Some parameters for advancement of Leishmania tropica infection were examined in three groups of golden hamsters, Group (1) inoculated with autoclaved killed Leishmania tropica , Group (2) inoculated with BCG vaccine alone while Group (3) Inoculated with mixed vaccine (autoclaved killed Leishmania with BCG). The follow up of experimentally infected animals with virulent isolation of Leishmania tropica was done for 90 days, the animals inoculated with mixed vaccine (autoclaved killed Leishmania with BCG) showed the minimum average in each of foot pad thickness (2.3 ± 0.05) mm after (60) days of infection, spleen enlargement (1.13±0.38) after (45) days of infection, spleen length (23.9±0.08) mm after (30) days of infection, liver weight(3.

Abstract

This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' at

Purpose: The research aims to build an integrated knowledge framework for the basic research topic. The spirituality of the workplace is through access to the most important scientific proposals on these topics. In management thought framing, the knowledge within them in a serious attempt is to provide the appropriate answers about the intellectual dilemma of research by diagnosing the nature of the relationship with the influential elements and its historical development . Methodology: The study is relied on the analytical survey method. The research sample targeted (88) managers in the center of the Iraqi Ministry of Health exclusively from the researched senior leaders (general manager, assistant general manager, and head of department),

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The nephrotoxicity induced by methotrexate is a severe condition that greatly affects its therapeutic potential and has a significant inflammatory component. Fimasartan is an angiotensin receptor blocker that offers organ-protective effects and may be useful in mitigating renal injury. The present study explored the anti-inflammatory potential of two doses of fimasartan against methotrexate-mediated nephrotoxicity. Albino rats were intraperitoneally administered a single methotrexate (20 mg/kg). Intraperitoneal treatment with fimasartan (5 or 10 mg/kg/day) was initiated on day two after methotrexate injection and continued for seven consecutive days. Methotrexate significantly increased serum urea, creatinine, and NGAL concentrations. It al