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BACKGROUND: Since the inception of the Youth Risk Behavior Surveillance System in 1991, all surveys have been conducted in schools, using paper and pencil instruments (PAPI). For the 2019 YRBSS, sites were offered the opportunity to conduct their surveys using electronic data collection. This study aimed to determine whether differences in select metrics existed between students who completed the survey electronically versus using PAPI. METHODS: Thirty risk behaviors were examined in this study. Data completeness, response rates and bivariate comparisons of risk behavior prevalence between administration modes were examined. RESULTS: Twenty‐nine of 30 questions examined had more complete responses among students using electronic surveys. Small differences were found for student and school response rates between modes. Twenty‐five of 30 adolescent risk behaviors showed no mode effect. CONCLUSIONS: Seven of 44 states and DC participated electronically. Because survey data were more complete; school and student response rates were consistent; and minor differences existed in risk behaviors between modes, the acceptability of collecting data electronically was demonstrated. [ABSTRACT FROM AUTHOR]

Copyright of Al-Bahith Al-Aalami is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose Institutional bibliometric analyses compare as a rule the performance of different institutions. The purpose of this paper is to use a statistical approach which not only allows a comparison of the citation impact of papers from selected institutions, but also a comparison of the citation impact of the papers of these institutions with all other papers published in a particular time frame.Design/methodology/approach The study is based on a randomly selected cluster sample (n=4,327,013 articles and reviews from 2000 to 2004), which is drawn from a bibliometric in-house database including Web of Science data. Regression models are used to analyze citation impact scores. Subsequent to the models, average predictions at specific interesting values are calculated to analyze which factors could have an effect on the impact scores-the journal impact factor (JIF), of the journals which published the papers and the number of affiliations given in a paper.Findings Three anonymous German institutions are compared with one another and with the set of all other papers in the time frame. As an indicator of institutional performance, fractionally counted PPtop 50% on the level of individual papers are used. This indicator is a normalized impact score whereas each paper is fractionally assigned to the 50 percent most frequently cited papers within its subject category and publication year. The results show that the JIF and the number of affiliations have a statistically significant effect on the institutional performance.Originality/value Fractional regression models are introduced to analyze the fractionally counted PPtop 50% on the level of individual papers. [ABSTRACT FROM AUTHOR]

Background: Vitality and happiness are one of the important components of social welfare affecting individuals' efficiency and quality of life. Lifestyle variations, especially the type of health-oriented lifestyle, are important determinants of social happiness. According to this, the aim of this study was to investigate the relationship between lifestyle and social happiness of women over 18 years in Sanandaj in 2017-2018. Methods: The method of this study was descriptive type of correlational. The statistical population consisted of women over 18 years in Sanandaj. The sample size was 380 based on the Cochran formula and were selected by multi-stage cluster sampling. The research's tool was a combination of Walker's Standard Questionnaire and researcher-made questionnaire. Results: The Pearson correlation and regression analysis were used to analyze the data by SPSS 22 software. Descriptive results indicated that dimensions of healthy life-style (spiritual growth and Self-actualization, responsibility about health, interpersonal relationships and nutrition, exercise and physical activity, and stress management) caused 37% of changes in the happiness among women of Sanandaj. In addition, the effect of interpersonal relationships has been more than the others. Conclusion: Based on findings, it can be concluded that choosing a healthy lifestyle will lead to increase happiness among women and in this field, the role of interpersonal relationship as one of lifestyle indicators for happiness is more determinative and important so it would be worthy of attention to the cultural, medical and even educational centers of Iran. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries for autonomous driving, which can be used for the simulated verification of different ADAS functions. Firstly, the operational design domain (ODD) of a functional scenario is selected, and the weight values of the ODD elements are calculated. Then, a combination test algorithm based on parameter weights is improved to generate virtually simulated autonomous driving test cases for the ODD elements, which can effectively reduce the number of generated test cases compared with the traditional combination test algorithm. Then, the traffic participant elements in each test case are sampled and clustered so as to obtain hazard-specific scenarios. Then, the values of the subelements under the traffic participant element in each test case are sampled and clustered to obtain hazard-specific scenarios. Finally, the specific scenarios are applied to the automatic emergency braking (AEB) system on the model-in-the-loop (MIL) testbed to verify the effectiveness of this scenario generation method. [ABSTRACT FROM AUTHOR]

Background: Community health worker programmes have the potential to contribute critically towards universal health coverage. However, CHWs globally have often continued to operate on the periphery of the health care system, viewed as a non-essential cadre. This results in a workforce that often remains disempowered and under-supported. This paper presents evidence from a study conducted in a rural part of South Africa, to better understand issues of CHW prioritisation, integration, and empowerment. Methods: We applied an analytical lens based on empowerment theory and conducted a secondary analysis of qualitative data emerging from a sub-study of a cRCT evaluating the effectiveness of supportive supervision for CHWs within a large-scale national CHW programme. The cRCT was conducted between 2017 and 2022, and 39 CHWs were included in the study. Results: We organised our findings across the four domains of structural empowerment; information, resources, support, and opportunity, and mapped these domains against the domains of psychological empowerment. Our findings show how CHWs are still working in the periphery of the healthcare system. Without sufficient prioritisation, high level-support from national and district governments, and sufficient investments in programmatic domains—such as training, equipment, and supportive supervision—it is likely that the CHW cadre will continue to be seen as informal health care workers. Conclusions: CHW empowerment could be a lever to potentially transform the current health system towards universal coverage; however, this process can only happen with sufficient high-level prioritization and investment. [ABSTRACT FROM AUTHOR]

Selecting emergency suppliers from a wide range of candidates based on their performance under each criterion can be regarded as a multi-criterion decision making (MCDM) problem. Existing MCDM models to solve the emergency supplier selection problem ignored situations where large-scale suppliers exist, the influence of criteria weights on the robustness of ranking results, and the influence of psychology of regret aversion and disappointment aversion on decision results. To make up for these deficiencies, this paper proposes an MCDM model to solve emergency supplier selection problem with large-scale alternatives. Firstly, to avoid the influence of criteria weights on ranking of alternatives, the Robustness, Correlation, and Standard Deviation (ROCOSD) method is introduced to determine objective weights of criteria based on three objectives. Secondly, the τ-balanced clustering method is applied to cluster large-scale alternatives into balanced clusters. Next, considering the psychology of regret aversion and disappointment aversion of decision makers, a two-stage method is proposed to rank alternatives, which identifies the optimal alternative within each cluster and forms a new cluster consisting of these optimal alternatives in the first stage, and selects the optimal alternative from the new-formed cluster in the second stage. A numerical case is given to validate the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes two classes of robust ratio type estimators of finite population mean and two classes of robust ratio type estimators of finite population variance using a single auxiliary variable under the adaptive cluster sampling design. Seven robust ratio type estimators have been developed from each class. The generalized expressions of bias and mean square error for each class have been derived up to the first order of approximation. The exact expressions of bias and MSE for all the developed estimators have been presented. Using simulation studies conducted in R programming, the high efficiency of all the developed estimators over similar existing estimators in adaptive cluster sampling has been demonstrated. [ABSTRACT FROM AUTHOR]

Purpose: The paper identifies the influence of socio-economic factors and livelihood training in stimulating micro-entrepreneurship among women self-help group (SHG) members. Design/methodology/approach: The study is based on a sample of 416 women SHG members drawn from all the four districts of Sikkim using cluster sampling procedure. A multivariate binary logistic model is used to find the impact of socio-economic factors, and a Poisson regression has been used to find the impact of training on fostering micro-entrepreneurship. The result is validated using a propensity score matching approach which corrects for the potential self-selection bias in the sample. Subsequently, a covariate adjustment estimator verifies the robustness of the approach. Findings: The study finds that "size of landownership", "amount of loan borrowed", "member's age", "number of earning and dependent members", "number of years of SHG enrolment" as well as the "district to which the member belongs to" have a statistically significant influence on the graduation of SHG members to micro-entrepreneurs. Furthermore, it is found that members attending the livelihood training programmes had a significantly higher number of microenterprises. Originality/value: The study differentiates itself by providing empirical evidence on how socio-economic factors and livelihood training stimulate micro-entrepreneurship among SHG women of Sikkim, which has so far remained unexplored. Moreover, advanced econometric method has been used to eliminate the possible self-selection bias involved with training participation and thereby provides reliable and robust results. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0070 [ABSTRACT FROM AUTHOR]

Federated learning has gained significant attention due to its groundbreaking ability to enable distributed learning while maintaining privacy constraints. However, as a consequence of data heterogeneity among decentralized devices, it inherently experiences significant learning degradation and slow convergence speed. Therefore, it is natural to employ the concept of clustering homogeneous clients into the same group, allowing only the model weights within each group to be aggregated. While most existing clustered federated learning methods employ either model gradients or inference outputs as metrics for client partitioning to group similar devices together, heterogeneity may still exist within each cluster. Moreover, there is a scarcity of research exploring the underlying reasons for determining the appropriate timing for clustering, resulting in the common practice of assigning each client to its own individual cluster, particularly in the context of highly non-independent and identically distributed (Non-IID) data. In this paper, we introduce a two-stage decoupling federated learning algorithm with adaptive personalization layers named FedTSDP, where client clustering is performed twice according to inference outputs and model weights, respectively. Hopkins amended sampling is adopted to determine the appropriate timing for clustering and the sampling weight of public unlabeled data. In addition, a simple yet effective approach is developed to adaptively adjust the personalization layers based on varying degrees of data skew. Experimental results show that our proposed method has reliable performance on both IID and non-IID scenarios. [ABSTRACT FROM AUTHOR]

The objective of this paper is to highlight the role that perceived cost, computer self-efficacy and the technology acceptance model (TAM) constructs have in e-training adoption in the Nigerian civil service. With the use of the SmartPLS 2.0 M3 software, a framework that included perceived cost, computer self-efficacy and TAM constructs (perceived usefulness (PU) and perceived ease of use (PEOU)) was tested on 450 heads of departments. Scales on perceived cost, computer self-efficacy, PU and PEOU developed by previous studies were modified accordingly and used. This paper found perceived cost to have a significant effect on e-training adoption. Computer self-efficacy was statistically insignificant through PEOU. In addition, PEOU had an indirect effect through PU. Therefore, only PU of the TAM constructs indicated strong predictive strength in e-training adoption. This paper showed that with e-training adoption, facilities such as computers can be put in place, which can improve the outlook of the civil service. In addition, the cost that is usually associated with traditional training can be reduced, increasing the opportunity to invest in other aspects of the civil service which can help in adding to the overall performance. Relationships were examined in this paper, which were shown to be favourable to e-training adoption in the Nigerian civil service. [ABSTRACT FROM PUBLISHER]

Background: Indigenous Maya women in the rural highlands of Guatemala have traditionally faced constraints to decision-making and participation in community affairs. Anecdotal experiences from previous Curamericas Global projects in Guatemala and Liberia have suggested that interventions using the CBIO+ Approach (which consists of implementing together the Census-Based, Impact-Oriented Approach, the Care Group Approach, and Community Birthing Centers), can be empowering and can facilitate improvements in maternal and child health. This paper, the eighth in a series of 10 papers examining the effectiveness of CBIO+ in improving the health and well-being of mothers and children in an isolated mountainous rural area of the Department of Huehuetenango, explores changes in women's empowerment among mothers of young children associated with the Curamericas/Guatemala Maternal and Child Health Project, 2011–2015. Methods: Knowledge, practice, and coverage (KPC) surveys and focus group discussions (FGDs) were used to explore six indicators of women's empowerment focusing on participation in health-related decision-making and participation in community meetings. KPC surveys were conducted at baseline (January 2012) and endline (June 2015) using standard stratified cluster sampling. Seventeen FGDs (9 with women, 3 with men, 2 with mothers-in-law, and 3 with health committees), approximately 120 people in all, were conducted to obtain opinions about changes in empowerment and to identify and assess qualitative factors that facilitate and/or impede women's empowerment. Results: The KPC surveys revealed statistically significant increases in women's active participation in community meetings. Women also reported statistically significant increases in rates of participation in health-related decision-making. Further, the findings show a dose-response effect for two of the six empowerment indicators. The qualitative findings from FGDs show that the Project accelerated progress in increasing women's empowerment though women still face major barriers in accessing needed health care services for themselves and their children. Conclusion: The Project achieved some notable improvements in women's decision-making autonomy and participation in community activities. These improvements often translated into making decisions to practice recommended health behaviors. Traditional cultural norms and the barriers to accessing needed health services are not easily overcome, even when empowerment strategies are effective. [ABSTRACT FROM AUTHOR]

The health of young people is crucial for the future and development of a nation. It is the collective responsibility and imperative mission of society to ensure the holistic well-being, both physically and mentally, of young individuals. Therefore, it is essential to thoroughly comprehend the factors that influence their health in order to expedite the exploration of effective solutions. The objective of this study is to comprehend the mechanisms that underlie the correlation between physical exercise behavior and psychological resilience among teenagers, while also examining the mediating role played by social sensitivity and need to belong. So put forward the hypothesis: (1) physical exercise behavior can positively predict the psychological resilience. (2) Social sensitivity and need to belong plays a mediating role between physical exercise behavior and psychological resilience. (3) Social sensitivity and need to belong plays a chain mediating role between physical exercise behavior and psychological resilience. Using the cluster sampling method, a total of 1106 students (with an average age of 15.7 and a standard deviation of 0.598) who met the requirements were surveyed from Shandong Province in China. Standard scales were utilized to assess Physical Exercise Behavior, Psychological Resilience, Social Sensitivity, and Need to Belong. For data analysis, Pearson's correlation analysis and bias-corrected percentile Bootstrap method were sequentially conducted. (1) The present study did not find any significant methodological bias, and the observed correlations between physical exercise behavior, psychological resilience, social sensitivity, and need to belong were all statistically significant; (2) Based on the self-determination theory, this study elucidates the relationship between physical exercise behavior and psychological resilience among teenagers. The findings indicate that physical exercise behavior positively predicts the need to belong and psychological resilience, while negatively predicting social sensitivity. Similarly, social sensitivity negatively predicts the need to belong and psychological resilience. Moreover, the need to belong directly and positively predicts psychological resilience. Importantly, all hypotheses proposed in this paper were empirically supported. (3) The indirect effect of the path mediated by social sensitivity is 0.009, while the indirect effect of the path mediated by need to belong is 0.033. Additionally, the combined indirect effect of both social sensitivity and need to belong as mediating variables is 0.014. (4) The cumulative sum of all these indirect effects amounts to 0.056. Based on the self-determination theory, we propose a chain mediation model, specially, physical exercise behavior can significantly positively predict psychological resilience, among which, social sensitivity and need to belong play a significant mediating role between Physical exercise behavior and psychological resilience. In addition, the adoption of good physical exercise behavior can enhance the psychological resilience of adolescents by diminishing social sensitivity and augmenting the need to belong. [ABSTRACT FROM AUTHOR]

This paper aims to estimate the prevalence of client-perpetrated violence against female sex workers (FSWs) in Bogotá and to understand what structural and environmental factors are associated with such victimization. The project used secondary data from interviews with 2,684 FSWs. Multivariable binary logistic regression was used to test for associations with client-perpetrated violence. Findings reveal that factors such as experiencing police harassment and social stigma were positively associated with client-perpetrated violence. Situational factors such as providing services in motels, hotels, on the street, and in cars were also associated with increased odds of becoming a victim of violence. [ABSTRACT FROM AUTHOR]

Unsupervised person re-identification (re-ID) aims to identify the same person in unsupervised settings, which is a realistic and challenging problem due to getting rid of the dependence on annotations. Existing pseudo-label-based methods have been proved to be effective by discriminative representation learning and high-quality pseudo labels. However, there are some undesirable similarity structures in images affected by different states (e.g., backgrounds, occlusions, or other target confusions) which may generate noisy labels and lead to model degradation. To tackle the above issues, this paper analyzes the key factors for unsupervised re-ID performance from two perspectives: network structure and loss function. Specifically, we propose a multi-confidence contrastive learning with feature refinement (MCFR) model which can enhance the feature discriminative ability and meanwhile alleviate the impact of noisy data. For network architecture, a feature refined block is embedded into a multi-branch network, constructing FR-net. For loss function, a multi-confidence contrastive loss (MCCL) based on similarity and confidence relationship is developed. MCCL can flexibly update the list of hard negative samples in clusters and outliers, promoting the model by learning from confident samples. Extensive experiments including visualizations and ablation studies validate the effectiveness of each component in the MCFR model. Additionally, compared with the state-of-the-art unsupervised re-ID methods, our method achieves considerable performance on three benchmark datasets. [ABSTRACT FROM AUTHOR]

The complexity of the data type and distribution leads to the increase in uncertainty in the relationship between samples, which brings challenges to effectively mining the potential cluster structure of data. Ensemble clustering aims to obtain a unified cluster division by fusing multiple different base clustering results. This paper proposes a three-way ensemble clustering algorithm based on sample's perturbation theory to solve the problem of inaccurate decision making caused by inaccurate information or insufficient data. The algorithm first combines the natural nearest neighbor algorithm to generate two sets of perturbed data sets, randomly extracts the feature subsets of the samples, and uses the traditional clustering algorithm to obtain different base clusters. The sample's stability is obtained by using the co-association matrix and determinacy function, and then the samples can be divided into a stable region and unstable region according to a threshold for the sample's stability. The stable region consists of high-stability samples and is divided into the core region of each cluster using the K-means algorithm. The unstable region consists of low-stability samples and is assigned to the fringe regions of each cluster. Therefore, a three-way clustering result is formed. The experimental results show that the proposed algorithm in this paper can obtain better clustering results compared with other clustering ensemble algorithms on the UCI Machine Learning Repository data set, and can effectively reveal the clustering structure. [ABSTRACT FROM AUTHOR]

