Background: Crohn's disease (CD) is an immunological disorder associated with chronic inflammatory process of several unspecific regions of gastrointestinal tract but frequently detected in the terminal Ilium and proximal colon or both. This disease frequently presented with various oral manifestations as a consequence of inflammatory process of the disease, nutritional deficiency or medications side effects. Several therapeutic approaches have been developed for CD management that are targeting the inflammatory process and directed at controlling the host immune response. Immunosuppressants such as Azathioprine and anti-TNF α agents as well as the combination of them have been widely used as an effective therapeutic modality with a bett

In this study, low cost biosorbent ̶inactive biomass (IB) granules (dp=0.433mm) taken from drying beds of Al-Rustomia Wastewater Treatment Plant, Baghdad-Iraq were used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physico-chemical parameters such as initial metal ion concentration (50 to 200 mg/l), equilibrium time (0-180 min), pH (2-9), agitation speed (50-200 rpm), particles size (0.433 mm), and adsorbent dosage (0.05-1 g/100 ml) were studied. Six mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich–Peterson, Sips, Khan, and Toth models. The best fit to the P

The MTX was converted to MTX  nanoparticles  by the modified method based on changing the pH gradually . For the first time MTX NPs+Meropenem complex were prepared and evaluated as a potential tool to overcome antimicrobial resistance and to improve pharmacokinetics of the drug, the results showed that the antibacterial activity of complex (MTX NPs plus MEM) has increased (from 1( µg/ml) to >0.5( µg/ml) for p1 , from 2( µg/ml) to 1( µg/ml) for p10 and from 8( µg/ml) to 4( µg/ml) for p48).

Cilnidipine is a dihydropyridine calcium channel blocker used to improve the neurological outcome following subarachnoid hemorrhage. It belongs to BCS class II drugs that have a low oral bioavailability of 13%, thus preparation as nanoparticles would be expected to improve bioavailability. The aim of the study is to prepare Cilnidipine as nanoparticles using different carriers and co-carriers, concentrations, and types. Cilnidipine nanoparticles were prepared by a solvent anti-solvent method using different carriers (Soluplus®, Poloxamer 188, PVA cold) with co-stabilizers (PEG200, glycerol) at different ratios. Based on the obtained results, formula N4, which included Soloplus in a 5:5:1.19 weight ratio of drug to

Palladium nanoparticles are produced by Polyol method. The characterization of the Pd nanoparticle has been conducted by various techniques such as SEM and AFM. The results of Pd powder showed that the particle size is directly proportional to the temperature and the reaction time. The optimum conditions for obtaining minimum nanoparticles size are 45 oC reaction temperature and 60 min reaction time and the smaller particle size achieved is equal to 25 nm. The optical limiting of smaller size nanoparticles has been studied. The palladium nanoparticles appear to be attractive candidates for optical limiting applications.

Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic 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 proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic 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 proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat