Personal Thermal Management by Radiative Cooling and Heating

Maintaining thermal comfort within the human body is crucial for optimal health and overall well-being.By merely broadening the setpoint of indoor temperatures,we could significantly slash energy usage in building heating,ventilation,and air-conditioning systems.In recent years,there has been a surge in advancements in personal thermal management(PTM),aiming to regulate heat and moisture transfer within our immediate surroundings,clothing,and skin.The advent of PTM is driven by the rapid development in nano/micro-materials and energy science and engineering.An emerging research area in PTM is personal radiative thermal management(PRTM),which demonstrates immense potential with its high radiative heat transfer efficiency and ease of regulation.However,it is less taken into account in traditional textiles,and there currently lies a gap in our knowledge and understanding of PRTM.In this review,we aim to present a thorough analysis of advanced textile materials and technologies for PRTM.Specifically,we will introduce and discuss the underlying radiation heat transfer mechanisms,fabrication methods of textiles,and various indoor/outdoor applications in light of their different regulation functionalities,including radiative cooling,radiative heating,and dual-mode thermoregulation.Furthermore,we will shine a light on the current hurdles,propose potential strategies,and delve into future technology trends for PRTM with an emphasis on functionalities and applications.

On People’s Worries about Becoming a Victim of Events or Conditions Often Blamed on Those up There

The authors study people’s worries about becoming victimized by events and conditions often blamed on“those up there”.Excessive worries are bad for people’s performance because they lead to risk avoidance and lower self-confidence.In two representative surveys conducted in Germany,it is found that victimization concerns are positively correlated with people’s gender,previous victimization,their estimated likelihood of being victimized,their fear of crime,their crime-avoidance behavior,their striving for tradition and security,and their negative attitudes toward crimes.Negative correlations are found for people’s education,their striving for universalism,and their social capital.When considering all predictors combined,people’s expected likelihood to become victimized is found to be the optimal predictor of victimization concerns.It is recommended that management concentrates on setting realistic levels of such risk estimates to avoid negative effects on people’s performance.

The Implementation of Human Resource Management Information System

Human resource management has begun to conduct information technology to enhance the efficiency of human resource work.The research objectives are:(1)Does the implementation of human resource management information system enhance work efficiency?(2)What are key factors to influence the implementation of human resource management information system?This research adopts case study with in-depth interviews at W University of Science and Technology.The interviewees of this study were mainly one director and four staffs working at the Department of Human Resource.The research results show that the system quality is acceptable and the system security is perfect.All users have consistent opinions on the bad quality of information and they spend more time to check the data at work.The system use frequency of each user is different,mainly depending on the content of their work.Users who are used less have higher user satisfaction in human resource management information system.Most users perceive that the personal benefit is increased,and feel that this system can enhance personal benefits and improve the organization benefits for personnel management.

The Public Law Construction of Government Agencies’Obligations to Disclose When Handling Personal Information in the Digital Age

The protection of personal information plays an extremely important role in the construction of digital government.The duty to inform is a prerequisite core obligation that the government should fulfill in processing personal information,a concrete expression of the right to self-determination of personal information,and a prerequisite for the right to protection of personal information that works as a fundamental right to defense the intrusion from the government,as well as a procedural regulatory tool to restrain the government’s information power and prevent the risk of infringement.As the rules on the processing of personal information and the duty to inform have both the nature of public law,the government’s processing of personal information is also public law in nature,especially because of the constitutional value and power control function of the duty to inform,the construction of a system for the duty to inform cannot be copied from the rules applicable to private subjects,but should be tailored to the public law characteristics of the government’s processing of personal information,overcoming the shortcomings of the current rough and fragmented legislation,and set up a systematic regulation based on the public law in term of the legal subject,procedure,content,consequences of obligation violations and legal protection.

Personalized medicine approach to osteoporosis management in women: integrating genetics, pharmacogenomics, and precision treatments

Osteoporosis has emerged as a significant health issue among postmenopausal women.Addressing this concern necessitates a multifaceted approach encompassing genetics,pharmacogenomics,bone turnover markers,lifestyle factors,concurrent medical conditions,biomarkers,and advanced imaging techniques.Nonetheless,challenges in terms of cost-effectiveness and ethical considerations do exist.Fortunately,the convergence of technological progress and research endeavors offers a promising trajectory.The integration of genetic testing and pharmacogenomics into clinical practice holds substantial potential.This integration empowers healthcare professionals to forecast treatment responses and pinpoint individuals with elevated susceptibility,thereby enabling the implementation of tailored and efficacious interventions that optimize outcomes–personalized medicine.Given the intricate nature of osteoporosis,personalized strategies stand to greatly benefit women grappling with this condition.Further research and collaborative efforts are imperative to propel advancements within this domain,paving the way for further breakthroughs.

Bifunctional Asymmetric Fabric with Tailored Thermal Conduction and Radiation for Personal Cooling and Warming

Personal thermal management is emerging as a promising strategy to provide thermal comfort for the human body while conserving energy.By improving control over the heat dissipating from the human body,personal thermal management can provide effective personal cooling and warming.Here,we propose a facile surface modification approach to tailor the thermal conduction and radiation properties based on commercially available fabrics,to realize better management of the whole heat transport pathway from the human body to the ambient.A bifunctional asymmetric fabric(BAF)offering both a cooling and a warming effect is demonstrated.Due to the advantages of roughness asymmetry and surface modification,the BAF demonstrates an effective cooling effect through enhanced heat conduction and radiation in the cooling mode;in the warming mode,heat dissipation along both routes is reduced for personal warming.As a result,a 4.6℃ skin temperature difference is measured between the cooling and warming BAF modes,indicating that the thermal comfort zone of the human body can be enlarged with one piece of BAF clothing.We expect this work to present new insights for the design of personal thermal management textiles as well as a novel solution for the facile modification of available fabrics for both personal cooling and warming.

Development of Trees Management System Using Radial Basis Function Neural Network for Rain Forecast

Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitable planning of farming operation. Radial Basis Function Neural Network (RBFNN) algorithm was used in this study to predict rainfall and the main focus of this study is to analyze the factor that affects the performance of neural model. This study found that the model works better the more hidden nodes and the optimum learning rate is 0.01 with the RMSE 49% and the percentage accuracy is 57%. Besides that, it is found that the meteorology data also affect the model performance. Future research can be conducted to improve the rainfall forecast of this study and improve the tree management system.

Management of a Cluster of Foreign Body Ingestion Incidents in Patients with Borderline Personality Disorder

Objective: Deliberate foreign body ingestion (DFBI) has been reported in patients with personality disorders as part of a spectrum of self-harming behaviours, however the published literature is small (15 case reports). Method: This was a retrospective audit of medical and psychological management of a cluster of 12 DFBI incidents over 9 months in 4 young female patients with Borderline Personality Disorder (BPD). Results: All four patients knew one another from outpatient psychotherapy programmes. DFBI was associated with substance use in 5/12 incidents, and with precipitants (experiencing strong emotions, witnessing self-harm) in 4/12 incidents. Most DFBI involved sharp objects (razor blades, glass, safety pins). Medical intervention was initially active (endoscopy/surgery) but progressed to a more conservative, observational approach. Psychological management was initially restrictive, but also changed over time to focus on identifying distress, enhancing coping mechanisms and patient responsibility. Co-ordination of patient care management involvedintensive liaison (provision of interdisciplinary support and education) between medical, surgical and psychiatric teams. Conclusion: Management of DFBI in patients with BPD requires high levels of interdisciplinary collaboration. In this cluster of DFBI incidents, effective management was achieved with conservative medical/surgical methods (observation) and non-restrictive psychological approaches that enhanced patient self-efficacy.

Establishment of Person and Enterprise Process Model in Product Data Management System

Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.

Personal Data Use and Morality in the E-Business Environment

This paper deals with personal data use by firms in the e-business environment from the viewpoint of business administration and information ethics. Whereas the tremendous development of information and communication technology (ICT) has made it easier for firms to acquire, store, share, and utilise personal data on their customers, firms that use personal data are exposed to risks related to privacy issues. Since individuals fear the invasion of their privacy, the failure of a firm to appear or remain trustworthy would make it difficult for it to maintain accurate, up-to-date databases and to construct desirable business processes, which would affect the bottom line. Therefore, modern firms should do what they can to ensure that their customers trust them. For them, one promising way to remain trustworthy is to behave as a moral agent. Although it is difficult for any firm to meet the conditions necessary to be a moral agent, competence in behaving as a moral agent is a hard-to-imitate capability af firms for which personal data use is vital for enjoying the benefits of business relationships in the e-business environment.

Using self-determination theory to identify organizational interventions to support coal mineworkers’ dust-reducing practices

Advancing the application of safety and health(S&H)technologies is likely to remain a value in the mining industry.However,any information that technologies generate must be translated from the organization to the workforce in a targeted way to result in sustainable change.Using a case study approach with continuous personal dust monitors(CPDMs),this paper argues for an organizational focus on technology integration.Although CPDMs provide mineworkers with near real-time feedback about their respirable coal dust exposure,they do not ensure that workers or the organization will continuously use the information to learn about and reduce exposure sources.This study used self-determination theory(SDT)to help three mines manage and communicate about information learned from the CPDM technology.Specifically,35 mineworkers participated in two mixed-method data collection efforts to discuss why they do or do not use CPDMs to engage in dust-reducing practices.Subsequently,the data was analyzed to better understand how organizations can improve the integration of technology through their management systems.Results indicate that using the CPDM to reduce sources of dust exposure is consistent with mineworkers’self-values to protect their health and not necessarily because of compliance to a manager or mine.

Design and Implementation of Book Recommendation Management System Based on Improved Apriori Algorithm

The traditional Apriori applied in books management system causes slow system operation due to frequent scanning of database and excessive quantity of candidate item-sets, so an information recommendation book management system based on improved Apriori data mining algorithm is designed, in which the C/S (client/server) architecture and B/S (browser/server) architecture are integrated, so as to open the book information to library staff and borrowers. The related information data of the borrowers and books can be extracted from books lending database by the data preprocessing sub-module in the system function module. After the data is cleaned, converted and integrated, the association rule mining sub-module is used to mine the strong association rules with support degree greater than minimum support degree threshold and confidence coefficient greater than minimum confidence coefficient threshold according to the processed data and by means of the improved Apriori data mining algorithm to generate association rule database. The association matching is performed by the personalized recommendation sub-module according to the borrower and his selected books in the association rule database. The book information associated with the books read by borrower is recommended to him to realize personalized recommendation of the book information. The experimental results show that the system can effectively recommend book related information, and its CPU occupation rate is only 6.47% under the condition that 50 clients are running it at the same time. Anyway, it has good performance.

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare

Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the advent of the“Smart Healthcare”era,a series of cutting-edge technologies has brought new experiences to the management of chronic diseases.Among them,smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.However,how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management,in terms of quality of life,patient outcomes,and privacy protection,is an urgent issue that needs to be addressed.Artificial intelligence(AI)can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases.In addition,blockchain can improve healthcare services by authorizing decentralized data sharing,protecting the privacy of users,providing data empowerment,and ensuring the reliability of data management.Integrating AI,blockchain,and wearable technology could optimize the existing chronic disease management models,with a shift from a hospital-centered model to a patient-centered one.In this paper,we conceptually demonstrate a patient-centric technical framework based on AI,blockchain,and wearable technology and further explore the application of these integrated technologies in chronic disease management.Finally,the shortcomings of this new paradigm and future research directions are also discussed.

Component-Based Software Developing Method for Group Companies Management Information System

Considering the special requirements of group enterprise information management software, a new method of massive software development was put forward basing on the component technology and facing the ＂assemblage＂. It generalizes five key parts of the method system including the overall strategy, the application project method basing on the operation ＂assemblage＂, the field project method basing on component, the development method facing the component on the basis of the visible component platform, and the software development process model basing on the component ＂assemblage＂. Besides, this paper describes the process and principle of this method application with an example of the construction of a Communications Investment Group enterprise＇s management information system. The method provides a new idea for breaking away from the predicament appeared in the construction of present enterprise informatization and exploring the way of software industrialization.

An Authenticated Dynamic Key Management Scheme for Clustered Sensor Networks

Secure sensor networks has received much attention in the last few years.A sensor network always works unattended possibly in a hostile environment such as a battlefield.In such environments,sensor networks are subject to node capture.Constrained energy,memory,and computational capabilities of sensor nodes mandate a clever design of security solutions to minimize overhead while maintaining secure communication over the lifespan of the network.In this paper,an authenticated dynamic key management scheme,ADKM has been proposed.It provides efficient,scalable,and survivable dynamic keying in a clustered sensor network with a large number of sensor nodes.ADKM employs a combinatorial exclusion basis system (EBS) for efficiency and one-way hash chains for authentication.Analysis of security and performance demonstrate that ADKM is efficient in security of sensor networks.

Decentralized Mobile SNS Architecture and Its Personal Information Management Mechanism

Mobile SNS is one of the most popular topics of mobile Internet.In order to fulfill the user demand for self-maintained independent social network and ensure the privacy of their personal information and resources,the paper proposes system architecture of decentralized mobile SNS.In the temporary scenarios,the system makes use of the existent specification of FOAF(Friendof-a-Friend) to describe users' personal information and act as a certificate to be identified by SNS sites.Ticket-based Access Authorization System(TAAS) is provided to grant permission to acquire resources on personal portal.Meanwhile,the mechanism and algorithm are devised for user profile complete deletion when users are going to quit the service for the temporary scenarios.

Resolution of Relationship between Organizational Performance and Human Resource Management through Nonlinear Modeling

The relation between the HRM and the firm performance is analyzed statistically by many researchers in the literature. However, there are very few nonlinear approaches in literature for finding the relation between Human Resource Management (FIRM) and firm performance. This paper exposes the relationship between human resource management and organizational performance through the use of nonlinear modeling technique. The modeling is proposed based on Radial Basis Function (RBF) which is nonlinear modeling technique in literature. The relation between 12 input and 9 output parameters is investigated in this research that is collected between 54 companies in Turkey which indicated that the relationship between organizational management performance and relationship management can be modelled through nonlinearly.