Active learning: a new look at learning organizations

This article aims to analyze the national scientific production on andragogy, active learning and organizational learning, in the period from 2015 to 2021, in order to identify the contribution of distance education (DL) in the learning process to overcome the challenges faced by organizations today. To this end, a systematic literature review was conducted based on the protocol for selecting and analyzing sources defined by Cronnin, et al. (2008). The qualitative and quantitative research was carried out in journals classified as Qualis Capes A1 to B2, in the Web of Science database. Bibliometric mapping was used to analyze the publications and Iramuteq software was used to process the lexical data of the s of the selected articles. The results of the research point to distance education as a potential model for the educational process capable of working on different organizational competencies.

TEACHING-LEARNING RELATIONSHIPS IN THE CONTEXT OF POST-COVID-19 HYBRID EDUCATION

Purposes: This article seeks to understand the perception of the hybrid teaching system in the post-covid 19 context of the teachers of the National Polytechnic Institute. Theoretical reference: the research problematizes the hybrid teaching-learning relationship in the current context, taking as a reference the worsening of the educational crisis caused by the context of the Covid-19 pandemic. Method: From a qualitative approach, a survey was carried out seeking to know the perception of some teachers about hybrid teaching in the context of higher education of the Higher School of Computing of the National Polytechnic Institute. Results and conclusion: The results point to the difficulties encountered in this process, as well as the challenge to strengthen the hybrid skills of the teachers, and the use of teaching methodologies, as well as technologies to design better experiences based on the development of skills of both face-to-face students how much online. The Covid-19 pandemic highlights our educational weaknesses in terms of our study plans, pedagogical projects and didactic strategies for what we find ourselves in face of the need for a curriculum and didactic strategies that prioritize the reality of everyday life, reconozcan and face social and digital inequalities. Therefore, hybrid teaching-learning brings with it a change of paradigms for the teacher. Research implications: The research contributes from its theoretical review with reflections so that we reassess and plan other ways of teaching and learning in the post-covid19 world. Originality/value: The results obtained in this study are unprecedented, innovative and relevant to the scientific community, contributing mainly to the training of educators, especially environmental educators in crisis contexts. © 2023 ANPAD - Associacao Nacional de Pos-Graduacao e Pesquisa em Administracao. All rights reserved.

An In-depth Analysis on the Use of Long Short-term Memory Networks to Predict Incidence and Prevalence of Covid-19 in Latin America

The use of machine learning techniques, especially deep learning, could improve the predictions of the currently used epidemiological models for predicting Covid-19 in the short term. This information is essential for better decision making and to reduce the impacts of the disease spread in different countries. We explored the use of support vector regression (SVR) and long short-term memory networks (LSTM), the state of the art neural network architecture for time series analysis, to predict the daily incidence and prevalence for nine countries in Latin America. Our methodology and the models used can be replicated in other countries. Our main findings were: (i) there is no single best model or best hyperparameters configuration for all countries and targets;(ii) the LSTM showed an average MAE that was around 50% lower for incidence and 20% lower for prevalence when considering all countries;(iii) the LSTM showed better results for predicting incidence for most countries (Argentina, Bolivia, Brazil, Guatemala, and Haiti);(iv) the SVR showed better results for predicting prevalence for most countries (Argentina, Bolivia, Colombia, Cuba, Guatemala, and Haiti);and (v) for Brazil, the LSTM provided better results for both targets, with an MAE that was 68% lower for incidence and 73% lower for prevalence. © 2021 ACM.

Impact of COVID-19 in the screening and treatment of breast cancer in the Brazilian public health system: Data from a healthcare data warehouse

Background:Since December 2019, the world is facing a pandemic caused by a novel coronavirus (SARS-CoV-2). We sought to analyze the behavior of cancer treatments and procedures in breast cancer in Brazil after the beginning of the COVID-19 pandemic through an artificial intelligence platform with real life data. Methods:Data evaluation was performed using the TechTrials platform. This platform created a unique healthcare data warehouse containing hundreds of different publicly available data sources about Brazilian Public Health System and with proprietary technology, developed several analytics products that explore and release real-world data (RWD) insights. For this analysis data were extracted from DATASUS - SIA (outpatients information system). For each outcome, data from January 2011 to February 2020 were used to adjust a time series to predict values for March to November 2020. Those values were compared with the observed ones. Results: Biopsies, mammograms and procedures showed a sharp decrease (41.9%, 73.7% and 31.1%, respectively), in April 2020 (following month of the first COVID-19 case in Brazil) with some recovering in the following months. All observed values of biopsies, the number of mammograms from March to October and the number of procedures in April and May were significantly smaller than the predicted ones. Number of women undergoing chemotherapy began to decline in August and remained falling until the last month of available data.(Table). Conclusions: This study is the first one that analyzes RWD of breast cancer screening, diagnosis and treatment in Brazil as a result of the COVID-19 pandemic. The impact of the decrease observed in screening and diagnosis is already evident in the number of women undergoing chemotherapy. These data will continue to be monitored in the coming months when only then will data be available for staging at diagnosis. Observed and predicted values (in thounsands) of biopsies, mammograms, procedures and number of women undergoing chemotherapy for breast cancer.

Nano-targeting lessons from the SARS-CoV-2.

The lack of targeting efficacy has frequently led functionalized nanoparticles to accumulate in unwanted cells and tissues while boosting toxicity-related effects. Conversely, viruses are natural nanoparticles that precisely and responsively interact with the biological machinery through an effective-driven fashion. This interaction is enhanced by a meticulous spatial arrangement which results in a quasi-crystalline distribution of proteins on the viruses' surface. Amidst the COVID-19 pandemic, we propose to look at the SARS-CoV-2 nanoscale viral scaffold as an example of a highly-ordered architecture that must inspire and tailor the production of targeted synthetic nanoparticles.