<span lang="EN-US">Smart home is one of the most important applications of the internet of things (IoT). Smart home makes life simpler, easier to control, saves energy based on user’s behavior and interaction with the home appliances. Many existing approaches have designed a smart home system using data mining algorithms. However, these approaches do not consider multiusers that exist in the same location and time (which needs a complex control). They also use centralized mining algorithm, then the system’s efficiency is reduced when datasets increase. Therefore, in this paper, we firstly build a context-aware recommender system that considers multi-user’s preferences and solves their conflicts by using unsupervised algorithms to deliver useful recommendation services. Secondly, we improve smart home’s responsive using parallel computing. The results reveal that the proposed method is better than existing approaches.</span>
Female pattern hair loss (FPHL) is the most common form of nonscaring alopecia in women. It is polygenic and multifactorial and characterized by progressive replacement of terminal hair follicles over the frontal and vertex regions by miniaturized follicles that leads progressively to visible reduction in hair density. 1 Histologically, the miniaturization process is associated with inflammatory lymphocytic infiltrate in the peri-infundibular region. This leads to increased expression of pro-apoptotic and proinflammatory cytokines, which act as sources of reactive oxygen species (ROS) and can cause damage to cellular components, such as nucleic acids, proteins, and lipids of the cell membrane leading to increased expression of cytokines such as tumor necrosis factorα, transforming growth factorβ, and interleukin-1α, resulting in apoptosis. [2][3][4][5][6] The regression of the normal follicle during the catagen phase is an apoptotic-driven process, and the premature termination of anagen phase is a landmark event in the development of FPHL. 2
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