Journal of University of Babylon

Investigate on kidney poison has been commended by new molecular ways, with an distinction on IMR and genetic susceptibility. The story accentuates custom-made treatment tactics and housings into the complexities of Glomerulonephritis and Interstitial Nephritis therapies in order to augment results for patients suffering from these kidney diseases. From theory to action: a synthesis of insights in glomerulonephritis and interstitial nephritis This abstract assortments thoughts from several sources to offer a complex lookout that both contests and reinforces present thinking. It offers healthcare practitioners a full toolkit for treating glomerulonephritis and interstitial nephritis by combining academic acquaintance with real-world applications.A more accurate system has been unconventional to identify interstitial nephritis and glomerulonephritis. Guided Therapeutic Terrain: Administration Tactics for Glomerulonephritis and Interstitial Nephritis. This demonstration confers many systems to so long as successful patient care, including pharmacological treatment and lifestyle changes. It provides health care physicians with a comprehensive toolset for treating glomerulonephritis and interstitial nephritis by integrating academic knowledge and practical implementations. The paper includes a comprehensive examination of advanced diagnostic procedures as well as current approaches for diagnosing glomerulonephritis and interstitial nephropathy. Through the integration of molecular biomarkers, modern tomography technologies, and modified medicine, the debate aims to give new approaches for quick and accurate diagnosis.

Background:
Dermatophytes are keratophilic fungi that consider exogenous organisms, and cause serious infections of the skin, hair, and nails. The main goal of the current study is to present a survey of fungal skin infections in Musayyib general hospital of Babylon Province Iraq, through the identification of the incidence of some types of Tineae and the extent of spread in different age groups.
Materials and Methods
A256 patients clinically suspected of dermatophytosis, 210 were positive in direct examination and/or culture. From the positive patients' sample that includes skin scrapping, hair fragments, and nails
Results
The current study showed that Dermatomycosis infected in males more than females with a ratio of 151 (71.90 %) males and 59 (28.09%) females. The highest percentage of infection with Tinea capitis appeared in males , while the lowest percentage of infection with Tinea ungums with a rate equal between males and females. According to age groups.
Conclusions
According to the findings of the study, it absolves that although Covid 19 pandemic the world went through fundamental changes by increasing the level of understanding and awareness of people to use different sterilizers and detergents. In addition to reducing contact between people and taking care of personal hygiene. Unfortunately, these procedures did not have a positive effect on reducing dermatophytosis infection in Musayyib General Hospital.

Background:
In this study, we utilize the IBM-1 model to theoretically investigate the structural characteristics of (_42^94)Mo , with a specific emphasis on a nucleus consisting of 5 bosons. Employing the IBM-1, an innovative interacting boson model, we analyze the nuclear structure.
Materials and Methods:
In our theoretical exploration, we delved into the nuclear architecture of Molybdenum. Employing the Interacting Boson Model (IBM-1), we identified the pertinent Hamiltonian to scrutinize the(_42^94)Mo isotope in this research endeavor.
Results:
Our investigation delved into the (〖E4〗_1^+)/(〖E2〗_1^+ ) symmetry limit of the proposed nucleus, unveiling its stable nature within the SU(5) dynamical symmetry domain. To optimize alignment with observed energy states in experiments, we meticulously determined the parameters in the IBM-1 Hamiltonian equation. Furthermore, our research extends to the computation of B(E2) transitions, quadrupole moments, and energy levels across all bands for the examined nucleus.
Conclusions:
Our investigation reveals the stability of the nucleus in the (_42^94)Mo isotope, showcasing the presence of SU(5) dynamical symmetry. These findings offer fresh perspectives by suggesting additional electric quadrupole moments.

It is a complex task to find out a specific reason of breast cancer which are based on multiple factors. Nevertheless, hormones, especially estrogens, are the ones that are mostly responsible for hampering unrestricted division of cancerous cells in the mammary gland. Fully knowing their role is pivotal for matching preventive and therapeutic plans. Chromosomal anomalies are abundant in this inborn module but they are next to BRCA1 and BRCA2, the errors that increase the risk. The diagnostic technologies which include HER2/neu testing and gene expression profiling are made to personalize the therapy practice with the intention to enhance the outcomes. The amalgam of environmental, hormonal, and genetic influences results in the creation of an individuality. The effectiveness of rehabilitation can be drastically boosted through the early identification of a disease process. A mammogram, the top screening tool for breast cancer built-in, can spot a cancer even before it shows any symptoms. In the matter of particles the breast cancer treatment has been changed greatly. Distressed tablets like trastuzumab and aromatase inhibitors in the event when accompanied by traditional chemotherapy, which in return produce efficacy with lesser side effects. Preventative policies encompass the realization of lifestyle changes as well as medical intervention. Maintaining a healthy weight, doing some extra movements, and limiting alcohol intake are all good examples of what you can do to reduce your chances of complications. Successful chemoprevention among high-risk subjects, via drugs like raloxifene and tamoxifene, has been founded. Immunotherapy is a novel approach of curing cancer by triggering immune response of the body.A review of its mechanism of operation, and preventive measures. The precision of staging is improved because of other supplementary information that is available in additional techniques like MRI and ultrasound. Such individuals can be candidates for preventive procedures such as oophorectomy or mastectomy.

The domain of facial detection has witnessed significant advancement, mostly attributed to the progress in machine learning and deep learning methodologies. These enhancements have resulted in a fundamental change in the field. Face detection algorithms are extensively utilized in several domains, such as security, surveillance, and social networking applications. This survey has thoroughly investigated various methodologies for facial identification, with a focus on the challenges, applications, and evolution from traditional to deep learning-based approaches. Furthermore, it provides important insights into commonly used datasets for facial detection, including a comprehensive examination of their unique characteristics. The study is structured sequentially, commencing with an introduction to the assessment of significant previous research and the challenges faced by face detection algorithms. Subsequently, the investigation delves into different practical uses, delineates methods for identifying, and scrutinizes frequently employed data sets. The transition from traditional classifiers to deep learning models in face identification technology represents a significant improvement in addressing the complexities of face detection in various environments. Despite the obstacles that now exist, the continuous advancements in deep learning offer promising solutions that enhance the accuracy and efficiency of face identification systems in a wide range of applications.

Background:
The Alu element is a widely distributed short interspersed nuclear element (SINE) in the human genome and has important applications in forensic science. The current study focused on assessing the effectiveness of Alu insertion polymorphism in forensic DNA profiling to identifying samples of some individuals living in the Babylon Governorate.

Materials and methods:
DNA was extracted From frozen blood samples (60) individuals were collected from Babylon - Al-Hilla Governorate from 8/8/2022 until 8/9/2022.

Results:
purified then a PCR technique Alu insertions were A(2q21.1)(111-115bp) 0.75, Alu deletion (0.25), B(8q23.1) (0.375) (0.625) C(13q34) (0.5)(0.5), D(15q23) (0.775) (0.225), E(16q23.3) (0.692) (0.308) and F(19q13.12)(0.616)(0.384) respectively.The alleles with Alu insertions at (2q21.1) were the most prevalent, whereas the Alu insertions at (8q23.1) were the least common. The similarity coefficient among individuals varied from 0.4 to 1, based on the proportion of genetic relatedness between them.

Conclusions:
Alu elements have efficacy in families’ discrimination it can be used more than one site, set of Alu insertion sequences should be used to accurate results.

Background:
Automatic keyphrase extraction (AKE) is essential to many NLP and information retrieval tasks. Extracting high-quality key phrases is difficult due to technological advancements and the exponential growth ‎of ‎textual data and digital sources. Unsupervised keyphrase extraction with cheap computing cost that relies ‎on ‎heuristic notions of phrase importance such as embedding similarities but their development necessitates in-depth subject expertise.
Materials and Methods:
This paper presents a method to obtain a semantic understanding of the query ‎and index documents by using ‎the embedding technique(universal Sentence ‎encoder (USE) ) while keeping the most informative ‎using Maximal Marginal Relevance (MMR) and then scoring(an ‎inverted index) the most documents relevant to the query ‎vector to improve the ‎performance of IR systems.‎
Results:
The proposed retrieval model implement on the (Fire2011) dataset. The final ‎stage was evaluating the results of the baseline and the results (indexing and ranking) by using mean average precision (MAP). The ‎result of the baseline was 0.61, while the result ‎inverted index was 0.6277519 .‎
Conclusions:
In this paper, we have discussed document retrieval using keep key phrases that ‎have ‏informativeness ‎properties by ‎using maximal ‎marginal ‎relevance, since if we extract a fixed number of top ‎keyphrases, ‎redundancy ‎hinders the diversification of the ‎extracted keyphrases.

Background:
The (IDEA), which represents International Data Encryption Algorithm is a widely used cipher algorithm that has raised concerns due to the discovery of numerous weak keys, as highlighted in previous research. These weak keys, specifically those containing consecutive sequences of single digits, have been found to impede the algorithm's evolution and result in a sluggish avalanche effect. To address these vulnerabilities, this research aims to develop an enhanced and secure encryption algorithm by incorporating Chaos Theory principles into IDEA.
Materials and methods:
The primary objective is to address the weaknesses associated with IDEA's key generation process by leveraging Chaos Theory to generate strong, highly random keys that replace the algorithm's weak keys t. The study also aims to assess the security and cryptographic strength of the enhanced IDEA algorithm through evaluations and comparisons with the original algorithm.
Results:
The results showed that the proposed key passed 11 tests out of the 15 total tests, while the Traditional key of IDEA passed only 7. This indicates that the proposed method is superior by 4 tests over the Traditional method of generating keys. Also, cipher text 1 with the proposed key passed 10 tests out of the 15 total tests, while with the Traditional key passed only 8 .
Conclusion:
This indicates the superiority of the proposed method of IDEA in encryption over the traditional method of IDEA.

Background: In recent years, one of the most pervasive issues regarding global public health is bacterial foodborne diseases
Materials and Methods: A total of 164 different food samples were collected from September 2023 to November 2023 from a range of supermarkets and farmers throughout different locations in Babylon City. Milk products77 (52.70% ), meat products19(13%), seeds32(21.90%)and , canned 18(12.32%) . then culture in blood agar, chromogenic agar and not growth on macConkey agar, The virulence gene was amplified via the polymerase chain reaction (PCR).
Results: The prevalence of Bacillus spp. , according to the cultured, biochemical, and molecular identification was 17(10.3%). The result of sequencing found the Bacillus spp. Isolates belong to the flowing species B.subtilis (2), B.cereus (6), B.thuringiensis(1), B.anthracis (1), B.spizizenii (1) and, Bacillus spp. (6). The result of molecular detection of virulence gene present hblA, nheA, and entFM in prevalence 4(23.5),11(64.7) , and 14(82.3) respectively
Conclusion: The isolates of Bacillus spp. exhibited a variety of virulence factors correlated with symptoms of diarrhea. As a result, it is imperative to tightly enforce sanitary practices and pay more attention while processing food, adding chemicals only from reliable sources.

The health information data includes reports on the patient’s condition, including addresses, names, tests, treatments, diagnoses, and medical history. It is sensitive information for patients, and all means of protection must be provided to prevent third parties from manipulation or fraudulent use. The goal of this paper presents studies of safeguard the transfer of sensitive data over an unsecured network using DNA techniques to enhance security. A comparison analysis is used to show the security issues of the various DNA-based data (ciphering, concealing, and compression) techniques that are studied and investigated. Also, in our study is to provide future researchers with the necessary knowledge to conduct data security research to develop or improve DNA-based data- ciphering, compression-hiding strategies that are more reliable, secure, and efficient. Thus, future researchers need to propose a trustworthy DNA-based data (ciphering, hiding, and compression) techniques. The result of our study appears the perceived vulnerability of medical data and health insurance to concerns of security as well as common security issues, also the nature of these common security concerns, for reducing medical data security risks

