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

Persons with spinal cord injury are at high risk of developing pressure injuries, and their caregivers are in a critical position to help prevent them. The objective of this study was to evaluate the effectiveness of an educational program for caregivers of persons with spinal cord injuries to prevent pressure injuries in Iraq. A pre- and post-test design was used and involved 25 caregivers of persons with spinal cord injury during the acute care phase in an SCI-specific unit of a hospital. A scale and questionnaire were used to gather the participants’ demographic information, pre- and post-educational program knowledge, and observations of their pre- and post-program performance of pressure injury preventive tasks. Descriptive s

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti