Journal of Kerbala University

1

Beta-Glucan: An Overview of its Properties, sources, Health Benefits, immunity and Extraction methods

Mustafa Abdul Kareem Hameed, Ameer H. Alsafah, Hayder Talib Mahdi

Pages: 1-13 English

Abstract

A common homopolysaccharide made of D-glucose, beta glucan has a number of biological actions, such as anti-inflammatory, antioxidant, and anti-tumor effects. It is also found in cereals and microbes. More recently, there has been increasing evidence that β-glucan acts as a physiologically active compound that regulates adaptive immune responses, promotes dendritic cell maturation, and secretes cytokines. These processes are all directly linked to -glucan-regulated glucan receptors. This review focuses on the sources, characteristics, immunomodulatory properties, health benefits, extraction methods, and purification techniques of β-glucan

Keywords

Beta glucan extraction healthy benefits Immunity

2

A proposed network of an effective deep belief for the recognition of Alzheimer

Shaymaa Adnan Abdulrahman

Pages: 14-22

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Abstract

Alzheimer(A.Z) is a gradually advancing condition that leads to the degeneration of brain cells. rendering an individual unable of independent functioning. During the initial stages of AZ development, an individual may forget prior talks or the occurrence of an incident. Subsequently, there may be a substantial decline in memory, rendering the individual unable of doing daily tasks . Therefore, this study aims to differentiate between patients with AZ and those in the normal control (NC) group by employing magnetic resonance imaging (MRI). Four phases were used in our study: collected (420)subjects as dataset , preprocessing with a 2D Gaussian filter, and feature extraction by using deep neural networks , while last step is classification . Machine learning algorithms are used to determine if the subject are demented or not . In this study , applied Random Forest and Naive Bayesian
methods as classifier . For analysis purpose , (WEKA.) tool is utilized .The experimental results show that accuracy was 83 %with Random forest while 79% with Naive Bayesian

Keywords

Alzheimer’s disease Classification . Deep learning

3

An Overview of Techniques for Various Image Segmentation

,Shaymaa Adnan Abdulrahman, Mohamed Roushdy, Abdel-Badeeh M. Salem

Pages: 23-35 English

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Abstract

One of the most important image processing tasks is thought to be image segmentation. The process of splitting or partitioning an image into what are known as segments is known as image segmentation. Since it is inefficient to process the entire image for these kinds of applications, it is mostly helpful for image compression and object recognition applications. In order to separate the portions of a picture for additional processing, image segmentation is utilized. Many image segmentation algorithms are available that divide a picture into multiple segments according to certain properties such as color, texture, and pixel intensity value. These methods are all grouped according on the segmentation approach that was applied. This study reviews and discusses numerous image segmentation approaches, and ends with a comparison of their benefits and drawback

Keywords

image processing Segmentation

4

Biochemical and Demographical study in patients with corona virus

Taha H. Alnasrawi

Pages: 36-52 English

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Abstract

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Most people infected with the virus will experience mild to moderate respiratory illness and recover without requiring special treatment. However, some will become seriously ill and require medical attention. Older people and those with un-derlying medical conditions like cardiovascular disease, diabetes, chronic respiratory disease, or cancer are more likely to develop serious illness. Anyone can get sick with COVID-19 and become seriously ill or die at any age. The objective of this study is to eval-uate of some biochemical test and their complication in patients with COVID-19. The practical part included cross-sectional study and collecting any information and tests about the 49 patients with COVID-19 and 55 as a control in Karbala province. The obtained data were classified according to sex, age, mortality besides the bio-chemical tests. The results of this study showed that there is an in-crement in the concentration of urea and CRP comparing with the normal range as well as the level of WBC. In addition, the results revealed that the percentage of covid-19 patients in male was more than in female and the percentage of infected of age over 45 years was high. Furthermore, the D-dimer of 88% of patients was over 250 ng/ml. Besides, the mortality rate of male (57%) was more than in the female

Keywords

Covid-19 respiratory syndrome World Health Organization.

