Olanzapine (OLZ) is classified as a typical antipsychotic drug utilized for the treatment of schizophrenia. Its oral bioavailability is 60% due to its low solubility and pre-systemic metabolism. Hence, the present work aims to formulate and evaluate OLZ nanoparticles dissolving microneedles (MNs) for transdermal delivery to overcome the problems associated with drug administration orally. OLZ nanoparticles were prepared by the nanoprecipitation method. The optimized OLZ nanoparticle formula was utilized for the fabrication of dissolving MNs by loading OLZ nanodispersion into polydimethylsiloxane (PDMS) micromould cavities, followed by casting the polymeric solution of polyvinylpyrrolidone(PVP-K30) and polyvinyl alcohol (PVA) to form

As a well-known oral and intravenous antifungal, voriconazole (VRN) has an extensive history of usage in the medical field. Solid lipid nanoparticles (SLNs) have been produced to treat ocular fungal keratitis in the eye. A 32Box-behnken design was used to produce a variety of new formulas for hot-melt extrusion. The SLNs were evaluated by entrapment efficiency (EE percent), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). A series of in-vitro and in-vivo studies were carried out on the new formula. The produced vesicles’ EE, PS, PDI, and ZP values were all good. SLNs eye drops were numerically adjusted to include carbopol, a stabilizer, lipids, and a surfactant, among other substances. ZP of -36.5 ± 0.20 m

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

The Research is interested in the detailed comparative study of certain selection of
Imam Alsamarqandi in some subjects of washing and touching the Gracious Quran.
The value of this study is that it is related to one aspect of the duties obliged on Muslim
like parity.
The study has tried to collect certain scholars’ opinions of eight doctrines with the
selection of Alsamarqandi to make a comp arson between them and to show how
Alsamarqandi is able to create legal laws from his sources to lead the researchers nto have
knowledge about the syllabi of the famous scientists.
Finally we ask God to bless to what is right and to accept this study and make it part of
our good deeds, Ameen.

Providing Iraqi students with proficiency in English is the ultimate goal of the educational system which is a way of getting knowledge in the fields of arts, sciences, transferring knowledge and sciences to other communities. Therefore, conducting such a type of study is very important because the contents of English textbooks have a huge influence on learning of the students. Once the content of English textbooks contain errors as the correct one, this will effect on his/her learning. The present study is an attempt to evaluate the new course entitled “English for Iraq” for fifth grade students for secondary schools, by Olivia Johnston and Mark Farell. It aims to answer eleven questions relating to the following domains: strength, obj