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The relations between shyness and internalizing problems have been mainly explored at the individual level, with little known about its dynamics at the group level. This study aims to examine the mediating effect of individual-level sport engagement and the moderating effect of class-level sport participation in the relations between shyness and internalizing problems. The participants were 951 children attending primary and middle school from grade 3 to grade 7 (Mage = 11 years, 509 boys) in urban areas of China. Cross-sectional data were collected using self-report assessments. Multi-level analysis indicated that (1) shyness was positively associated with internalizing problems; (2) sport engagement partially mediated the relations between shyness and internalizing problems; and (3) class sport participation was a cross-level moderator in the mediating relations between shyness, sport engagement, and internalizing problems. Shy children in classes with a higher level of sport participation tend to have less sport engagement and more internalizing problems than those in classes with a lower level of sport participation. These findings illuminate implications from a multi-level perspective for shy children's adjustment in a Chinese context. The well-being of shy children could be improved by intervening in sport activity, addressing both individual engagement and group dynamics, such as class participation. [ABSTRACT FROM AUTHOR]

The sustainability of the salmon farming industry is being challenged by increased mortality rates. Scotland’s open-source salmon production data provides the possibility of developing an industry-wide mortality monitoring model, valuable for identifying and addressing unexpected increases in mortality without needing data sharing agreements across different companies. This study aimed to utilize these data to develop a hierarchical dynamic linear model (DLM) for monitoring monthly mortality of maricultured Atlantic salmon in Scotland. We evaluated whether considering the hierarchical structure present in the data (country, region, and site) would improve mortality predictions when compared to the production cycle level DLMs developed in a previous study. Our findings demonstrated that the hierarchical DLM outperformed the production cycle level DLMs, confirming the value of this more complex modelling approach. Nevertheless, the hierarchical model, like the production cycle level DLMs, exhibited some uncertainty in the mortality predictions. When mortality is higher than expected, site level warnings are generated, which can encourage producers and inspectors to further investigate the cause. Between 2015 and 2020, approximately 25% of the production cycles and 50% of the sites encountered at least one warning, with most warnings happening in the summer and autumn months. Additionally, the hierarchical model enabled monitoring mortality at multiple levels. This information is useful for various stakeholders as part of a monitoring system, offering insights into mortality trends at national, regional, and sites levels that may benefit from strategic resource management. Recommendations for model improvements include utilizing shorter data aggregation periods, such as weekly, which are not currently available as open-source data.

Abstract Background In Norrtälje municipality, within Region Stockholm, there is a joint integrated care organisation providing health and social care, which may have facilitated a more coordinated response to the covid-19 pandemic compared to the otherwise decentralised Swedish system. This study compares the risk of covid-19 mortality among persons 70 years and older, in the municipalities of Stockholm, Södertälje, and Norrtälje, while considering area and individual risk factors. Methods A population-based study using linked register data to examine covid-19 mortality among those 70 + years (N = 127,575) within the municipalities of interest between the periods March-August 2020 and September 2020-February 2021. The effect of individual and area level variables on covid-19 mortality among inhabitants in 68 catchment areas were examined using multi-level logistic models. Results Individual factors associated with covid-19 mortality were sex, older age, primary education, country of birth and poorer health as indicated by the Charlson Co-morbidity Index. The area-level variables associated were high deprivation (OR: 1.56, CI: 1.18–2.08), population density (OR: 1.14, CI: 1.08–1.21), and usual care. Together, this explained 85.7% of the variation between catchment areas in period 1 and most variation was due to individual risk factors in period 2. Little of the residual variation was attributed to differences between catchment areas. Conclusion Integrated care in Norrtälje may have facilitated a more coordinated response during period 1, compared to municipalities with usual care. In the future, integrated care should be considered as an approach to better protect and meet the care needs of older people during emergency situations.

The relations between shyness and internalizing problems have been mainly explored at the individual level, with little known about its dynamics at the group level. This study aims to examine the mediating effect of individual-level sport engagement and the moderating effect of class-level sport participation in the relations between shyness and internalizing problems. The participants were 951 children attending primary and middle school from grade 3 to grade 7 (Mage = 11 years, 509 boys) in urban areas of China. Cross-sectional data were collected using self-report assessments. Multi-level analysis indicated that (1) shyness was positively associated with internalizing problems; (2) sport engagement partially mediated the relations between shyness and internalizing problems; and (3) class sport participation was a cross-level moderator in the mediating relations between shyness, sport engagement, and internalizing problems. Shy children in classes with a higher level of sport participation tend to have less sport engagement and more internalizing problems than those in classes with a lower level of sport participation. These findings illuminate implications from a multi-level perspective for shy children’s adjustment in a Chinese context. The well-being of shy children could be improved by intervening in sport activity, addressing both individual engagement and group dynamics, such as class participation.

