Exploring the Relationship between Early Leaving of Education and Training and Mental Health among Youth in Spain

This study aimed to explore the relationship between Early Leaving Education and Training and mental health perceived by young Spanish school leavers, as well as develop mid-range theories to better understand this relationship. The study uses a grounded theory approach; specifically, Charmaz’s constructivist approach and its informed version have guided the study. Through qualitative interviews with individuals who had left school prematurely, the results of this study showed a bidirectional relationship between ELET and mental health, where the detriment in the mental health of young people who leave school early should be understood as both a cause and an effect of the process of ELET. In addition, the findings suggest that certain socio-economic and educational factors, such as bullying, academic stress, self-responsibilization of failure, and labels such as “NEET” can contribute to a decrease in mental health. Overall, this study has provided new insights into the ELET-mental health relationship, contributing to the development of mid-range theories that can inform future research and interventions to minimize these problems

Advancing Gender Equality in Schools through Inclusive Physical Education and Teaching Training: A Systematic Review

The importance of achieving an inclusive education to ensure parity and equality between genders is a worldwide challenge. Consequently, it is essential to rethink the various places and spaces within the school environment where gender inequalities are produced. Physical education is one of these spaces which has been identified as a problematic area in the literature. In order to address this issue and respond to the needs identified in the research, this systematic review presents action initiatives aimed at applying certain teaching strategies highlighted in the study. The PRISMA method was used to review 274 studies which explore this topic at various levels of education, emphasizing the need for coeducational teaching of physical education and the necessity of proposing motivational tasks for both sexes. In particular, results show that some studies have focused on the need for physical education teachers to be aware of potential gender-biased structures when developing curricula, approaches and materials. Other research has highlighted that in order for physical education classes to be inclusive, equitable opportunities must be provided for all students to participate. In addition, strategies should be implemented which promote positive attitudes towards physical activity by addressing any underlying gender stereotypes and by breaking down traditional boundaries that exist between genders. In conclusion, this systematic review has identified a number of teaching strategies which could help teachers create an equitable learning environment within physical education classes. This could subsequently lead to greater success in achieving an inclusive education which promotes parity and equality between genders

MiniAnDE: a reduced AnDE ensemble to deal with microarray data

This article focuses on the supervised classification of datasets with a large number of variables and a small number of instances. This is the case, for example, for microarray data sets commonly used in bioinformatics. Complex classifiers that require estimating statistics over many variables are not suitable for this type of data. Probabilistic classifiers with low-order probability tables, e.g. NB and AODE, are good alternatives for dealing with this type of data. AODE usually improves NB in accuracy, but suffers from high spatial complexity since $k$ models, each with $n+1$ variables, are included in the AODE ensemble. In this paper, we propose MiniAnDE, an algorithm that includes only a small number of heterogeneous base classifiers in the ensemble, i.e., each model only includes a different subset of the $k$ predictive variables. Experimental evaluation shows that using MiniAnDE classifiers on microarray data is feasible and outperforms NB and other ensembles such as bagging and random forest

A fuzzy logic model for the analysis of social corporate responsibility

Introduction: Critical public opinion, based on information that is made available to the public through different systems, has led companies that operate in the environment to continually improve their social, environmental, and ethical performance. Objectives: This paper aims to propose a fuzzy-logic-based model for the analysis of social corporate responsibility in cases of environmental accidents. Methods: Our study employs techniques derived from social network analysis. The data was collected from the online database of The New York Times for the timespan from March 24, 1989, to September 1, 2017. Results: The results show that the proposed model can be replicated, after some adjustments. Conclusion: We conclude that, despite the complexity of an analysis of this kind in which the model is applied considering isolated words in the text and not the semantic aspects, the proposed model based on fuzzy logic is adequate for the analysis of social corporate responsibility.We would like to thank professors Mariana Claudia Broens, Jose Arthur Quilici Gonzalez and Maria Eunice Quilici Gonzalez for the helpful supervision and indications during the fundamental stages of this research. This paper was supported by the "Understanding opinion and language dynamics using massive data", funded by The São Paulo Research Foundation - FAPESP (reference: 2016/50256-0) (Trans-Atlantic Platform Social Sciences and Humanities, Digging into Data Challenges). We would like to thank the whole team of this project for their discussion and feedback. Ana Claudia Golzio also received support by FAPESP (process number: 2019/08442-9) during the development of this paper, and Mirelys Puerta-Díaz received funding from Coordination for the Improvement of Higher Education Personnel (CAPES) - Financial Code 001

Identification of the HSP70-II gene in Leishmania braziliensis HSP70 locus: genomic organization and UTRs characterization

<p>Abstract</p> <p>Background</p> <p>The heat stress suffered by <it>Leishmania sp </it>during its digenetic life-cycle is a key trigger for its stage differentiation. In <it>Leishmania </it>subgenera two classes of <it>HSP70 </it>genes differing in their 3' UTR were described. Although the presence of <it>HSP70</it>-<it>I </it>genes was previously suggested in <it>Leishmania (Viannia) braziliensis</it>, <it>HSP70</it>-<it>II </it>genes had been reluctant to be uncovered.</p> <p>Results</p> <p>Here, we report the existence of two types of <it>HSP70 </it>genes in <it>L. braziliensis </it>and the genomic organization of the <it>HSP70 </it>locus. RT-PCR experiments were used to map the untranslated regions (UTR) of both types of genes. The 3' UTR-II has a low sequence identity (55-57%) when compared with this region in other <it>Leishmania </it>species. In contrast, the 5' UTR, common to both types of genes, and the 3' UTR-I were found to be highly conserved among all <it>Leishmania </it>species (77-81%). Southern blot assays suggested that <it>L. braziliensis </it><it>HSP70 </it>gene cluster may contain around 6 tandemly-repeated <it>HSP70</it>-<it>I </it>genes followed by one <it>HSP70</it>-<it>II </it>gene, located at chromosome 28. Northern blot analysis indicated that levels of both types of mRNAs are not affected by heat shock.</p> <p>Conclusions</p> <p>This study has led to establishing the composition and structure of the HSP70 locus of <it>L. braziliensis</it>, complementing the information available in the GeneDB genome database for this species. <it>L. braziliensis </it><it>HSP70 </it>gene regulation does not seem to operate by mRNA stabilization as occurs in other <it>Leishmania </it>species.</p