Density functional theory (DFT) with B3LYP level and 6-311G[Formula: see text] basis sets for light atoms like N and O and SDD basis sets for heavy atoms like Sn is used to examine the interaction of tin dioxide nanocrystals with nitrogen dioxide as a function of temperature from 273[Formula: see text]K to 373[Formula: see text]K through a Gaussian 09W software program. Gibbs free energy, enthalpy, and entropy of activation and reaction are calculated. The situation of transition of SnO₂ clusters toward nitrogen dioxide is investigated. According to the findings, the activation energy of SnO₂ clusters with nitrogen dioxide increases as the temperature rises (in negative value). Gauss view 0

This study evaluated the functional response of the larva of the predator Chrysoperla carnea by offering varying densities of cabbage aphid, Brevicoryne brassicae (L.) . Results showed conformity with type–II functional response, where the number of prey killed approaches asymptote hyperbolically as prey density increases (declining proportion of prey killed or the inverse density dependent) till it reached the stability stage determined by handling time and predator satiation. Also, the values of attack rate and handling time changed with age progress for both predator and prey. It has been observed an increase in the attack rate and reduction in handling time with the progress of the predator age when feeding on a particular nymphal in

Research on the role of organizational change in easing the organizational conflict focuses for being one of the important topics and relatively modern and which have a significant impact on the future of organizations, so this study was to identify the relationship and the impact of organizational change and of deportation (technological, organizational structure, human resources, the change in the task) at the organizational conflict in the Earth company link Iraq, in order to reach the goals of the research, it has been the development of a questionnaire distributed to a random sample of (100) composed employees from managers and heads of departments and the people and staff at the Earth company link Iraq, the study found: the

This work aims to detect the associations of C-peptide and the homeostasis model assessment of beta-cells function (HOMA2-B%) with inflammatory biomarkers in pregnant-women in comparison with non-pregnant women. Sera of 28 normal pregnant women at late pregnancy versus 27 matched age non-pregnant women (control), were used to estimate C-peptide, triiodothyronine (T3), and thyroxin (T4) by Enzyme-linked-immunosorbent assay (ELISA), fasting blood sugar (FBS) by automatic analyzer Biolis 24i, hematology-tests by hematology analyzer and the calculation of HOMA2-B% and homeostasis model assessment of insulin sensitivity (HOMA2-S%) by using C-peptide values instead of insulin. The comparisons, correlations, regression analysis tests were perfo

تعد لعبة كرة السلة من الألعاب الرياضية التي تحتاج متطلبات بدنية ووظيفية خاصة بها، وذلك من خلال الانتقال داخل الملعب بالكرة أو بدونها والسبل للتخلص من ملاحقة الخصم أثناء الدفاع وكيفية المناورة أثناء الهجوم مع إجادة التصويب بكافة أنواعه داخل الملعب، ومن هنا تكونت مشكلة البحث في كيفية تطوير تلك العوامل الوظيفية والتي لها الأثر في الارتقاء بمستوى أداء اللاعب أثناء اللعب، وعن طريق استخدام الباحثان لطريقة جهاز ا

This study is concerned with the comparison of the results of some tests of passing and dribbling of the basketball of tow different years between teams of chosen young players in Baghdad. Calculative methods were used namely (Arithmetic mean, Value digression and T.test for incompatible specimens). After careful calculative treatments, it has been that there were abstract or no abstract differences in the find results of chestpass, highdribble and cross-over dribble. The clubs were: (Al-Khark, Air defence, Police and Al-Adamiyah) each one separate from the other for the year (2000-2001). After all that many findings were reached such as the lack of objective valuation (periodical tests) between one sport season and the other. In the light

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

This research aims to examine the ability of impact of the cash flow statement indicators in the change in the market value of the industrial firms listed on the Palestine Stock Exchange. The research population consisted of (13) firms during the period (2015-2020). Data were collected from the annual financial statements of the firms. The research relies on the Pooled effects model to analyze the cross-section data (Panel Data), and the multiple regression method to test the hypotheses. The research finds a positive significant impact of (the ratios of cash flows from operating activities to sales, the return on assets from operating cash flows, and cash flows from operating activities to total current liabilities) in the change

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a