Pure Sciences International Journal of Kerbala

Low affinity energy thresholds were precisely tailored into the Zn3Se3 cluster's molecular geometry configurations. The structural and electronic characteristics of the Zn3Se3 composite were examined using the 6-113G (d, p) basis set for density functional theory calculations (DFT/B3LYP). Comprehensive vibrational mode frequencies were methodically examined using potential energy distribution as a basis for analysis. The energy band gap (E????) for the Zn3Se3 structured was computed and plotted HOMO and LUMO, or high occupied and low unoccupied molecular orbitals, are frontier values. The result is the value of E???? (0.0383) eV. The molecular electrostatic potential as well as surface and contour diagram of Zn3S3 were determined, along with electronic properties of the stated structures. These include IP, EA, Ef, E????, ????????, χ, η, S, and ω.

The grafted nanocopolymers were synthesized via an esterification process, where the first step was to generate a linear copolymer by reacting terephthalic acid with glycerol. Then, a certain amount of maleic anhydride was added to the resulting linear copolymer solution to obtain the grafted PTGM nanoparticles. The prepared nanopolymers were characterized using FT-IR spectroscopy, 1H-NMR, and atomic force microscopy (AFM). The average particle height was 8.3 nm and was exposed to three different temperatures (298, 308, and 318 K). Four different concentrations (1, 3, 5, and 7 ppm) of the nanocopolymers were examined and it was evident that they play a vital role in the adsorption process. The experimental results showed that the average surface area of this nanopolymer for adsorption of dye (methyl orange) decreased with increasing temperature, indicating that the process is endothermic. It was also observed that the highly efficient nanocopolymers were able to successfully remove (methyl orange) from aqueous solutions.

Polycystic ovarian syndrome (PCOS) is characterized by several symptoms, such as hirsutism hyperandrogenism, amenorrhea, anovulation, sterility, as well as metabolic and endocrine disorders. This study was conducted to evaluate the efficacy of an extract from the roots of Asparagus officinalis L. in treating female rats with induced polycystic ovarian syndrome. In this study, the impact of 400mg/kg of asparagus officinalis L. roots extract on the polycystic ovarian syndrome was examined over a period of 28 days in order to scrutinize the effects of asparagus officinalis L. roots extract on letrozole-induced polycystic ovary syndrome.
Thirty female albino rats were chosen. They were divided into five groups. Group 1 Control, Group 2 asparagus officinal is Extract 400 mg/ kg for 28 days, Group 3 is the PCOS inducer. Rats were given letrozole (1 mg/kg) orally for 28 days in a 0.5% Carboxy-Methylcellulose (CMC) solution. Group 4 is a treatment group in which the animals were dosed with letrozole for 28 days. After that, they were dosed with asparagus root extract for another 28 days, and Group 5 is the preventive group, which received asparagus root extract for 28 days. Then, it was dosed with letrozole for the same period. The Trichrome stain showed results low in stroma and collagen fibers of the structure ovaries in all groups, including control except the PCOS group that indicates a high presence of collagen. In addition to the number of primary, antral, and graphene follicles increased considerably. The treatment and preventative groups showed fewer cystic follicles than the PCOS group. The findings reveal decrease in collagen fibers by asparagus root extract. Therefore, it speeds up oogenesis and early cell divisions.

Background: Pfizer vaccine, which is a nucleoside-modified mRNA vaccine against coronavirus disease 2019 (COVID-19) is one of the first mRNA products to be approved by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA).
Aim of the study: The aim of this study is to study the impact of Pfizer vaccine on the levels of interlukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) after 3 months and 6 months of vaccination with Pfizer vaccine.
Materials and methods: The study was done during the period from May /2022 to September / 2022). A case-control study involved 150 subjects who were divided into three groups (each group included 50 subjects). The first group included (50) vaccinated group 3 months after second dose of Pfizer vaccine, and the second group included (50) vaccinated group 6 month after second dose of Pfizer vaccine. The third group was the control group which included (50) healthy unvaccinated subjects. Serum levels of IL-6 and TNF-α were estimated by ELISA technique. Results: The results showed that the mean levels of TNF-α among male participants (after 3 months of vaccination, after 6 months of vaccinations, and in the control group) were (65.40, 47.34, and 9.45), respectively, with highly significant differences between the three groups (p<0.01). The results showed that the mean levels of TNF-α among female participants (after 3 months of vaccination, after 6 months of vaccinations, and the control group) were (67.50, 48.74, and 9.06), respectively, with highly significant differences between the three groups (p<0.01). In addition, the results showed that the mean levels of IL-6 among male participants (after 3 months of vaccination, after 6 months of vaccinations, and the control group) were (81.36, 101.88, and 51.26), respectively, with highly significant differences between the three groups (p<0.01). The results showed that the mean levels of IL-6 among female participants (after 3 months of vaccination, after 6 months of vaccinations, and the control group) were (83.05, 98.03, and 52.07), respectively, with highly significant differences between the three groups (p<0.01). Conclusion: Pfizer vaccine was shown to have significant impacts on IL-6 and TNF-α levels among vaccinated individuals.

