Experiences, attitudes, and knowledge of medical students regarding intellectual and developmental disability: a Canadian study.

Background: As the healthcare of individuals with intellectual and developmental disabilities (IDD) shifts toward community-based services, physicians in all areas of medicine are more likely to care for this population. To ensure that all physicians can provide high-quality care to people with IDD, further understanding and attention to undergraduate medical education related to IDD is needed.

Methods: A 24-item survey assessed the experiences, attitudes, knowledge, skills, and future interest of Canadian medical students regarding IDD.

Predictors of mental well-being among family caregivers of adults with intellectual and developmental disabilities during COVID-19.

Background: Internationally, stresses related to the COVID-19 pandemic negatively affected the mental health of family caregivers of adults with intellectual and developmental disabilities (IDDs).

Aims: This cross-sectional study investigated demographic, situational and psychological variables associated with mental wellbeing among family caregivers of adults with IDDs during the COVID-19 pandemic.

Method: Baseline data from 202 family caregivers participating in virtual courses to support caregiver mental well-being were collected from October 2020 to June 2022 via online survey.

The experiences and attitudes of family caregivers of adults with intellectual and developmental disabilities at different timepoints in the COVID-19 pandemic.

Background: The COVID-19 pandemic has resulted in increased pressures for family caregivers of adults with intellectual and developmental disabilities (IDD). However, little is known about how their attitudes and perceptions have changed over the course of the pandemic.

Objective: To compare the COVID-19 experiences and attitudes of two groups of family caregivers, reported at different timepoints in the pandemic: prior to vaccine availability and after.

Guidelines are needed for studies of pre-treatment HIV drug resistance: a methodological study.

Background: The expansion of access to antiretroviral therapy (ART) has been accompanied by an increase in pre-treatment drug resistance (PDR). While it is critical to monitor the increasing prevalence of PDR across countries and populations to inform optimal regimen selection, the completeness of reporting is often suboptimal, limiting the interpretation and generalizability of the results. Indeed, there is no formal guidance on how studies investigating the prevalence of drug resistance should be reported.

An approach on the implementation of full batch, online and mini-batch learning on a Mamdani based neuro-fuzzy system with center-of-sets defuzzification: Analysis and evaluation about its functionality, performance, and behavior.

Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the methods for its processing have to adapt to this condition, focusing mainly on ensuring the computation is efficient, especially when the analysis tools are based on computational intelligence techniques. As we know, if you do not have a good control of the handling of the volume of the data, some techniques that are based on learning iterative processes could represent an excessive load of computation and could take a prohibitive time in trying to find a solution that could not come close to desired.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot.

Fuzzy Index to Evaluate Edge Detection in Digital Images.

In literature, we can find different metrics to evaluate the detected edges in digital images, like Pratt's figure of merit (FOM), Jaccard's index (JI) and Dice's coefficient (DC). These metrics compare two images, the first one is the reference edges image, and the second one is the detected edges image. It is important to mention that all existing metrics must binarize images before their evaluation.