Search Results (807)

Ongoing changes in the distribution and abundance of several tick species of medical relevance in Canada have prompted the development of the eTick platform—an image-based crowd-sourcing public surveillance tool for Canada enabling rapid tick species identification by trained personnel, and public health guidance based on tick species and province of residence of the submitter. Considering that more than 100,000 images from over 73,500 identified records representing 25 tick species have been submitted to eTick since the public launch in 2018, a partial automation of the image processing workflow could save substantial human resources, especially as submission numbers have been steadily increasing since 2021. In this study, we evaluate an end-to-end artificial intelligence (AI) pipeline to support tick identification from eTick user-submitted images, characterized by heterogeneous quality and uncontrolled acquisition conditions. Our framework integrates (i) tick localization using a fine-tuned YOLOv7 object detection model, (ii) resolution enhancement of cropped images via super-resolution Generative Adversarial Networks (RealESRGAN and SwinIR), and (iii) image classification using deep convolutional (ResNet-50) and transformer-based (ViT) architectures across three datasets (12, 6, and 3 classes) of decreasing granularities in terms of taxonomic resolution, tick life stage, and specimen viewing angle. ViT consistently outperformed ResNet-50, especially in complex classification settings. The configuration yielding the best performance—relying on object detection without incorporating super-resolution—achieved a macro-averaged F1-score exceeding 86% in the 3-class model (Dermacentor sp., other species, bad images), with minimal critical misclassifications (0.7% of “other species” misclassified as Dermacentor). Given that Dermacentor ticks represent more than 60% of tick volume submitted on the eTick platform, the integration of a low granularity model in the processing workflow could save significant time while maintaining very high standards of identification accuracy. Our findings highlight the potential of combining modern AI methods to facilitate efficient and accurate tick image processing in community science platforms, while emphasizing the need to adapt model complexity and class resolution to task-specific constraints. Full article

Background: Quality care of individuals with sickle cell disease (SCD) is dependent upon education of the providers on their care team. Previous studies demonstrate lack of resident and provider comfort regarding care of patients with SCD, yet none have assessed these in medical students. Objective: This study aims to evaluate the adequacy of the research instrument for measuring medical students’ knowledge, confidence, and comfort regarding SCD and related complications prior to wider distribution. Methods: A self-assessment survey was distributed to medical students at two universities to evaluate their knowledge, confidence, and comfort in general SCD topics, in all clinical settings, and regarding common complications. Results: Of the 98 responses, knowledge (p < 0.001) and confidence (p = 0.02) were significantly different between topics, including epidemiology and genetics, pathophysiology, and treatment options. For “treatment options”, there were significant differences in knowledge (p = 0.02) and confidence (p = 0.02) between medical students at different levels of training. Students felt least knowledgeable and least comfortable with care of pregnant women and most knowledgeable and most comfortable with acute pain management. Caring for patients with specific SCD-related conditions increased knowledge and comfort across all domains. Conclusions: This instrument was adequate for measuring knowledge, confidence, and comfort in caring for those with SCD across all clinical settings. We identified a lack of knowledge, confidence, and comfort regarding treatment for those with SCD starting early in medical careers, which improves after caring for patients with various complications. Thus, educating and providing SCD patient experiences is crucial for medical student management confidence related to SCD. Full article

Recent years have seen frequent heavy rainfall events in Japan, often linked to Baiu fronts and typhoons. These events are exacerbated by global warming, leading to an increased frequency and intensity. As floods represent a serious threat to sustainable urban development and community resilience, this study contributes to sustainability-focused risk reduction through integrated analysis. This study focuses on the 2 June 2023 heavy rain disaster in Toyohashi City, Japan, which caused extensive damage due to flooding from the Yagyu and Umeda Rivers. Using numerical models, this study accurately reproduces flooding patterns, revealing that high tides amplified the inundation area by 1.5 times at the Yagyu River. A resident questionnaire conducted in collaboration with Toyohashi City identifies key trends in evacuation behavior and disaster information usage. Traditional media such as TV remain dominant, but younger generations leverage electronic devices for disaster updates. These insights emphasize the need for targeted information dissemination and enhanced disaster preparedness strategies, including online materials and flexible training programs. The methods and findings presented in this study can inform local and regional governments in building adaptive disaster management policies, which contribute to a more sustainable society. Full article

This study investigates the encroachment risk in the Makause informal settlement by analysing resident survey data to identify key contributing factors and build predictive models. Encroachment threatens the water infrastructure through damage, contamination, and service disruptions, highlighting the need for informed, community-based planning. The data was collected from 105 residents, with responses (“Yes,” “No,” “Unsure”) analysed using descriptive statistics and a one-way ANOVA to identify significant differences across categories. The ReliefF algorithm was used to rank the importance of features predicting the encroachment risk. These inputs were then used to train, validate, and test an Artificial Neural Network (ANN) model. The Artificial Neural Network demonstrated a high predictive accuracy, achieving correlation coefficients above 95% and low mean squared errors. The ANOVA identified statistically significant mean differences for selected variables, while ReliefF helped determine the most influential predictors. A high agreement level (p > 0.900) between predicted and actual responses confirmed the model’s validity. This research introduces an innovative, data-driven framework that integrates machine learning and a statistical analysis to support municipalities and utility providers in engaging informal communities to protect infrastructure. While this study is limited to Makause and may be affected by a self-reported bias, it demonstrates the potential of Artificial Neural Networks and ReliefF in enhancing the risk analysis and infrastructure management in informal settlements. Full article

Currently, the role of a university in promoting the development of rural areas has been emphasized. However, an increase in academic training can lead to a growth in rural migration due to the lack of job opportunities for university graduates. Given the scarcity of studies on the impact of higher education institutions in areas at risk of depopulation, a research study has been conducted with university students residing in Castilla y León (Spain) in order to understand their insights on the benefits that university education can bring to rural areas, as well as to comprehend the reasons that would motivate the migration of university students or even the interest of institutions in addressing the issue of depopulation. The results achieved suggest that an increase in education could help slow down this process, with the proximity of the university being a decisive factor for population settlement. Additionally, while the shortage of job opportunities would be the main cause of migration, there would also be other factors contributing to depopulation, such as lack of leisure or services, despite a will to stay. Finally, the survey respondents expressed skepticism about the institutions’ interest in addressing this problem. Full article

Objectives: Older adults who worry about not being able to stand up from the floor after a fall, reduce their physical activity, which leads to a higher risk of falling. The Backward Chaining Method (BCM) was developed specifically for this population to safely teach and practice the movement sequence required to stand up from the floor. Our aim is to evaluate the effectiveness of using the BCM to teach older adults how to stand up from the floor, and to determine whether this training has an impact on functional mobility, muscle strength, fear of falling, and life-space mobility. Methods: A total of 26 residents of a long-term care facility were randomly allocated to two groups. Residents in the intervention group (IG, n = 13) participated in a seven-week training program to learn how to stand up from the floor with BCM, in addition to the usual care generally offered in long-term care facilities. The participants in the control group (CG, n = 13) received the usual care alone. The primary outcome measure was functional mobility, assessed by the Timed Up and Go test. Secondary outcome measures included functional lower limb strength, grip strength, fear of falling, and life-space mobility. The outcomes were measured at baseline and after the seven-week intervention period. Results: We found no significant between-group differences in functional mobility, lower limb strength and grip strength; however, IG subjects demonstrated significantly lower fear of falling scores, and significantly higher life-space mobility and independent life-space mobility scores compared to CG subjects after the training program. Conclusions: This study demonstrates that the Backward Chaining Method is a feasible, well-tolerated intervention in a long-term care setting and it may have meaningful benefits, particularly in lessening fear of falling and improving life-space mobility and independent life-space mobility when incorporated into the usual physiotherapy interventions. Full article

High-speed trains have revolutionized modern transportation with their exceptional speeds, yet the essence of this technological breakthrough resides in the train’s wheels. These components are engineered to endure extreme mechanical stresses while ensuring high safety and reliability. In this paper, we selected the rim and web as representative components of the wheel and conducted a comprehensive and systematic study on their microstructure and mechanical properties. The wheels are typically produced through integral forging. To improve the mechanical performance of the wheel/rail contact surface (i.e., the tread), the rim is subjected to surface quenching or other heat treatments. This endows the rim with strength and hardness second only to the tread and lowers its ductility. This results in a more isotropic structure with improved fatigue resistance in low-cycle and high-cycle regimes under rotating bending. The web connects the wheel axle to the rim and retains the microstructure formed during the forging process. Its strength is lower than that of the rim, while its ductility is slightly better. The web satisfies current property standards, although the microstructure suggests further optimization may be achievable through heat treatment refinement. Full article

Healthcare abuse is a critical human rights and public health issue, particularly impacting medical interns and trainees who are vulnerable to mistreatment during their formative professional years. This cross-sectional study, conducted from February to June 2024, evaluated the prevalence and psychological impact of harassment and discrimination among 463 healthcare interns in Saudi Arabia from various specialties, including medicine, nursing, pharmacy, and dentistry. Using a self-administered online questionnaire, we found that mistreatment was widely reported, with female interns experiencing significantly higher rates of sexual harassment and gender-based discrimination. Common perpetrators included residents, lecturers, professors, nurses, and patients, with incidents most frequently occurring in surgical and internal medicine departments. Despite high prevalence, only 9% of interns reported the abuse due to mistrust in reporting systems or failure to recognize the behavior as abuse. These experiences were associated with significant psychological distress, including frustration, reduced motivation to learn, and higher DASS scores, particularly among female interns. The study underscores the need for institutional reforms, including policy development, cultural change, and effective reporting systems to ensure a safe and supportive learning environment for future healthcare professionals. Addressing abuse in medical training is essential for individual well-being and the sustainability and integrity of healthcare systems. Full article

Background/Objectives: Migraine affects approximately 3–10% of school-aged children and up to 28% of adolescents, with prevalence increasing during adolescence. For pediatric specialty providers, increased awareness of this condition may influence patient care. This study examined pediatric dentists’ education, clinical exposure, and perceived knowledge gaps related to pediatric migraine, with the goal of identifying barriers to recognition and referral, as well as informing future training to support accurate diagnosis and interdisciplinary care. Methods: A 28-item electronic questionnaire was distributed to all members of the American Academy of Pediatric Dentistry, including pediatric dentists and postgraduate pediatric dental residents, assessing knowledge, beliefs, clinical experience, and interest in further training regarding pediatric headache/migraine management. Respondents with and without previous training were compared in terms of general understanding using t-tests; a linear regression model analyzed predictors of provider awareness regarding links between oral conditions and headache/migraine. Results: Among 315 respondents, the mean self-perceived awareness score was 2.7 ± 1.3 (on a 0–5 scale). The most frequently identified contributing factors were clenching (73.7%), bruxism (72.4%), and temporomandibular disorders (65.7%). Nearly all respondents (95.2%) reported no formal education on headache/migraine prevention, yet 78.1% agreed on the importance of understanding the relationship between oral health and headache/migraine. Respondents with prior training were significantly more aware (p < 0.001) than those without prior training. Educating families (p < 0.001), frequency of patient encounters with headache (p = 0.032), coordination with healthcare providers (p = 0.002), and access to appropriate management resources (p < 0.001) were significant predictors of providers’ awareness. Conclusions: Pediatric dental providers expressed strong interest in enhancing their knowledge of headache/migraine management, highlighting the value of integrating headache/migraine-related education into training programs and promoting greater interdisciplinary collaboration. Full article

National parks represent a global initiative for biodiversity conservation and environmentally sustainable societal development, with China having launched its own national park program. The establishment and operation of these parks significantly impact local residents’ livelihoods. Based on DFID’s Sustainable Livelihoods Framework, an assessment tool introduced by the UK Department for International Development (DFID) for evaluating the livelihood standards of residents, this study constructs a structural equation modeling (SEM) framework to analyze how national parks affect residents’ livelihoods, discussing livelihood risk management and feasible capacity-building interventions. Focusing on the Northeast Tiger and Leopard National Park as a case study, the research reveals that indirect wildlife-inflicted damage poses more pronounced negative impacts on local communities than park establishment policies. Both regulatory land-use restrictions and wildlife conflicts disrupt land-based livelihood activities, ultimately affecting residents’ livelihood stability. Mitigation requires comprehensive measures, including retaining essential farmland; providing vocational skill training; offering specialized loans; diversifying employment channels; and improving compensation mechanisms to safeguard residents’ livelihood security. Full article

Regulatory air pollution monitoring is performed using a sparse monitoring network designed to provide background concentrations of pollutants but may miss small area variations due to local emission sources. Low-cost air pollution sensors operated by trained citizen scientists provide an opportunity to fill this gap. We describe the development and implementation of an air pollution monitoring and community engagement plan in response to resident concerns regarding excessive smoke production from a neighborhood restaurant. Particulate matter (PM_2.5) was measured using a low-cost, portable sensor. When cooking was taking place, the highest PM_2.5 readings were within 50 m of the source (mean PM_2.5 36.9 µg/m³) versus greater than 50 m away (mean PM_2.5 13.0 µg/m³). Sharing results with local government officials did not result in any action to address the source of the smoke emissions, due to lack of jurisdiction. A review of air pollution regulations across the United States indicated that only seven states regulate food cookers and six states specifically exempted cookers from air pollution regulations. Concerns about the smoke were communicated with the restaurant owner who eventually changed the cooking fuel. Following this change, less smoke was observed from the restaurant and PM_2.5 measurements were reduced to background levels. Although current environmental health regulations may not protect residents living near sources of food cooker-based sources of PM_2.5, community engagement shows promise in addressing these emissions. Full article

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

Background: Minimally invasive surgery (MIS) is increasingly adopted in pediatric surgical practice, yet it demands specific technical skills that require structured training. Simulation-based education offers a safe and effective environment for skill acquisition, especially in complex procedures such as thoracoscopic repair of esophageal atresia with tracheoesophageal fistula (EA-TEF). Objective: This study aimed to evaluate the effectiveness of a 3D-printed simulator for training pediatric surgeons in thoracoscopic EA-TEF repair, assessing improvements in operative time and technical performance. Methods: A high-fidelity, 3D-printed simulator replicating neonatal thoracic anatomy was developed. Six pediatric surgeons at different training levels performed eight simulation sessions, including fistula ligation and esophageal anastomosis. Operative time and technical skill were assessed using the Stanford Microsurgery and Resident Training (SMaRT) Scale. Results: All participants showed significant improvements. The average operative time decreased from 115.6 ± 3.51 to 90 ± 6.55 min for junior trainees and from 100.5 ± 3.55 to 77.5 ± 4.94 min for senior trainees. The mean SMaRT score increased from 23.8 ± 3.18 to 38.3 ± 3.93. These results demonstrate a clear learning curve and enhanced technical performance after repeated sessions. Conclusions: Such 3D-printed simulation models represent an effective tool for pediatric MIS training. Even within a short time frame, repeated practice significantly improves surgical proficiency, supporting their integration into pediatric surgical curricula as an ethical, safe, and efficient educational strategy. Full article

Background/Objectives: Injury prevention programs (IPPs) are evidence-based interventions that reduce musculoskeletal injuries in youth sports. Despite their proven benefits, the adoption of IPPs by coaches remains limited. This study aimed to evaluate the awareness, usage, and perceptions of IPPs among youth sports coaches in Poland and to identify factors associated with their implementation. Methods: A cross-sectional study was conducted using a web-based survey tailored to youth sports coaches in Poland. Coaches of athletes aged 9–17 were recruited through targeted outreach to clubs and professional networks. The survey assessed IPP awareness, implementation, perceptions, and sources of information. Statistical analyses included chi-square tests, non-parametric comparisons, Firth’s logistic regression, and cluster profiling. Results: Only 54.6% of coaches (59 out of 108) were aware of IPPs, and among them, just 47.5% reported using them. No significant associations were found between IPP use and demographic variables such as gender, sport, or place of residence. Coaches who were aware of IPPs were significantly younger than those who were unaware (p = 0.029). The information source was the strongest predictor of IPP implementation: coaches trained via formal courses were over 20 times more likely to use IPPs compared to those learning from peers (OR = 20.4, p < 0.001). While coaches generally perceived IPPs as beneficial for fitness and recovery, 28.6% expressed doubts about their effectiveness in reducing injury risk. Conclusions: Despite broadly positive beliefs, only 47.5% of coaches who were aware of IPPs reported using them. Formal training significantly enhances the likelihood of adoption. These findings emphasize the need for structured educational efforts and improved dissemination strategies to promote evidence-based injury prevention in youth sports settings. Full article

Background: Residency training is a formative and rigorous experience, with burnout rates reported at 76%. Formal peer support groups have shown improvement in burnout among healthcare workers with anxiety and depression. Objective: Implement a peer support program for emergency medicine (EM) residents and characterize utilization of metrics by demographics, burnout rates of participants, and overall session impact. Methods: An IRB-approved, longitudinal, prospective cohort study of 73 EM and EM/Pediatrics residents post-graduate year (PGY) 1–5 from July 2021–June 2022 was performed. Resident peer leaders were trained using a novel curriculum to lead peer support groups. Residents were invited to participate in biweekly sessions, with optional pre- and post-session surveys measuring demographics, burnout, themes discussed, and how they felt after sessions (Patients’ Global Impression of Change scale). Results: There were 134 attendances over 20 sessions, averaging 6 residents per session. Of 73 total residents, 37 (50%) participated at least once. All levels of training were represented, with half being female, 20% underrepresented in medicine, and 14% LGBTQ+. Overall burnout rates were unchanged for first-time attendances (49%, n = 18) vs. recurrent (50%, n = 11). Females had higher burnout at both baseline (60%, n = 15) and recurrent sessions (69%, n = 13). Following sessions, 94% of participants reported feeling immediately better and 100% of leaders felt prepared leading peer support sessions. Conclusions: This study demonstrates that residents utilize peer support, with many returning more than once. Despite stable burnout rates, 94% of participants felt immediately better after the session, suggesting that peer support is a valuable resource for residents actively experiencing burnout. Full article