Big Model Strategy for Bridge Structural Health Monitoring Based on Data-Driven, Adaptive Method and Convolutional Neural Network (CNN) Group

This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemble methods,collaborative learning,and distributed computing,the approach effectively manages the complexity and scale of large-scale bridge data.The CNN employs transfer learning,fine-tuning,and continuous monitoring to optimize models for adaptive and accurate structural health assessments,focusing on extracting meaningful features through time-frequency analysis.By integrating Finite Element Analysis,time-frequency analysis,and CNNs,the strategy provides a comprehensive understanding of bridge health.Utilizing diverse sensor data,sophisticated feature extraction,and advanced CNN architecture,the model is optimized through rigorous preprocessing and hyperparameter tuning.This approach significantly enhances the ability to make accurate predictions,monitor structural health,and support proactive maintenance practices,thereby ensuring the safety and longevity of critical infrastructure.

The Impact of Big Five Personality Traits on Older Europeans’ Physical Health

Investigating the role of Big Five personality traits in relation to various health outcomes has been extensively studied. The impact of “Big Five” on physical health is here explored for older Europeans with a focus on examining age groups differences. The study sample included 378,500 respondents derived from the seventh data wave of Survey of Health, Aging and Retirement in Europe (SHARE). The physical health status of older Europeans was estimated by constructing an index considering the combined effect of well-established health indicators such as the number of chronic diseases, mobility limitations, limitations with basic and instrumental activities of daily living, and self-perceived health. This index was used for an overall physical health assessment, for which the higher the score for an individual, the worst health level. Then, through a dichotomization process applied to the retrieved Principal Component Analysis scores, a two-group discrimination (good or bad health status) of SHARE participants was obtained as regards their physical health condition, allowing for further con-structing logistic regression models to assess the predictive significance of “Big Five” and their protective role for physical health. Results showed that neuroti-cism was the most significant predictor of physical health for all age groups un-der consideration, while extraversion, agreeableness and openness were not found to significantly affect the self-reported physical health levels of midlife adults aged 50 up to 64. Older adults aged 65 up to 79 were more prone to open-ness, whereas the oldest old individuals aged 80 up to 105 were mainly affected by openness and conscientiousness. .

Opportunities and Challenges of College Mental Health Education from the Perspective of Big Data

This paper explores the opportunities and challenges of college mental health education from the perspective of big data.Firstly,through literature review,the importance of mental health education and the current issues are elucidated.Then,from the perspective of big data,the potential opportunities of big data in college mental health education are analyzed,including data-driven personalized education,real-time monitoring and warning systems,and interdisciplinary research and collaboration.At the same time,the challenges faced by college mental health education under the perspective of big data are also pointed out,such as data privacy and security issues,insufficient data analysis and interpretation capabilities,and inadequate technical facilities and talent support.Lastly,the research content of this paper is summarized,and directions and suggestions for future research are proposed.

Big tech,big data and the new world of digital health

This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech companies into healthcare,the second will be the monetization of consumer data and the creation of health data marketplaces;and the third will be the growth of Asia as a leader in digital health.Big tech already has the advantage of a massive consiuner base,data and analytics which enable them to understand consumers;and complementary technologies,like wearables,that will drive the consumerization of healthcare.This expansion can happen quickly and already is creating challenges for regulators as they try to catch up.The vast volumes of data and the ability of technology such as blockchain to enable data owners to monetize their data,will lead to the development of health data marketplaces,which can connect and monetize data for data owners and make it available for scientific discovery.The developments in self-sovereign identity,will make it possible for individuals to monetize their health data in the future.Finally,we see the emergence of Asia as a powerhouse for the digital health of the future,with vast populations,mobile technology and increasing adoption of wearable devices.Consumer focused health care driven by data will change the institutional models of the past.

Motives Underlying Organic Food Consumption in Turkey： Impact of Health, Environment, and Consumer Values on Purchase Intentions

Raising ecological awareness and health concerns create question marks about healthiness and sustainability of conventional foods in customers＇ minds. Due to augmented mass media coverage of environmental problems, health concerns related to consumption of genetically modified food and/or chemical contaminants in food, and consumers＇ increasing interest in healthy nutrition and environmental protection, there is a growing interest for organic foods in all over the world. Growing interest for organic foods, and increasing production and demand in organic food market has made organic food consumption a significant topic of research. Although organic food market and demand for organic foods have also been growing in Turkey, literature regarding organic food consumption is not very extensive. Therefore, this study aims to understand the underlying motives for organic food consumption in Turkey, and to explore the factors affecting Turkish consumers＇ attitudes towards organic foods and the behavioral intention of Turkish consumers to purchase organic food by the help of the theory of reasoned action （TRA）. The results of 622 successful surveys used for this empirical research indicate that Turkish consumers＇ attitudes towards organic foods are determined by perception of organic foods, consumer values, and price perception, while their purchase intention is determined by health consciousness, perception of organic foods, consumer values, price perception, and environmental concerns.

Addressing the Security Challenges of Big Data Analytics in Healthcare Research

Big data and associated analytics have the potential to revolutionize healthcare through the tools and techniques they offer to manage and exploit the large volumes of heterogeneous data being collected in the healthcare domain. The strict security and privacy constraints on this data, however, pose a major obstacle to the successful use of these tools and techniques. The paper first describes the security challenges associated with big data analytics in healthcare research from a unique perspective based on the big data analytics pipeline. The paper then examines the use of data safe havens as an approach to addressing the security challenges and argues for the approach by providing a detailed introduction to the security mechanisms implemented in a novel data safe haven. The CIMVHR Data Safe Haven (CDSH) was developed to support research into the health and well-being of Canadian military, Veterans, and their families. The CDSH is shown to overcome the security challenges presented in the different stages of the big data analytics pipeline.

Analysis on the Risks of Health Information Platform under the Environment of Big Data

Big Data applications in the health service field have gradually been paid more close attention. Based on big data technology, more and more health information platforms are beginning to take effects, such as disease prevention, precision medicine, reducing expenditures for medical care and public health, improving medicine research and development. Meanwhile, the platforms have to face a lot of risks, such as health data disclosure, dispute of health data ownership, implicit contradiction explicit, unsustainable platform operation and so on. With the solutions of these risks, the construction of the public platform can provide better service for the citizens, hospital, pharmaceutical company, R＆D institutions or and other parties.

Exploring the Significance and Implementation Strategies of Mental Health Education for College Students

College students are influenced by diverse cultures in the new era,thus their inner world is rich and changing rapidly.The acceleration of social rhythm can easily lead to different kinds of psychological problems.Mental health education is people-oriented,using scientific methods and means to train high-quality talents with all-round development across the world.A healthy psychological state can promote the sound development of students,make them establish correct core social values,and realize self-value.At present,there are some problems in university mental health education,such as single form and imperfect system.At the same time,college education plays an important role in the formation of ideas for college students’ideological values.As a front-line student worker,college counselors should cooperate with the school’s psychological departments to improve the college psychological education system,rationally plan the psychological teaching program,and pay attention to the college students’mental health education.The government should also take into account the need to ensure that the education system is not undermined by the lack of a comprehensive and effective education system.

An Edge-Fog-Cloud Computing-Based Digital Twin Model for Prognostics Health Management of Process Manufacturing Systems

The prognostics health management(PHM)fromthe systematic viewis critical to the healthy continuous operation of processmanufacturing systems(PMS),with different kinds of dynamic interference events.This paper proposes a three leveled digital twinmodel for the systematic PHMof PMSs.The unit-leveled digital twinmodel of each basic device unit of PMSs is constructed based on edge computing,which can provide real-time monitoring and analysis of the device status.The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters,which are deployed for the manufacturing execution on the fog server.The shop-leveled digital twin maintenancemodel is designed for production planning,which gives production instructions fromthe private industrial cloud server.To cope with the dynamic disturbances of a PMS,a big data-driven framework is proposed to control the three-level digital twin models,which contains indicator prediction,influence evaluation,and decisionmaking.Finally,a case study with a real chemical fiber system is introduced to illustrate the effectiveness of the digital twin model with edge-fog-cloud computing for the systematic PHM of PMSs.The result demonstrates that the three-leveled digital twin model for the systematic PHM in PMSs works well in the system’s respects.

Digital interventions empowering mental health reconstruction among students after the COVID-19 pandemic

With the gradual end of the coronavirus disease 2019(COVID-19)pandemic,the reconstruction of students’mental health is urgently necessary.Digital interventions offer advantages such as high accessibility,anonymity,and accurate identification,which can promote the reconstruction of students’mental health through the provision of psychological support platforms,psychological assessment tools,and online mental health activities.However,we recognize that digital interventions must undergo many adjustments,and corresponding ethical norms require further clarification.It is crucial for different stakeholders to collaborate and work toward maximizing the effectiveness of digital interventions for the reconstruction of mental health after the COVID-19 pandemic.

An investigation of the health value and self-care capabilities of the elderly in urban-rural fringe area nursing homes and the related in？uencing factors

Objective：To investigate the health value and self-care capabilities of the elderly living in urban-rural fringe area nursing homes and the factors that influence these variables.Methods：A cluster sampling method was used to select 280 elderly individuals from seven urban-rural fringe communities in Xianning to complete a survey regarding their health value and self-care capabilities.Results：The total health value and self-care capability scores of the elderly were 7.45 ± 1.45 and100.25±22.56,respectively.Both of these scores significantly differed by age,education level,marital status,and income（P 〈 0.05,P 〈 0.01）.Self-care capability was correlated with health value（r=0.521）.A multivariate linear regression analysis showed that health value,marital status,and age predicted selfcare capability.Conclusions：Elderly people living in the urban-rural fringe area with higher health values also had higher self-care capabilities.The self-care capabilities of the elderly can be enhanced by improving their health value using the ＂knowing-trusting-acting＂ model.

Valuing Health Effects of Natural Radionuclides Releases from Yatagan Power Plant

The objective of this paper is the valuation of radiological health effects of Yatagan Power Plant. To this aim the radiation dose calculations are carried out for the population living within 80 km radius of the plant. The average of the maximum measured specific isotopes 238U, 232Th and 226Ra in the flying ash samples are considered as radioactive sources. Based on the dose calculations, first the stochastic health effects and then monetary health effects are estimated. The estimated total collective dose and economic value of the pre-dicted health effects are 0.3098 man Sv/y and 14791 US$/y respectively. The results obtained from the dose calculations are lower than the limits of International Commission of Radiation Protection (ICRP) and it does not pose any risk for public health. Monetary value of health risks is also negligible in comparison to the av-erage yearly sales revenue of the plant which is 250 million US$.

Female Genital Cut in Relation to Its Value and Health Risks among the Kisii of Western Kenya

Background: The practice of female genital cutting as a cultural obligation is widespread in Kenya but there is little consensus about its effects on health. Some of the health risks associated with female genital cut range from minor and short-term to major and long-term effects including pain, bleeding, infections, and, in the extreme, death. Female genital cut is widespread among the Kisii but there is no adequate information about how it is currently practised and the value people attach to it. Objective: The objective was to establish the value of female genital cut as well as the health risks associated with the practice among the Kisii community of western Kenya. Methods: This was a cross-sectional study, which employed a mixed method approach to generate both quantitative and qualitative data. The quantitative data were obtained from a randomly selected sample of 373 respondents while quantitative data were generated from focus group discussions as well as key informants interviews. Results: The Kisii consider female genital cut a cultural identifier inherited from past generations and whose main value is a rite of passage from girlhood to womanhood. Majority (63%) had heard of the health risks associated with female genital cut including transmission of infections, excessive bleeding and pain. But most of the community did not seem to know the long-term health consequences associated with female genital cut. Even though knowledge on the campaigns to eradicate the practice was found to be wide spread, the community’s response toward the campaigns was less than positive. Conclusions: The authors conclude that female genital cut continues to persist in this community because of its value as a rite of passage, which currently has no substitute. This cultural demand by far outweighs the health risks associated with female genital cut, which are being mitigated through medicalization of the practice. For intervention programmes to succeed a more culturally sensitive campaign that is acceptable or appropriate alternative rite of passage is required.

A Study Protocol on the Evaluation of Referral Strategies for Inflammatory Arthritis in Primary Care Patients at the Level of Healthcare Organization, Patient Relevant Outcomes and Costs

Background: Considering the importance of getting the right patient at the right location to maintain and optimize quality of life of inflammatory arthritis patients, appropriate referral by general practitioners is essential. This study aims to assess the effect and cost effectiveness of different referral strategies for inflammatory arthritis in primary care patients. Methods: This study follows a cluster randomized controlled trial design. General practitioners from primary care centers in Southwest-The Netherlands are randomly assigned to either one of the two strategic interventions for referring adult patients who are in the opinion of the general practitioner suspected of inflammatory arthritis: 1) Standardized digital referral algorithm based on existing referral models PEST, CaFaSpA and CARE;2) Triage by a rheumatologist in the local primary care center. These interventions will be compared to a control group, e.g. usual care. The primary outcome is the percentage of patients diagnosed with inflammatory arthritis by the rheumatologist. Secondary outcomes are quality of life as a patient reported outcome, work participation and healthcare costs. These data, including demographic and clinical parameters, are prospectively collected at baseline, three, six, and twelve months. Discussion: If this study can demonstrate improvements in appropriate referrals to the rheumatologist, thereby improving cost-effectiveness, there is sufficient supporting evidence to implement one of the referral strategies as a standard of care. Finally, with these optimization strategies a higher quality of care can be achieved, that might be of value for all patients with arthralgia. Trial Registration: NCT03454438, date of registration: March 5, 2018. Retrospectively registered: https://clinicaltrials.gov/ct2/show/NCT03454438?term=NCT03454438&draw=1&rank=1.

Health Analytics, Economics and Medicine toward a 21st Century Health Care System

After a review of recent developments in precision medicine, population health sciences and innovative clinical trial designs, and in health economics and policy, we show how innovations in health analytics can capitalize on the advances in biomedicine and health economics towards developing a data-driven and cost-effective 21st century health care system. In particular, we propose a mutually beneficial public-private partnership that combines individual responsibility with community solidarity in building this health care system.

Human Exposure Assessment of Element Pollution for Environmental Health Implications: Teeth as a Biomonitoring Tool

Reference values reflecting the findings of natural concentrations of teeth in a well-defined group of individuals, are indispensable, if one is to interpret results generated for clinical utility. Hence, a comprehensive compilation of literature survey is attempted to make available as a reference guideline for tooth element concentrations. Presently, the reference values are proposed for 19 elements. Several factors that are found influencing element levels, are common to any biosample and are broadly grouped under four categories namely, the factors of teeth, donor, environment and analytical methods. How best the influencing factors to be considered during analysis, are discussed. It is elucidated that standardized method of analysis with quality assurance and precision will reduce the ambiguity of comparison of inter-laboratory measurement. When the merits and demerits of element measurements are evaluated, it is recognized that except a hurdle of difficult specific sampling, many advantages make teeth an attractive material for environmental health monitoring of population and for assessment of element status of deficiency and excess due to differential exposure. The available data of tooth elements are lesser in comparison to data of blood and hair;further studies are required for reference values of others elements and for distribution pattern in different conditions, parts and types of teeth.

Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact

In this study, we explored to combine traffic maps and smartphone trajectories to model traffic air pollution, exposure and health impact. The approach was step-by-step modeling through the causal chain: engine emission, traffic density versus traffic velocity, traffic pollution concentration, exposure along individual trajectories, and health risk. A generic street with 100 km/h speed limit was used as an example to test the model. A single fixed-time trajectory had maximum exposure at velocity of 45 km/h at maximum pollution concentration. The street population had maximum exposure shifted to a velocity of 15 km/h due to the congestion density of vehicles. The shift is a universal effect of exposure. In this approach, nearly every modeling step of traffic pollution depended on traffic velocity. A traffic map is a super-efficient pre-processor for calculating real-time traffic pollution exposure at global scale using big data analytics.

The Acceptance Intention of Consumers for a Dynamic Payment Mechanism for Health Insurance Coverage

Currently, a consumer＇s monthly premium payment amount remitted to the National Health Insurance is based on the ＂monthly real wages,＂ while commercial health insurance uses ＂consumer age＂ as the basis for the premium amount charged. In reality, health, salary, and age have no visible connection. Therefore, the insurance premium scheme using salary and age as standards should be improved and adjusted upon. This study uses the Decomposed Theory of Planned Behavior as the research basis, and through the designed questionnaire, investigates the health data gathered from wearable devices and uses big data to process the constructed health assessment indicators. These indicators will be used to analyze whether consumers are willing to contribute to their health insurance using the dynamic payment mechanism. Subsequently, empirical research was performed using hypothesis architecture and structural equation.

Circular Economy in HealthCare Challenges and Issues

Some major countries like India investing in biopharmaceutical industry have designed new business models of circular economics called the“Uber for HealthCare”for instance by Basu et al.,for medical equipment in India(Euro,Healthcare Stream,&Dublin 2018).This raises major challenges for global supply of medicine and Value Chains in life science.This contribution will provide a review of recent experiences and an analysis of how it impacts current global value chains.Current economic model development strengthening the demand side of the system and applications of choice modeling to capture heterogeneity of demand at individual level face with new circular strategies implemented by health care organizations and economic suppliers.The all-value system is challenged by such models including the critical decision points at prognostic,diagnostic,and treatment stages;platforms such as the Her2adaptive technology platform with cost sensitivity indexes proposed by Huttin and Liebman(Technology&HealthCare,2011)face also potential adaptation to integrate new priorities:for instance,in circular economy with integration of circular touch points.Research results like Van Boerdonk et al.(2021),demonstrate that reaching cleaner production with higher environmental values may become“paradoxical with lower or unimportant customer value”.Government and payers may need to create new policies for waste management and for sustaining reasonable and fair value for money in the health system.Moreover,the economics of sharing economy may need to find appropriate forms of centralization or decentralization in the organizations of health systems and decision-making processes.Circular models in health care in sharing economy may benefit single pathway models,often too expensive for affordable welfare contracts.This paper will continue the previous research agenda and papers on global value chains with the use of TiVa OECD database(joined in the WB-WTO project)and a quality paper on the biotech development chain and Covid-19(Huttin,2019;2021).

Elderly Health Care-Security and Privacy Issue

The current trend in offering universal health care based on open distributed health care network which will provide health care to elderly,socially and economically weak population,and physically challenged patients has lead to rapid digitization of health care data,and wireless medium for data communication.Although it has many advantages and has immense potential to improve health care availability,it has created many challenges in maintaining health care services,in particular in offering security and privacy of the most vulnerable members of society who are the elderly.In this paper we identify the current status of elderly care,their vulnerabilities,and challenges faced to offer them health care in total privacy and dignity.