5

Synthesis and Preliminary Antibacterial Activities of novel Schiff bases Derivatives of 3,6-diazahomoadamantane

Zeinab Mohammed Ali, Rahman Tama Alasadi

Pages: 53-59 English

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Abstract

This work includes synthesis of new Schiff bases derivatives of di-azahomoadamntane.
First, 1,3,6,8-tetraazatricyclo[4.4.1.13,8]dodecane 1 was treated with anisyl acetone to produce
1-(4-methoxybenzyl)-3,6-diazahomoadamantan-9-one
2. Reaction of ketone compound 2 with aqueous hydrazine yielded 1-(4-methoxybenzyl)-3,6-diazahomoadamantan-9-hydrazone
3. Condensation of hydrazone derivative 3 with some benzaldehydes including (4-carboxybenzaldehyde, 3-chlorobenzaldehyde, 3-hydroxybenzaldehyde, 4-nitrobenzaldehyde) under reflux in ethanol afforded imine derivatives of diazahomoadamntane
4a¬¬–d. The structures of newly synthesized derivatives have been de-duced via FT-IR, 1H NMR, and Mass spectral means. Antibacterial test of new derivatives 4a-d showed that compounds 4b, 4c, and 4d have activity against Staphylococcus aurous more than Gentamycin as a ref-erence drug, also compound 4d pointed higher activity against Esche-richia coli than the standard drug.

Keywords

azaadamantane; Schiff Bases; heterocyclic; anisylacetone; ad-amanzane.

6

Synthesis and Characterization of Novel Nano Graft Copolymer-N-acetylpseudoephedrine drug Composite and Studying their Effect in the Treatment of Lung Cancer

Zainab N. F. Al-Yasiry, Alaa Jawad Kadhim, Mohammad N. AL-Baiati

Pages: 60-71 English

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Abstract

The research includes two steps: in the first step, preparation of a nano co-polymer from the reaction of one mole of glycerol with three moles of phthalic anhydride and was chracterized using 1H-NMR, FT-IR, TEM, AFM. The second step is the loading of the drug (N-acetyl pseudoephedrine) onto the nano co-polymer via ester bonds. In order to determine the protein binding site for the amino acid bond under investigation, an AutoDock software was used to investigate molecular docking. The above-mentioned chemotherapy drug was tested on a lung cancer cell line, and the results showed its high effectiveness in preventing the spread of lung cancer cells, as evidenced by the noticeable decrease in the percentage of these cells compared to the control group. Novel cytotoxicity of nano composites containing N-acetyl pseudoephedrine in A549 cells. The IC50 value is 45.033 µg/mL

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Development and Validation of a 1-Year-Old Computational Voxel Phantom for Improved Dosimetric Accuracy in Paediatric Dental Cone Beam Computed Tomography

Nabeel Ibrahim Ashour

Pages: 72-85 English

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Abstract

Cone Beam Computed Tomography (CBCT) offers a lower radiation dose alternative for paediatric patients compared to conventional CT scan, particularly in managing cleft lip and palate (CLP). Accurate dosimetry is essential to balance benefits and risks, with Monte Carlo simulations being a feasible approach. Despite advancements in computational phantoms, a gap exists for 1-year-old paediatric phantoms specific to CLP cases in dental CBCT. This study addresses this gap by developing and validating a 1-year-old voxel model for dental CBCT, utilising binary data from medical images as outlined in International Commission on Radiological Protection publication 143. The binary data were converted to voxel images using (X) MedCon software and processed in 3DSlicer to create a 3D model representing head and neck organs and tissues, including modifications for CLP anatomical variations. Validation against anthropometric data confirmed the model's accuracy. Monte Carlo GATE simulations were then used to calculate absorbed and effective organ doses during dental CBCT procedures. Effective dose (ED) values ranged from 0.02 mSv to 2.98 mSv, with dose reductions achieved by lowering the tube current-time product. The cochlea received the highest dose due to its proximity to the cone beam's field of view, while the brain and thyroid received the lowest doses due to protective anatomical positioning. The study provides a reliable dosimetry voxel phantom and emphasises optimising exposure parameters in paediatric imaging to minimise radiation risks.

Keywords

3D voxel model 3DSlicer software Medical image data Monte Carlo paediatric phantom design and effective dose.

