A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such...A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.展开更多
This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergenc...This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergency services frequently, clinicians often face difficulties when providing medical and behavioral services to these patients. It may be difficult for nurse practitioners to determine if a patient with BPD who presents to the ED in crisis should be admitted, medicated, observed, or discharged. Self-harm is frequently confused with suicide attempts, which can result in unnecessary hospitalizations. This case study seeks to examine the proper management and difficulties encountered by healthcare providers in managing crises involving individuals with BPD in ED settings. The case study underscores the significance of thorough evaluation, recognition of BPD characteristics, active engagement in treatment, the therapeutic alliance, and the emphasis on interpersonal connections and stressors alongside the utilization of psychopharmacology.展开更多
Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Betwee...Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.展开更多
Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients a...Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.展开更多
Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with...Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.展开更多
The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of d...The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.展开更多
Personal video recorders (PVRs) have altered the way users consume television (TV) content by allowing users to record programs and watch them at their convenience, overcoming the constraints of live broadcasting. How...Personal video recorders (PVRs) have altered the way users consume television (TV) content by allowing users to record programs and watch them at their convenience, overcoming the constraints of live broadcasting. However, standalone PVRs are limited by their individual storage capacities, restricting the number of programs they can store. While online catch-up TV services such as Hulu and Netflix mitigate this limitation by offering on-demand access to broadcast programs shortly after their initial broadcast, they require substantial storage and network resources, leading to significant infrastructural costs for service providers. To address these challenges, we propose a collaborative TV content recording system that leverages distributed PVRs, combining their storage into a virtual shared pool without additional costs. Our system aims to support all concurrent playback requests without service interruption while ensuring program availability comparable to that of local devices. The main contributions of our proposed system are fourfold. First, by sharing storage and upload bandwidth among PVRs, our system significantly expands the overall recording capacity and enables simultaneous recording of multiple programs without the physical constraints of standalone devices. Second, by utilizing erasure coding efficiently, our system reduces the storage space required for each program, allowing more programs to be recorded compared to traditional replication. Third, we propose an adaptive redundancy scheme to control the degree of redundancy of each program based on its evolving playback demand, ensuring high-quality playback by providing sufficient bandwidth for popular programs. Finally, we introduce a contribution-based incentive policy that encourages PVRs to actively participate by contributing resources, while discouraging excessive consumption of the combined storage pool. Through extensive experiments, we demonstrate the effectiveness of our proposed collaborative TV program recording system in terms of storage efficiency and performance.展开更多
Personal care products(PCPs)are a class of emerging pollutants that have attracted public concern owing to their harmful effects on humans and the environment.Biomonitoring data is valuable for insight the levels of P...Personal care products(PCPs)are a class of emerging pollutants that have attracted public concern owing to their harmful effects on humans and the environment.Biomonitoring data is valuable for insight the levels of PCPs in the human body and can be crucial for identifying potential health hazards.To gain a better understanding of timely exposure profiles and health risk of reproductive-age population to PCPs,we determined six parabens,six benzophenone-type ultraviolet filters,and three disinfectants in 256 urine samples collected from young adults aged 18-44 years in Beijing,China.The urinary levels of benzophenone-3(BP-3)and 4-hydroxybenzophenone(4-OHBP)were significantly higher in summer compared to winter,suggesting these compounds have different seasonal usage patterns.Moreover,the total concentration of 15 PCPs in female was 430 ng/mL,approximately two times higher than that in male.P-chloro-m-xylenol(PCMX),as a new type of antibacterial agent,has the greatest level among all target analytes,indicating the increasingly use of this antibacterial alternative recently.Five potential influencing factors that lead to the elevated exposure level of PCPs were identified.Over 19%of the target population had a high hazard index value(greater than 1)which was attributed to exposure to propyl paraben(PrP),benzophenone-1(BP-1),BP-3 and PCMX,indicating that PCPs may pose a relatively high exposure risk at environmental levels that should be a cause for concern.展开更多
With the continuously increasing awareness of energy conservation and the intensifying impacts of global warming, Personal Thermal Management (PTM) technologies are increasingly recognized for their potential to ensur...With the continuously increasing awareness of energy conservation and the intensifying impacts of global warming, Personal Thermal Management (PTM) technologies are increasingly recognized for their potential to ensure human thermal comfort in extreme environments. Biomimetic structures have emerged as a novel source of inspiration for PTM applications. This review systematically summarizes the biomimetic structures, phase change materials, manufacturing methods, and the performance of multifunctional PTM wearables. Firstly, it analyzes the biomimetic structures with thermal regulation and encapsulated phase change material functionalities from different dimensions, highlighting their applications in PTM. Subsequently, it outlines the conventional manufacturing methods incorporating various biomimetic structures, offering strategies for the production of PTM wearables. The review also discusses the typical performance characteristics of multifunctional PTM wearables, addressing the current demands in thermal management. Finally, opportunities and challenges in PTM field are proposed, proposing new directions for future research.展开更多
In the era of global climate change,personal thermoregulation has become critical to addressing the growing demands for thermoadaptability,comfort,health,and work efficiency in dynamic environments.Here,we introduce a...In the era of global climate change,personal thermoregulation has become critical to addressing the growing demands for thermoadaptability,comfort,health,and work efficiency in dynamic environments.Here,we introduce an innovative three-dimensional(3D)self-folding knitted fabric that achieves dual thermal regulation modes through architectural reconfiguration.In the warming mode,the fabric maintains its natural 3D structure,trapping still air with extremely low thermal conductivity to provide high thermal resistance(0.06 m^(2) K W^(−1)),effectively minimizing heat loss.In the cooling mode,the fabric transitions to a 2D flat state via stretching,with titanium dioxide(TiO_(2))and polydimethylsiloxane(PDMS)coatings that enhance solar reflectivity(89.5%)and infrared emissivity(93.5%),achieving a cooling effect of 4.3℃under sunlight.The fabric demonstrates exceptional durability and washability,enduring over 1000 folding cycles,and is manufactured using scalable and cost-effective knitting techniques.Beyond thermoregulation,it exhibits excellent breathability,sweat management,and flexibility,ensuring wear comfort and tactile feel under diverse conditions.This study presents an innovative solution for next-generation adaptive textiles,addressing the limitations of static thermal fabrics and advancing personal thermal management with wide applications for wearable technology,extreme environments,and sustainable fashion.展开更多
Radiative cooling fabric creates a thermally comfortable environment without energy input,providing a sustainable approach to personal thermal management.However,most currently reported fabrics mainly focus on outdoor...Radiative cooling fabric creates a thermally comfortable environment without energy input,providing a sustainable approach to personal thermal management.However,most currently reported fabrics mainly focus on outdoor cooling,ignoring to achieve simultaneous cooling both indoors and outdoors,thereby weakening the overall cooling performance.Herein,a full-scale structure fabric with selective emission properties is constructed for simultaneous indoor and outdoor cooling.The fabric achieves 94%reflectance performance in the sunlight band(0.3–2.5μm)and 6%in the mid-infrared band(2.5–25μm),effectively minimizing heat absorption and radiation release obstruction.It also demonstrates 81%radiative emission performance in the atmospheric window band(8–13μm)and 25%radiative transmission performance in the mid-infrared band(2.5–25μm),providing 60 and 26 W m−2 net cooling power outdoors and indoors.In practical applications,the fabric achieves excellent indoor and outdoor human cooling,with temperatures 1.4–5.5℃ lower than typical polydimethylsiloxane film.This work proposes a novel design for the advanced radiative cooling fabric,offering significant potential to realize sustainable personal thermal management.展开更多
This study investigated the mediating role of basic psychological needs satisfaction in relationship between teacher support and adolescents’personal growth initiative.A total of 493 adolescents(females=44.8%,mean ag...This study investigated the mediating role of basic psychological needs satisfaction in relationship between teacher support and adolescents’personal growth initiative.A total of 493 adolescents(females=44.8%,mean age=12.46,SD=0.57)completed the Teacher Support Scale,the Adolescents’Personal Growth Initiative Scale,and the Basic Psychological Needs Scale.The results,analyzed through a Mediation model analysis results indicated higher teacher support to be significantly associated with higher adolescents’personal growth initiative.Teacher support was also associated with higher basic psychological needs satisfaction.Basic psychological needs satisfaction mediated the relationship between teacher support and adolescents’personal growth initiative for higher personal growth initiative.Thus,enhancing students’perceptions of teacher support would support the student’s sense of proactive and resilient growth with basic psychological needs satisfaction.展开更多
Pharmaceuticals and personal care products(PPCPs)have been considered as potential contributors to thyroid nodule(TN)and abnormal thyroid homeostasis,but epidemiological evidence is scarce.A total of 1261 individuals ...Pharmaceuticals and personal care products(PPCPs)have been considered as potential contributors to thyroid nodule(TN)and abnormal thyroid homeostasis,but epidemiological evidence is scarce.A total of 1261 individuals comprised of 367 TN patients and 895 controls were recruited from Sichuan,China.The urinary concentrations of fourteen PPCPs were measured.Five thyroid hormones(THs)in serum were determined as indicators of thyroid homeostasis,including thyroid-stimulating hormone,triiodothyronine(T3),thyroxine(T4),free-T3 and free-T4.Serum levels of thyroglobulin antibody(TGAb)and thyroperoxidase antibody(TPOAb)were quantified to identify individual thyroid antibody(TA)statuses.TN patients exhibited higher propyl-paraben(PrP)(median:1.30μg/g Cr)level than controls(0.64μg/g Cr).PrP were significantly associated with TN risk with ORs of 1.060(95%CI:1.002,1.122).The relationship of methyl-paraben with TN risk was nonlinear(p=0.049).PPCP exposurewas significantwith TN risk only in females and TA positive(TPOAb or TGAb)groups,indicating that PPCP susceptibility to TN differs by sex and TA status.Linear regression models showed ethyl-paraben was significantly negatively associated with T4(β:-0.005,95%CI:-0.011,-0.002)and T3(β:-0.007,95%CI:-0.015,-0.002),and positively associated with TPOAb(β:0.059,95%CI:0.000,0.119),suggesting that certain PPCP exposure could affect thyroid homeostasis and autoimmunity.The effects of PPCP exposure on TH and TA levels presented sex-specific.Our findings suggest that PPCP exposure increases TN risk and affects thyroid homeostasis,exhibiting sex and antibody status dependence.展开更多
This study presents an automated system for monitoring Personal Protective Equipment(PPE)compliance using advanced computer vision techniques in industrial settings.Despite strict safety regulations,manual monitoring ...This study presents an automated system for monitoring Personal Protective Equipment(PPE)compliance using advanced computer vision techniques in industrial settings.Despite strict safety regulations,manual monitoring of PPE compliance remains inefficient and prone to human error,particularly in harsh environmental conditions like in Saudi Arabia’s Eastern Province.The proposed solution leverages the state-of-the-art YOLOv11 deep learning model to detect multiple safety equipment classes,including safety vests,hard hats,safety shoes,gloves,and their absence(no_hardhat,no_safety_vest,no_safety_shoes,no_gloves)along with person detection.The system is designed to perform real-time detection of safety gear while maintaining accuracy despite challenging conditions such as extreme heat,dust,and variable lighting.In this regard,a state-of-the-art augmented and rich dataset obtained from real-life CCTV,warehouse,and smartphone footage has been investigated using YOLOv11,the latest in its family.Preliminary testing indicates the highest detection rate of 98.6% across various environmental conditions,significantly improving workplace safety compliance and reducing the resources required for manual checks.Additionally,a userfriendly administrative interface provides immediate notification upon detection of breaches so that corrective action can be taken immediately.This initiative contributes to Industry 4.0 practice development and reinforces Saudi Vision 2030’s emphasis on workplace safety and technology.展开更多
Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are importa...Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are important to achieve this cohesive combination in nursing.Accordingly,this study was conducted to determine the relationship between nurses’personality traits and the esthetics of nursing care.Methods:A cross-sectional descriptive design was employed.Study participants that consisted of 95 nurses and 285 patients from health centers in Iran were selected by convenience sampling method.Measures included the five-factor personality questionnaires(NEO-FFI)scale and Esthetics of Nursing Care Scale(ENCS).Results:The findings indicated a significant relationship between neuroticism(r=−0.149,P=0.028)and extraversion traits(r=0.136,P=0.045)of nurses in esthetics nursing care.In this study,no significant relationship was found between the personality traits and esthetics of nursing care using nurses’demographic information.Conclusions:The esthetics of nursing care depends on nurse personality traits.Since the art of nursing complements the expected care,it is suggested that nursing managers pay attention to the personality traits of nurses in planning to provide effective care.展开更多
This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 internation...This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 international students from 32 countries attending a Chinese university(females=43%,mean age=21.17 years,SD=4.45 years).They reported on their acculturation to China and physical and psychological well-being.Results from t-tests and correlation analyses indicate political liberals had more positive attitudes toward China than the conservatives,and higher self-reported physical and psychological results.Higher scores on the“interdependence”dimension of self-construal,as well as the“extraversion”and“emotional stability”dimensions of personality traits,were associated with more positive views of China and better health outcomes.These findings are consistent with Berry’s framework for acculturation,which posits that individual-level variables are related to cultural adaptation,and that cultural adaptation is associated with improved physical and mental health.International student offices at host universities should implement comprehensive support programs,including language assistance,cultural orientation,and social integration initiatives to effectively enhance the health related quality of life of international students.展开更多
Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patient...Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patients,and provide a theoretical basis for clinical practice.Therefore,in the context of the new era,it is necessary to deeply analyze the essence and connotation of personalized nursing,and analyze the existing deficiencies in current emergency pediatric personalized nursing,so as to develop effective improvement plans.Research shows that personalized nursing can significantly improve the satisfaction of emergency pediatric nursing,largely avoid nursing risks,and has strong clinical application value.This article summarizes and explores the research on the influence of personalized nursing on improving the satisfaction of emergency pediatric nursing,and puts forward corresponding views.展开更多
Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opport...Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opportunities for textual evaluation.Utilising the user corpus,characteristics of social platform users,and other data,academic research may accurately discern the personality traits of users.This research examines the traits of consumer personalities.Usually,personality tests administered by psychological experts via interviews or self-report questionnaires are costly,time-consuming,complex,and labour-intensive.Currently,academics in computational linguistics are increasingly focused on predicting personality traits from social media data.An individual’s personality comprises their traits and behavioral habits.To address this distinction,we propose a novel LSTMapproach(BERT-LIWC-LSTM)that simultaneously incorporates users’enduring and immediate personality characteristics for textual personality recognition.Long-termPersonality Encoding in the proposed paradigmcaptures and represents persisting personality traits.Short-termPersonality Capturing records changing personality states.Experimental results demonstrate that the designed BERT-LIWC-LSTM model achieves an average improvement in accuracy of 3.41% on the Big Five dataset compared to current methods,thereby justifying the efficacy of encoding both stable and dynamic personality traits simultaneously through long-and short-term feature interaction.展开更多
Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategie...Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.展开更多
Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure...Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.展开更多
基金Shanghai Frontier Science Research Center for Modern Textiles,Donghua University,ChinaOpen Project of Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,China(No.IM202303)National Key Research and Development Program of China(No.2019YFB1706300)。
文摘A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.
文摘This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergency services frequently, clinicians often face difficulties when providing medical and behavioral services to these patients. It may be difficult for nurse practitioners to determine if a patient with BPD who presents to the ED in crisis should be admitted, medicated, observed, or discharged. Self-harm is frequently confused with suicide attempts, which can result in unnecessary hospitalizations. This case study seeks to examine the proper management and difficulties encountered by healthcare providers in managing crises involving individuals with BPD in ED settings. The case study underscores the significance of thorough evaluation, recognition of BPD characteristics, active engagement in treatment, the therapeutic alliance, and the emphasis on interpersonal connections and stressors alongside the utilization of psychopharmacology.
基金supported by a project of the National Natural Science Foundation of China:Research on the integration of artificial intelligence and virtual reality technology to promote psychological rehabilitation of breast cancer patients with different personalities(project approval no.82073408).
文摘Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.
基金supported by the Foundation of President of Hebei University(XZJJ202303).
文摘Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.
文摘Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through project number RI-44-0833.
文摘The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Nos.2019R1A2C1002221 and RS-2023-00252186)Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(Nos.2021-0-00590,RS-2021-II210590Decentralized High Performance Consensus for Large-Scale Blockchains).
文摘Personal video recorders (PVRs) have altered the way users consume television (TV) content by allowing users to record programs and watch them at their convenience, overcoming the constraints of live broadcasting. However, standalone PVRs are limited by their individual storage capacities, restricting the number of programs they can store. While online catch-up TV services such as Hulu and Netflix mitigate this limitation by offering on-demand access to broadcast programs shortly after their initial broadcast, they require substantial storage and network resources, leading to significant infrastructural costs for service providers. To address these challenges, we propose a collaborative TV content recording system that leverages distributed PVRs, combining their storage into a virtual shared pool without additional costs. Our system aims to support all concurrent playback requests without service interruption while ensuring program availability comparable to that of local devices. The main contributions of our proposed system are fourfold. First, by sharing storage and upload bandwidth among PVRs, our system significantly expands the overall recording capacity and enables simultaneous recording of multiple programs without the physical constraints of standalone devices. Second, by utilizing erasure coding efficiently, our system reduces the storage space required for each program, allowing more programs to be recorded compared to traditional replication. Third, we propose an adaptive redundancy scheme to control the degree of redundancy of each program based on its evolving playback demand, ensuring high-quality playback by providing sufficient bandwidth for popular programs. Finally, we introduce a contribution-based incentive policy that encourages PVRs to actively participate by contributing resources, while discouraging excessive consumption of the combined storage pool. Through extensive experiments, we demonstrate the effectiveness of our proposed collaborative TV program recording system in terms of storage efficiency and performance.
基金supported by the National Natural Science Foundation of China (No.22106154).
文摘Personal care products(PCPs)are a class of emerging pollutants that have attracted public concern owing to their harmful effects on humans and the environment.Biomonitoring data is valuable for insight the levels of PCPs in the human body and can be crucial for identifying potential health hazards.To gain a better understanding of timely exposure profiles and health risk of reproductive-age population to PCPs,we determined six parabens,six benzophenone-type ultraviolet filters,and three disinfectants in 256 urine samples collected from young adults aged 18-44 years in Beijing,China.The urinary levels of benzophenone-3(BP-3)and 4-hydroxybenzophenone(4-OHBP)were significantly higher in summer compared to winter,suggesting these compounds have different seasonal usage patterns.Moreover,the total concentration of 15 PCPs in female was 430 ng/mL,approximately two times higher than that in male.P-chloro-m-xylenol(PCMX),as a new type of antibacterial agent,has the greatest level among all target analytes,indicating the increasingly use of this antibacterial alternative recently.Five potential influencing factors that lead to the elevated exposure level of PCPs were identified.Over 19%of the target population had a high hazard index value(greater than 1)which was attributed to exposure to propyl paraben(PrP),benzophenone-1(BP-1),BP-3 and PCMX,indicating that PCPs may pose a relatively high exposure risk at environmental levels that should be a cause for concern.
基金supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2024A1515010772)State Key Laboratory of Massive Personalized Customization System and Technology,No.H&C-MPC-2023-02-06(Q)+2 种基金“CUG scholar”Scientific Research Funds at China University of Geosciences,Wuhan(No.CUG2022185)Guangzhou Youth Top Talent ProgramChina College Student Innovation and Entrepreneurship Training Program(No.S202410491063).
文摘With the continuously increasing awareness of energy conservation and the intensifying impacts of global warming, Personal Thermal Management (PTM) technologies are increasingly recognized for their potential to ensure human thermal comfort in extreme environments. Biomimetic structures have emerged as a novel source of inspiration for PTM applications. This review systematically summarizes the biomimetic structures, phase change materials, manufacturing methods, and the performance of multifunctional PTM wearables. Firstly, it analyzes the biomimetic structures with thermal regulation and encapsulated phase change material functionalities from different dimensions, highlighting their applications in PTM. Subsequently, it outlines the conventional manufacturing methods incorporating various biomimetic structures, offering strategies for the production of PTM wearables. The review also discusses the typical performance characteristics of multifunctional PTM wearables, addressing the current demands in thermal management. Finally, opportunities and challenges in PTM field are proposed, proposing new directions for future research.
基金the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant No.:PolyU 152157/24E)Green Tech Fund(Project No.:GTF202220106)+1 种基金the PolyU Awarding Fund Scheme(Project No.:BBFR)the PolyU Endowed Young Scholars Scheme(Project No.:84CC).
文摘In the era of global climate change,personal thermoregulation has become critical to addressing the growing demands for thermoadaptability,comfort,health,and work efficiency in dynamic environments.Here,we introduce an innovative three-dimensional(3D)self-folding knitted fabric that achieves dual thermal regulation modes through architectural reconfiguration.In the warming mode,the fabric maintains its natural 3D structure,trapping still air with extremely low thermal conductivity to provide high thermal resistance(0.06 m^(2) K W^(−1)),effectively minimizing heat loss.In the cooling mode,the fabric transitions to a 2D flat state via stretching,with titanium dioxide(TiO_(2))and polydimethylsiloxane(PDMS)coatings that enhance solar reflectivity(89.5%)and infrared emissivity(93.5%),achieving a cooling effect of 4.3℃under sunlight.The fabric demonstrates exceptional durability and washability,enduring over 1000 folding cycles,and is manufactured using scalable and cost-effective knitting techniques.Beyond thermoregulation,it exhibits excellent breathability,sweat management,and flexibility,ensuring wear comfort and tactile feel under diverse conditions.This study presents an innovative solution for next-generation adaptive textiles,addressing the limitations of static thermal fabrics and advancing personal thermal management with wide applications for wearable technology,extreme environments,and sustainable fashion.
基金financially supported by Heilongjiang Postdoctoral Fund(Grant No.LBH-Z24057)Outstanding Master’s and Doctoral Thesis of Longjiang in the New Era(Grant No.LJYXL2023-076).
文摘Radiative cooling fabric creates a thermally comfortable environment without energy input,providing a sustainable approach to personal thermal management.However,most currently reported fabrics mainly focus on outdoor cooling,ignoring to achieve simultaneous cooling both indoors and outdoors,thereby weakening the overall cooling performance.Herein,a full-scale structure fabric with selective emission properties is constructed for simultaneous indoor and outdoor cooling.The fabric achieves 94%reflectance performance in the sunlight band(0.3–2.5μm)and 6%in the mid-infrared band(2.5–25μm),effectively minimizing heat absorption and radiation release obstruction.It also demonstrates 81%radiative emission performance in the atmospheric window band(8–13μm)and 25%radiative transmission performance in the mid-infrared band(2.5–25μm),providing 60 and 26 W m−2 net cooling power outdoors and indoors.In practical applications,the fabric achieves excellent indoor and outdoor human cooling,with temperatures 1.4–5.5℃ lower than typical polydimethylsiloxane film.This work proposes a novel design for the advanced radiative cooling fabric,offering significant potential to realize sustainable personal thermal management.