Objective To investigate the current situation of reproductive health education among floating women of childbearing age and to explore its influencing factors, to provide reference for promoting the equalization of basic public services for health and family planning and improving the level of health literacy of floating population. Methods In total, 61 086 floating women aged 15 to 49 years in the 2018 national floating population dynamic monitoring survey were selected as the research subjects, a multi-level logistic model was established and considering the fact of inter-regional heterogeneity. Results Floating women of childbearing age accounted for 40.18% of the respondents of the floating population, and the acceptance rate of reproductive health education was 49.39%. The acceptance rate of reproductive health education services in the central and western regions were higher than those in the eastern and northeast regions. The results of multi-level logistic model analysis showed that the acceptance rate of reproductive health education for floating women of childbearing age was aggregated at the community level, and that qualified management of community health education services (OR=1.305, 95%CI: 1.182-1.440) and neighborhood committee (OR=L756, 95%CI: 1.567-1.969) were promoting factors for receiving reproductive health education services. At the individual level, women who were aged 30 to 39 years (OR=1.59& 95%CI: 1.346-1.897), married (OR=1.751, 95%CI: 1.591-1.927), with college eduction (0=2.059, 95%CZ:1.877-2259), enrolled in health insurance (OR-1.386: 95%CZ: 1.267-1.516), employed (OR = 1.242, 95%a:1.171-1317), and had children (1 child: OR = 1.662, 95%C7: 1.514-1.824; more than 2 children: OR=1.715: 95%CI: 1.544-1.905), did not undergo induced abortion (OR=1.207, 95%CI: 1.070-1362), currently pregnant (0R=2.143, 95%C7:1.870-2.455), and self-rated health (0R=1.222, 95%CI: 1.134-1.317) in the past year were more likely to receive reproductive health education. Conclusion Reproductive health education for floating women of childbearing age is related to individual factors and community factors. Reproductive health education services should focus on floating women of childbearing age who are not married, have not given birth to children, and have experienced induced abortion in the past year. [ABSTRACT FROM AUTHOR]

Objective: For computer-aided Chinese medical diagnosis and aiming at the problem of insufficient segmentation, a novel multi-level method based on the multi-scale fusion residual neural network (MF2ResU-Net) model is proposed. Methods: To obtain refined features of retinal blood vessels, three cascade connected U-Net networks are employed. To deal with the problem of difference between the parts of encoder and decoder, in MF2ResU-Net, shortcut connections are used to combine the encoder and decoder layers in the blocks. To refine the feature of segmentation, atrous spatial pyramid pooling (ASPP) is embedded to achieve multi-scale features for the final segmentation networks. Results: The MF2ResU-Net was superior to the existing methods on the criteria of sensitivity (Sen), specificity (Spe), accuracy (ACC), and area under curve (AUC), the values of which are 0.8013 and 0.8102, 0.9842 and 0.9809, 0.9700 and 0.9776, and 0.9797 and 0.9837, respectively for DRIVE and CHASE DB1. The results of experiments demonstrated the effectiveness and robustness of the model in the segmentation of complex curvature and small blood vessels. Conclusion: Based on residual connections and multi-feature fusion, the proposed method can obtain accurate segmentation of retinal blood vessels by refining the segmentation features, which can provide another diagnosis method for computer-aided Chinese medical diagnosis.

This mixed-method study investigated how primary school mathematics teachers in South Africa and Germany utilise educational technology. The perceptions of the principals and teachers regarding the use of educational technology and the obstacles to its integration were contrasted. In addition, the Trends in International Mathematics and Science Study (TIMSS) 2019 data from these countries were used to evaluate the relationship between educational technology and learner accomplishment. The results showed that teachers from both nations employed educational technology as a presentation-, reinforcement-, supplement-, and problem-solving tool, and also used it to stimulate the learning environment, as shown through semi-structured interviews and classroom observations. In addition, obstacles such as a lack of tablets/computers, technical support, and a lack of relevant continuous professional development impeded the incorporation of educational technology in mathematics by these teachers. Additionally, multi-level models revealed that access to a computer and internet connectivity at home correlated positively with German learners' mathematics performances, while no statistically significant relationship was observed in South Africa. The results of this study have policy implications and are discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

Researchers have been increasingly taking advantage of the stochastic actor-oriented modeling framework as a method to analyze the evolution of network ties. Although the framework has proven to be a useful method to model longitudinal network data, it is designed to analyze a sample of one bounded network. For group and team researchers, this can be a significant limitation because such researchers often collect data on more than one team. This paper presents a nontechnical and hands-on introduction for a meta-level technique for stochastic actor-oriented models in RSIENA where researchers can simultaneously analyze network drivers from multiple samples of teams and groups. Moreover, we follow up with a multilevel Bayesian version of the model when it is appropriate. We also provide a framework for researchers to understand what types of research questions and theories could be examined and tested.

Boundary spanner corruption—voluntary collaborative behavior between individuals representing different organizations that violates their organizations' norms—is a serious problem in business-to-business (B2B) marketing relationships. Drawing on insights from the literatures on the dark side of business relationships and deviance in sales and service organizations, the authors identify boundary spanner corruption as a potential dark side complication inherent in close B2B marketing relationships. The same elements that generate benefits in interorganizational relationships, such as those between customer and seller firms, also enable the development of boundary-spanning social cocoons that can foment corrupt activities under certain conditions. A conceptual framework illustrates how trust at the interpersonal, intraorganizational, and interorganizational levels enables corrupt behaviors by allowing deviance-inducing factors stemming from the task environment or from the individual boundary spanner to manifest in boundary spanner corruption. Interpersonal trust between representatives of different organizations, interorganizational trust between these organizations, and intraorganizational agency trust of management in their representatives foster the development of a boundary-spanning social cocoon—a microculture that can inculcate deviant norms leading to corrupt behavior. Boundary spanner corruption imposes direct and opportunity costs on the involved organizations, with the additional burden of latent financial risk associated with potential exposure. The authors substantiate their multi-level framework and propositions with field-based insights from qualitative interviews with senior executives. The multi-level framework of boundary spanner corruption extends beyond extant marketing literature, highlights intriguing directions for future research, and offers new managerial insights. [ABSTRACT FROM AUTHOR]

Forest height is an essential parameter used to derive important information about forest ecosystems, such as forest above-ground biomass. In this article, a forest height estimation approach combining P-band and X-band interferometric synthetic aperture radar (InSAR) was introduced. The forest height was estimated using the difference in the penetration of long- and short-wavelength radars to the forest. That is, the P-band and X-band InSAR data were used to extract the digital terrain model (DTM) and digital surface model (DSM), respectively. For the DTM, an improved time-frequency (TF) analysis method was used to reduce the effect of forest scatterers on the extraction of a pure understory terrain phase based on P-band InSAR. For the DSM, a novel compensation algorithm based on a multi-layer model (MLM) was proposed to remove the penetration bias of the X-band. Compared to the existing method based on the infinitely deep uniform volumes (IDUV) model, the MLM-based method is more in line with the characteristics of forest structure and the scattering mechanism for X-band InSAR. The airborne P-band repeat-pass InSAR and spaceborne X-band (TanDEM-X) single-pass InSAR data were used to verify the proposed method over the study area in the Saihanba Forest Farm in Hebei, China. The results demonstrated that the improved TF method can achieve high-precision DTM extraction based on P-band InSAR data, and the root mean square error (RMSE) was 0.94 m. The proposed MLM-based compensation method of the DSM achieved a smaller error (RMSE: 1.67 m) compared to the IDUV-based method (RMSE: 3.01 m). Under the same DTM extracted by P-band InSAR, the estimation accuracy of forest height based on the MLM method was 86.58% (RMSE: 1.81 m), which was 8.49% higher than that of the IDUV-based method (RMSE: 2.98 m). [ABSTRACT FROM AUTHOR]

Abstract Background HIV/AIDS has transformed into a chronic controllable but not yet curable infectious disease as other chronic diseases to some extent. The additional of so called fourth 90% that included the improved health-related quality of life (HRQoL) for people living with HIV (PLWHIV) required solutions beyond antiretroviral therapy and viral load suppression. This study will explore the role of personality, social economic and prevention strategy effection on HRQoL among people living with HIV/AIDS. Methods A cross-sectional study was conducted among PLWHIV aged more than 16 years old in the 10 municipalities in Yunnan Province, China from October 2019 to May 2020, enrolling total 1997 participants. Individual-level HRQoL data were measured by 12-item Short Form Health Survey (SF-12) and EuroQol Five Dimensions Questionnaire (EQ-5D-5L). We assembled municipal-level data about social economic from Yunnan Statistical Yearbook in 2020 and strategy practice information from the self-evaluation system. We used the principal component analysis to build the social economic and strategy effect on each area respectively and one-way ANOVA was used to perform univariate analysis to identify the predictors with significant differences. Finally we used multi-level model (MLM) to explore the personality, social economic and strategy effects in health-related quality of life among PLWHIV. Results The global score for quality of life measured using EQ-5D-5L had an estimated mean score (standard deviation, SD) of 0.901 ± 0.146. The HRQoL score measured using PCS-12 had an estimated mean score (SD) of 46.62 ± 8.55. The mean MCS-12 score (SD) was estimated to be 47.80 ± 9.71. The area-level predictors explained a proportion of 13.6–17.2% for the between-area variation of the HRQoL scores, regardless of the total HRQoL, physical component and mental component. The impacts of stigma (P

Neighborhood context can change the effect of a socio-demographic attribute on the risk of suicide. Eight hypotheses about the interactions between neighborhood composition, ethnicity, income, and socially disadvantaged propositions are proposed based on social support, social comparison, and social regulation mechanisms. They are tested with a population-based dataset of all adults (1.4 million) who lived in the greater Stockholm area in the 1990s. On one hand, multilevel analysis shows that suicide risk increases with the level of affluence in one's neighborhood, particularly among individuals with low income. This supports the notion that income comparison can have negative consequences. On the other hand, social welfare recipients are less likely to commit suicide when there are other social welfare recipients in the neighborhood. Suicide risk among immigrants deceases with the proportion of co-ethnics in the neighborhood, confirming previous findings on social support and suicide. However, further analyses show that the protection effect of having co-ethnic neighbors is limited to immigrants from countries with low suicide rates. This study shows that administrative data can be used to examine neighborhood effects on rare outcomes. The findings are relevant to the contemporary trends towards rising income inequality and ethnic diversity.

• Study construction service scheduling with fairness on platforms for the first time. • Define fairness, as pricing and solution fairness, and its evaluation indicator. • A multi-level model and an algorithm is proposed to offer fair prices and solution. • The proposed approach outperforms other models and algorithms in terms of fairness. Advancements of electronic platforms in construction industry makes it possible for construction service scheduling (CSS). However, fairness concerns in CSS, such as unfairness in scheduling solutions due to information asymmetry, remains inadequately addressed among existing studies. This study proposes a fairness scheduling model that considers the preferences of participants. According to real engineering practices, a multi-level CSS model with 12 objectives is established by thoroughly considering participants' preferences, aiming to deliver equitable prices and CSS solutions. In solving the model, a clustering operation considering price fairness and inheritance operation considering participants' preferences are designed for the developed evolutionary algorithm. Finally, a simulated case study derived from a real-world construction project demonstrates the effectiveness of the proposed model and algorithm. The results show the superior performance of the proposed model, as it recommends fairer prices and solutions to the CSS problem over the five comparator models. Meanwhile, the proposed algorithm offers more fair solutions with better comprehensive performance than the NSGA3, MOEA/D, MOEA/DD, and RVEA algorithms. This study can be extended to scheduling fairness issues in other fields (e.g., e-commerce, cloud manufacturing, and energy trading), while providing references for researches on service scheduling. [ABSTRACT FROM AUTHOR]

Gender equality in leadership positions is important for sport organizations to achieve economic and social sustainability. Based on a multi-level framework, this study examines spillover effects from economic and social state-level factors in sport organizations' environment on critical masses of women on their boards (in terms of share and numbers) and board gender diversity (reflected by different types of boards). Data of national and regional sport governing bodies in Germany were collected (n = 930), with variables capturing organizational characteristics (e.g., board composition) and economic and social factors at the state level. The results of regression analyses show that women's attainment in tertiary education increases the likelihood of a critical mass of at least 30% women on the board, and a higher divorce rate increases the likelihood of a critical mass of three women on the board. Sport organizations in states with a higher gender wage gap are more likely to have balanced boards, indicating that volunteering might be a substitute to paid work. The findings suggest that the presence of women in sport leadership is affected by economic and social conditions in the organizations' geographical surroundings and that spillover effects occur from the state level to the organizational level. [ABSTRACT FROM AUTHOR]