Background:
A steganography investigation model that uses improved dim scale List of capabilities, for identifying information inside uncompressed RGB pictures.
Materials and Methods:
in this paper, a bunch of 2000 RGB pictures was made utilizing normal tones, in BMP design with a size of 512 x 512 pixels. Clean pictures are Inserted secret picture information, utilizing two Payload plans, 2 pieces for every channel (BPC) and 4 pieces for each channel. The arrangement of chosen highlights comprises of 24 elements for every variety channel, and 72 highlights for each variety channel The picture, incorporates dim-level co-event grid highlights, entropy Elements, and factual proportions of variety. The list of capabilities components is determined as Individual channels, joined into picture vector highlights. The cycle depends on steganography examination On AI, utilizing Paired vector machine (SVM) support Execute the exercise manual in MATLAB.
Results:
The outcomes showed that the new method had overcome the benchmark with more than 80% identification accuracy
Conclusion :
a new Steganalysis model was introduced by using SVM. The model can recognize the presence of stowed-away information inside RGB variety pictures, removing the highlights from datasets of perfect and messy pictures and ordering utilizing the support Vector Machine calculation. the results were compared with the DNA algorithm.

Background:
This research aims to investigate certain requirements for the presence of eigenvalues, as well as the boundaries of eigenfunctions and their derivatives, specifically, the eigenfunctions' first as well as second derivatives.
Materials and Methods:
In this study, we use the spectral problem of second-order differential equations:
L[f]=-f^'' (x)+f^' (x)+p(x)f(x)=λr(x)f(x),x∈[0,α],
with mixed boundary conditions
f^' (α)-i λf(α)=f^' (0)-f(0)=0, where λ is a spectral parameter.
and the normalized condition ∫_0^α▒〖r(x) |f(x)|^2 dx=1〗, where r(x)>0.
Results:
We get that the spectral parameter of a second-order differential operator is real. And we obtain Lagrange’s identity for a spectral problem. Also, we prove that the spectral problem is self-adjoint, and the property of orthogonality of eigenfunctions is shown.
Conclusions:
In this research, we studied the existence of eigenvalues and the estimation of the norm of eigenfunctions for problem (1) - (3). Furthermore, we investigated the self-adjoint nature of the problem, and we proved that the eigenfunctions are orthogonal.

Background: Nurses have effect on patient education on a heart disease. The educational role of nurses helps to improve their health. The study's goals are to determine the roles of nurses in health education.
Materials and Methods:This study was conducted at selected hospitals in Erbil, from June 20, 2021, to January 20, 2022. A sample of 123 nurses was interviewed, with the questionnaire consisting of three parts: socio-demographic, educational roles for patients, and learning practices for patient adaptation. The study aimed to identify the health education and practical roles among nurses. The reliability of the questions was 0.926, indicating acceptable reliability.
Results: The majority of participants were aged between 32 and 42. Female nurses comprised 55.3%, with 57.3% holding diploma. Nurses' educational role in patient care, with 65% performing well. 59.3% taught patients’ healthy habits, and 65% effectively educated patients about self-care. The study reveals a significant relationship between nurses' socio-demographic factors, their overall educational role, and nurses' overall learning role. The good educational role was significantly associated with the hospitals they worked in and their units (P <0.001). Nurses also demonstrated good learning roles in their qualifications. However, the learning role was not significant with the other socio-demographic.
Conclusion: Most nurses play an important role as an educator while patients are in the hospital and after they leave. There was a strong relationship between their roles, their qualifications, and the units in which they worked.

Background: Several reviews have shown a pro-inflammatory role of Interleukin-17 (IL-17) level and have an association to numerous inflammatory illnesses, like rheumatoid arthritis, allograft rejection, systemic lupus erythematosus, and asthma. The T helper-17 (Th-17) cellular fraction of CD4+ T-cells that have been involved as the principal pathogenic cells in a variety of illnesses that has an autoimmune base, produce the cytokine interleukin-17A (IL-17A).
Asthma is a chronic inflammatory disease associated with recurrent airways obstruction that is relieved either spontaneously or with medications. Both innate and adaptive immunogenic cells in asthma collaborate with respiratory epithelium to generate "bronchial hyper-reactivity (BHR)". To determine the role of IL-17 in asthmatic patients and the relationship between IL-17 and asthma severity.
Materials and methods : The participants in the study ranged in age from 20 to 50 years old. These individuals were divided into two groups: 50 patients with asthma and 50 people who appeared to be healthy. serum IL-17 was measured in all study participants.
Results: IL-17 revealed a significant (p-0.001) rise in the values of IL-17 among asthmatic cases (mean = 176.6) compared to healthy controls (mean=22.55). The difference in IL-17 levels between severe and mild asthma was also significant, with a p-value of 0.005.
Conclusion: This study suggests that there was a significant difference in the concentrations of IL-17 between asthmatics and healthy control (p-0.001). In severe asthma, IL-17 levels are significantly (p-0.005) higher than in mild/moderate asthma.

