Journal of University of Babylon

Introduction:
This study was conducted to know the effect of adding wormwood extract to drinking water and comparing it with the antibiotic tylosin on some immune and biochemical characteristics of broiler chickens.
Methods:
525 broiler chickens of the Rose 308 strain used in this experiment, divided into 6 treatments with 3 replicates for each treatment. The treatments were as follows: (T1) drinking water without addition (control treatment), (T2), (T3) 0.25, 0.50 gm tylosin / liter of water. (T4), (T5), (T6) 0.25, 0.50, 1 ml wormwood extract / liter of water. Some blood biochemical parameters were measured like total protein, glucose, cholesterol, triglycerides and immune parameters to determine the amount of antibodies against Newcastle disease, Gumboro, infectious bronchitis and influenza in broiler chickens.
Results:
The results showed no significant differences in the percentage of glucose and triglycerides, while there significant differences (P≤0.01) in the percentage of cholesterol and total protein, in which the wormwood treatments were superior compared to the tylosin treatments and control. In the immune characteristics, there significant differences (P≤0.01) in the size of antibodies directed against Newcastle disease and influenza, in favor of the tylosin treatments compared to the wormwood treatments, while for gumboro and infectious bronchitis, there were no significant differences.
Conclusion:
The aqueous extract of wormwood gave a similar effect to the antibiotic tylosin with regard to the biochemical characteristics of blood, there was no significant difference between the treatments with regard to antibodies directed against the Newcastle, gumboro , infectious bronchitis and influenza.

Laser technology has a significant impact on our lives in numerous ways. Its contributions to the fields of medicine and dentistry are significantly impacting patient care and well-being. Gingivectomy, pulpotomy, frenectomy, cavities, cysts, tumors, ulcers, and other soft and hard tissue procedures have all been transformed by laser technology, which has also transformed dental care. It has become a fascinating technology in dentistry, and it is used in various clinical practices for multiple procedures. Because of their significant absorption in haemoglobin, near-infrared (NIR) wavelengths have proven excellent for multiple soft tissue treatments. This article provides a comprehensive overview of NIR lasers and their applications in dentistry, focusing on how these tools may precisely cut, coagulate, ablate, or vaporize particular tissues while improving efficiency, specificity, comfort, and ease of use.

Background:
Polyvinyl alcohol (PVA) is a versatile synthetic polymer with excellent optical and mechanical properties, making it suitable choice for a range of applications. The incorporation of tungsten disulfide (WS₂) nanoparticles into PVA offers the potential to enhance these properties, enabling applications in flexible electronics and optoelectronic devices.
Materials and Methods:
Thin films of PVA doped with WS₂ nanoparticles at concentrations of 0.5%, 1%, and 2% were prepared using the casting method. The films were deposited with a thickness of 150 nm on glass substrates. Structural and optical characterizations were performed using X-ray diffraction (XRD) and UV-Vis spectroscopy to study the semi-crystalline nature and optical behavior of the composites.
Results:
The XRD analysis revealed that the semi-crystalline nature of pure PVA and the formation of crystalline WS₂ phases with increased doping ratio. UV-Vis measurement showed enhanced light absorption in the visible region, with a consistent red shift in the absorption edge. The direct band gap decreased from 4.1 eV for pure PVA to 4.03 eV for 2% WS₂-doped films, while the Urbach Energy increased, indicating higher structural disorder with increasing doping.
Conclusions:
The incorporation of the WS₂ nanoparticles into PVA significantly alters its structural and optical properties, reducing the band gap and enhancing light absorption. Results highlight the potential of PVA/WS₂ Nano-composites for use in photonic and optoelectronic applications.

Background: This experiment was conducted to study the effect of adding anise and clove oil on the physiological performance of broiler, represented by biochemical traits and carcass components, for a period of 35 days.
Materials and Methods: In this experiment 300 Ross 308 broiler chicks One-day old were used. The chicks were randomly distributed into six equal treatments with two replicates for each treatment (25 birds per replicate). The birds were divided into treatments as follows: The first treatment (T1) basic diet, second and third treatment (T2 and T3) basic diet with anise oil added at 0.5 and 0.1 ml/kg feed respectively, fourth and fifth treatment (T4 and T5) basic diet with clove oil added at 0.5 and 0.1 ml/kg feed respectively, and sixth treatment (T6) basic diet with 0.5 ml/kg of each anise and clove oil. Some biochemical traits of blood, carcass and dressing percentage were measured.
Results: The results of the experiment showed that adding anise oil, clove oil and their mixture had a significantly excelled (P<0.05) in the biochemical traits and carcass properties compared to the control. The results also showed that adding a mixture of anise and clove oil 0.5 for each of them had the best biochemical traits and carcass properties, which was found in the sixth treatment of the experiment.
Conclusion: We can conclude that adding anise and cloves oil has a positive effect on some biochemical characteristics of the blood and it also improves the weight of the carcass for broiler.

