A total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- based DESs exhibited higher S∞, while phenyl phosphonium-based DESs showed higher C∞. DESs with Cl- anions provided higher selectivity, whereas those with Br- anions had higher capacity. Generally, DESs with high S∞ also showed high PI, indicating superior separation performance.
Stress is an inevitable part of life. Stress occurs when stressful events of self, environmental, or social origin affect the individual's resilience and threaten to collapse his psychological and physical systems. The stress represents difficulties and obstacles that may exceed the individual's ability to bear them and deal with them, which causes him stress and causes negative effects on his psychological and physical health. Therefore, the current research aimed to identify the negative effects of psychological stress on the psychological and physical health of the individual through the literature that dealt with this topic. It was among the results of the research that one of the negative effects of stresses on mental health is the
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
... Show MoreThis paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
... Show MoreAim: To evaluate the effect of two bonding systems and two curing systems on sealing ability of class V composite restorative materials. Materials and methods: This study was performed in vitro on 40 caries free upper first premolar teeth. The Standardized class V cavity preparation on buccal and lin- gual surfaces of each tooth was done. Then the teeth were randomly divided into two major groups each of twenty. 40 cavities were performed on these teeth and the first group7th generation bonding agent (i Bond) were applied according to the manufacturer instructions and single increment of univer- sal composite (XRV Herculite) from kerr were applied and twenty of the cavities were cured with con- ventional light cure device (astralis-5) and t
... Show MoreWe investigated at the optical properties, structural makeup, and morphology of thin films of cadmium telluride (CdTe) with a thickness of 150 nm produced by thermal evaporation over glass. The X-ray diffraction study showed that the films had a crystalline composition, a cubic structure, and a preference for grain formation along the (111) crystallographic direction. The outcomes of the inquiry were used to determine these traits. With the use of thin films of CdTe that were doped with Ag at a concentration of 0.5%, the crystallization orientations of pure CdTe (23.58, 39.02, and 46.22) and CdTe:Ag were both determined by X-ray diffraction. orientations (23.72, 39.21, 46.40) For samples that were pure and those that were doped with
... Show MoreVol. 6, Issue 1 (2025)
The research aims to identify the most important areas of voluntary work available to women in society, stand on the most important controls that push women to work in voluntary areas in society. The research also seeks to stand on the most prominent obstacles to the voluntary work of women in society. The research contained four main chapters: Chapter I: Definition of research, Chapter 2: Objectives, areas, controls and effects of volunteer work, Chapter 3: Voluntary Work of Women in the Celestial Religions, and lastly, Chapter 4: Theories, Constraints, and Recommendations for Voluntary Work for Women.The researcher suggested several recommendations: 1-establishing a unit responsible for planning,
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