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The WELL® Building Standard
Published in Traci Rose Rider, Margaret van Bakergem, Building for Well-Being, 2021
Traci Rose Rider, Margaret van Bakergem
The cardiovascular system is charged with distributing supportive elements like oxygen, hormones, and nutrients to cells throughout the body, and removing waste products like carbon dioxide from body tissues. These activities can be hampered by both environmental pollutants and unhealthy lifestyle choices, often leading to chronic health conditions such as coronary heart disease, heart failure, heart arrhythmias, strokes, and more. WELL® focuses on these health impacts in preconditions and optimizations across the system in terms of stress, nutrition, environmental pollutants, and fitness. The digestive system is also largely impacted by stress. There is considerable energy around the topic of gut health, and with good reason. The digestive system is large and responsible for nutrient breakdown and getting those nutrients to different organs throughout the body. Stress can significantly impact the functioning of the digestive system, literally changing the bacteria in the gut to shift mood and brain function. While our food intake is a large part of gut health, and is addressed in the WELL® Building Standard, operational strategies including surface cleaning and stress mitigation are also important strategies to consider.
Factors Affecting Mechanical Work in Humans
Published in Joseph D. Bronzino, Donald R. Peterson, Biomedical Engineering Fundamentals, 2019
Ben F. Hurley and Arthur T. Johnson
27.1.4.2.1 Aerobic Exercise Training When aerobic exercise is performed regularly, it stimulates many biochemical reactions that raise the critical threshold level of exercise intensity at which metabolic homeostasis (equilibrium) can be maintained. Many compensatory reactions allow the body to adapt to minor stresses, such as mild aerobic exercise, so that homeostasis (equilibrium) can be maintained. For example, the increased energy demands of aerobic exercise stimulate an increase in heart rate, respiration, blood ow, and many other cardiovascular and metabolic reactions that allow the body to maintain homeostasis. As the intensity of exercise increases, it becomes more dicult for compensatory mechanisms to maintain homeostasis. Aer exceeding about 80% of an untrained person’s maximal exercise capacity, homeostasis can no longer be maintained for more than a few minutes before exhaustion results.
Chronic Arsenic Exposure to Drinking Water
Published in M. Manzurul Hassan, Arsenic in Groundwater, 2018
The integumentary system is an organ system comprising skin, hair, nails, exocrine glands, and nerve receptors that protect the body from infections. Cutaneous abnormalities are well-known early signs of chronic inorganic arsenic poisoning (Chen et al., 2009; Yamaguchi et al., 2016). In humans, skin is the most sensitive target organ for chronic arsenic exposure (Pei et al., 2013; Yoshida et al., 2004), and skin lesions like raindrop pigmentation, palmar and plantar hyperkeratosis, and hypo- and hyper-pigmentation are regarded as hallmarks of arsenic toxicity (Bhattacharjee et al., 2013a; Samal et al., 2013). Among these skin lesions, palmar and plantar hyperkeratoses are known as pre-malignant skin lesions, which later develop into skin cancer like basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and Bowen's disease (BD) (Banerjee et al., 2011; Tseng et al., 1968). Malignancy from these diseases may occur after about 15–20 years of clinical onset of the disease as monocentric or multicentric SCC. Malignancy in other organs, e.g., lungs, bladder, liver, uterus, etc., may also develop (Chakraborti et al., 2017a). A line of literature shows the association between arsenic exposure to drinking water and the occurrence of skin lesions (Nriagu et al., 2012; Sarma, 2016). Skin lesions are generally referred to as the early manifestation of chronic arsenic intoxication, and hypopigmented skin spots have been associated with arsenic cytoxicity and melanocytes, being more sensitive to arsenic than other cell types of the skin (Graham-Evans et al., 2004) (Table 4.1).
Mathematical analysis of oxygen and carbon dioxide exchange in the human capillary and tissue system
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Ahsan Ul Haq Lone, M. A. Khanday
The human respiratory system has two main functions: oxygen intake from the surrounding air to the body, and to exhale carbon dioxide from the blood to outside air. Those transfers are achieved through passive diffusion across a membrane which separates the gaseous air and the liquid blood, at an instantaneous rate by means of the difference in partial pressures, the area of the exchange surface, and its properties in terms of diffusion (Guyton and Hall 2011; West 2011). As this diffusion tends to reduce the partial pressure difference, a constant renewal must be made on both sides of the membrane. Renewal of air is achieved by the ventilation process, which consists of in periodic inspiration-expiration cycles that provide the inside of the lung with fresh air, whereas venous blood is periodically pumped onto the exchange zone by the heart. The exchange area is the boundary of a huge collection of small cavities (around 300 million units), called alveoli, which makes an exchange area of about 100 m2 (Guyton and Hall 2011; West 2011; Tortora and Derrickson 2012; Nunn 2013). Each of this alveolus is surrounded by a network of very small blood vessels, called capillaries, whose diameter is about 5–10 μm (Guyton and Hall 2011; West 2011). Gas exchange occur through the alveolar-capillary membrane, which is less than a micrometre wide (West 2011; Tortora and Derrickson 2012). The alveoli are connected to the outside world through the respiratory tract, which is an assembling of interconnected pipes following a dyadic-tree structure.
Quality and safety of South African hand sanitisers during the COVID-19 pandemic
Published in International Journal of Environmental Health Research, 2023
W. de Bruin, M. C. van Zijl, N. H. Aneck-Hahn, L. Korsten
Excipients may also have endocrine-disruptive properties. The endocrine system regulates all biological processes in the body, including growth, reproduction, and metabolism. Endocrine disruptors are linked to neurological and behavioural disorders, obesity and metabolic dysfunction, reproductive disorders, and hormone-sensitive cancers (WHO/UNEP 2013). Endocrine disruptors that may be present in hand sanitisers include triclosan, benzophenone-4, and nonylphenol. Triclosan can be absorbed by the skin and has been detected in blood, urine, and breast milk samples. Various in vivo and/or in vitro studies demonstrated the estrogenic, anti-estrogenic, androgenic, and anti-thyroid activities of triclosan, benzophenone-4, and nonylphenol (Kunz and Fent 2006; Olaniyan et al. 2016).
Detection and classification of gastrointestinal disease using convolutional neural network and SVM
Published in Cogent Engineering, 2022
Melaku Bitew Haile, Ayodeji Olalekan Salau, Belay Enyew, Abebech Jenber Belay
The digestive system consists of the gastrointestinal tract and other organs which help the body to break down and absorb food. The gastrointestinal tract may be affected by a variety of diseases which affect its functionality. The domain of gastrointestinal endoscopy includes the endoscopic diagnosis of various digestive diseases using image analysis and various devices. Endoscopy is currently the preferred method for examining the gastrointestinal tract; however, previous studies have shown that there is a need for improvement as some classes are more difficult to identify than others. In this study, we proposed a concatenated neural network model by concatenating the extracted features of VGGNet and InceptionNet networks to develop a gastrointestinal disease diagnosis model. The deep convolutional neural networks VGGNet and InceptionNet are trained and used to extract features from the given endoscopy images. The proposed model achieves a classification accuracy of 98% and Matthews’s Correlation Coefficient of 97.8%, which is a significant improvement over previous techniques and other neural network architectures.