Background:
Accurate diagnosis and treatment rely on medical imaging, which presents challenges due to the vast data generated by MRIs and CT scans. Managing such volumes is complex in storage and transmission. Efficient image compression techniques are essential for telemedicine and cloud-based systems, enabling seamless data transfer while preserving quality.
Materials and Methods:
This study compares three widely used compression techniques: Adaptive Huffman Coding (lossless), Discrete Cosine Transform (DCT) (lossy), and Adaptive Multi-Layer Run-Length Encoding (AMLRLE) (lossless). A dataset of DICOM medical images was used, and techniques were evaluated based on three key performance metrics: compression ratio (CR) for data reduction, processing time (PT) for computational efficiency, and Peak Signal-to-Noise Ratio (PSNR) for assessing image quality.
Results:
Huffman Coding, a lossless technique, achieved a high compression ratio of 0.972 with an average compression time of 0.028 seconds. However, it exhibited lower image quality than DCT and AMLRLE. DCT, a lossy method that converts image data into frequency components, provided a compression ratio of 0.964, a processing time of 0.088 seconds, and a PSNR of 317.55 dB. AMLRLE, another lossless technique, showed performance nearly identical to DCT, maintaining the same compression ratio, processing time, and PSNR.
Conclusion:
Huffman Coding suits applications needing fast processing, while DCT and AMLRLE are better for high-quality imaging. The choice of compression method depends on system needs—speed, storage, or diagnostic precision. Future research will integrate these techniques with machine learning to enhance adaptive compression for medical imaging.

Background:
In the United States, cancer is a leading cause of death and a significant cost of healthcare. Improving treatment outcomes and survival rates depends on accurate early cancer prediction and understanding the genetic pathways underlying its formation. Over the past 20 years, efforts have been made to classify cancer types using machine learning and deep learning techniques.
Materials and Methods:
In this study, a data sample of (138) patients was used, where the sample for the first population (myeloid leukemia) was 65 patients who were given (1), and the second population sample (lymphocytic leukemia) was 73 patients who were given (2). The data was divided into 75% for training and 25% for testing.
Results:
Classification results using neural networks were good, showing high prediction accuracy and a classification rate of 91.4%, confirming the high efficiency of the neural network. However, the results could be more robust and generalizable with access to a larger dataset. To address this issue, we plan to conduct future experiments on a larger and more diverse dataset to further validate the performance of our model.

Background:
Breast cancer is a disease that develops in breast tissue as a result of internal and external factors, such as genetic mutations, lifestyle, environmental exposure, and psychological and social factors. The overall incidence of breast cancer ranges from 5% to 10%, 20% to 30%, respectively.
Materials and Methods:
Breast masses, classified as malignant or benign, were identified using ultrasound images. Pre-processing included resizing images to 150x150 pixels, contrast normalization, data augmentation, and resampling to address class imbalance. A pre-trained EfficientNetB7 model was used for binary classification. The dataset was split into training (80%) and testing (20%). Model performance was validated using the "Multi Cancer Dataset" from Kaggle, which contains 2,191 images.
Results:
The model performed exceptionally well in distinguishing malignant and benign cases. For malignant cases, it achieved 0.98 accuracy, 0.99 sensitivity, and 0.99 F1-score. For benign cases, accuracy was 0.92, with sensitivity and F1-score of 0.87 and 0.89, respectively. The overall accuracy, sensitivity, and F1-score were 0.98. The ROC curve showed an AUC value above 0.9, indicating high sensitivity and a low false-positive rate. On external datasets, the model maintained an accuracy of 0.94.
Conclusion:
The results indicate that pre-trained deep convolutional neural networks can make significant progress in accurately detecting malignant cases while reducing false alarms, enhancing its clinical application and role in improving breast cancer diagnosis using AI techniques.

