Journal of University of Babylon

Background: The objective of the research is to determine the various ostracod species assemblages present in contemporary sediments of Northern Basrah Governorate. This investigation aims to clarify the characteristics of the sedimentary environments in those sediments, as well as uncover the events that have influenced their environmental conditions.
Materials and Methods:
A total of thirty one samples were collected from fourteen different locations and subjected to grain size analysis through wet sieving for the separation of sand from silt and clay the identification of sediment types. For the microfaunal taxa study, all samples were washed and dried thoroughly. Carapaces and valves of ostracod were then meticulously selected by hand under a binocular microscope. Photographic documented of the ostracod species to the identification of the ostracod assemblages present.
Results:
The analysis of the sediment composition reveals that 55% of the total samples fall within the silt category, while 26% as sandy silt and the remaining 19% are classified as belonging to the mud zone. The ostracod species were classified into distinct assemblages to define the environmental conditions, which are; Assemblage I, Assemblage II, and Assemblage III.
Conclusion:
There are three sedimentary textures: silt, sandy silt, and mud. Silt deposits are the most commonly found. In terms of identified ostracod species, Assemblage I shows characteristics typical of an estuarine environment. Assemblage II reflects a marsh environment. Assemblage Ⅲ environment varied from oligohaline/lake environment at the bottom to fluvial freshwater environment at the top.

Background:
Educational systems are increasingly leveraging analytic methods to improve student academic quality. Predicting student performance is an important area using data mining and machine learning can offers significant insights. This study emphasizes the potential of machine learning in environments by providing information for data-driven interventions aimed at improving student outcomes and supporting educational strategies.
Materials and Methods:
This initial processing phase guarantees model suitability. The second phase forward for training step using classifiers, like Logistic Regression Decision Tree Random Forest Support Vector Machine (SVM), K. Nearest Neighbors (KNN) and Naive Bayes.
Results:
The student results are obtained and tested using six classification models; Logistic Regression came on top with 99% accuracy; followed by SVM and K nearest Neighbors at 99%; Random Forest performed at 98%; Decision Tree, at 97%; and Naive Bayes, at 96%. The results of accuracy and recall scores showed that the models performed well, with logistic regression and k-nearest neighbors achieving around 100% perfect rates. The results of heat maps for the confusion matrix for the performance comparison reveal the effectiveness of ensemble and margin-based classifiers in this task.
Conclusions:
The results highlight how machine learning can help schools make decisions on student support and anticipate student needs effectively. For future work, the proposed work will consider metrics like behavior and engagement data and updating models consistently to improve accuracy for better student performance.

Background:
Numerous studies have confirmed the importance of manufacturing solar cells and photodetectors as well as different types of sensors. This is due to their essential rolls in many industries.
Working methods:
Two materials, gold (metal) and cadmium sulfate were used, which waspowder pressed at 15 megapascals pressure in a disc form with a 2 cm diameter.(PLD) technique was used to form thin films, where the number of pulses was changed and the laser power was fixed at 100 millijoules with a 1064 nanometers wavelength.
Results:
Au/CdS film exhibited a polycrystalline structure with a hexagonal lattice, The presence of gold in the CdS material resulted in very low lattice strain, as the atomic radii of CdS (0.154 nm) and Au (0.165 nm) are closely matched
Conclusions:
This study revealed The possibility of manufacturing cadmium sulfate films with Au by thermal diffusion method. The current and voltage values of the prepared solar cell increase with the increase of the layers of thin films on the surface of the solar cell, thus increasing the lighting current, as direct energy transfer occurs. X-ray examinations of the films prepared by the pulsed laser deposition method showed that they have a polycrystalline structure and a hexagonal lattice. The films prepared in the case of CdS-Au showed the size of the grains of the thin films increases with the increase of the laser energy and the number of pulses. We also note that the surface roughness decreases with the decrease of the concentration.

