Background and Aim: The use of food dyes can cause certain diseases, such as anemia and indigestion, along with other disorders, tumors, and even cancer. Therefore, this study aimed to determine the chemical nature and toxicity of some commercial dyes locally used in processed foods compared with standard food dyes. Materials and Methods: Three types of standard and commercial food color additives (Sunset Yellow, Tartrazine, and Carmoisine) were extensively examined. The chemical structures and functional groups of the dyes were evaluated by Fourier-transform infrared (FTIR) spectroscopy. The melting temperatures of the dyes were also determined by chemical thermal analysis. The acute toxicity test to evaluate the standard and commercial

Background: Meclizine hydrochloride (MCZ) is an antihistamine that is used as an antiemetic to prevent and cure nausea and vomiting. Because of its limited water solubility and first-pass metabolism, it exhibits variable absorption. Objective: To formulate and evaluate MCZ as an intranasal in situ gel with increased residence time and permeability. Methods: We made an inclusion complex of MCZ using various cyclodextrins as a complexing agent to help the drug dissolve better. The complexes were studied, and the ones that were better at dissolving were chosen to be used in the creation of an in situ gel with poloxamer 407 (17–20% w/v) and hyaluronic acid (0.25–0.75% w/v). Prepared formulas were subjected to various evaluation tes

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algo

Galantamine was isolated from the bulb part of Narcissus jonquilla L. plant cultivated in Iraq. The compound was identified by different chemical analysis like: Fourier Transforms Infrared spectra (FTIR), High Performance Liquid Chromatography (HPLC) and mass spectroscopy and 1H-NMR.

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

New heterocyclic derivatives of quinoline are reported. Reaction of quinoline-2-thiol 4 with hydrazine hydrate gave 2-hydrazionoquinoline 5. Treatment of 5 with CS2 in pyridine afforded 1,2,4-triazolo-[4,3-a]- quinolin-1-2H-thione 6, whereas the reaction of 5 with carboxylic acids namely formic acid or acetic acid, yielded the 1,2,4-triazol-[4,3-a]-quinolin 7 or 5-methyl-1,2,4-triazolo [4,3-a]-quinoline 8 through ring closure. Diazotization of 5 under acidic conditions produced the fused tetrazole compound 9, tetrzolo-[1,5-a]- quinoline. Moreover, treatment of 5 with active methlyene compounds gave two pyrazole derivatives 10 and 11. Azomethines 12a-e were prepared through condensation of 5 with aromatic aldehydes or ketones.