In this paper, we suggest using a partial randomized response model using Poisson distribution to efficiently estimate a rare sensitive attribute by applying the probability proportional to size (PPS) sampling method when the population is composed of several different and sensitive clusters. We have obtained estimators for a rare and sensitive attribute and their variances and variance estimates by applying PPS sampling and two-stage equal probability sampling. We compare the efficiency between the estimators of the rare sensitive attribute, one obtained via PPS sampling with replacement and the other obtained using the two-stage equal probability sampling with replacement. As a result, it is confirmed that the estimate obtained via the PPS sampling with replacement is more efficient than the estimate provided by the two-stage equal probability sampling with replacement when the cluster sizes are different. [ABSTRACT FROM AUTHOR]

The purpose of this study was to collect preliminary data for the design of real-time and integrated performance assessments in science practicum at two public universities and two private universities in Eastern Indonesia. The case study design and quantitative and qualitative approaches were adopted in this study. Cluster random sampling technique was used to select four universities, 376 participants respectively from university students and lecturers, four vice deans, four heads of study programs, four heads of laboratories, and four teaching assistants. Data were gathered through questionnaires, in-depth interviews, and observations. The chi-square test was used to analyze the data descriptively. Findings indicated that a performance assessment was not carried out since standard measurement instruments that provided real-time and integrated feedback had not been developed. There was no significant difference (p > 0.05) between public and private universities on the science practicum assessment, implying that both public and private universities still used paper-based practicum assessments. There was also no significant difference between the responses of university students and lecturers on practicum performance assessments (p > 0.05). University students' experience in assessing science practicums was similar to those of lecturers', which suggests that practicum of performance assessments was not real-time and integrated with feedback. This study recommends developing a real-time and integrated performance assessment with automated feedback on the science practicum, in order to provide continuous improvement of students and monitoring their learning progress. [ABSTRACT FROM AUTHOR]

This paper examines the dynamics of learning and how they relate to the optimal teaching strategies for learners. The authors aim to enhance learners' information processing abilities by highlighting the importance of considering different learning theories in the classroom. These considerations are based on the qualitative behaviour of learners' conscious awareness, cognitive and metacognitive engagement. A multi-stage cluster sampling procedure was employed to select a sample of 840 Grade 11 learners from 20 schools in the education district. A questionnaire was used to collect data, and statistical tests were conducted to validate and analyse the data. The study's results suggest that it is crucial for teachers to use a variety of learning theories and to consider variables that facilitate effective information processing by learners. Understanding diverse learning theories and their interplay positively influence the cognitive development of learners. The study's findings, which include SEM and HLM analyses and implications from teachers' application of juxtaposed theories, suggest that inefficiencies may exist in certain teaching approaches and in individual learners' information processing. Teachers who understand and apply the simultaneous impact of juxtaposed theories of learning can enable learners to assimilate or accommodate incoming information into their cognitive schema, leading to deeper and more meaningful understanding. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economics & Administrative Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: This study aimed to explore and confirm the factor structure and item distribution of the Chinese version of Self‐care Ability Scale for the Elderly among older Chinese people. Methods: A cluster random sampling method was used to collect 2856 older people from five different cities of China from July 2018 to July 2019. A questionnaire comprised of socio‐demographic information and the Chinese version of the Self‐care Ability Scale for the Elderly was administered, and SPSS 21.0 and Mplus 7.4 were used for analyses. Results: Participants were aged 60 to 92 years, with a mean age of 71.52 (SD = 7.68) years. In the Exploratory Factor Analysis, the three‐factor structure and item distribution of the Chinese version of the Self‐care Ability Scale for the Elderly were verified to be better than other options. The factor loadings varied from 0.428 to 0.800, and the communality values ranged from 0.426 to 0.792. The modified model showed a good fit in the Confirmatory Factor Analysis. Conclusion: The Chinese version of the Self‐care Ability Scale for the Elderly has a clear three‐factor structure and a good item distribution. It serves as a convenient and accurate assessment tool to assess the self‐care ability of older Chinese people. Summary statement: What is already known about this topic? Assessing self‐care ability plays a significant role in the care of older people.The Chinese version of the Self‐care Ability Scale for the Elderly is often used to assess the self‐care ability of older people in China but whilst it has good reliability and content validity, its factor structure and item distribution are not clearly explained in recent literature.Solid evidence on the factor analysis of the Chinese version of the Self‐care Ability Scale for the Elderly is needed to maintain a high standard of health care assessment for the older Chinese people. What this paper adds? We confirmed that the Chinese version of the Self‐care Ability Scale for the Elderly has a clear three‐factor structure and item distribution.The Chinese version of the Self‐care Ability Scale for the Elderly can now be used as the study confirmed its validity and reliability. The implications of this paper: The instrument can be effective in older Chinese people to identify their self‐care support needs and thereby to enable provision of opportunities to implement appropriate nursing care.Health care professionals can use this instrument to assess the alterations in self‐care ability of older Chinese people after particular interventions. [ABSTRACT FROM AUTHOR]

Publications in peer-reviewed journals are often looked upon as tenets on which future scientific thought is built. Published information is not always flawless and errors in published research should be expediently reported, preferably by a peer-review process. We review a recent publication by Gopalaswamy et al. (10.1111/2041-210X.12351) that challenges the use of "double sampling" in largescale animal surveys. Double sampling is often resorted to as an established economical and practical approach for large-scale surveys since it calibrates abundance indices against absolute abundance, thereby potentially addressing the statistical shortfalls of indices. Empirical data used by Gopalaswamy et al. (10.1111/2041-210X.12351) to test their theoretical model, relate to tiger sign and tiger abundance referred to as an Index-Calibration experiment (IC-Karanth). These data on tiger abundance and signs should be paired in time and space to qualify as a calibration experiment for double sampling, but original data of IC-Karanth show lags of (up to) several years. Further, data points used in the paper do not match the original sources. We show that by use of inappropriate and incorrect data collected through a faulty experimental design, poor parameterization of their theoretical model, and selectively picked estimates from literature on detection probability, the inferences of this paper are highly questionable. We highlight how the results of Gopalaswamy et al. were further distorted in popular media. If left unaddressed, the paper of Gopalaswamy et al. could have serious implications on statistical design of large-scale animal surveys by propagating unreliable inferences. [ABSTRACT FROM AUTHOR]

Background: This paper describes the methodological considerations of developing an urban Health and Demographic Surveillance System (HDSS), in the Sleman District of Yogyakarta, Indonesia. Methods: 1) The Sleman District was selected because it is mostly an urban area. 2) The minimum sample size was calculated to measure infant mortality as the key variable and resulted in a sample of 4942 households. A two-stage cluster sampling procedure with probability proportionate to size was applied; first, 216 Censuses Blocks (CBs) were selected, and second, 25 households in each CB were selected. 3) A baseline survey was started in 2015, and collected data on demographic and economic characteristics and verbal autopsy (VA); the 2nd cycle collected updated demographic data, VA, type of morbidity (communicable and non-communicable diseases, disability and injury) and health access. 4) The data were collected at a home visit through a Computer-Assisted Personal Interview (CAPI) on a tablet device, and the data were transferred to the server through the Internet. 5) The quality control consisted of spot-checks of 5% of interviews to control for adherence to the protocol, re-checks to ensure the validity of the interview, and computer-based data cleaning. 6) A utilization system was designed for policy-makers (government) and researchers. Results: In total, 5147 households participated in the baseline assessment in 2015, and 4996 households participated in the second cycle in 2016 (97.0% response rate). Conclusions: Development of an urban HDSS is possible and is beneficial in providing data complementary to the existing demographic and health information system at local, national and global levels. [ABSTRACT FROM AUTHOR]

Background: This paper presents the baseline characteristics and their moderators in the Healthy Learning Mind (HLM)– school-based cluster-randomized controlled trial. Objectives: The paper evaluates the state of various measures of well-being, their moderators and how these results compare to national and global norms/population studies. Methods: Data were collected from all participants prior to the intervention and further analyzed by gender, grade and perceived socioeconomic status, including standardized measures for resilience, depressive symptoms and socioemotional functioning; health-related quality of life, dispositional mindfulness, satisfaction with life, compassion/self-kindness, self-rated health and morning tiredness. Results: Participating 2793 students (1425 girls, 1368 boys), ages 12 to 15 years, filled in the questionnaires. The outcomes were in line with previous research, demonstrating gender differentiation and lower wellbeing among older children and adolescents. Conclusions: All outcomes were associated with perceived socioeconomic status, suggesting that perceived low socioeconomic status should be addressed as a serious risk factor and included as a moderator in similar trials. [ABSTRACT FROM AUTHOR]