文摘This study investigated the mediating role of basic psychological needs satisfaction in relationship between teacher support and adolescents’personal growth initiative.A total of 493 adolescents(females=44.8%,mean age=12.46,SD=0.57)completed the Teacher Support Scale,the Adolescents’Personal Growth Initiative Scale,and the Basic Psychological Needs Scale.The results,analyzed through a Mediation model analysis results indicated higher teacher support to be significantly associated with higher adolescents’personal growth initiative.Teacher support was also associated with higher basic psychological needs satisfaction.Basic psychological needs satisfaction mediated the relationship between teacher support and adolescents’personal growth initiative for higher personal growth initiative.Thus,enhancing students’perceptions of teacher support would support the student’s sense of proactive and resilient growth with basic psychological needs satisfaction.
基金supported by the National Natural Science Foundation of China(Nos.21976046 and 42177412)the Ministry of Education of China(No.B17025).
文摘Pharmaceuticals and personal care products(PPCPs)have been considered as potential contributors to thyroid nodule(TN)and abnormal thyroid homeostasis,but epidemiological evidence is scarce.A total of 1261 individuals comprised of 367 TN patients and 895 controls were recruited from Sichuan,China.The urinary concentrations of fourteen PPCPs were measured.Five thyroid hormones(THs)in serum were determined as indicators of thyroid homeostasis,including thyroid-stimulating hormone,triiodothyronine(T3),thyroxine(T4),free-T3 and free-T4.Serum levels of thyroglobulin antibody(TGAb)and thyroperoxidase antibody(TPOAb)were quantified to identify individual thyroid antibody(TA)statuses.TN patients exhibited higher propyl-paraben(PrP)(median:1.30μg/g Cr)level than controls(0.64μg/g Cr).PrP were significantly associated with TN risk with ORs of 1.060(95%CI:1.002,1.122).The relationship of methyl-paraben with TN risk was nonlinear(p=0.049).PPCP exposurewas significantwith TN risk only in females and TA positive(TPOAb or TGAb)groups,indicating that PPCP susceptibility to TN differs by sex and TA status.Linear regression models showed ethyl-paraben was significantly negatively associated with T4(β:-0.005,95%CI:-0.011,-0.002)and T3(β:-0.007,95%CI:-0.015,-0.002),and positively associated with TPOAb(β:0.059,95%CI:0.000,0.119),suggesting that certain PPCP exposure could affect thyroid homeostasis and autoimmunity.The effects of PPCP exposure on TH and TA levels presented sex-specific.Our findings suggest that PPCP exposure increases TN risk and affects thyroid homeostasis,exhibiting sex and antibody status dependence.
文摘This study presents an automated system for monitoring Personal Protective Equipment(PPE)compliance using advanced computer vision techniques in industrial settings.Despite strict safety regulations,manual monitoring of PPE compliance remains inefficient and prone to human error,particularly in harsh environmental conditions like in Saudi Arabia’s Eastern Province.The proposed solution leverages the state-of-the-art YOLOv11 deep learning model to detect multiple safety equipment classes,including safety vests,hard hats,safety shoes,gloves,and their absence(no_hardhat,no_safety_vest,no_safety_shoes,no_gloves)along with person detection.The system is designed to perform real-time detection of safety gear while maintaining accuracy despite challenging conditions such as extreme heat,dust,and variable lighting.In this regard,a state-of-the-art augmented and rich dataset obtained from real-life CCTV,warehouse,and smartphone footage has been investigated using YOLOv11,the latest in its family.Preliminary testing indicates the highest detection rate of 98.6% across various environmental conditions,significantly improving workplace safety compliance and reducing the resources required for manual checks.Additionally,a userfriendly administrative interface provides immediate notification upon detection of breaches so that corrective action can be taken immediately.This initiative contributes to Industry 4.0 practice development and reinforces Saudi Vision 2030’s emphasis on workplace safety and technology.
文摘Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are important to achieve this cohesive combination in nursing.Accordingly,this study was conducted to determine the relationship between nurses’personality traits and the esthetics of nursing care.Methods:A cross-sectional descriptive design was employed.Study participants that consisted of 95 nurses and 285 patients from health centers in Iran were selected by convenience sampling method.Measures included the five-factor personality questionnaires(NEO-FFI)scale and Esthetics of Nursing Care Scale(ENCS).Results:The findings indicated a significant relationship between neuroticism(r=−0.149,P=0.028)and extraversion traits(r=0.136,P=0.045)of nurses in esthetics nursing care.In this study,no significant relationship was found between the personality traits and esthetics of nursing care using nurses’demographic information.Conclusions:The esthetics of nursing care depends on nurse personality traits.Since the art of nursing complements the expected care,it is suggested that nursing managers pay attention to the personality traits of nurses in planning to provide effective care.
文摘This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 international students from 32 countries attending a Chinese university(females=43%,mean age=21.17 years,SD=4.45 years).They reported on their acculturation to China and physical and psychological well-being.Results from t-tests and correlation analyses indicate political liberals had more positive attitudes toward China than the conservatives,and higher self-reported physical and psychological results.Higher scores on the“interdependence”dimension of self-construal,as well as the“extraversion”and“emotional stability”dimensions of personality traits,were associated with more positive views of China and better health outcomes.These findings are consistent with Berry’s framework for acculturation,which posits that individual-level variables are related to cultural adaptation,and that cultural adaptation is associated with improved physical and mental health.International student offices at host universities should implement comprehensive support programs,including language assistance,cultural orientation,and social integration initiatives to effectively enhance the health related quality of life of international students.
文摘Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patients,and provide a theoretical basis for clinical practice.Therefore,in the context of the new era,it is necessary to deeply analyze the essence and connotation of personalized nursing,and analyze the existing deficiencies in current emergency pediatric personalized nursing,so as to develop effective improvement plans.Research shows that personalized nursing can significantly improve the satisfaction of emergency pediatric nursing,largely avoid nursing risks,and has strong clinical application value.This article summarizes and explores the research on the influence of personalized nursing on improving the satisfaction of emergency pediatric nursing,and puts forward corresponding views.
文摘Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opportunities for textual evaluation.Utilising the user corpus,characteristics of social platform users,and other data,academic research may accurately discern the personality traits of users.This research examines the traits of consumer personalities.Usually,personality tests administered by psychological experts via interviews or self-report questionnaires are costly,time-consuming,complex,and labour-intensive.Currently,academics in computational linguistics are increasingly focused on predicting personality traits from social media data.An individual’s personality comprises their traits and behavioral habits.To address this distinction,we propose a novel LSTMapproach(BERT-LIWC-LSTM)that simultaneously incorporates users’enduring and immediate personality characteristics for textual personality recognition.Long-termPersonality Encoding in the proposed paradigmcaptures and represents persisting personality traits.Short-termPersonality Capturing records changing personality states.Experimental results demonstrate that the designed BERT-LIWC-LSTM model achieves an average improvement in accuracy of 3.41% on the Big Five dataset compared to current methods,thereby justifying the efficacy of encoding both stable and dynamic personality traits simultaneously through long-and short-term feature interaction.
文摘Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.
文摘Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.