Background defining features of the COVID-19 pandemic in many countries were the tragic extent to which care home residents were affected and the difficulty in preventing the introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was the transfer of patients from hospitals that were experiencing high levels of nosocomial events. Methods we tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period from March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in case rates following exposure to a hospital discharge using multi-level hierarchical logistic regression and a novel stochastic Hawkes process outbreak model. Findings in regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI: 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated that approximately 1.8% of hospital discharged patients may have been infected. Interpretation there is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients and action taken within care homes following transfer all may have contributed to the mitigation. The precise key transmission routes from the community remain to be quantified. [ABSTRACT FROM AUTHOR]

In the realm of behavioral interventions, a combined approach of yoga and a cognitive-behavioral strategy in the form of introspective meditation (manan-dhyana) may offer benefits as a stress management tool. This pilot study focuses on introspective meditation performed before seeking pleasurable activities, which is a self-reflection about whether to pursue a goal that will bring sensory pleasure in life. A non-probability sample of college students was recruited from a mid-sized Southern University of the United States using a 52-items web-based survey built in Qualtrics. Univariate, bivariate, and multivariate statistics were used to analyze data. Of total 65 students, only 21.5% students reported being engaged in the introspective meditation. The sample constituted predominantly females (75.4%), White (64.6%), and undergraduate students (87.7%). The proportions of anxiety, depression, and moderate/high stress were 50.8%, 40.0%, 86.1% respectively. In the hierarchical regression for initiation, the final model explained nearly 21.1% of variance in initiating introspective meditation among participants (n = 51) who had not been practicing it. With each unit increment in subscales of initiation (i.e., changes in physical environment), the conditional mean for initiating introspective meditation behavior increased by 0.373 units. In the hierarchical regression for sustenance, the final model explained nearly 50.5% of variance in sustaining introspective meditation behavior among participants (n = 51) who had not been practicing it. With each unit increment in subscales of sustenance (i.e., emotional transformation), the conditional mean for sustaining introspective meditation behavior increased by 0.330 units. This study can pave a way for designing interventions for college students to promote introspective meditation directed toward seeking pleasurable activities before engaging in them. This has implications for the reduction of stress as well as a preemptive measure for sexual risk-taking, indulgence in maladaptive behaviors such as smoking, vaping, alcohol, and substance use. [ABSTRACT FROM AUTHOR]

Cognitive aging researchers have been challenged with demonstrating age-related effects above and beyond global slowing ever since Cerella raised this issue in 1990. As the literature has made clear, this has indeed proved to be a difficult task and continues to plague the field. One way that researchers have attempted to test for disproportionate age differences across task conditions is by using Brinley plots, or plotting the mean response latencies of older adults against the mean latencies for younger adults. The simplicity and large proportion of variance accounted for by these models has led to the widespread use of Brinley plots over the years. However, as systematically tested here through eight cases of simulated data, it is clear that the Brinley technique is not well suited to either identify or display the underlying structure of datasets examining age-related differences in attentional control. Some of the problems with conventional Brinley plots can be resolved by using a modified Brinley plot that includes study-specific slopes linking trial types and a no-age-difference reference line. Multilevel models find all of the relevant effects, especially if applied to trial-level data, and have the advantage of incorporating study-level moderators that might account for slope heterogeneity. Ultimately, we encourage fellow cognitive aging researchers to access the code and data for this project on OSF (https://osf.io/zxus8/) and employ the use of multilevel models over Brinley plots. [ABSTRACT FROM AUTHOR]

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Cognitive aging researchers have been challenged with demonstrating age-related effects above and beyond global slowing ever since Cerella raised this issue in 1990. As the literature has made clear, this has indeed proved to be a difficult task and continues to plague the field. One way that researchers have attempted to test for disproportionate age differences across task conditions is by using Brinley plots, or plotting the mean response latencies of older adults against the mean latencies for younger adults. The simplicity and large proportion of variance accounted for by these models has led to the widespread use of Brinley plots over the years. However, as systematically tested here through eight cases of simulated data, it is clear that the Brinley technique is not well suited to either identify or display the underlying structure of datasets examining age-related differences in attentional control. Some of the problems with conventional Brinley plots can be resolved by using a modified Brinley plot that includes study-specific slopes linking trial types and a no-age-difference reference line. Multilevel models find all of the relevant effects, especially if applied to trial-level data, and have the advantage of incorporating study-level moderators that might account for slope heterogeneity. Ultimately, we encourage fellow cognitive aging researchers to access the code and data for this project on OSF (https://osf.io/zxus8/) and employ the use of multilevel models over Brinley plots.

