The Relationship Between Social Support And Social Withdrawal Of Left-Behind Adolescents: A Chain Mediating Model

Background: Nowadays, as more and more Chinese farmers in rural area went to city for work, they left their kids at home. These kids were left-behind adolescents and they developed without their parental accompany. The family function of left-behind adolescents was deficient, which may result in their social withdrawal in social situations. Therefore, in this study, in order to improve left-behind adolescents’ psychological and behavior problems, we aimed to investigate their level of social withdrawal and its impact factors. Method: There were 339 left-behind adolescents and 289 non-left-behind adolescents recruited from a Chinese junior high school. Their social withdrawal, social support, relative deprivation, and resilience were measured through questionnaires. Results: The results showed that compared with non-left-behind adolescents, left-behind adolescents had lower social support and resilience, but their social withdrawal and relative deprivation were higher; besides, left-behind adolescents’ social support negatively predicted social withdrawal, while relative deprivation and resilience played a chain mediating role between them. Conclusion: This study found that compared with none-left-behind adolescents, left-behind adolescents had difficulty in social adaptation. However, there was a “context-process-outcome” model in which social support negatively predicted social withdrawal, while relative deprivation and resilience played a chain mediating role between them. In sum, this study provided suggestions to promote the mental health and social behavioral development of left-behind adolescents.

SEMANTIC MODELING IN RESILIENCE RESEARCH OF ENERGY AND SOCIO-ECOLOGICAL SYSTEMS

В статье рассматриваются возможности применения семантического моделирования, включающего, в частности, онтологическое и когнитивное моделирование для поддержки совместных исследований энергетических и социо-экологических систем. Работа посвящена использованию онтологического инжиниринга для структурирования знаний предметных областей и когнитивного моделирования в исследованиях влияния функционирования энергетических объектов на природную среду и человека. Онтологическое моделирование используется для выявления, описания и согласования базовых понятий предметных областей исследований и позволяет систематизировать и наглядно представить взаимосвязи между элементами природной среды, объектами энергетики и их характеристиками, факторами воздействия и методами их расчета. Когнитивное моделирование используется для выявления структуры причинно-следственных связей между факторами, влияющими на устойчивость системы. The article discusses the possibilities of applying semantic modeling, including, in particular, ontological and cognitive modeling to support joint research of energy and socio-ecological systems. The work is devoted to the use of ontological engineering for structuring knowledge of subject areas and cognitive modeling in studies of the impact of the functioning of energy facilities on the natural environment and humans. Ontological modeling is used to identify, describe and coordinate the basic concepts of subject areas of research and allows you to systematize and visualize the relationship between elements of the natural environment, energy facilities and their characteristics, impact factors and methods of their calculation. Cognitive modeling is used to identify the structure of causal relationships between factors affecting the stability of the system.

Dynamic Response of a Vehicle-Bridge Expansion Joint Coupled System

The paper investigates the dynamic vibration property of the vehicle-bridge expansion joint coupled system with the proposed model. The dynamic response of the expansion joint under the action of the vehicle is the key factor affecting the life of the expansion joint. The changes of contact state and tire geometric characteristics were frequently left aside in the past to simplify the tire model. This is because the contact between tire and expansion joint is a very complex process. But this will seriously underestimate the impact effect of the vehicle on the expansion joint. In this paper, a dynamic mathematical model of the 2-axle vehicle-modular bridge expansion joint (MBEJ) coupled system is established by introducing a flexible roller tire model. The influence of tread rigid displacement and change in the tire contact patch length are considered in the dynamic model. Based on this model, the characteristics of the dynamic tire load and the center beam vibration displacement in the coupled system are obtained by simulation. The results show that the maximum dynamic tire load of the vehicle occurs at the end of the bridge deck behind the MBEJ, so local structure reinforcement needs to be considered. The interaction between the front and rear wheels of the 2-axle vehicle can be ignored. The vehicle position, vehicle velocity, gap width, and spring stiffness of the center beam bearing have significant effects on the impact factors of tire load and center beam vibration displacement. The impact factor of tire load may exceed the recommended values of Chinese and European bridge codes. These should be taken seriously.

ФОРСАЙТ СОЦІАЛЬНО-ТРУДОВОЇ МОБІЛЬНОСТІ МОЛОДІ НА ОСНОВІ ВИКОРИСТАННЯ ХАКАТОН-ЕКОСИСТЕМИ

The article discusses contemporary issues related to social and labor mobility of youth. In particular, it is observed that social and labor mobility is influenced by such factors as social order; ethnocultural stereotypes at the modern stage of social process development; system of social and moral values; changes in the employment types and patterns, a range of professions and occupational prestige in public opinion; demographic processes; regional specifics; social structure and organisation; settlement structure, etc. The study reveals that from a microenvironment perspective, the youth social and labor mobility level is primarily affected by the following group of impact factors: family, education system, immediate environment, media, territorial specifics of professional and social structure and others. The study findings demonstrate that the correlation between objective realia and microenvironment in the process of professional self-identity of an individual could be viewed as the relationship between the two external sources of shaping a person’s professional focus. To attain the research agenda, foresight technologies were employed to encourage social and labor mobility of young people. Data collection on graduates was conducted at the Kyiv National University of Technologies and Design during 2019–2020. Based on the use of the Hackathon ecosystem, this study presents a foresight on youth social and labor mobility. It is argued that such a mechanism contributes to building socioeconomic relationships between institutions, enterprises and organizations on youth social and labor mobility, applying a systematic approach to tackling the issues under consideration, developing the key areas for effective interaction, establishing socioeconomic, legal, psychological and didactic terms to coordinate their activity. The regulatory framework to manage social and labor attitudes of young people based on the University Hackathon ecosystem involves the following mechanisms: institutional (developing and implementing a regulatory framework as well as the government workforce policy), organizational (assessing the situation within the educational environment: social, household-based, psychological), economic (which covers optimality, efficiency, structuring) along with personal and motivational (insights into the demands, values, interests and motifs).

Applying Machine Learning and AI Explanations to Analyze Vaccine Hesitancy

The paper identifies and quantifies the impact of race, poverty, politics, and age on COVID-19 vaccination rates in counties across the continental US. Both traditional Ordinary Least Square (OLS) regression analysis and Random Forest machine learning algorithms are applied to quantify contributing factors for county-level vaccination hesitancy. With the machine learning model, joint effects of multiple variables (race/ethnicity, partisanship, age etc.) are considered simultaneously to capture the unique combination of what factors affect the vaccination rate. By implementing a state-of-the-art Artificial Intelligence Explanations (AIX) algorithm, it is possible to solve the black box problem with machine learning models and provide answers to the "how much" question for each measured impact factor in every county. For most counties a higher percentage vote for Republicans, a greater African American population share, and a higher poverty rate lower the vaccination rate. While a higher Asian population share increases the predicted vaccination rate. The impact on the vaccination rate from the Hispanic population proportion is positive in the OLS model, but only positive for counties with very high Hispanic population (65% and more) in the Random Forest model. Both the proportion of seniors and the one for young people in a county have a significant impact in the OLS model - positive and negative, respectively. In contrast, the impacts are ambiguous in the Random Forest model. Because results vary between geographies and since the AIX algorithm is able to quantify vaccine impacts individually for each county, this research can be tailored to local communities. This way it is a helpful tool for local health officials and other policymakers to improve vaccination rates. An interactive online mapping dashboard that identifies impact factors for individual U.S. counties is available at https://www.cpp.edu/~clange/vacmap.html. It is apparent that the influence of impact factors is not universally the same across different geographies.

Dynamics of Donor-Derived Cell-Free DNA at the Early Phase After Pediatric Kidney Transplantation: A Prospective Cohort Study

Background: Donor-derived cell-free DNA (ddcfDNA) has been suggested as an indicator of allograft injury in adult and pediatric kidney transplantation (KTx). However, the dynamics of ddcfDNA in pediatric KTx have not been investigated. In addition, it has not been demonstrated whether donor-recipient (D/R) size mismatch affect ddcfDNA level.Methods: Pediatric KTx recipients with a single donor kidney were enrolled and followed up for 1 year. ddcfDNA, calculated as a fraction (%) in the recipient plasma, was examined longitudinally within 3 months post-transplant. D/R size mismatch degree was described as D/R height ratio. The 33rd percentile of D/R height ratio (0.70) was used as the cut-off to divide the patients into low donor-recipient height ratio group (<0.70) and high donor-recipient height ratio group (≥0.70). The dynamics of ddcfDNA were analyzed and the impact factors were explored. Stable ddcfDNA was defined as the first lowest ddcfDNA. ddcfDNA flare-up was defined as a remarkable elevation by a proportion of >30% from stable value with a peak value >1% during elevation.Results: Twenty-one clinically stable recipients were enrolled. The median D/R height ratio was 0.83 (0.62–0.88). It took a median of 8 days for ddcfDNA to drop from day 1 and reach a stable value of 0.67% (0.46–0.73%). Nevertheless, 61.5% patients presented ddcfDNA>1% at day 30. Besides, 81.0% (17/21) of patients experienced elevated ddcfDNA and 47.6% (10/21) met the standard of ddcfDNA flare-up. Donor-recipient height ratio was an independent risk factor for ddcfDNA flare-up (odds ratio = 0.469 per 0.1, 95% CI 0.237–0.925, p = 0.029) and low donor-recipient height ratio (<0.70) was found to increase the risk of flare-up occurrence (odds ratio = 15.00, 95% CI 1.342–167.638, p = 0.028).Conclusions: ddcfDNA rebounds in many stable pediatric KTx recipients without rejection. This may be induced by significant D/R size mismatch and may affect its diagnostic performance at the early phase after pediatric KTx in children.

Towards more inclusive metrics and open science to measure research assessment in Earth and natural sciences

Science's success and effect measures are built on a system that prioritizes citations and impact factors. These measurements are inaccurate and biased against already under-represented groups, and they fail to convey the range of individuals' significant scientific contributions, especially open science. We argue for a transition in this out-of-date value system that promotes science by promoting diversity, equity, and inclusion. To achieve systemic change, it will necessitate a concerted effort led by academic leaders and administrators.

Thrombocytopenia predicts mortality in Chinese hemodialysis patients- an analysis of the China DOPPS

Background Hemodialysis (HD) patients have a higher mortality rate compared with general population. Our previous study revealed that platelet counts might be a potential risk factor. The role of platelets in HD patients has rarely been studied. The aim of this study is to examine if there is an association of thrombocytopenia (TP) with elevated risk of all-cause mortality and cardiovascular (CV) death in Chinese HD patients. Methods Data from a prospective cohort study, China Dialysis Outcomes and Practice Patterns Study (DOPPS) 5, were analyzed. Demographic data, comorbidities, platelet counts and other lab data, and death records which extracted from the medical record were analyzed. TP was defined as the platelet count below the lower normal limit (< 100*109/L). Associations between platelet counts and all-cause and CV mortality were evaluated using Cox regression models. Stepwise multivariate logistic regression was used to identify the independent associated factors, and subgroup analyses were also carried out. Results Of 1369 patients, 11.2% (154) had TP at enrollment. The all-cause mortality rates were 26.0% vs. 13.3% (p < 0.001) in patients with and without TP. TP was associated with higher all-cause mortality after adjusted for covariates (HR:1.73,95%CI:1.11,2.71), but was not associated with CV death after fully adjusted (HR:1.71,95%CI:0.88,3.33). Multivariate logistic regression showed that urine output < 200 ml/day, cerebrovascular disease, hepatitis (B or C), and white blood cells were independent impact factors (P < 0.05). Subgroup analysis found that the effect of TP on all-cause mortality was more prominent in patients with diabetes or hypertension, who on dialysis thrice a week, with lower ALB (< 4 g/dl) or higher hemoglobin, and patients without congestive heart failure, cerebrovascular disease, or hepatitis (P < 0.05). Conclusion In Chinese HD patients, TP is associated with higher risk of all-cause mortality, but not cardiovascular mortality. Platelet counts may be a useful prognostic marker for clinical outcomes among HD patients, though additional study is needed.