Background:
Fractional calculus is an area of mathematics that discusses the research and applications of non-integer calculus in ℝ or ????. I present the variable iterative method for calculating numerical approximations to solve classical differential equations that was developed to solve linear fractional differential equations.
Materials and Methods:
Were studied using the variable iterative method, where fractional derivatives according to Caputo’s derivative were used. Some examples were studied to test the accuracy of the results we obtained. This comparison was presented using the curves for these examples used to compare the absolute error of the approximate solution and the exact solution.
Results:
The results of Table (3) prove that there is acceptable agreement between the approximate and exact solution for Example (2). when n is larger, the closer the approximate solution approaching. Through the results of the three example tables, the effectiveness of numerical methods in obtain acceptable results demonstrated.
Conclusion:
When studying the examples given in the research, when using the variable iterative method and through examples and tables. I noticed the effectiveness of the variable iterative method when used, especially in the second example in the case α = 0.9

Background
Rothia dentocariosa is a part of the normal flora found in the oral cavity of many humans, which can become opportunistic pathogens in cases of oral infections, diseases, and viral infections such as coronavirus, and other causes that may lead to immunodeficiency in the host.
Material and methods
A total of 120 samples (swabs) were collected from the oral cavity of individuals suffering from gum and dental problems. Phenotypic, biochemical, and molecular tests were conducted on the collected samples to obtain the necessary results.
Results
After culturing and biochemical testing, 25 samples containing the target bacteria were identified. Following the application of PCR technique on the isolates using a specific primer for R. dentocariosa and conducting gel electrophoresis, the results showed 11 positive samples out of 25 isolates, with genetic bands at a single molecular level, and a molecular weight of (551 bp).
Conclusions
The DNA sequencing of the positive isolates was conducted, and a phylogenetic tree was constructed to determine their genetic similarity with isolates registered in the NCBI-GenBank.

Background
Rothia dentocariosa is a part of the normal flora found in the oral cavity of many humans, which can become opportunistic pathogens in cases of oral infections, diseases, and viral infections such as coronavirus, and other causes that may lead to immunodeficiency in the host.
Material and methods
A total of 120 samples (swabs) were collected from the oral cavity of individuals suffering from gum and dental problems. Phenotypic, biochemical, and molecular tests were conducted on the collected samples to obtain the necessary results.
Results
After culturing and biochemical testing, 25 samples containing the target bacteria were identified. Following the application of PCR technique on the isolates using a specific primer for R. dentocariosa and conducting gel electrophoresis, the results showed 11 positive samples out of 25 isolates, with genetic bands at a single molecular level, and a molecular weight of (551 bp).
Conclusions
The DNA sequencing of the positive isolates was conducted, and a phylogenetic tree was constructed to determine their genetic similarity with isolates registered in the NCBI-GenBank.

Due to the discovery of new resistance mechanisms and the decline in effective and high-quality treatments for common pathogenic illnesses, the increased spread of antibiotic resistance across many infectious pathogens has become an increasingly pressing global public health concern. This has resulted in microbial responses to traditional medication that have not been successful, which may increase the risk of death, extend disease, and increase health care costs.
. Multiple drugs Protein complexes called efflux pumps are found in the cell envelope and allow bacteria to expel a variety of chemicals important for infection in addition to drugs. They thus have a significant role in the pathogenesis of microbes. Efflux pumps have the ability to expel external substances, such as antibacterial chemicals produced by the host. Pathogens can withstand antibiotics and get past the host's defenses by means of this extrusion. Nevertheless, endogenous substances including metabolites, virulence factors, and signaling molecules for bacterial communication are also extruded via efflux pumps. Consequently, efflux pumps have a role in regulating bacterial pathogenicity and behavior additionally to preserving bacterial homeostasis in response to various host-derived stimuli. Thus, the purpose of this work is to inform the public about the threat posed by the global rise in multiple medication resistance and the need for prompt action to treat microbial diseases. The purpose of this review was to give a general overview of efflux pumps' use in One Health settings.

The current review analyzed bacterial urinary tract infections (UTIs) in Iraq from 2019 to 2023 by highlighting the prevalence of gram-positive and gram-negative Bacteria among UTIs. Escherichia coli was the main pathogen, with 1430 bacterial isolates from UTI cases, followed by Klebsiella pneumonia with 721 isolates, and Pseudomonas sp. with 182 isolates. The current study showed that the gram-positive bacteria, represented by Staphylococcus aureus, were the dominant pathogen in UTI cases, with 229 isolates. The distribution of these pathogens varied annually, indicating changes in infection trends. The dominance of E.coli and its multi-drug resistance were consistent with global findings, confirming its clinical importance. The study highlighted other bacterial species responsible for UTIs, which were Proteus sp., Enterobacter sp., and Enterococcus sp., confirming the complexity of the pathogenesis of UTIs. This statistical study provides critical insights into bacterial epidemiology and guides future research for the management of UTIs in Iraq.
Conclusions: The present review provides a comprehensive analysis of bacterial UTIs in Iraq from 2019 to 2023, emphasizing the prevalence and distribution of pathogens. E. coli was the most commonly causative agent, followed by K. pneumonia and Pseudomonas sp., with significant multi-drug resistance patterns noted, mirroring global trends. Gram-positive bacteria, S. aureus was predominant. Variability in pathogen distribution highlights evolving infection trends and complexities in UTI pathogenesis. The findings underscore the critical need for ongoing epidemiological surveillance and antibiotic stewardship to manage UTIs effectively and mitigate resistance. This data is pivotal for improving healthcare strategies and patient outcomes in Iraq.

Background: Type 1 diabetes mellitus, also known as insulin-dependent diabetes, characterized by elevated levels of blood glucose (hyperglycemia), which produced by the autoimmune destruction of pancreatic islet β-cells insulin-producing.
Objective: This study aimed to examine the alterations in Apelin, Lipid profiles, fasting blood glucose, HbA1C, calcium, parathyroid hormone and vitamin D in adolescents with type 1 diabetic and healthy adolescents.
Methods: This study was done in the Maternity and Children Teaching Hospital and Al-Ramadi Teaching Hospital in Ramadi city in Iraq, between January 2024 to July 2024. One hundred adolescents were selected: 60 patients with diabetes and 40 healthy as a control group. Biochemical tests for blood samples were performed.
Results: The results showed there was a significantly increase in concentrations of Apelin, lipid profile (except high-density lipoprotein cholesterol), fasting blood glucose, HbA1C and calcium in patients with diabetes than control group. Whereas, there was a significantly reduction in concentration of the high-density lipoprotein cholesterol, parathyroid hormone and vitamin D in patients with diabetes than control group. The results showed a significant positive correlation among glucose concentrations and Apelin concentrations, while there was a significant inverse relationship between blood parathyroid hormone and blood glucose concentrations, and also, there was a significant inverse relationship between vitamin D concentration and HbA1c.
Conclusion: The high serum concentrations of Apelin in diabetic patients supports the function of Apelin in diabetes mellitus development and highlight the utilize of Apelin as a medical sign in diabetes.

The gut microbiome is a plentiful and a diversity of microbes community that live in the gut and play a critical role in the host’s physiology, such as food metabolism, digestion, immunity, brain development, and behaviour. Their diversity is very important to the body; however it is always changed by the environmental factors. Any change in the variation and composition of the microbiome can have consequent impacts on the host’s health. The interaction between gut microbiota, external factors, host physiology, development, and infectious diseases is really complicated. For example, food can modulate the gut microbiota at the same time the food is the main source of microbial metabolites that play an essential role in modulating immunity, and the regulation of immunity by the microbiome influences brain development and vice versa. In conclusion, the understanding of various pathways in which gut microbiome could affect and affected by digestion and immunity offers new approaches to treat various immune and infectious diseases. Therefore, this review sheds the light on various interaction mechanisms between gut microbiome, food digestion, and immunity.