Background: HIV/AIDS has transformed into a chronic controllable but not yet curable infectious disease as other chronic diseases to some extent. The additional of so called fourth 90% that included the improved health-related quality of life (HRQoL) for people living with HIV (PLWHIV) required solutions beyond antiretroviral therapy and viral load suppression. This study will explore the role of personality, social economic and prevention strategy effection on HRQoL among people living with HIV/AIDS. Methods: A cross-sectional study was conducted among PLWHIV aged more than 16 years old in the 10 municipalities in Yunnan Province, China from October 2019 to May 2020, enrolling total 1997 participants. Individual-level HRQoL data were measured by 12-item Short Form Health Survey (SF-12) and EuroQol Five Dimensions Questionnaire (EQ-5D-5L). We assembled municipal-level data about social economic from Yunnan Statistical Yearbook in 2020 and strategy practice information from the self-evaluation system. We used the principal component analysis to build the social economic and strategy effect on each area respectively and one-way ANOVA was used to perform univariate analysis to identify the predictors with significant differences. Finally we used multi-level model (MLM) to explore the personality, social economic and strategy effects in health-related quality of life among PLWHIV. Results: The global score for quality of life measured using EQ-5D-5L had an estimated mean score (standard deviation, SD) of 0.901 ± 0.146. The HRQoL score measured using PCS-12 had an estimated mean score (SD) of 46.62 ± 8.55. The mean MCS-12 score (SD) was estimated to be 47.80 ± 9.71. The area-level predictors explained a proportion of 13.6–17.2% for the between-area variation of the HRQoL scores, regardless of the total HRQoL, physical component and mental component. The impacts of stigma (P < 0.01), social support (P < 0.001), anxiety (P < 0.001), depression (P < 0.05) and social economic status (P < 0.05) on HRQoL at the individual-level were significantly different. The plots visualized the impact of individual-level factors on a respondent's HRQoL was modified by the area-level characteristics. Conclusions: The study identified the possible strategy determinant of individual HRQoL of PLWHIV and also the area effect on HRQoL. Stigma, social support, anxiety, depression and social economic status were the individual-level determinants on HRQoL. These could be a valuable resource for evaluating the overall health of the areas and help improve local decision making. [ABSTRACT FROM AUTHOR]

Glucose homeostasis is the tight control of glucose in the blood. This complex control is important, due to its malfunction in serious diseases like diabetes, and not yet sufficiently understood. Due to the involvement of numerous organs and sub-systems, each with their own intra-cellular control, we have developed a multi-level mathematical model, for glucose homeostasis, which integrates a variety of data. Over the last 10 years, this model has been used to insert new insights from the intra-cellular level into the larger whole-body perspective. However, the original cell-organ-body translation has during these years never been updated, despite several critical shortcomings, which also have not been resolved by other modeling efforts. For this reason, we here present an updated multi-level model. This model provides a more accurate sub-division of how much glucose is being taken up by the different organs. Unlike the original model, we now also account for the different dynamics seen in the different organs. The new model also incorporates the central impact of blood flow on insulin-stimulated glucose uptake. Each new improvement is clear upon visual inspection, and they are also supported by statistical tests. The final multi-level model describes >300 data points in >40 time-series and dose-response curves, resulting from a large variety of perturbations, describing both intra-cellular processes, organ fluxes, and whole-body meal responses. We hope that this model will serve as an improved basis for future data integration, useful for research and drug developments within diabetes.

Glucose homeostasis is the tight control of glucose in the blood. This complex control is important, due to its malfunction in serious diseases like diabetes, and not yet sufficiently understood. Due to the involvement of numerous organs and sub-systems, each with their own intra-cellular control, we have developed a multi-level mathematical model, for glucose homeostasis, which integrates a variety of data. Over the last 10 years, this model has been used to insert new insights from the intra-cellular level into the larger whole-body perspective. However, the original cell-organ-body translation has during these years never been updated, despite several critical shortcomings, which also have not been resolved by other modeling efforts. For this reason, we here present an updated multi-level model. This model provides a more accurate sub-division of how much glucose is being taken up by the different organs. Unlike the original model, we now also account for the different dynamics seen in the different organs. The new model also incorporates the central impact of blood flow on insulin-stimulated glucose uptake. Each new improvement is clear upon visual inspection, and they are also supported by statistical tests. The final multi-level model describes >300 data points in >40 time-series and dose-response curves, resulting from a large variety of perturbations, describing both intra-cellular processes, organ fluxes, and whole-body meal responses. We hope that this model will serve as an improved basis for future data integration, useful for research and drug developments within diabetes. [ABSTRACT FROM AUTHOR]

Abstract Background Active travel for utilitarian purposes contributes to total physical activity and may help counter the obesity epidemic. However, the evidence linking active travel and individual-level body weight is equivocal. Statistical modeling that accounts for spatial autocorrelation and unmeasured spatial predictors has not yet used to explore whether the health benefits of active travel are shared equally across socioeconomic groups. Methods Bayesian hierarchical models with spatial random effects were developed using travel survey data from Saskatoon, Canada (N = 4625). Differences in log-transformed body mass index (BMI) were estimated for levels of active travel use (vehicular travel only, mixed vehicular/active travel, and active travel only), household income, and neighbourhood deprivation after controlling for sociodemographic and physical activity variables. The modifying effect of household income on the association between active travel and BMI was also evaluated. Results Significant and meaningful decreases in BMI were observed for mixed (β = − 0.02, CrI − 0.036 to − 0.004) and active only (β = − 0.043, CrI − 0.06 to − 0.025) compared to vehicular only travelers. BMI was significantly associated with levels of household income and neighbourhood deprivation. Accounting for the interaction between travel mode and household income, decreases in BMI were observed for active only compared to vehicular only travellers in the highest income category (β = − 0.061, CrI − 0.115 to − 0.007). Conclusion Strategies to increase active travel use can support healthy weight loss and maintenance, but the opportunity to benefit from active travel use may be limited by low income. Considerations should be given to how interventions to increase active transportation might exacerbate social inequalities in BMI. Spatial statistical models are needed to account for unmeasured but spatially structured neighbourhood factors.

Forest height is an essential parameter used to derive important information about forest ecosystems, such as forest above-ground biomass. In this article, a forest height estimation approach combining P-band and X-band interferometric synthetic aperture radar (InSAR) was introduced. The forest height was estimated using the difference in the penetration of long- and short-wavelength radars to the forest. That is, the P-band and X-band InSAR data were used to extract the digital terrain model (DTM) and digital surface model (DSM), respectively. For the DTM, an improved time-frequency (TF) analysis method was used to reduce the effect of forest scatterers on the extraction of a pure understory terrain phase based on P-band InSAR. For the DSM, a novel compensation algorithm based on a multi-layer model (MLM) was proposed to remove the penetration bias of the X-band. Compared to the existing method based on the infinitely deep uniform volumes (IDUV) model, the MLM-based method is more in line with the characteristics of forest structure and the scattering mechanism for X-band InSAR. The airborne P-band repeat-pass InSAR and spaceborne X-band (TanDEM-X) single-pass InSAR data were used to verify the proposed method over the study area in the Saihanba Forest Farm in Hebei, China. The results demonstrated that the improved TF method can achieve high-precision DTM extraction based on P-band InSAR data, and the root mean square error (RMSE) was 0.94 m. The proposed MLM-based compensation method of the DSM achieved a smaller error (RMSE: 1.67 m) compared to the IDUV-based method (RMSE: 3.01 m). Under the same DTM extracted by P-band InSAR, the estimation accuracy of forest height based on the MLM method was 86.58% (RMSE: 1.81 m), which was 8.49% higher than that of the IDUV-based method (RMSE: 2.98 m).

This paper investigates, using a multi-product paradigm, the market structure of the Iranian banking sector to evaluate the role of scale. In so doing, we checked for economies of scope by multi-product cost function as well as the impact of potential economies on the banking sector structure including 18 banks during the period 2008–2014. The changes in Panzar-Rosse H-Statistic as a result of the variety in products reflect changes in the monopolistic power. The results show that an increase in the variety of offered products increases banks’ monopolistic power.

In the realm of behavioral interventions, a combined approach of yoga and a cognitive-behavioral strategy in the form of introspective meditation (manan-dhyana) may offer benefits as a stress management tool. This pilot study focuses on introspective meditation performed before seeking pleasurable activities, which is a self-reflection about whether to pursue a goal that will bring sensory pleasure in life. A non-probability sample of college students was recruited from a mid-sized Southern University of the United States using a 52-items web-based survey built in Qualtrics. Univariate, bivariate, and multivariate statistics were used to analyze data. Of total 65 students, only 21.5% students reported being engaged in the introspective meditation. The sample constituted predominantly females (75.4%), White (64.6%), and undergraduate students (87.7%). The proportions of anxiety, depression, and moderate/high stress were 50.8%, 40.0%, 86.1% respectively. In the hierarchical regression for initiation, the final model explained nearly 21.1% of variance in initiating introspective meditation among participants (n = 51) who had not been practicing it. With each unit increment in subscales of initiation (i.e., changes in physical environment), the conditional mean for initiating introspective meditation behavior increased by 0.373 units. In the hierarchical regression for sustenance, the final model explained nearly 50.5% of variance in sustaining introspective meditation behavior among participants (n = 51) who had not been practicing it. With each unit increment in subscales of sustenance (i.e., emotional transformation), the conditional mean for sustaining introspective meditation behavior increased by 0.330 units. This study can pave a way for designing interventions for college students to promote introspective meditation directed toward seeking pleasurable activities before engaging in them. This has implications for the reduction of stress as well as a preemptive measure for sexual risk-taking, indulgence in maladaptive behaviors such as smoking, vaping, alcohol, and substance use.

This study examined the association between two dimensions of social capital, structural and cognitive, and depression, as well as investigating their within- and between-effects. Using the Wisconsin Longitudinal Study, I applied a multi-level 2-wave longitudinal analysis, over a 7-year period, to examine these two dimensions of social capital influence on individual's depressive symptoms at both the between- and within-person levels. Results suggest both dimensions of social capital are negatively related with levels of depressive symptoms. The within-person changes for both self-efficacy and sense of belonging were larger than the estimates of between-effects, while trust and structural social capital effects were equal. These findings add to the growing body of literature examining depressive symptoms in late life, while also providing evidence for policymakers to hone in on key areas that can address depressive symptoms with social capital interventions.

While the use of evidence-based interventions (EBIs) has been advocated by the medical research community for quite some time, uptake of these interventions by healthcare providers has been slow. One possible explanation is that it is challenging for providers to estimate impacts of a specific EBI on their particular organization. To address that concern, we developed and evaluated a type of simulation called a policy flight simulator to determine if it could improve the adoption decision about a specific EBI, the transitional care model (TCM). The TCM uses an advanced practice nurse-led model of care to transition older adults with multiple chronic conditions from a hospitalization to home. An evaluation by a National Advisory Committee, made up of senior representatives from various stakeholders in the U.S. healthcare system, found the policy flight simulator to be a useful tool that has the potential to better inform adoption decisions. This paper describes the simulation development effort and documents lessons learned that may be useful to the healthcare modeling community and those interested in using simulation to support decisions based on EBIs.

Ecologists are increasingly familiar with Bayesian statistical modeling and its associated Markov chain Monte Carlo (MCMC) methodology to infer about or to discover interesting effects in data. The complexity of ecological data often suggests implementation of (statistical) models with a commensurately rich structure of effects, including crossed or nested (i.e., hierarchical or multi‐level) structures of fixed and/or random effects. Yet, our experience suggests that most ecologists are not familiar with subtle but important problems that often arise with such models and with their implementation in popular software. Of foremost consideration for us is the notion of effect identifiability, which generally concerns how well data, models, or implementation approaches inform about, i.e., identify, quantities of interest. In this paper, we focus on implementation pitfalls that potentially misinform subsequent inference, despite otherwise informative data and models. We illustrate the aforementioned issues using random effects regressions on synthetic data. We show how to diagnose identifiability issues and how to remediate these issues with model reparameterization and computational and/or coding practices in popular software, with a focus on JAGS, OpenBUGS, and Stan. We also show how these solutions can be extended to more complex models involving multiple groups of nested, crossed, additive, or multiplicative effects, for models involving random and/or fixed effects. Finally, we provide example code (JAGS/OpenBUGS and Stan) that practitioners can modify and use for their own applications. [ABSTRACT FROM AUTHOR]

