Non-partisan school : a conservative education initiative in Brazil

The main goal of this article is to analyse the Non-Partisan School movement (EsP, or Escola sem Partido) which articulates social and political actors around a conservative agenda for education in Brazil. Based on Ball’s studies, this article analyses political governance networks using a free software, GEPHI, using a qualitative network methodology. The article analyses some relevant social actors in this conservative initiative. The research shows that the Non-Partisan School, though presented as an initiative against ideological indoctrination, is in fact the result of a strong combination of ideological, conservative and partisan interests. The article shows that EsP is a conservative agenda among other movements in the struggle for ideological hegemony in the educational field

From ad hoc to durable? Development cooperation and institutional bricolage in the cotton sector in Benin

This thesis is about the history of development encounters in the cotton sector in Benin. It presents a perspective that is centred on the long durée of the host context instead of the short-lived and specific experiences of each cotton project. I substantiate this change of perspective by addressing the following question: how has the cotton sector in Benin come to incorporate the institutional arrangements of development cooperation projects into enduring institutions? This thesis contends that development projects, although temporary and specific, are inserted into a historical continuum that has regularised development cooperation practices over time, and that is perpetuated by both implementers and hosts. Thus, while a project in isolation appears to be unable to change the wider structure and practices, successive processes of institutional bricolage with project components may. In the first three chapters, I describe the learning journey that led me to my research question and outline its relevance to contemporary debates on development. I go on to detail the conceptual framework and research methods. In the third chapter, I define the boundaries of my research, situating it in the history of Benin’s cotton sector since independence in 1960 until 2018. I identify the successive waves of development assistance projects taking place over this period. In chapters four to seven, I examine how development cooperation projects have shaped the structure and practices both of subsequent projects and of the cotton sector itself. The conclusion discusses and reviews my findings in light of my research question. It appears that institutional bricolage with projects’ institutional arrangements is a process shaped by power relations in which early experiences have particular weight. This research shows that the way projects work depends on their place in the historical trajectory of development cooperation in the host context. It thus contributes to our understanding of how projects work in a certain way and in a particular moment in time

A Comparative Study on Machine Learning Algorithms for Assessing Energy Efficiency of Buildings

© Springer Nature Switzerland AG 2021. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.1007/978-3-030-93733-1_41An increase in energy demand in buildings continues to give rise to air pollution with a consequent impact on human health. To curb this trend, energy efficiency assessment plays a crucial role in helping to understand the energy in buildings and to recommend strategies to improve efficiency. Unfortunately, many existing approaches to assessing the energy efficiency of buildings are failing to do it accurately. Hence, the recommended energy efficiency strategies thereafter are failing to achieve the expected result. One approach in recent times uses data-driven predictive analytics techniques like machine learning (ML) algorithms to assess a building's energy efficiency towards improving its performance. However, as many ML algorithms exist, the selection of the right one is important for a successful assessment. Unfortunately, many of the existing works in this regard have simply adopted an ML algorithm without a justified rationale which may result in poor selection of the good performing ML algorithm. Therefore, in this study, a premise to compare the performance of ML algorithms for the assessment of energy efficiency of buildings was proposed. First, consolidated energy efficiency ratings of buildings from different data sources are used to develop predictive models using several ML algorithms. Thereafter, identification of best performing model was done by comparing evaluation metrics like RMSE, R-Squared, and Adjusted R-Squared. From the comparison, Extra Trees predictive model came top with RMSE, R-Squared, and Adjusted R-Squared of 2.79, 93%, and 93% respectively. This approach helps in the initial selection of suitable and better-performing ML algorithms

A new methodology to predict damage tolerance based on compliance via global-local analysis

