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The objective of this study was to investigate and analyze the status and influential factors of gender equality awareness, self-esteem, and subjective well-being in school-age boys and girls. The results can help schools and teachers provide more effective gender equality and mental health education. In the study, 284 valid questionnaires were collected from a total of 323 school-age boys and girls in the Hunan Province, China (effective response rate of 87.93%). The questionnaire covered gender equality awareness, self-esteem, and subjective well-being, with the influencing factors analyzed through multiple linear regression. There was a significant correlation among children’s gender equality awareness in all areas examined (family, occupation, and school), with both boys and girls having the lowest awareness of gender equality in occupational fields. The children’s self-esteem and subjective well-being were significantly correlated as well. Gender equality awareness, self-esteem, and subjective well-being among boys and girls reflected different influential factors. Androgynous traits (neither feminine nor masculine) were conducive to the development of gender equality awareness and self-esteem among the children. Therefore, schools and teachers need to provide gender equality and mental health education according to the specific psychological characteristics of each boy and girl.

Abstract Background After the lockdown of Wuhan on January 23, 2020, the government used community-based pandemic prevention and control as the core strategy to fight the pandemic, and explored a set of standardized community pandemic prevention measures that were uniformly implemented throughout the city. One month later, the city announced its first lists of “high-risk” communities and COVID-19-free communities. Under the standardized measures of pandemic prevention and mitigation, why some communities showed a high degree of resilience and effectively avoided escalation, while the situation spun out of control in other communities? This study investigated: 1) key factors that affect the effective response of urban communities to the pandemic, and 2) types of COVID-19 susceptible communities. Methods This study employs the crisp-set qualitative comparative analysis method to explore the influencing variables and possible causal condition combination paths that affect community resilience during the pandemic outbreak. Relying on extreme-case approach, 26 high-risk communities and 14 COVID-19 free communities were selected as empirical research subjects from the lists announced by Wuhan government. The community resilience assessment framework that evaluates the communities’ capacity on pandemic prevention and mitigation covers four dimensions, namely spatial resilience, capital resilience, social resilience, and governance resilience, each dimension is measured by one to three variables. Results The results of measuring the necessity of 7 single-condition variables found that the consistency index of “whether the physical structure of the community is favorable to virus transmission” reached 0.9, which constitutes a necessary condition for COVID-19 susceptible communities. By analyzing the seven condition configurations with high row coverage and unique coverage in the obtained complex solutions and intermediate solutions, we found that outbreaks are most likely to occur in communities populated by disadvantaged populations. However, if lacking spatial-, capital-, and governance resilience, middle-class and even wealthy communities could also become areas where COVID-19 spreads easily. Conclusions Three types of communities namely vulnerable communities, alienated communities, and inefficient communities have lower risk resilience. Spatial resilience, rather than social resilience, constitutes the key influencing factor of COVID-19-susceptible communities, and the dual deficiencies of social resilience and governance resilience are the common features of these communities.

Chronic lymphocytic leukemia (CLL) has experienced a clinical revolution—thanks to the discovery of crucial pathogenic mechanisms. CLL is still an incurable disease due to intrinsic or acquired resistance of the leukemic clone. Venetoclax is a Bcl-2 inhibitor with a marked activity in CLL, but emerging patterns of resistance are being described. We hypothesize that intrinsic features of CLL cells may contribute to drive mechanisms of resistance to venetoclax. We analyzed the expression of Interferon Regulatory Factor 4 (IRF4), Notch2, and Mcl-1 in a cohort of CLL patients. We evaluated CLL cell viability after genetic and pharmaceutical modulation of Notch2 expression in patients harboring trisomy 12. We tested venetoclax in trisomy 12 CLL cells either silenced or not for Notch2 expression or in combination with an inhibitor of Mcl-1, AMG-176. Trisomy 12 CLL cells were characterized by low expression of IRF4 associated with high levels of Notch2 and Mcl-1. Notch2 and Mcl-1 expression determined protection of CLL cells from spontaneous and drug-induced apoptosis. Considering the involvement of Mcl-1 in venetoclax resistance, our data demonstrated a contribution of high levels of Notch2 and Mcl-1 in a reduced response to venetoclax in CLL cells carrying trisomy 12. Furthermore, reduction of Mcl-1 expression by silencing Notch2 or by treatment with AMG-176 was able to restore the response of CLL cells to venetoclax. The expression of Notch2 identifies a subset of CLL patients, mainly harboring trisomy 12, characterized by high levels of Mcl-1. This biological mechanism may compromise an effective response to venetoclax.

This work presents a machine-learning approach to predict peak-stress clusters in heterogeneous polycrystalline materials. Prior work on using machine learning in the context of mechanics has largely focused on predicting the effective response and overall structure of stress fields. However, their ability to predict peak – which are of critical importance to failure – is unexplored, because the peak-stress clusters occupy a small spatial volume relative to the entire domain, and hence require computationally expensive training. This work develops a deep-learning-based convolutional encoder–decoder method that focuses on predicting peak-stress clusters, specifically on the size and other characteristics of the clusters in the framework of heterogeneous linear elasticity. This method is based on convolutional filters that model local spatial relations between microstructures and stress fields using spatially weighted averaging operations. The model is first trained against linear elastic calculations of stress under applied macroscopic strain in synthetically generated microstructures, which serves as the ground truth. The trained model is then applied to predict the stress field given a (synthetically generated) microstructure and then to detect peak-stress clusters within the predicted stress field. The accuracy of the peak-stress predictions is analyzed using the cosine similarity metric and by comparing the geometric characteristics of the peak-stress clusters against the ground-truth calculations. It is observed that the model is able to learn and predict the geometric details of the peak-stress clusters and, in particular, performed better for higher (normalized) values of the peak stress as compared to lower values of the peak stress. These comparisons showed that the proposed method is well-suited to predict the characteristics of peak-stress clusters.

