This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil: (contaminated soil with the a

This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil:

The purpose of this study is to demonstrate a simple high sensitivity vapor sensor for propanol ((CH3)2CHOH). A free space gap was employed in two arms of a Mach-Zehnder interferometer to serve as the sensing mechanism by adding propanol volume (0.2, 0.4, 0.6, 0.8, and 1) ml and to set the phase reference with a physical spacing of (0.5, 1, 1.5, and 2) mm. The propagation constant of transmitted light in the Mach-Zehnder interferometer’s gap changes due to the small variation in the refractive index inside sensing arm that will further shift the optical phase of the signal. Experimental results indicated that the highest sensitivity of propanol was about 0.0275 nm/ml in different liquid volume while highest phase shift was 0.182×103 i

The importance of the study lies in highlighting the role of smartwatches as a modern tool for analyzing training load based on functional indicators, such as heart rate and calorie consumption. This allows coaches to monitor individual players’ responses during different training periods, helping to improve physical performance efficiency and reduce the risk of overload-induced fatigue. The study aimed to analyze calorie consumption at different heart rate levels between the special preparation and competition periods for youth football players, with the goal of determining the effect of physiological adaptation on energy efficiency. To achieve this objective, the researcher adopted the descriptive method due to its suitability f

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings