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The recognition of food images is of great significance for nutrition monitoring, food retrieval and food recommendation. However, the accuracy of recognition had not been high enough due to the complex background of food images and the characteristics of small inter-class differences and large intra-class differences. To solve these problems, this paper proposed a food image recognition method based on transfer learning and ensemble learning. Firstly, generic image features were extracted by using the convolutional neural network models (VGG19, ResNet50, MobileNet V2, AlexNet) pre-trained on the ImageNet dataset. Secondly, the 4 pre-trained models were transferred to the food image dataset for model fine-tuning. Finally, different basic learner combination strategies were adopted to establish the ensemble model and classify feature information. In this paper, several kinds of experiments were performed to compare the results of food image recognition between single models and ensemble models on food-11 dataset. The experimental results demonstrated that the accuracy of the ensemble model was the highest, reaching 96.88%, which was superior to any base learner. Therefore, the convolutional neural network model based on transfer learning and ensemble learning has strong learning ability and generalization ability, and it is feasible and practical to apply the method to food image recognition. [ABSTRACT FROM AUTHOR]

The rapid increase in the number of older people under the background of population aging has gradually changed the disease spectrum of society, making aging diseases more prevalent, and increasing the demand for health care services, medical and health services, and health insurance among older people, ultimately leading to increasing household and social spending on old age. This study is conducted to assess the impact of those spending burden on the sustainable development of economy and find out some practical and effective solutions. This paper constructs a theoretical model to illustrate the relationship between the old-age dependency ratio and the marginal product of capital (MPK), and then establishes a two-way fixed effect model based on transnational panel data of 81 countries from 1981 to 2017 to verify this relationship empirically. This paper finds that, after controlling a series of variables, an increased burden of old-age dependency leads to a decline in the MPK, a key macroeconomic variable and also a sustainable development criteria, but in which health care, health security systems, and technological innovation play a key and moderating role. The conclusion is also valid after tackling the problem of endogeneity with different methods, like two-stage least squares (TSLS) and the generalized methods of moments (GMM). Overall, before population aging, countries that are old-but-not-rich should encourage more supply-side investments in public health system or technological innovation, and adjust retirement system, or gradually encourage childbearing to strive for time and space for later sustainable development of public health system and economy. [ABSTRACT FROM AUTHOR]

Background: Adult Day care centres provide an important aspect of care provision through all phases of the dementia illness from diagnosis to the end of life (Dabelko HI 2008) supporting the well-being of both older people living with dementia and their care partners. Services within adult day care settings are designed to provide biopsychosocial health benefits to participants as well as care partner respite. Objective: To examine research studies, literature reviews and grey literature and identify and map the literature on psychosocial interventions used in day care services for older people living with dementia and chart their use, evaluation and outcomes. The research review question is "what are the psychosocial interventions used in day care service for older people living with dementia?" Psychosocial interventions are important non-pharmacological interventions which support people's wellbeing. Methods: Inclusion/Exclusion criteria were identified and guided the search strategy. Participants were people aged 60 years and over living with dementia attending day care services. The use of psychosocial interventions for this cohort was the focus of the review. Databases were searched (Cochrane Reviews, CINAHL, Embase, Medline EBSCO, Medline Ovid, Medline PubMed, PsycINFO, Scopus, Open Grey, Lenus and WHO Global Index Medicus databases) using keywords/terms with Boolean operators from 2011 to 2023. Rayyan was used to extract and manage the data. Results: The findings present a narrative and charting of the data from the 45 papers that met the review criteria, and this data is mapped onto the five objectives. Within this review, interventions were grouped into five broad types: nature (n = 6 papers), memory/cognitive (n = 11 papers), social (n = 17 papers), animal (n = 4 papers), or physical/sensory (n = 7 papers) based interventions. Conclusions: This review has illustrated the wide variety in the types, range and facilitation of psychosocial interventions within adult day care services. This review highlights the potential benefits of these interventions. However, findings must be considered in the context that many were provided as brief intervention studies with little evidence of continuation after the study and further research is required given the complex and diverse range of interventions. Results will be of interest to practitioners planning to implement or evaluate psychosocial interventions used in day care services for older people living with dementia. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic elicited a substantial hike in journal submissions and a global push to get medical evidence quickly through the review process. Editorial decisions and peer-assessments were made under intensified time constraints, which may have amplified social disparities in the outcomes of peer-reviewing, especially for COVID-19 related research. This study quantifies the differential impact of the pandemic on the duration of the peer-review process for women and men and for scientists at different strata of the institutional-prestige hierarchy. Using mixed-effects regression models with observations clustered at the journal level, we analysed newly available data on the submission and acceptance dates of 78,085 medical research articles published in 2019 and 2020. We found that institution-related disparities in the average time from manuscript submission to acceptance increased marginally in 2020, although half of the observed change was driven by speedy reviews of COVID-19 research. For COVID-19 papers, we found more substantial institution-related disparities in review times in favour of authors from highly-ranked institutions. Descriptive survival plots also indicated that scientists with prestigious affiliations benefitted more from fast-track peer reviewing than did colleagues from less reputed institutions. This difference was more pronounced for journals with a single-blind review procedure compared to journals with a double-blind review procedure. Gender-related changes in the duration of the peer-review process were small and inconsistent, although we observed a minor difference in the average review time of COVID-19 papers first authored by women and men. [ABSTRACT FROM AUTHOR]

In recent years, blockchain technology has developed rapidly and has been widely used in medical, financial, energy and other fields. However, in the process of practical application, each blockchain is a small independent ecosystem, with all transactions and operations limited to the chain, resulting in a large number of mutually heterogeneous to independent blockchains. It presents challenges for cross-chain interactions, cross-organization data sharing, and cross-blockchain expansion, and hinders the wider application of blockchain technology. In addition, the traditional digital signature method based on elliptic curve cipher faces the threat of being cracked by quantum computing attacks. To solve the aforementioned problems, this paper proposed a blockchain smart contract technique based on quantum computing attack resistance(BSCTQCAT). The technique first introduces the digital signature of the lattice cipher into the blockchain to resist the quantum search algorithm attack. Then, based on the smart contract authentication scheme, the nodes on multiple heterogeneous chains are organized into an identity agent layer P2P network, through which transactions on the chain will establish a credible identity management and message authentication mechanism between different chains, solving the current problem that each chain is difficult to communicate with each other. In this paper, the performance of the algorithm is evaluated by simulating the Bitcoin transaction scenario and analyzing the experimental data. [ABSTRACT FROM AUTHOR]

We report the first use of ERP measures to identify text engagement differences when reading digitally or in print. Depth of semantic encoding is key for reading comprehension, and we predicted that deeper reading of expository texts would facilitate stronger associations with subsequently-presented related words, resulting in enhanced N400 responses to unrelated probe words and a graded attenuation of the N400 to related and moderately related words. In contrast, shallow reading would produce weaker associations between probe words and text passages, resulting in enhanced N400 responses to both moderately related and unrelated words, and an attenuated response to related words. Behavioral research has shown deeper semantic encoding of text from paper than from a screen. Hence, we predicted that the N400 would index deeper reading of text passages that were presented in print, and shallower reading of texts presented digitally. Middle-school students (n = 59) read passages in digital and print formats and high-density EEG was recorded while participants completed single-word semantic judgment tasks after each passage. Following digital text presentation, the N400 response pattern to moderately-related words indicated shallow reading, tracking with responses to words that were unrelated to the text. Following print reading, the N400 responses to moderately-related words patterned instead with responses to related words, interpreted as an index of deeper reading. These findings provide evidence of differences in brain responses to texts presented in print and digital media, including deeper semantic encoding for print than digital texts. [ABSTRACT FROM AUTHOR]

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors. [ABSTRACT FROM AUTHOR]

Background: The physical, paper-based Georgia TB Reference Guide has served as the clinical reference handbook on tuberculosis (TB) diagnostic and treatment guidelines for the state of Georgia in the United States. Supported by the Georgia Department of Public Health, the production of the 112-page palm-sized booklet was previously led by a team of Georgia-based TB experts at Emory University and printed every three-five years with updates to clinical management guidelines and TB consult contact information. However, the costs associated with editorial printing combined with delays in updating a static printed booklet with revised guidance hampered the utility of the tool. Considering the barriers with paper-based production and based on the beneficial use of apps to support the dissemination of clinical management guidance in other settings, the booklet was converted into a mobile application. This paper describes the process of developing a mobile app version of the Georgia TB Reference Guide in an easy-to-update and readily available format. Methods: We employed a user-centered design approach to develop the app, including a series of qualitative interviews and quantitative surveys. Participants included a mix of state officials and local TB experts. First, initial foundational interviews were conducted to conceptualize current utilization practices of both the paper and PDF versions of the tool. Second, the findings from the initial interviews were organized thematically and informed the design of the app, which was then beta tested by a round of previously unsampled TB experts as well as a re-sample from the initial interviews. Third, the designs were coded into developmental phases and beta tested among users of the current Georgia TB Reference Guide. Fourth, the app was published and downloaded by a pre-selected group of local users who provided answers to a follow-up survey after using the app for one month. Fifth, user growth, self-reported demographics, and app usage between February and July 2022 were recorded through automatic data metrics built into the app. Results: The paper copy Georgia TB Reference Guide usage themes included commonly referenced content, navigation paths, and desired features and content. The themes were converted into features and designs such as prioritizing commonly reviewed topics and guide customization with bookmarks and notes. Iterations of the designs were driven by feedback from TB experts and included home page featured content, improving content readability, and improving the search feature. The follow-up survey revealed a 90% preference for the app over the paper version of the guide. In the six months following the app's release, the app was downloaded by 281 individuals in the United States. The majority of downloads were in Georgia and the app also expanded organically to 19 other states. Conclusion: The experience of converting the Georgia TB Reference Guide offers specific and effective steps to converting a medical reference guide into a mobile application tool that is readily available, easy to use, and easy to update. The organic dissemination of the app beyond the state of Georgia's borders within the first six months of app launch underscores desire among TB healthcare professionals for high-quality digital reference content outside the state. This experience offers clear outlines for replication in other contexts and demonstrates the utility of similar mobile medical reference tools. [ABSTRACT FROM AUTHOR]

The "Three Rural Issues", encompass challenges related to agriculture, farmer, and rural area, which hold significant importance in driving comprehensive rural revitalization efforts in China. Farmer entrepreneurship, as a crucial means to enhance productivity, create job opportunities, and increase residents' income, has gradually become a key driving force in promoting rural revitalization in the new stage of development in China. With the rapid development of rural e-commerce, farmer entrepreneurship has encountered new opportunities. This study utilizes the 2020 China Family Panel Studies (CFPS) data and employs a structural equation model (SEM) to analyze the direct impact of rural e-commerce participation on farmer entrepreneurial behavior, considering factors such as human capital, social capital, and network infrastructure. This study further explores the indirect effects and mechanisms of e-commerce participation as a mediating variable and analyzes the impact and mechanisms on agricultural entrepreneurship behavior. The findings are as follows: (1) E-commerce participation significantly promotes farmer entrepreneurial behavior; (2) E-commerce participation as a mediating variable has a positive indirect effect on the relationship between social trust, network infrastructure, human capital, and farmer entrepreneurial behavior; (3) E-commerce participation has a significant positive influence on farmer entrepreneurship in the agricultural sector, and farmers with higher levels of network infrastructure and human capital have a higher probability of choosing agricultural entrepreneurship under the influence of e-commerce participation. Finally, this study provides policy recommendations in terms of infrastructure construction, entrepreneurial policy environment, and education level, aiming to optimize the situation of farmer entrepreneurship and contribute to the comprehensive promotion of rural revitalization.Overall, the research in this paper effectively combines theory and empirical evidence to outline the direct and indirect impact mechanisms of rural e-commerce participation on farmers' entrepreneurial behavior and agriculture-related entrepreneurial behavior and to test the effects of their impacts. First, most of the existing literature deals with farmers in individual sample areas, while the sample selected in this paper is farmers in the whole country, which is relatively more generalizable; second, most of the previous studies explore the level of e-commerce in the inter-provincial or county areas, while this paper expands the empirical study of rural e-commerce on the entrepreneurial behavior of farmers and the micro-period of agricultural entrepreneurial behavior, and focuses on the impacts of the e-commerce activities of farmers on their entrepreneurial behavior. [ABSTRACT FROM AUTHOR]

This paper uses the difference-in-differences model to research how the "piercing the corporate veil" system marked by the 2005 Company Law amendment affects the level of corporate creditor protection. The research results show that private enterprises and local state-owned enterprises are sensitive and significant to this legal amendment. In contrast, local state-owned enterprises are more sensitive and have a stronger motivation to protect the interests of creditors. The motivation of companies with weaker profitability for creditor protection lasts not only for the year of law revision but also extends to the year of implementation. With the law's implementation, the growth effect of creditor protection for local state-owned enterprises has become more significant. Further analysis shows that the main findings of this article are more significant in companies with larger debt scales, companies with a higher year-on-year growth rate of operating income, companies with controlling shareholders, and companies with higher stock market capitalization. From an empirical research view, this paper explains the economic effect and mechanism of the whole corporate personality under the complete system and adds economic evidence for how the law acts on the capital market. [ABSTRACT FROM AUTHOR]

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

Introduction: While the putative benefits of "fitness trackers" continue to fuel a booming consumer market, results of device-based clinical interventions remain remarkably mixed. This study will explore factors influencing wearable physical activity (PA) sensor use in the context of stroke prevention and rehabilitation for older adults. The findings of this thematic synthesis will provide insights into factors influencing the use of PA sensors in stroke which may inform more effective device-based interventions. Methods and analysis: Thematic synthesis as a formal method described by Thomas and Arden can be used within a systematic review to synthesize primary qualitative research. Accordingly, the proposed study will systematically search bibliographic databases for relevant peer-reviewed papers and synthesize coded thematic data within included papers. The quality of papers will be assessed using the JBI Critical Appraisal Checklist for Qualitative Research. Patterns in the text will be coded, preliminary data visualised, and higher-level analytical themes discerned to explain factors influencing the use of PA sensors in older stroke patients. Discussion: This study does not require ethics approval. Results are expected to be available by June 2024. Data from the thematic synthesis will provide insights into barriers and facilitators influencing the use of wearable PA sensors in stroke and older adults at risk, and implications these factors have for the design of effective device-based interventions. Trial registration: Systematic review registration: PROSPERO registration number: CRD42020211472. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211472. [ABSTRACT FROM AUTHOR]

Background: Self-harm and suicide behaviours are a major public health concern. Several factors are associated with these behaviours among military communities. Identifying these factors may have important implications for policy and clinical services. The aim of this review was to identify the risk and protective factors associated with self-harm and suicide behaviours among serving and ex-serving personnel of the United Kingdom Armed Forces, Canadian Armed Forces, Australian Defence Force and New Zealand Defence Force. Methods: A systematic search of seven online databases (PubMed, Web of Science, Embase, Global Health, PsycINFO, PTSDpubs and CINAHL) was conducted alongside cross-referencing, in October 2022. Following an a priori PROSPERO approved protocol (CRD42022348867), papers were independently screened and assessed for quality. Data were synthesised using a narrative approach. Results: Overall, 28 papers were included: 13 from Canada, 10 from the United Kingdom, five from Australia and none from New Zealand. Identified risk factors included being single/ex-relationship, early service leavers, shorter length of service (but not necessarily early service leavers), junior ranks, exposure to deployment-related traumatic events, physical and mental health diagnoses, and experience of childhood adversity. Protective factors included being married/in a relationship, higher educational attainment, employment, senior ranks, and higher levels of perceived social support. Conclusion: Adequate care and support are a necessity for the military community. Prevention and intervention strategies for self-harm and suicide behaviours may be introduced early and may promote social networks as a key source of support. This review found a paucity of peer-reviewed research within some populations. More peer-reviewed research is needed, particularly among these populations where current work is limited, and regarding modifiable risk and protective factors. [ABSTRACT FROM AUTHOR]