The gut microbiome is a plentiful and a diversity of microbes community that live in the gut and play a critical role in the host’s physiology, such as food metabolism, digestion, immunity, brain development, and behaviour. Their diversity is very important to the body; however it is always changed by the environmental factors. Any change in the variation and composition of the microbiome can have consequent impacts on the host’s health. The interaction between gut microbiota, external factors, host physiology, development, and infectious diseases is really complicated. For example, food can modulate the gut microbiota at the same time the food is the main source of microbial metabolites that play an essential role in modulating immunity, and the regulation of immunity by the microbiome influences brain development and vice versa. In conclusion, the understanding of various pathways in which gut microbiome could affect and affected by digestion and immunity offers new approaches to treat various immune and infectious diseases. Therefore, this review sheds the light on various interaction mechanisms between gut microbiome, food digestion, and immunity.

It is known that Lagrange interpolation polynomial is considered as one of important tools to approximate the chosen function by a polynomial of degree n with knowing points that belong in it. Also, amount of error between the original function and this polynomial is known in books of approximation and numerical analysis. But studying the effects and amount of error of this polynomial in convex and compact regions has not been studied before. In this article, we will study in some detail the behavior of the Lagrange interpolation polynomial in such regions in terms of the form and its characteristics and the extent of the difference between this polynomial and the function in question. We will notice that this polynomial will be turned into a convex function when applied to a function in a convex region, and the degree of error or the amount of difference between it and the original function gets smaller if we apply our polynomial on the desired function in a convex region. The same is true if the effect of this polynomial is applied on a function in a compact region, and notice that the amount of difference between it and this function is reduced to zero if n goes to infinity.

Background
In this paper, the ensemble average and deep neural networks approach is proposed for detecting rice leaf diseases. The system consists of two different deep neural networks represented by GoogLeNet and MobileNetV2 where trained separately by dataset of rice leaves images.
Materials and Methods
These images represent various conditions of the leaves, including healthy leaves, and five types of diseases. The dataset is preprocessed by resizing and normalizing to standardize the inputs for the networks. Then it is split into training and testing sets to ensure robust model evaluation. After training of these two networks, the ensemble average module combines the predictions from both networks by averaging them during the testing phase.
Results
The proposed model was compared with the other two models based on the performance metrics accuracy, precision, recall, and F1-score, and the proposed model highlights the superiority of the proposed approach in detecting rice leaf diseases. The proposed model achieved the highest accuracy at 97.07%, precision at 97.1%, recall at 97.06%, and F1-score at 97.08% which outperformed the other two models across all metrics because the averaging process reduces variance and enhances the accuracy of the final decision of detection the rice leaf diseases
Conclusion
This ensemble-based approach illustrates superior performance for rice leaf diseases detection, offering a more reliable and precise tool for managing the agricultural diseases.

Background:
Phishing attacks have become a serious threat to enterprise security, exploiting our human vulnerabilities to gain access to sensitive information. Especially in critical sectors such as finance, healthcare, and technology. The primary objective of this study is to delve deeply into the financial, operational, and reputational consequences of these malicious attacks. It will also measure the effectiveness of various strategies aimed at thwarting them.
Methods:
The scientific and practical approach of this research is to conduct a series of multiple trips on different routes to collect information from employees and officials. It's analyzed using advanced machine learning algorithms(SVM), which carefully dissect the data to reveal rich insights. These results highlight the effectiveness of large number of anti-phishing strategies, providing clearer picture how to protect against deceptive threats.
Results:
Employees trained in security awareness have seen significant 30% reduction in their exposure to attacks. Meanwhile, AI models that leverage powerful natural language processing techniques, including BERT and GPT-3, have been shown achieve 90% accuracy in detecting phishing scams. Even more impressive, AI-based systems designed to combat this type of threat have an astonishing 85% accuracy.
Conclusions:
Combining security awareness initiatives with AI technologies and psychological insights can reduce phishing threats. Research confirms that ongoing training with AI-powered detection systems improves detection accuracy and enhances overall security. This holistic philosophy is critical for organizations to reduce their exposure to phishing attacks and enhance their resilience to cyber threats.