Recently, the demand for birds in cages has increased significantly, driven by the desire to enjoy the beauty of birds and their songs and the pressure of individuals, especially children, to raise and tame them so they can live in their homes. The most popular pet birds are cockatiels, canaries, budgerigars, and lovebirds. Inhalation, vector-borne, and fecal-oral pathways are how zoonotic illnesses are spread. Humans can contract zoonotic infections from direct or indirect contact with contaminated bird droppings, cages, or food sources. Histoplasmosis is one of the most important fungal diseases affecting humans, and it originated in birds. Subclinical or moderate respiratory illnesses are among its clinical symptoms, as is progressive disseminated histoplasmosis (PDH), a potentially fatal sickness whose precise identification is still difficult and scarce in many nations where it is widespread. One way to help avoid zoonosis in humans and birds is to use human protective equipment, clean and sanitize bird cages, and practice biosecurity and hygiene.

Background:
A detailed study of the nuclear structure of 〖Ne〗^20 has been conducted using the nuclear shell model in conjunction with Hartree-Fock parameterization techniques to provide a deeper understanding of its structural properties.
Materials and Methods:
The investigation utilized the psd model space along with the PSDMK effective interaction, taking 〖He〗^4 as an inert core. The model treats the remaining 16 nucleons as active particles interacting within the defined space. Radial wave functions essential for calculating matrix elements were generated using the Hartree-Fock method with various Skyrme force parameterizations, including SkXcsb, SkXta, and SLy4. In addition, harmonic oscillator (HO) wave functions were employed for comparative analysis to evaluate the effect of different single-particle bases on nuclear observables.
Results:
Several nuclear properties were systematically analyzed, such as longitudinal electron scattering form factors, low-lying energy levels, B(E2) transition strengths, magnetic dipole moments, electric quadrupole moments, root mean square charge radii, and total binding energy.
Conclusions:
This study emphasizes the benefits of utilizing a 〖He〗^4 core in shell-model calculations for 〖Ne〗^20 by modeling it as a system of five alpha-like clusters. The results indicate that such a cluster-based approach improves theoretical predictions and offers a robust framework for exploring nuclear structure phenomena in light nuclei.

Background: The compatibility of Trichoderma harzianum with some recent commercial fungicides by combining them to promote an efficacious IDM for controlling plant pathogens and prohibiting chemical resistance evolution in pathogens.
Materials and Methods: laboratory experiments were conducted to study the compatibility of Trichoderma harzianum with three commercial systemic fungicides: Al-Sary (Carbendazim 50%WP), Top Topsin (Thiophanate-methyl 70%), and Tachichem (Hymexazol 30%WP) at recommended doses (2500 ppm for Al-Sary fungicide, 500 ppm for Top topsin, and 1.5 ppm for Tachichem) by the food poisoning technique against six pathogenic fungi: Alternaria sp., Aspergillus flavus, Aspergillus niger, Aspergillu wentii, Penicillium sp., and Rhizopus sp .
Results:T. harzianum displays various degrees of antagonism against the tested pathogenic fungi in dual culture. Asp. wentii was most sensitive to the T. harzianum antagonistic activity, with an inhibition percent of 67.91%, while Rhizopus sp. displayed complete resistance to the antagonistic activity. The results showed Asp. niger, Asp. wentii, and Penicillium sp. were completely inhibited by Al-Sary fungicide. Asp. wentii and Penicillium sp. were totally inhibited by Top Topsin fungicide, Rhizops sp. was not affected by the two fungicides. Asp. niger displays high sensitivity to Tachichem fungicide (87.23%), whereas Penicillium sp. was resistant to the fungicide (0.0%). Tachichem fungicide showed complete compatibility with T. harzianum,but Al Sary and Top-Topsin fungicides were remarkably toxic to T. harzianum. The effect of fungicides on T. harzianum antagonistic activity was estimated in PDA medium.
Conclusion The compatible fungicide Tachichem can be applied with T. harzianum in a comprehensive way to disease control techniques.

Microorganisms within the oral cavity exist in balance with one another and the host's immune system, contributing to oral health. Disruption of this balance can result in microbial activity that leads to oral diseases and oral diseases are linked to microorganisms that exist in the oral cavity. Mouth contains one of the utmost complex in addition to various microorganism ecosystems in the human body. The oral microorganism contributes to maintaining homeostasis within the oral host. However, environmental, behavioral, or systemic changes can lead to ecological shifts in the balanced microbial community, leading to oral diseases including dental caries and periodontitis. These microorganisms exist in a balanced manner with each other and with the immune system of the organism, and thus this leads to maintaining oral health. However, any imbalance in this balance leads to the microorganisms living in the mouth becoming disease-causing. This review aims for survey the structure and dynamics of the mouth microorganism, the transition from commensalism to pathogenesis, diseases caused by microorganisms present in the mouth, the relationship of these microorganisms to people with immune deficiency, and current procedures to restore microbial balance. Understanding these dynamics can guide the development of targeted therapies for oral and systemic health.