Background:
A planar graph (PG) is a graph with no intersecting edges. Particular to both crisp and neutrosophic graphs (NG) is the planar graph, in contrast to crisp planar graphs. NPGs allow for the intersection of neutrosophic edge NEs, since the value of planarity in these graphs is the degree of planarity of the intersected NEs. The NPGs are often represented on a flat surface.
Materials and Methods:
This study discusses how to embed NGs on surfaces such as spheres and m-toruses by defining the degree of intersection of the neutrosophic edges of NGs with finding the faces on the given graph structures using Euler's theorems. Here, the proofs of Euler's theorems help us find, given the total NFV of G, the interval containing that value.
Result:
As result of this work obtained that for any two isomorphic planer graphs, they have the same planarity value. For any neutrosophic planer graph with f = (1,1,1) can be embedded in the plane if it can be embedded in the sphere and according to NPGs, for planar and spherical surfaces, equivalent theorems to Euler's formula are proved and shown.
Conclusion:
It concludes that by using neutrosophic sets and crisp graphs to construct neutrosophic graphs with the benefit of Euler’s theorem, it can provide the concept of embedding neutrosophic graphs in different topological surfaces such as a plane, sphere, and m-torus.

Background:
Cybersecurity is a prominent concern in today's interconnected world, encompassing both local and remote wireless and wired access across diverse communication technology platforms. It is important to recognize the threat posed by hackers who are currently compromising organizational functionalities, bypassing security measures, and stealing hypersensitive information. Common hacking techniques such as Portscan, Distributed Denial of Service (DDoS) attacks, and the use of Botnets, are frequently utilized by hackers.
Materials and Methods:
The authors explore the advantages of using Machine Learning (ML) to classify attacks such as Port Scanning, DDoS, Botnet, and Botnet-Attempt in a mixture of both benign and attack traffic. They use various Artificial Neural Networks (ANN) structures, each having distinct properties, to train and test on a benchmark dataset (CICIDS2017). The aim is to identify the most effective ANN model and the optimal number of input features required to classify data that contains events of Portscan, DDoS, Botnet, and Botnet-Attempt attacks.
Results:
Various features are used as inputs for an ML model with single and multiple hidden layers, each with different neurons, to evaluate their impact on classification accuracy using a Python language. The best accuracy obtained is 99.71%, achieved by using all features of the dataset and 4 hidden layers, while the accuracy obtained using only 7 features is 97.6%.
Conclusion:
ANN models can perform well in classifying network traffic against adversarial attacks by using an optimal combination of features as input and hidden layers.

Background:
Bacterial infections are often associated with respiratory infections, commonly complicating conditions like pneumonia, bronchitis, and sinusitis. Understanding this link is crucial for effective diagnosis and treatment in managing respiratory health.
Materials and Methods:
Researcher cultivate bacteria from patients with respiratory diseases in a specialized nutritional medium. This process allows for the identification and characterization of pathogenic microorganisms and their interactions within the respiratory tract. By studying these cultivated samples, scientists can gain valuable insights into the nature of respiratory infections, including the types of bacteria presents, their behaviors, and how they interact with the respiratory system. This method plays a crucial role in understanding the microbiology of respiratory diseases, facilitating the development of targeted treatments and interventions to combat these conditions.
Results:
The results of our study revealed a significant correlation between the variables under investigation, supporting our hypothesis. Statistical analysis demonstrated a clear pattern of outcomes, with notable trends and variations observed in the collected data.
Conclusion:
In conclusion, our study underscores the importance of addressing bacterial infections as a critical aspect of managing respiratory illnesses. These findings contribute to a broader understanding of respiratory health and may inform strategies for more effective prevention and management of bacterial complications in respiratory infections.

With the rapid advancement of Internet technology in recent years, online financial transactions have become increasingly popular for purchasing a wide range of goods and services over the Internet, owing to their numerous advantages. The widespread adoption of credit cards has thus heightened the potential for abuse. Present a significant menace to users as a result of pervasive fraudulent operations. Credit card fraud has become an essential concern in today's digital era, posing substantial financial losses and security risks for financial institutions and consumers. In response to this growing challenge, researchers and industry experts have continuously developed and refined fraud detection techniques to safeguard against fraudulent activities. This survey paper aims to provide a comprehensive overview of the latest advances in fraud detection techniques for credit card transactions. Explore various methodologies, data sources, and machine learning algorithms used in fraud detection systems. Additionally, they discuss the challenges these systems face.

Background:
The concept has been studied fuzzy- Socle-Jacobson–Two-Absorbiang submodules and some fuzzy relationships According to the concept above. Where the new definition was named fuzzy Socle-Jacobson–Two-Absorbiang, we used a few algebraic techniques to determine the rapport between fuzzy Two-Absorbing and fuzzy Socle-Jacobson–Two-Absorbiang. In addition to studying functions and some other related concepts. Our study's ramifications can be utilized to identify novel ideas that rely on hazy Socle-Jacobson–Two-Absorbiang concepts. In addition, we used some of the basics of modules and partial modules to prove that the intersection process in the new concept does not necessarily have to be achieved. In this study, the functions in modules and their relationship with the same concept and investigated some of the properties of those functions. The properties of the distributive module were also used in this research to achieve some theorems. In this research, it was also proven that the process of combining does not necessarily occur between two sub modules that bear the characteristics of the studied concept.
Results:
Using previous properties to find a new fuzzy sub module and a new definition.
Conclusions:
In this work, we presented a new type of fuzzy sub modules using the properties of addition and intersection between them and some properties of the new fuzzy submodule.

This review aims to identify the causes that contribute to global warming and offers the most likely cause, according to the published evidence. Additionally, this page provides various mitigation strategies for the global warming issue. The most practical economic and technical solution to the global warming problem is the simultaneous adoption of mitigation and adaptation techniques.
Global warming is a major consequence of human activities caused by the excessive use of old fuels as an energy- source, which has caused increased quantities of “greenhouse gases” (GHGs). The atmosphere contains gases that increase the Earth's average surface temperature, such as carbon dioxide, methane, nitrous oxide, and water vapor. Global warming phenomena have become a global problem with negative effects on various parts of the environment due to the glaciers melting, overflowing carbon dioxide (CO2), and too much warming of aquatic bodies, among others. Generality people are still unaware of global warming and do not see it as a main problem in the coming years.

Background:
Innate receptor called toll-like receptor 9 is capable of identifying both microbial and vertebrate DNA.It has been found in both normal mammary gland epithelial cells and breast milk cells.TLR-9was estimated in serum of patients and breast tissue for breast disease.
Methods:
A 100 women (17–60 years old) were determined undergoing breast surgery at Babylon Province's Al-Fayhaa Al Ahly Hospital and AL-Hilla Teaching Hospital provided blood and breast tissue samples. Hospital histology lab and clinical surgery performed histological confirmation of breast diseases( benign and malignant tumors). Twenty blood samples were taken as controls from women who appeared to be in good health. TLR9 was measured in the serum of patients with breast diseases as well as the control group using ELIZA.
Results:
The mean level of TLR9 in serum of patient was 339.4667 ng/l while control was 316.9929 ng/l with found significant differences where P_value was (0.05). while tissue of patient was 276.1064 ng/l. Concentrations of TLR9 were significantly higher in serum compared with tissues at (P≥0.05).The results found no significantly differences in concentrations of TLR9 among types of diseases in sera of patients. This study found concentration of TLR9 increased with primary breast diseases and it might be prognostic marker
Conclusion :
This study found concentration of TLR 9 increased with primary breast diseases and it might be prognostic marker