Rational Allocation Of Resources Research Articles

Dempster–Shafer theory-based information fusion for natural disaster emergency management: A systematic literature review

The frequency and unpredictability of natural disasters pose serious challenges to emergency management in modern society. Effective emergency management requires not only rapid response, but also accurate assessment of the situation, rational allocation of resources and scientific decision-making. Dempster–Shafer theory (DST), as a powerful information fusion tool, has been widely used in natural disaster emergency management in recent years. This study sorted out the core related articles of DST in various directions in the field of natural disaster emergency management, and formed a systematic literature review. In order to support and guide the completion of this work, keywords were selected according to the rules of Systematic literature review (SLR) and the requirements of article content research to screen and determine the literatures. On this basis, relevant information of the selected literatures was analyzed, including authors, institutions, countries, keywords, etc. Then, according to the theoretical framework of integrated emergency management, fifteen structured research questions are put forward, involving various aspects of integrated emergency management system, and these questions are answered in detail. After that, it discussed the literature, and summarized the contribution and future development direction of DST based on information fusion in natural disaster emergency management. The final results show that in the field of natural disaster emergency management, DST plays various and important roles, among which one of the most important roles is the integration of decision-making evidence at various stages of disasters, so as to make better decisions. By combining with other methods, DST improves its limitations. And in the process to expand their scope of use. Then, it focuses on how to solve the extended theory, practical application dimension and related defects of DST in the field of natural disaster emergency management.

Evaluating the Snow Cover Service Value on the Qinghai–Tibet Plateau

The Snow Cover Service Value (SCSV) is an important component of the ecological assets of the Qinghai–Tibet Plateau (QTP). Exploring the SCSVs on the QTP is the key to maintaining the functions of climate regulators and Asian water towers, and it is also an important theoretical basis for maintaining the ecological security of ecological barrier areas. Using multi-source data such as daily and monthly observation data sets and related statistical yearbooks, an evaluation framework for the SCSVs on the QTP was constructed for the first time. The results showed that the average annual SCSV of the QTP from 2001 to 2020 was 6.99 trillion yuan, and the average annual climate regulation value was 5.81 trillion yuan, which was the most important SCSV. The Inner Plateau Basin, the Brahmaputra Basin, and the Yangtze Basin had the highest SCSVs, while the Yellow Basin had the lowest unit SCSV, where it was the most vulnerable area of snow cover resources on the QTP, and the SCSV of the Yellow Basin was significantly correlated with rainfall. The correlation between the SCSV and the temperature in the Indus and Ganges Basins was significant. The freshwater supply value of the snow in the Indus Basin and Tarim Basin was found to be able to reach 30% of the whole year in June, where it would be necessary to pay attention to the risk of flooding caused by snowmelt during the melting period. Finally, this paper discussed the strategies for the protection and development of snow resources in each basin based on the spatial distribution characteristics, seasonal variation characteristics, and influencing factors of the SCSVs. The research can provide reference for the rational allocation of snow resources and ecological protection on the QTP.

Multi‐graph representation spatio‐temporal attention networks for traffic forecasting in the cinematic metaverse

AbstractThe cinematic metaverse aims to create a virtual space with the context of a film. Users can enter this space in the form of avatars, experiencing the cinematic plot firsthand in an immersive manner. This requires us to design a rational computation resource allocation and synchronization algorithm to meet the demands of multi‐objective joint optimization, such as low latency and high throughput, which ensures that users can seamlessly switch between virtual and real worlds and acquire immersive experiences. Unfortunately, the explosive growth in the number of users makes it difficult to jointly optimize multiple objectives. Predicting traffic generated by the users' avatars in the cinematic metaverse is significant for the optimization process. Although graph neural networks‐based traffic prediction models achieve superior prediction accuracy, these methods rely only on physical distances‐based topological graph information, while failing to comprehensively reflect the real relationships between avatars in the cinematic metaverse. To address this issue, we present a novel Multi‐Graph Representation Spatio‐Temporal Attention Networks (MGRSTANet) for traffic prediction in the cinematic metaverse. Specifically, based on multiple topological graph information (e.g., physical distances, centerity, and similarity), we first design Multi‐Graph Embedding (MGE) module to generate multiple graph representations, thus reflecting on the real relationships between avatars more comprehensively. The Spatio‐Temporal Attention (STAtt) module is then proposed to extract spatio‐temporal correlations in each graph representations, thus improving prediction accuracy. We conduct simulation experiments to evaluate the effectiveness of MGRSTANet. The experimental results demonstrate that our proposed model outperforms the state‐of‐the‐art baselines in terms of prediction accuracy, making it appropriate for traffic forecasting in the cinematic metaverse.

