Al-Kitab Journal for Pure Sciences

Semantic segmentation is considered as one of the most important and challenging problem in the field of computer vision which aims at assigning a class label to each pixel in an image which leads to sophisticated scene understanding. This task has been extensively used in various application areas including the self-driving cars, medical diagnosis, and environmental monitoring. Semantic segmentation has come a long way since its early detection algorithms based on features extractions to state-of-the-art deep learning methods.
This paper aims at presenting the evolution of the semantic segmentation, and specifically, how the deep learning has changed the field. The conventional approaches consisting of edge detection and histogram analysis offered a basic level of understanding but were constrained by the use of hand crafted features. Deep learning, however, is capable of learning features and has produced very promising results across numerous tasks. Some important architectures that have set the benchmark in the field include Fully Convolutional Networks (FCNs), U-Net, and DeepLab which have used convolutional layers, encoder-decoder architecture, and atrous convolutions for improving the accuracy of the segmentation. The article also reviews some of the publicly available datasets which include Cityscapes, PASCAL VOC and ISIC 2017 which are widely used to assess the performance of the segmentation models. These datasets differ in their complexity, resolution, and the application domain that they cover which makes the problems that they present to researchers diverse. Also, we compare the traditional and deep learning based feature extraction methods and present the characteristics of each method, their advantages, and disadvantages, and areas of application. This survey aims at assisting researchers and practitioners by presenting the current best practice in the form of state-of-the-art methodologies, discussing the potential of application of such methodologies in the real world, and identifying the directions for further research.Therefore, despite the advancement of deep learning in the area of semantic segmentation, there are still numerous issues which need to be addressed in the future, including efficiency, scalability, and domain specific issues. This all-encompassing review paper is hoped to be beneficial to those wishing to gain more knowledge on the current trends as well as find a way to contribute to the field of semantic segmentation in the future.

Somatic embryos are regarded the primary plant material for producing artificial seeds, and these seeds provide for agricultural institutions genetically uniform seeds, unlike the traditional seeds that often produce plants with different traits from the parent plant; in addition to the possibility of storing it for a long time Arabidopsis thaliana, locally known as mouse ears, is a promising model because it is self-fertile, which makes it conserved, and can produce thousands of seeds, which makes it ideal for mutation experiments. It is diploid (10=2n), and the identification of selectable traits is more straightforward because it has a relatively small genome (125 Mpb). The genome organization in Arabidopsis thaliana is simple and particularly suitable for genetic and molecular biology experiments.. This study produced Arabidopsis thaliana Nossen (NO-0) plants from the differentiation of callus tissues from its growing seedlings on MS medium (roots, stems, leaves). The B5 medium free of growth regulators successfully induced root callus, while the highest response for callus induction from stem segments was observed on B5 medium containing 0.05 mgL-1 kinetin (Kin) and 0.5 mgL -1 2-4, Dichlorophenoxy acetic acid (2,4-D). The B5 medium containing 0.05 mgL-1 (Kin) kinetin and 1.0 mg/L-1 (2,4-D) 2,4-Dichlorophenxy acetic acid (2,4-D) also affected leaf callus induction. The results of the statistical program SPSS version 16 also showed a significant difference at a probability level of 1% in the percentage of calyx creation for the plant parts used .The MS medium containing 0.5 mgL-1 Thidiazuron (TDZ) and 1.0 mgL-1 6-Benzyl adenine (BA) was effective in producing embryonic phases from transferred root callus. Meanwhile, the embryonic phases from stem and leaf callus were produced on MS medium supplemented with 0.5 mgL-1 Thidiazuron (TDZ), resulting in a group of 290 shoots. A 2% sodium alginate concentration was used in experiments to encapsulate somatic embryos, yielding the best form of artificial seeds in spherical structures (Beads) and achieving a high conversion rate of 80% when stored for 20 days at 4°C, and 60% when stored for 20 days at 25°C. There are significant differences at the 5% level in the germination of seeds stored for 20 days at a temperature of 25°C. The number of plants resulting from the artificial seeds was 36 green shoots. The experiments were carried out over a period of six months in the Tissue Culture and Genetic Applications Laboratories at the College of Education for Pure Sciences/University of Mosul.

Globally, intestinal parasites cause of a considerable amount of illness and death. Parasites in the gut are a serious public health concern in poor countries. Infections with intestinal parasites are among the most prevalent diseases worldwide. Low-quality drinking water and unclean personal and environmental conditions are often associated with them. This study aimed to determine the prevalence of gastrointestinal parasites from patients who attended Sherkhan General Hospital, Shekhan District, Duhok, Iraq. The study conducted a retrospective cross-sectional analysis from January to November 2023. Overall, 228 recorded stool samples for eleven months were included in this study, and direct wet stool examinations were done for all stool samples to record intestinal protozoan stages. 228 stool samples were reported for eleven months between January and November 2023. Of them, 90 (39.47%) were recorded positive for intestinal protozoan parasites. The highest infection rate was found in September (8.3%), while the lowest rate of intestinal parasites was in November (0.0%). Regarding gender, the infection rate with parasitic infection was higher in males (22.3%) than in females (17.1%). Regarding a total of 228 samples the most prevalent age group aged <10 years (6.7%), the moderate one was in ages between 10-30 years (8.8%), and the lowest was in ages >30 years (3.9%). Finally, this study recorded that the most common gastrointestinal protozoan parasites were Giardia lamblia (21.1%) and Entamoeba histolytica (17.1%). Infections can be prevented and controlled by practicing epidemiological surveillance, keeping oneself clean, and improving environmental cleanliness.

Analysis of the structural and dielectric properties of Ag-substituted Ni-Co spinel ferrite, represented by the formula Ni0.4Co(0.6-x)Ag2xFe2O4, were examined for values of (0.00 ≥ X ≤ 0.45). An auto-combustion sol-gel process was used to synthesis this ferrite, which was then calcined at temperatures up to (1000°C). The ferrite samples underwent X-ray diffraction (XRD) research to determine their particle size, lattice characteristics, bulk density, and hopping length. The size of the crystallites varied between (32.952 nm and 43.926 nm), while the lattice parameter rose between 8.291 and 8.326 Å as the amount of silver ions increased. The X-ray density increased from 5.466 to 5.904 g/cm³, which was attributed to the larger molecular mass of silver (Ag) at 107.87 g/mol compared to cobalt (Co) at 58.93 g/mol.Dielectric properties were also studied, including both the real (ε^\\') and imaginary (ε^\\'\\') components of the dielectric constant, the dielectric loss represented by the loss tangent (tan δ), and electrical resistivity(ρ_ac(. The results showed a decrease in both the real and imaginary dielectric constants, as well as a reduction in dielectric loss with increasing applied frequency. Additionally, a decrease in electrical resistivity was observed with increasing frequency.

Vitamin C has effects on cancer as both an antioxidant and a pro-oxidant. It serves as an antioxidant by reducing oxidative stressors and minimizing genetic damage. Conversely, high pharmacological doses of vitamin C can act as pro-oxidants impacts that are detrimental to cancerous cells. Moreover, vitamin C can modify the metabolomics and epigenetic profiles of cancer cells, leading to the elimination of cancer stem cells. Additionally, it can enhance immune system activity and suppress cancer transformation through various pathways.
The review included several studies that dealt with the effect of vitamin C on leukemia patients or associated it with treatment in vitro or in vivo to enhance patients’ response to treatment and minimise side effects. It has been shown through previous and recent studies that the role of vitamin C is effective in treating leukemia patients. Additional researches are required to better understand the mechanistic and clinical dimensions of these effects.

Cardiovascular diseases, particularly coronary heart disease (CHD), are among the most prevalent conditions associated with atherosclerosis, primarily affecting adults aged 40 years and older. Oxidative damage plays a crucial role in various pathological conditions, with reactive oxygen species (ROS) contributing significantly to CHD progression. This study included 60 CHD patients (30 males and 30 females) aged 40–69 years, all of whom were non-smokers, non-alcoholics, and free from comorbidities such as hypertension or diabetes. A control group of 30 healthy individuals (15 males and 15 females) aged 40–67 years was also included. Blood samples were collected from hospitals in Kirkuk for biochemical analysis.
The findings revealed a significant decrease (P ≤ 0.05) in the levels of high-density lipoprotein (HDL), superoxide dismutase (SOD), vitamin E (VE), and total antioxidant capacity (TAC) in CHD patients compared to the control group. The measured values were 29.128 ± 2.001 mg/dL (HDL), 40.038 ± 7.245 U/mL (SOD), 26.136 ± 6.376 µmol/L (VE), 216.19 ± 34.85 μmol/L (TAC), whereas the control group exhibited 56.267 ± 8.890 mg/dL, 72.191 ± 2.729 U/mL, 39.251 ± 7.839 umol/L, and 422.66 ± 69.11mg/mL, respectively. Additionally, gender showed a statistically significant effect (P ≤ 0.05) on CHD risk, with differences observed between male and female patients compared to the healthy group. Age also played a critical role, with significant variations (P ≤ 0.05) across age groups, indicating an increased CHD risk with advancing age. Furthermore, body mass index (BMI) showed significant differences (P ≤ 0.05) when comparing all biochemical variables between patients and the control group. The study highlights the significant role of oxidative stress and antioxidant depletion in CHD patients, with age, gender, and BMI contributing to disease progression. These findings emphasize the importance of early intervention strategies to manage oxidative stress and reduce CHD risk. The results revealed a significant decrease in antioxidants (SOD, vitamin E, TAC) and HDL levels in CAD patients compared to controls, confirming oxidative stress\\\\&#039;s role in disease progression. Age, gender, and BMI were linked to higher risk. These findings highlight the importance of early detection and risk factor management in heart disease prevention.

The features of water and aqueous systems used in the directed synthesis of materials with specified properties are shown. Water simultaneously plays the role of the initial medium, \\"building material\\" and \\"tool\\" in this synthesis. The conditions of directed crystallization and melting of ice are discussed as the basis for controlling the physicochemical transformations of components in aqueous systems. New methods of studying and using aqueous systems are considered - the \\"floating reactor\\" method and its based on the use of the Pettier and Seebeck effects.

Integrating nanoparticles (NPs) with heterocyclic compounds has emerged as a multidisciplinary innovation that spans materials science, medicinal chemistry, and nanotechnology. Nanoparticles, with their distinct physicochemical properties such as high surface area-to-volume ratio, surface reactivity, and functionalizability, provide an ideal platform for enhancing the performance and delivery of heterocyclic compounds. Heterocycles, which contain at least one atom other than carbon in their ring structure, are foundational to many pharmaceuticals, agrochemicals, and optoelectronic materials. When conjugated with or loaded onto nanoparticles, these compounds often exhibit improved solubility, stability, and biological availability. The nature of the interaction, whether through physical adsorption, covalent bonding, or coordination chemistry, significantly influences the functionality of the resulting hybrid nanomaterials. Applications range from targeted drug delivery and controlled release systems to heterogeneous catalysis and environmental sensing. Additionally, green synthesis approaches have enabled more sustainable production of these conjugates, using plant extracts and biological materials as reducing and stabilizing agents. However, challenges such as toxicity, environmental accumulation, and regulatory oversight remain barriers to large-scale implementation. This review explores the chemistry behind NP with heterocycle interactions, the synthesis and characterization techniques employed, and the current and emerging applications in various scientific and industrial fields. By critically evaluating recent progress, this study provides insight into the potential of these hybrid systems and highlights future directions for their optimization and safe application.

The pot experiments were conducted in winter 2024-2025 at the Department of Biology green house, College of Science in the University of Mosul. Treatments were done alongside the pure leaf of (Ficus carica and Punica granatum) by adding soil to the pots with the rate of 10 g/kg soil. All the parameters applied in the experiments were randomly allocated in accordance with absolutely randomization of the design (CRD) to know their influence on the Vicia. faba L. seed germination and growth. The results indicated that leaves at 10% for P. granatum had a significant stimulatory in shoot length 37.5cm, root length at an average of 20.7 cm and its fresh weight 14.8 g. while F.carica had a significant increased growth parameters (germination 96% , shoot length and its fresh weight ,39.4 cm and 25.9 g) respectively, root length and its fresh weight(18.2 cm,13.6 g), as well as the number of nodes and flowers, compared to the control. The findings of this research suggest the potential of applying fresh leaf of F. carica and P. granatum as a bio stimulant for V. faba plants\\' germination and development.

Artificial intelligence (AI) is transforming healthcare, with (ML) offering significant potential for early disease diagnosis and personalized treatment, particularly in diabetes management. This capability is crucial for enhancing diagnostic accuracy. However, accurately predicting type 2 diabetes remains challenging due to diverse patient populations and complex data, as traditional methods can be slow and miss subtle early indicators, leading to delayed interventions. There is a clear need for robust predictive models. This paper proposes and evaluates various ML algorithms and data mining techniques for effective type 2 diabetes prediction. We utilized a unique Iraqi dataset with comprehensive features including HbA1c, lipid profiles, age, and BMI. Our methodology involved rigorous data preprocessing, including cleaning and handling class imbalance with SMOTE. Eight ML algorithms were compared: Decision Tree (DT), Naïve Bayes (NB), Random Forest (RF), Gradient Boosting (GB), K-Nearest Neighbor (KNN), Logistic Regression (LR), and Artificial Neural Networks (ANN). Model performance was assessed using accuracy, precision, recall, F1-score, MAE, RMSE, and AVE, with cross-validation ensuring robustness. The DT algorithm achieved the highest performance, with an accuracy of 99.44%, outperforming all other models. This highlights DT’s effectiveness and its potential for accurate early diagnosis, confirming HbA1c, age, and BMI as key predictors. Future work should establish a national health database in Iraq and explore advanced deep learning techniques, such as Convolutional Neural Network and Recurrent Neural Network.

This paper presents a comprehensive review and experimental analysis of machine learning algorithms applied to load balancing in Software-Defined Networking (SDN). From a review standpoint, it considers the rapid development of data centers and the increasing complexity of traffic, underscoring the shortcomings of traditional algorithms. The studies examined are systematically compared in terms of their pros and cons in real-life situations. In addition to the review, the paper presents original findings by assessing specific machine learning techniques, notably Artificial Neural Networks (ANN) and Deep Learning (DL) models, via tenfold cross-validation. The experimental results indicate that the ANN achieves the lowest average response time (1.955 ms), closely followed by the DL (1.962 ms), which demonstrates the highest stability across runs. SVM with C=100C=100C=100 gets the best classification accuracy in ten-fold cross-validation. DL comes in third, and ANN comes in last. When considering both latency and accuracy, DL offers the best overall trade-off between speed, stability, and accuracy for SDN load balancing. It beats traditional baselines (LR: 4.461 ms; SVM: 17.9–18.0 ms). These results, which are directly related to the method used, show that advanced ML methods are better for SDN load balancing. The paper also addresses significant challenges, such as scalability and adaptability, and proposes future research directions for hybrid AI-driven models to enhance the efficiency of SDN-based network management.

Vaginal candidiasis is a common condition among women due to genetic and environmental factors, which are associated with the causative agents of Candida species sp, leading to physical symptoms in affected women. Sixty-five samples (45 samples from women with vaginal candidiasis and 20 samples from healthy women) were collected from vaginal swabs and blood samples. Microscopic diagnostic tests were performed to investigate and identify Candida species. Tetra-ARMS PCR was also conducted to determine the association of the interleukin-10 gene polymorphism with vaginal candidiasis in women from the city of Mosul, northern Iraq. Furthermore, genetic variation results were analyzed using five molecular tests. The microscopic examination results of vaginal swabs revealed four types of yeast: Candida albicans represented 67% of sample frequency, C. glabrata 21%, C. tropicalis 7%, while C. krusei represented 5% of sample frequency. Moreover, the results of Tetra-ARMS-PCR of blood samples from infected women showed a higher percentage of the wild CC genotype (70%) compared to the mutant TT genotype (12%), while the heterozygous CT genotype was (18%) compared to the healthy group (55%, 5%, 40% respectively). The frequency of the (C) allele in infected samples was high (80%) compared to the mutant (T) allele (20%), whereas in the healthy group, the frequencies of the C and T alleles were (75% and 25% respectively). The Hardy–Weinberg equilibrium test showed an environmental factor effect and the disappearance of the genetic factor.

Herpesviruses are complex DNA viruses that rely on host-cell machinery for replication and pathogenesis. One critical aspect of their lifecycle involves the transport of viral and host proteins between the nucleus and cytoplasm. This review aims to explore the role of shuttling proteins in herpesvirus infection, focusing on their transport mechanisms, interaction with nuclear transport receptors, and contribution to viral replication and immune evasion. the viral lifecycle is significantly impacted by the transportation of different proteins between the cytoplasm and nucleus throughout viral infection. Shuttling proteins usually consist of nuclear localization signals as well as nuclear export signals for the purpose of mediating proper positioning for themselves and other proteins. They are crucial components in nucleocytoplasmic information transmission inside the cells. The nuclear pore complex on nuclear envelope facilitates the nucleocytoplasmic transport mechanism, which is mediated by certain protein carriers. Ongoing research has progressively clarified which herpesvirus proteins function via nucleocytoplasmic shuttling. An outline of how shuttling proteins use nuclear transport receptors as well as nucleocytoplasmic shuttling signals for nucleocytoplasmic transport is given in the presented work. This research offers a resource for comprehending herpesvirus infection pathogenesis and formulating novel anti-viral approaches. It also explains how herpesvirus shuttling proteins contribute to efficient infection of viruses through altering their life-cycle and engaging in innate immunity.

This work condensed 4-hydroxybenzaldehyde and triazole-based primary amines to form triazole–imine compounds (A–D). Generated compounds revealed azomethine links in FTIR and NMR. Streptococcus pneumoniae and Bacillus subtilis antibacterial activity was measured by 0.1, 0.001, and 0.00001 mg/mL agar diffusion derivative C had the largest concentration-dependent inhibition zones of 23 mm against S. pneumoniae and 25 mm against B. subtilis. MTT also assessed PC-3 and MCF-7 cytotoxicity. The derivative A dose-dependently reduced PC-3 and MCF-7 cell viability by 4.99% and 8%, respectively, at 320 μg/mL. Docking DNA-associated protein (8RZX) explains these biological results. Docking data show stable binding conformations, with RMSD values around 2 Å and binding energies −2.5 kcal/mol, especially for derivative C. The majority of interactions were hydrogen bonding with phosphate groups and π–π stacking with nucleobases. Experimental and computational evidence suggest triazole–imine compounds are potential antibacterial and anticancer scaffolds.

As a material transitions below its critical temperature, a defining characteristic of superconductivity is the Meissner effect, which is the removal of magnetic fields from the material. Within the Ginzburg-Landau and BCS models, this effect is thoroughly comprehended in traditional (single-band) superconductors. . In multiband superconductors like MgB₂ and iron-based superconductors, exceptions to this usual pattern of action have been found. Clustering of anomalous vortices, mixed-phase vortex states, paramagnetic. Meissner responses are all examples of such phenomena. Type-1.5 superconductivity, giant paramagnetic Meissner responses, and implications for advanced superconducting applications are the main topics of this paper\\'s review of recent experimental and theoretical results on the anomalous Meissner effect in multiband superconductors.

This paper discuses the decomposition of Fundamental Function of Finsler space by Lie-derivative in generalized fifth recurrent Finsler space for Cartan's fourth curvature tensor K_jkh^i in sense of Berwald. The decomposition of Lie-derivative of some tensors is studied by using a covariant, contravariant and mixed tensor in GBK-5RF_(n ). The decomposition tensor φ_kh^ibehaves as fifth-recurrent is proved. Also, new identities are established in generalized BK- fifth recurrent Finsler space that admits tensors decomposition.