Thermal energy storage is an important component in energy units to decrease the gap between energy supply and demand. Free convection and the locations of the tubes carrying the heat-transfer fluid (HTF) have a significant influence on both the energy discharging potential and the buoyancy effect during the solidification mode. In the present study, the impact of the tube position was examined during the discharging process. Liquid-fraction evolution and energy removal rate with thermo-fluid contour profiles were used to examine the performance of the unit. Heat exchanger tubes are proposed with different numbers and positions in the unit for various cases including uniform and non-uniform tubes distribution. The results show that

The "Corona" pandemic that strikes the world has cast a shadow over contractual obligations, whether between individuals or companies, and emergency accidents and force majeure circumstances have a direct impact on them. Here, the legislation intervenes and sets the legal mechanisms to restore the obligations to their equal status and achieve the economic balance of the contract. Health crises are among the material facts whose effects are reflected and their features can be monitored on legal relations in general and contractual relations in particular, including the extent of the impact that this pandemic can have on the obligations that arise within the framework of a contractual relationship, which can be talked about in my theory Force

Background: Stroke is an acute neurologic injury and represents the 2^nd leading cause of mortality worldwide, and also the most leading cause of acquired disability and morbidity in adults.

Objective: Effect and association between stroke and risk factors.

Type of the study: A retrospective study.

Methods: The study conducted on 312 patients in 2016, all data were collected from patients’ files from the emergency unit, which included basic demographic and disease characteristic, co morbid diseases, risk factors, final diagnosis.

Results: both previous stroke, ischemic heart disease was strong predictor of new

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall