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.
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Free vibration behavior was developed under the ratio of critical buckling temperature of laminated composite thin plates with the general elastic boundary condition. The equations of motion were found based on classical laminated plate theory (CLPT) while the solution functions consists of trigonometric function and a continuous function that is added to guarantee the sufficient smoother of the so-named remaining displacement function at the boundaries, in this research, a modified Fourier series were used, a generalized procedure solution was developed using Ritz method combined with the imaginary spring technique. The influences of many design parameters such as angles of layers, aspect ratio, thickness ratio, and ratio of initial in-
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Background: Considering the antioxidant, anti-inflammatory, and antimicrobial properties of green tea, this study aimed to evaluate the histopathological effect of the sulcular irrigation of green tea extract in the treatment of experimental gingivitis in rabbit.
Materials and methods: For this experimental study, 45 male rabbits, separated in two groups, control non- irrigated group (5rabbits) and study group (40 rabbits), gingivitis induced by ligatures was packed subgingivally in the lower right central incisors of the experimental group for seven days. Then, the animals were randomly designated to two irrigated groups (20 rabbits
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The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated
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A novel demountable shear connector for precast steel-concrete composite bridges is presented. The connector uses high-strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents bolts from slipping within their holes. Moreover, the connector promotes accelerated construction and overcomes the typical construction tolerance issues of precast structures. Most importantly, the connector allows bridge disassembly. Therefore, it can address different bridge deterioration scenarios with minimum disturbance to traffic flow including the following: (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (
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The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var
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A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.