Purpose: Savouring interventions aim to amplify the intensity and duration of positive feelings and positive affect. Research has shown that the potential benefits of savouring include the promotion of psychological well-being and diminution of negative affective states. Savouring strategies may be particularly useful amongst clinical populations in changing biobehavioural processes which can strengthen an individual's propensity to exert control over how to develop, intensify and promote psychological well-being, while simultaneously mitigating negative affective states. This paper outlines a protocol for a systematic review that will be used to identify, critically appraise and synthesise findings of studies examining the effectiveness of savouring interventions in adult clinical populations. Savouring interventions will be defined broadly, operationalised as any savouring strategy focusing on past, present or future events or experiences whereby participants are instructed to attend to and amplify positive affect relating to same. The goal of our review is to include the extent of the literature on this topic and contribute to the overall evidence to support savouring interventions. Methods: This protocol is carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Protocols Guidelines. The protocol has been registered with PROSPERO (CRD42023404857). The databases PsycINFO, PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Scopus will be searched alongside a search of grey literature. An examination of the first 200 papers on Google Scholar will also be done to identify relevant papers. Studies describing randomised controlled trials evaluating the effects of savouring interventions as described within this article on adult clinical populations will be included in the review. Outcomes will include well-being, quality of life, depression, anxiety or stress. Study selection and data extraction will be completed by three independent reviewers to reduce risk of bias. Interrater percentage agreement and interrater reliability will be reported on same. The quality of studies will be assessed using criteria based on the Cochrane Collaboration's tool for assessing risk of bias and the Jadad scale. A narrative synthesis with tables of study characteristics will be provided. Separate considerations of the three time perspectives of savouring interventions (past-focused, present-focused, and future-focused) will also be described. Conclusions: This systematic review will provide important clinical insights into the potential efficacy of savouring interventions when working with adult clinical samples. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, concerns were raised that face covering use may elicit risk compensation; a false sense of security resulting in reduced adherence to other protective behaviours such as physical distancing. This systematic review aimed to investigate the effect of face covering use on adherence to other COVID-19 related protective behaviours. Medline, Embase, PsychInfo, EmCare, medRxiv preprints, Research Square and WHO COVID-19 Research Database were searched for all primary research studies published from 1st January 2020 to 17th May 2022 that investigated the effect of face covering use on adherence to other protective behaviours in public settings during the COVID-19 pandemic. Papers were selected and screened in accordance with the PRISMA framework. Backwards and forwards citation searches of included papers were also conducted on 16th September 2022, with eligible papers published between 1st January 2020 and that date being included. A quality appraisal including risk of bias was assessed using the Academy of Nutrition and Dietetics' Quality Criteria Checklist. This review is registered on PROSPERO, number CRD42022331961. 47 papers were included, with quality ranging from low to high. These papers investigated the effects of face covering use and face covering policies on adherence to six categories of behaviour: physical distancing; mobility; face-touching; hand hygiene; close contacts; and generalised protective behaviour. Results reveal no consistent evidence for or against risk compensation, with findings varying according to behaviour and across study types, and therefore confident conclusions cannot be made. Any policy decisions related to face coverings must consider the inconsistencies and caveats in this evidence base. [ABSTRACT FROM AUTHOR]

Space medicine is a vital discipline with often time-intensive and costly projects and constrained opportunities for studying various elements such as space missions, astronauts, and simulated environments. Moreover, private interests gain increasing influence in this discipline. In scientific disciplines with these features, transparent and rigorous methods are essential. Here, we undertook an evaluation of transparency indicators in publications within the field of space medicine. A meta-epidemiological assessment of PubMed Central Open Access (PMC OA) eligible articles within the field of space medicine was performed for prevalence of code sharing, data sharing, pre-registration, conflicts of interest, and funding. Text mining was performed with the rtransparent text mining algorithms with manual validation of 200 random articles to obtain corrected estimates. Across 1215 included articles, 39 (3%) shared code, 258 (21%) shared data, 10 (1%) were registered, 110 (90%) contained a conflict-of-interest statement, and 1141 (93%) included a funding statement. After manual validation, the corrected estimates for code sharing, data sharing, and registration were 5%, 27%, and 1%, respectively. Data sharing was 32% when limited to original articles and highest in space/parabolic flights (46%). Overall, across space medicine we observed modest rates of data sharing, rare sharing of code and almost non-existent protocol registration. Enhancing transparency in space medicine research is imperative for safeguarding its scientific rigor and reproducibility. [ABSTRACT FROM AUTHOR]

The text describes improvements made to the random forest model to enhance its distinctiveness in addressing tax risks within the real estate industry, thereby tackling issues related to tax losses. Firstly, the paper introduces the potential application of the random forest model in identifying tax risks. Subsequently, the experimental analysis focuses on the selection of indicators for tax risk. Finally, the paper develops and utilizes actual taxpayer data to test a risk identification model, confirming its effectiveness. The experimental results indicate that the model's output report includes basic taxpayer information, a summary of tax compliance risks, value-added tax refund situations, directions of suspicious items, and detailed information on common indicators. This paper comprehensively presents detailed taxpayer data, providing an intuitive understanding of tax-related risks. Additionally, the paper reveals the level of enterprise risk registration assessment, risk probability, risk value, and risk assessment ranking. Further analysis shows that enterprise risk points primarily exist in operating income, selling expenses, financial expenses, and total profit. Additionally, the results indicate significant differences between the model's judgment values and declared values, especially in the high-risk probability of total operating income and profit. This implies a significant underreporting issue concerning corporate income tax for real estate enterprises. Therefore, this paper contributes to enhancing the identification of tax risks for real estate enterprises. Using the optimized random forest model makes it possible to accurately assess enterprises' tax compliance risks and identify specific risk points. [ABSTRACT FROM AUTHOR]

To overcome the problem of the high initial position of the point cloud required by the traditional Iterative Closest Point (ICP) algorithm, in this paper, we propose a point cloud registration method based on normal vector and directional histogram features (SHOT). Firstly, a hybrid filtering method based on the voxel idea is proposed and verified using the measured point cloud data, and the noise removal rates of 97.5%, 97.8%, and 93.8% are obtained. Secondly, in terms of feature point extraction, the original algorithm is optimized, and the optimized algorithm can better extract the missing part of the point cloud. Finally, a fine alignment method based on normal vector and directional histogram features (SHOT) is proposed, and the improved algorithm is compared with the existing algorithm. Taking the Stanford University point cloud data and the self-measured point cloud data as examples, the plotted iteration-error plots can be concluded that the improved method can reduce the number of iterations by 40.23% and 37.62%, respectively. [ABSTRACT FROM AUTHOR]

Since the concept of toughness was introduced to transportation systems, transportation system toughness has received extensive attention from researchers in the field of transportation worldwide. In this paper, a methodology for quantifying and assessing the toughness of urban transportation systems is proposed in the context of the New Crown epidemic. Firstly, the definition of urban transportation system toughness in this context is clarified, and the entropy evaluation method is applied to construct the performance curve of urban transportation systems over time. Then, it is proposed to quantify the system's resistance, recovery, and adaptive ability in terms of the change in the cumulative amount of system performance. Finally, the three characteristic abilities of system toughness are organically combined to obtain a comprehensive assessment of system toughness. Example calculations and analyses are carried out in four Chinese cities with different levels of development, and the results show that the performance of urban transportation systems is positively correlated with their levels of development, and all of them fluctuate greatly under the influence of the epidemic, but Wuhan has the strongest resistance and recovery ability of the transportation system, and shows the highest toughness, followed by Lanzhou, Changchun, and Shanghai. The system toughness quantification and assessment methods proposed in this paper provide a reference for research on improving the ability of urban transportation systems to deal with multiple uncertainty disturbances. [ABSTRACT FROM AUTHOR]

This study is a comprehensive assessment of the waste management system in Besisahar municipality. Information and some data have been collected from the municipality of Besisahar, followed by interviews with municipal officials responsible for waste management, stakeholders, waste workers, and residents. A total of 230 households, 20 schools, 10 government and private offices, 10 financial institutions, 60 commercial hotels, restaurants, and shops, and 20 medical shops and healthcare institutions, were selected in this study by random sampling. An extensive field study was conducted within all municipal wards and at dump sites. The results indicated that 42.14% of solid waste was collected through door-to-door collection services, 5.87% was mismanaged in open public places, 11.21% was used as compost manure, and the rest was discarded on riverbanks, dug up, and burned. A large component of the characterization of household waste consisted of organic waste (68.03%), followed by paper/paper products (8.13%), agricultural waste (5.5%), plastic (5.21%), construction (3.81%), textile (2.72%), metals (0.54%), glass (1.01%), rubber (0.10%), electronic (0.05%), pharmaceutical (0.1%) and others (4.78%) in the Besishahar municipality. Solid waste generation was found to be at 197.604 g/capita/day, as revealed by cluster sampling in 230 households. Around 4.285 tons-solid waste/day were generated in urban areas, while 16.13 tons-solid waste/day was estimated for the whole municipality. An important correlation between the parameters of solid waste was found by statistical analysis. Currently, solid waste is dumped on riverbanks, open fields, and springs, creating environmental and health hazards. The findings of this study will be useful to Besisahar municipality and its stakeholders in forming policies that facilitate waste management practices in this region and promote sustainable waste management systems. [ABSTRACT FROM AUTHOR]

Marine fishery carbon emissions play a significant role in agricultural carbon emissions, making resource allocation a crucial topic for the overall marine ecological protection. This paper evaluates the dynamic iteration method as a research approach with the factors of resource allocation consisting of value assessment, optimization objective, difference between value assessment and objective, and optimization calculation. The paper selects the shadow price from the Super-SBM model as the judgment function for the goal value, aiming for the fairness criterion. From an equity standpoint, the allocation of carbon resources in marine capture fisheries proves to be unreasonable. The fishery model exhibits an excessive supply of carbon resources, resulting in wastage, while the green fishery model faces a relatively limited supply, with a focus on energy conservation and environmental protection. To address this issue, this paper proposes a new method and discusses the corrective results. This result shows that the stabilization point achieved is a short-term equilibrium rather than a long-term one. By rectifying the social contradiction of profit-oriented approaches, this research provides a fresh perspective for economic studies and applications, particularly in industrial layout and resource utilization optimization. [ABSTRACT FROM AUTHOR]

The regional networking strategy is widely implemented in China as a normative policy aimed at fostering cohesion and enhancing competitiveness. However, the empirical basis for this strategy remains relatively weak due to limitations in measurement methods and data availability. This paper establishes the urban networks by the enterprise investment data, and then accurately measures the network's external effects of each city by the method of MGWR model. The results show that: (1) Regional networking plays a significant role in urban development, although it is not the dominant factor. (2) The benefits of network connections may vary depending on the location and level of cities. (3) The major cities assume a pivotal role in the urban network. Based upon the aforementioned research conclusions, this paper presents strategic measures to enhance the network's external impacts, aiming to offer insights for other regions in formulating regional development strategies and establishing regional urban networks. [ABSTRACT FROM AUTHOR]

Simultaneously achieving economic development and environmental protection is a shared global challenge. While the positive effect of environmental regulations on protecting the environment has been widely recognized, the attention paid to low-carbon governance and corporate green transformation remains insufficient. Based on the two-stage least square regression model (2SLS) of instrumental variables, this paper utilizes panel data from China to identify the influence mechanism of government low-carbon governance on enterprise green development. It explores the effect of low-carbon governance on enterprise green development from the perspective of fiscal decentralization. The findings show that (1) Low-carbon governance significantly promotes corporate green development, primarily through improving industrial structure and technological innovation; (2) Low-carbon governance notably promotes the green development of private enterprises but has little effect on state-owned enterprises. There are also geographical differences, and the results are better in Eastern China than in the Central and Western parts of China; (3) Fiscal decentralization at both central and local levels inhibits the effect of low-carbon governance on driving corporate green development by causing a mismatch of human resources. Therefore, to promote corporate green development, low-carbon governance must prioritize green development, actively guide industrial structural upgrading and enterprise technological innovation, implement differentiated low-carbon governance measures tailored to different ownership enterprises, and optimize the assessment indicators for fiscal decentralization. This paper helps deepen the understanding of the relationship between government low-carbon governance and enterprise green development in developing countries. It can be used as a reference for government departments to formulate relevant policies. [ABSTRACT FROM AUTHOR]

Citations play an important role in researchers' careers as a key factor in evaluation of scientific impact. Many anecdotes advice authors to exploit this fact and cite prospective reviewers to try obtaining a more positive evaluation for their submission. In this work, we investigate if such a citation bias actually exists: Does the citation of a reviewer's own work in a submission cause them to be positively biased towards the submission? In conjunction with the review process of two flagship conferences in machine learning and algorithmic economics, we execute an observational study to test for citation bias in peer review. In our analysis, we carefully account for various confounding factors such as paper quality and reviewer expertise, and apply different modeling techniques to alleviate concerns regarding the model mismatch. Overall, our analysis involves 1,314 papers and 1,717 reviewers and detects citation bias in both venues we consider. In terms of the effect size, by citing a reviewer's work, a submission has a non-trivial chance of getting a higher score from the reviewer: an expected increase in the score is approximately 0.23 on a 5-point Likert item. For reference, a one-point increase of a score by a single reviewer improves the position of a submission by 11% on average. [ABSTRACT FROM AUTHOR]

Background: The World Health Organisation and palliative care stakeholders recommend that healthcare workers are educated in palliative care. Provision of high-quality palliative care is fundamental to nursing practice. However, caring for palliative care patients and meeting family needs is challenging without appropriate knowledge and experience. Palliative care education and clinical skill development for undergraduate student nurses is a priority to ensure graduate nurses are equipped with the knowledge and skill to deliver safe and competent care. Methods: A scoping review guided by Arksey and O'Malley's framework was used to identify undergraduate student nurses' palliative care education and preparation. A comprehensive literature search of five electronic databases and grey literature were conducted from January 2002 to December 2021. The aim was to review the empirical evidence and ascertain how undergraduate student nurses' palliative care education is organised, facilitated, delivered and evaluated. Screening was performed independently by two reviewers against eligibility criteria with meetings to discuss included papers and form a consensus. Data was extracted and related to palliative care undergraduate student nurses' education, educational model, methodology, key findings, and recommendations. Analysed and summarised data was mapped onto the four key review questions (educational models utilised, methods used to assess effectiveness, facilitators/barriers and gaps in the literature). Results: 34 papers met the criteria for this review. The review highlights that undergraduate nursing palliative care education is more evident in high income countries. Limited and diverse published research existing in low- and middle-income countries. Educational models utilised were theoretical and experiential learning and educational process, early integration and multiple learning methods which were highlighted as facilitating factors. However, crowded curricula, lack of palliative care clinical placement expertise, difficulty providing clinical placement, timing and delivery of palliative care and difficulty responding to simulated environments (manikins) were perceived barriers. Nevertheless, palliative care education can increase knowledge, positive attitude, self-confidence and adequate preparation of undergraduate student nurses. Conclusion: This review highlights that there is limited research regarding the timing and delivery of palliative care principles and practice in undergraduate student nurse education. Early integration of palliative care education impacts upon students perceived preparedness for practice and positively influences their attitudes to palliative care provision. [ABSTRACT FROM AUTHOR]

Scientific literature, as the major medium that carries knowledge between scientists, exhibits explosive growth in the last century. Despite the frequent use of many tangible measures, to quantify the influence of literature from different perspectives, it remains unclear how knowledge is embodied and measured among tremendous scientific productivity, as knowledge underlying scientific literature is abstract and difficult to concretize. In this regard, there has laid a vacancy in the theoretical embodiment of knowledge for their evaluation and excavation. Here, for the first time, we quantify the knowledge from the perspective of information structurization and define a new measure of knowledge quantification index (KQI) that leverages the extent of disorder difference caused by hierarchical structure in the citation network to represent knowledge production in the literature. Built upon 214 million articles, published from 1800 to 2021, KQI is demonstrated for mining influential classics and laureates that are omitted by traditional metrics, thanks to in-depth utilization of structure. Due to the additivity of entropy and the interconnectivity of the network, KQI assembles numerous scientific impact metrics into one and gains interpretability and resistance to manipulation. In addition, KQI explores a new perspective regarding knowledge measurement through entropy and structure, utilizing structure rather than semantics to avoid ambiguity and attain applicability. [ABSTRACT FROM AUTHOR]

Background: Difficulties in parent-child interaction are easily observed and are a potential target for early intervention. This review aimed to assess the utility of current observational methods used to assess parent-child interactions–within the first year of life–and their ability to screen and identify children from low-risk samples most at risk of developing childhood psychopathology. Methods: Six bibliographic databases were searched, and reference lists screened. All peer reviewed papers studying the association between an independent observation of parent-child interaction and later childhood psychopathology in community-based samples were included. Included studies were those recruiting from population or community-based birth cohort data, which we define as 'low-risk'. Studies based on populations known to have a diagnosis of psychiatric illness or developmental disorder, or at high genetic or environmental risk of being diagnosed with such disorder, were excluded. Results were synthesised qualitatively due to high heterogeneity. Results: 20,051 papers were identified, nine were included in this study. Childhood psychopathology was associated with fewer positive parent-infant interactions, lower parent vocalisation frequency and lower levels of adult speech and activity. Maternal sensitivity was inversely related to separation anxiety and oppositional defiant/conduct disorders were associated with lower shared look rates. Disruptive behaviour disorders were associated with higher frequency of child vocalisation. Conclusion: Assessment of parent-child interactions, particularly the level of maternal activity, may be an early indicator of later childhood psychopathology in low-risk samples. Further longitudinal, population-based studies are required. Trial registration: PROSPERO review registration: CRD42020162917https://www.google.com/search?client=firefox-b-d&q=CRD42020162917. [ABSTRACT FROM AUTHOR]

Background: Survivors of sexual violence deserve timely and high-quality forensic examination, evidence collection, and documentation as part of comprehensive care. However, in many countries, the quality of medical-legal documentation is severely limited. MediCapt is an innovative digital application that enables clinicians to document forensic medical evidence as well as capture and securely store forensic photographs of injuries. This study evaluated the effectiveness and usability of MediCapt to document forensic medical evidence of sexual violence. Methods: This mixed-methods evaluation involved key-informant interviews, usability questionnaires, and forensic record reviews. Participants included clinicians, medical records personnel, information technology personnel, and health facility administrators, as well as law enforcement and legal professionals in Kenya. Results: The Physicians for Human Rights (PHR) data quality checklist found that using MediCapt led to significantly higher data-quality scores compared to paper-based forms. MediCapt forms scored higher on 23 of 26 checklist items. While a wide difference in quality was seen among paper-based forms, MediCapt appeared to both standardize and improve quality of documentation across sites. MediCapt strengths included data security and confidentiality, accuracy and efficiency, and supplemental documentation with photography. Weaknesses included infrastructure challenges, required technological proficiencies, and time to learn the new system. Although it is early to assess the impact of MediCapt on prosecutions, providers and law and justice sector professionals were optimistic about its usefulness. They identified MediCapt as appropriate for use with survivors of sexual violence and reported MediCapt's legibility and photography features had already been commended by the court. Conclusion: MediCapt was well-received across all sectors, its use was perceived as feasible and sustainable, and it significantly improved the quality of collected forensic data. It is anticipated this improvement in forensic documentation will increase successful prosecutions, strengthen accountability for perpetrators, and improve justice for survivors. [ABSTRACT FROM AUTHOR]

Twitter has become an important promotional tool for scholarly work, but individual academic publications have varied degrees of visibility on the platform. We explain this variation through the concept of Twitter-worthiness: factors making certain academic publications more likely to be visible on Twitter. Using publications from communication studies as our analytical case, we conduct statistical analyses of 32187 articles spanning 82 journals. Findings show that publications from G12 countries, covering social media topics and published open access tend to be mentioned more on Twitter. Similar to prior studies, this study demonstrates that Twitter mentions are associated with peer citations. Nevertheless, Twitter also has the potential to reinforce pre-existing disparities between communication research communities, especially between researchers from developed and less-developed regions. Open access, however, does not reinforce such disparities. [ABSTRACT FROM AUTHOR]

Since various dance teaching systems have attracted much attention with the development of Artificial Intelligence (AI) technology, this paper improves the recognition performance of Latin dance teaching systems by optimizing the action recognition model. Firstly, the object detection and action recognition technology under the current AI technology is analyzed, and the Two-stage object detection algorithm and One-stage object detection algorithm are evaluated. Secondly, the technologies and functions contained in the adolescent health Latin dance teaching system are described, including image acquisition, feature extraction, object detection, and action recognition. Finally, the action recognition algorithm is optimized based on object detection, and the rationality and feasibility of the proposed algorithm are verified by experiments. The experimental results show that the optimization algorithm can search the optimal feature subset after five iterations on Undefine Classes of 101 (UCF101) dataset, but it needs seven iterations on Human Motion Database 51 (HMDB51) dataset. Meanwhile, when using support vector machine classifier, the optimization algorithm can achieve the highest accuracy of motion recognition. Regressive Function, Multinomial Naive Bayes and Gaussian Naive Bayes Algorithms have lower prediction delay, as low as 0.01s. Therefore, this paper has certain reference significance for the design and implementation of adolescent health Latin dance teaching system. [ABSTRACT FROM AUTHOR]

A deep understanding of the relationship between the knowledge acquired and the graduation requirements is essential for students to precisely meet the graduation requirements and to become human resources with specific knowledge, skills and professionalism. In this paper, we define the ontology layer of the knowledge graph by deeply analyzing the relationship between graduation requirement, course and knowledge. Based on the implementation of the concept of Outcome Based Education, we use Knowledge extraction, fusion, reasoning techniques to construct a hierarchical knowledge graph with the main line of "knowledge-course-graduation requirements. In the process of knowledge extraction, in order to alleviate the huge labor overhead brought by traditional extraction methods, this paper adopts a transfer learning method to extract triadic knowledge using the multi-task framework EERJE, Finally, knowledge reasoning was also performed with the help of LLM to further expand the knowledge scope. The comprehensiveness, correctness and relatedness of the data were evaluated through the experiment, and the F1 value of the ternary group extraction was 87.76%, the accuracy rate of entity classification was 85.42%, the data coverage was more comprehensive, and the results showed that the data quality was better, and the knowledge graph constructed in this way can fully optimize the organization and management of teaching resources, help students intuitively and comprehensively grasp the correlation and difference between graduation requirements and various knowledge points, and let the Students can carry out personalized independent learning through the navigation mode of knowledge graph, strengthen their weak links, and complete the relevant graduation requirements, which effectively improves the degree of students' graduation requirements achievement. This new paradigm of knowledge graph enabled teaching is of reference significance for engineering education majors to improve the degree of graduation requirements achievement. [ABSTRACT FROM AUTHOR]

This paper focuses on the cooperative driving challenges of connected and automated vehicles (CAVs) at single-lane roundabouts. First, a geometric path planning method is proposed for CAVs navigating a single-lane roundabout. Based on this method, a vehicle roundabout model is established. Four potential traffic scenarios for CAVs are established, and the optimal arrival times at conflict points are analyzed. By correlating the optimal arrival times at conflict points with the optimal entry times into the roundabout, the multi-vehicle coordination problem in complex intersections is simplified to a speed control issue during entry. Utilizing the principles of optimal control and Pontryagin minimization, two speed optimization strategies are proposed. Finally, MATLAB is employed for simulation analysis. The results indicate that the control strategy proposed in this paper enables the system to clearly identify potential conflicts between vehicles and implement an optimal control strategy, ensuring that vehicles can navigate the roundabout efficiently in terms of time and fuel without collisions. Additionally, the minimum time interval is established at 0.2 seconds to completely prevent vehicle collisions. In this study, the fusion problem involving two vehicles at a single conflict point is further expanded to encompass multiple vehicles at multiple conflict points. Thus, the efficient scheduling of multiple vehicles in single-lane roundabouts is realized. [ABSTRACT FROM AUTHOR]

Introduction: Currently, literature on spiritual health remains limited. Even more so, literature on spiritual health remains limited in Canada. This is exacerbated by the fact that spiritual health is a term that remains widely contested with no concrete definition. Meanwhile, the semantic connection between "religion" and "spirituality" remains ambiguous in the West and scholars hold different positions. In this paper, we outline our scoping review protocol to describe the current landscape of spiritual health and spirituality (in relation to health) research in Canada, including the meaning and understanding behind these two concepts. Methods and analysis: This protocol for our scoping review is documented in accordance with the PRISMA-P reporting guidelines and adheres to Arksey and O'Malley's scoping review methodology. We will conduct a search strategy across select electronic databases and review the reference lists of chosen papers. Two reviewers, HMB and MM, will independently and blindly screen all title/abstracts and full-text studies for eligibility. Any Canadian-situated studies that centrally mention and focus on "spirituality" or "spiritual health" will be included. Relevant variables will be extracted through an iterative process, with the data charting being continuously reviewed and refined. Findings from this scoping review will support the future of health research and conceptual expansion of health beyond the mental, physical and social. Approval from a research ethics board is not required, nor has it been obtained, as the data is derived from journal articles and academic publications. [ABSTRACT FROM AUTHOR]

In order to solve the problem of image quality and morphological characteristics of primary underglaze brown decorative pattern extraction, this paper proposes a method of primary underglaze brown decorative pattern extraction based on the coupling of single scale gamma correction and gray sharpening. The single-scale gamma correction is combined with the gray sharpening method. The single-scale gamma correction improves the contrast and brightness of the image by nonlinear transformation, but may lead to the loss of image detail. Gray sharpening can enhance the high frequency component and improve the clarity of the image, but it will introduce noise. Combining these two technologies can compensate for their shortcomings. The experimental results show that this method can improve the efficiency of last element underglaze brown decorative pattern extraction by enhancing the image retention detail and reducing the influence of noise. The experimental results showed that F1Score, Miou(%), Recall, Precision and Accuracy(%) were 0.92745, 0.82253, 0.97942, 0.92458 and 0.92745, respectively. [ABSTRACT FROM AUTHOR]

Background: Gender discrimination of women is often emphasized in work contexts, whereas less focus is on how men are discriminated against in social relationships. Gender discrimination in decisions of family relations, is essential to study as the contact between parent and child is commonly viewed as the most important relationship in people's life, as well as being the most important aspect of our life. Following separations, decisions on custody disputes are made by social workers. The purpose of this paper is to study gender discrimination in such decisions. Method: Participants were instructed to give a recommendation of shared parenting based on a custody case vinjett, where we manipulate the gender of the risk parent. Results: The participants' recommendation of living was mainly dependent on the risk parent's gender, where the mother was considerably more likely to receive shared custody than the father. Conclusions: Professional social workers show selective gender discrimination against fathers in terms of living recommendations. [ABSTRACT FROM AUTHOR]

The standard way to study Large Language Models (LLMs) through benchmarks or psychology questionnaires is to provide many different queries from similar minimal contexts (e.g. multiple choice questions). However, due to LLM's highly context-dependent nature, conclusions from such minimal-context evaluations may be little informative about the model's behavior in deployment (where it will be exposed to many new contexts). We argue that context-dependence should be studied as another dimension of LLM comparison alongside others such as cognitive abilities, knowledge, or model size. In this paper, we present a case-study about the stability of value expression over different contexts (simulated conversations on different topics), and as measured using a standard psychology questionnaire (PVQ) and behavioral downstream tasks. We consider 21 LLMs from six families. Reusing methods from psychology, we study Rank-order stability on the population (interpersonal) level, and Ipsative stability on the individual (intrapersonal) level. We explore two settings: with and without instructing LLMs to simulate particular personalities. We observe similar trends in the stability of models and model families—Mixtral, Mistral, GPT-3.5 and Qwen families being more stable than LLaMa-2 and Phi—over those two settings, two different simulated populations, and even on three downstream behavioral tasks. When instructed to simulate particular personas, LLMs exhibit low Rank-Order stability, and this stability further diminishes with conversation length. This highlights the need for future research directions on LLMs that can coherently simulate a diversity of personas, as well as how context-dependence can be studied in more thorough and efficient ways. This paper provides a foundational step in that direction, and, to our knowledge, it is the first study of value stability in LLMs. The project website with code is available at https://sites.google.com/view/llmvaluestability. [ABSTRACT FROM AUTHOR]

Logistics resilience is a significant representation of sustainable development ability and a necessary support for high-quality economic development. In order to explore the influencing factors and realization mechanism of the improvement of logistics resilience of the Yangtze River Economic Belt and the high-quality and sustainable development of the economy, this paper comprehensively considers factors of the supply and demand relationship of the logistics market, industrial structure and ecological environment, and evaluates the urban logistics resilience of the Yangtze River Economic Belt by using POI data and statistical data. Combined with the spatial Durbin model, the influencing factors and spatial spillover effects of inter-city logistics resilience were revealed. This study found that the urban logistics resilience in the lower reaches of the Yangtze River has been high. Except Chongqing and Shanghai, the COVID-19 epidemic happened in 2020 led to a significant decrease in logistics resilience. In the meanwhile, every 1% increase in the logistics resilience of the city will promote the logistics resilience of the adjacent cities by 0.145%. Economic condition and urban development potential have positive effects on logistics resilience of the city and its adjacent cities. The economic condition has a direct effect coefficient of 0.166 and an indirect effect coefficient of 0.181, The direct and indirect effects of urban development potential are significantly positive, and the coefficients are 0.001 and 0.006, respectively. The level of information, government support and ability of technological innovation are helpful for the improvement of urban logistics resilience while hindering the enhancement of logistics resilience in adjacent cities. The research area can be extended in the future and more influencing factors can be considered in the future. [ABSTRACT FROM AUTHOR]

