Damage Assessment of Concrete under Wind-Sand Load

In this paper, a numerical model of wind-sand flow is established to explore the influence of wind-sand flow parameters on the stress state of the concrete. According to the contact mechanics theory, the wind erosion critical pressure of concrete members and the corresponding stress state of concrete are analyzed. A wind erosion damage assessment index based on stress fatigue theory is proposed.

Remote-mount Actuation Control: A Veritable Solution to Unreliability of Anti-surge Control Valves in Gas Compressors

This paper presents the design and implementation of a remotely mounted Anti-surge Control Valve (ASCV) for a mixed refrigerant gas compressor deployed in an industrial plant. The traditional ASCV model which is usually self-mounted is plagued by component failures due to stress fatigue from excessive vibrations leading to unreliability of the system. A new system with a remote-mount actuation control system was developed, tested, installed and commissioned in place of the initial self-mount system. Test results showed that average percentage of trips caused by failure of the ASCV dropped from 70% with the initial set-up to 0% with the modified set-up. Hence, a lasting solution to the issue of component fatigue failure from vibrations has been resolved using the highly reliable developed remote-mount actuation control.

A method of searching and marking artifacts in images applying detection and segmentation algorithms

The paper explores the possibility of using neural networks to single out target artifacts on different types of documents. Numerous types of neural networks are often used for document processing, from text analysis to the allocation of certain areas where the desired information may be contained. However, to date, there are no perfect document processing systems that can work autonomously, compensating for human errors that may appear in the process of work due to stress, fatigue and many other reasons. In this work, the emphasis is on the search and selection of target artifacts in drawings, in conditions of a small amount of initial data. The proposed method of searching and highlighting artifacts in the image consists of two main parts, detection and semantic segmentation of the detected area. The method is based on training with a teacher on marked-up data for two convolutional neural networks. The first convolutional network is used to detect an area with an artifact, in this example YoloV4 was taken as the basis. For semantic segmentation, the U-Net architecture is used, where the basis is the pre-trained Efficientnetb0. By combining these neural networks, good results were achieved, even for the selection of certain handwritten texts, without using the specifics of building neural network models for text recognition. This method can be used to search for and highlight artifacts in large datasets, while the artifacts themselves may be different in shape, color and type, and they may be located in different places of the image, have or not have intersection with other objects.

Waste Anesthetic Gase: A Forgotten Problems

Waste anesthetic gas (WAG) is a small amount of inhaled anesthetic gas that comes out of the patient’s anesthesia breathing circuit into the envorinment air while the patient is under anesthesia. According to American Occupation Safety and HealthAdministration (OSHA) more than 200.000 healthcare workers especially aneaesthesiologist, surgery nurse, obstetrician and surgeons are at risk of developing work-related disease due to chronic exposure to WAG. Exposure to WAG in short time associated with multiple problems such as headaches, irritability, fatigue, nausea, drowsiness, decrease work efficiency and difficulty with judgment and coordination. While chronic exposure of WAG is associated with genotoxicity, mutagenicity, oxidative stress, fatigue, headache, irritability, nausea, nephrotoxic, neurotoxic, hepatotoxic, immunosuppressive and reproductive toxicological effect. Waste anesthetic gases are known as environmental pollutants and will be released from the OR to the outside environment then the substance will reach the atmosphere damaging ozone layer. Exposure to trace WAG in the perioperative environment cannot be eliminated completely,but it can be controlled. Controlling WAG can be achieve by using scavenging system, proper ventilation, airway management, ideal anesthetic choice, maintaining anesthesia machine and equipment, hospital regulation and routine healthcare workers health status examination.

In-Season Internal Load and Wellness Variations in Professional Women Soccer Players: Comparisons between Playing Positions and Status

The internal intensity monitoring in soccer has been used more in recent years in men’s football; however, in women’s soccer, the existing literature is still scarce. The aims of this study were threefold: (a) to describe the weekly variations of training monotony, training strain and acute: chronic workload ratio through session Rated Perceived Exertion (s-RPE); (b) to describe weekly variations of Hooper Index [stress, fatigue, Delayed Onset Muscle Soreness (DOMS) and sleep]; and (c) to compare those variations between playing positions and player status. Nineteen players (24.1 ± 2.7 years) from a Portuguese BPI League professional team participated in this study. All variables were collected in a 10-week in-season period with three training sessions and one match per week during the 2019/20 season. Considering the overall team, the results showed that there were some associations between Hooper Index categories and s-RPE like stress or fatigue (0.693, p < 0.01), stress or DOMS (0.593, p < 0.01), stress or s-RPE (−0.516, p < 0.05) and fatigue or DOMS (0.688, p < 0.01). There were no differences between all parameters in playing positions or player status. In conclusion, the study revealed that higher levels of fatigue and DOMS occur concurrently with better nights of sleep. Moreover, any in-season variations concerning internal load and perceived wellness seems independent of position or status in outfield players. The data also showed that the higher the players’ reported stress, the lower the observed s-RPE, thus possibly indicating a mutual interference of experienced stress levels on the assimilation of training intensity by elite women soccer players.

Effects of yoga on stress, fatigue, musculoskeletal pain, and the quality of life among employees of diamond industry: A new approach in employee wellness

BACKGROUND: Diamond industry employees often experience musculoskeletal pain, fatigue, and stress, contributing to a low quality of life (QoL). Yoga is an ancient discipline of mind-body practice Yoga has numerous health benefits. OBJECTIVE: This study investigated the efficacy of workplace yoga in improving stress, musculoskeletal pain, fatigue, and QoL among employees of the diamond industry. METHODS: One-hundred sixty-six employees of the diamond industry between the ages of 20 and 60 participated in the study. Participants were assigned to either yoga (n = 84) or waitlist (n = 82) groups. The yoga group received one hour of yoga, four days a week for three consecutive months. Participants in the waitlist group followed their daily routines. Musculoskeletal pain, fatigue, stress, and QoL were assessed at baseline and after three months. RESULTS: One-hundred fifty-five employees completed the study. The yoga group showed significant (p < 0.05) improvement in pain, perceived stress, fatigue, and QoL domains after three months compared to baseline. The waitlist group showed no significant improvement in any of the measures. In the post scores comparison between the groups revealed a significant difference between the groups. CONCLUSION: Workplace yoga found to be a useful, cost-effective and feasible intervention in improving stress, musculoskeletal pain, fatigues and quality of life among employees of the diamond industry. Yoga may be implemented in the workplace as a wellness program at the workplace.

Effects of Exercise-Induced ROS on the Pathophysiological Functions of Skeletal Muscle

Oxidative stress is the imbalance of the redox system in the body, which produces excessive reactive oxygen species, leads to multiple cellular damages, and closely relates to some pathological conditions, such as insulin resistance and inflammation. Meanwhile, exercise as an external stimulus of oxidative stress causes the changes of pathophysiological functions in the tissues and organs, including skeletal muscle. Exercise-induced oxidative stress is considered to have different effects on the structure and function of skeletal muscle. Long-term regular or moderate exercise-induced oxidative stress is closely related to the formation of muscle adaptation, while excessive free radicals produced by strenuous or acute exercise can cause muscle oxidative stress fatigue and damage, which impacts exercise capacity and damages the body’s health. The present review systematically summarizes the relationship between exercise-induced oxidative stress and the adaptions, damage, and fatigue in skeletal muscle, in order to clarify the effects of exercise-induced oxidative stress on the pathophysiological functions of skeletal muscle.

Longitudinal changes of COVID-19 symptoms in social media: Observational study (Preprint)

BACKGROUND In December 2019, the Coronavirus disease 2019 (COVID-19) outbreak started in China and rapidly spread around the world. Many studies have been conducted to understand clinical characteristics of COVID-19, and recently post-infection sequelae of this disease have begun to be investigated. However, there is little consensus on the longitudinal changes of lasting physical or psychological symptoms from prior COVID-19 infection. OBJECTIVE This study aims to investigate and analyze public social media data to understand the longitudinal impact of COVID-19 symptoms before and after the recovery of COVID-19. METHODS Through semantic analysis, we collected 84,140 Reddit posts from 1,036 COVID-19 positive users. In total, 292 active users, who frequently reported disease progress on Reddit, along with their 2,213 longitudinal Reddit posts were identified. Machine-learning tools to extract biomedical information were applied to identify COVID-19 symptoms mentioned in social media. We then examined longitudinal changes of individual physiological and psychological characteristics before and after the recovery from COVID-19 infection. RESULTS In total, 58 physiological and 3 psychological symptoms were identified in social media before and after the recovery from COVID-19 infection. From longitudinal analyses of social media, symptoms of COVID-19 patients lasted 2.5 months. On average, symptoms appeared around a month before the recovery and remained for 1.5 months after the recovery. Well-known COVID-19 symptoms (e.g., fever, cough, and chest congestion) appeared relatively earlier in patient journeys and were frequently observed before the recovery of COVID-19. Meanwhile, mental discomfort or distress (e.g., brain fog or stress), fatigue, and manifestations on toes or fingers were frequently mentioned after the recovery and remained as intermediate and longer-term sequelae. CONCLUSIONS Symptom presentation and duration during COVID-19 patients’ journeys may serve as surrogate indicators to predict their clinical outcomes and provide appropriate treatment. CLINICALTRIAL NA