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Move via actual physical in order to virtual school room amongst COVID-19 crisis: Inspecting students' viewpoint to drive development in the current on-line educating methodology.
cticed by the community and traditional faith healers could be dangerous leading to high mortality. Therefore, a multi-sectoral approach of community awareness, mapping of vulnerable populations, capacity building of health care facility, empowerment of health care workers (HCWs) could be useful for reducing the mortality and morbidity due to snakebite envenoming in India.
2021 Global Initiative for Chronic Obstructive Lung Disease (GOLD) Reports recommends that patients with clinically significant symptoms and exacerbations of chronic obstructive pulmonary disease (COPD) should escalate to triple therapy, a combined use of inhaled corticosteroids (ICS), long-acting muscarinic antagonists (LAMA) and long-acting b2-agonists (LABA)(ICS/LAMA/LABA). Triple therapy in fixed-dose combinations (FDCs), i.e., combining ICS, LABA with LAMA and administrating by a single inhalation device, has appeared in recent years. This study aims to compare the efficacy of triple therapy in FDCs in treating patients with moderate to severe COPD.

Literature search will be conducted on PubMed, Embase and Web of science, according to pre-specified and corresponding search strategies, for relevant reports published since the inception dates of the databases. Randomised controlled trials (RCT) which compared the triple therapy in FDCs with other pharmacological therapies will be included. The Cochrane risk of bias assessment tool (RoB 2) will be used to assess the RCT quality. The outcomes will be analyzed as rate ratios and mean differences under a random-effects model in a frequentist network meta-analysis (NMA). Additional statistical analyses including subgroup analysis, sensitivity analysis, and publication bias analysis will be performed to assess the evidential heterogeneity and robustness. The strength of evidence from the NMA will be evaluated with the Grading of Recommendation, Assessment, Development and Evaluation (GRADE) methods.

No ethics approval is required as this systematic review and network meta-analysis do not collect confidential personal data and do not carry out interventions in treating patients.

CRD42021240823.
CRD42021240823.Geographical characteristics have been proven to be effective in improving the quality of point-of-interest (POI) recommendation. However, existing works on POI recommendation focus on cost (time or money) of travel for a user. An important geographical aspect that has not been studied adequately is the neighborhood effect, which captures a user's POI visiting behavior based on the user's preference not only to a POI, but also to the POI's neighborhood. To provide an interpretable framework to fully study the neighborhood effect, first, we develop different sets of insightful features, representing different aspects of neighborhood effect. We employ a Yelp data set to evaluate how different aspects of the neighborhood effect affect a user's POI visiting behavior. Second, we propose a deep learning-based recommendation framework that exploits the neighborhood effect. Experimental results show that our approach is more effective than two state-of-the-art matrix factorization-based POI recommendation techniques.The forecasting of lower limb trajectories can improve the operation of assistive devices and minimise the risk of tripping and balance loss. The aim of this work was to examine four Long Short Term Memory (LSTM) neural network architectures (Vanilla, Stacked, Bidirectional and Autoencoders) in predicting the future trajectories of lower limb kinematics, i.e. ML364 clinical trial Angular Velocity (AV) and Linear Acceleration (LA). Kinematics data of foot, shank and thigh (LA and AV) were collected from 13 male and 3 female participants (28 ± 4 years old, 1.72 ± 0.07 m in height, 66 ± 10 kg in mass) who walked for 10 minutes at preferred walking speed (4.34 ± 0.43 km.h-1) and at an imposed speed (5km.h-1, 15.4% ± 7.6% faster) on a 0% gradient treadmill. The sliding window technique was adopted for training and testing the LSTM models with total kinematics time-series data of 10,500 strides. Results based on leave-one-out cross validation, suggested that the LSTM autoencoders is the top predictor of the lower limb kinematics trajectories (i.e. up to 0.1s). The normalised mean squared error was evaluated on trajectory predictions at each time-step and it obtained 2.82-5.31% for the LSTM autoencoders. The ability to predict future lower limb motions may have a wide range of applications including the design and control of bionics allowing improved human-machine interface and mitigating the risk of falls and balance loss.Exercise intolerance after acute myocardial infarction (AMI) is a predictor of worse prognosis, but its causes are complex and poorly studied. This study assessed the determinants of exercise intolerance using combined stress echocardiography and cardiopulmonary exercise testing (CPET-SE) in patients treated for AMI. We prospectively enrolled patients with left ventricular ejection fraction (LV EF) ≥40% for more than 4 weeks after the first AMI. Stroke volume, heart rate, and arteriovenous oxygen difference (A-VO2Diff) were assessed during symptom-limited CPET-SE. Patients were divided into four groups according to the percentage of predicted oxygen uptake (VO2) (Group 1, less then 50%; Group 2, 50-74%; Group 3, 75-99%; and Group 4, ≥100%). Among 81 patients (70% male, mean age 58 ± 11 years, 47% ST-segment elevation AMI) mean peak VO2 was 19.5 ± 5.4 mL/kg/min. A better exercise capacity was related to a higher percent predicted heart rate (Group 2 vs. Group 4, p less then 0.01), higher peak A-VO2Diff (Group 1 vs. Group 3, p less then 0.01) but without differences in stroke volume. Peak VO2 and percent predicted VO2 had a significant positive correlation with percent predicted heart rate at peak exercise (r = 0.28, p = 0.01 and r = 0.46, p less then 0.001) and peak A-VO2Diff (r = 0.68, p less then 0.001 and r = 0.36, p = 0.001) but not with peak stroke volume. Exercise capacity in patients treated for AMI with LV EF ≥40% is related to heart rate response during exercise and peak peripheral oxygen extraction. CPET-SE enables non-invasive assessment of the mechanisms of exercise intolerance.No diagnostic or predictive instruments to help with early diagnosis and timely therapeutic intervention are available as yet for most neuro-psychiatric disorders. A quantum potential mean and variability score (qpmvs), to identify neuropsychiatric and neurocognitive disorders with high accuracy, based on routine EEG recordings, was developed. Information processing in the brain is assumed to involve integration of neuronal activity in various areas of the brain. Thus, the presumed quantum-like structure allows quantification of connectivity as a function of space and time (locality) as well as of instantaneous quantum-like effects in information space (non-locality). EEG signals reflect the holistic (nonseparable) function of the brain, including the highly ordered hierarchy of the brain, expressed by the quantum potential according to Bohmian mechanics, combined with dendrogram representation of data and p-adic numbers. Participants consisted of 230 participants including 28 with major depression, 42 with schizophrenia, 65 with cognitive impairment, and 95 controls. Routine EEG recordings were used for the calculation of qpmvs based on ultrametric analyses, closely coupled with p-adic numbers and quantum theory. Based on area under the curve, high accuracy was obtained in separating healthy controls from those diagnosed with schizophrenia (p less then 0.0001), depression (p less then 0.0001), Alzheimer's disease (AD; p less then 0.0001), and mild cognitive impairment (MCI; p less then 0.0001) as well as in differentiating participants with schizophrenia from those with depression (p less then 0.0001), AD (p less then 0.0001) or MCI (p less then 0.0001) and in differentiating people with depression from those with AD (p less then 0.0001) or MCI (p less then 0.0001). The novel EEG analytic algorithm (qpmvs) seems to be a useful and sufficiently accurate tool for diagnosis of neuropsychiatric and neurocognitive diseases and may be able to predict disease course and response to treatment.
Non-professional care provided in domestic settings by a family member or someone from the close environment and without a connection to a professional care service, is increasingly assumed by older people, mainly the spouses of those requiring care. The aim of this study was to describe the experience of older people providing care at home to older dependents.

