JOURNAL OF EDUCATION AND SCIENCE

This research offers detailed insights into managing and preventing meningococcal disease, highlighting Neisseria meningitidis and Neisseria gonorrhoeae as key pathogens. It focuses on the epidemiological diversity and classification of meningococcal serogroups, along with their worldwide distribution. A significant portion of the study is dedicated to advancements in vaccination, especially conjugate and protein-based vaccines, which have markedly enhanced prevention. The study examines the transmission and carriage mechanisms of N. meningitidis, emphasizing its carrier state and potential to cause severe diseases like meningitis and sepsis. It also explores virulence factors such as the polysaccharide capsule, lipooligosaccharide (LPS), and Type IV pili, and their contribution to disease pathogenesis. Additionally, it discusses nasopharyngeal epithelium colonization and the host\'s immune response role. The research ultimately highlights the crucial need for ongoing surveillance, vaccination, and international public health initiatives in effectively addressing meningococcal disease. The research provides valuable insights into the management and prevention of meningococcal disease. It emphasizes the critical role of vaccination, the need for ongoing surveillance, and the importance of global public health initiatives to mitigate the impact of this disease.

There is a rising interest in nanocomposites with unanticipated features that are different from traditional materials to fulfill the demands of these applications. Cobalt oxide (Co3O4) nanoparticles, and cobalt oxide with multi-walled carbon nanotubes (Co3O4/ MWCNTs) as nanocomposites were created. In this study, cobalt oxide nanoparticles (Co3O4 NPs) were synthesized via co-precipitation method chemical using CoCl2 salt as a source of cobalt nanoparticles and sodium hydroxide solution as a factor agent at room temperature. The cobalt hydroxide (Co(OH)2) precipitate was obtained, then it calcinated the cobalt hydroxide precipitate at 600°C to obtain the cobalt oxides nanoparticles (Co3O4 NPs). Also, MWCNTs were prepared by a locally manufactured reactor at 423 k. Binary composites were prepared by solution method using cobalt oxide nanoparticles dispersion over MWCNTs surfaces. The structural, morphological, and spectral properties were confirmed and investigated by using FE-SEM, Raman spectroscopy, and (XRD), respectively. The surface area and pore size obtained by BET and BJH showed that the binary nanocomposites (Co3O4/MWCNTs) have a higher surface area than their pristine cobalt oxide and multi-walled carbon nanotubes nanoparticles. The adsorption processes of nanocomposites have attracted significant care from the scientific public because of their distinctive possessions and aptitude to reduce and adsorb Cu+2 and Ni+2 as heavy metals from water pollution. As a result, Co3O4 and its nanocomposite with MWCNTs were used to remove copper and nickel ions from the dilute aqueous solution.

Imaging is a vital component of the diagnostic and early detection processes for many medical disorders. However, the noise in the images can sometimes interfere with the accuracy of the diagnosis. Speckle noise, Poisson noise, salt and pepper noise, and Gaussian noise are a few instances of these disturbances, which are produced by imaging techniques and reduce diagnostic accuracy as well as image quality. Noise reduction methods, such as spatial filtering and transformational domain filtering, have a lot of problems when dealing with various kinds of noise. With the growth of deep learning, especially generative adversarial networks, the capabilities of image noise reduction are even superior to those of traditional techniques. This study compares the efficacy of GAN techniques with traditional de-noising techniques and illustrates the effects of various noise sources on medical imaging. Besides that, it describes how the GAN accomplishes the noise reduction task in medical imaging by discussing its advantages, uses, and efficiency in comparison to other techniques. The study\'s outcomes revealed a new approach to using GAN to filter out the noise in medical images and the possibility of utilizing this technique in real-world cases to generate accurate diagnosis and analysis. But, in addition to that, it serves as a passageway to more in-depth research that focuses on medical image enhancement and patient healthcare.

In this paper, we solved the SEIR system (a system that describes the spread of viruses in computers) using the homogeneous balance method, which is one of the methods concerned with finding the accurate solution for equations of various types, linear, non-linear, partial, and ordinary. SEIR is a system of nonlinear partial equations. Studying this system helps reduce the damage caused by viruses to computers and the problems they cause to devices by predicting the presence of viruses before they spread to computers. The system was solved and the exact solution of the SEIR system was found. The effect of the parameters was studied, and it was found that the smaller these parameters were (close to zero), the slower the viruses leaked into computers. The impact of parameters and how much performance they can cause to devices is explained using 3D graphics. It has become clear that these viruses pose a great danger to devices, so studying them is a topic that deserves attention.

Yearly, an amount of funds is spent to achieve defect detection in the principle of infrastructure represented by roads, bridges, and buildings. Urban infrastructure is affected by weather conditions, the natural disasters such as floods and earthquakes. As well as, mistakes during street paving operations and quality of paving materials. Various types of damage may appear in the form of small or vast cracks, which gradually spread, destroying the structure. Therefore, it requires building automatic systems for these inspection operations to guarantee its effectiveness and dependability. Hybrid image processing and machine learning approaches are being applied to guarantee better enhancement outcomes and strength in crack detection. This paper aims to offer a review of road image crack detection techniques that apply image processing with/without machine learning. A total of 32 research articles have been composed and studied for the review which has been issued in publications and conferences in the past years. This research manners a thorough analysis and comparison of various methods to identify the most promising automated methods for crack detection. After analyzing and reviewing previous research using digital image processing methods, it is clear from the results obtained that the best of them is the Franji filter method, whose accuracy is close to 98.7%. While discussing and presenting machine learning techniques and convolutional networks, the deduced results that the best of them is the Support Vector Machine (SVM) technique, whose precision is approximately 98.29%

In the current study, the effect of lethal concentrations of drug solutions and chemicals against pupae of Culex pipiens molestus mosquitoes was investigated after 24 hours and up to 3 days of the experiment using different concentrations. Regarding the drug solutions, the concentration of 100 ppm of the niclosamide drug solution showed a 100% lethal effect on the second day of the experiment, and the value of LC50 was 113.7 ppm. The concentration of 800 ppm of the sulfasalazine drug solution caused the death of all the pupa, with a death rate of 100% on the third day of the experiment, and the value of LC50 was 854.7 ppm. The concentration of 2000 ppm for both piperazine and isoniazid medicinal solutions caused a death rate of 100% on the second and third day of the experiment, respectively, and the LC50 value for both piperazine and isoniazid was 2220.7 and 2273.0 ppm, respectively. The concentration of 14,000 ppm of the drug solution 4-aminoantipyrine caused the death of all pupal mosquitoes on the second day of the experiment, and the value of LC50 was 14,360.0 ppm. As for solutions of chemicals, the concentration of 150 ppm of the chemical solution ethyl salicylate showed a lethal effect on all pupal mosquitoes, with a 100% death rate on the second day of the experiment, and the value of LC50 was 176.2 ppm. The death rate of mosquito pups reached 100% when using chemical solutions of thymol, sulfamic acid, sulfanilamide, and 2,6-dihydroxytoluene at concentrations of 240, 2000, 2500 and 10,000 ppm, respectively. The value of LC50 for each of thymol and sulfamic acid was, Sulfanilamide and 2,6-dihydroxytoluene 352.1, 2940.8, 2582.5 and 10750.0 ppm, respectively.

This study was conducted to investigate one of the most prominent bacteria that causes acne (Cutibacterium acnes), studying the spread of the phenomenon of resistance to the various antibiotics used to treat acne and studying the evolutionary relationship between isolates of Cutibacterium acnes. 125 samples were collected from patients with acne vulgaris cases in Mosul city, from dermatology consultations at Al-Salam Teaching Hospital and Mosul General Hospital, the diagnosis was made for samples through routine examinations (macroscopic and microscopic) and through molecular diagnosis based on universal 16s rRNA gene, the results of the isolation and diagnosis were obtaining seven isolates of Cutibacterium acnes and one isolate of Cutibacterium avidum with (5.6%) and (0.8%) respectively from all samples.
Eight antibiotics were chosen to perform the susceptibility tests by disc diffusion assay, the study showed that seven of C. acnes isolates were resistant to fusidic acid and azithromycin with 85.7%, tetracycline with 71.4%, clindamycin, and gentamycin with 57.1% respectively and vancomycin 42.8% the isolates were sensitive 100% to imipenem and levofloxacin. In this study, an evolutionary tree was created depending on the degree of neighbor- joining among these molecularly diagnosed isolates based on the MEGA11 program strains 103, 107, and 111 each showed a genetic similarity with 93%, and their cluster formed a 91% similarity with strain 112, which in turn clustered with 89% with strain 118 and their similarity with strain 117 decreased to 74%. In turn, it clustered with strain 110 at a rate of 99%. C. avidum strain was distant fromC. acnes strain. Naturally, the Staphylococcus aureus strain was at the end of the tree, which was used to create a root for the genetic tree of the strains .

This study succeeded in developing hairy roots from the hypocotyledonous stems of chamomile Matricaria chamomilla L. plant seedlings by Ri plasmid isolated from Agrobacterium rhizogenes ATCC 15834 using direct injection technology, and exceeding the concentration 1214.32 In encouraging the development of hair roots by 80% after7 day. After isolating the hair roots from their places of formation and placing them individually or as tufts on solid Murashige and Skoog (MS) medium, typical cultures were produced and required subcultured every 25 One day, the hair roots were characterized by being white, branched, and growing negative geotrpism. The results of electrophoresis on an agarose gel of the isolated polymerase chain reaction (PCR) product, which included the amplification of deoxyribonucleic acid (DNA), showed the appearance of a single band with a molecular size of 248 bp, which is similar to the molecular size of the specific primer of the rol A gene, and this is evidence of the success of the transformation. Genetic analysis by transferring T-DNA genes from plasmids and inserting them into the cell genome of seedlings of the chamomile plant.

Prenatal care refers to medical attention that a woman receives to maintain her health and the health of her unborn child. The traditional methods of medical experts in prenatal care advice can sometimes be inadequate and less efficient due to a number of factors. One major issue is the lack of knowledge in the area of prenatal care for most medical experts, which hinders quality advice to pregnant women. In order to overcome some of these challenges, computer-based methods for any health issue have been proposed, which have shown to be more effective and are being utilized more frequently to raise the standard of medical care. This research work proposes the use of an expert system approach based on a forward-chain inference engine. Java programming language was used in the implementation of the proposed expert system. The expert system for prenatal care recommendations had a mean satisfaction level score of 3.87 out of a possible 5.0, according to the assessment results based on survey opinions. This suggests a 77.5% level of user satisfaction. The performance level of the expert system in providing quality advice to pregnant women indicates that it is faster, more sensitive, and more reliable than the traditional method of using medical experts to provide prenatal care advice.

In this study, five isolates of Rhizobium bacteria were isolated from root nodules of different leguminous plants as follows: Ensifer meliloti EW7 from Medicago sativa L., Ensifer fredii bv. fredii EW33 from Vigna unguiculata L., R. leguminosarum bv. phaseoli EW15 from Phaseolus vulgaris L., R. leguminosarium bv. trifolii EW19 from Trifolium alexandrium L. and R. legumiosarium bv. viciae EW30 from viciae faba L., which were collected from different cultural areas in Nineveh, Governorate-Iraq. Then pure Rhizobium colonies were obtained, and their agronomic and biochemical characteristics were studied. These isolates were a rod-shaped and negative Gram-stain. Whereas positive for TSI, BTB, CUT, Kovak’s test, urase test, and for the methyl red and Voges-Proskauer tests. All of the rhizobial isolates showed positive results for the catalase test and for motility when tested on TY semi-solid medium. Tolerance of local Rhizobium isolates was tested against four heavy metal salts as follows: Pb(CH3COO)2, Nicl2, CdCl2, and CoCl2. The isolates showed a varied response to tolerance or resistance to heavy metal salts. The highest mean of inhibition zone reached 21mm in isolate Ensifer fredii bv. fredii EW33 against heavy metal CdCl2. Whereas the isolate R. legumiosarium bv. viciae, EW30 showed less affects which mean of inhibition zone was 9 mm only with 5000 concentration of heavy metal CoCl2.