The research aims at the scholars’attention to the importance and role of Arab Muslim women through books and historical studies that historians and scholars have taken up like Ibn Al-Jawzi (597 AH) and his book Safwat Al-Safwa, where he presented the conduct of worship and their words and deeds, and explained to women worshipers other aspects of their lives, such as the scientific aspect Crafts and works as well as their prominent role in preaching and religious guidance, and the impact of this on their morals and qualities. This study showed the strength of the personality of women and their high interest in worship. The importance of the study lies in knowledge.The research followed the role of Muslim women to carry the banner of Arab-Islamic civilization,culture, and preserved human thought.The Islamic community has stood up in pride and honor in front of the Muslim women who are straight and religious, as the leading scholars of preaching and guidance were asking her to preach and remind.Individuals cherished her career, as most of the women’s worshipers ’news came through their husbands, sons, or fathers, which indicates mutual respect, kindness, and love among members of the Muslim family.The researchers committed to documenting information from its sources and following the method of historical research method in investigating and supporting this with tables that count the number of female worshipers in each town.
In this work a chemical sensor was built by using Plane Wave Expansion (PWE) modeling technique by filling the core of 1550 hollow core photonic crystal fiber with chloroform that has different concentrations after being diluted with distilled water. The minimum photonic bandgap width is.0003 and .0005 rad/sec with 19 and 7 cells respectively and a concentration of chloroform that filled these two fibers is 75%.
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Objective: To review and identify the major drivers for COVID-19 vaccine acceptance. Methods: A scoping review of studies of COVID-19 vaccine perceptions and barriers to using the COVID-19 vaccines. Two search engines, including PubMed and Google Scholar, were purposefully searched. Results: Eight studies from different countries were reviewed to categorize factors influencing people's acceptance of COVID-19 according to the Health Belief Model (HBM). Perceived susceptibility, and severity of the disease (COVID-19), in addition to perceived benefits of COVID-19 vaccination and "cues to action", can enhance vaccination acceptance. In contrast, perceived barriers to the COVID-19 vaccine can increase people's hesitancy to be vaccinated
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Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.
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Modern agriculture is challenged by soil degradation, nutrient depletion, plant diseases, and excessive dependence on chemical fertilizers and pesticides. By examining different strains of Pantoea, the study highlights their role in promoting plant growth, improving their tolerance to stress, reducing reliance on synthetic agricultural inputs, and contributing to more sustainable and environmentally friendly agricultural practices. Using a combination of practical qualitative methods and reliable quantitative data, the research gathers extensive information on how these microbes impact various crops and key soil health indicators. The improvements in plant growth statistics and nutrient levels are often quite astonishing. The result
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In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.
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Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in
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