Towards gender equality in engineering programs. A case study

The low participation of women in STEM fields is considered a critical issue in our society. We analyzed the student population by gender of the school of engineering at Universidad Tecnologica de Bolivar. We found that the share of female first-time students shows a decreasing trend since 2015 and was only 24% in 2020. Gender gaps are wider in electrical, electronic, systems, mechanic, and mechatronic engineering. We also observed that females have lower access to engineering programs, especially in the last three years. The effects of the COVID-19 pandemic have been observed as a reduction of the share of enrolled students vs applicants. In order to increase the participation of women in the programs with higher gender gaps, we developed several activities in 2020 specially designed for secondary students with the participation of female instructors as role models.

COVID-19 Severity Classification Using a Hierarchical Classification Deep Learning Model

One of the most important situations in recent years has been originated by the 2019 Coronavirus disease (COVID-19). Nowadays this disease continues to cause a large number of deaths and remains one of the main diseases in the world. In this disease is very important the early detection to avoid the spread, as well as to monitor the progress of the disease in patients, and techniques of artificial intelligence (AI) is very useful for this. This is where this work comes from, trying to contribute in the study to detect infected patients. Drawing inspiration from previous work, we studied the use of deep learning models to detect COVID-19 and classify the patients with this disease. The work was divided into three phases to detect, evaluate the percentage of infection and classify patients of COVID-19. The initial stage use CNN Densenet-161 models pre-trained to detects the COVID-19 using multi-class X-Ray images (COVID-19 vs. No-Findings vs. Pneumonia), obtaining 88.00% in accuracy, 91.3% in precision, 87.33% in recall, and 89.00% in F1-score. The next stage also use CNN Densenet-161 models pre-trained to evidenced the percentage of infection COVID-19 in the different CT-scans slices belonging to a patient, obtaining in the evaluation metrics a result of 0.95 in PC, 5.14 in MAE and 8.47 in RMSE. The last stage creates a database of histograms of different patients using their lung infections and classifies them into different degrees of severity using K-Means unsupervised learning algorithms with PCA. © 2022, Springer Nature Switzerland AG.

Phenomenon-Brand? Visual identity for developing events. The case of COVID-19

This essay looks into the construction of brands to represent socio-cultural phenomena, specifically, by the media about developing news. It discusses the use of branding strategies and its relation to the traditional concept of brand. And, it analyses this kind of brands from three perspectives, based on the case of the Coronavirus, COVID-19: from its practical use, from the naturalization of its use, and from its potential discursive use.

Coronavirus first wave effect on antibiotic consumption and antimicrobial resistance

Background and importance In the absence of evidence about the incidence of bacterial co-infection, antibiotic treatment was widely prescribed to prevent this potential complication. Increasing antibiotic consumption could have exerted an ecological pressure on microorganisms with potential clinical implications that need to be examined. Aim and objectives The aim of this study was to analyse antibiotic consumption and antimicrobial resistant microorganism isolates during the peak incidence of the COVID-19 first wave at our hospital. Material and methods An observational, descriptive, cross sectional study was carried out. Antibiotic consumption data for March and April 2020 and 2019 were analysed. Defined daily dose (DDD) per 100 bed days was used as the consumption indicator and changes were expressed in absolute and percentage terms. Isolates of Enterobacteriaceae (Escherichia coli and Klebsiella pneumoniae) were examined for March and April 2020 and compared with the average over 2019. Extended spectrum beta-lactamase (ESBL) producing Enterobacteriaceae were expressed in relative terms over their total isolates. Results For the period under study, antibiotic consumption increased from 79.94 to 141.10 DDD/100 bed days in 2020, which was an increase of 77%. Macrolides and cephalosporins were among the groups of antibiotics with the highest consumption, representing 37% (52.79 DDD/100 bed days) and 32% (45.41 DDD/100 bed days) of total consumption, respectively, and almost 70% jointly. Additionally, ceftriaxone and azithromycin showed an increase in DDD/100 bed days of 4.5× (8.91 vs 39.97) and 27.4× (1.89 vs 51.90) with respect to the same period in 2019. The share of ESBL producing Escherichia coli was 12% (13/111 isolates) and 23% (20/87 isolates) in March and April 2020 compared with an average of 11% (273/2494 isolates) in 2019. ESBL producing Klebsiella pneumoniae was 23% (8/ 35 isolates) and 57% (25/44 isolates) in March and April 2020 versus 24% (153/642 isolates) on average in 2019. Conclusion and relevance During the study period, antibiotic consumption increased markedly. The increasing use of third generation cephalosporins, which have no effect on ESBL producing Enterobacteriaceae, may have contributed to the observed changes in the bacterial ecology in our hospital. As the incidence of bacterial co-infection on admission was reported to be lower than 5% and the increase in antibiotic consumption translated into selection of antibiotic resistant bacteria, it is important to properly assess antibiotic treatment for each particular case in future outbreaks of SARS-CoV-2 infections.

Intervention by the Clinical Psychology team from the Liaison Unit of the IPS Gregorio Maranon during the COVID-19 crisis

The Covid-19 pandemic is generating an array of psychological difficulties in survivors, families and first-line health professionals. The need for psychological interventions within the hospital has led to the increase in the capacity of the Clinical Psychology Liaison Service in the Gregorio Maraiion General University Hospital. The crisis intervention model has underpinned the organization of the care, with a focus on preventing complicated grief and post-traumatic stress disorder. In this paper, the most frequently reported psychological difficulties are outlined and the interventions carried out in the service are described (reduced groups for professionals, face-to-face and telephone-based interventions with patients, families and professionals, crisis intervention, consulting role of the physicians and nurses, etc.).