Mask Acne (Maskne): A New Variant of Acne Mechanica

Mask acne (maskne) is the new variant of acne mechanica, associated with personal protective equipment usage in healthcare workers. Widespread daily use of facial masks for many hours during the COVID-19 pandemic has been linked to the development of new acne or exacerbation of the previous acne over the masked area, with a distinct pattern, referred to as the “O” zone area around the mouth. Maskne can be caused by friction, irritation, local increase in skin temperature, and humidity, the same mechanism as observed in acne mechanica. Keywords: Maskne; Pathophysiology; Diagnosis; Treatment; Prevention

The Relation Between Knowledge and Attitude towards Behavior of Personal Protective Equipment Usage in Nurses

Introduction: Nurses are health workers who have the highest intensity of interactions with patients, so they have high risk of exposure to hazards in a workplace. Work accidents and nosocomial infections are hazards in hospitals that can threaten the safety and health of nurses. The proper use of Personal Protective Equipment is, therefore, mandatory to be implemented as an effort to prevent and minimize the risk of exposure or infection. This research was conducted to identify nurses’ behavior of Personal Protective Equipment (PPE) usage as well as to identify the relation between the level of knowledge and attitude as an internal factor of an individual in nurses’ behavior of PPE usage. Method: The research method used was observational with a cross-sectional study research design. The sample used in this research was determined by the total number of population, which was 12 nurses of pulmonary inpatient rooms at RSU Haji Surabaya in January-February 2020. The process of collecting data was done through interviews, questionnaires and observation on nursing care. The variables in this research were the level of knowledge, attitude, and behavior of PPE usage. Results: Most of the nurses had poor behavior (50%) of PPE usage with the majority having a moderate level of knowledge and attitude. Conclusion: There was a positive relation with strong correlation (ρ=0.635) between the level of knowledge and quiet strong correlation (ρ=0.417) between attitude that nurses had with their behavior of PPE usage.Keywords: attitude, behavior of personal protective equipment usage, knowledge, nurses

The impact of deep learning–based equipment usage detection on building energy demand estimation

As external temperatures and internal gains from equipment rise, office buildings’ cooling demand and issues are likely to increase. Solutions such as demand-driven controls can help minimise energy consumption and maintain thermal comfort in buildings by coordinating the real-time heating, ventilation and air-conditioning (HVAC) use to the requirements of the conditioned spaces. The present study introduces a real-time equipment usage detection and recognition approach for demand-driven controls using a deep learning method. A Faster R-CNN model was trained and deployed to a camera. The performance of this model was assessed through different evaluation metrics. Based on the initial field experiment results, a detection accuracy of 76.21% was achieved. To investigate the impact of the proposed approach on building heating and cooling energy demand, the case study building was modelled and simulated. The results showed that the deep learning–based method predicted up to 35.95% lower internal heat gains compared to static or ‘fixed’ schedules based on the set conditions. Practical Application: As the appliances and equipment in building spaces contribute to the internal heat gains, their usage can influence the building energy demand and indoor thermal environment. Linking equipment usage with occupants’ presence in space may not be fully accurate and may lead to the over- or under-estimation of heat emissions, especially when the space is unoccupied, and the equipment is powered ON or the opposite. This approach can be integrated with demand-driven controls for HVAC systems, which can minimise unnecessary building energy consumption while maintaining a comfortable indoor environment using computer vision and deep learning detection and recognition methods.

Strength and Conditioning Facilities in Texas High Schools: A Quantitative Analysis

The health and athletic performance benefits of strength training for adolescents have increased the demand for the development and use of strength and conditioning facilities (SCFs) within the high school setting. Despite the growing prevalence of these facilities, research on high school SCFs is limited. Therefore, the purpose of this study was to investigate the space, equipment, usage, and staffing patterns of SCFs in the state of Texas. This examination provided descriptive data on SCFs’ space, equipment, usage, and staffing patterns based upon the state athletic governing body’s six-tier classification level. Significant differences in SCFs’ size and available equipment were determined; as well, facility usage for athletics (99.2%), physical education (24.5%), and community (30.6%) was determined. These results are indicative of the need for additional research on high school SCFs for the establishment of better school standards and best practices.

DAMAGE FEATURES OF TANKS OF FIRE TRUCKS AND STRENGTH ASSESSMENT OF THEIR WELDED JOINTS

The analysis of emergency rescue equipment usage on the territory of the Republic of Belarus made it possible to identify that the main technical unit involved into emergency situations is a fire truck tank. One of the main reasons for its repair and withdrawal from operational status is tank leakage that occurs due to peculiarities of equipment usage. As a result of a complex of studies, the recommendations for the modernization of a standard tank with 5 m3 volume of a fire truck were developed on the MAZ-5337 chassis. The stress state of a standard and modernized tank of a fire engine was investigated by the strain-gauge method under various operating modes of movement.

Personal protective equipment usage, recycling and disposal among spine surgeons: An Asia Pacific Spine Society survey

Purpose: In this study we investigated on the personal protective equipment (PPE) usage, recycling, and disposal among spine surgeons in the Asia Pacific region. Methods: A cross-sectional survey was carried out among spine surgeons in Asia Pacific. The questionnaires were focused on the usage, recycling and disposal of PPE. Results: Two hundred and twenty-two surgeons from 19 countries participated in the survey. When we sub-analysed the differences between countries, the provision of adequate PPE by hospitals ranged from 37.5% to 100%. The usage of PPE was generally high. The most used PPE were surgical face masks (88.7%), followed by surgical caps (88.3%), gowns (85.6%), sterile gloves (83.3%) and face shields (82.0%). The least used PPE were powered air-purifying respirators (PAPR) (23.0%) and shoes/boots (45.0%). The commonly used PPE for surgeries involving COVID-19 positive patients were N95 masks (74.8%), sterile gloves (73.0%), gowns (72.1%), surgical caps (71.6%), face shields (64.4%), goggles (64.0%), shoe covers (58.6%), plastic aprons (45.9%), shoes/boots (45.9%), surgical face masks (36.5%) and PAPRs (21.2%). Most PPE were not recycled. Biohazard bins were the preferred method of disposal for all types of PPE items compared to general waste. Conclusions: The usage of PPE was generally high among most countries especially for surgeries involving COVID-19 positive patients except for Myanmar and Nepal. Overall, the most used PPE were surgical face masks. For surgeries involving COVID-19 positive patients, the most used PPE were N95 masks. Most PPE were not recycled. Biohazard bins were the preferred method of disposal for all types of PPE.

A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

COMPARATIVE ANALYSIS OF GOST R AND IMO MSC/CIRC. REQUIREMENTS DETERMINING THE QUALITY OF FOAMING AGENTS USED FOR FIRE EXTINGUISHING BY FOAMS

В статье представлен анализ требований ГОСТ Р и IMO MSC/Circ., определяющих качество пенообразователей, используемых для тушения пожаров пенами. Показаны различия и схожесть подходов к проведению испытаний, возможность использования оборудования при проведении испытаний по различным действующим стандартам в рамках стандартов России и Морского регистра судоходства. The article provides the analysis of the GOST R and IMO MSC/Circ. requirements determining the quality of foaming agents used for fire extinguishing by foams. There are presented the differences and similarity of testing approaches, as well as the possibility of equipment usage for testing according to various acting standards in the context of Russian standards and the Maritime Register of Shipping.