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The medical field is facing a physician-scientist shortage, threatening future medical research and development. Medical institutions can contribute to developing physician-scientists by stimulating students' involvement in research. In this study, a medical undergraduate teaching module to develop research skills and encourage interest in research was held in Chongqing, China. Undergraduate medical students at Chongqing Medical University completed research skills training. Before and after the training, an online, anonymous, self-reported questionnaire was administered. The self-reported questionnaire investigated students' demographic characteristics, students' perception of attitudes toward conducting research, research skills (e.g., identifying and utilizing information, critical appraisal of literature, paper writing, and understanding of research), and feedback on scientific research training. The module was implemented with 25 students from July 2019 to October 2019, and 96.0% (N = 24) of participants responded to the questionnaire both prior to and after the training. In the evaluation of research skills, results showed that use of appropriate tools for research (Z = -3.340, p < 0.01), students' ability to undertake a focused literature search (Z = -3.40, p < 0.01), identifying and utilizing information (Z = -3.34, p < 0.01), and paper-writing skills (Z = -3.49, p < 0.01) were significantly improved after the undergraduates participated in the scientific research training. A qualitative analysis of the feedback showed that students found that the training helped to enhance their knowledge, improve their study scores, and motivate them to conduct research in the future. Early scientific research ability training strengthened the research skills of medical undergraduates and motivated them to pursue research.

While several test concordance tables have been published, the research underpinning such tables has rarely been examined in detail. This study aimed to survey the publically available studies or documentation underpinning the test concordance tables of the providers of four major international language tests, all accepted by the Australian Department of Home Affairs for Australian visa purposes. To evaluate the concordance studies, we first identified the good practice principles in concordance research through a review of both the relevant literature and leading professional standards in the field of educational measurement and language assessment. Next, we reviewed the concordance studies against the identified good practice principles. Our findings revealed that the information supplied by test providers varied, with some making the full research papers available, whereas others providing little information about their underpinning research. None of the concordance studies fulfilled all the good practice principles. Based on the findings of this study, we offer recommendations for future concordance research in the field of language testing as well as suggestions for practice.

This paper examines the quality evaluations of the Greek Universities highlighting those which offer a full-fledged study program of primary education. There are eight principles-criteria according to which each university is evaluated. For each principle, scores may range from 1 (noncompliance with the principle) to 4 (fully compliance). I present and compare results of the Greek university evaluations completed by the Hellenic Quality Assurance and Accreditation Agency (HQA). Surprisingly, no university has been graded as non-compliant in any of the eight principles-criteria. These evaluations are performed by an alleged "external" and "independent" committee. For all practical purposes, they are, nevertheless, based on subjective and biased opinions of academics affiliated with international universities with links to Greece and its universities. Independent and evidence-based evaluations paint a different picture. Universities which get perfect scores in the quality evaluation processes perform badly in the pertinent international ranking systems. As a case study, their primary education departments have lower research performance with high variability between faculty members and departments. Given that one criterion of evaluating quality is research, then not all Greek universities can be evaluated as highly performing research institutions, either in absolute or relevant terms. This criterion of quality is not satisfied by the primary education departments of Greek universities. According to this evidence, using the HQA as an agency to assess and accredit quality is useless. It should be abolished. A new system should be based on objective criteria such as independent teaching evaluations and research performance. These do not require any committee to evaluate performance and can be constructed on evidence-based policy. The latter relies solely on rigorously established objective facts.

Impact assessment research has developed theory-based approaches to trace the societal impact of scientific research. Impact assessment typically starts from the perspective of a research investment, organization, or project. Research users, non-academic actors involved in knowledge production, translation, and application, are well represented in many of these approaches. Researcher users are usually positioned as contributors to research, recipients of research outputs, or beneficiaries of research-driven outcomes. This paper argues that impact assessment would benefit from a more comprehensive understanding and analysis of research valorization processes from the user perspective. The first half of the paper reviews key impact assessment literature to identify how research users are positioned and portrayed in relation to valorization processes. In the second half of the paper, we use the results of this review to propose a set of principles to guide a systematic approach to constructing user perspectives on research impact. We suggest four concepts for operationalization of this approach. The paper concludes that the addition of a more comprehensive research user perspective on research valorization would complement and enhance existing impact assessment approaches.

The quality of a research study application sends a distinct signal to the institutional review board (IRB) about the skills, capacities, preparation, communication, experience, and resources of its authors. However, efforts to research and define IRB application quality have been insufficient. Inattention to the quality of an IRB application is consequential because the application precedes IRB review, and perceptions of quality between the two may be interrelated and interdependent. Without a clear understanding of quality, IRBs do not know how to define quality and researchers do not know how to achieve quality. This position has not been systematically studied to date, and future research could provide much-needed empirical validation. This paper lays the conceptual groundwork for future investigation into what constitutes quality in an IRB application. It includes a landscape review of multidisciplinary research on quality, as well as a discussion of quality frameworks analogous to research with human participants that exist in the published literature. It also examines the background and significance of federal research regulations, regulatory burdens, researchers' regulatory literacy, and the roles and responsibilities of IRB professionals within this ecosystem.

This paper is concerned with the process of selecting between the increasingly popular bi-factor model and the second-order factor model in measurement research. It is indicated that in certain settings widely used in empirical studies, the second-order model is nested in the bi-factor model and obtained from the latter after imposing appropriate parameter constraints. These restrictions can be directly tested within the framework of the latent variable modeling methodology employing widely circulated software. The outlined model selection procedure provides a readily applied means of choosing between the two models of growing interest to measurement scholars, and is illustrated using numerical data.

Although encompassing a variety of research approaches, qualitative research in music education shares the assumption that reality is socially constructed; it takes this construction to be based on the specific perspective of the individual human; and it considers epistemology and ontology to be different fields of study. The posthuman theory of agential realism, on the other hand, argues that the world is becoming through intra-actions; it decentres the individual humanist subject; and it studies onto-epistemology -- practices of knowing-in-being. Considering these fundamental differences, the quality criteria of qualitative research are not applicable to posthuman music education research. Nevertheless, posthuman research is concerned with the ethics of research and how to response-ably and ethically take part in the world's becoming. Thus, the emerging field of posthuman music education research must develop other ways of evaluating research beyond the quality criteria found in qualitative methodologies. This paper argues that diffraction -- both as a physical and musical phenomenon and as a philosophical concept -- might be a fruitful approach. By reading quality criteria diffractively through the agential realist concept of response-ability, it poses critical and creative questions, moving us towards evaluating the quality of posthuman music education research on its own terms.

