This narrative review focused on research investigating the impact of loneliness on the prevalence of dementia and its relationship with other risk factors. A comprehensive and rigorous search was conducted using a variety of scientific databases with specific keywords to identify all prior studies that examined the correlation between dementia and loneliness. The inquiry was confined to articles published in English from January 2017 to March 2024. The narrative review identified a consensus regarding the role of loneliness in enhancing the risk of all‐cause dementia, with a particular emphasis on the subjective perception of loneliness. This phenomenon may be caused by the sensations of exclusion, discrimination, and alienation that are typically associated with low self‐esteem and low life satisfaction, which may contribute to cognitive impairment and depressive symptoms. This finding was obtained despite the absence of robust evidence regarding the involvement of loneliness in the pathogenesis of dementia. Existing research has not yet identified a correlation between hereditary factors that influence the development of dementia and feelings of loneliness. However, loneliness is strongly associated with depression, which is a potential risk factor for dementia. Previous studies have reported a moderate correlation between depression and loneliness, as individuals who are isolated and lack a sense of community exhibit higher levels of depression. Meditation, social cognitive training, and social support are three strategies that have been implemented to address loneliness and are reported to be the most effective interventions. A strong correlation exists between dementia and loneliness. Although such strategies are unlikely to impede the progression of the disease if cognitive deterioration is already underway, understanding these associations can assist in the development of strategies to alleviate the effects of loneliness on vulnerable individuals.
In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime
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Reactive oxygen species (ROS) are produced as a result of biochemical processes that are not in balance with the body's antioxidant defense mechanism. This metabolic dysfunction is referred to the oxidative stress (OS). Metabolic dysfunction-associated diseases are affected by changes in the redox balance. It is now widely recognized that oxidative stress significantly affects diabetes mellitus (DM), particularly type 2 diabetes. The biochemical changes associated with DM could disturb the oxidative milieu, leading to several microvascular complications in diabetic patients. Thus, DM is a perfect disease to explore the harmful consequences of oxidative stress and how to treat it. Oxidative stress triggered by hyperglycemia is
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Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal
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This article is part of the bigger project of my PhD thesis which investigates the influence of the British war poetry of the twentieth century on the development of Iraqi poetry in the century/Plymouth University/UK. The article examines the influences of British poetry on the development of the forms of poetry in Iraq after the Second World War. The aim is to shed the light on the creation of the ‘third product’ or the Iraqi poetry that shows the influences of the translated British poetry or the ‘second product’; which was written in prose for it is almost impossible to transfer the rhyme and rhythm of poetry from one language to another. Those who translated the poetry where also the pioneers of the major formal revolution in Ar
... Show MoreThe current research deals with the study of aesthetic relations in the field of interior design and the extent to which its mechanisms achieve sensory stimulation between the internal and external spaces, to generate a continuous visual connection that is an extension of it, achieving in turn sensory stimulation for the users of those spaces. The internal and external spaces meet the desired purpose of feeling pleasure and beauty.” The current research aims to “discover the nature of aesthetic relations between the internal and external spaces and the extent to which mechanisms can achieve sensory stimulation in residential spaces.” The first topic included the concept of aesthetic relations, sensory excitement, and perception at
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Through this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model
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