Faces of the individual in his life many stressful events, which includes expertise undesirable, and events may involve a lot of sources of tension and the risk factors and threats in all areas of life, and this would make the stressful events play a role in the genesis of many diseases physical.            

The high blood pressure is one of the most Actual manifestations of mental stress in the present scale physical disorders which may frequently in men relative to women, which may be caused by spasms in the blood vessels.      

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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

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

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

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

The study evaluated the recovery performance of any home herbs group as first aid in some emergency cases. The study involved 10 items of herbs (chamomile, black pepper, cloves, cinnamon, and anise) which used in acute cases such as cold, colic, inflammation of the intestine and tonsillitis, and (hibiscus, catnip, dried lime, cress seed, and ginger) were used for chronic cases such as hypertension, cardiovascular disease, and arthritis. The results showed the herbs had healing power and efficiency in the primary remedy for the above-mentioned diseases. The side effects, the contradictions, and the overdoses of these substances were discussed. It was concluded that home herbs could be used for treatment in emergency cases until moder

Urbanization led to significant changes in the properties of the land surface. That appends additional heat loads at the city, which threaten comfort and health of people. There is unclear understanding represent of the relationship between climate indicators and the features of the early virtual urban design. The research focused on simulation capability, and the affect in urban microclimate. It is assumed that the adoption of certain scenarios and strategies to mitigate the intensity of the UHI leads to the improvement of the local climate and reduce the impact of global warming. The aim is to show on the UHI methods simulation and the programs that supporting simulation and mitigate the effect UHI. UHI reviewed has been conducted the for

Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-