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The Importance of Nanotechnology in Modern Medicine and its Use as Antimicrobial and Anticancer: a review

Raful.M.mahdi, Fatema Ali AL Kafhage, Ghufran S. Salih, Rana A. Jawad

Pages: 86-98 English

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Abstract

Therapy utilizing nanoparticles has become known as a promising therapeutic modality. Those nanoparticles' nanosized gives them certain physical and chemical features as well as improves how well they interact with the biological system. Nanomaterials are characterized by treating many diseases, such as the treatment for cancer along with the significant issue of drug resistance in infection control. Incorporating antimicrobial Nano compounds into materials to prevent microbial adhesion or kill microorganisms has become an increasingly challenging strategy. Recently, many studies have been conducted on the preparation of nanomaterials with antimicrobial properties against diseases caused by pathogens. Despite tremendous efforts to produce antibacterial materials, there is little systematic research on antimicrobial coatings. In this article, we set out to provide a comprehensive overview of nanomaterials-based antimicrobial coatings that can be used to stop the spread of contamination on surfaces. Because of these particles' unique size, shape, and range of fundamental and chemical behaviors, they are being utilized to enhance current treatments. Together with a thorough overview of the condition of nanotechnology in medicine today, the writers covered the application of nanoparticles in the treatment of cancer, illnesses brought from bacteria that are resistant to drugs, including biofilm prevention.

Keywords

antimicrobial bacteria Cancer. nanoparticles

9

Molecular identification of antibiotics resistance genes of pathogenic bacteria isolated from different clinical sources

Gufran kareem Abd, Ali A. Al-Hisnawi

Pages: 99-115 English

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Abstract

Most of the acquired antibacterial resistance can be obtained by mutations occurring in genes due to certain physical and chemical factors. These mutations are present in chromosomal gene and plasmids , among other types of mobile genetic elements. Aim of the current study is to determine the resistance genes in isolated pathogenic bacteria and their effectiveness in resisting pathogenic bacteria to antibiotics. In the present study, Samples from patients suffering from burns, wounds and urinary tract infection were collected . These samples were cultured on the proper media and colonies were identified by different biochemical tests. Identified pathogenic bacteria were applied to investigate their resistance against wide range of antibiotics using VITEK system. PCR technique was used to detect the antibiotics resistant genes among bacterial isolates. Results showed that K. pneumoniae carried all tested genes. However, tem and shv genes were absent in St. aureus, E. coli and P. aeruginosa. It can be concluded that all tested bacteria were dangerous due to the antibiotics resistance activity but K. pneumoniae were the most dangerous.

Keywords

antibiotics resistance E. Coli K. pneumoniae P. aeruginosa St. aureus β-lactam

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Molecular identification of antibiotics resistance genes of pathogenic bacteria isolated from different clinical sources

Gufran kareem Abd, Ali A. Al-Hisnawi

Pages: 99-115 English

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Abstract

Most of the acquired antibacterial resistance can be obtained by mutations occurring in genes due to certain physical and chemical factors. These mutations are present in chromosomal gene and plasmids , among other types of mobile genetic elements. Aim of the current study is to determine the resistance genes in isolated pathogenic bacteria and their effectiveness in resisting pathogenic bacteria to antibiotics. In the present study, Samples from patients suffering from burns, wounds and urinary tract infection were collected . These samples were cultured on the proper media and colonies were identified by different biochemical tests. Identified pathogenic bacteria were applied to investigate their resistance against wide range of antibiotics using VITEK system. PCR technique was used to detect the antibiotics resistant genes among bacterial isolates. Results showed that K. pneumoniae carried all tested genes. However, tem and shv genes were absent in St. aureus, E. coli and P. aeruginosa. It can be concluded that all tested bacteria were dangerous due to the antibiotics resistance activity but K. pneumoniae were the most dangerous.

Keywords

antibiotics resistance E. Coli K. pneumoniae P. aeruginosa St. aureus β-lactam

11

The relationship between fibrinogen and the development of foot ulcer inflammation in patients with and without type 2 diabetes

Abeer Thaher Naji Al-Hasnawi, Afaf K. Shwaikh Ismail, Dhiaa H. Alwan

Pages: 116-126 English

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Abstract

Background: Diabetes-specific consequences include diabetic foot ulcer (DFU). In DFU a variety of bacterial communities have been found to be involved in the prognosis of infection. Fibrinogen is another easy and reliable indicator of inflammation. It has been observed that individuals with diabetic foot illness have higher levels of this protein.
Materials and Methods: In the current cross-sectional investigation, there were 100 samples total of diabetic type 2; 50 of the patients had type 2 diabetes with foot ulcers, while the other 50 did not. To identify the bacterial species, swab specimens were gathered and cultured.
Results: Based on the statistical analysis of this study, as age, and smoking there are a significant difference in most of the characteristics compared between the study populations. However, when comparing diabetic patients with foot ulcers to those without ulcers, the statistical analysis showed a statistically significant increase in fibrinogen levels. According to bacterial kind, gram-negative bacteria accounted for 78% of bacterial growth and gram-positive bacteria for 22%. The bacterial genera Staphylococcus aureus had the highest percentage of isolates from ulcers (34%), followed by Klebsiella pneumonia (28%), and Proteus mirabilis (26%).

Keywords

Bacterial culture Diabetic foot ulcer Fibrinogen Type 2 diabetic

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The relationship between fibrinogen and the development of foot ulcer inflammation in patients with and without type 2 diabetes

Abeer Thaher Naji Al-Hasnawi, Afaf K. Shwaikh Ismail, Dhiaa H. Alwan

Pages: 116-126 English

Full Text Issues

Abstract

Background: Diabetes-specific consequences include diabetic foot ulcer (DFU). In DFU a variety of bacterial communities have been found to be involved in the prognosis of infection. Fibrinogen is another easy and reliable indicator of inflammation. It has been observed that individuals with diabetic foot illness have higher levels of this protein.
Materials and Methods: In the current cross-sectional investigation, there were 100 samples total of diabetic type 2; 50 of the patients had type 2 diabetes with foot ulcers, while the other 50 did not. To identify the bacterial species, swab specimens were gathered and cultured.
Results: Based on the statistical analysis of this study, as age, and smoking there are a significant difference in most of the characteristics compared between the study populations. However, when comparing diabetic patients with foot ulcers to those without ulcers, the statistical analysis showed a statistically significant increase in fibrinogen levels. According to bacterial kind, gram-negative bacteria accounted for 78% of bacterial growth and gram-positive bacteria for 22%. The bacterial genera Staphylococcus aureus had the highest percentage of isolates from ulcers (34%), followed by Klebsiella pneumonia (28%), and Proteus mirabilis (26%).

Keywords

Bacterial culture Diabetic foot ulcer Fibrinogen Type 2 diabetic

13

Levels of serum concentration adiponkines (ghrelin and obestatin) in patient with hypothyroidism

Teeba Haider Abdul ameer, Jasem Hanoon Hashim AL-AWADI, Rana Majeed Hameed

Pages: 127-135 English

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Abstract

Background: Hypothyroidism is one of the most widespread disorders affecting the thyroid gland in the world, which associated with hormonal disorders. Objective: the aim of this study to measured adipokines (ghrelin and obestatin) in hypothyroidism patients.
Patient and method: A case-control study comprised 60 samples from hypothyroidism patients and 30 healthy samples from female patients ranging in age from 20 to 70 . A questionnaire was designed for collecting patiens as required in criteria of the study and to distinguish them from healthy controls. This questionnaire include Age, hight, weight, BMI, chronic disease and duration of illness for patients. A thorough clinical history, physical examination, and pertinent laboratory tests were performed on the patients, and an evaluation of laboratory measures for thyroid diseases was used to establish the kind of problem. Serum ghrelin and obestatin concentrations were measured in serum samples using the enzyme-linked immunosorbent assay system (ELISA) using the Competitive-ELISA method

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Detection of Some Antibiotic Resistance of beta lactam and flouroquinolines Gene Among Coliform Bacteria isolated from Al-Hussainiya river

Asia Jawad Kareem, ,Ali A. Al-Hisnawi

Pages: 136-149 English

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Abstract

Background: Coliform bacteria are the most important bacterial contaminate the water bodies.
Objectives: the present study aimed to detect antibiotics resistance and biofilm formation activities among coliform bacteria isolated from different places on Al-Hussainiya river.
Method :- During a period of July 2023 to February 2024, 18 samples were collected from three different places ( Baron, Al-Atishi area and the white arch) on Al-Hussainiya river in summer and winter (9 samples in summer and 9 samples in winter for isolation of coliform. Most probable number (MPN) methods were used for evaluated the numbers of coliform bacteria during two seasons. The isolated coliform were further identified using Biochemical tests and Vitek 2 technique. PCR method was used to detect some genes including SHV, TEM, CTX, qur-A and Aac(6) Ib in 15 isolates of coliform during summer and winter. The current data showed that the numbers of coliform were significantly higher in summer in the white arch and Baron hotel. In contrast coliform appeared to be significantly lower in winter compared to summer in Al-Atishi point. Two way anova showed significant differences between stations and seasons (P≤0.05

Keywords

Aac(6) Ib biofilm. coliform ESBL genes PCR assay qnr-A river water

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Detection of Some Antibiotic Resistance of beta lactam and flouroquinolines Gene Among Coliform Bacteria isolated from Al-Hussainiya river

Asia Jawad Kareem, ,Ali A. Al-Hisnawi

Pages: 136-149 English

Full Text Issues

Abstract

Background: Coliform bacteria are the most important bacterial contaminate the water bodies.
Objectives: the present study aimed to detect antibiotics resistance and biofilm formation activities among coliform bacteria isolated from different places on Al-Hussainiya river.
Method :- During a period of July 2023 to February 2024, 18 samples were collected from three different places ( Baron, Al-Atishi area and the white arch) on Al-Hussainiya river in summer and winter (9 samples in summer and 9 samples in winter for isolation of coliform. Most probable number (MPN) methods were used for evaluated the numbers of coliform bacteria during two seasons. The isolated coliform were further identified using Biochemical tests and Vitek 2 technique. PCR method was used to detect some genes including SHV, TEM, CTX, qur-A and Aac(6) Ib in 15 isolates of coliform during summer and winter. The current data showed that the numbers of coliform were significantly higher in summer in the white arch and Baron hotel. In contrast coliform appeared to be significantly lower in winter compared to summer in Al-Atishi point. Two way anova showed significant differences between stations and seasons (P≤0.05

Keywords

Aac(6) Ib biofilm. coliform ESBL genes PCR assay qnr-A river water

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Detection of Some Antibiotic Resistance of beta lactam and flouroquinolines Gene Among Coliform Bacteria isolated from Al-Hussainiya river

Asia Jawad Kareem, ,Ali A. Al-Hisnawi

Pages: 136-149 English

Full Text Issues

Abstract

Background: Coliform bacteria are the most important bacterial contaminate the water bodies.
Objectives: the present study aimed to detect antibiotics resistance and biofilm formation activities among coliform bacteria isolated from different places on Al-Hussainiya river.
Method :- During a period of July 2023 to February 2024, 18 samples were collected from three different places ( Baron, Al-Atishi area and the white arch) on Al-Hussainiya river in summer and winter (9 samples in summer and 9 samples in winter for isolation of coliform. Most probable number (MPN) methods were used for evaluated the numbers of coliform bacteria during two seasons. The isolated coliform were further identified using Biochemical tests and Vitek 2 technique. PCR method was used to detect some genes including SHV, TEM, CTX, qur-A and Aac(6) Ib in 15 isolates of coliform during summer and winter. The current data showed that the numbers of coliform were significantly higher in summer in the white arch and Baron hotel. In contrast coliform appeared to be significantly lower in winter compared to summer in Al-Atishi point. Two way anova showed significant differences between stations and seasons (P≤0.05

Keywords

Aac(6) Ib biofilm. coliform ESBL genes PCR assay qnr-A river water

17

Stability of Riemann–Hadamard Fractional Differential Nonlinear System with Delay Riemann −Katugampola

Ahmed Sami Sleibi, Sameer Qasim Hasan

Pages: 150-171 English

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Abstract

The purpose of this paper is to investigate the finite-time stability of a proposal problem containing a Riemann-Hadamard fractional differential nonlinear control system with delay Riemann-Katugampola fractional-order systems. The inequalities for satisfying the stability depend on Gronwald's general formulation, which constrains the types of fractionals. The necessary and sufficient conditions are presented in different results to support the stability with delay time of solution with nonlinear functions as well as the numerical examples to illustrate all the interesting results.

Keywords

and Stability Nonlinear Control System Riemann Riemann−Katugampola Riemann-Hadamard

18

Cipher algorithms challenges of IoT applications: A review

Zaid M. Jawad Kubba, Wisam Abed Shukur, Mustafa A. Ali

Pages: 171-182 English

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Abstract

The enormous developments in the Internet and communications applications present new security challenges, such as sensitive data col-lection of IoT devices. Cipher algorithms play a key role in IoT applica-tions, countless cryptosystems are presented for securing such applica-tions. Various challenges were intensely presented due to the vast in-crease in the developments of IoT applications and the requirements of the cipher algorithms which are considered the main challenges for adapting lightweight cryptosystems. Thus, in this study, different cipher algorithms are reviewed and analyzed based on lightweight cryptosys-tems. Moreover, various features are examined and discussed through the most common cipher algorithms for designing cipher algorithms to be efficient in IoT applications. The result showed the major challenges and factors that should be undertaken when designing cryptosystems of IoT applications. The challenges are experimented with parameters such as key size, computational cost, time, etc. This work would be refer-enced for developing an efficient cipher algorithm for IoT applications which presents the main factors and challenges that should be consid-ered when designing such cryptosystems.

Keywords

Cryptography; Information Security; IoT; Cryptosystems

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Expanding Network Function Virtualization (NFV) Technology's Performance and Reliability in LTE Systems

Nabil Abdulwahab Abdulrazaq Baban

Pages: 183-197 English

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Abstract

As Long-Term Evolution (LTE) systems evolve to meet growing data traffic and service demands, Network Function Virtualization (NFV) has emerged as a key enabler to improve network flexibility, scalability, and cost-efficiency. However, the performance and reliability of NFV implementations in LTE environments remain a significant challenge due to latency issues, resource allocation inefficiencies, and the complexity of ensuring consistent service availability. This paper addresses these challenges by proposing a novel framework that enhances NFV's operational efficiency and reliability within LTE networks. The framework integrates dynamic resource management techniques with intelligent orchestration policies, which optimize the allocation of virtualized network functions (VNFs) while minimizing the impact on system performance. Additionally, the solution introduces enhanced failover mechanisms to mitigate the risks of service disturbence during VNF migration or hardware failures. Experimental results demonstrate improved throughput, reduced latency, and higher service availability compared to existing NFV solutions. This contribution significantly advances NFV's potential to support next-generation LTE systems, paving the way for more robust and adaptable mobile network infrastructures

Keywords

eNodeBs EPC LTE MIMO NFV NFVO OFDMA SDN SFC UEs vBBU vEPC VIM. vMME VNFM vPGW vRAN vRRH vSGW

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Expanding Network Function Virtualization (NFV) Technology's Performance and Reliability in LTE Systems

Nabil Abdulwahab Abdulrazaq Baban

Pages: 183-197 English

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Abstract

As Long-Term Evolution (LTE) systems evolve to meet growing data traffic and service demands, Network Function Virtualization (NFV) has emerged as a key enabler to improve network flexibility, scalability, and cost-efficiency. However, the performance and reliability of NFV implementations in LTE environments remain a significant challenge due to latency issues, resource allocation inefficiencies, and the complexity of ensuring consistent service availability. This paper addresses these challenges by proposing a novel framework that enhances NFV's operational efficiency and reliability within LTE networks. The framework integrates dynamic resource management techniques with intelligent orchestration policies, which optimize the allocation of virtualized network functions (VNFs) while minimizing the impact on system performance. Additionally, the solution introduces enhanced failover mechanisms to mitigate the risks of service disturbence during VNF migration or hardware failures. Experimental results demonstrate improved throughput, reduced latency, and higher service availability compared to existing NFV solutions. This contribution significantly advances NFV's potential to support next-generation LTE systems, paving the way for more robust and adaptable mobile network infrastructures

Keywords

eNodeBs EPC LTE MIMO NFV NFVO OFDMA SDN SFC UEs vBBU vEPC VIM. vMME VNFM vPGW vRAN vRRH vSGW

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Face Expression Classification Based On Behavioral Pattern Recognition Using Deep Learning

Sabah Mohammed Fayadh, Elham Mohammed Thabit A. Alsaadi, Meeras Salman Al-Shemarry, Soheir Noori

Pages: 198-209 English

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Abstract

In this study, a novel personal identification and engagement monitoring approach based on facial recognition in online examinations is proposed. First, the proposed Back Propagation Convolutional Neural Network (BPCNN) model uses deep transfer learning to perform student identity verification and to unravel emotional cues indicating engagement. The system includes a serious of comprehensive authentication modules to block unauthorized access and guarantee integrity of testing. Furthermore, facial expressions like happiness, anger, sadness, surprise are captured to get the insights into the variations in student engagement. Likewise, the system does not utilize separate facial expression analysis refinements, but indirectly uses emotional cues to improve assessment reliability. The model is shown to have achieved a high accuracy rate of 92% overtaking conventional models against key performance metrics including accuracy, recall, and F1 score. This solution integrates robust facial recognition with indirect emotion based insights for improved security and engagement tracking in e learning environments.

Keywords

deep learning Face Recognition Facial expression transfer learning.

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Face Expression Classification Based On Behavioral Pattern Recognition Using Deep Learning

Sabah Mohammed Fayadh, Elham Mohammed Thabit A. Alsaadi, Meeras Salman Al-Shemarry, Soheir Noori

Pages: 198-209 English

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Abstract

In this study, a novel personal identification and engagement monitoring approach based on facial recognition in online examinations is proposed. First, the proposed Back Propagation Convolutional Neural Network (BPCNN) model uses deep transfer learning to perform student identity verification and to unravel emotional cues indicating engagement. The system includes a serious of comprehensive authentication modules to block unauthorized access and guarantee integrity of testing. Furthermore, facial expressions like happiness, anger, sadness, surprise are captured to get the insights into the variations in student engagement. Likewise, the system does not utilize separate facial expression analysis refinements, but indirectly uses emotional cues to improve assessment reliability. The model is shown to have achieved a high accuracy rate of 92% overtaking conventional models against key performance metrics including accuracy, recall, and F1 score. This solution integrates robust facial recognition with indirect emotion based insights for improved security and engagement tracking in e learning environments.

Keywords

deep learning Face Recognition Facial expression transfer learning.

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Face Expression Classification Based On Behavioral Pattern Recognition Using Deep Learning

Sabah Mohammed Fayadh, Elham Mohammed Thabit A. Alsaadi, Meeras Salman Al-Shemarry, Soheir Noori

Pages: 198-209 English

Full Text Issues

Abstract

In this study, a novel personal identification and engagement monitoring approach based on facial recognition in online examinations is proposed. First, the proposed Back Propagation Convolutional Neural Network (BPCNN) model uses deep transfer learning to perform student identity verification and to unravel emotional cues indicating engagement. The system includes a serious of comprehensive authentication modules to block unauthorized access and guarantee integrity of testing. Furthermore, facial expressions like happiness, anger, sadness, surprise are captured to get the insights into the variations in student engagement. Likewise, the system does not utilize separate facial expression analysis refinements, but indirectly uses emotional cues to improve assessment reliability. The model is shown to have achieved a high accuracy rate of 92% overtaking conventional models against key performance metrics including accuracy, recall, and F1 score. This solution integrates robust facial recognition with indirect emotion based insights for improved security and engagement tracking in e learning environments.

Keywords

deep learning Face Recognition Facial expression transfer learning.

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Face Expression Classification Based On Behavioral Pattern Recognition Using Deep Learning

Sabah Mohammed Fayadh, Elham Mohammed Thabit A. Alsaadi, Meeras Salman Al-Shemarry, Soheir Noori

Pages: 198-209 English

Full Text Issues

Abstract

In this study, a novel personal identification and engagement monitoring approach based on facial recognition in online examinations is proposed. First, the proposed Back Propagation Convolutional Neural Network (BPCNN) model uses deep transfer learning to perform student identity verification and to unravel emotional cues indicating engagement. The system includes a serious of comprehensive authentication modules to block unauthorized access and guarantee integrity of testing. Furthermore, facial expressions like happiness, anger, sadness, surprise are captured to get the insights into the variations in student engagement. Likewise, the system does not utilize separate facial expression analysis refinements, but indirectly uses emotional cues to improve assessment reliability. The model is shown to have achieved a high accuracy rate of 92% overtaking conventional models against key performance metrics including accuracy, recall, and F1 score. This solution integrates robust facial recognition with indirect emotion based insights for improved security and engagement tracking in e learning environments.

Keywords

deep learning Face Recognition Facial expression transfer learning.

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Evaluation of Novel Biomarkers Fetuin-A and KIM-1 and Bacterial Isolation in Early Diagnosis of Chronic Kidney Disease in Iraq

Haneen f. Noory, Ayyed hameed hasan, Sajidah F. Hasan

Pages: 210-221 English

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Abstract

This study evaluates the role of novel biomarkers Fetuin-A and Kidney Injury Molecule-1 (KIM-1) in early chronic kidney disease (CKD) diagnosis. It identifies bacterial isolates associated with CKD patients in Iraq. One hundred-five samples (60 CKD patients and 45 healthy controls) were analyzed using ELISA for biomarker levels, and bacterial isolation was performed using standard culture methods. Results showed significantly elevated levels of Fetuin-A and KIM-1 in CKD patients compared to controls, correlating with disease progression stages. Commonly isolated bacteria included Klebsiella, E. coli, and Staphylococcus aureus, highlighting potential infection risks in CKD. These findings suggest that Fetuin-A and KIM-1 are valuable biomarkers for early CKD detection, and bacterial infections are prevalent among CKD patients, emphasizing the need for early screening and targeted interventions. The novel biomarkers and high levels of renal function (urea and creatinine ) are related.

Keywords

Bacteria isolation biomarker Chronic Kidney Disease fetain A human kidney injury molecule-1 renal function test

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Evaluation of Novel Biomarkers Fetuin-A and KIM-1 and Bacterial Isolation in Early Diagnosis of Chronic Kidney Disease in Iraq

Haneen f. Noory, Ayyed hameed hasan, Sajidah F. Hasan

Pages: 210-221 English

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Abstract

This study evaluates the role of novel biomarkers Fetuin-A and Kidney Injury Molecule-1 (KIM-1) in early chronic kidney disease (CKD) diagnosis. It identifies bacterial isolates associated with CKD patients in Iraq. One hundred-five samples (60 CKD patients and 45 healthy controls) were analyzed using ELISA for biomarker levels, and bacterial isolation was performed using standard culture methods. Results showed significantly elevated levels of Fetuin-A and KIM-1 in CKD patients compared to controls, correlating with disease progression stages. Commonly isolated bacteria included Klebsiella, E. coli, and Staphylococcus aureus, highlighting potential infection risks in CKD. These findings suggest that Fetuin-A and KIM-1 are valuable biomarkers for early CKD detection, and bacterial infections are prevalent among CKD patients, emphasizing the need for early screening and targeted interventions. The novel biomarkers and high levels of renal function (urea and creatinine ) are related.

Keywords

Bacteria isolation biomarker Chronic Kidney Disease fetain A human kidney injury molecule-1 renal function test

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Unraveling MS Pathogenesis: The Critical Roles of B and T Cells in Disease Development

Etab Abdul Ameer Al-Ogla, Haneen Saeed Muhsen Al-Mosawei, Rasha A.Abidalmutalib Aljabawi, Karrar Mahmood Shaker Alkhfaji

Pages: 222-241 English

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Abstract

Introduction
Multiple sclerosis is a complex inflammatory disease characterized by the immune system's aberrant attack on the central nervous system , leading to localized inflammation and demyelination of nerve cell sheaths. This autoimmune response is primarily mediated by lymphocytes, the body's defensive cells, which mistakenly target healthy central nervous system nerve cells, ultimately causing neurological impairments and a range of debilitating symptoms.
LiteratureReview
In recent years, extensive studies have explored the underlying mechanisms of Multiple sclerosis pathophysiology. Traditionally, T cells have been understood as central to MS progression, mediating immune-driven central nerve system damage. However, emerging research has uncovered an equally critical role for B cells, challenging the established paradigm and broadening the understanding of immune involvement in Multiple sclerosis. This review reevaluates past research and recent findings on the dual contributions of T and B cells to MS pathology, highlighting how B cells may drive disease progression through mechanisms distinct from those of T cells

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The Effect of Aqueous and Oil Extracts of Foeniculum vulgare (Sweet Fennel) on the Larval Stages of Ephestia cautella (Fig Moth)

Ali Alshalji, Yousif Dakheel Rashid

Pages: 242-247 English

Full Text Issues

Abstract

A series of laboratory experiments were conducted in the Graduate Studies Laboratory, Department of Biological Resistance Technologies, Al-Musayyib Technical College, from 1st October 2023 to 1st December 2023. The experiments aimed to assess the effects of hot, cold aqueous, and oil extracts of Foeniculum vulgare (sweet fennel) on the various larval stages of Ephestia cautella (fig moth). The results indicated that the oil extract of fennel seeds outperformed the cold and hot aqueous extracts, with the highest mortality rate of 66.70% observed for the oil extract at a a concentration of 1% after 72 hours. In comparison, the highest mortality rates for the hot aqueous extract and cold aqueous extract at the same concentration were 40.00% and 53.30%, respectively, after 72 hours. The lowest mortality rate for the oil extract was observed at a concentration of 0.25%, registering 10.00%, while the cold aqueous extract resulted in a minimum mortality rate of 6.70% at a concentration of 0.25% after 72 hours post-treatment.
The findings also revealed that the percentage of mortality increased with higher extract concentrations and longer exposure times.

Keywords

Cold Aqueous Extract Date Moth Extracts Fennel Seeds Hot Extract Oil extract

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