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
The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been conside...The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.展开更多
A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social netw...A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.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
A recommender system is a tool designed to suggest relevant items to users based on their preferences and behaviors.Collaborative filtering,a popular technique within recommender systems,predicts user interests by ana...A recommender system is a tool designed to suggest relevant items to users based on their preferences and behaviors.Collaborative filtering,a popular technique within recommender systems,predicts user interests by analyzing patterns in interactions and similarities between users,leveraging past behavior data to make personalized recommendations.Despite its popularity,collaborative filtering faces notable challenges,and one of them is the issue of grey-sheep users who have unusual tastes in the system.Surprisingly,existing research has not extensively explored outlier detection techniques to address the grey-sheep problem.To fill this research gap,this study conducts a comprehensive comparison of 12 outlier detectionmethods(such as LOF,ABOD,HBOS,etc.)and introduces innovative user representations aimed at improving the identification of outliers within recommender systems.More specifically,we proposed and examined three types of user representations:1)the distribution statistics of user-user similarities,where similarities were calculated based on users’rating vectors;2)the distribution statistics of user-user similarities,but with similarities derived from users represented by latent factors;and 3)latent-factor vector representations.Our experiments on the Movie Lens and Yahoo!Movie datasets demonstrate that user representations based on latent-factor vectors consistently facilitate the identification of more grey-sheep users when applying outlier detection methods.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
A new wave of artificial intelligence(AI) development is sweeping the world. Considering its technology maturity and application scale, AI is in an infant stage of development. However, as the core technology and appl...A new wave of artificial intelligence(AI) development is sweeping the world. Considering its technology maturity and application scale, AI is in an infant stage of development. However, as the core technology and application driving the fourth scientific and technological revolution, AI has attracted worldwide attention for its potential transformative nature. The international community has expressed great concern over AI security, and the call for strengthening governance is growing. The international governance of AI has exhibited a strong preference for security. The underlying logic relates to AI's history,technological characteristics, and geopolitical changes. Such a security preference has determined the cognition, vision, and practical priorities of AI governance and will impact the future of AI and even the international balance of power.展开更多
Transient receptor potential(TRP)channels are a class of ion channel proteins that are closely related to thermosensation in insects.They are involved in detecting the ambient temperature and play vital roles in insec...Transient receptor potential(TRP)channels are a class of ion channel proteins that are closely related to thermosensation in insects.They are involved in detecting the ambient temperature and play vital roles in insect survival and reproduction.In this study,we identifed and cloned two variants of the TRPA subfamily gene in Myzus persicae,MperTRPA1(A)and MperTRPA1(B),and analyzed their tissue expression by real-time quantitative PCR.Subsequently,these two variants of MperTRPA1 were expressed in the Xenopus oocyte system,and their functions were investigated using the two-electrode voltage clamp technique.The role of the MperTRPA1 gene in temperature adaptation of M.persicae was further determined by RNA interference and a behavioral choice assay to evaluate responses to temperature gradients.The results showed that the MperTRPA1 gene is widely expressed in tissues of M.persicae,with MperTRPA1(A)highly expressed in the mouthparts and MperTRPA1(B)mainly expressed in the antennae.The functional characterization results showed that both variants of MperTRPA1 could be activated and were not desensitized when the temperature increased from 20 to 45℃.The current value and thermal sensitivity(coeffcient Q_(10)value)of MperTRPA1(B)were signifcantly higher than those of MperTRPA1(A).When the MperTRPA1 gene was knocked down,the behavioral preference of M.persicae for the optimal temperature was reduced and tended to be at a higher temperature,showing a shift in the temperature adaptation range compared to both the wild type and ds GFP-treated M.persicae.In summary,our results elucidated the molecular mechanism of adaptive temperature perception in M.persicae mediated by the thermal sensor MperTRPA1.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
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
Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF developmen...Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF development trajectories during junior high school students,investigate their influence on social avoidance(SA),and further examine the mediating role of preference for solitude(PS)between them.Methods:A three-wave longitudinal study was used with six-month intervals.Questionnaire data were collected from 436 junior high school students in Jiangxi Province,China.Participants ranged in age from 11 to 14 years old(Mean=12.89 years,SD=1.08;50.2%male).Results:Four heterogeneous types of FF trajectories were identified:(1)a high and increasing group(14.7%);(2)a consistently high group(36.24%);(3)a consistently moderate group(45.86%);and(4)a rapid growth group(3.2%).The developmental trajectories of FF among junior high students significantly varied in their levels of SA(F(3,432)=32.03,p<0.001).Compared to the high and increasing groups,the consistently high,consistently medium,and rapid growth groups exhibited higher levels of SA.PS mediated the association between the developmental trajectory of FF and SA.Conclusion:There was a close relationship between the developmental trajectory of FF and SA.Interventions focusing on family system optimization and solitary preference management could effectively mitigate SA behaviors.These findings are important for promoting healthy socialization in adolescents.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
The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresp...Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresponsive trains and pre-scheduled trains is pivotal in addressing this issue.To delve into passengers’choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demandresponsive service in high-speed railways,the stated preference survey method is employed to investigate travel intention of passengers.Based on the survey data obtained in China,the heterogeneity of passengers is analyzed from three aspects:personal socio-economic characteristics,travel characteristics,and travel mode choice.Considering the situation that demand-responsive train cannot operate,the risk attributes are considered.To bolster the appeal of demand-responsive trains,personalized service product attributes are added.Mixed Logit mode,which takes into account the heterogeneous travel choice behavior of passengers,is developed,and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters.The willingness to pay in terms of different factors of passengers is determined.The results indicate that early arrival deviation time,late arrival deviation time,demand response time,and success rate of ticket purchase remarkable influence passengers’decision regarding demand-responsive train,with only the success rate of ticket purchase positively impacting train choice.Moreover,the significant difference in train ticket price is observed solely in the self-funded long distance scenario,while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario.Through the Willingness To Pay(WTP)analysis,it is discovered that by shortening demand response time,enhancing the success rate of ticket purchase,and minimizing the deviation times of early arrival and late arrival of trains,the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented.This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains.展开更多
Identifying influential users in social networks is of great significance in areas such as public opinion monitoring and commercial promotion.Existing identification methods based on Graph Neural Networks(GNNs)often l...Identifying influential users in social networks is of great significance in areas such as public opinion monitoring and commercial promotion.Existing identification methods based on Graph Neural Networks(GNNs)often lead to yield inaccurate features of influential users due to neighborhood aggregation,and require a large substantial amount of labeled data for training,making them difficult and challenging to apply in practice.To address this issue,we propose a semi-supervised contrastive learning method for identifying influential users.First,the proposed method constructs positive and negative samples for contrastive learning based on multiple node centrality metrics related to influence;then,contrastive learning is employed to guide the encoder to generate various influence-related features for users;finally,with only a small amount of labeled data,an attention-based user classifier is trained to accurately identify influential users.Experiments conducted on three public social network datasets demonstrate that the proposed method,using only 20%of the labeled data as the training set,achieves F1 values that are 5.9%,5.8%,and 8.7%higher than those unsupervised EVC method,and it matches the performance of GNN-based methods such as DeepInf,InfGCN and OlapGN,which require 80%of labeled data as the training set.展开更多
A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,...A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.展开更多
Over the last decade, the popularity of Transportation Network Companies (TNCs) as a mode of travel has been increasing at a steady pace. This trend <span style="font-family:Verdana;">highlights the im...Over the last decade, the popularity of Transportation Network Companies (TNCs) as a mode of travel has been increasing at a steady pace. This trend <span style="font-family:Verdana;">highlights the importance of identifying the determinants that influence transportati</span><span style="font-family:Verdana;">on users to adopt TNCs as a preferred mode choice and the impacts of su</span><span style="font-family:Verdana;">ch preferences on their travel patterns and transportation network o</span><span style="font-family:Verdana;">peration. This paper reports on a recent study undertaken in Birmingham, AL aiming at understanding and documenting the factors that influence transportation users to select TNCs (such as Uber/Lyft) for completing typical day trips. In </span><span style="font-family:Verdana;">doing so, a travel diary questionnaire survey was developed in accordance with</span> <span style="font-family:Verdana;">the Institute of Transportation Engineers (ITE) Manual on Transportation Engineering Studies using the Qualtrics Research Core platform. The que</span><span style="font-family:Verdana;">stionnair</span><span style="font-family:Verdana;">e was used to survey over 450 transportation users in the Birmingham Metro area. The survey participants provided detailed trip information for a </span><span style="font-family:Verdana;">typical 24-hr day along with demographic data and travel preference informatio</span><span style="font-family:Verdana;">n. The survey responses provide high-resolution micro-level indicators </span><span style="font-family:Verdana;">of travel preferences and behaviors in a TNC-served area, which is a much-needed </span><span style="font-family:Verdana;">type of information for researchers and transportation planning agencies.</span>展开更多
<span style="font-family:Verdana;">For past deca</span><span style="font-family:Verdana;">des, research of designing </span><span style="font-family:Verdana;"&...<span style="font-family:Verdana;">For past deca</span><span style="font-family:Verdana;">des, research of designing </span><span style="font-family:Verdana;">“</span><span style="font-family:Verdana;">pleasure</span><span style="font-family:Verdana;">”</span><span style="font-family:Verdana;"> into products</span><span style="font-family:Verdana;"> in the aca</span><span style="font-family:Verdana;">demic community has produced a multitude of evaluation models and fra</span><span style="font-family:Verdana;">mework</span><span style="font-family:Verdana;">s. These models address the critical issues of plea</span><span style="font-family:Verdana;">surable product design </span><span style="font-family:Verdana;">leading to emotional design. This study is intended to explore the change fr</span><span style="font-family:Verdana;">om the need of “usability” for the product design to the need of “pleasure” for the user experience. The questionnaires were used to obtain data from 343 subjects. The four keyboard designs were adopted in the experiment to study the differ</span><span style="font-family:Verdana;">ence and the change from “usability” to</span><span style="font-family:Verdana;"> “pleasure” of users” preference. The results show that the need for pleasure is higher than usability, as well as </span><span style="font-family:Verdana;">attractive things also transmit the feel of work better. Besides, preference is re</span><span style="font-family:Verdana;">lated to gender, age, major, and educational background. Results presented her</span><span style="font-family:Verdana;">ein </span><span style="font-family:Verdana;">provide designers with a valuable reference for examining the</span><span style="font-family:Verdana;"> way how to </span><span style="font-family:Verdana;">design “pleasure” into product and the interactive experience of users in the de</span><span style="font-family:Verdana;">sign process.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
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.
基金supported by Natural Science Foundation of China(Grant 61901070,61801065,62271096,61871062,U20A20157 and 62061007)in part by the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant KJQN202000603 and KJQN201900611)+3 种基金in part by the Natural Science Foundation of Chongqing(Grant CSTB2022NSCQMSX0468,cstc2020jcyjzdxmX0024 and cstc2021jcyjmsxmX0892)in part by University Innovation Research Group of Chongqing(Grant CxQT20017)in part by Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04)in part by the Chongqing Graduate Student Scientific Research Innovation Project(CYB22246)。
文摘The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.
基金supported by the National Natural Science Foundation of China Project(No.62302540)The Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness(No.HNTS2022020)+2 种基金Natural Science Foundation of Henan Province Project(No.232300420422)The Natural Science Foundation of Zhongyuan University of Technology(No.K2023QN018)Key Research and Promotion Project of Henan Province in 2021(No.212102310480).
文摘A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.
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.
文摘A recommender system is a tool designed to suggest relevant items to users based on their preferences and behaviors.Collaborative filtering,a popular technique within recommender systems,predicts user interests by analyzing patterns in interactions and similarities between users,leveraging past behavior data to make personalized recommendations.Despite its popularity,collaborative filtering faces notable challenges,and one of them is the issue of grey-sheep users who have unusual tastes in the system.Surprisingly,existing research has not extensively explored outlier detection techniques to address the grey-sheep problem.To fill this research gap,this study conducts a comprehensive comparison of 12 outlier detectionmethods(such as LOF,ABOD,HBOS,etc.)and introduces innovative user representations aimed at improving the identification of outliers within recommender systems.More specifically,we proposed and examined three types of user representations:1)the distribution statistics of user-user similarities,where similarities were calculated based on users’rating vectors;2)the distribution statistics of user-user similarities,but with similarities derived from users represented by latent factors;and 3)latent-factor vector representations.Our experiments on the Movie Lens and Yahoo!Movie datasets demonstrate that user representations based on latent-factor vectors consistently facilitate the identification of more grey-sheep users when applying outlier detection methods.
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.
文摘A new wave of artificial intelligence(AI) development is sweeping the world. Considering its technology maturity and application scale, AI is in an infant stage of development. However, as the core technology and application driving the fourth scientific and technological revolution, AI has attracted worldwide attention for its potential transformative nature. The international community has expressed great concern over AI security, and the call for strengthening governance is growing. The international governance of AI has exhibited a strong preference for security. The underlying logic relates to AI's history,technological characteristics, and geopolitical changes. Such a security preference has determined the cognition, vision, and practical priorities of AI governance and will impact the future of AI and even the international balance of power.
基金funded by the National Natural Science Foundation of China(32472553 and 31872039)the Major Special Projects for Green Pest Control,China(110202201017(LS-01))+1 种基金the Shenzhen Science and Technology Program,China(KQTD20180411143628272)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences。
文摘Transient receptor potential(TRP)channels are a class of ion channel proteins that are closely related to thermosensation in insects.They are involved in detecting the ambient temperature and play vital roles in insect survival and reproduction.In this study,we identifed and cloned two variants of the TRPA subfamily gene in Myzus persicae,MperTRPA1(A)and MperTRPA1(B),and analyzed their tissue expression by real-time quantitative PCR.Subsequently,these two variants of MperTRPA1 were expressed in the Xenopus oocyte system,and their functions were investigated using the two-electrode voltage clamp technique.The role of the MperTRPA1 gene in temperature adaptation of M.persicae was further determined by RNA interference and a behavioral choice assay to evaluate responses to temperature gradients.The results showed that the MperTRPA1 gene is widely expressed in tissues of M.persicae,with MperTRPA1(A)highly expressed in the mouthparts and MperTRPA1(B)mainly expressed in the antennae.The functional characterization results showed that both variants of MperTRPA1 could be activated and were not desensitized when the temperature increased from 20 to 45℃.The current value and thermal sensitivity(coeffcient Q_(10)value)of MperTRPA1(B)were signifcantly higher than those of MperTRPA1(A).When the MperTRPA1 gene was knocked down,the behavioral preference of M.persicae for the optimal temperature was reduced and tended to be at a higher temperature,showing a shift in the temperature adaptation range compared to both the wild type and ds GFP-treated M.persicae.In summary,our results elucidated the molecular mechanism of adaptive temperature perception in M.persicae mediated by the thermal sensor MperTRPA1.
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 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 Natural Science Foundation of China(72164018)National Social Science Fund Project(BFA200065)Jiangxi Social Science Foundation Project(21JY13).
文摘Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF development trajectories during junior high school students,investigate their influence on social avoidance(SA),and further examine the mediating role of preference for solitude(PS)between them.Methods:A three-wave longitudinal study was used with six-month intervals.Questionnaire data were collected from 436 junior high school students in Jiangxi Province,China.Participants ranged in age from 11 to 14 years old(Mean=12.89 years,SD=1.08;50.2%male).Results:Four heterogeneous types of FF trajectories were identified:(1)a high and increasing group(14.7%);(2)a consistently high group(36.24%);(3)a consistently moderate group(45.86%);and(4)a rapid growth group(3.2%).The developmental trajectories of FF among junior high students significantly varied in their levels of SA(F(3,432)=32.03,p<0.001).Compared to the high and increasing groups,the consistently high,consistently medium,and rapid growth groups exhibited higher levels of SA.PS mediated the association between the developmental trajectory of FF and SA.Conclusion:There was a close relationship between the developmental trajectory of FF and SA.Interventions focusing on family system optimization and solitary preference management could effectively mitigate SA behaviors.These findings are important for promoting healthy socialization in adolescents.
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funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
基金supported by the National Natural Science Foundation of China(No.72471023,71971019)the Fundamental Research Funds for the Central Universities(No.2024QYBS025).
文摘Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresponsive trains and pre-scheduled trains is pivotal in addressing this issue.To delve into passengers’choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demandresponsive service in high-speed railways,the stated preference survey method is employed to investigate travel intention of passengers.Based on the survey data obtained in China,the heterogeneity of passengers is analyzed from three aspects:personal socio-economic characteristics,travel characteristics,and travel mode choice.Considering the situation that demand-responsive train cannot operate,the risk attributes are considered.To bolster the appeal of demand-responsive trains,personalized service product attributes are added.Mixed Logit mode,which takes into account the heterogeneous travel choice behavior of passengers,is developed,and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters.The willingness to pay in terms of different factors of passengers is determined.The results indicate that early arrival deviation time,late arrival deviation time,demand response time,and success rate of ticket purchase remarkable influence passengers’decision regarding demand-responsive train,with only the success rate of ticket purchase positively impacting train choice.Moreover,the significant difference in train ticket price is observed solely in the self-funded long distance scenario,while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario.Through the Willingness To Pay(WTP)analysis,it is discovered that by shortening demand response time,enhancing the success rate of ticket purchase,and minimizing the deviation times of early arrival and late arrival of trains,the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented.This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains.
基金supported by the National Key Project of the National Natural Science Foundation of China under Grant No.U23A20305.
文摘Identifying influential users in social networks is of great significance in areas such as public opinion monitoring and commercial promotion.Existing identification methods based on Graph Neural Networks(GNNs)often lead to yield inaccurate features of influential users due to neighborhood aggregation,and require a large substantial amount of labeled data for training,making them difficult and challenging to apply in practice.To address this issue,we propose a semi-supervised contrastive learning method for identifying influential users.First,the proposed method constructs positive and negative samples for contrastive learning based on multiple node centrality metrics related to influence;then,contrastive learning is employed to guide the encoder to generate various influence-related features for users;finally,with only a small amount of labeled data,an attention-based user classifier is trained to accurately identify influential users.Experiments conducted on three public social network datasets demonstrate that the proposed method,using only 20%of the labeled data as the training set,achieves F1 values that are 5.9%,5.8%,and 8.7%higher than those unsupervised EVC method,and it matches the performance of GNN-based methods such as DeepInf,InfGCN and OlapGN,which require 80%of labeled data as the training set.
基金supported by the National Natural Science Foundation of China(32273037 and 32102636)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030007)+4 种基金Laboratory of Lingnan Modern Agriculture Project(NT2021007)the Guangdong Science and Technology Innovation Leading Talent Program(2019TX05N098)the 111 Center(D20008)the double first-class discipline promotion project(2023B10564003)the Department of Education of Guangdong Province(2019KZDXM004 and 2019KCXTD001).
文摘A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.
文摘Over the last decade, the popularity of Transportation Network Companies (TNCs) as a mode of travel has been increasing at a steady pace. This trend <span style="font-family:Verdana;">highlights the importance of identifying the determinants that influence transportati</span><span style="font-family:Verdana;">on users to adopt TNCs as a preferred mode choice and the impacts of su</span><span style="font-family:Verdana;">ch preferences on their travel patterns and transportation network o</span><span style="font-family:Verdana;">peration. This paper reports on a recent study undertaken in Birmingham, AL aiming at understanding and documenting the factors that influence transportation users to select TNCs (such as Uber/Lyft) for completing typical day trips. In </span><span style="font-family:Verdana;">doing so, a travel diary questionnaire survey was developed in accordance with</span> <span style="font-family:Verdana;">the Institute of Transportation Engineers (ITE) Manual on Transportation Engineering Studies using the Qualtrics Research Core platform. The que</span><span style="font-family:Verdana;">stionnair</span><span style="font-family:Verdana;">e was used to survey over 450 transportation users in the Birmingham Metro area. The survey participants provided detailed trip information for a </span><span style="font-family:Verdana;">typical 24-hr day along with demographic data and travel preference informatio</span><span style="font-family:Verdana;">n. The survey responses provide high-resolution micro-level indicators </span><span style="font-family:Verdana;">of travel preferences and behaviors in a TNC-served area, which is a much-needed </span><span style="font-family:Verdana;">type of information for researchers and transportation planning agencies.</span>
文摘<span style="font-family:Verdana;">For past deca</span><span style="font-family:Verdana;">des, research of designing </span><span style="font-family:Verdana;">“</span><span style="font-family:Verdana;">pleasure</span><span style="font-family:Verdana;">”</span><span style="font-family:Verdana;"> into products</span><span style="font-family:Verdana;"> in the aca</span><span style="font-family:Verdana;">demic community has produced a multitude of evaluation models and fra</span><span style="font-family:Verdana;">mework</span><span style="font-family:Verdana;">s. These models address the critical issues of plea</span><span style="font-family:Verdana;">surable product design </span><span style="font-family:Verdana;">leading to emotional design. This study is intended to explore the change fr</span><span style="font-family:Verdana;">om the need of “usability” for the product design to the need of “pleasure” for the user experience. The questionnaires were used to obtain data from 343 subjects. The four keyboard designs were adopted in the experiment to study the differ</span><span style="font-family:Verdana;">ence and the change from “usability” to</span><span style="font-family:Verdana;"> “pleasure” of users” preference. The results show that the need for pleasure is higher than usability, as well as </span><span style="font-family:Verdana;">attractive things also transmit the feel of work better. Besides, preference is re</span><span style="font-family:Verdana;">lated to gender, age, major, and educational background. Results presented her</span><span style="font-family:Verdana;">ein </span><span style="font-family:Verdana;">provide designers with a valuable reference for examining the</span><span style="font-family:Verdana;"> way how to </span><span style="font-family:Verdana;">design “pleasure” into product and the interactive experience of users in the de</span><span style="font-family:Verdana;">sign process.
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.