This research aims at the relationships between the subjective norm, attitude, personal norm, perceived behavioral control, and behavioral intention. The interviewees consist of the body painting learners, who have undergone the survey of the print questionnaire. After deleting 20 ineffective questionnaires, the remaining 300 questionnaires yield the effective response rate of 93.7%. The conclusions based on this research are listed as follow: (1) The subjective norm places positive impact on the attitude. (2) The intention is positively influenced by the attitude. (3) The subjective norm positively impacts on the personal norm of the intention. (4) The intention is positively influenced by the personal norm. (5) The perceived behavioral control is positively influenced by the subjective norm. (6) The perceived control positively effects on the intention. (7) The subjective norm positively influences the intention. (8) The attitude fully places the mediation effects between the subjective norm and the behavioral intention. (9) The personal norms partially place the mediation effect between the subjective norm and the behavioral intention. (10) The perceived behavioral control partially places the mediation effect between the subjective norm and the behavioral intention.  

An effective response to climate change that assures a sustainable development pathway will require a fundamental transformation towards a low carbon, climate-resilient societies. Each change need for solid financial support, financial solutions, and dedicated instruments, taking into account ESG factors and taking into account the impact of financial crises. This chapter aims to bring together theories, trends, dilemmas, and directional concepts to answer the question about changes in the existing paradigm of climate finance. On the other hand, the analysis of trends and presenting future prospects regarding sustainable finance will be aimed at enhancing the substantive and practical knowledge of the target audience. In addition, in this chapter, the following issues will be presented in particular: changes in the sustainable finance paradigm and the emergence of the climate finance paradigm, macro-and micro-financial aspects of climate change taking into account the influence of risk (including ESG risk), and a new landscape of climate finance.

This study draws implications through a case analysis of disaster sites with multiple casualties. Based on this, through a survey targeting firefighters working at disaster sites, this study aimed to present an effective response improvement plan at disaster sites with multiple casualties. First, it is necessary to strengthen the operational capability of the emergency medical center of the first responders. Second, an easy and convenient triage pocket book should be produced and distributed to strengthen the triage capability of all firefighters, including paramedics. Third, it is necessary to introduce the multiple casualty e-triage system for casualty management. Fourth, the communication system for prompt on-site dispatch at public health centers and DMAT should be improved. Lastly, it is necessary to re-establish the severity classification criteria for cardiac arrest patients at disaster sites.

The purpose of this study is that healthcare professionals play the most significant role in tackling pandemic COVID-19 and are considered as the most vulnerable and at-risk population for infection. An effective response to a pandemic depends on the attitudes and behaviors of physicians, nursing, staff, lab technicians, and other support staff.  The study was conducted to explore the attitudes and behaviors of health care professionals towards preventive measures against COVID-19. The study was designed following the positivistic research paradigm hence cross-sectional survey research was selected as the most appropriate design. For the purpose of data collection, a self-administered structured questionnaire was developed and used. The survey was conducted during the month of March 2020 in Punjab through an online data collection method from 150 health care professionals working in various public sector hospitals in Punjab. The questionnaire was uploaded on the survey monkey website and shared on various social media platforms to collect data in order to get responses. Results show that self-reported anxiety level is high among physicians and nurses as compared to technical and support staff.  Data shows that there are significant differences in attitudes and behaviors towards preventive measures against pandemic COVID-19 between physicians and nurses especially about the adoption of various techniques for improving immunity.  It was also found that there are significant attitudinal and behavioral differences according to sex, region of residence, and marital status of health care professionals. 

Numerous nations have implemented lockdown measures in response to the COVID-19 pandemic. As a consequence of the lockdown on daily living, social participation, and health service accessibility, vulnerable people, for example, new mothers, may experience an increase in mental health problems. This cross-sectional survey was conducted to investigate the impact of the COVID-19 pandemic lockdown on Thai new mothers and the variables affecting their mental health. The survey data were collected from 903 Thai mothers with infants aged 0–12 months using an online platform and a face-to-face interview questionnaire survey between 17 July and 17 October 2020, during the first nationwide COVID-19 lockdown period. For the final analysis, there were 862 participants who completed all of the questions. The full exploratory analysis was performed by multivariable linear regression to identify the variables influencing maternal mental health. Our study demonstrated that new mothers reported feeling a high extent to some extent of worry (44.9%), increased appetite (40.4%), becoming easily annoyed or irritable (39.1%), and feeling down (33.5%), whereas 82.7% felt able to cope with the first lockdown situation. Practiced relaxation techniques were associated with positive maternal mental health (adjusted β = 1.05, 95% CI 0.57 to 1.52, p < 0.001). The perceived impact of the COVID-19 lockdown was on the household’s ability to pay for rent, to make mortgage payments (adjusted β = −1.59, 95% CI −2.87 to −0.36, p = 0.011), the household’s ability to pay for other essentials, such as utilities and medication (adjusted β = −1.99, 95% CI −3.16 to −0.81, p = 0.001), household crowding after lockdown (adjusted β = −3.46, 95% CI −4.86 to −2.06, p < 0.001), and not going outside or doing outdoor activities (adjusted β = −2.22, 95% CI −3.35 to −1.08, p < 0.001). These impacts were significantly associated with negative mental health. In conclusion, our results emphasize the critical need for continuous monitoring of maternal mental health and developing an effective response strategy and activity for promoting maternal mental health under the stress of repetitive lockdowns and increased economic pressures.