The world faces, in the last years of the last century and the beginning
of the current century i.e. the 21st century, a great expansion and a large
openness on new worlds in studies differ in their development, detection of
thinking methods and practice of mental processes.
The recent studies have proved an increase in the scientific
achievement among students through the presence of new techniques one of
which is Landa Organizing and Exploring Model concerning Physiology that
deals with various body organs.
This research aims at identifying the effectiveness of Landa Model on
the achievement of the Technical Medicine Institute students in Physiology so
as to be sure of the following nil hypothesis: there i

           The Anticyclone Merge affects Iraq’s climate clearly through its impact on the different climatic elements. where it appears while they pass through special and distinctive weather . and most of this affection appears in temperatures, Therefore, this research study the relationship between the repetition and the survival period of the Anticyclone Merge and temperature average by using coefficient correlation (Pearson) that shows there’s strong inverse relationship between the integration of Anticyclones and temperatures average.                        &nbs

The rapid development of information technology and its use in all areas has had a positive impact on all areas, and financial markets have had a share of this development through the use of an electronic trading system to settle transactions, enhance transparency and disclosure in all activities of these markets and revitalize their performance.

The reason for choosing this topic is that it is a very important topic for what modern technology addresses in trading operations in financial markets. It is worth noting that these innovations have eliminated the need for direct contact with people, but through the Internet and telephone networks, and the new technology has reduced the costs of building systems

The crystal structures of a new polymorph and seven new derivatives of 2-(1-phenyl-1H-1,2,3-triazol-4-yl)pyridine have been characterized and examined along with three structures from the literature to identify trends in their intermolecular contact patterns and packing arrangements in order to develop an insight into the crystallization behaviour of this class of compound. Seven unique C-H...X contacts were identified in the structures and three of these are present in four or more structures, indicating that these are reliable supramolecular synthons. Analysis of the packing arrangements of the molecules using XPac identified two closely related supramolecular constructs that are present in eight of the 11 structures; in all cases, the st

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

Determining the actual amounts of active ingredients in various pharmaceutical commercial forms is still receiving a lot of attention. Two flow injection analysis (FIA) methods were suggested for determination of mesalazine (MES) in pharmaceutical forms. Normal and reverse FIA systems (nFIA and rFIA) combined with UV-Vis spectrophotometric technique were used for the analysis. The methods involved using two mods of FIA systems for measuring a colored product result from coupling of MES with 2,2'-dihydroxybiphenyl after oxidized with sodium periodate in alkaline medium. The absorbance of the red colored dye was measured at maximum wavelength of 500 nm. The calibration graphs for MES were linear in the ranges 2.5-200 and 0.5-60 µg/mL with

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an