Objectives: Assess nurses` practices for children with chemical poisoning, and find out relationship between nurses` socio- demographic data and their practices for children with chemical poisoning.

Methodology: A descriptive correlational design used to achieve the purpose of the study, the study was conducted at Al-Basrah Hospital for Maternal and Children throughout the period 12^th of September 2021 to 10^th of October 2022. A non- probability sample of (30) nurse at emergency department was selected. The instrument of the study was constructed based on previous literatures that related to study project, which include nurses` socio-demographic data and questionnaire format

The most common form of childhood cancer is leukemia, Calculation for more than one third of all childhood cancers among those ages 1 day – 14 years. The diseases of leukemia are worldwide, it occurred in both genders from male and females and in all age. A total of 80 different samples of patient children were collected from the central teaching hospital of pediatric in Baghdad. Obtained during the period from 1st Sept. 2019 till the 31 th of Aug. 2020. Each isolates identification by using Vitek 2. Isolated organism in leukemic children show 18 (22.5 %) gram positive and 62 (77.5 %) gram negative from the total sample 80 (100.0 %). The percent of male is 45 more than female which represents 35 in most age groups between age (1 d

The present paper describes and analyses three proposed cogeneration plants include back pressure steam-turbine system, gas turbine system, diesel-engine system, and the present Dura refinery plant. Selected actual operating data are employed for analysis. The same amount of electrical and thermal product outputs is considered for all systems to facilitate comparisons. The theoretical analysis was done according to 1st and 2nd law of thermodynamic. The results demonstrate that exergy analysis is a useful tool in performance analysis of cogeneration systems and permits meaningful comparisons of different cogeneration systems based on their merits, also the result showed that the back pressure steam-turbine is more efficient than other pro

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Catalytic microwave-assisted pyrolysis of biomass is gaining popularity as an alternative to fossil fuels due to health, environmental, climate, and economic issues. This study conducted a catalytic pyrolysis process of the Albizia plant's branches using an Iraqi clay catalyst (bentonite) focusing on the variables including the biomass-particle size, experimental time, microwave power level, and the catalyst-to-biomass ratio. The physical and chemical properties of the resulting biofuel were analyzed presented by HHV, acidity, density, viscosity, GC-MS, FTIR for bio-oil and SEM, EDX, BET, HHV, FTIR for biochar. The study revealed that addition of bentonite as a catalyst led to enhanced production of biogas produced from 5% to 45% an

The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c