Effectiveness of colorectal cancer screening integrating non-genetic and genetic risk: a prospective study based on UK Biobank data.

Few studies have evaluated the benefits of colorectal cancer (CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model (QCancer-10) and a 139-variant polygenic risk score to evaluate the effectiveness of screening on CRC incidence and mortality. We applied the integrated model to calculate 10-year CRC risk for 430,908 participants in the UK Biobank, and divided the participants into low-, intermediate-, and high-risk groups. We calculated the screening-associated hazard ratios (HRs) and absolute risk reductions (ARRs) for CRC incidence and mortality according to risk stratification. During a median follow-up of 11.03 years and 12.60 years, we observed 5,158 CRC cases and 1,487 CRC deaths, respectively. CRC incidence and mortality were significantly lower among screened than non-screened participants in both the intermediate- and high-risk groups [incidence: HR: 0.87, 95% confidence interval (CI): 0.81-0.94; 0.81, 0.73-0.90; mortality: 0.75, 0.64-0.87; 0.70, 0.58-0.85], which composed approximately 60% of the study population. The ARRs (95% CI) were 0.17 (0.11-0.24) and 0.43 (0.24-0.61), respectively, for CRC incidence, and 0.08 (0.05-0.11) and 0.24 (0.15-0.33), respectively, for mortality. Screening did not significantly reduce the relative or absolute risk of CRC incidence and mortality in the low-risk group. Further analysis revealed that screening was most effective for men and individuals with distal CRC among the intermediate to high-risk groups. After integrating both genetic and non-genetic factors, our findings provided priority evidence of risk-stratified CRC screening and valuable insights for the rational allocation of health resources.

Research on Compensation System of Land Expropriation and Requisition

With the development of our country's economy and the advancement of the urbanization process, the demand for land is increasing, and the phenomenon of land requisition to the countryside around the cities is becoming more and more common, affecting farmers' interests and the social security problem of landless farmers has become increasingly prominent. To deal with the land problem is the most important in the sustainable development of national economy, and the land expropriation compensation system is an important system to maintain the social stability of our country, and an important basis for rational allocation of land resources in our country. Therefore, it is particularly important to perfect the land expropriation compensation system in our country. Relevant government departments should determine reasonable compensation standards for land expropriation based on public interests, so as to reflect the rationality of land expropriation. At the same time, we should improve the compensation measures for land expropriation and requisition to ensure the maximization of farmers' interests.

How e-commerce can boost China’s high-quality agricultural exports

IntroductionExport quality improvement is a crucial path for a country or region to climb up the advanced division of labor in the global value chain. For developing countries that have long been at the lower end of the global value chain division of labor, the dominance of agricultural trade is often controlled by international retailers, leading to higher costs of agricultural trade and hindering the upgrading of the quality of agricultural exports. As a traditional agricultural exporting country, China still needs a competitive advantage despite the large scale of its agricultural exports. Currently, e-commerce can provide buyers and sellers with comprehensive transaction information and technical support, allowing them to realize rational allocation of resources and export upgrading. Therefore, studying how e-commerce can promote the quality upgrade of agricultural exports is crucial for China to build a trade power.MethodsThis paper clarifies the mechanism of e-commerce’s theoretical impact on the quality of agricultural exports and then empirically tests it using a high-dimensional fixed-effects model with Chinese customs data from 2000 to 2020 as a sample.ResultsThe results show that e-commerce significantly promotes the quality of agricultural exports in all regions of China, and this conclusion still holds after various robustness tests; the heterogeneity test shows that e-commerce fosters the quality of agricultural exports in eastern China, densely populated regions, and economically underdeveloped regions, especially in the case of heterogeneous products; the mechanism analysis confirms that e-commerce promotes the quality of agricultural exports mainly through the optimization of the agricultural industry chain and supply chain, and the enhancement of the level of servicing. Mechanism analysis confirms that e-commerce improves agricultural export quality mainly through optimizing the agricultural industry chain and supply chain, improving the level of servitization, and docking the demand information of the consumer market, etc. Expanded analysis shows that constructing cross-border e-commerce platforms also significantly improves the quality of micro enterprises’ agricultural exports. This paper enriches the research on e-commerce and agricultural trade.DiscussionThis paper provides an essential reference for constructing a robust agricultural trade country and developing high-quality agriculture. Despite encompassing data up to 2020, in the context of today’s global economic volatility directly affecting agricultural trade, future investigations will broaden the scope to delve deeper into how e-commerce can help countries cope with global economic uncertainty.

Efficiency and greenness evaluation of urban land use change in the Yangtze River Economic Belt, China

AbstractImproving urban land use efficiency and greenness is essential for achieving sustainable urban development and improving the well‐being of urban settlements. Using satellite‐based land use data, socioeconomic data, and sustainable development goal (SDG) indicators, we quantified the changes in the urban land use efficiency and greenness under rapid urban expansion in provincial cities in the Yangtze River Economic Belt (YREB) from 1990 to 2020. Over this period, urban area increased significantly, by 254.57%, at a rate of 191.41 km2 per year in the YREB, as national macro‐policies shifted the center of urban expansion westward. Nevertheless, the urban land use efficiency and greenness have both increased. The ratio of land consumption rate to population growth rate increased from 0.55 in 1990–2000 to 0.83 in 2010–2020 in the YREB, accompanied by an increase in the investment output ratio of fixed assets. In addition, the population‐weighted greenspace exposure increased by 5.31%, due to an 8.16% increase in the urban greenspace coverage, which improved the urban living environment amidst substantial urban population growth. We emphasize the importance of fostering coordinated development between central and western cities in the YREB. The results provide an important reference for the rational allocation of land resources, improving land use efficiency, and building resilient cities within global urbanization hotspots under the SDG framework.

Methods of Work Organization on Complex Restoration Capital Construction Projects

Statement of the problem. During a special military operation in Ukraine, a lot of buildings were destroyed. Also, with a high degree of probability, the production facilities that generate construction materials could be destroyed. In this regard, it is necessary to create a methodology that will allow, even at the planning stage, to reduce production costs and avoid downtime during construction and setup work due to the rational allocation of work and resources over time. Results. The method of restoration is proposed, which allows combining the survey of buildings, analysis of survey results, followed by a point selection of measures for the restoration of objects (repair, reconstruction, restoration) and optimization of the calendar plan by using matrices of combination coefficients, taking into account the fact of limited material resources in the places of restoration. Conclusions. The proposed methodology enables one to take into account all the limiting factors that arise in the process of construction, repair or reconstruction.

Evolution of an arid social-ecosystem with different water utilization spanning 12,000 years

Understanding the regime shifts of social-ecological systems (SES) and their local and spillover effects over time is crucial for ensuring future sustainability. However, limited research has focused on regime changes in SES under different modes of water resource utilization. In this study, we employ a concise theoretical framework to analyze regime shifts in the arid Tarim River Basin, considering changes in SES components. Additionally, we explore the drivers and local and regional effects of these shifts. The regime shifts in SES are categorized into four evolutionary phases: “Low productivity,” “Slow population expansion,” “Rapid environmental destruction,” and “Ecological restoration and improvement” over the past 12,000 years. The reciprocal coupling of SES components plays a vital role in determining the regime of SES, which is heavily influenced by the utilization of water resources and the degradation of the environment. While increasing water consumption is a core factor leading to environmental destruction, it also drives socioeconomic growth. During the process of SES shift, the rational allocation and use of water resources can shape an ideal regime that promotes regional ecosystem restoration. The empirical connections between the different phases of SES in the regime shift, their drivers, and their adverse or beneficial impacts provide valuable insights for sustainable SES management. Lessons from basin management that solely pursues single goals and focuses on local aspects, without considering these connections, have significant implications for long-term planning and policy formulation in arid basins worldwide.

Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering

The study of the expansion potential of artificial oases based on remote sensing data is of great significance for the rational allocation of water resources and urban planning in arid areas. Based on the spatio-temporal relationship between morphogenetic landform types and the development of artificial oases in Xinjiang, this study explored the development pattern of artificial oases in the past 30 years by using trend analysis and centroid migration analysis, constructing a series of landform–artificial oasis change indices, and investigating the suitability of different landforms for the development of artificial oases based on geomorphological location by adopting a hierarchical clustering method. The following conclusions are drawn: (1) From 1990 to 2020, the area of artificial oases in the whole territory continued to increase, with significant expansion to the south from 2005 to 2010. (2) Six categories of landform types for artificial oasis development were created based on the clustering results. Of these, 7.39% and 6.15% of the area’s geomorphological types belonged to the first and second suitability classes, respectively. (3) The optimal scale for analyzing the suitability of landforms for the development of artificial oases over the past 30 years in the whole area was 8 km, which could explain more than 96% of the changes in the growth of artificial oases. The distribution of landforms of first- and second-class suitability within the 8 km buffer zone of an artificial oasis in the year 2020 was 10.55% and 9.90%, respectively, and landforms of first-class suitability were mainly concentrated in the near plain side of the urban agglomerations located on the northern and southern slopes of the Tianshan Mountains, and the urban agglomerations at the southern edge of Altai Mountains. This study quantified the potential of different geomorphological types for the development of artificial oases and provided a basis for site selection in future artificial oasis planning and urban construction.

Employee-centered Industry 5.0 - Case analysis of Haier

How green digital intelligence and ecology promote enterprises to transform into industry 5.0 has attracted the attention of the industry and academia. Still, its internal driving mechanism at the micro level has not been clarified. Based on the perspective of enterprise dynamic capability and resource allocation, this paper studies the “path-process-capability” logical scheme of Industry 5.0 restructuring value chain. Firstly, the multi-case configuration analysis is carried out through focused stepwise quantitative case analysis to explore the resource collaboration path of Industry 5.0 transformation. Then, the process of digital intelligence and ecological reconstruction of the value chain is studied longitudinally for a single case, and the stage characteristics of green digital intelligence and ecology driving the Industrial 5.0 transformation of manufacturing enterprises are studied by combining the time series interval method and the critical event method. The process mechanism of digital intelligence and Industry 5.0 key capabilities are found. Aimed at the path problem of green digital intelligence and ecological reconstruction of the manufacturing value chain, based on multi-case statistical analysis and single-case in-depth analysis, the reconstruction mechanism and scheme of manufacturing ecological value chain were obtained. The research findings are as follows: firstly, four configuration forms of digital intelligence and ecological resource allocation are identified, and the rational allocation of resources is realized through the collaborative effect of resources. Secondly, the ecological process of green digital intelligence of manufacturing enterprises is based on the process of “standardization - online - integration - intelligence - ecological - Industry 5.0”, and the key technologies of each stage are identified. Third, in the transformation process of Industry 5.0, three key capabilities of enterprise digital production, digital drive, and ecological economy are constructed and data-led to promote the transformation and development of enterprise intelligent services and leverage the new business form of digital ecology.