Microbiome is an enormous abundance and diversity of microbial community that lives symbiotically in and on the human body. They offer important and beneficial functions for the human health. Most of microbiome lives in the in gut and participate in the regulation of body physiology. Recently the importance role of the microbiome in the regulation many physiological aspect has more attractive. Moreover, it was found that the absence of gut microbes caused immune and metabolic alteration in the experimental animal, as well as developing number of infectious diseases due to disturbance of microbial community composition. Interestingly there is an evidence that commensal microbiome can influences the brain development, cognition and behaviour via gut-brain axis. Furthermore, it was observed that changing in the behaviour can lead to the alteration in the composition of intestinal microbial community and vice versa the alteration in the commensal gut microbiota composition can cause depression like behaviour. The gut microbiota’s function in brain development will be covered in the review. The understanding of interaction mechanisms between gut microbiota and brain development offer new approach to treat various mental diseases. The conclusions, there is a requirement for applying microbiome analysis on broad human community along life-course with more respect to individual differences between people, and for further development of analytical approaches

Microbiome is an enormous abundance and diversity of microbial community that lives symbiotically in and on the human body. They offer important and beneficial functions for the human health. Most of microbiome lives in the in gut and participate in the regulation of body physiology. Recently the importance role of the microbiome in the regulation many physiological aspect has more attractive. Moreover, it was found that the absence of gut microbes caused immune and metabolic alteration in the experimental animal, as well as developing number of infectious diseases due to disturbance of microbial community composition. Interestingly there is an evidence that commensal microbiome can influences the brain development, cognition and behaviour via gut-brain axis. Furthermore, it was observed that changing in the behaviour can lead to the alteration in the composition of intestinal microbial community and vice versa the alteration in the commensal gut microbiota composition can cause depression like behaviour. The gut microbiota’s function in brain development will be covered in the review. The understanding of interaction mechanisms between gut microbiota and brain development offer new approach to treat various mental diseases. The conclusions, there is a requirement for applying microbiome analysis on broad human community along life-course with more respect to individual differences between people, and for further development of analytical approaches

The gut microbiome is a plentiful and a diversity of microbes community that live in the gut and play a critical role in the host’s physiology, such as food metabolism, digestion, immunity, brain development, and behaviour. Their diversity is very important to the body; however it is always changed by the environmental factors. Any change in the variation and composition of the microbiome can have consequent impacts on the host’s health. The interaction between gut microbiota, external factors, host physiology, development, and infectious diseases is really complicated. For example, food can modulate the gut microbiota at the same time the food is the main source of microbial metabolites that play an essential role in modulating immunity, and the regulation of immunity by the microbiome influences brain development and vice versa. In conclusion, the understanding of various pathways in which gut microbiome could affect and affected by digestion and immunity offers new approaches to treat various immune and infectious diseases. Therefore, this review sheds the light on various interaction mechanisms between gut microbiome, food digestion, and immunity.

Background: Objective: This research aims to measure the extent of the impact of commercial credit risks in its dimensions (risk assessment, risk management policy) on joint stock companies in its dimensions (commercial credit, credit policy objectives, strategic planning dimensions, interest in innovation, administrative leadership).
Methods: The research relies on the questionnaire as a research tool, as the research community consisted of a number of banks and investment companies in the provinces of Babylon and Karbala, numbering (4).
Conclusions: The results showed a relationship between the impact of commercial credit risks on joint stock companies. In light of these results, the research presented several recommendations, which are:
Establishing an independent unit dedicated to risk management, providing the necessary resources to facilitate this, developing a strategic plan and structural models such as early warning of risks, as well as expanding the training of program specialists and ongoing courses.

