Schiff bases (SBs) represent multipurpose ligands that can be prepared from the concentration of prime amines with carbonyl clusters. Creation of SB transition metal compounds via as ligands has opportunity of attaining coordination complexes of abnormal arrangement and stability. These transition metal compounds have extraordinary attention as a consequence of their dynamic portion in metalloenzymes and as biomimetic prototypical complexes as a result of their proximity to usual enzymes and proteins. These complexes are imperative in medicinal disciplines owing to their widespread range of biological actions. They mostly exhibit organic actions involving antifungal, antibacterial, antitumor, antidiabetic, herbicidal, antiproliferative, ant

Advanced drug delivery systems offer undeniable benefits for drug delivery. In the past three decades, new methods have been proposed to develop a novel carriers for drug delivery. Nowadays, the major goal is to maximize therapeutic benefit while minimizing side effects. Drug delivery technique is clearly shifting from the micro to nanoscale. Nano-drug delivery systems (NDDSs) are the most promising approach utilized to improve the accuracy of drug delivery and the efficacy of drugs.In this narrative review article, we evaluate how delivery challenges associated with commercial marketed products and discuss newer DDS is being carried out to overcome these challenges .Different colloidal carrier systems such as carbon nanotube ,li

Schiff bases (SBs) represent multipurpose ligands that can be prepared from the concentration of prime amines with carbonyl clusters. Creation of SB transition metal compounds via as ligands has opportunity of attaining coordination complexes of abnormal arrangement and stability. These transition metal compounds have extraordinary attention as a consequence of their dynamic portion in metalloenzymes and as biomimetic prototypical complexes as a result of their proximity to usual enzymes and proteins. These complexes are imperative in medicinal disciplines owing to their widespread range of biological actions. They mostly exhibit organic actions involving antifungal, antibacterial, antitumor, antidiabetic, herbicidal, antiproliferative, ant

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

The Electrical power system has become vast and more complex, so it is subjected to sudden changes in load levels. Stability is an important concept which determines the stable operation of the power system. Transient stability analysis has become one of the significant studies in the power system to ensure the system stability to withstand a considerable disturbance. The effect of temporary occurrence can lead to malfunction of electronic control equipment. The application of flexible AC transmission systems (FACTS) devices in the transmission system have introduced several changes in the power system. These changes have a significant impact on the power system protection, due to differences inline impedance, line curre

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

sanaa tareq, Baghdad Science Journal, - Cited by 1