Retention of survival swimming skills among SwimSafe graduates in rural communities of Bangladesh: Results from a cross-sectional study.

Background: Drowning is the leading cause of death among children in rural Bangladesh. While survival swimming for children ages 6 years and above is recommended in low-income and middle-income countries, research into the long-term retention of survival swimming skills is absent.

Methods: The retention of four survival swimming skills, including swimming for 25 m, floating/treading for 30 s, reach rescue skills and throw rescue skills, was observed among those trained under the SwimSafe programme more than 10 years ago.

Caregivers' Compliance and Perception of Daycare Centers-A Community-Based Childhood Drowning Prevention Intervention Implemented in Rural Bangladesh.

Drowning was one of the most prevalent causes of death worldwide for children under five in 2020. Drowning was the second leading cause of death for children under five in Bangladesh, while 58% of all deaths in the 1-5 years old age group resulted from drowning. Adult supervision helps prevent child drowning in rural areas where water bodies are easily accessible and located very close to homes.

Compliance to playpen usages to enhance parental supervision of under-five children in rural community of Bangladesh.

Introduction: In Bangladesh, injury is one of the leading causes of death and morbidity in children. All children under 5 years of age are at high risk for drowning though the risks are highest when children first learn to walk and crawl while they do not understand the danger of water. The Centre for Injury Prevention and Research, Bangladesh (CIPRB) in collaboration with Johns Hopkins International Injury Research Unit (JH-IIRU) has been implementing two drowning prevention interventions, providing playpens and community day care centres (anchal), or both in three rural sub-districts of Bangladesh under Saving of Lives from Drowning (SoLiD) project in Bangladesh.

Detecting COVID-19 Pneumonia over Fuzzy Image Enhancement on Computed Tomography Images.

COVID-19 is the worst pandemic that has hit the globe in recent history, causing an increase in deaths. As a result of this pandemic, a number of research interests emerged in several fields such as medicine, health informatics, medical imaging, artificial intelligence and social sciences. Lung infection or pneumonia is the regular complication of COVID-19, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) and computed tomography (CT) have played important roles to diagnose the disease.

Challenges in Preventive Practices and Risk Communication towards COVID-19: A Cross-Sectional Study in Bangladesh.

Bangladesh recently experienced a COVID-19 second wave, resulting in the highest number of new cases and deaths in a single day. This study aims to identify the challenges for COVID-19 preventive practices and risk communications and associated factors among Bangladeshi adults. A cross-sectional survey was conducted between December 2020 and January 2021 involving 1382 Bangladeshi adults (aged ≥ 18-years) in randomly selected urban and rural areas from all eight divisions in Bangladesh.

A Comprehensive Study of Artificial Intelligence and Machine Learning Approaches in Confronting the Coronavirus (COVID-19) Pandemic.

The novel coronavirus disease (COVID-19) has spread over 219 countries of the globe as a pandemic, creating alarming impacts on health care, socioeconomic environments, and international relationships. The principal objective of the study is to provide the current technological aspects of artificial intelligence (AI) and other relevant technologies and their implications for confronting COVID-19 and preventing the pandemic's dreadful effects. This article presents AI approaches that have significant contributions in the fields of health care, then highlights and categorizes their applications in confronting COVID-19, such as detection and diagnosis, data analysis and treatment procedures, research and drug development, social control and services, and the prediction of outbreaks.

Predictors of non-fatal violence or assault among adolescents in rural Bangladesh: cross-sectional study.

Objective: To determine the predictors of non-fatal violence or assault among adolescents in rural Bangladesh to inform evidence-based interventions.

Design: Cross-sectional study.

Setting: Household survey and national census in 51 unions of rural Bangladesh.

Oral Hygiene Awareness and Practices among a Sample of Primary School Children in Rural Bangladesh.

Inadequate oral health knowledge and awareness is more likely to cause oral diseases among all age groups, including children. Reports about the oral health awareness and oral hygiene practices of children in Bangladesh are insufficient. Therefore, the objective of this study was to evaluate the oral health awareness and practices of junior school children in Mathbaria upazila of Pirojpur District, Bangladesh.

Animal-related injuries and fatalities: evidence from a large-scale population-based cross-sectional survey in rural Bangladesh.

Objective: This study determines the magnitude and pattern of animal-related injury mortalities and morbidities in rural Bangladesh.

Design And Setting: A cross-sectional survey was conducted in 51 Unions of 7 subdistricts of Bangladesh from June 2013 to September 2013.

Participants: A total of approximately 1.

On fuzzy semantic similarity measure for DNA coding.

A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemical attributes of nucleotides have been proposed in recent decades. Such coding measure schemes lack the biologically meaningful aspects of nucleotide data and hence do not significantly discriminate coding regions from non-coding regions.

Transfer between pose and illumination training in face recognition.

The relationship between pose and illumination learning in face recognition was examined in a yes-no recognition paradigm. The authors assessed whether pose training can transfer to a new illumination or vice versa. Results show that an extensive level of pose training through a face-name association task was able to generalize to a new illumination (Experiments 1 and 3), but an equal level of illumination training failed to generalize to a new pose (Experiment 2).