Abstract PO4-20-01: A PROSPECTIVE PILOT STUDY OF MAMMOGRAPHIC PREDICTION OF WOMEN’S RISK (M-POWER) IN NIGERIA

Abstract Background There have been no sustained efforts at stemming the rising incidence and mortality from breast cancer in sub-Saharan African countries like Nigeria. Mammography is the gold standard for breast cancer screening and is associated with improved survival particularly among women 50 to 69. Reports from various parts of Nigeria show very low mammography screening uptake. Causes include lack of geographical access, financial issues (less than 5% of the population is covered by the National Health Insurance Scheme), lack of awareness and the increasing expertise gap from the continued brain drain, despite the already low number of radiologists in the country. Given these obstacles, our long-term goal is to devise a rational basis for identifying mammographic risk categories so that this resource can be deployed cost-effectively. We propose to carry out a 5-year prospective mammographic study in Nigerian women and to use machine learning to develop a risk prediction algorithm, so that following a single screening mammogram, the appropriate frequency of subsequent mammograms can be determined. Our immediate goal is to examine the feasibility of performing such a study. To this end, we have initiated a cross-sectional pilot study that will recruit up to 2000 women in multiple urban centers in Nigeria. Objective: To explore feasibility of creating a digital mammography image database representative of the radiological features of the breast of Nigerian women. Objective: To explore feasibility of creating a database that can be used to inform a predictive mammographic risk model for breast cancer and identify the appropriate population that will benefit from breast cancer screening in Nigeria. Design This is a prospective, open-label, cross-sectional pilot study in 2000 eligible women in Nigeria and will include a single screening mammography examination. The mammography images will be read by the study radiologist. The Pilot phase will determine the feasibility and aid in the design of the of the Extension phase in which up to 20,000 participants will undergo yearly mammography examination for 5 years. Incident cases of breast cancer during the study period will permit the development of deep learning algorithms for predicting the risk of breast cancer in this population. Main Eligibility Criteria: Inclusion Criteria All consecutive women aged ≥40 years and < 65 years presenting for screening mammography at the participating institutions will be eligible. Signed study-specific written informed consent. Exclusion Criteria Complaint of a focal dominant lump or a bloody or clear nipple discharge. History of breast implants. Any woman who is pregnant or has reason to believe that she might be pregnant. Statistical Methods Analyses of continuous data will be summarized using descriptive statistics where the following parameters will be reported: Number of observations, Number of missing observations, Mean, Median, Standard deviation (SD), Minimum (Min), Maximum (Max) Categorical data will be presented with absolute and relative frequency (n and %). Present Accrual and Target accrual Two hundred ninety-six women have been enrolled and screening digital mammographic images using GE Digital mammography equipment have been obtained on all participants at 2 study sites in 2 cities in Southern Nigeria. The target accrual is 2000 participants over 12 months. Conclusion Our preliminary experience to date suggests the feasibility of proceeding with a larger prospective study to define mammographic risk groups in Nigerian women which will permit the rational allocation of resources for breast cancer prevention activities in this underserved population. Contact Information: Dr Toyin Shonukan at tshonukan@yemanjacancercare.org Citation Format: Oluwatoyin Shonukan, Hyelakumi Ibrahim, Esther Udoh, Wahab Egbeolu, Kanyinsola Oyeyinka, Jonas Haggstrom. A PROSPECTIVE PILOT STUDY OF MAMMOGRAPHIC PREDICTION OF WOMEN’S RISK (M-POWER) IN NIGERIA [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-20-01.

Spatial distribution and influencing factors of CDC health resources in China: a study based on panel data from 2016-2021.

Measuring the development of Chinese centers for disease control and prevention only by analyzing human resources for health seems incomplete. Moreover, previous studies have focused more on the quantitative changes in healthcare resources and ignored its determinants. Therefore, this study aimed to analyze the allocation of healthcare resources in Chinese centers for disease control and prevention from the perspective of population and spatial distribution, and to further explore the characteristics and influencing factors of the spatial distribution of healthcare resources. Disease control personnel density, disease control and prevention centers density, and health expenditures density were used to represent human, physical, and financial resources for health, respectively. First, health resources were analyzed descriptively. Then, spatial autocorrelation was used to analyze the spatial distribution characteristics of healthcare resources. Finally, we used spatial econometric modeling to explore the influencing factors of healthcare resources. The global Moran index for disease control and prevention centers density decreased from 1.3164 to 0.2662 (p < 0.01), while the global Moran index for disease control personnel density increased from 0.4782 to 0.5067 (p < 0.01), while the global Moran index for health expenditures density was statistically significant only in 2016 (p < 0.1). All three types of healthcare resources showed spatial aggregation. Population density and urbanization have a negative impact on the disease control and prevention centers density. There are direct and indirect effects of disease control personnel density and health expenditures density. Population density and urbanization had significant negative effects on local disease control personnel density. Urbanization has an indirect effect on health expenditures density. There were obvious differences in the spatial distribution of healthcare resources in Chinese centers for disease control and prevention. Social, economic and policy factors can affect healthcare resources. The government should consider the rational allocation of healthcare resources at the macro level.

A Study on the Comprehensive Education Model of "Job Course Competition Certificate" for Vocational Undergraduate Big Data and Accounting Majors

The comprehensive education model of "on-the-job course competition certification" is an innovative talent cultivation model aimed at cultivating high-quality skilled talents that meet the needs of the new era. This model combines job skills, course learning, skill competitions, and certificate certification to provide students with a more practical educational experience. This time, the comprehensive education model of "on-the-job course competition certificate" will be applied to the teaching practice of vocational undergraduate big data and accounting majors. After briefly explaining the connotation of the "on-the-job course competition certificate" education model, this article analyzes and summarizes the integration methods of "on-the-job course competition certificate" from four aspects: course post integration, course certificate integration, course competition integration, and competition certificate integration. Finally, combining with the current situation of big data and accounting major teaching in vocational colleges, this article explores the practical path of the "on-the-job course competition certificate" comprehensive education model from the rational allocation of school enterprise resources, setting of talent training standards, construction of teacher teams, optimization of curriculum systems, and improvement of assessment and evaluation systems.

Risk management and empirical study of the doctor-patient relationship: based on 1790 litigation cases of medical damage liability disputes in China

BackgroundCompensation for medical damage liability disputes (CMDLD) seriously hinders the healthy development of hospitals and undermines the harmony of the doctor-patient relationships (DPR). Risk management in the DPR has become an urgent issue of the day. The study aims to provide a comprehensive description of CMDLD in China and explore its influencing factors, and make corresponding recommendations for the management of risks in the DPR.MethodsThis study extracted data from the China Judgment Online - the official judicial search website with the most comprehensive coverage. Statistical analysis of 1,790 litigation cases of medical damage liability disputes (COMDLD) available from 2015 to 2021.ResultsCOMDLD generally tended to increase with the year and was unevenly distributed by regions; the compensation rate was 52.46%, the median compensation was 134,900 yuan and the maximum was 2,234,666 yuan; the results of the single factor analysis showed that there were statistically significant differences between the compensation for different years, regions, treatment attributes, and trial procedures (P < 0.05); the correlation analysis showed that types of hospitals were significantly negatively associated with regions (R=-0.082, P < 0.05); trial procedures were significantly negatively correlated with years (R=-0.484, P < 0.001); compensat- ion was significantly positively correlated with years, regions, and treatment attributes (R = 0.098–0.294, P < 0.001) and negatively correlated with trial procedures (R=-0.090, P < 0.01); regression analysis showed that years, treatment attributes, and regions were the main factors affecting the CMDLD (P < 0.05).ConclusionsYears, regions, treatment attributes, and trial procedures affect the outcome of CMDLD. This paper further puts forward relevant suggestions and countermeasures for the governance of doctor-patient risks based on the empirical results. Including rational allocation of medical resources to narrow the differences between regions; promoting the expansion and sinking of high-quality resources to improve the level of medical services in hospitals at all levels; and developing a third-party negotiation mechanism for medical disputes to reduce the cost of medical litigation.

Postural control and cognitive flexibility in skilled athletes: Insights from dual-task performance and event-related potentials

Athletes of skill-oriented sports (hereinafter referred to as “skilled athletes”), such as gymnasts and rhythmic gymnasts, have demonstrated better postural control than nonathletes. However, previous studies have mainly focused on single postural tasks and have not considered how skilled athletes use and allocate attentional resources during postural control. This research used the event-related potential (ERP) to explore the postural control performance of skilled athletes under cognitive processes and their utilization and allocation of attentional resources. A dual-task paradigm was used to simulate the actual situation in sports. 26 skilled athletes and 26 nonathletes were required to perform postural control and task-switching simultaneously. The results showed that skilled athletes demonstrated more postural control stability and a higher accuracy of task-switching than nonathletes in all dual tasks. Compared with nonathletes, they showed a stable enhanced N1 (electrodes: Oz, O1, and O2) amplitude during three postures. Moreover, larger N2 component on Fz, FCz, and Cz and theta band power was found in the frontal cortex (on Fz, FCz) of skilled athletes under feet together and single leg standing posture. The study illustrated that skilled athletes show greater frontal activation during dual tasks, which allows for more rational and flexible brain attentional resource input and allocation in cognitive processes, this may be due to long-term professional training, which enables them to have a higher level of automation of postural control and cognitive flexibility. This study’s results offer valuable insights into the interplay between postural control and multitasking in skilled athletes, and its outcomes carry significant implications for the training and assessment of athletes across various sports.

"Why Do 'Zombie Companies' Remain 'Undead'?"

"Zombie companies" have long been a significant problem troubling the economic development and social progress of our country. Based on this issue, this project aims to explore the social impact factors of "zombie companies" and support enterprises to "de-zombify" to facilitate the rational and effective allocation of market resources. The discussion unfolds from theoretical, practical, mechanism, and policy levels consecutively. By exploring the intrinsic logical relationship between "zombie companies" and the market, we analyze reasonable mechanisms that can enable the effective exit of zombie companies, which aligns with the orderly operation of the market under modern economic conditions. This is conducive to the theoretical logic of facilitating the domestic circulation and achieving a virtuous cycle of industrial capital and financial capital. At the same time, it reveals potential internal issues within enterprises, such as lack of initiative, irrational allocation of resources, repayment of financial debts, etc., and proposes relevant policy recommendations for these issues, laying a solid foundation for the long-term development of enterprises and the market.

Choosing health facilities and impact factors of the choice in context of tiered medical system: A questionnaire survey of opinions of patients with multi-morbidity

BackgroundIn recent years, there has been limited research in China on the behavior of patients with multi-morbidity in choosing healthcare facilities under tiered medical system. Exploring the pattern of their choice will inform to better policy practice. ObjectiveThis study aims to analyze the behavior of patients with multi-morbidity in choosing healthcare facilities in context of tiered medical system, and its influencing factors. This will provide a reference for further implementing the tiered medical system and the rational allocation of medical resources. MethodsUsing a random sampling method, we selected patients with multi-morbidity who attended from June 1, 2019, to January 1, 2020, at the Shanghai Yangpu District Central Hospital Regional Medical Group, which includes Shanghai Yangpu District Central Hospital and three community health centers (Dinghai, Yanji, and Changbai). A self-designed questionnaire was used to collect general data from patients with multi-morbidity, to understand their awareness and actual compliance with the tiered medical system policy, their willingness to first visit community health centers under different disease control conditions, and the factors they consider when choosing healthcare facilities. Binary logistic regression was used to analyze the factors influencing the decision of patients with multi-morbidity to choose community health center for their initial consultation. ResultsA total of 1,100 questionnaires were distributed, and 1,072 valid questionnaires were completed, with a response rate of 97.45 %. Of the 1,072 participants with multi-morbidity, 912 (85.07 %) were aged above 60 years old; 624 participants (58.21 %) were aware of the tiered medical system; 940 participants (87.69 %) were willing to follow the design of medical treatment process under tiered medical system; 368 participants (34.33 %) were very familiar with the “1+1+1” (patients can choose one community health centre, one district hospital and one city hospital as preferred medical facilities, so called ‘1+1+1’ preference) combination contract project; 964 participants (89.93 %) had participated in the “1+1+1” combination contract project, but among these, 44 participants (4.56 %) chose non-contract medical facilities for their current medical treatment. 86.57 % (928/1072) patients with stable multiple conditions and 85.82 % (920/1072) patients with mild poorly controlled conditions choose community health centre as their first preferred medical provider. The factors considered by participants with multi-morbidity when choosing healthcare facilities were ranked by average score as follows: medical accessibility (5.50), medical technology level (5.13), patient satisfaction (3.74), medical insurance (3.60), medical expenses (2.93), and other factors (2.24). Binary logistic regression analysis showed that age and medical insurance were significant influencing factors in the decision to choose community health center for their initial consultation (P<0.05). ConclusionOlder adults are the most affected group by multi-morbidity and the main group choosing community health centre as their preferred medical service providers. Compared to regional medical centers, community health center has higher accessibility, which is a favorable factor for achieving first consultations in primary care for patients with multi-morbidity. Therefore, accelerating the construction of regional medical group, promoting the sharing and applying of high-quality resources in primary care, and improving the service quality and capacity of primary care facilities are beneficial for achieving the first consultations in primary care advocated by tiered medical system.

Using Copula functions to predict climatic change impacts on floods in river source regions

Flood frequency in river source regions is significantly affected by rainfall and snowmelt as part of climatic changes. A traditional univariate flood frequency analysis cannot reflect the complexity of floods, and when used in isolation, it can only underestimate flood risk. For effective flood prevention and mitigation, it is essential to consider the combined effects of precipitation and snowmelt. Copula functions can effectively quantify the joint distribution relationship between floods and their associated variables without restrictions on their distribution characteristics. This study uses copula functions to consider a multivariate probability distribution model of flood peak flow (Q) with cumulative snowmelt (CSm) and cumulative precipitation (CPr) for the Hutubi River basin located in northern Xinjiang, China. The joint frequencies of rainfall and snowmelt floods are predicted using copula models based on the Coupled Model Intercomparison Project Phase 6 data. The results show that Q has a significant positive correlation with 24-d CSm (r = 0.559, p = 0.002) and 23-d CPr (r = 0.965, p < 0.05). Flood frequency will increase in the future, and mid- (2050–2074) and long-term (2075–2099) floods will be more severe than those in the near-term (2025–2049). The probability of flood occurrence is higher under the SSP2-4.5 and SSP1-2.6 scenarios than under SSP5-8.5. Precipitation during the historical period (1990–2014) led to extreme floods, and increasing future precipitation trends are found to be insignificant. Snowmelt increases with rising temperatures and occurs earlier than estimated, leading to an earlier flood period in the basin and more frequent snowmelt floods. The Q under the joint return period is larger than that during the same univariate return period. This difference indicates that neglecting the interaction between precipitation and snowmelt for floods leads to an underestimation of the flood risk (with underestimations ranging from 0.3% to 22%). The underestimations decrease with an increase in the return period. The joint risks of rainfall or snowmelt according to various flood periods should be considered for rivers with multi-source runoff recharge in flood control design. This study reveals the joint impact of precipitation and snowmelt on extreme floods under climate change in river source regions. This study also provides a scientific basis for regional flood prevention and mitigation strategies, as well as for the rational allocation of water resources.

MADRLOM: A Computation offloading mechanism for software-defined cloud-edge computing power network

Cloud-edge computing power network often exhibits complex and heterogeneous structures, posing several challenges to computation offloading that significantly impact network performance and the efficient utilization of computation resources. In this paper, we propose a cloud-edge computing power network architecture that efficiently integrates cloud and edge computing resources into a single network system using software-defined networking technology to support upper-layer business applications. In this context, existing computation offloading methods struggle with issues like users' personalized requirements for latency and energy consumption, as well as the inability to adapt to dynamically complex environments. To overcome these challenges, we introduce a computation offloading mechanism, MADRLOM, focusing on the network's heterogeneity and modeling the computation offloading problem at the cloud-edge end. We formalize the offloading problem as a Markov process and employ a multi-agent deep reinforcement learning algorithm based on priority experience replay sampling to address the planning problem of computation offloading, allowing user equipment to continuously optimize offloading strategies in response to environmental changes and achieve rational resource allocation. Through dynamic offloading strategies, computation tasks can be intelligently allocated to appropriate computing nodes, thereby achieving optimal resource utilization. We utilized the Mininet simulation platform to construct the experimental environment for the software-defined cloud-edge computing power network and compared it with several representative computation offloading strategies. The experimental results demonstrate that the MADRLOM significantly reduces the total system overhead in the software-defined cloud-edge computing network and shows excellent adaptability to environmental changes.