when the query with similar is submitted by users who have similar user interests. Detailed simulation results and comparison with other algorithms prove that the proposed PWPR can adaptively provide personalized ranking and truly relevant information to user preferences.
文摘Many agricultural landscapes have been formed through the interaction and co-evolution of nature and people, and represent the living landscapes shaped over time through intensive and continuous human cultivation. Terraced paddy fields are being re-evaluated to take into account the multiple functions they fill beyond only rice cultivation, particularly their contribution to the national biodiversity strategy of Japan. Since the 1990 s, terraced paddy fields have been considered a representative cultural landscape of Japan and, at the same time, multi-stakeholder conservation activities have been conducted throughout Japan to reverse the increasing abandonment of terraces. Shiroyone Senmaida is an outstanding cultural landscape and a major tourist attraction in Noto Peninsula, Ishikawa Prefecture, which was designated through an initiative by the Food and Agriculture Organization(FAO) as a Globally Important Agricultural Heritage Systems(GIAHS) pilot site in 2011. It is important to clarify tourist preference for terraced paddy field landscapes to contribute to future policy making toward improved agricultural landscape conservation. A key finding of this study is that tourists visiting toenjoy the agricultural landscape are also concerned on the sustainability of the farming methods and preferred to maintain the naturalness of the landscape. Respondents with higher educational levels and greater concern for the biological and traditional farming knowledge aspects of the rice terraces were also more inclined to favor sustainable farming practices. Tourists preferred to maintain the naturalness and rurality of the agricultural landscape, and indicated that construction of excessive tourist facilities would cause the landscape to deteriorate. It was suggested that the local community and surroundings, including rural settlements, hills, and forests, should also be conserved together with the scenic terrace.
基金Project supported by the National Basic Research Program of China(Grant No.2012CB719705)the National Natural Science Foundation of China(Grant Nos.91224008,91024032,and 71373139)
文摘As a physical model, the cellular automata （CA） model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees＇ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees＇ walk preference and how evacuee＇s psychology influences their behaviors are introduced into this model. Evacuees＇ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants.
基金supported by the National Science Foundation for Outstanding Youth of China(70925004)Fujian Province Transportation Hall of Science and Technology Development Projects,China(201319)the Science and Technology Project in Fujian Province Department of Education,China(JB14122)
文摘Case-based reasoning(CBR) is one of the best methods for generating an effective solution in an emergency. In recent years, some methods for generating emergency alternatives have been included in practical CBR applications, but there have been no in-depth studies of these processes. In this study,we propose a new method for dynamic case retrieval with subjective preferences and objective information, which considers the personal preferences of the decision makers and changes in the attributes of the emergency as the situation develops. First,we present a formula for calculating the case similarity and changing trends in the case considered, where similar cases are obtained. Next, we describe a method for measuring the overall assessment value with respect to similar historical cases, which is obtained by aggregating the case similarity, the utility case similarity, the first response time, and the implementation effect.The subjective preferences and objective information are also integrated in the decision-making process. Finally, we present a case study based on the emergency response to a fire in a highrise building, which illustrates the applicability and feasibility of the proposed method.
