Notes

School Achievement, Dependability, and Burnout within Family members Remedies Citizens.
Two-thirds of the world population do not have access to safe, affordable and timely surgery. This global surgical crisis largely affects low and middle-income countries, and it will surpass the challenges created by communicable diseases. The barriers of access to surgery range from cost of surgery and patient transportation to availability and quality of surgical infrastructure and providers. Mercy Ships is a Non-Governmental Organisation (NGO) providing free world-class life-saving and life-transforming surgery to the poorest of the poor in West Africa. In order to address barriers to access surgical assessment and care, Mercy Ships switched from centralised patient selection mainly in port cities or capitals to decentralised selection strategy staffed by experienced nursing teams travelling to remote locations nearer to patients' homes. In this way, the under-served rural population is given equal opportunity to access Mercy Ships' free specialised surgical services. In each country served by the Mercy ShD-19 pandemic. Moreover our state-of-art on-board simulation laboratories and traditional practical training of local healthcare providers will further enhance and build their medical capacity. The Global Mercy will become the largest floating and training platform to train next generation African medical and health care professionals so that they can save countless lives by training others in the future. We therefore invite you to partner with us in bringing hope and healing to the forgotten poor in West Africa.The combination of hydroxyapatite and the herbal extract ellagic acid is expected to accelerate the bone healing process (osteogenesis) due to the extract's anti-inflammatory and antioxidant properties. The osteogenesis process is closely associated with angiogenesis markers, such as fibroblast growth factor 2 (FGF-2), vascular endothelial growth factor (VEGF) and alkali phosphatase (ALP). The objective of this study is to analyse the combination of ellagic acid and hydroxyapatite to promote FGF-2, VEGF and ALP expression as angiogenesis markers in a bone defect model. The research sample comprised 30 male Wistar rats with a defect introduced on the left femur; these were divided into three groups for treatment with ellagic acid and hydroxyapatite, hydroxyapatite and polyethylene glycol (PEG) (control). On days 7 and 14 days after treatment, the Wistar rats were euthanised, and the femoral bone tissue was removed for the immunohistochemical analysis of FGF-2, VEGF and ALP expression. FGF-2 and ALP expression increased in the group treated with ellagic acid and hydroxyapatite on days 7 and 14 post treatment (p less then 0.05), and there was an increase in VEGF expression on day 7 post treatment (p less then 0.05). The combination of ellagic acid and hydroxyapatite promoted FGF-2, VEGF and ALP expression as angiogenesis markers in the bone defect model.
Obstructive Sleep Apnea (OSA), the most prevalent form of sleep-related breathing disorder has practical and financial limitations in diagnosis by polysomnography, hence OSA risk-assessment can identify OSA-related symptoms early.

To develop a mobile application for OSA-risk assessment and tests its validity, feasibility, and application in a hospital-based pilot sample.

The study comprised of two parts.

Development of a mobile application "OSA-Risk Assessment Tool" using automated questionnaires.

A pilot study to screen OSA-risk in 200 patients (100 adults,100 children) from the orthodontic OPD of a Govt. Dental Hospital, using the mobile application. Internal validation by manual and mobile-based methods was done on 30 random patients. Non-parametric tests assessed the statistical differences between OSA-risk and nonOSA-risk variables.

The prevalence of OSA-risk was 21.4% in adults and 8% in children. In adults, OSA-risk showed significantly greater neck circumference (p=0.0001), waist circumfer. The future upgraded versions may include preventive modules and real-time coordination with the nearest sleep clinics and specialists.The purpose of this paper is to explore the problematisation of fatness in contemporary responses to the COVID-19 pandemic. This paper draws from the catalogue of reports from journalists informed largely by an array of non-peer reviewed scientific literature documenting the relationship between fatness and COVID-19. Our method of enquiry is to examine fatness and COVID-19 through a problematisation lens that enables us to interrogate the scientific, political, and economic processes implicated in the production of fat bodies as problems. Fatness has been problematised in the COVID-19 pandemic. This has diverted responsibility for preparedness and well-being away from health systems and governments and onto the back of fat people and communities. This is unjust and unethical. Selleckchem Entinostat In juxtaposition, fat activists around the world have challenged the problematisation of fatness and its effects, finding ways for fat people to subvert fat phobic institutions in the midst of the COVID-19 pandemic by collectively organising to support one another. The ways in which fatness is being taken up in current COVID-19 pandemic responses diverts responsibility for health system preparedness and community resiliency to fat individuals. This is both unjust and also obstructs meaningful action to address the health inequities laid bare by COVID-19. This paper is believed to be the first to analyse the problematisation of fatness in COVID-19, highlighting that lessons can be learned about health justice in disasters from the work of fat activists during this COVID-19 pandemic.Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard rate order implies ordering of dynamic survival Rényi entropy. Our models are considered a more comprehensive version of generalized order statistics and give some properties and characterization results. Finally, a non-parametric estimation of survival Rényi entropy is included based on real COVID-19 data and simulated data.The term COVID-19 is an abbreviation of Coronavirus 2019, which is considered a global pandemic that threatens the lives of millions of people. Early detection of the disease offers ample opportunity of recovery and prevention of spreading. This paper proposes a method for classification and early detection of COVID-19 through image processing using X-ray images. A set of procedures are applied, including preprocessing (image noise removal, image thresholding, and morphological operation), Region of Interest (ROI) detection and segmentation, feature extraction, (Local binary pattern (LBP), Histogram of Gradient (HOG), and Haralick texture features) and classification (K-Nearest Neighbor (KNN) and Support Vector Machine (SVM)). The combinations of the feature extraction operators and classifiers results in six models, namely LBP-KNN, HOG-KNN, Haralick-KNN, LBP-SVM, HOG-SVM, and Haralick-SVM. The six models are tested based on test samples of 5,000 images with the percentage of training of 5-folds cross-validation. The evaluation results show high diagnosis accuracy from 89.2% up to 98.66%. The LBP-KNN model outperforms the other models in which it achieves an average accuracy of 98.66%, a sensitivity of 97.76%, specificity of 100%, and precision of 100%. The proposed method for early detection and classification of COVID-19 through image processing using X-ray images is proven to be usable in which it provides an end-to-end structure without the need for manual feature extraction and manual selection methods.Mental healthcare professionals often have limited awareness of different obsessive-compulsive disorder (OCD) symptom presentations, which may contribute to years between OCD symptom onset and treatment initiation. While research has identified high rates of OCD misdiagnosis among clinicians from the United States and Canada, research on OCD symptom awareness among healthcare providers in Latin American (LATAM) regions is limited. In this study, LATAM mental healthcare providers (N = 83) provided diagnostic impressions based on five OCD vignettes three with symptoms centered on taboo thoughts (sexual, harming others, and religion/scrupulosity) and two about contamination or symmetry obsessions. Rates of incorrect (non-OCD) diagnoses were significantly higher for the taboo thoughts vignettes (sexual, 52.7%; harm/aggression, 42.0%; and religious, 34.7%) vs. contamination obsessions (11.0%) and symmetry obsessions (6.9%). The OCD vignette depicting sexual obsessions was often attributed to a paraphilic disorder (36.5%). Bachelor's level clinicians had significantly lower odds of accurately identifying all three vignettes related to taboo thoughts compared to respondents with a graduate degree. Accurate identification of the three taboo vignettes was also associated with first-line psychological treatment recommendations (i.e., cognitive-behavioral therapy) even when controlling for respondents' theoretical orientation. Exposure was rarely mentioned when clinicians were prompted to provide treatment recommendations for each vignette (8-9% of the time for symmetry and contamination vignettes, 5-7% for taboo though vignettes). Like clinicians in the United States and Canada, mental health professionals in LATAM may misidentify OCD symptom presentations, particularly sexual obsessions, highlighting a need for education and training.Various social distancing measures were carried out in many cities worldwide during the coronavirus disease 2019 pandemic (COVID-19). These measures have led to decreased physical activity levels and higher health risks among urban populations. Strong evidence has been established that built environment characteristics can stimulate physical activity and thus improve public health during non-pandemic periods. Urban density was arguably one of the most important built environment characteristics. However, little is known about whether high urban density amplifies or attenuates the decline in physical activity during the pandemic. Based on two-wave physical activity data collected before and during the pandemic (in January and May 2020, respectively), we used moderation analysis to compare the changes in physical activity levels between people living in low- and high-density neighborhoods. Our results showed that people living in low-density areas have a smaller decrease in physical activity conducted in neighborhood, compared to those living in high-density areas. Our findings suggest that a flexible and porous urban development strategy could enhance the resilience of a city during the coronavirus pandemic and beyond.Buildings' occupancy is one of the important factors causing the energy performance and sustainability gap in buildings. Better occupancy prediction decreases this gap both in the design stage and in the use phase of the building. Machine learning-based models proved to be very accurate and fast for occupancy prediction when buildings are exploited under normal conditions. Meanwhile, during the Covid-19 pandemic occupancy of the offices has dramatically changed. The study presents 2 office buildings' long-term monitoring results for different periods of the pandemic. It aims to analyse actual occupancies during the pandemic and its influence on the ELM (Extreme Learning Machine) based occupancy-forecasting models' reliability. The results show much lower actual occupancies in the offices than given in standards and methodologies; it is still low even when quarantines are cancelled. Average peak occupancy within the whole measured period is for Building A - 12-20% and for Building B - 2-23%. The daily occupancy schedules differ for both offices as they belong to different industries.
Website: https://www.selleckchem.com/products/ms-275.html