Background: This research intended to assess the impact of various taurine dosages on angiogenesis and their effect on some hematological and biochemical traits (Hemoglobin (Hb), packed cell volum PCV, cholesterol, triglyceride ,glutathion GSH, malondialdehyde MDA, body weight of animal after and before experiments, and hepatocyte tissues. in rats males exposed to Taurine (500,1000,1500,2000) mg for months.
Material and Method: Six groups of eight rats each were created from the rats. Six groups of eight rats each were created from the rats. receiving different doses of taurine.

Result: results revealed a significant increase for (Hb, PCV, GSH, body weight before experiment) while a significant decrease to (TG, MDA, Cholesterol, body weight after experiment), and many histological changes including congestion of sinusoidal and central vein, infiltration of inflammation cell around central vein and sever vacuolation of hepatocyte.
Conclusion: High doses of taurine affect angiogenesis in hepatic tissue and stimulate hematological and biochemical responses.

Background:
This study examined toxic effect of a member of the macrolide antibiotic family, erythromycin, on the levels of certain enzymes, namely glutathione (GSH) and catalase (CAT), and investigated the protective role of Vitamin C in mitigating its toxicity in male albino mice (Mus musculus).
Materials and Methods:
A total of 25 male albino mice were used in the experiment and divided into five groups. The first group served as the control. The second and third groups (treatment groups) were administered erythromycin at doses of 15 mg/kg and 30 mg/kg, respectively. The fourth and fifth groups (protective groups) were given Vitamin C at a dose of 100 mg/kg along with erythromycin. The experiment lasted for 14 days.
Results:
A significant decrease in GSH and CAT levels was observed in the treatment groups: (31.2 ± 0.3 µmol/L, 402.9 ± 15.08 U/L) for the second group and (32.1 ± 0.1 µmol/L, 374.9 ± 17.9 U/L) for the third group, which received erythromycin at doses of 15 mg/kg and 30 mg/kg, respectively, compared to the control group at a significance level of (P≤0.05). However, the fourth and fifth groups, which were administered vitamin C along with erythromycin, exhibited an increase in enzyme levels, with no significant differences compared to the control group at the same significance level.
Conclusion:
Erythromycin exerts a dose-dependent toxic effect on the levels of glutathione and catalase enzymes in the serum of albino mice. Additionally, vitamin C has a protective role in reducing the drug’s toxicity when administered together.

Federated Learning (FL) represents a transformative advancement in Artificial Intelligence that enables decentralized model training across multiple institutions or devices without transferring raw data. This paradigm is particularly significant for sectors such as healthcare, where privacy, security, and compliance are paramount. This review explores the core principles of FL, its architectural framework, and key differentiators such as horizontal and vertical FL, while examining its major applications across domains including healthcare, finance, mobile systems, and robotics. Through a critical analysis of recent studies, the paper highlights FL's potential to enhance data privacy, mitigate bias from heterogeneous datasets, resist cybersecurity threats, and optimize communication efficiency. It also addresses the limitations that challenge FL's broader adoption, such as high computational costs, vulnerability to adversarial attacks, and data inconsistency across nodes. The findings suggest that FL has the potential to reshape the future of AI by enabling collaborative intelligence without compromising data confidentiality. The paper concludes by outlining future directions for FL research, including adaptive aggregation, secure federated algorithms, and energy-efficient frameworks to enable scalable, ethical, and privacy-aware AI systems.

Both adults and children can have tonsillitis, a common respiratory illness. Allergies, respiratory issues, and bacterial and viral infections account for the majority of tonsillitis instances. Inflammatory factors like bacteria and the tonsils' lymphoid tissue interact in tonsillitis. Fever, enlarged tonsils, congestion, and diminished function are some of the symptoms brought on by this interaction. As two lymphoid organs, the palatine tonsils, are in charge of immunological defense against eaten and breathed microorganisms and are situated at the start of the upper gastrointestinal tract. Mediating host defensive mechanisms against a range of infections, particularly those of bacterial origin, Th17 cells and their effector cytokines also It has a role pathophysiology of several autoimmune illnesses. Streptococcus pyogenes is the main cause of tonsillitis, caused by bacteria that play a significant role in tonsil infection. Streptococcus pyogenes is resistant to many drugs, including cefepime and clindamycin. The ASOT index measures the severity of the infection, while IL-10 is a sensitive indicator of infection.

Chronic kidney disease (CKD) as well as other organ systems could be impacted by Hepatitis C virus (HCV) infection, a global health issue with a considerable economic and health burden. Furthermore, compared to the general population, the frequency of hepatitis C is still greater in patients who have chronic kidney disease (CKD), such as those receiving chronic hemodialysis and those who have received a kidney transplant. Since Kidney Disease: Improving Global Outcome (KDIGO) released its 2008 guideline for the diagnosis, prevention, and therapy of hepatitis C in CKD, there has been a significant change in the way hepatitis C has been managed. Consequently, KDIGO released an update to such a recommendation in the year 2018. In this review, the suggestion for HCV detection and screening in CKD, HCV treatment prior to and following kidney transplantation, HCV treatment in CKD patients, treatment of kidney disease related to HCV infection, and HCV transmission prevention in hemodialysis units. This review focus on the clinical implications pertaining to direct-acting antivirals in patients undergoing dialysis, individuals afflicted with severe chronic kidney disease, as well as recipients of kidney transplants. This study emphasizes the critical importance of meticulously monitoring potential drug-drug interactions between immunosuppressive therapies and DAAs, discuss the optimal timing for initiating hepatitis C virus treatment in relation to the timing of kidney transplantation. Finally, the study identifies areas of ambiguity that necessitate further research prior to the formulation of definitive recommendations.

Background: Osteoporosis (OP) is a long-term skeletal disturbance marked by loss of bone mass and bone tissue degradation, which increases fragility and the risk of fractures. Because of hormonal changes that speed up bone resorption, postmenopausal women are most affected by this disorder. Oxidative stress indicators are among the many biomarkers that are essential for understanding the metabolic mechanisms that underlie osteoporosis.
Materials and Methods A case-control study of 120 participants (80 patients, 40 controls) was conducted. Serum levels of MDA, BSAP, D3 and Ca+ were measured using ELISA kits, Statistical analysis was performed using SPSS, with a significance level set at P < 0.05.
Results: A statistical analysis using the SPSS program demonstrated a significant reduction in vitamin D levels among patients suffering from osteoporosis and a healthy control group (P<0.005). Furthermore, individuals with osteoporosis showed elevated of BSAP, and malondialdehyde (MDA) levels, indicating heightened oxidative stress.
Conclusion: This study highlights the association between oxidative stress and osteoporosis severity. The results suggest that vitamin D may play a crucial role in counteracting oxidative damage and preserving bone integrity.

Background:
The zero-divisor graph Г_(0 ) (R) is central in algebraic graph theory. Let R be a commutative ring with identity 1≠0. In this work we define the multiplicative regular graph Г_(MR ) (R) as a generalization that captures the behavior of regular elements those satisfying a=aba or b=bab.

Materials and Methods:
The graph Г_MR (R) is defined using ring-theoretic conditions and graph-theoretic representations, Two distinct none-zero elements x and y are adjacent if and only if xy∈Reg(R). A Python-based algorithm is used to construct and visualize Г_MR (R) for finite commutative rings.
Results:
We prove that Г_(MR ) (R)≅Г_(0 ) (R) if and only if R={0,1}, and Г_(MR ) (R)≅G_(Vnr^+ ) (R) when R is a regular ring. The study includes analysis of key graph invariants such as connectivity, diameter, girth, and regularity.

Conclusion:
The graph Г_(MR ) (R) offers a generalization of existing graphs of commutative rings. By emphasizing regular elements, this model uncovers new structural relationships within the ring and explores ring-theoretic properties through graph-theoretic methods.

Background
It's been documented that Iraq houses numerous soil types that exist as an expression of varied climates, landscapes, and land-use patterns. This study focuses on the physical and chemical soil characteristics existing within five of Iraq's major geographical regions: Al-Anbar, Baghdad, Basrah, Erbil, and Diyala.
Materials and Methods
Analysis showed significant variation in salinity, organic matter content, bulk density, and soil texture from one region to another. For example, Al-Anbar soils are predominantly sandy (82%), with a high bulk density (1.60 g/cm³) and low organic matter (0.6%). On the other hand, clay-rich soils found in Basrah are extremely saline (EC = 8.0 dS/m, ESP = 45%), although bulk density is much lower (1.25 g/cm³).
Results
Baghdad and Diyala were loamier with more balanced textures and moderate fertility, as well as organic matter of between 1.8 and 1.9%. The hilly soils of Erbil, being of moderate permeability and low salinity (EC = 1.9 dS/m), were suitable for crop rotation and orchards.
Conclusion:
The findings clearly indicate that soil management practices are region-specific, calling for organic amendment applications to sandy soils, improved drainage in saline clay soils, and conservation methods in loamy areas.

Background: Black cumin (Nigella sativa L.) is a medicinal and aromatic herb from the Ranunculaceae family, traditionally used for its health benefits. It supports immune function, enhances brain activity, and offers protection against various chronic diseases. This study aimed to investigate the effects of black cumin on cholesterol and total protein levels (albumin and globulin) in healthy male rabbits.
Materials and Methods: Twenty-four healthy male New Zealand rabbits (5–6 months old, weighing 1200–1500 g) were divided into six groups. One group served as the control, while the other five received increasing doses of aqueous black cumin extract: 80, 130, 180, 230, and 280 mg/kg body weight per day. Blood samples were collected to assess serum cholesterol, total protein, albumin, and globulin levels after dosing.
Results: Cholesterol levels significantly decreased in the 80 and 130 mg/kg groups, while higher doses (180–280 mg/kg) caused a significant increase. Total protein levels were significantly elevated in groups C, D, and E, with the highest in group E (90.4 ± 1.4) compared to the control (70.6 ± 0.85). Globulin also increased in group E (280 mg/kg),while albumin levels showed no significant changes.
Conclusion:Low doses of black cumin reduced cholesterol levels, whereas high doses increased them. Total protein and globulin levels increased, while albumin remained unchanged.

ABSTRACT
Background:
The most common cause of death and disability in the world is stroke — which is a severe disruption of cerebral blood flow. We also see the biomarkers Troponin, Lactate Dehydrogenase (LDH), Creatine Kinase (CK), Hexokinase, and D-dimer used for stroke pathophysiology. Such biomarkers are associated with different disease parts, such as myocardial stress, cell damage, metabolic disturbance, and coagulopathy.
Objective:
This study aims to evaluate the correlation among Troponin, LDH, CK, Hexokinase, and D-Dimer levels in stroke patients to explore their clinical significance and potential as powerful diagnostic and prognostic tools.
Methods:
In a prospective study of 120 stroke patients, ischemic and hemorrhagic strokes. Blood was taken 24 hours after hospital admission for Troponin, LDH, CK, Hexokinase, and D-Dimer because of the beak of Troponin and other parameters will be reached after 24 hours from MI. The correlations of these biomarkers were calculated using Pearson correlation.
Results:
This is strong evidence of the positive correlations between all biomarkers that we found in our studies. Troponins correlated strongly with Lactate dehydrogenase LDH (r = 0.68, p 0.001), Creatin kinase CK (r = 0.71, p 0.001), and D-Dimer (r = 0.62, p 0.001) where r is statistically correlation-coefficient and p value is the probability. Similarly, LDH correlated strongly with CK (r = 0.75, p 0.001) and D-Dimer fragment of cross linked Fibrin D-Dimer (r = 0.65, p 0.001). Hexokinase was slightly inversely related to other biomarkers, suggesting an ischemic metabolic response.
Conclusion:
Because these biomarkers are significantly correlated, they may play an integrated role in stroke pathophysiology. Troponin, LDH, CK, Hexokinase, and D-Dimer might all be alternative markers for tissue injury, metabolic dysfunction, and coagulation abnormalities in stroke patients. This capability to be used in practice would go a long way toward improving stroke diagnosis and treatment, giving stroke patients a reason to feel confident in stroke care’s future.

Background: In this study, the optimal allocation calculation was adopted to determine the reliability of the neural network, as it is considered a mathematical model whose purpose is to process data and machine learning. This study contracts with the reliability of neural networks and finding the optimal work for them.
Materials and Methods: This research used a genetic algorithm with an exponential cost function to understand how the human brain works, taking into account the cost of each component. Simulating the human brain using genetic algorithms has been the subject of research by many researchers in recent decades.
Results: The results were excellent in terms of improving the neural network allocation and reliability, as all the network elements were taken into account and tested for their reliability well to provide better results in processing. The study was compared to several research papers that addressed reliability testing in other scientific and technological fields, and the comparison was more favorable in terms of numerical results.
Conclusion: the study's findings increased the neural network's allocation and dependability. The reliability of each network component is divided by the system optimization problem, which makes use of the most crucial location. Because it involves limitations on both human and material resources (the neural network's reliability).