In an earlier paper, the basic analytical formula for particle-hole nuclear state densities was derived for non-Equidistant Spacing Model (non-ESM) approach. In this paper, an extension of the former equation was made to include pairing. Also a suggestion was made to derive the exact formula for the particle-hole state densities that depends exactly on Fermi energy and nuclear binding energies. The results indicated that the effects of pairing reduce the state density values, with similar dependence in the ESM system but with less strength. The results of the suggested exact formula indicated some modification from earlier non-ESM approximate treatment, on the cost of more calculation time

Metallic nanoparticles are increasingly studied for their biomedical applications due to their unique physicochemical and catalytic properties. Here, a broccoli-mediated gold/platinum nanohybrid (Au@Pt NH) was synthesized using an ultrasound-assisted green method with an aqueous extract of Brassica oleracea var. italica for multifunctional biomedical evaluation. XRD and TEM confirmed a crystalline nanohybrid with an average crystallite size of 7.56 nm and a mean particle diameter of 13.08 ± 7.58 nm. The broccoli extract produced no inhibition zones, whereas Au@Pt NH inhibited Staphylococcus aureus (18 mm), Staphylococcus epidermidis (21 mm), Escherichia coli (18 mm), Klebsiella pneumoniae (20 mm), and Candida albicans (21 mm). In vivo,

Among the undesirable effects of soil compaction is a measurable reduction in plant growth and crop yield. The prevailing belief is that compacted tillage pans are caused by repetitive farming practices, heavy tractors, tillage tools, and field traffic. This experiment was conducted to determine and map the hardpan layers across an agricultural field through advanced technologies of precision agriculture. These valuable techniques such as data logger, yield map, and data analysis of performance indicators were linked with accurate global positioning systems (GPS) datasets. These important technologies provided the farmers and helped them to identify and manage areas of the fields with higher compacted layers. Three ground speeds 4.3

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

New ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin

The current research aimed to identify the level of moral identity and social affiliation among students exposed to shock pressures, as well as to reveal the relationship between these variables. To achieve these objectives, the researcher adopted the diagnostic tool for the measure of post-traumatic stress disorder (PDS-5) scale (Foa, 2013) translated to Arabic language by (Imran, 2017). The researcher also adopted the moral identity scale built by (Al-Bayati, 2015) and the measure of social affiliation built by (Al-Jashami, 2013), which were applied to a random sample of (200) male and female students chose from al Anbar University. They were exposed to shock pressures. The results of the research showed that the sample has an average

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of