In this paper, the authors formulated the problem of finding optimum values of cluster size and sampling units for multivariate cluster sampling surveys. In multivariate case, the use of individual optimum allocations is not advisable. For such cases, any suitable criterion is required to decide the acceptable cluster size and sampling unit which may be optimum for all characteristics under study. Moreover, the use of Gamma cost function is introduced for the study of multivariate cluster sampling surveys. The problem is formulated as an All Integer Nonlinear Programing Problem (AINLPP). In this paper, the solution procedures are suggested for solving the formulated AINLPP. The numerical examples show the practical applications of the solution procedures for multivariate cluster sampling design. [ABSTRACT FROM AUTHOR]

Conversational recommender systems elicit user preference via conversational interactions. By introducing conversational key-terms, existing conversational recommenders can effectively reduce the need for extensive exploration required by a traditional interactive recommender. However, there are still limitations of existing conversational recommender approaches eliciting user preference via key-terms. First, the key-term data of the items needs to be carefully labeled, which requires a lot of human efforts. Second, the number of the human labeled key-terms is limited and the granularity of the key-terms is fixed, while the elicited user preference is usually from coarse-grained to fine-grained during the conversations. In this paper, we propose a clustering of conversational bandits algorithm. To avoid the human labeling efforts and automatically learn the key-terms with the proper granularity, we online cluster the items and generate meaningful key-terms for the items during the conversational interactions. Our algorithm is general and can also be used in the user clustering when the feedback from multiple users is available, which further leads to more accurate learning and generations of conversational key-terms. Moreover, to learn the user clustering structure more efficiently in more complex user clustering structure, we further propose a simple yet effective soft user clustering module to perform exploration on user clustering via sampling the posterior user representations. We analyze the regret bound of our learning algorithm. In the empirical evaluations, without using any human labeled key-terms, our algorithm effectively generates meaningful coarse-to-fine grained key-terms and performs as well as or better than the state-of-the-art baseline. [ABSTRACT FROM AUTHOR]

Because the number of clustering cores needs to be set before implementing the K-means algorithm, this type of algorithm often fails in applications with increasing data and changing distribution characteristics. This paper proposes an evolutionary algorithm DCC, which can dynamically adjust the number of clustering cores with data change. DCC algorithm uses the Gaussian function as the activation function of each core. Each clustering core can adjust its center vector and coverage based on the response to the input data and its memory state to better fit the sample clusters in the space. The DCC algorithm model can evolve from 0. After each new sample is added, the winning dynamic core can be adjusted or split by competitive learning, so that the number of clustering cores of the algorithm always maintains a better adaptation relationship with the existing data. Furthermore, because its clustering core can split, it can subdivide the densely distributed data clusters. Finally, detailed experimental results show that the evolutionary clustering algorithm DCC based on the dynamic core method has excellent clustering performance and strong robustness. [ABSTRACT FROM AUTHOR]

The available surface defect detection methods for disposable wooden spoons still involve screening with the naked eye. This detection method is not only inefficient but also accompanied by problems such as false detection and missed detection. Therefore, this paper proposes a detection method based on an improved YOLOv5 network model (YOLOv5-TSPP). This method uses the K-Means ++ algorithm to cluster the target samples in the data set to obtain anchor frames that are more in line with different target scales. The Coordinate Attention module is added to the backbone network of the YOLOv5 network model to improve the feature extraction ability of the model. A new SPP module is added to the backbone network to increase the important features in the receptive field extraction network to improve the detection accuracy of small targets. The experimental results show: The YOLOv5-TSPP algorithm has better detection performance and the mAP of defect detection reaches 80.3%, which is 9.2% higher than that of the YOLOv5 algorithm. Among them, the detection accuracy of black knot defect reached 98.6%, the detection accuracy of back crack defect reached 92.1%, and the detection accuracy of mineral line defect reached 92.3%. [ABSTRACT FROM AUTHOR]

Screen time and the use of social networks is the most frequent form of leisure time occupation and socializing for adolescents. The present study is aimed at understanding and characterizing, from an ecological perspective, what distinguishes healthy and less healthy or even dependent use of social media in young people and the influence on adolescents' well-being. This paper is based on the Health Behaviour in School-aged Children (HBSC) from 2022, a survey carried out every 4 years, in collaboration with the World Health Organisation (WHO), following an international protocol. A total of 7643 students from the 6th, 8th, 10th, and 12th school grades responded, of which 53.9% were female, with an average age of 15.05 (SD = 2.36). The sample is representative of the school grades under study. The results allow us to study and identify similarities and differences between three groups related to the level of healthiness in the use of social networks and its relations to well-being from an ecological perspective. What distinguishes adolescents with less healthy use of social networks is that they are more often female, older, have more self-injurious behaviour, higher alcohol consumption, and a worse relationship with teachers. The adolescents with the highest level of dependence on social networks are those who have a higher perception of lack of safety at school and in their area of residence, as well as a higher use of screen time as a leisure activity. The well-being of adolescents using social media in a healthy way is explained by fewer psychological symptoms, better stress management strategies, better body awareness, more physical activity, less time online with friends, and better relationships with family and teachers. Technologies and social networks are important for the well-being of adolescents; it is essential to promote a healthy, critical and balanced use with other "screen-free" activities and to promote socio-emotional skills, a lack of which seems to be one of the biggest risk factors associated with the healthy use of technologies. [ABSTRACT FROM AUTHOR]

Background: Recently known as the genito-pelvic pain/penetration disorder (GPPPD), Dyspareunia is considered a negative factor affecting a couple's sexual health. This paper analyzes pain in Dyspareunia cases and determines protective factors causing lower levels of sexual distress among patients. Methods: In a population-based cross-sectional study conducted in 2017, the cluster quota sampling technique was adopted to randomly select 590 Iranian married women aged 18–70 years from 30 health centers. The research tools included demographic data, a sexual distress scale, and Binik's GPPPD questionnaire. Results: In this study, the prevalence of self-report Dyspareunia, confirmed moderate Dyspareunia, and confirmed severe Dyspareunia (based on Binik's proposed criteria) were 33 %, 25.8 %, and 10.5 %, respectively. Interestingly, 32 (34 %) out of 94 women who experienced severe pain based on Binik's criteria reported no sexual distress. Compared to women with distress, they also had more positive body images, higher self-confidence, higher levels of sexual satisfaction, and more intimacy in their relationships (P = 0.000). In contrast, 8.5 % of the participants reported significant sexual distress even without confirmed Dyspareunia. Conclusions: Improving intrapersonal characteristics such as self-confidence and body image as well as interpersonal factors such as sexual satisfaction and intimacy with a spouse can effectively treat Dyspareunia by alleviating sexual distress. The partner's role in female pain and distress management would be more critical than previously thought. Plain English summary: Dyspareunia is a condition that can negatively affect sexual health among individuals and couples. This paper addresses the pattern of sexual pain as well as some interpersonal and intrapersonal factors that may lessen sexual pain by mitigating sexual distress. This population-based cross-sectional study was conducted on 590 randomly selected Iranian married women aged 18–70 years. According to the research results, the prevalence of self-report sexual pain was 33 %. However, based on strict Binik's criteria and sexual distress, the prevalence of severe Dyspareunia decreased to 10.5 %. The most common location, time, and type of pain were reported to be in the vaginal entrance at the beginning of intercourse with irritation. Interestingly, a substantial number of women reported no sexual distress, despite having severe Dyspareunia. Compared to patients with distress, they experienced higher levels of sexual satisfaction, more positive body images, higher levels of self-confidence, and more intimacy in their relationships (P =.000). In addition to the routine management of sexual pain, clinicians should consider these protective factors that can lead to better pain tolerance and less sexual distress among patients. The research findings emphasized the importance of attendance and collaboration of spouses in the treatment process. At the same time, observing the sexual distress of women with no sexual dysfunctions would clarify that their own perception of sexual difficulty per se is an important factor. In other words, "sexual dysfunction" and "sexual problems" are both significant because defining sexual problems is subjective and depends on a woman and her partner's values, desires, and sexual knowledge. [ABSTRACT FROM AUTHOR]

This paper deals with making inference on parameters of a two‐level model matching the design hierarchy of a two‐stage sample. In a pioneering paper, Scott and Smith (Journal of the American Statistical Association, 1969, 64, 830–840) proposed a Bayesian model based or prediction approach to estimating a finite population mean under two‐stage cluster sampling. We provide a brief account of their pioneering work. We review two methods for the analysis of two‐level models based on matching two‐stage samples. Those methods are based on pseudo maximum likelihood and pseudo composite likelihood taking account of design weights. We then propose a new method for analysis of two‐level models based on a normal approximation to the estimated cluster effects and taking account of design weights. This method does not require cluster sizes to be constants or unrelated to cluster effects. We evaluate the relative performance of the three methods in a simulation study. Finally, we apply the methods to real data obtained from 2011 Nepal Demographic and Health Survey (NDHS). [ABSTRACT FROM AUTHOR]