Journal of Education for Pure Science-University of Thi-Qar

This study explained the protective effects of silymarin against liver toxicity induced by carbon tetrachloride (CCl4) in female rats. Silymarin, a natural herbal compound extracted from the Milk thistle (Silybum marianum) plant. The experiment included three groups, each consisting of six rats. The first group served as the negative control. The second group was exposed to CCl4 (CCl4 30 % dissolved in olive oil intraperitoneally (i.p) 3ml/kg body weight twice a week for four weeks to induce toxicity. The third group received a combination of silymarin100 mg/kg b.w and the CCl4 3ml/.kg b.w daily for Three weeks to assess its protective effects. In the conducted experiment, rats that received silymarin alongside CCl4 exhibited significant improvements(reduction) in liver enzyme toward the normal values (Alanine Aminotransferase ALT, Aspartate Aminotransferase AST, Alkaline Phosphatase ALP, and Gamma-Glutamyl Transferase GGT) levels and also exhibited significant improvements(reduction)in lipid profiles (Total Cholesterol (TC), Triglycerides (TG), Low-Density Lipoprotein (LDL) and Very Low-Density Lipoprotein (VLDL) and elevation in High-Density Lipoprotein (HDL), compared to those treated only with CCl4. While, they were significantly elevated in the CCl4 group compared to the control group, indicating the presence of liver injury. These findings indicate that silymarin may serve as a potential preventive option for reducing liver damage caused by CCl4. Conclusion: The silymarin demonstrates significant potential in protecting against CCl4-
Journal of Education for Pure Science- University of Thi-Qar
Vol.14, No. 4 (2024)
Website: jceps.utq.edu.iq Email:jceps@eps.utq.edu.iq
25
induced liver damage, making it a viable candidate for further investigation and potential therapeutic use in liver disease management Additional research is needed to comprehensively understand silymarin's impact on lipid metabolism and liver injury.

The research focuses on chatbot interaction enrichment using reinforcement learning and user modeling. It aims to develop a personalized RL-based response generation framework for the optimization of satisfaction, engagement, and completion rates for the users. Anonymized historical interaction data from 500 users were collected to generalize user-profiles and contextual models. This was done by extracting features and observing and evaluating the control and experimental groups to test the efficacy of the working personalized system. Results indicated an overall increase of 35 percent in user satisfaction, 50 percent in session duration, and 25 percent in rates of completion of tasks against the traditional rule-based system. The results are very much in line with current literature on the improvements personalization can bring to the user's experience across many domains. The results from this study thus propose that personal AI systems powered with fine-grained models of users and reinforcement learning could obtain more engaging and efficient user interactions. The result has further-reaching implications for, for example, e-learning, customer service, and healthcare applications.

People can now communicate with each other and share ideas thanks to social media by posting content on many communication platforms every day. Text comments have become the most widely used in posts across various social media platforms, through which users express their opinions. Manually classifying these comments is a time-consuming process, so this study aims to use artificial intelligence techniques to solve this problem effectively. In this study, we rely on natural language processing (NLP) techniques to classify comments into three categories: positive, negative, and neutral, while using deep learning techniques to increase classification accuracy. The study focuses on classifying tweets posted in the English language on the Twitter platform, using a dataset obtained from Kaggle. A long-short-term memory (LSTM) network architecture improved the model performance. The results showed that the proposed model was able to achieve up to 87% accuracy in classifying tweets, highlighting its effectiveness in this field. This model enables reviews to be automatically categorized, which helps customers in their search for goods or services before transacting and saves time. Additionally, marketers can use it to find out what audiences think about their brands and products.

Cirrhosis is an advanced stage of many chronic liver diseases, primarily caused by viral hepatitis. Early detection is crucial to prevent further liver tissue scarring and to prolong patient survival. AI-based computer-assisted diagnostics, utilizing Machine Learning (ML) and Deep Learning (DL) methods, offer significant advantages over conventional approaches by reducing time, effort, and risks, in addition to improving the accuracy and efficiency of diagnosis. This paper aims to review recent key studies on diagnosing various liver diseases, with a focus on cirrhosis, using ML and DL techniques. Additionally, it will cover publicly accessible liver disorder datasets and metrics for evaluating model performance and discuss existing research restrictions and future works for the automatic detection of cirrhosis

The current research is concerned with double stage shrunken technique in order to estimate the shape parameter (Burr XII) distribution, when previous knowledge regarding the value shape is available as the original estimate. The formulas for the Relative efficiency, mean squared error, and bias ratio are derived, For the aforementioned expressions, numerical results and conclusions were shown.