This study examines the productivity performance of Balkan firms within and outside the European Union (EU), including the influence of loans. A multiple treatment model is used to compare the effects on productivity of membership and loans both separately and collectively, which in the case of loans allows a separate analysis of their influence on firms in non-member states. The use of conditional quantile regressions measures the effect on productivity of membership and loans separately as treatment variables. This provides an analysis of where the treatment influence is greatest across the distribution curve and identifies the significance of selected control variables on the outcome. In the full sample, the findings indicate that EU membership and loans have a positive effect on productivity, with membership being more important than loans. Outside the EU, firms in receipt of loans are more productive than those without. However, the significance of both membership and loans is restricted to the lower end of the productivity distribution curve. The manufacturing sample shows that EU membership has a significant positive effect across 70% of the deciles measured, whilst the influence of loans is restricted to the lower deciles, with rental capital (leasing) also positively significant in the lower four deciles. In the services sector, however, membership is significant up to 90% of the distribution, with loans at 60%.

The purpose of this paper was to measure the quality of concordance of one- and two-level structural equation models by testing the two following statistical hypotheses: first, the structure of the two-level model is more efficient than that of the one-level model; second, economic and social determinants and intermediate variables have a significant effect on current and future fertility in Giza Governorate. A two-tier bicameral model (women, geographical area) was built on 1500 families divided equally into three districts (urban, rural, and slum). The districts were divided into 294 convergent communities according to the standard of living. M−Plus 8.0 was used to estimate the numbers of four models. The first estimated structural relationships between the determinants of fertility within the layers; the second estimated relationships between the second and third strata; the third estimated structural equations at the second level; and the fourth included the constants and a random slope in the model. The results show that the estimated parameters of the models corresponded well to the model and the multi-level model, whose indicators are proposed within acceptable limits. The final proposed model and the significance of its coefficients were tested to ensure the quality of the compatibility of the final model. The results show that the overall quality of the proposed compatibility is very high and that the indicators are within the accepted limits. The compatibility quality index is 0.99, the correlation quality is corrected by 0.98, and the CI index of significance is 0.00. Therefore, we can say that the proposed multi-level structural model (based on the indicators of total compatibility quality) is more efficient than the one-level model, supporting the first hypothesis. The second hypothesis is that economic and social determinants and intermediate variables have a significant impact on current and future fertility. [ABSTRACT FROM AUTHOR]

Background: Active travel for utilitarian purposes contributes to total physical activity and may help counter the obesity epidemic. However, the evidence linking active travel and individual-level body weight is equivocal. Statistical modeling that accounts for spatial autocorrelation and unmeasured spatial predictors has not yet used to explore whether the health benefits of active travel are shared equally across socioeconomic groups. Methods: Bayesian hierarchical models with spatial random effects were developed using travel survey data from Saskatoon, Canada (N = 4625). Differences in log-transformed body mass index (BMI) were estimated for levels of active travel use (vehicular travel only, mixed vehicular/active travel, and active travel only), household income, and neighbourhood deprivation after controlling for sociodemographic and physical activity variables. The modifying effect of household income on the association between active travel and BMI was also evaluated. Results: Significant and meaningful decreases in BMI were observed for mixed (β = − 0.02, CrI − 0.036 to − 0.004) and active only (β = − 0.043, CrI − 0.06 to − 0.025) compared to vehicular only travelers. BMI was significantly associated with levels of household income and neighbourhood deprivation. Accounting for the interaction between travel mode and household income, decreases in BMI were observed for active only compared to vehicular only travellers in the highest income category (β = − 0.061, CrI − 0.115 to − 0.007). Conclusion: Strategies to increase active travel use can support healthy weight loss and maintenance, but the opportunity to benefit from active travel use may be limited by low income. Considerations should be given to how interventions to increase active transportation might exacerbate social inequalities in BMI. Spatial statistical models are needed to account for unmeasured but spatially structured neighbourhood factors. [ABSTRACT FROM AUTHOR]

Terrorism has the potential to affect population health through various pathways. Since the literature mostly analyzes tangible economic costs, there is dearth of evidence on health effects of terrorism. In an effort to address that gap, this article explores the relationship between terrorism and health satisfaction of Turkish citizens by combining province-level and individual-level data sets. In order to quantify determinants of health satisfac - tion, a multi-level modeling framework is employed. Empirical analysis suggests that individuals with higher exposure to terrorism are more likely to report lower health satisfaction in Turkey. Health satisfaction of individu - als is significantly and positively correlated with individual-level covariates such as education level, marital status, employment status, household income, housing floor area per person, interest in health issues and becoming a parent within the past year. Age, being female and utilization of health services display negative associations with health satisfaction of individuals. Finally, province-level GDP per capita and schooling ratio exhibit significantly positive associations with individual health satisfaction in Turkey. [ABSTRACT FROM AUTHOR]

Although schools are known to play a major role in the spread of influenza virus, few studies have evaluated the effectiveness of vaccination and non-pharmaceutical measures for preventing influenza outbreaks in schools. We investigated all febrile illness outbreaks in primary and secondary schools in Beijing reported between August 2018 and July 2019. We obtained epidemiological information on febrile illness outbreaks and oral pharyngeal swabs from students in the outbreaks to test for influenza virus. We surveyed schools that did not report febrile illness outbreaks. We developed multi-level models to identify and evaluate factors associated with serious influenza outbreaks and explored the association of vaccine coverage and outbreaks using multi-stage regression models. We identified a total of 748 febrile illness outbreaks involving 8176 students in Beijing; 462 outbreaks were caused by influenza virus. Adjusted regression modeling showed that large class size (odds ratio (OR) = 2.38) and the number of days from identification of the first case to initiation of an intervention (OR = 1.17) were statistically significant and positively associated with serious outbreaks, and that high vaccination coverage (relative risk (RR) = 0.50) was statistically significant and negatively associated with outbreaks. Multi-stage regression modeling showed that RR decreased fastest when vaccination coverage was 45% to 51%. We conclude that high influenza vaccination coverage can prevent influenza outbreaks in schools and that rapid identification of febrile children and early initiation of non-pharmaceutical measures can reduce outbreak size.

