ABSTRACT
Objective The COVID-19 pandemic has highlighted the racial disparities in health outcomes within our nation. This is especially relevant in the field of radiology where the lack of minority representation is particularly striking. The purpose of this paper is to describe a pipeline program designed to support underrepresented minority (URM) students and provide a model to bridge URMs to careers in medicine hence cultivating health equity. Methods We designed a radiology pipeline program within The Travelers Summer Research Fellowship Program (TSRF) to give underrepresented students an opportunity to engage with radiologists. Participants experience a rich inquiry-based curriculum and completed pre- and post-intervention surveys that measured motivational factors for medical education and interest level in medical careers. Results 29 undergraduate students participated in the 2021 TSRF Program. The data comparing the pre- and post-surveys demonstrated that the TSRF program played a positive role in sparking interest in radiology, debunking misperceptions about radiologists, and boosting participant confidence regarding medical school applications. Discussion We created an interactive curriculum for URM students to cultivate a new generation of radiologists that will reflect and better meet the needs of the populations they are serving thereby mitigating the current health disparities in our nation.
ABSTRACT
Fighting against climate change and global warming is one of the biggest challenges faced by the Maritime Industry nowadays to make the supply chain greener and environmentally sustainable. Cutting greenhouse gases (GHG) emissions and decarbonizing the international shipping has been a paramount activity for the International Maritime Organization (IMO) since the first set of international mandatory measures to improve ships' energy efficiency and reduce CO2 emissions per transport work, as part of the International Convention for the Prevention of Pollution from Ships (MARPOL) released in 2011. Besides that, changes in consumption habits around the globe (i.e., digitalization and growth of e-commerce) plus disruptive events like the COVID-19 or the blocking of the Suez Canal, to name only a few, have also highlighted the need for building more resilient maritime transport networks. In this work, a pragmatical analysis of the principal machine learning algorithms has been carried out to provide a qualitative prediction of the Estimate Time of Arrival (ETA) of container vessels applied to short-sea shipping where the distance between ports is reduced. By exploiting both, the Automatic Identification System (AIS) and meteorological data gathered over a desired area of interest, the developed approach delivers a model capable of predicting the ETA of ships where the reaction time of the stakeholders involved in the management of the Port Call is very reduced (i.e., less than two hours of sailing between ports) and therefore, tolerance for error is low. Very positive results were obtained for the training dataset collected under real conditions for more than a year. The best results were obtained by the RF model with a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 11.31 and 19.56 minutes respectively. © 2003-2012 IEEE.
ABSTRACT
Currently, information and Communication Technologies (ICT) have developed rapidly, becoming evident, especially after the beginning of the SARS Covid-19 virus pandemic. As a measure to reduce the number of people infected by the disease, the National Health System (SNS) started to require the COVID Digital Certificate, so that the citizen has access to certain places. The present study is a qualitative methodology, action-research, and aims to evaluate the difficulties that the elderly find to access the COVID Digital Certificate, through the application made available by the SNS, and evaluate the benefits of the Iconographic Tutorial/ Certdigit@l. © 2022 IEEE Computer Society. All rights reserved.
ABSTRACT
The context of the pandemic we experienced, caused by COVID-19, implied the adoption of several measures, in an attempt to limit its dissemination. Among which, there is social isolation and the prohibition of visits to institutionalized elderly people. These measures favor the worsening or onset of mental illnesses in the elderly, including depression. As a way to reduce these consequences, video calls began to be made in the institutions so that users could see and talk to their family/friends. For the realization of video calls, the informal caregivers began to request the WhatsApp application, because it is currently the most used application in this context. This is how we get to the question of this study: Is the digital application WhatsApp adapted for the institutionalized elderly population? This study then aims to: to know the opinion of the elderly about WhatsApp;identify the advantages, obstacles, limitations pointed out by them about this application;reduce the infoexclusion among the elderly population;stimulate the creation/maintenance of digital social networks;decrease consequences of the isolation caused by COVID-19. The methodology adopted for this study was qualitative, being an Exploratory Case Study, based on descriptive logic. A non-probabilistic convenience sample was selected, composed of 5 subjects institutionalized in an institution of Idanha-a-Nova. For data collection, a characterization questionnaire was applied, and the participant was observed in the interaction with WhatsApp, during which the field notes and observation grid were registered and finally the Focus Group technique was used. It was concluded that the application and the equipment itself are not adapted to the institutionalized elderly belonging to this study, mainly due to the difficulty in accessing effectively, efficiently and satisfactorily. © 2021 AISTI.