A qualitative study was carried out to describe and explore the experience of older people, caregivers of dependent older people in the home.

Four themes emerged as a result of the analysis interpersonal relationships established in the caregivers' immediate environment; the need and request for public and private resources; consequences of providing care during old age; and adaptation to the circumstance of being a caregiver during old age. Older people who provide home-based care, experience their situation as stressful, feel that it limits their daily life, deprives them of their freedom, and affects their interpersonal relationships and social activities.

Older caregivers learn quickly and can manage the skills issues. The volume of work is their challenge. Interpersonal relationships are altered depending on the length of time spent together and the demand for care. Public services and benefits are not adapted to the demands of caregivers or dependent persons.
Older caregivers learn quickly and can manage the skills issues. The volume of work is their challenge. Interpersonal relationships are altered depending on the length of time spent together and the demand for care. Public services and benefits are not adapted to the demands of caregivers or dependent persons.
In the absence of a universally accepted association between smoking and COVID-19 health outcomes, we investigated this relationship in a representative cohort from one of the world's highest tobacco consuming regions. This is the first report from the Middle East and North Africa that tackles specifically the association of smoking and COVID-19 mortality while demonstrating a novel sex-discrepancy in the survival rates among patients.

Clinical data for 743 hospitalized COVID-19 patients was retrospectively collected from the leading centre for COVID-19 testing and treatment in Lebanon. Logistic regression, Kaplan-Meier survival curves and Cox proportional hazards model adjusted for age and stratified by sex were used to assess the association between the current cigarette smoking status of patients and COVID-19 outcomes.

In addition to the high smoking prevalence among our hospitalized COVID-19 patients (42.3%), enrolled smokers tended to have higher reported ICU admissions (28.3% vs 16.6%, p<0.001)ected in our hospitalized COVID-19 cohort combined with worse prognosis and higher mortality rate in smoking patients. Our study was the first to highlight potential sex-specific consequences for smoking on COVID-19 outcomes that might further explain the higher vulnerability to death from this disease among men.
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