Over the years several design philosophies to fatigue developed in order to combine structural safety and economy to manufacturing and operating aircraft process. The safe-life approach, which consists of designing and manufacturing a safe aeronautical structure throughout its useful life, results in factors that oversize the structural elements, preventing the possibility of failure and evidently leading to high design costs. On the other hand, the approach based on the damage tolerance concept, in which it is assumed that the structure, even whether damaged, is able to withstand the actions for which it was designed until the detection of a crack due to fatigue or other defects during its operation. Here, we propose a new methodology to the damage tolerance problem in which two-dimensional global-local analysis at different levels of external requests will be made by means of compliance, aimed at finding a relationship between fatigue life and the Paris constant. Moreover, the BemCracker2D program for simulating two-dimensional crack growth is used. This methodology has been proved to be an efficient and applied alternative in the damage tolerance analysis

A neurofeedback protocol to improve mild anxiety and sleep quality

Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Univ Fed Sao Paulo UNIFESP, Dept Psiquiatria, Sao Paulo, SP, BrazilUniv Fed Sao Paulo UNIFESP, Dept Psiquiatria, Sao Paulo, SP, BrazilFAPESP: 2015/3931-0Web of Scienc

Comparison of Machine Learning Algorithms for Evaluating Building Energy Efficiency Using Big Data Analytics

© 2022, Emerald Publishing Limited. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1108/jedt-05-2022-0238Purpose: This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings. Design/methodology/approach: This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics. Findings: Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting. Research limitations/implications: While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK. Practical implications: This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system. Originality/value: This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.Peer reviewe

Biofortificação com lítio em plantas de alface via adubação foliar

It is known that the application of increasing doses of Li promotes the increase of Li in the plants, resulting in its biofortification. However, the influence of this element on the dry mass of the aerial part of the plants is reported in the literature in a contradictory way. In this way, the objective of this work was to systematically review and analyze the studies comparing the different effects of Li on shoot dry mass in order to obtain answers on the effect of this element on plants. A quantitative meta-analysis of 16 English-language articles published in the period between 1941 and 2018 was carried out, despising dissertations, theses, books or articles of low impact. The articles were selected based on the objective of this meta-analysis and through the potential of the Qualis analysis and the Journal Citation Reports (JCR). The variable MSPA stratified in function of Li doses was adjusted to the cultivation mode, species or cultivated genotype and plant age. Based on the information contained in the articles of this meta-analysis it was possible to observe the occurrence of four response patterns for the application of Li in cultures, the most representative is the linear increase (+) in Li contents in shoot dry mass and linear reduction (-) in the shoot dry mass of the crops in the same condition. Through the meta-analysis it was possible to verify that the application of Li in wild or agricultural crops suits to a quadratic response, an increase in shoot dry mass occurs, in smaller doses a reduction in these characteristics and in higher doses characterizing effect of toxicitySabe-se que a aplicação de doses crescentes de Li promove o aumento de Li nas plantas, resultando em sua biofortificação. Entretanto, a influência deste elemento na massa seca da parte aérea das plantas é relatada na literatura de forma contraditória. Desta forma, o objetivo deste trabalho foi revisar e analisar sistematicamente os estudos comparando os diferentes efeitos do Li na massa seca da parte aérea a fim de se conseguir respostas sobre o efeito deste elemento nas plantas. Foi realizado uma meta-análise quantitativa de 16 artigos no idioma inglês publicados no período entre 1941 e 2018, desprezando dissertações, teses, livros ou artigos de baixo conceito. Os artigos foram selecionados com base no objetivo desta meta-análise e através do potencial através da análise do Qualis e o Journal Citation Reports (JCR). A variável MSPA estratificadas em função das doses de Li foi ajustada para meio de cultivo, espécie ou genótipo cultivado e idade da planta. Baseado nas informações contida nos artigos desta meta-análise foi possível observar a ocorrência de quatro padrões de reposta para os efeitos da aplicação de Li em culturas, o mais representativo refere-se ao aumento linear (+) nos teores de Li na massa seca da parte aérea e redução linear (-) na massa seca da parte aérea das culturas na mesma condição. Através da meta-análise foi possível constatar que a aplicação de Li em culturas silvestres ou agrícolas se adequa significativamente a uma resposta quadrática, ocorre realmente um aumento na massa seca da parte aérea, em doses menores e uma redução nestas características em doses maiores caracterizando efeito de toxidade