ABSTRACT
This article describes a data science challenge-based learning experience introduced to non-IT second-year engineering students. The methodology proposed in this article was successful in the short introductory course. The students presented well-considered, practical solutions to two challenges of a different nature derived from excellent, quality data processing. The students used free-access databases from Airbnb and Johns Hopkins University to tackle both challenges. Although the students' data analysis methods corresponded more to data analytics, the two student teams incorporated Machine Learning techniques and exceeded our initial expectations. The selection of the programming environment for this experience was a crucial issue addressed in this article. To illustrate the students' work in the course using this methodology, we present a selection of their results, including a new index to measure the degree of herd immunity in a country, relating this index with the possible appearance of a new strain of COVID-19.
ABSTRACT
The pandemic caused by the coronavirus triggered the possibility of the crisis in several segments, especially with the adoption of social isolation, the main action for the control of the infectious disease, therefore, the present study is justified by the concern in relation to the trends of sustainable development in the post-pandemic of COVID-19, in the state of Rio Grande do Sul. Measuring the degree of sustainability of the municipalities follows the thesis that the greater the degree of sustainability of the municipalities, the less the impact of the pandemic, and the greater the resources to restore balance. The objective of the research is to analyze the spatial distribution of the potential for sustainability in the post-pandemic of COVID-19, in the municipalities of Rio Grande do Sul, in order to generate a risk map with less and greater potential for sustainability in the post-pandemic. This study was carried out by means of an ecological analysis and application of the Barometer of sustainability, later the distribution and spatial analysis was carried out by means of the Moran Index. The spatial analysis, performed by calculating the Moran Index, showed significant spatial independence for confirmed cases (I = 0.058;p = 0.024) and deaths (I = 0.032;p = 0.039), and a significant, albeit weak, correlation. for the incidence coefficient (I = 0.234;p = 0.001) of COVID-19. Spatiality does not explain the distribution of cases and deaths. However, when taking into account the population size of the municipalities, in relation to the number of cases, expressed by the incidence coefficient, the spatial aggregation gains merit. The potential for sustainability was estimated and the risk map of the potential for sustainability was generated, in the post-pandemic of COVID-19, for the municipalities of Rio Grande do Sul. © 2021, Universidade Federal de Pernambuco. All rights reserved.
ABSTRACT
Intended for Mexico, the 'Beautiful Patterns' young-women STEM bootcamp was created in 2017 at the Massachusetts Institute of Technology, finding a strategic partner in the Tecnológico de Monterrey, a recognized Mexican university. The idea behind 'Beautiful Patterns' is promoting the STEM majors as a future, promising and country-needed option for high school women students in economies like Mexico's where only 17% of the graduated engineering population are women. In 2021, this bootcamp will become international, including instructors and participants from Canada and some Latin American, European and Asian countries. In 2019, after having taken part in this program, 89% of the student participants stated that they had a different perspective about engineering and information technologies recognizing women's potential in STEM areas. The 2020 edition was canceled due to the pandemic of CoVid-19. In this paper we present all our results and conclusions of the 2019 implementation in Aguascalientes Campus of Tecnológico de Monterrey. © 2021 IEEE.
ABSTRACT
Background: Children and young adults were initially reported as largely spared from severe complications of SARS-CoV-2 infection, but the impact to this population has been significant. Methods: This observational retrospective cohort study includes 420 symptomatic children and young adults with lab confirmed SARS-CoV-2 infection treated between March 15 and June 16, 2020 at Children's National Hospital in Washington DC. We identified and compared cohorts of non-hospitalized (N=324) and hospitalized (N=96) patients, including non-critically ill (N=64) and critically ill hospitalized (N=32) patients. Clinical and demographic data were extracted from medical records Results: Of 420 SARS-CoV-2-infected symptomatic patients, 23% required hospitalization, of which 67% were non-critically ill and 33% were critically ill. All age groups were represented in the symptomatic cohort, with a median age of 8.6 years. Patients > 15 years of age represented 44% of critical care admissions. Males and females were equally represented in all cohorts. Underlying medical conditions were present in 36%, but more common in hospitalized (59 %) and critically ill (66 %) patients. The most frequent underlying diagnosis overall was asthma (16 %), but also included neurologic (6 %), diabetes (3 %), obesity (3 %), cardiac (3 %), hematologic (3 %) and oncologic (1 %) conditions. The majority (66 %) of SARSCoV- 2 infected patients presented with respiratory symptoms with or without fever. Other symptoms were also present, including diarrhea/vomiting (21 %), myalgia (11 %), chest pain (8 %) and loss of sense of smell or taste (7%). Hospitalized patients required varying levels of respiratory support, including mechanical ventilation, BiPAP, RAM cannula and HFNC. Additional presentations included diabetic hyperglycemia, sickle cell vaso-occlusive crisis, vascular complications, and multisystem inflammation. Treatment included remdesivir, convalescent plasma, tocilizumab and other therapies. Conclusion: Although children/young adults have been less affected than elderly adults, the impact of SARS-CoV2 on this population has been significant in Washington DC and informs other regions anticipating their surge.