Purpose: The purpose of this study is to systematically review the practice of reverse mentoring and draw a timeline of the research over the past two decades. Considering the novelty of this intervention, this paper proposed an agenda for future research on this burgeoning topic. Design/methodology/approach: By adopting narrative literature review and Gregory and Denniss' (2018) four-step process, this paper reviewed 54 studies grounded in conceptual, literature review and empirical research published between 1998 and 2020. Findings: The articles included in the literature review on reverse mentoring research were summarized according to journal publications, research methodologies, contextual settings, theoretical framework, purpose and outcomes. Reverse mentoring studies are dominantly published in educational journals using primarily qualitative and conceptual approaches to explore both academic and business contexts within the USA and Europe. Theories frequently used to frame and examine the need of reverse mentoring included social exchange theory and leader-member exchange theory. The fundamental purpose of reverse mentoring research is to transfer knowledge and to bridge the technology divide between intergenerational groups. Reverse mentoring has been used to promote inclusivity between multiple generations in relation to gender, ethnicity and culture. Originality/value: As per the knowledge, this is the first-ever comprehensive English summary of reverse mentoring research done in the past two decades. Findings from this research can be used to better understand reverse mentoring research trends and directions.

The purpose of this research is to make a meta-evaluation of the program evaluation studies on teacher training programs in Turkey. Meta-evaluation is the process of revealing the deficiencies and errors of the research as the last stage of the program evaluation process. In this context, the steps of the meta-evaluation processes were followed methodically. In the in this research, 9 program evaluation studies conducted between 2010 and 2020 about teacher training programs, using any program evaluation approach and model, were meta-evaluated. The sampling method of the research is criterion sampling.. Research data was collected using the "Program Evaluation Standards Checklist" developed by the researchers. During the development of the relevant data collection tool, the "Program Evaluation Standards" created by the Joint Committee on Standards for Educational Evaluation (JCSEE) were benefited. The studies included in the research were examined by 6 program experts who formed the meta-evaluation team. Each expert evaluated 3 studies using the checklist. Research data was analyzed using descriptive analysis method. Research findings indicate that the examined program evaluation studies meet the program evaluation standards by 55.67%. From this point, some suggestions that are believed to contribute to future program evaluation and meta-evaluation studies on teacher training were presented. [This study was an oral presentation in "International Pegem Conference on Education", Diyarbakir, Türkiye, 16-18 September 2020.]

Although robust evidence has been accumulating over the last decades supporting the effectiveness of career counseling in various populations, yet there are scarce conceptual or empirical studies investigating the impact of distinct approaches, such as traditional-"psychometric," narrative, or a mixed (integrative) one. The primary aim of this paper is to make a contribution in the field, providing a synthetic overview of contemporary research findings regarding the effectiveness of narrative and mixed career counseling approaches with a special focus on university students. The recent trend of utilizing mixed approaches in career assessment and intervention is also emphasized in the article, suggesting they may have a great potential in helping young adults advance meaning-making about career and life design. Finally, a discussion of both benefits and challenges relating to narrative and mixed interventions along with recommendations for extending research in the area of assessing career interventions' effectiveness for university students is provided.

As curricular reforms are implemented, there is often urgency among scholars to swiftly evaluate curricular outcomes and establish whether desired impacts have been realized. Consequently, many evaluative studies focus on summative program outcomes without accompanying evaluations of implementation. This runs the risk of Type III errors, whereby outcome evaluations rest on unverified assumptions about the appropriate implementation of prescribed curricular activities. Such errors challenge the usefulness of the evaluative studies, casting doubt on accumulated knowledge about curricular innovations, and posing problems for educational systems working to mobilize scarce resources. Unfortunately, however, there is long-standing inattention to the evaluation of implementation in health professions education (HPE). To address this, we propose an accessible framework that provides substantive guidance for evaluative research on implementation of curricular innovations. The Prescribed-Intended-Enacted-Sustainable (PIES) framework that is articulated in this paper, introduces new concepts to HPE--with a view to facilitating more nuanced examination of the evolution of curricula as they are implemented. Critically, the framework is theoretically grounded, integrating evaluation and implementation science as well as education theory. It outlines when, how, and why evaluators need to direct attention to curricular implementation, providing guidance on how programs can map out meaningful evaluative research agendas. Ultimately, this work is intended to support evaluators and educators, seeking to design evaluation studies that provide more faithful, useful representations of the intricacies of curricular change implementation.

Background: High-frequency patient-reported outcome (PRO) assessments are used to measure patients' symptoms after surgery for surgical research; however, the quality of those longitudinal PRO data has seldom been discussed.Objective: The aim of this study was to determine data quality-influencing factors and to profile error trajectories of data longitudinally collected via paper-and-pencil (P&P) or web-based assessment (electronic PRO [ePRO]) after thoracic surgery.Methods: We extracted longitudinal PRO data with 678 patients scheduled for lung surgery from an observational study (n=512) and a randomized clinical trial (n=166) on the evaluation of different perioperative care strategies. PROs were assessed by the MD Anderson Symptom Inventory Lung Cancer Module and single-item Quality of Life Scale before surgery and then daily after surgery until discharge or up to 14 days of hospitalization. Patient compliance and data error were identified and compared between P&P and ePRO. Generalized estimating equations model and 2-piecewise model were used to describe trajectories of error incidence over time and to identify the risk factors.Results: Among 678 patients, 629 with at least 2 PRO assessments, 440 completed 3347 P&P assessments and 189 completed 1291 ePRO assessments. In total, 49.4% of patients had at least one error, including (1) missing items (64.69%, 1070/1654), (2) modifications without signatures (27.99%, 463/1654), (3) selection of multiple options (3.02%, 50/1654), (4) missing patient signatures (2.54%, 42/1654), (5) missing researcher signatures (1.45%, 24/1654), and (6) missing completion dates (0.30%, 5/1654). Patients who completed ePRO had fewer errors than those who completed P&P assessments (ePRO: 30.2% [57/189] vs. P&P: 57.7% [254/440]; P<.001). Compared with ePRO patients, those using P&P were older, less educated, and sicker. Common risk factors of having errors were a lower education level (P&P: odds ratio [OR] 1.39, 95% CI 1.20-1.62; P<.001; ePRO: OR 1.82, 95% CI 1.22-2.72; P=.003), treated in a provincial hospital (P&P: OR 3.34, 95% CI 2.10-5.33; P<.001; ePRO: OR 4.73, 95% CI 2.18-10.25; P<.001), and with severe disease (P&P: OR 1.63, 95% CI 1.33-1.99; P<.001; ePRO: OR 2.70, 95% CI 1.53-4.75; P<.001). Errors peaked on postoperative day (POD) 1 for P&P, and on POD 2 for ePRO.Conclusions: It is possible to improve data quality of longitudinally collected PRO through ePRO, compared with P&P. However, ePRO-related sampling bias needs to be considered when designing clinical research using longitudinal PROs as major outcomes. [ABSTRACT FROM AUTHOR]

Increased charter school demand creates a critical need for reliable information on outcomes. Stanford's Center for Research on Education Outcomes (CREDO) has a series of influential reports on charter schools using the virtual control record (VCR) method. However, the VCR method has been criticized and the validity of CREDO's findings challenged, leading to confusion among stakeholders. In this paper, we synthesize charter school evaluation literature, explain CREDO's methods as well as other evaluation methods, and consider the limitations of matching in this context. We find that, while the matching techniques are imperfect, they provide necessary information on the greatest percentage of charter school students.