In this paper, we have learned about the memristor in a simple way from previous studies.
Here, we introduce it into a simple circuit, which is the Muthuswamy- Chua circuit, which
consists of a resistor, an inductor, and a nonlinear element that we will replace with the
memristor. We will know the mathematical relationships using dimensionless equations, as
we use two different formulas for the memristor. To compare the two formulas and know
which formula is better in producing chaos and which is better in stability, we use branching
diagrams, time series, and phase diagrams. We find chaotic behavior, fractals, and also the
periodic binary and tri-periodic binary of the two formulas.

his study examines heavy metal concentrations in desert flora from two locations in Basra Province, Iraq, offering essential insights into environmental pollution. Heavy metals were analyzed at various locations to assess variability. Cadmium displayed stable levels, whereas cobalt demonstrated considerable variations, signifying an irregular distribution. Manganese was abundant although markedly inconsistent. Nickel exhibited stability. Lead had stable amounts, but zinc displayed significant presence and change. These results guide environmental evaluations and management strategies. The variability among places and plant species underscores the impact of local variables and physiological characteristics. Erodium glaucophyllum, Diplotaxis harra, and Astragalus spinosaexhibited unique accumulation capacities. Soil properties varied, clarifying ecological processes. This study enhances the comprehension of heavy metal accumulation patterns in Iraqi desert vegetation, supporting efforts for conservation and contamination reduction.

This study explained the protective effects of silymarin against liver toxicity induced by carbon tetrachloride (CCl4) in female rats. Silymarin, a natural herbal compound extracted from the Milk thistle (Silybummarianum)plant.The experiment included three groups, each consisting of six rats. The first group served as the negative control. The second group was exposed to CCl4 (CCl4 30 % dissolved in olive oil intraperitoneally (i.p) 3ml/kg body weight twice a week for four weeks to induce toxicity. The third group received a combination of silymarin100 mg/kg b.w and the CCl4 3ml/.kg b.w daily for Three weeks to assess its protective effects. In the conducted experiment, rats that received silymarin alongside CCl4 exhibited significant improvements(reduction) in liver enzyme toward the normal values (Alanine Aminotransferase ALT, Aspartate Aminotransferase AST, Alkaline Phosphatase ALP, and Gamma-Glutamyl Transferase GGT) levels and also exhibited significant improvements(reduction)in lipid profiles (Total Cholesterol (TC), Triglycerides (TG), Low-Density Lipoprotein (LDL) and Very Low-Density Lipoprotein (VLDL) and elevation in High-Density Lipoprotein (HDL), compared to those treated only with CCl4.While, they were significantly elevated in the CCl4 group compared to the control group, indicating the presence of liver injury. These findings indicate that silymarin may serve as a potential preventive option for reducing liver damage caused by CCl4. Conclusion: The silymarin demonstrates significant potential in protecting against CCl4-
JournalofEducationfor Pure Science-UniversityofThi-QarVol.14, No. 4 (2024)Website:jceps.utq.edu.iqEmail:jceps@eps.utq.edu.iq25induced liver damage, making it a viable candidate for further investigation and potential therapeutic use in liver disease management Additional research is needed to comprehensively understand silymarin's impact on lipid metabolism and liver injury.

This study presented new analytical and numerical solutions for the two-dimensional heat-like differential equation with fourdifferent fractional derivatives using the Laplace-Adomian decomposition method. This paper introduced the algorithm of the method used with each of the four fractional derivatives and then presents the analytical solutions of the heat equation as well asthe numerical solutions and two-dimensional graphs with the help of Maplesoft and MATLAB.