Background: Globally, reduction of patient waiting time has been identified as one of the major characteristics of a functional health system. In South Africa, 83% of the general population visiting primary healthcare (PHC) facilities must contend with long waiting times, overcrowding, staff shortages, poor quality of care, an ineffective appointment booking system, and a lack of medication. These experiences may, in turn, affect how patients view service quality. Methods: This scoping review was guided by Arksey and O'Malley methodological framework. The primary literature search of peer-reviewed and review articles was achieved through PubMed/MEDLINE, Google Scholar, Science Direct, and World Health Organization (WHO) library databases, using waiting times, outpatient departments, factors, interventions, and primary healthcare facilities as keywords. Two independent reviewers screened abstracts and full articles, using the set inclusion and exclusion criteria. We used NVIVO® version 10 software to facilitate thematic analysis of the results from included studies. Results: From the initial 250 records screened, nine studies were eligible for inclusion in this scoping review. Seven papers identified the factors contributing to waiting time, and five papers mentioned effective interventions implemented to reduce waiting times within PHC facilities. Our analysis produced three (patient factors, staff factors, and administrative systems) and two (manual-based waiting time reduction systems and electronic-based waiting time reduction systems) main themes pertaining to factors contributing to long waiting times and interventions to reduce waiting times, respectively. Conclusion: Our results revealed that the patients, staff, and administrative systems all contribute to long waiting times within the PHC facilities. Patient waiting times recorded a wider and more evenly spread patient arrival pattern after the identified interventions in our study were implemented. There is a need to constantly strategize on measures such as implementing the use of an electronic appointment scheduling system and database, improving staff training on efficient patient flow management, and regularly assessing and optimizing administrative processes. By continuously monitoring and adapting these strategies, PHC facility managers can create a more efficient and patient-centered healthcare experience. [ABSTRACT FROM AUTHOR]

The access of new energy improves the flexibility of distribution network operation, but also leads to more complex mechanism of line loss. Therefore, starting from the nonlinear, fluctuating and multi-scale characteristics of line loss data, and based on the idea of decomposition prediction, this paper proposes a new method of line loss frequency division prediction based on wavelet transform and BIGRU-LSTM (Bidirectional Gated Recurrent Unit-Long Short Term Memory Network).Firstly, the grey relation analysis and the improved NARMA (Nonlinear Autoregressive Moving Average) correlation analysis method are used to extract the non-temporal and temporal influencing factors of line loss, and the corresponding feature data set is constructed. Then, the historical line loss data is decomposed into physical signals of different frequency bands by using wavelet transform, and the multi-dimensional input data of the prediction network is formed with the above characteristic data set. Finally, the BIGRU-LSTM prediction network is built to realize the probabilistic prediction of high-frequency and low-frequency components of line loss. The effectiveness and applicability of the method proposed in this paper were verified through numerical simulation. By dividing the line loss data into different frequency bands for frequency prediction, the mapping relationship between different line loss components and influencing factors was accurately matched, thereby improving the prediction accuracy. [ABSTRACT FROM AUTHOR]

Existing studies have explored the impact of venture capital shareholding on the GEM-listed companies before and after listing from multiple perspectives. However, there has been limited research on the influence of venture capital shareholding on these companies' mergers and acquisitions(M&A) activities and performance. Additionally, two conflicting research findings have been presented in limited relevant studies. In order to clarify the mechanism by which venture capital shareholding affects M&A activities and performance of GEM-listed companies and verify existing research conclusions, this paper takes 468 M&A events completed by the acquirer of China's GEM-listed companies between 2014 and 2016 as samples to explore venture capital shareholding's effects on the M&A performance of GEM-listed enterprises. The empirical findings demonstrate that GEM-listed enterprises with venture capital shareholding perform significantly better in terms of short-term and long-term M&A performance than those without; with the increase in venture capital shareholding ratio, the short-term M&A performance of GEM-listed enterprises has remarkably improved, but the long-term M&A performance does not show obvious correlation; joint investment of venture capital can significantly improve the short-term M&A performance of GEM-listed enterprises, but it has no substantial influence on long-term M&A performance. Based on further analysis of the empirical study, it is concluded that the common one-share ownership structure of GEM-listed enterprises is not conducive to the play of the monitoring function of venture capital, and the insufficient incentives and free-riding thinking also weaken the motivation and input of some venture capital shareholders to provide value-added services. This study systematically elucidates the mechanism and impact of venture capital shareholding on the M&A performance of GEM-listed companies, addressing the shortcomings in existing research. It is conducive for GEM-listed companies to gain a rational understanding and effectively leverage the active role of venture capital shareholders in M&A activities. [ABSTRACT FROM AUTHOR]

Introduction: Radiation exposure in medical settings stands as the primary source of artificial radiation, compounded by the yearly rise in healthcare worker numbers. Ensuring radiation protection is crucial for safeguarding their occupational health. Nevertheless, existing studies on radiation protection behavior exhibit considerable heterogeneity due to various factors. Objective: This scoping review aims to explore the current status of research on radiation protection behavior and identify research gaps, intending to guide future research directions. Methods and analysis: The scoping review will follow the Arksey and O'Malley framework and the Joanna Briggs Institute methodology. A systematic search will be conducted across English databases including PubMed, Web of Science, Embase, and Medline, as well as Chinese databases such as CNKI, Wanfang, VIP, and China Biomedical Literature Database. Two independent reviewers will screen the studies based on predefined eligibility criteria and extract the data. Any disagreements will be resolved through discussion by a third reviewer. The review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews. Strengths and limitations of this study: A stakeholder consultation will provide an opportunity to validate the findings and address any potential gaps in the article. In this scoping review, all types of studies will be considered. The effectiveness of the methodological quality of the included studies will not be reported, which may lead to some studies of poor quality being included. Only studies published in English or Chinese after 2010 will be considered in this review, potentially leading to the omission of relevant papers. [ABSTRACT FROM AUTHOR]

The increased usage of navigation technologies has caused conflicts in local traffic management, resulting in congested residential areas among other challenges for residents. This paper uses content analysis to investigate such negative social externalities within local communities and neighbourhoods. Through a corpus of 90 news articles about traffic incidents caused by navigation technologies, we identified negative traffic and safety-related externalities, including congestion, damage, pollution, and accidents. We also report on countermeasures by local communities and governments, including street closures, speed limit reduction, and turn bans. Based on our results, we discuss the implications for designing mobile navigation technologies that reduce negative social externalities. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of digital finance on the breakthrough innovation of enterprises with a sample of A-share listed companies in Shanghai and Shenzhen from 2011 to 2022. It is found that digital finance can promote corporate breakthrough innovation, and presents certain structural heterogeneity characteristics. The mechanism test shows that digital finance has the dual attributes of a financing platform and a social platform, which can promote breakthrough innovation by alleviating corporate financing constraints and expanding corporate social networks. Heterogeneity analysis reveals that the role of digital finance in promoting breakthrough innovation is characterized by regional heterogeneity, with digital finance playing a greater role in promoting breakthrough innovation in provinces with a low level of development of the banking sector, provinces with a high level of development of the capital market sector, and the central region. In addition, the degree of firms' external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on firms' breakthrough innovation. This paper enriches the related research on the impact of digital finance on enterprise innovation, and provides theoretical basis and policy insights on how digital finance can better assist the innovation-driven development strategy. [ABSTRACT FROM AUTHOR]

This paper examines the impact of the digital economy on sustainable development, using panel data from cities at the prefecture level and above in China from 2011 to 2019. The results indicate: (1) The digital economy is conducive to boosting growth, increasing employment, reducing energy consumption, and cutting emissions, thereby promoting sustainable development. These findings prove robust. (2) Mechanism test outcomes reveal that, from the perspective of technological innovation, the digital economy can promote sustainable development through increasing R&D input and enhancing innovation output. (3) An extended analysis of the risk of a digital "divide" demonstrates that "dividend" of the digital economy is primarily manifests in spurring economic growth, enhancing energy efficiency, and strengthening environmental protection in lagging regions, while the digital "divide" effect is manifested in the stronger employment stimulating effect of developed regions versus backward areas. The results of this study not only enrich the relevant research system, but also provide empirical evidence to support accelerating digital transformation, strengthening technological innovation governance, and advancing sustainable development. [ABSTRACT FROM AUTHOR]

As a key mechanism of belt conveyor, the health status and working state of its parts have a profound impact on whether the belt conveyor can run normally and safely. In the composition of the standard belt conveyor, the number of rollers is numerous and scattered. At the same time, under the complex environment of the work site, the fault detection of each roller is particularly difficult. In order to solve the above problems, a diagnosis method based on thermal infrared image features is proposed to detect the faults of each roller mechanism in the belt conveyor. Firstly, the position of the idler is identified based on the YOLOv4 identification method, and then the sticking resistance and bearing damage of the idler are detected based on the temperature difference discrimination method. In this paper, the target recognition method based on YOLOv4 is used to identify the position of the roller, and the recognition accuracy is 93.8%, which meets the requirements of the project. The infrared image obtained by the dual-spectrum camera is used to distinguish the fault of the idler in the coal mine. The temperature of the bearing and surface of the normal roller increases rapidly within 10 minutes of operation, and the temperature changes slightly after 10 minutes of operation. The bearing damaged idler has a greater friction effect at the bearing, so the temperature at the bearing rises faster, and there is a temperature difference of about 7°C between the bearing and the normal roller. The surface temperature of the idler in the blocking state is also fast for about 20 minutes, and there will be a temperature difference of about 8°between the surface of the idler and the normal roller. In this paper, it is determined that the temperature rise coefficients of the roller surface and bearing under normal conditions are 24% 28% and 18% 22% respectively. It is determined that the threshold value of the temperature rise coefficient in the blocking state and the damaged state is 30% and 25% respectively, that is, when the surface temperature rise coefficient of the roller is detected to be more than 30%, it is determined that the card resistance fault occurs, when the temperature rise coefficient at the roller bearing is detected > 25%, the bearing damage fault is judged. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the SSD algorithm does not fully extract the feature information contained in each feature layer, as well as the feature information is easily lost during the sampling process, which makes the feature expression ineffective and leads to insufficient performance in small target detection. In this paper, AMT-SSD is proposed, a small target detection algorithm that incorporates the multi-branch stacking and new sampling transition module of the attention mechanism. In this algorithm, the composite attention mechanism is utilized to improve the correlation of features of the samples to be detected in terms of spatial and channels, and the efficiency of the algorithm; secondly, multi-branch stacking module is used to extract multi-size features for each feature layer, and different sizes of convolution kernels are utilized in parallel to fully extract their features and improve the expression of features; meanwhile, during the sampling process, the problem of missing features is solved by applying inverse subpixel convolution in the new sampling transition module. Experimentally, the AMT-SSD algorithm achieves 84.6% and 53.4% mAP metrics on the PASCAL VOC dataset and MS COCO dataset, respectively. This indicates that the AMT-SSD algorithm can effectively extract feature information that is beneficial to detection samples, and also performs well in reducing feature loss, which is effective for the algorithm to improve the algorithm on small targets. [ABSTRACT FROM AUTHOR]

Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level. [ABSTRACT FROM AUTHOR]

Background: Surgical Patients and hospitals are now facing financial strain due to direct anesthetic demand as a result of the development of new anesthetic drugs, equipment, and techniques. Up to 15% of a hospital's pharmacy budget is currently allocated to anesthetic drug expenses. Drug wastage during anesthesia practice is a widespread hidden source of healthcare waste that leads to anesthetic drug shortages as well as poor operating room efficiency. On the other hand, despite the fact that it is preventable in the vast majority of cases, it is well described that drug wastage is routinely observed, including in developing countries where the consequences significantly affect both hospitals and patients. Methods: This review aims to review the prevalence of anesthetic drug waste across the world and systematically formulate and describe preventive strategies. Relevant publications were identified using systematic searches on databases including Google Scholar, Medline (PubMed), the Cochrane Library, and Embase. In addition, papers were detected and then selected through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria guidelines and the inclusion and exclusion criteria. Using the predetermined terms and dates from the searching databases, a total of 504 articles were identified. Based on the screening criteria, 16 papers were considered eligible and included in the final review. In addition, the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis was used for evaluating the quality of selected articles. This study is registered on PROSPERO, number CRD42024497044. Results: Of the sixteen publications from eleven different nations that were considered suitable for inclusion, only two of them addressed the waste of inhalational anesthetics. In more than half of eligible articles, propofol was the frequently wasted drug that contributed to increased financial loss through drug waste. The first most significant factor contributing to the waste of intravenous and inhalational anesthetics was the disposal of multidrug vials following their use for a single patient and high fresh gas flow, respectively. Conclusion: Anesthetic medication waste is a common occurrence worldwide, despite the fact that it is expensive and has a significant negative impact on operating room efficiency. Because the majority of drug waste is avoidable, preventive measures may lower drug waste and improve patient and hospital efficiency. [ABSTRACT FROM AUTHOR]

The method of partial differential equations for image inpainting achieves better repair results and is economically feasible with fast repair time. Addresses the inability of Curvature-Driven Diffusion (CDD) models to repair complex textures or edges when the input image is affected by severe noise or distortion, resulting in discontinuous repair features, blurred detail textures, and an inability to deal with the consistency of global image content, In this paper, we have the CDD model of P-Laplace operator term to image inpainting. In this method, the P-Laplace operator is firstly introduced into the diffusion term of CDD model to regulate the diffusion speed; then the improved CDD model is discretized, and the known information around the broken region is divided into two weighted average iterations to get the inpainting image; finally, the final inpainting image is obtained by weighted averaging the two image inpainting images according to the distancing. Experiments show that the model restoration results in this paper are more rational in terms of texture structure and outperform other models in terms of visualization and objective data. Comparing the inpainting images with 150, 1000 and 100 iterations respectively, Total Variation(TV) model and the CDD model inpainting algorithm always has inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well, TV model and the CDD model inpainting algorithm always have inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well. Of the images used for testing, the highest PSNR reached 38.7982, SSIM reached 0.9407, and FSIM reached 0.9781, the algorithm not only inpainting the effect and, but also has fewer iterations. [ABSTRACT FROM AUTHOR]

The rapid advances in Generative AI tools have produced both excitement and worry about how AI will impact academic writing. However, little is known about what norms are emerging around AI use in manuscript preparation or how these norms might be enforced. We address both gaps in the literature by conducting a survey of 271 academics about whether it is necessary to report ChatGPT use in manuscript preparation and by running GPT-modified abstracts from 2,716 published papers through a leading AI detection software to see if these detectors can detect different AI uses in manuscript preparation. We find that most academics do not think that using ChatGPT to fix grammar needs to be reported, but detection software did not always draw this distinction, as abstracts for which GPT was used to fix grammar were often flagged as having a high chance of being written by AI. We also find disagreements among academics on whether more substantial use of ChatGPT to rewrite text needs to be reported, and these differences were related to perceptions of ethics, academic role, and English language background. Finally, we found little difference in their perceptions about reporting ChatGPT and research assistant help, but significant differences in reporting perceptions between these sources of assistance and paid proofreading and other AI assistant tools (Grammarly and Word). Our results suggest that there might be challenges in getting authors to report AI use in manuscript preparation because (i) there is not uniform agreement about what uses of AI should be reported and (ii) journals might have trouble enforcing nuanced reporting requirements using AI detection tools. [ABSTRACT FROM AUTHOR]