Rating scale development in the field of language assessment is often considered in dichotomous ways: It is assumed to be guided either by expert intuition or by drawing on performance data. Even though quite a few authors have argued that rating scale development is rarely so easily classifiable, this dyadic view has dominated language testing research for over a decade. In this paper we refine the dominant model of rating scale development by drawing on a corpus of 36 studies identified in a systematic review. We present a model showing the different sources of scale construct in the corpus. In the discussion, we argue that rating scale designers, just like test developers more broadly, need to start by determining the purpose of the test, the relevant policies that guide test development and score use, and the intended score use when considering the design choices available to them. These include considering the impact of such sources on the generalizability of the scores, the precision of the post-test predictions that can be made about test takers' future performances and scoring reliability. The most important contributions of the model are that it gives rating scale developers a framework to consider prior to starting scale development and validation activities.

Background: Information security is essential for organisations, hence the risk assessment. Information security risk assessment (ISRA) identifies, assesses, and prioritizes risks according to organisational goals. Previous studies have analysed and discussed information security risk assessment. Therefore, it is necessary to understand the models more systematically. Objective: This study aims to determine types of ISRA and fill a gap in literature review research by categorizing existing frameworks, models, and methods. Methods: The systematic literature review (SLR) approach developed by Kitchenham is applied in this research. A total of 25 studies were selected, classified, and analysed according to defined criteria. Results: Most selected studies focus on implementing and developing new models for risk assessment. In addition, most are related to information systems in general. Conclusion: The findings show that there is no single best framework or model because the best framework needs to be tailored according to organisational goals. Previous researchers have developed several new ISRA models, but empirical evaluation research is needed. Future research needs to develop more robust models for risk assessments for cloud computing systems. [ABSTRACT FROM AUTHOR]

Dear Editor, We are pleased our article is of interest to readers of I Caries Research i and appreciate the opportunity to respond to the "Letter to Editor" comments by Balachandran et al. [2022] regarding our publication, "Dental Health Inequalities among Indigenous Populations: A Systematic Review and Meta-Analysis"[Nath et al., 2021]. The funnel plot is a scatter diagram that represents study-specific effect sizes against study precision and means for detecting publication bias and exploring small study effect [Sterne et al., 2011]. Therefore, we decided to use a more generalized proxy terminology for dental caries inequality as "dental health inequalities.". [Extracted from the article]

Recent software advances have led to an expansion of the development and usage of application programming interfaces (APIs). From millions of Android packages (APKs) available on Google Store to millions of open-source packages available in Maven, PyPI, and npm, APIs have become an integral part of software development. Like any software artifact, software APIs evolve and suffer from this evolution. Prior research has uncovered many challenges to the development, usage, and evolution of APIs. While some challenges have been studied and solved, many remain. These challenges are scattered in the literature, which hides advances and cloaks the remaining challenges. In this systematic literature review on APIs and API evolution, we uncover and describe publication trends and trending topics.We compile common research goals, evaluation methods, metrics, and subjects.We summarize the current state-of-the-art and outline known existing challenges aswell as newchallenges uncovered during this review. We conclude that the main remaining challenges related to APIs and API evolution are (1) automatically identifying and leveraging factors that drive API changes, (2) creating and using uniform benchmarks for research evaluation, and (3) understanding the impact of API evolution on API developers and users with respect to various programming languages. [ABSTRACT FROM AUTHOR]

Background: Changing the food environment is an important public health lever for encouraging sustainable food choices. Targeting the availability of vegetarian main meals served in cafeterias substantially affects food choice, but acceptability has never been assessed. We examined the effects of an availability intervention at a French university cafeteria on students' main meal choices, meal offer satisfaction and liking. Methods: A four-week controlled trial was conducted in a university cafeteria in Dijon, France. During the two-week control period, vegetarian main meals constituted 24% of the offer. In the subsequent two-week intervention period, this proportion increased to 48%, while all the other menu items remained unchanged. Students were not informed of the change. Student choices were tracked using production data, and daily paper ballots were used to assess student satisfaction with the meal offer and liking of the main meal they chose (score range [1;5]). Nutritional quality, environmental impact, and cost of production of meal choices were calculated for each lunchtime. Food waste was measured over 4 lunchtimes during control and intervention periods. An online questionnaire collected student feedback at the end of the study. Results: Doubling availability of vegetarian main meals significantly increased the likelihood of choosing vegetarian options (OR = 2.57, 95% CI = [2.41; 2.74]). Responses of the paper ballots (n = 18,342) indicated slight improvements in meal offer satisfaction from 4.05 ± 0.92 to 4.07 ± 0.93 (p = 0.028) and in liking from 4.09 ± 0.90 to 4.13 ± 0.92 (p < 0.001) during control and intervention periods, respectively. The end-of-study questionnaire (n = 510) revealed that only 6% of students noticed a change the availability of vegetarian main meals. The intervention led to a decrease in the environmental impact of the main meals chosen, a slight decrease in nutritional quality, a slight increase in meal costs and no change in food waste. Conclusions: Doubling availability of vegetarian main meals in a university cafeteria resulted in a twofold increase in their selection, with students reporting being more satisfied and liking the main meals more during the intervention period. These results suggest that serving an equal proportion of vegetarian and nonvegetarian main meals could be considered in French university cafeterias to tackle environmental issues. Trial registration: Study protocol and analysis plan were pre-registered on the Open Science Framework (https://osf.io/pf3x7/). [ABSTRACT FROM AUTHOR]

Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning performance (LLP) through vocabulary learning performance (VLP) in the context of mobile vocabulary‐assisted listening learning by using two mobile learning tools. Methods: A total of 129 college students with a pre‐intermediate level of English were recruited as participants, and a 10‐week mobile vocabulary‐assisted, listening‐learning course was conducted in 2022. In each task of this course, the students had to learn target words from a listening passage on Quizlet and then engage in listening activities on Randall's ESL Cyber Listening Lab. Quantitative responses obtained through an online questionnaire were analysed through partial‐least‐squares structural equation modelling. Results: The analysis results indicated that BI significantly predicted LLP through VLP. Perceived ease of use (PEU) and perceived usefulness (PU) were significant antecedents of BI. However, PEU did not significantly predict PU because of the difficulty of navigating between the two technological tools used in this study. The extended model demonstrated its effectiveness in explaining listening learning performance, as evidenced by an explained variance (R2) of 69%. Conclusion: The extended model validates the influence of BI on learning performance and it can also draw teachers' focus toward the significance of enhancing students' BI to improve their listening learning performance. Pedagogical implications based on the results are provided in this paper. Lay Description: What is already known about this topic?: TAM was used to study learners' acceptance of mobile‐assisted language learning.TAM incorporates latent variables to explore mobile‐assisted language learning.Investigating factors influencing BI is a primary research focus in extended TAM literature.Mobile tools could improve listening learning and vocabulary retention. What this paper adds to that: Learning performance was considered as a dependent variable in an extended TAM.BI might predict students' learning performance in vocabulary and listening in an extended TAM.Teachers used two mobile tools to design mobile vocabulary‐assisted listening tasks.Pre‐learning the target words facilitate students' listening learning performance. Implications for practice and/or policy: We show the importance of BI on predicting listening learning performance.The impact of BI on other factors became another focus of TAM research.Results highlight pre‐learning target words' importance for better listening performance.Existing mobile tools improve listening performance, avoiding new system development. [ABSTRACT FROM AUTHOR]

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Purpose: This paper aims to describe a response to the needs of mental health workers (MHWs) in India during COVID-19 pandemic, through an online training program on trauma-informed intervention and care. Design/methodology/approach: A four-module online training program was developed. Two modules were aimed to bridge the knowledge gap on trauma for MHWs, so that they could effectively address the associated symptoms of fear and grief. The other two modules aimed to support MHWs' self-care and create supportive connections among colleagues. In this mixed method evaluation study, needs expressed before the training and lessons derived from the training were collected through questionnaires, focus group discussion and interviews. Findings: Of the 3,168 MHWs who registered for the training, 534 completed the pre-questionnaire. Of the 125 post-questionnaire records, 38 had watched all four modules. A great need for learning to work with grief and manage the increased workload without burnout was observed. Post-training gains included skills for working with fear and grief, which increased the confidence of MHWs. The importance of self-care was an eye-opener for many. Social implications: This study indicates a way to equip MHWs to address the trauma that will continue to live in people in the aftermath of crises. Originality/value: This study examined the challenges MHWs in India faced during the COVID-19 pandemic, revealing a knowledge gap on dealing with this level of trauma. It can contribute to the knowledge on how to support MHWs in such crises. [ABSTRACT FROM AUTHOR]

Inter-municipal cooperation (IMC) is a popular policy lacking appropriate performance measurement. This paper critically examines academic literature on the performance measurement of inter-municipal cooperation. It suggests a starting point for new evaluation research specific to IMC. Relevant papers are analysed to identify and explore potential research paths and formulate an agenda. The main criticality tackled by this review regards the "measurement for the sake of measurement" mindset, which leads to unbalance towards quantitative data, which is insufficient to reflect the complexities of public administration. Starting from the results, we posit a research agenda for further investigation of the performance of local shared services. [ABSTRACT FROM AUTHOR]

The editorial independence of biomedical journals allows flexibility to meet a wide range of research interests. However, it also is a barrier for coordination between journals to solve challenging issues such as racial bias in the scientific literature. A standardized tool to screen for racial bias could prevent the publication of racially biased papers. Biomedical journals would maintain editorial autonomy while still allowing comparable data to be collected and analyzed across journals. A racially diverse research team carried out a three-phase study to generate and test a racial bias assessment tool for biomedical research. Phase 1, an in-depth, structured literature search to identify recommendations, found near complete agreement in the literature on addressing race in biomedical research. Phase 2, construction of a framework from those recommendations, provides the major innovation of this paper. The framework includes three dimensions of race: 1) context, 2) tone and terminology, and 3) analysis, which are the basis for the Race Equity Vetting Instrument for Editorial Workflow (REVIEW) tool. Phase 3, pilot testing the assessment tool, showed that the REVIEW tool was effective at flagging multiple concerns in widely criticized articles. This study demonstrates the feasibility of the proposed REVIEW tool to reduce racial bias in research. Next steps include testing this tool on a broader sample of biomedical research to determine how the tool performs on more subtle examples of racial bias. [ABSTRACT FROM AUTHOR]

The high reliability demand of the machining center emphasizes the accuracy of the fault risk evaluation. In the traditional fault risk evaluation research of the machining center, the influence of fault mode is mostly based on subjective recommendation or does not consider the propagation and diffusion of fault, which makes the risk evaluation results different from the real situation. Therefore, this paper presents a framework to evaluate the fault risk for machining center components. A certain type of machining center is considered as a case study. The fault mode frequency ratio of components is calculated by fault mode analysis. The fault rate calculation is conducted based on the Johnson method. Considering that different fault modes have different influences on fault propagation breadth and depth, the hypergraph theory is used to build a hypernetwork model. The propagation and diffusion influence degree are defined to describe the propagation and diffusion process of faults. Then, the comprehensive influence degree of fault mode is calculated. The risk evaluation is realized by considering the component fault rate, fault mode frequency ratio, and the comprehensive influence degree of fault mode. The method proposed in this paper can provide a reference for the formulation of risk strategies for the machining center. [ABSTRACT FROM AUTHOR]

Background: There is a growing need for methods that acknowledge and successfully capture the dynamic interaction between context and implementation of complex interventions. Case study research has the potential to provide such understanding, enabling in-depth investigation of the particularities of phenomena. However, there is limited guidance on how and when to best use different case study research approaches when evaluating complex interventions. This study aimed to review and synthesise the literature on case study research across relevant disciplines, and determine relevance to the study of contextual influences on complex interventions in health systems and public health research.Methods: Systematic meta-narrative review of the literature comprising (i) a scoping review of seminal texts (n = 60) on case study methodology and on context, complexity and interventions, (ii) detailed review of empirical literature on case study, context and complex interventions (n = 71), and (iii) identifying and reviewing 'hybrid papers' (n = 8) focused on the merits and challenges of case study in the evaluation of complex interventions.Results: We identified four broad (and to some extent overlapping) research traditions, all using case study in a slightly different way and with different goals: 1) developing and testing complex interventions in healthcare; 2) analysing change in organisations; 3) undertaking realist evaluations; 4) studying complex change naturalistically. Each tradition conceptualised context differently-respectively as the backdrop to, or factors impacting on, the intervention; sets of interacting conditions and relationships; circumstances triggering intervention mechanisms; and socially structured practices. Overall, these traditions drew on a small number of case study methodologists and disciplines. Few studies problematised the nature and boundaries of 'the case' and 'context' or considered the implications of such conceptualisations for methods and knowledge production.Conclusions: Case study research on complex interventions in healthcare draws on a number of different research traditions, each with different epistemological and methodological preferences. The approach used and consequences for knowledge produced often remains implicit. This has implications for how researchers, practitioners and decision makers understand, implement and evaluate complex interventions in different settings. Deeper engagement with case study research as a methodology is strongly recommended. [ABSTRACT FROM AUTHOR]

The heart and soul of the Chinese people and the greatest cultural soft power of contemporary China are excellent Chinese healthy cultural environments. Short video platforms and short videos have a chance to develop as the Internet revolution continues to intensify and mobile clients gain popularity. This essay examines the challenges involved in producing brief videos that promote a healthy cultural environment in the new context of internet plus, as well as the means of transmitting such videos and creative methods for doing so. Excellent communication content is created in this paper from two perspectives of visual presentation and in-depth meaning, allowing users to fully understand the connotation of a healthy cultural environment. Through the theme of a healthy cultural environment, topic discussion and characteristic activities will be carried out to encourage users' spontaneous sharing of the interactive behavior of communication and the fission communication of brief videos of a healthy environment. This paper develops a model for intelligent recommendation and short video content analysis based on this. In order to further encourage the creative dissemination and development of short videos about healthy cultural environments, the model is used to choose high-quality videos and accurately recommend them to the appropriate users and to serve as an example of how a quick video can be used to communicate innovation and a healthy cultural environment. [ABSTRACT FROM AUTHOR]

Background: STEM education providers increasingly use complex intervention models to redress persistent under-representation in STEM sectors. These intervention models require robust evaluation to determine their effectiveness. The study examines a complex, sustained intervention intended to build science capital in young people aged 11–15 over 3 years, which drew on science capital theory and related research to inform intervention design and evaluation. When evaluation results differed from those anticipated, process evaluation supported authors to interpret these findings. By outlining challenges faced in the evaluation of a complex, sustained STEM outreach intervention, this paper addresses critique that outreach programmes focus too often on short-term and positive findings. Results: Intervention outcomes were assessed using a quantitative questionnaire adapted from science capital research, issued to pupils at the intervention's baseline (2015), midpoint (2017) and endpoint (2019). Adopting a cohort-based model, the 2015 questionnaire collected a baseline for the Year 7 intervention group (children aged 11–12, N = 464), and established baseline comparator groups for Year 9 (children aged 13–14, N = 556) and Year 11 (children aged 15–16, N = 342). The Year 7 intervention group was re-evaluated again in 2017 when in Year 9 (N = 556), and in 2019 when in Year 11 (N = 349). Analysis explored differences in science capital between the intervention and comparator groups and identified lower composite science capital scores and greater proportions of low- and medium-science capital in the intervention group when compared with the two comparator groups. A rationale for this emerged from the subsequent process evaluation. Conclusions: This study's main contribution is the provision of nuanced insight into the evaluation of STEM interventions for use by others evaluating in similar circumstances, particularly those adopting sustained or complex delivery models. This paper concludes that assessing the effectiveness of complex interventions cannot rely on quantitative evaluation of outcomes alone. Process evaluation can complement quantitative instruments and aid interventions to better understand variability and interpret results. While this study highlights the value of science capital when designing intervention models, it also illustrates the inherent challenges of using an outcome measure of 'building science capital', and quantifying levels over an intervention's course. [ABSTRACT FROM AUTHOR]

Background: The literature on qualitative data analysis mostly concerns analyses pertaining to an individual research question and the organization of data within that research question. Few authors have written about the entire qualitative dataset from which multiple and separate analyses could be conducted and reported. The concept of analytic direction is a strategy that can assist qualitative researchers in deciding which findings to highlight within a dataset. The objectives of this paper were to: 1) describe the importance of analytic direction in qualitative research, and 2) provide a working example of the concept of analytic direction.Methods: A qualitative dataset from one of the author's research programs was selected for review. Ten potential analytic directions were identified after the initial phenomenological analysis was conducted. Three analytic directions based on the same coding template but different content areas of the data were further developed using phenomenological analysis (n = 2) and qualitative description (n = 1) and are the focus of this paper. Development and selection of these three analytic directions was determined partially relying on methodological criteria to promote rigour including a comprehensive examination of the data, the use of multiple analysts, direct quotations to support claims, negative case analysis, and reflexivity.Results: The three analytic directions addressed topics within the scope of the overall research question. Each analytic direction had its own central point or story line and each highlighted a different perspective or voice. The use of an inductive and deductive approach to analysis and how the role of theory was integrated varied in each analytic direction.Conclusions: The concept of analytic direction enables researchers to organize their qualitative datasets in order to tell different and unique "stories". The concept relies upon, and promotes, the conduct of rigourous qualitative research. [ABSTRACT FROM AUTHOR]

This paper proposes an image quality evaluation (IQE) metric by considering gradient, visual saliency, and color information. Visual saliency and gradient information are two types of effective features for quality evaluation research. Different regions within an image are not uniformly important for IQE. Visual saliency can find the most attractive regions to the human visual system in a given image. These attractive image regions are more strongly correlated with image quality results. In addition, the degradation of gradient information is related to the structure distortion which is a very important factor for image quality. However, the two types of features cannot accurately evaluate the color distortion of images. In order to evaluate chromatic distortion, this paper proposes the color similarity which is measured in the YIQ color space. The computation of the proposed method begins with the similarity calculation of local gradient information, visual saliency, and color information. Then, the final quality score is obtained by the standard deviation on each similarity component. The experimental results on five benchmark databases (i.e., CSIQ, IVC, LIVE, TID2013, and TID2008) show that the proposed IQE method performs better than other methods in the correlation with subjective quality judgment. [ABSTRACT FROM AUTHOR]

Introduction: Involving service users in health service design and delivery is considered important to improve the quality of healthcare because it ensures that the delivery of healthcare is adapted to the needs of the users. Co‐production is a process used to involve service users, but multiple papers have highlighted the need for the mechanisms and values guiding co‐production to be more clearly stated. The aim of this paper was to evaluate the mechanisms and values that guided the co‐production approach of the Stories for Change project, which used Public Narrative as part of the co‐design process to create change in National Health Service maternity services. Methods: This study was conducted using a rapid feedback evaluation approach. Semistructured interviews (n = 16) were the main source of data, six of which were maternity service users, with observations (5 h) and documentary analysis also carried out in parallel. RREAL sheets were used for data analysis to organize data based on key topics of interest. Results: This study identified three broad mechanisms and values underpinning the co‐production approach: creating an open and safe space to share ideas, learning how to tell stories using Public Narrative and having service providers who play a key role in strengthening the health system listen to stories compelling them to action. This study identified the main areas for improvement of the Stories for Change project related to recruitment, the inclusion of participants, the co‐design process, the Skills Session and the Learning Event. Conclusion: Our study provided a deeper understanding of the co‐production approach that addresses the need to uncover the mechanism and values underlying co‐production and co‐design approaches. This study expands on the literature pertaining to the influence of storytelling in creating meaningful change in health care. We propose a co‐design methodology that uses Public Narrative as a model for service user engagement to help inform future healthcare development processes. Patient or Public Contribution: The experiences and perceptions of maternity service users and health professionals informed this evaluation. The project organizers were involved in the manuscript preparation stage by providing feedback, and service users wrote a commentary on the project from the lived experience perspective. [ABSTRACT FROM AUTHOR]

Aim: To demonstrate how implementing a system‐wide measurement and improvement programme can make the delivery of the Fundamentals of Care visible in practice. Design: Discussion paper. Data Sources: A retrospective evaluation of the experience of implementing a system‐wide peer review programme using the Promoting Action on Research Implementation in Health Services framework. Implications for Nursing: Implementing this programme engages nursing leaders at all levels in fundamental care delivery, evaluation and improvement. It positions nursing leaders as accountable for and champions of fundamental care. Conclusion: The peer review programme offers a solution to the complex challenge of measuring the fundamentals of care in practice. Successful implementations of this programme at two New Zealand inpatient sites have shown positive results in improved care and patient experience. This makes it worthy of consideration for other health organizations. Nursing leadership has proven to be critical to success. The Promoting Action on Research Implementation in Health Services framework highlights the components that assist with successful implementation and assists in presenting a case for change. Impact This paper addressed the problem of the lack of action and dearth of quality, integrated data, visibility of the patient experience and the contribution of nursing leadership in an inpatient setting. Findings indicate that the peer review programme is translatable, modifiable and sensitive to ethnicity and disability. Using the implementation framework to evaluate the process has provided a guide for future implementations. [ABSTRACT FROM AUTHOR]

Background: Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.a. process cohorts. This comparison can help to identify insights for improving processes. There are a few software supports to enable process cohort comparison based on the frequencies of process activities and performance metrics. These metrics are effective in cohort analysis, but they cannot support cohort comparison based on the probability of transitions among states, which is an important enabler for cohort analysis in healthcare.Results: This paper defines an approach to compare process cohorts using Markov models. The approach is formalized, and it is implemented as an open-source python library, named dfgcompare. This library can be used by other researchers to compare process cohorts. The implementation is also used to compare caregivers' behavior when prescribing drugs in the Stockholm Region. The result shows that the approach enables the comparison of process cohorts in practice.Conclusions: We conclude that dfgcompare supports identifying differences among process cohorts. [ABSTRACT FROM AUTHOR]

The incidence of many hormone-dependent diseases, including testicular cancer, has sharply increased in all high-income countries during the 20th century. This is not fully explained by established risk factors. Concurrent, increasing exposure to antiandrogenic environmental endocrine disrupting chemicals (EDCs) in fetal life may partially explain this trend. This systematic review assessed available evidence regarding the association between environmental EDC exposure and risk of testicular cancer (seminomas and nonseminomas). Following PRISMA guidelines, a search of English peer-reviewed literature published prior to December 14, 2020 in the databases PubMed and Embase® was performed. Among the 279 identified records, 19 were eligible for quality assessment and 10 for further meta-analysis. The completeness of reporting was high across papers, but over 50% were considered subject to potential risk of bias. Mean age at diagnosis was 31.9 years. None considered effects of EDC multipollutant mixtures. The meta-analyses showed that maternal exposure to combined EDCs was associated with a higher risk of testicular cancer in male offspring [summary risk ratios: 2.16, (95% CI:1.78-2.62), 1.93 (95% CI:1.49-2.48), and 2.78 (95% CI:2.27-3.41) for all, seminoma, and nonseminoma, respectively]. Similarly, high maternal exposures to grouped organochlorines and organohalogens were associated with higher risk of seminoma and nonseminoma in the offspring. Summary estimates related to postnatal adult male EDC exposures were inconsistent. Maternal, but not postnatal adult male, EDC exposures were consistently associated with a higher risk of testicular cancer, particularly risk of nonseminomas. However, the quality of studies was mixed, and considering the fields complexity, more prospective studies of prenatal EDC multipollutant mixture exposures and testicular cancer are needed. [ABSTRACT FROM AUTHOR]

Background: In recent years, with the development of artificial intelligence, the use of deep learning technology for clinical information extraction has become a new trend. Clinical Event Detection (CED) as its subtask has attracted the attention from academia and industry. However, directly applying the advancements in deep learning to CED task often yields unsatisfactory results. The main reasons are due to the following two points: (1) A great number of obscure professional terms in the electronic medical record leads to poor recognition performance of model. (2) The scarcity of datasets required for the task leads to poor model robustness. Therefore, it is urgent to solve these two problems to improve model performance.Methods: This paper proposes a combining data augmentation and domain information with TENER Model for Clinical Event Detection.Results: We use two evaluation metrics to compare the overall performance of the proposed model with the existing model on the 2012 i2b2 challenge dataset. Experimental results demonstrate that our proposed model achieves the best F1-score of 80.26%, type accuracy of 93% and Span F1-score of 90.33%, and outperforms the state-of-the-art approaches.Conclusions: This paper proposes a multi-granularity information fusion encoder-decoder framework, which applies the TENER model to the CED task for the first time. It uses the pre-trained language model (BioBERT) to generate word-level features, solving the problem of a great number of obscure professional terms in the electronic medical record lead to poor recognition performance of model. In addition, this paper proposes a new data augmentation method for sequence labeling tasks, solving the problem of the scarcity of datasets required for the task leads to poor model robustness. [ABSTRACT FROM AUTHOR]

This paper analyzes a UK-based psychoeducational intervention for users of online child sexual exploitation material (CSEM). It is founded on 17 months of anthropological research in group programs with 81 participants and 15 staff. The article argues that group exercises help participants reframe knowledge about their offending, and ultimately reinforce the theoretical concept of discipline (Foucault) toward internal and external surveillance, normalization, and decreased risk. The paper first discusses factors participants believed contributed to offending. It then analyzes the program and participants' experiences, focusing on exercises about the mind (fantasy), Internet usage (disclosure and relationships), needs met by offending (Good Lives and true needs), and planning for the future (relapse prevention). Critical is that participants are encouraged to reengage offline lives and enact discipline on and to the online world. Thus, the article ends with an anthropologically-minded discussion about digital norms, online morality, and implications for Internet offender psychoeducational practice. [ABSTRACT FROM AUTHOR]

This research examines the differential effect of research-writing teaching innovation on proposal and dissertation completion rates at the Turfloop Graduate School of Leadership (TGSL). The method combined a review with a longitudinal quantitative secondary data design. The data on proposal and dissertation completion rates were compared using a t-test statistics. Findings show that at an alpha level of 0.05, a significant difference (at P<0.05) exists in the proposal and dissertation completion rates between the pre-innovation teaching period and within the innovation teaching period – with improved completion rate occurring during the teaching innovation period. Results also depict a mean difference in research methodology pass marks (albeit insignificance). Based on the findings, the paper contributes by developing an agency-based inclusive framework for teaching dissertation research writing. This framework provides an agenda for further research on teacher and student agency, and hence inclusive teaching of academic writing. [ABSTRACT FROM AUTHOR]

Time-Sensitive Networking (TSN) is a set of Ethernet standards aimed to improve determinism in packet delivery for converged networks. The main goal is to provide mechanisms that enable low and predictable transmission latency and high availability for demanding applications such as real-time audio/video streaming, automotive, and industrial control. To provide the required guarantees, TSN integrates different traffic shaping mechanisms including 802.1Qbv, 802.1Qch, and 802.1Qcr, allowing for the coexistence of different traffic classes with different priorities on the same network. Achieving the required quality of service (QoS) level needs proper selection and configuration of shaping mechanisms, which is difficult due to the diversity in the requirements of the coexisting streams under the presence of potential end-system-induced jitter. This paper discusses the suitability of the TSN traffic shaping mechanisms for the different traffic types, analyzes the TSN network configuration problem, i.e., finds the optimal path and shaper configurations for all TSN elements in the network to provide the required QoS, discusses the goals, constraints, and challenges of time-aware scheduling, and elaborates on the evaluation criteria of both the network-wide schedules and the scheduling algorithms that derive the configurations to present a common ground for comparison between the different approaches. Finally, we analyze the evolution of the scheduling task, identify shortcomings, and suggest future research directions. [ABSTRACT FROM AUTHOR]

Background: A robust evidence base is required to assist healthcare commissioners and providers in selecting effective and sustainable approaches to improve cancer diagnosis and treatment. Such evidence can be difficult to build, given the fast-paced and highly pressured nature of healthcare delivery, the absence of incentives, and the presence of barriers in conducting pragmatic yet robust research evaluations. Cancer Research UK (CRUK) has played an active part in building the evidence base through its funding of programmes to identify, evaluate and scale-up innovative approaches across the UK. The aim of this paper is to describe and explain the research design and intended approach and activities for two cancer services improvement projects in Scotland funded by CRUK. Methods: A hybrid effectiveness-implementation study design will assess both the efficiency of the new pathways and their implementation strategies, with the aim of generating knowledge for scale-up. A range of implementation, service and clinical outcomes will be assessed as determined by the projects' Theories of Change (ToCs). A naturalistic case study approach will enable in-depth exploration of context and process, and the collection and synthesis of data from multiple sources including routine datasets, patient and staff surveys, in-depth interviews and observational and other data. The evaluations are informed throughout by a patient/public representatives' group, and by small group discussions with volunteer cancer patients. Discussion: Our approach has been designed to provide a holistic understanding of how (well) the improvement projects work (in relation to their anticipated outcomes), and how they interact with their wider contexts. The evaluations will help identify barriers, facilitators, and unanticipated consequences that can impact scalability, sustainability and spread. By opting for a pragmatic, participatory evaluation research design, we hope to inform strategies for scaling up successful innovations while addressing challenges in a targeted manner. [ABSTRACT FROM AUTHOR]

Background: Over 90% of the 50,000 deaf children in the UK have hearing parents, many of whom were not expecting a deaf child and may require specialist support. Deaf children can experience poorer long-term outcomes than hearing children across a range of domains. After early detection by the Universal Newborn Hearing Screening Programme, parents in the UK receive support from Qualified Teachers of the Deaf and audiologists but resources are tight and intervention support can vary by locality. There are challenges faced due to a lack of clarity around what specific parenting support interventions are most helpful.Methods: The aim of this research was to complete a systematic scoping review of the evidence to identify early support interventions for parents of deaf infants. From 5577 identified records, 54 met inclusion criteria. Two reviewers screened papers through three rounds before completing data extraction and quality assessment.Results: Identified parent support interventions included both group and individual sessions in various settings (including online). They were led by a range of professionals and targeted various outcomes. Internationally there were only five randomised controlled trials. Other designs included non-randomised comparison groups, pre / post and other designs e.g. longitudinal, qualitative and case studies. Quality assessment showed few high quality studies with most having some concerns over risk of bias.Conclusion: Interventions commonly focused on infant language and communication followed by parental knowledge and skills; parent wellbeing and empowerment; and parent/child relationship. There were no interventions that focused specifically on parent support to understand or nurture child socio-emotional development despite this being a well-established area of poor outcome for deaf children. There were few UK studies and research generally was not of high quality. Many studies were not recent and so not in the context of recent healthcare advances. Further research in this area is urgently needed to help develop evidence based early interventions. [ABSTRACT FROM AUTHOR]

This paper determines the assessment of publications submitted to the UK research evaluation carried out in 2014, the REF, which would have resulted if they had been assessed with the bibliometric algorithm used by the Italian evaluation agency, ANVUR, for its evaluation of the research of Italian universities. We find extremely high correlations between the two assessment approaches. [ABSTRACT FROM AUTHOR]

Aims: Most patients who receive implantable cardioverter defibrillators (ICDs) for primary prevention do not receive therapy during the lifespan of the ICD, whilst up to 50% of sudden cardiac death (SCD) occur in individuals who are considered low risk by conventional criteria. Machine learning offers a novel approach to risk stratification for ICD assignment.Methods and Results: Systematic search was performed in MEDLINE, Embase, Emcare, CINAHL, Cochrane Library, OpenGrey, MedrXiv, arXiv, Scopus, and Web of Science. Studies modelling SCD risk prediction within days to years using machine learning were eligible for inclusion. Transparency and quality of reporting (TRIPOD) and risk of bias (PROBAST) were assessed. A total of 4356 studies were screened with 11 meeting the inclusion criteria with heterogeneous populations, methods, and outcome measures preventing meta-analysis. The study size ranged from 122 to 124 097 participants. Input data sources included demographic, clinical, electrocardiogram, electrophysiological, imaging, and genetic data ranging from 4 to 72 variables per model. The most common outcome metric reported was the area under the receiver operator characteristic (n = 7) ranging between 0.71 and 0.96. In six studies comparing machine learning models and regression, machine learning improved performance in five. No studies adhered to a reporting standard. Five of the papers were at high risk of bias.Conclusion: Machine learning for SCD prediction has been under-applied and incorrectly implemented but is ripe for future investigation. It may have some incremental utility in predicting SCD over traditional models. The development of reporting standards for machine learning is required to improve the quality of evidence reporting in the field. [ABSTRACT FROM AUTHOR]

In the context of the new era, the distinctive function of BD (big data) analysis and prediction also introduces a new way of thinking to university IPE (ideological and political education), broadens the domain of university IPE, and enhances the curricular offerings of IPE universities. In order to enhance the intelligence and personalization of the intelligent teaching system, this paper describes in detail the design and implementation processes for each component of the system. It also uses the association mining rule algorithm of data mining. To maintain population diversity, a population initialization method and a neighborhood-based search operator are used, both of which are based on a thorough consideration of the characteristics of complex networks. The neighborhood search strategy enhances the local search capability of the TLBO (Teaching-Learning Based Optimization) algorithm. The optimized TLBO algorithm presented in this paper achieves the highest average modularity value of 0.5238 through testing on real-world data sets. The outcomes demonstrate that the algorithm performs well and is successful in identifying problems in the community. [ABSTRACT FROM AUTHOR]

Yan'an is one of the "two holy places" of the Chinese nation and the Chinese revolution and is one of the first cities of historical and cultural significance and an outstanding tourist city in China, as announced by the state council. The evaluation of the effectiveness of environmental conservation is one of the very important elements of the conservation of Yan'an's architectural heritage. However, the existing evaluation methods cannot provide new solutions for decision-making, the meaning of the comprehensive evaluation function is unclear, the naming clarity is low, there is less quantitative data and more qualitative components, and the results are not easily convincing. This paper proposes a method for evaluating the practical effects of environmental class measures in the conservation of Yan'an's architectural heritage based on recurrent neural networks. The recurrent neural network makes full use of the memory function in the network, considers the causal relationship of the actual effect, and efficiently evaluates the existing measures. In comparison with factor analysis and hierarchical analysis, this paper has greater applicability in evaluating the practical effects of environmental measures in the conservation of Yan'an's architectural heritage and is basically consistent with the results of the theoretical analysis. It provides a scientific basis for the construction and implementation of environmental measures for the architectural heritage of Yan'an. [ABSTRACT FROM AUTHOR]

The water environment is one of the basic elements that constitute the environment. It is an important place for the survival and development of human society, and it is also the most seriously disturbed and damaged area by humans. The pollution and destruction of water environment has become one of the major environmental problems in the world today. The essence of urban water space landscape design under the concept of integrating people's ecological design is the ecological landscape design of urban water spaces, while the development of ecological landscape design in the field of urban water space landscape design is still in its infancy, and the interpretation of its concept is also different. The ecological design of the landscape reflects a new dream of human beings, a new aesthetics and value: the true cooperative and fraternal relationship between man and nature. At present, the ecological design of urban water space landscape has not put forward a more accurate concept, clear principles and standards, and a complete and systematic theoretical basis, which requires further research, discussion, and continuous practice by this generation of designers to improve it. To this end, this paper proposed a research method on the integration of water environment governance in urban and rural spaces with natural ecological landscape design. This paper mainly talked about the status quo of water environment and its network sensor algorithm research and analyzed its coverage area one by one. Then, the water quality extraction is introduced in detail. And finally, the data analysis of the Beijing river waters, the analyzer rainfall, water quality, and so on are carried out in the experimental part. It could be seen from the experimental results that there were currently 22 reclaimed water plants in six urban areas of Beijing, with a daily water treatment capacity of 4.08 million cubic meters and a sewage treatment rate of 98%. As of 2016, 440 million cubic meters of reclaimed water has been reused. With the commissioning of the new reclaimed water system, the proportion of reclaimed water in the river and lake environment will continue to increase. [ABSTRACT FROM AUTHOR]

Introducing systems thinking concepts in the programme evaluation field has been mostly aimed at supporting the practice of evaluation, rather than towards making theoretical advancements in the evaluation field. This paper introduces ideas and principles from systems thinking at the theoretical and practical levels in the programme evaluation field as applied to a peace‐building programme called the Hermes Programme in Colombia. This document demonstrates how systems thinking concepts and tools were used in the practice of evaluation. We show the theoretical development of the proposed evaluation and explain how its stages were carried out in evaluating the Hermes Programme. This paper also illustrates the benefits of using systems thinking in evaluation. [ABSTRACT FROM AUTHOR]

In view of the fact that music courses are seldom offered in schools and lack of management, there are many problems in the management system of music and art. In order to improve the learning effect of students in music courses, this paper proposes to build a music art management curriculum system based on the in-depth learning model. This paper puts forward the requirements of in-depth learning in music and art curriculum indicators and puts forward the model framework of music and art learning. Through the combined application of music courses, first of all, the current music course model is compared with Ghostnet music course, Mobilenet music course, and traditional music course to verify that the current music course model has certain advantages in accuracy, precision, recall, and image recognition performance. This proves that the current music curriculum is more suitable for the construction of this model. Secondly, the proposed model has a high score through the comprehensive application of several indicators in the course. Finally, under the model constructed by deep learning, the opening of music courses in schools has also increased significantly and improves the interest point and the application of people on the music art course so as to achieve the final application effect. [ABSTRACT FROM AUTHOR]

In this paper, the safety of Tripterygium wilfordii polyglycoside (TW) preparation was evaluated by combining literature research and evidence-based evaluation research, so as to provide evidence-based safety information of Tripterygium wilfordii polyglycoside preparation (nephroptosis) for government decision making and clinical application. In this paper, we propose a network structure inspired by the LSTM gate mechanism. All the research methods of the included references are evaluated by internationally recognized evaluation tools or standards. Prevalence was analyzed according to the type of intervention (e.g., time of administration) and route of administration. The results of this experiment provide methods and suggestions for the evaluation of traditional Chinese medicine nephroptosis in the future. [ABSTRACT FROM AUTHOR]

Objectives: To assess the quality of evidence on the effectiveness of local US laws restricting the sale of flavored tobacco products.Methods: We conducted a systematic search and qualitative scoping review of English-language papers published through May 2020 that evaluated flavored tobacco sales policies implemented by US jurisdictions during 2010-2019. We constructed a conceptual model for flavored and menthol tobacco sales restriction outcomes, assigned GRADE quality of evidence ratings to policy outcomes evaluated through the included studies, and summarized factors that might explain weak or inconsistent findings.Results: We found moderate to high quality of evidence associating policy implementation with reduced availability, marketing, and sales of policy-restricted products, and decreased youth and adult tobacco use of these products; however, policy exclusions and exemptions, implementation challenges, tobacco industry actions (e.g., marketing of concept-named flavored products; exploiting policy exemptions for certain store types), and consumer responses (e.g., cross-border or illicit purchasing) might undermine or mitigate intended policy effects.Conclusions: Flavored and menthol tobacco product sales restrictions implemented and evaluated in US jurisdictions appear to have achieved some of their intended outcomes; however, deficiencies in study designs, methods, and metrics could contribute to equivocal findings on quality of evidence associating policy implementation and outcomes. Gaps in the evidence are beginning to be filled with research using more rigorous study designs, improved measurement and analytic methods, and longer-term follow-up.Implications: In the absence of comprehensive federal action, US jurisdictions have the obligation to restrict flavored and menthol product sales to protect vulnerable populations from tobacco-related harms. The considerable expenditure of financial resources, political will, and time dedicated to policy adoption and implementation argue for evaluation studies designed to maximize the quality of evidence. This review offers generalizable insights into evaluation findings that can inform efforts to enhance tobacco control policy implementation and impact in the US and globally. [ABSTRACT FROM AUTHOR]

Background: MiRNA is a class of non-coding single-stranded RNA molecules with a length of approximately 22 nucleotides encoded by endogenous genes, which can regulate the expression of other genes. Therefore, it is very important to predict the associations between miRNA and disease. Predecessors developed a new prediction method of drug-disease association, and it achieved good results.Methods: In this paper, we introduced the method of LAGCN to identify potential miRNA-disease associations. First, we integrate three associations into a heterogeneous network, such as the known miRNA-disease association, miRNA-miRNA similarities and disease-disease similarities, next we apply graph convolution network to learn the embedding of miRNA and disease. We use an attention mechanism to combine embedding from multiple convolution layers. Unobserved miRNA-disease associations are scored based on integrated embedding.Results: After fivefold cross-validations, the value of AUC is reached 0.9091, which is higher than other prediction methods and baseline methods.Conclusions: In this paper, we introduced the method of LAGCN to identify potential miRNA-disease associations. LAGCN has achieved good performance in predicting miRNA-disease associations, and it is superior to other association prediction methods and baseline methods. [ABSTRACT FROM AUTHOR]