A wide variety of commensal microorganisms reside on the skin, many of which secrete proteolytic
enzymes that might have detrimental effects following an injury. These bacteria are considered
opportunistic pathogens. The aim of this study is a detection and identification of Staphylococcus spp.
isolated from animal skin (cows) and conduct molecular characterization of the isolated strains in order to
examine their enzymatic production capabilities, and to determine the ideal conditions for bacterial
development. A total of 25 swab samples were obtained from animal skin wounds in Al-Shatrah city (from
veterinary clinic after the permission had been taken from the animal breeder). Each sample was inoculated
into each of nutrient agar, blood agar, and Brain Heart Infusion Agar (enrichment media); and Mannitol
salt agar (differential and selective medium). All isolates were subjected to molecular detection using the
PCR (The conventional polymerase chain reaction) technique. Moreover, 10 isolates were sequenced using
the Sangerdideoxy sequencing method targeting the 16S rRNA gene. Enzyme production properties were
analyzed, and the sensitivity of bacteria to six antibiotics was studied. Analysis of 25 swab samples taken
from animal skin wounds yielded a total of 18 isolates. According to the results, 18 bacterial strains were
isolated from the samples. Biochemical tests identified the majority of these strains as S. aureus, S.
haemolyticus, S. epidermidis, and S. borealis. Among these isolates, S. warneri and S. epidermidis showed
sensitivity to Novobiocin, with inhibition zones of 22mm and 21mm, respectively. However, all other
isolates tested exhibited resistance to novobiocin. Staphylococcus is categorized as an opportunistic
bacterium, meaning it can cause many clinical symptoms in animals and can be transmitted to humans through animal products. Additionally, the use of antibiotics in food contributes to the development of
antibiotic resistance among Streptococcus species. The current study is the first to isolate and identify
Staphylococcus sp. from superficial wounds on cows’ skin in Thi-Qar province/Shatrah city.

We theoretically study chaos synchronization of two diodes that emit light using quantum dots (QDLED) which are delay coupled via aclosed andopen –loop coupling systemactive relay. While the chaotic systems are synchronized, their dynamics is identical to a single QDLEDwith delayed optoelectronicfeedback for an open –loop system active relay. There is total synchronization in the system depending on the coupling parameters., i.e., the extent of the QDLED’s chaos regime under external optoelectronic feedback isevaluated in terms of the chaos synchronizationresidue and lag diagram for the optimal coupling strength range isdebatedas well. Under appositeconditions, the headsetQDLEDcanbe satisfactorily harmonizedwith the transmitter QDLEDdue tothe optoelectronicfeedback effect.

In order to protect data security, the study examined the relationship between online banks and their clients. Using a mixed-methods approach it was possible to identify a commitment to cybersecurity responsibilities and a common understanding between banking sector and their customers. The results showed that customers believe that banks' cybersecurity measures were effective and they had a strong sense of personal responsibility to follow security precautions when using online banking. The study also underlined how important cutting-edge technologies are to strengthening cybersecurity defenses. The study provides several recommendations to improve cybersecurity procedures and address cyber threats in the banking industry, including investi1ng in cybersecurity talent, collaborating with partners, integrating cutting-edge technologies, conducting frequent security assessments, and improving customer communication.

The concepts presented in this paper pertain to the development and examination of AB-coupled fixed point results for mapping in partially ordered S-metric spaces that possess the strong mixed monotone property. The existence and uniqueness of AB-coupled fixed points are also demonstrated. We generalize the main theorems of Gnana Bhaskarand Lakshmikantham (2006) in [15] and Virendra Singh Chouhan and Richa Sharma (2015) [4].

In this study, we introduced a novel scheme to attain approximate and closed-form solutions of fractional telegraph equations, which belong to the most consequential amplitude equations in physics. The Yang transforms (YT) and the Adomian decomposition method (ADM) is combined in the proposed method. We call it the Yang Adomian decomposition method (YDM). Some examples are given to illustrate the accuracy of the numerical results by YDM. As a result, YDM demonstrates that it is a useful and simple mathematical tool for getting approximate and exact analytical solutions to linear-nonlinear fractional telegraph equations (FTEs) of the given kind. The convergenceand absolute error analysis of the series solutions is also offered.Keywords:Yang transform; Adomian decomposition method; Telegraph equation; Caputo fractional operator.