Objectives: India's Covid-19 vaccination campaign engaged frontline workers (FLWs) to encourage vaccination among vulnerable segments of society. The FLWs report encountering a variety of barriers to vaccination and are often unsuccessful despite multiple visits to the same person. This cross-sectional study aims to pinpoint which of these barriers drive vaccine hesitancy among these segments, to help streamline vaccine communication, including FLW training, to better safeguard the population., Methods: Trained field enumerators contacted 893 individuals from five states across India and collected self-reported assessments of fifteen vaccination barriers (identified through discussions with FLWs), current vaccination status and future vaccination intentions, and covariates (demographics/comorbidities). Factor analysis of the fifteen barriers yielded two factors, one relating to fear of vaccine adverse effects and a second focused on peripheral concerns regarding the vaccine. The covariates significantly associated with current vaccination status were combined under a latent class regime to yield three cluster types (health access, financial strength, and demographics). The primary analysis examined the effect of the two barrier factors, the covariate clusters, and comorbidity, on current vaccination status and future vaccine intentions., Results: Fear of vaccine adverse effects was the primary driver of vaccine hesitancy; peripheral concerns frequently mentioned by the FLWs had no impact. Although cluster membership and the presence of comorbidities predicted vaccine uptake, neither of them materially altered the effect of fear of vaccine adverse effects with the following exception: fear of adverse effects was not associated with vaccination status among young Muslim men., Conclusion: Subject to limitations, these results indicate that interventions to decrease vaccine hesitancy should focus primarily on fear associated with vaccines rather than spend resources trying to address peripheral concerns., Competing Interests: Author MS, NK, PS, SK, RN, AbP and AdP was employed by company Catalyst Management Services. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Krishnamurthy, Mulvey, Gowda, Singh, Venkatesan, Syam, Shah, Kumar, Chaudhuri, Narayanan, Perne and Pangaria.)

Abstract: This study investigated the factors affecting piglet mortality (square root of mortality, SQRM) and average weaning weight (AWW) in commercial farms in central China. Information on sow diets, management and climate from 2478 weaning batches completed in 16 pig farms was collected from 2009 to 2013. Multi‐level mixed models, which included batch level (level 1) and farm level (level 2), were used to analyze the factors associated with SQRM and AWW. The mean values of SQRM and AWW were 2.52% (SD = 0.96) and 7.31 (SD = 0.77), respectively. Lactation sow diets supplemented with oregano essential oils (OEOs) decreased the SQRM (P < 0.05) and increased the AWW of piglets (P < 0.01). The SQRM was lower in period 2 (June to September, hot) than in period 1 (February to May, warm) and period 3 (October to January, cold; P < 0.05 and 0.001, respectively). The AWW was lower in periods 2 and 3 than in period 1 (P < 0.01). In conclusion, supplying OEOs to lactation diets can increase the weaning weight and reduce the mortality of piglets. The sources of variations in SQRM and AWW are of greater concern in the warm season than in the hot season. [ABSTRACT FROM AUTHOR]

Heterogeneity of local conditions and spatial dependencies are typical aspects of sociological phenomena. However, large-scale empirical data is often rather limited with regard to the spatial references that are (publicly) available to researchers. We describe several aspects of the problem and assess possibilities and potential errors associated with limited information. Our examples are returns to education and gender-based and migration-related wage gaps as popular research topics. We base our analyses upon widely used survey data from Germany, the GSOEP, which contains geographical information on various levels of aggregation. Our particular interest is in the decisions that have to be made with regard to problems of space and place in standard surveys, available options and consequences. We conclude with a number of practical suggestions for data users.

The products made by the forming of polycrystalline metals and alloys, which are in high demand in modern industries, have pronounced inhomogeneous distribution of grain orientations. The presence of specific orientation modes in such materials, i.e., crystallographic texture, is responsible for anisotropy of their physical and mechanical properties, e.g., elasticity. A type of anisotropy is usually unknown a priori, and possible ways of its determination is of considerable interest both from theoretical and practical viewpoints. In this work, emphasis is placed on the identification of elasticity classes of polycrystalline materials. By the newly introduced concept of "elasticity class" the union of congruent tensor subspaces of a special form is understood. In particular, it makes it possible to consider the so-called symmetry classification, which is widely spread in solid mechanics. The problem of identification of linear elasticity class for anisotropic material with elastic moduli given in an arbitrary orthonormal basis is formulated. To solve this problem, a general procedure based on constructing the hierarchy of approximations of elasticity tensor in different classes is formulated. This approach is then applied to analyze changes in the elastic symmetry of a representative volume element of polycrystalline copper during numerical experiments on severe plastic deformation. The microstructure evolution is described using a two-level crystal elasto-visco-plasticity model. The well-defined structures, which are indicative of the existence of essentially inhomogeneous distribution of crystallite orientations, were obtained in each experiment. However, the texture obtained in the quasi-axial upsetting experiment demonstrates the absence of significant macroscopic elastic anisotropy. Using the identification framework, it has been shown that the elasticity tensor corresponding to the resultant microstructure proves to be almost isotropic. [ABSTRACT FROM AUTHOR]