Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

Objective: Econazole nitrate (ECZ) is one of the triazole antifungal drugs with poor aqueous solubility and dissolution rate; there is a need for enhancement of solubility. Therefore; inclusion complexation with β cyclodextrin (βCD) was performed. Methods: In this study kneading method and co-evaporation method of preparation of inclusion complex between βCD and ECZ using two molar ratios of βCD. The solubility of these complexes in isotonic saline solution and distilled water was studied. Complexes prepared by kneading method were used for the preparation of different ophthalmic gel formulas using carbomer (CB) and sodium carboxymethylcellulose (sod CMC) as a gelling agent. The release profile and the rheological behaviour of the gel w

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Pregnancy- including hypertension(PIH), also known as preeclampsia, is one of the major causes of maternal and fetal death. This study was carried out on 30 pregnant women with preeclampsia and 30 healthy pregnant women as control ranging in age mean ±SD (28.84±3.55) years , BMI (76.80±9.78) Kg/m2 and gestation age(30.82±0.75)week. The aim of this research was studied the plasma Metanephrine level and other biochemical parameters such as Hemoglobin(Hb), serum Protein, S. Albumin, Globulin, Albumin/Globulin ratio (Alb/Glu. ratio), S.Glutamate Pyruvate aminotransferase (GPT), S.Glutamate Oxaloacetate aminotransferase(GOT). The obtained results have been compared with 30 healthy pregnant women as control group. The result showed

The objective of this study is to determine levels of some pro-inflammatory cytokines (IL-12 and SIL-2R) in pregnant women with polycystic ovary syndrome (PCOS) and also to determine incidence of spontaneous abortion during first trimester in pregnant women with PCOS compared with non-PCOS pregnant women. This Study was performed on (93) women, consisted of: 1- (63) pregnant women during the first trimester, which included:A- (33)PCOS pregnant women and subdivided into the following groups: (20) successful pregnant PCOS, (7) blighted Ovum PCOS and (6) missed abortion PCOS. B- (30) non-PCOS pregnant women, which included: (27) successful pregnant control and (3) non-PCOS pregnant women were withdrawn from this study because of their abortion

Three groups of subjects have been divided (25/group): healthy normotensive non-pregnant women (Group A), normal normotensive pregnant women (Group B), and women with preeclampsia (Group C).The levels of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin , creatinine , blood urea nitrogen, triglyceride , total cholesterol and glucose have been estimated in all subjects. All measured parameters were determined by spectrophotometric analysis. The results showed a significant(P<0.05) increase in serum ALT, AST, blood urea nitrogen, triglyceride and total cholesterol levels in group B as compared to group A. However creatinine, total bilirubin and glucose levels did not show any statistical significant alt

Numerous physiological and biochemical changes are linked to menopause. The current study was intended to examine the transforms linked to anthropometric measurements and bone-related factors. In this study of 80 women which included; they comprised 40 premenopausal women and 40 postmenopausal women. waist circumference (WC), body mass index (BMI), hip circumference (HC), moreover waist to hip ratio are among the anthropometric measurements (W-HR) recorded by standard procedures. The plasma samples were tested for the following biochemical parameters: bone-related parameters [calcium (Ca), phosphorus (P), uric acid (UA), alkaline phosphatase (ALP), and erythrocyte sedimentation rate (ESR)] and serological agglutination tests [rheumat