A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

This study was conducted to evaluate the efficacy of 6 isolates of Pseudomonas fluorescens and Trichoderma harzianum and there combination against Fusarium tomato wilt disease caused by Fusarium oxysporum F.sp. Lycopersisi under green house condition .The isolates of bacteria (B3) and Trichoderma (T1) were found to be highly effective in reducing the disease incidence to 13.3% , 21% respectively , compared to control treatment (40%).Furthermore, disease severity was reduced to 28 and 30% respectively in comparison to control (90%) .Colonization of the roots (cfu /g fresh root weight )by the two isolates whether alon or together was extremely high . The combination treatment had a high ability in reducing disease incidenece and sev

Asthma is a chronic respiratory disorder of airways characterized by inflammation, hyperresponsiveness, inflammatory cell infiltration, mucous secretion, and remodelling. Ammi majus is medicinal plant belong to family of Apiaceous which has anti-inflammatory and antioxidant activities. This study designed to investigate of anti-asthmatic activity of alcoholic extract of Ammi majus in improvement of asthma. Forty-eight healthy female mice divided to six groups Group I:  the negative control group (distal water only), Group II: Positive control group (ovalbumin group), Group III: Ammi majus (64 mg/kg/day) with sensitization, Group IV:Ammi majus  (128 mg/kg/day) w

Oryza sativa japonica (ofada rice) is largely grown in Aramoko, Abakaliki and Ofada are communities and consumed by both the poor and rich in Nigeria. A total of twenty ofada rice farmlands were identified in each study area and rice samples were randomly collected, thoroughly mixed to make a representative sample from each farmland. Soil samples were collected in each farm to a depth of 5-15cm from at least eight different points and thoroughly mixed together to form a representative sample. The samples were thereafter taken to the laboratory for preparation and spectroscopic analysis. A well-calibrated NaI(Tl) gamma-ray detector was used in spectrometric analysis of the samples and descriptive statistics was used to analyze th

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

In petroleum refineries, cooling towers, steam engines, and vacuum distillation all require a large volume of water. Before being dumped into the water bodies, it is then transported to an industrial water treatment facility. One of the study's objectives is to verify how well different processing units in the industrial wastewater treatment plant at the cycle refinery remove concentrations of chemical and biological oxygen demand (COD) and BOD. Five samples of industrial wastewater were collected before and after each treatment unit and one sample of wastewater was drained as a final product to the Tigris River. Over the summer, the BOD5 values after each processing unit were 180.8, 175.2, 111, 43, and 37 ppm. Winter readings were

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.