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Objective We aimed to investigate the feasibility and method of constructing a traditional Chinese medicine (TCM) curative effect prediction model based on the data of Kechuanting acupoint plastering therapy in the treatment of bronchial asthma (asthma). Methods Data from the Chronic Disease Management Research Platform of 303 patients with asthma who were treated with Kechuanting acupoint plastering therapy for 6 weeks in the Department of Acupuncture and Rehabilitation of Jiangsu Hospital of Traditional Chinese Medicine from June to August 2018 to 2021 were selected. We used Phyton 3.10 for statistical analysis. After data preprocessing, the influencing factors were used to build models by Logistic regression, support vector machine, K-means clustering algorithm, Bayes algorithm, random forest method and Light gradient boosting machine (LightGBM) respectively, with the improvement of asthma control test score (ACT), forced expiratory volume in one second (FEV1) and exhaled nitric oxide (FeNO) as the outcome indicators. Then, the models were compared and analyzed. Subsequently, the superior model was used to establish the efficacy prediction model and verify its stability to obtain the accuracy rate and eliminate the relatively important factors. Results The accuracy rate of the Kechuanting acupoint plastering therapy curative effect prediction model established by the LightGBM model was more than 70%. Five important factors were selected, including allergic history, tabacco and alcohol abuse, plastering duration, ACT before treatment, and FeNO before treatment. According to the classification analysis and the relationship between the important factors and the outcome indicators, Kechuanting acupoint plastering therapy significantly improved the ACT of patients with no history of allergy, no tabacco and alcohol abuse, and poor ACT:5-15 points (P < 0.05). Furthermore, Kechuanting acupoint plastering therapy improved FeNO more significantly in patients with more than 3 years of treatment than those with no more than 3 years (P < 0.05). However, Kechuanting acupoint plastering therapy only improved FeNO in a few patients with poor asthma control levels (P < 0.05) and severe airway inflammation (FeNO>50x10-9) (P>0.05). Conclusion Acupoint plastering application has a significant effect on improving the control level of asthma, but its effect on improving airway inflammation is limited. It is feasible to use data from the chronic disease management research platform to construct the prediction model. After optimization and testing, the predictive model established based on the data of this study may provide an effective evaluation tool for targeted clinical treatment. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis is the second most deadly infectious disease after COVID-19 and the 13th leading cause of death worldwide. Among the 30 countries with a high burden of TB, China ranks third in the estimated number of TB cases. China is in the top four of 75 countries with a deficit in funding for TB strategic plans. To reduce costs and improve the effectiveness of TB treatment in China, the NHSA developed an innovative BP method. This study aimed to simulate the effects of this payment approach on different stakeholders, reduce the economic burden on TB patients, improve the quality of medical services, facilitate policy optimization, and offer a model for health care payment reforms that can be referenced by other regions throughout the world. Methods: We developed a simulation model based on a decision tree analysis to project the expected effects of the payment method on the potential financial impacts on different stakeholders. Our analysis mainly focused on comparing changes in health care costs before and after receiving BPs for TB patients with Medicare in the pilot areas. The data that were used for the analysis included the TB service claim records for 2019–2021 from the health insurance agency, TB prevalence data from the local Centre for Disease Control, and health care facilities' revenue and expenditure data from the Statistic Yearbook. A Monte Carlo randomized simulation model was used to estimate the results. Results: After adopting the innovative BP method, for each TB patient per year, the total annual expenditure was estimated to decrease from $2,523.28 to $2,088.89, which is a reduction of $434.39 (17.22%). The TB patient out-of-pocket expenditure was expected to decrease from $1,249.02 to $1,034.00, which is a reduction of $215.02 (17.22%). The health care provider's revenue decreased from $2,523.28 to $2,308.26, but the health care provider/institution's revenue-expenditure ratio increased from -6.09% to 9.50%. Conclusions: This study highlights the potential of BPs to improve medical outcomes and control the costs associated with TB treatment. It demonstrates its feasibility and advantages in enhancing the coordination and sustainability of medical services, thus offering valuable insights for global health care payment reform. [ABSTRACT FROM AUTHOR]

This study advances the Health Belief Model (HBM) within the context of medical tourism, exploring the intricate interplay between destination image, health beliefs, psychological distance, and the behavioral intentions of potential medical tourists. Our investigation reveals that destination image significantly influences perceived barriers and severity of risks, which, along with perceived susceptibility and benefits, strongly predicts tourists’ visitation intentions. Notably, the study revealed the dual roles of psychological distance: as a mediator between destination image and tourist preferences, and as a moderator affecting the impact of destination image on perceived risks. These findings underscore the importance of psychological factors in medical tourism decisions, suggesting that addressing psychological distance can enhance marketing strategies and improve patient outcomes. [ABSTRACT FROM AUTHOR]

• The psychological factors are determinants for delivery drivers to adopt electric trucks. • It is necessary to integrate technology anxiety into the extended UTAUT model. • Expanded the literature on UTAUT in the context of electric trucks. [ABSTRACT FROM AUTHOR]

The dynamical behaviors of an isolated population model involving delay-dependent parameters are investigated. It is shown that the positive equilibrium switches from being stable to unstable and then back to stable as the delay increases, and the Hopf bifurcation occurs finite times between the two critical values of stability changes which can be analytically determined. Moreover, the bifurcating periodic solutions are expressed analytically in an approximate form by the perturbation approach and Floquet technique. The direction and stability of the bifurcating periodic solutions are also determined. Finally, the validity of the results is shown by the consistency with the numerical simulations. [ABSTRACT FROM AUTHOR]

Abstract: Iris biometry has been widely used to recognize an individual in a natural and intuitive way. Conventional iris recognition systems transfer iris images to rectangle using polar coordinate after accurate segmentation, and have performed very well on accurate data. However, bovine iris images are usually irregular with respect to inactive participant, and the conventional methods cannot achieve high accuracy and true rotation invariance. In this paper, a new scheme is proposed based on scale invariant feature transform (SIFT) and bag-of-features. Firstly, region-based active contour is used to detect the inner boundary. Secondly, SIFT method is applied to detect the keypoints in the iris image, and points located in pupil region are removed. Then, feature vocabulary is constructed, and histogram representation for each iris image is generated. Finally, histogram distance is adopted for the matching test. Experimental results are provided to show the effectiveness and potential of developed noncooperative iris recognition. [Copyright &y& Elsevier]

• Examined determinants for Chinese taxi drivers to adopt electric vehicles for living. • Extended the UTAUT2 framework in the context of adopting electric vehicles by taxis drivers. • Incorporated the construct Satisfaction with Incentive Policies in the UTAUT2 framework. • Governments should investigate taxi driver's satisfaction with different incentive policies. • Electric vehicle manufacturers should enhance test-driving experience to taxi drivers. Replacing combustion vehicles with electric vehicles has been promoted by the Chinese government as a viable policy to reduce fuel consumption and greenhouse gas emissions. The purpose of this study is to examine factors that influence Chinese taxi drivers' adoption of electric vehicles for living. This study takes the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as the theoretical framework and extends it to examine the influence of taxi drivers' satisfaction over government's invectives on their adoption of electric vehicles for living (i.e., adoption intention and use behavior). A questionnaire-based survey was conducted in Shenzhen and Guangzhou from November 2018 to April 2019, and 725 valid samples were collected. The model has good explanatory power, and its predictive validity accounts for about 89% of the variance in adoption intention and 50% in use behavior. The statistical results supported that such constructs as Satisfaction with Incentive Policies, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Hedonic Motivation, Price Value, and Habit, are influencing factors on taxi drivers' intention of using electric vehicles (i.e., behavior intention). These constructs, together with Social Influence but excluding Habit, are also influential to the actual use of electric vehicles by taxi drivers for living (i.e., use behavior). This study expands the existing theoretical modeling for characterizing the adoption of electrical vehicles. The study suggests policy makers further investigate taxi driver's satisfaction with different incentive policies, and electric vehicle manufacturers focus on improving hedonic motivation for taxi drivers, e.g., providing test-drive experiences. [ABSTRACT FROM AUTHOR]

The frequent occurrence of food safety incidents is not only to be hazardous to the health of consumers, but also impacts the market of food consumption. Integrating the consumers' willingness to pay for traceability and the difference between suppliers' traceability, this paper provides four sourcing strategies for the retailer. Then, we investigate the sourcing decision of the retailer considering consumers' willingness to pay for traceability, the portion of consumers with traceability consciousness, probability of food safety incident, and additional penalty incurred by food safety incident. We find that increasing consumers' willingness to pay for traceability or expanding the portion of consumers with traceability consciousness may incur unintended consequence, such as an increase in sourcing quantity of non-traceable food product, while efforts on strengthening inspection and penalizing the retailer always lead to more supply of traceable food in the market. [ABSTRACT FROM AUTHOR]

In this paper, we characterize the humanitarian objectives of emergency resource allocation and distribution in disaster response operations. We formulate the humanitarian principles as three objective functions, i.e., lifesaving utility, delay cost and fairness. An integrated multi-objective optimization model that combines resource allocation with emergency distribution is developed, where a time space network is used to incorporate the frequent information and decision updates in a rolling horizon approach. The proposed model is shown to be a convex quadratic network flow problem, for which we design an efficient Variational Inequality algorithm. Computational results are reported to illustrate the performance of the proposed model and algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we concentrate on solving a convex time space network flow problem with decomposable structures. We first describe the convex time space network flow optimization model, and transform it into an equivalent variational inequality problem. Then, after exploring the decomposable structure of primal decision variables, we propose a novel decomposable self-adaptive projection-based prediction–correction algorithm (DSPPCA) to solve the model, and then further provide its convergent theory. Finally, we report the computational performances through computational experiments. Numerical results reveal that DSPPCA not only can enhance the accuracy and convergence rate significantly, but also can be a powerful search algorithm for convex optimization problems with decomposable structures of decision variables. [Copyright &y& Elsevier]

Abstract: It is known that a consensus problem on any connected complete Riemannian manifold can be transformed into the one on its strongly convex balls via the compression–decompression along geodesics. From the viewpoint of interior metrics, this paper mainly provides a consensus protocol for strongly convex geodesic balls, in which the communication can be switching and directed. With the aid of nonsmooth analysis tools on Riemannian manifolds, our analysis shows that all dynamical points involved can achieve consensus in finite time. Meanwhile, the corresponding global algorithm is given, with its application to the consensus problem of rotation attitudes, as well as a case simulation, to demonstrate and verify our proposed techniques. [Copyright &y& Elsevier]

Abstract: In view of the fact that prototypes of Riemannian manifolds range from Euclidean surfaces to Lie groups, operator spaces, etc., the paper explores common consensus schemes for connected complete Riemannian manifolds. After studying the restriction exponential map, we introduce a local consensus protocol with switching communication topologies for the manifolds via the isometric mapping, based on one of the Euclidean consensus protocols. Equipped with the compression–decompression functions, we extend the local consensus protocol, and put forth a global consensus algorithm for any such manifolds. These consensus schemes can provide common solutions to the consensus problems arising from various nonlinear spaces or abstract spaces belonging to connected complete Riemannian manifolds. In particular, they are simple and concise, and can converge in finite time. Simulation on the unit sphere is provided to verify our consensus schemes, and to demonstrate the usage of our proposed techniques. [Copyright &y& Elsevier]

Background: Dietary behaviors significantly influence health outcomes across populations. Unhealthy diets are linked to serious diseases and substantial economic burdens, contributing to approximately 11 million deaths and significant disability-adjusted life years annually. Digital dietary interventions offer accessible solutions to improve dietary behaviors. However, attrition, defined as participant dropout before intervention completion, is a major challenge, with rates as high as 75%-99%. High attrition compromises intervention validity and reliability and exacerbates health disparities, highlighting the need to understand and address its causes., Objective: This study systematically reviews the literature on attrition in digital dietary interventions to identify the underlying causes, propose potential solutions, and integrate these findings with behavior theory concepts to develop a comprehensive theoretical framework. This framework aims to elucidate the behavioral mechanisms behind attrition and guide the design and implementation of more effective digital dietary interventions, ultimately reducing attrition rates and mitigating health inequalities., Methods: We conducted a systematic review, meta-analysis, and thematic synthesis. A comprehensive search across 7 electronic databases (PubMed, MEDLINE, Embase, CENTRAL, Web of Science, CINAHL Plus, and Academic Search Complete) was performed for studies published between 2013 and 2023. Eligibility criteria included original research exploring attrition in digital dietary interventions. Data extraction focused on study characteristics, sample demographics, attrition rates, reasons for attrition, and potential solutions. We followed ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and used RStudio (Posit) for meta-analysis and NVivo for thematic synthesis., Results: Out of the 442 identified studies, 21 met the inclusion criteria. The meta-analysis showed mean attrition rates of 35% for control groups, 38% for intervention groups, and 40% for observational studies, with high heterogeneity (I²=94%-99%) indicating diverse influencing factors. Thematic synthesis identified 15 interconnected themes that align with behavior theory concepts. Based on these themes, the force-resource model was developed to explore the underlying causes of attrition and guide the design and implementation of future interventions from a behavior theory perspective., Conclusions: High attrition rates are a significant issue in digital dietary interventions. The developed framework conceptualizes attrition through the interaction between the driving force system and the supporting resource system, providing a nuanced understanding of participant attrition, summarized as insufficient motivation and inadequate or poorly matched resources. It underscores the critical necessity for digital dietary interventions to balance motivational components with available resources dynamically. Key recommendations include user-friendly design, behavior-factor activation, literacy training, force-resource matching, social support, personalized adaptation, and dynamic follow-up. Expanding these strategies to a population level can enhance digital health equity. Further empirical validation of the framework is necessary, alongside the development of behavior theory-guided guidelines for digital dietary interventions., Trial Registration: PROSPERO CRD42024512902; https://tinyurl.com/3rjt2df9., (©Jian Wang, Jinli Mahe, Yujia Huo, Weiyuan Huang, Xinru Liu, Yang Zhao, Junjie Huang, Feng Shi, Zhihui Li, Dou Jiang, Yilong Li, Garon Perceval, Lindu Zhao, Lin Zhang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.08.2024.)

The world becomes advance rapidly, and the demand of perishable food increases in the global market. Food firms perceive the cheapest supply chain process for the delivery of products to end consumers. Apart from that, consumer demands high quality and safe products with competitive price. In the global intense competition, China introduced One Belt One Road (OBOR) advanced feature supply chain management system to cut the cost of production for these product firms as well as functionally deliver high quality and green products to end consumer without affecting from high environment temperature. Respectively, the graphical research model and the multi-objective method were developed to examine the estimated perishable product trading figures with consideration to quality, which is achieved by accumulating the advanced transportation features offered by OBOR supply chain management as compared to ancient rail route supply chain. To prove this, "simulation optimization function was applied to measure the probability of time-saving for perishable product quality from environmental effects and its influences over product demand." Some perishable products were selected, and their trading figures and demand value were measured by comparing both rail route environmental effects over demand, weights of products, and trade. The results declare perishable food quality and trading volume increased due to fast delivery of products to numerous countries, having cold supply chain feature under OBOR supply chain management and estimated 25 days of time-saving. Comparative analysis discloses the coherent picture of both trading routes used for delivering the products. "The findings show large amount of time-saving maximizes perishable product quality from environmental influence" estimated 3 times higher with fast train supply chain. Conceptually, perceived from the idea, when and if maglev train 600 km over an hour will be used for perishable product supply chain purpose in the near future, the estimated quality of perishable products and trading is considered to be more than 5 times higher as compared to ancient supply chain route. The study suggests future research direction on topics, food quality along with supply chain management system, and environmental impact measurement policy under different supply chain routes., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: Conflict of interests The authors declare that there is no conflict of interests.

Background: The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots., Objective: The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis., Methods: We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence., Results: The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention., Conclusions: Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including "allocative value," "technology value," and "personalized value.", (©Jianxia Gong, Vikrant Sihag, Qingxia Kong, Lindu Zhao. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 01.11.2021.)

Background and Purpose: Telehealth bring significant benefits including improved quality of healthcare, efficiency and cost containment, especially for chronic patients and the elderly. China is the second largest country of investment in telemedicine systems, but the acceptance and behavioral intentions of the technology are still low in the elderly. The objective of this study is to explain the micro-mechanism that determines the behavioral intentions to use telemedicine systems from the perspective of elderly patients based on an extended Technology Acceptance Model., Methods: A sample consisting of 436 elderlies selected through multistage cluster sampling from four cities in mainland China. The empirical study was conducted to examine the proposed model by two aspects: measurement model and structural model., Results: The study determined that medical service satisfaction (t = 6.770, β = 0.332), ease of use (t = 5.200, β = 0.179), information quality (t = 12.540, β = 0.639) had a significant impact on the elderly patients' acceptance to telehealth, and the acceptance had a significant impact (t = 14.356, β = 0.697) on the elderly patients' behavior intentions of telehealth. The results also show that the variable of acceptance has significant mediating effects among the theoretical model., Conclusions: This study confirms the applicability of the extended Technology Acceptance Model in the behavioral intentions among elderly people in China using telehealth systems. The results indicate that relationship between telehealth systems and physical medical services are mutually reinforcing rather than alternative. The study will help technology developers better understand the behavioral characteristics of the elderly and encourage healthcare providers to better understand the true need of telehealth systems. These findings provide valuable information to telehealth system developers, governments, investors, and hospitals to promote the use of this technology by elderly patients., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Competing Interests: Conflict of Interests The authors declare that there is no conflict of interests.