The emergence multidrug tolerance is the most threatening obstacle for the population health. During the last years, transporting pumps are implicated in the emergence of antibiotic resistance. More trans-membrane proteins have been observed in prokaryotes, archae-bacteria, fungi, and eukaryotic cells, involved in transferring various types of toxic substances out of cells. The upgrowth of resistance to various antibiotics is attributed to the spread of genes encoding different efflux pump proteins through horizontal transfer mechanisms. Antibacterial tolerance is obtained as a result of the encoding of efflux pump proteins, which increases the efficiency of pumps in eliminating the toxic substance by altering the types of amino acid involved in the efflux pump structure. There are five families belonged to efflux pumps protein. The transport proteins found in the cytoplasmic membrane have been involved in the evolution and spread the phenotype of antibiotic tolerance among bacterial strains. So, Perception the physiological function of MDR transport pumps still requires more research due to the sustained capacity of bacterial cells to manipulate and degrade antibiotics.

Background
The results showed that Grey Doppler and Color Doppler produce very different images and cannot diagnose the same things. Color Doppler ultrasound captures changes in blood flow more clearly and accurately than grayscale imaging, enabling doctors to diagnose artery problems more accurately. Both types of medical imaging showed the anatomy, blood flow patterns in the cyst, and arterial dilatation correctly.
Materials and Method
The Doppler examination is performed in the same way as a regular ultrasound, where after applying the gel to the area with a deep pen diluted on the area, the ultrasound examiner moves it or moves it until the doctor detects the signal well. It should start to move less noticeably, and then sounds that represent blood flow in the blood vessels are heard.
Results
The study found that Grey Doppler and Colour Doppler performed differently in problem diagnosis and photo quality. Colour Doppler ultrasonography displayed blood flow dynamics more accurately and precisely than greyscale imaging, enabling more accurate vascular abnormality detection. In medical imaging, both modalities precisely reconstruct anatomical features, cyst blood flow patterns, and artery dilations. Color Doppler ultrasound's clarity and detail in monitoring blood flow distribution in vessels improved the diagnosis's accuracy.
Conclusions
Using physical technology to enhance the accuracy and understanding of medical images, Doppler ultrasound has been investigated in advanced clinical settings such as diagnosing cardiovascular disorders and has been found to be highly accurate in diagnosis.

Background
The results showed that Grey Doppler and Color Doppler produce very different images and cannot diagnose the same things. Color Doppler ultrasound captures changes in blood flow more clearly and accurately than grayscale imaging, enabling doctors to diagnose artery problems more accurately. Both types of medical imaging showed the anatomy, blood flow patterns in the cyst, and arterial dilatation correctly.
Materials and Method
The Doppler examination is performed in the same way as a regular ultrasound, where after applying the gel to the area with a deep pen diluted on the area, the ultrasound examiner moves it or moves it until the doctor detects the signal well. It should start to move less noticeably, and then sounds that represent blood flow in the blood vessels are heard.
Results
The study found that Grey Doppler and Colour Doppler performed differently in problem diagnosis and photo quality. Colour Doppler ultrasonography displayed blood flow dynamics more accurately and precisely than greyscale imaging, enabling more accurate vascular abnormality detection. In medical imaging, both modalities precisely reconstruct anatomical features, cyst blood flow patterns, and artery dilations. Color Doppler ultrasound's clarity and detail in monitoring blood flow distribution in vessels improved the diagnosis's accuracy.
Conclusions
Using physical technology to enhance the accuracy and understanding of medical images, Doppler ultrasound has been investigated in advanced clinical settings such as diagnosing cardiovascular disorders and has been found to be highly accurate in diagnosis.

Background: Cigarette smoking is a risk factor for many respiratory diseases. There are different instruments used to assess the effects of smoking. The purpose of our study was to assess the levels of peak expiratory flow rate (PEFR) between different types of smoking.
Methods: This is a cross-sectional study involved 190 subjects aged from 10-40 years, the sample was taken from multiple cafes in different areas in Hilla city, Iraq. The study involved smokers and passive smokers. The work was performed by taking information from each subject that included questions about age, sex, type of smoking, duration of smoking and symptoms. In addition to that the study included measurement of pulmonary function by using peak flow meter.
Results: Most of participants were passive smokers (60.53%). Regarding distribution of symptoms, the study showed that the highest percentage of them had no symptoms (67.4%) and only 1% of them had wheeze. The highest numbers of participants with low levels of PEFR were in the age group 20-29 years old and the differences were significant between groups (p value= 0.037), The study also revealed significant relation between increased duration of smoking and the decrease in the level of PEFR (p value=0.000)
Conclusion: The results showed considerable effect of smoking whether active or passive on the values of PEFR. In addition, there were increased respiratory symptoms among smokers.

Background:
Growing antibiotic resistance is one of the major worldwide issues endangering human health. As a result, many approaches to lowering pathogens are being studied. G. lucidum's impact on some pathogenic species is the focus of the current investigation.
Materials and Methods:
In our study the effect of G. lucidum powder fungi compared with antibiotics. we prepared G. lucidum in three different concentrations (80, 100, and 200 mg/ml). The sensitivity of pathogenic fungi and positive and negative bacteria species to Gram stain was tested, and the results were compared to the antibiotic sensitivity of the same species used in the study.
Result:
The study showed that S. aureus bacteria were sensitive to all the used types of antibiotics, whereas E. coli were resistant to most of them; the remaining species had varied sensitivities.
While S. aureus showed greater sensitivity to an increasing concentration of the utilized powder, E. Coli, Bacillus, and Klebsiella bacteria all demonstrated resistance to the effects of the powder. The P. aeruginosa bacteria and the fungal species employed in the investigation exhibited no discernible sensitivity to the powder utilized.
Conclusion:
In contrast to the bacteria and fungi being studied, S. aureus had a higher sensitivity to increasing powder concentration.

Background: Even while traditional Raft is effective at leader election and log replication, it is not appropriate for sensitive applications like supply chains, financial systems, or healthcare because it lacks built-in privacy safeguards.
Materials and Methods: A privacy-preserving Raft consensus method is proposed to solve the privacy issues that occur when private information is transferred between nodes in a distributed system such as a blockchain. Raft itself, by default, does not provide any steps toward ensuring data confidentiality during consensus. By employing privacy-preserving cryptographic techniques like homomorphic encryption and zero-knowledge proofs, nodes can reach consensus while keeping sensitive data private.
Results: Traditional Raft performs much better in scenarios where performance matters, while Privacy-Perving Raft works better in a sensitive application to privacy (the average of write throughput is 5% lower than that of traditional Raft) and CPU is 40-60%.
Conclusion: Based on the gained privacy by some computational costs, it will be valid to draw the conclusion that this works for privacy-sensitive applications within decentralized systems with these performance and security analyses.

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is possible for SARS-CoV-2 to produce multiorgan failure (MOF), which can be fatal. The purpose of this review is to assess the amounts of certain minerals (zinc, iron, and selenium) then vitamins (C, A, D, and E) in coronavirus-infected persons. Every study we looked at showed deficiencies in the aforementioned vitamins and minerals. We come to the conclusion that the immune depends heavily on micronutrients, and that the immune system is significantly impacted by their inadequacies. It has been proposed that increasing antioxidant intake can improve immunity, even though the majority of antioxidants are thought to be found in food. Despite the immune system's continuous activity, the presence of pathogens increases the activation of specialized immunity. The expression of genes in immune cells is regulated by the metabolites of vitamins A, D, and other nutrients. The imaginable healing welfares of vitamins C, A, D, and E through immunomodulation in COVID-19 patients are assessed and investigated in this study. We discovered that zinc, iron, and selenium—essential micronutrient minerals—have antioxidant and antiviral qualities that strengthen the body's defenses via a variety of mechanisms and immunomodulatory pathways.