This study used Lie transformations to provide both numerical and analytical answers for the partial reaction-diffusion-adhesion equations for both time and space. If the balances allowed via the goal calculations permit the determination of Lie transformations, then we can reduce slight fractional variance calculations to normal variance calculations containing fractions. We suggest a different approach to find the numerical and analytical answers beginning from the numerical and analytical answers in the spatio-temporal fractal adhesion-diffusion-interaction model. Recent findings on the adhesion-diffusion interaction equation were obtained by the authors. Separate adhesion-diffusion reaction equations for partial temporal and spatial variables were presented.
The excellent accuracy of the suggested approach makes it a useful instrument for solving a Wide category of fractional differential equation problems. The numerical results show its effectiveness and applicability.

Ring theory is one of the branches of an abstract algebra. This field is the study of a mathematical system with two binary operations. In this branch, many articles have studied this algebraic structure and presented some new works. However, the concept of purity has been studied before more than 40 years ago, especially the relation between the pure ideal and some other ideals on the given ring. In this paper, we survey the important results that concern with pure ideals. Some different types of ideals have been discussed such as N-pure ideals, z-ideals, Π-pure ideals and strongly pure ideals. Moreover, some recent results based on the work of several researchers have been summarized. On the other hand, regarding these types of ideals, some questions have been presented. Furthermore, many important results about various types of rings which are based on the notion of pure ideals have been studied.

Generative Pre-Trained Transformer (GPT) is the arrangement of language models, displaying momentous changes over its forerunners through the integration of state-of-the-art procedures and modern calculations. This comprehensive term paper dives deeply into the complexities of Chat GPT-4, unwinding the basic strategies, novel progressions, and potential applications that make it a trailblazer in the early NLP model development. With a focus on both specialized and moral contemplations, the paper investigates the energetic scene encompassing Chat GPT-4. It fundamentally analyzes its potential moral suggestions, such as predispositions and reasonableness concerns, and emphasizes the requirement for mindful advancement and arrangement of such effective dialect models. The moral talk is expanded to include straightforwardness, responsibility, and societal effect, calling for vigorous rules and systems to guarantee the mindful and comprehensive utilization of Chat GPT-4 in various spaces. The term paper sheds light on the challenges that go with the modernity of Chat GPT-4, tending to issues such as fine-tuning, provoking building, and guaranteeing the model's flexibility to distinctive assignments and spaces. Besides, it traces potential future inquiries about headings, empowering proceeded investigation and progressions in dialect to demonstrate improvement. By emphasizing the significance of moral contemplations, talking about specialized headways, and investigating potential applications and challenges, this term paper serves as a comprehensive direction for analysts, professionals, and policymakers looking to explore the advancing scene of Chat GPT-4 and tackle its transformative potential whereas maintaining moral guidelines and societal values.

The fast improvements in Autonomous Vehicle (AV) systems have shown the necessity for effective image processing approaches to enable efficient decision-making. Current approaches generally fail to offer a balance between processing speed and precision, restricting their usefulness in AV scenarios. The work sets out to tackle these difficulties by applying advanced AI-driven methodologies, EfficientNet and MobileNet, to optimize picture analysis for AV systems. This research filled a breach by enhancing both the speed and accuracy of real-time image processing systems. Also, it contributed to scientific studies in this sector. According to the KITTI Vision Benchmark Suite and Berkeley DeepDrive datasets, the experimental quantitative research designs. Proposed models were trained and tested using these datasets. TensorFlow and Keras frameworks incorporated advanced convolutional neural network topologies with transfer learning algorithms. The models were released loose under varied driving circumstances to see how flexible and resilient they were. The statistical importance of performance parameters like accuracy, inference time, and F1-score was evaluated. The results reveal that EfficientNet can obtain an accuracy of 94.2% and an inference time of 18 ms/image, which is substantially better than the baseline. MobileNet was a plausible option, exhibiting amazing accuracy while being computationally efficient. This improvement was statistically significant, and qualitative assessments indicated that the models were powerful under bad conditions. The research advances real-time imaging analysis in AVs, pointing to the need for architectural adjustments and dataset diversity. As a result of this research, the field of AI-controlled image processing will advance and lead to creative developments in AV systems and their applications

Leishmaniasis is a protozoan parasitic disease caused by various strains of Leishmania spp. Leishmaniasis is one of the most common zoonotic infectious diseases worldwide. It is considered one of a major public health problem, with three diseases forms, cutaneous, mucocutaneous and visceral. It is known by various names but in Iraq cutaneous form is known as Baghdad boil. This paper includes the review of prevalence of Leishmania species in humans and dogs throughout Iraqi governorates and this dependes on Iraqi researches that have been published in different International and local journals .This study reportes wide variation in the infection rate of parasite due to many reasons such as Propaganda of public health, spread of insects, uncontrolled roaming of stray dogs and the different methods of diagnosis of parasite that lead to variation of prevalence rate in Iraq .