A number of ehemical ion materials were used as an absorber against solar energy. These materials were selected according to their absorption spectra in the wavelength range 300-800nm where the solar spectrum is coventrated. A solar olleetorw^esigd and The ability of each material inside the collector for absorbing the solar radiation was examined by a converter parameter “R”.According to the “R” parameter, the cohaltous and copperic ions material seems to be of higher capability for absorbing solar energy than the other materials.All the results were analyzed by means of a least-squared fitting program.

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

The present study aimed to investigate the anatomy, histology, and immunohistochemistry of parathyroid gland in two Iraqi mammals (Weasel, Herpestes javanicus and Long-ear hedgehog, Hemiechinus auritus) as a comparative study. A total of (20) animal for each species were used in the present study. Animals collected were immediately anesthesia and dissected to get the parathyroid gland. Methods of Humason and Bancroft and Stevens were employed for histological techniques. Different stains were used (Hematoxylin- Eosin stain-(H & E), Periodic Acid Schiff stain-(PAS), Azan stain, and Methyl Blue stain-(MB)) for staining the histological sections. Anti-calcitonin, code140778 marker used for immune-histochemical study. Results of the present stu

This study compared the effects of citric acid (CA) derived from microbial fermentation using Aspergillus niger (400 mg kg-1) and natural extraction from Citrus limon (400 mg kg1) in albino mice. Parameters assessed included cytogenetic damage via the micronucleus (MN) assay, immunological response through immunoglobulin (IgA, IgG, IgM) titers, and hepatoprotective activity based on liver enzyme levels (AST, ALT, ALP) and histopathological inves tigation. Mice were divided into six groups (n=10/group) as follows: (1) negative control, (2) carbon tetrachloride (CCl₄ 0.02%), (3) lemon CA, (4) A. niger, (5) CCl₄ + lemon CA, and (6) CCl₄ + A. niger CA. The CCl4 group exhibited a significantly higher MN frequency (0.06 ± 0.008) compa

Abstract

        This research aims to evaluate the application of the inspectors general of global indicators offices according to the axles (leadership, strategy and planning, employees, partners and resources, process management) and through the assumption main research which states that (there is an application for global indicators to evaluate performance in the offices of the ministries under study) which are subdivided into five sub-hypotheses according to the classification and division of the five axes of the checklist.

The researchers have taken refuge in the process of assessing the performance of the check list which included global i

Aqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.

The current research is a spectroscopic study of Coumarin 334 dissolved in methanol. The range of concentrations of the prepared stock solution was (3.39x10^-9 to 2.03x10^-8) M. Some optical characteristics of this dye were investigated such as absorbance and transmission spectra, absorption coefficient, refractive and extinction coefficients, oscillation and dispersion energies, and energy band gap. The absorbance spectra were recorded at 452 nm using Broad Band Cavity Enhanced Absorption Spectroscopy (BBCEAS) which depends on increasing the path length of the traveling light from the source to the detector. The minimum absorbance amount was 0.07 with a low concentration of 3.39x10^-9 M. As a result, the ot

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin