Al-Kitab Journal for Pure Sciences

Earthquakes are among the most dangerous natural disasters that can cause major losses to buildings and threaten human lives. The research community is very interested in the topic of earthquakes because they occur suddenly and predicting them is very important for human safety. Creating accurate earthquake prediction techniques by applying machine learning (ML) approaches will help save people\'s lives and prevent damage. To identify important features and analyze the correlation between these features before submitting them to classification models, we proposed a new feature selection approach in this paper which combines two filtering ways: Normalization which is based on the Chi-square approach and analysis of variance, and the correlation approach based on the logistic regression technique (CLR-AVCH). Accordingly, three algorithms are applied. Then a facilitated voting classifier is created that combines the two best models with the highest prediction accuracy (histogram-based gradient boosting, adaptive boosting) to create a single technique that includes the strengths of the techniques that were combined to help find important patterns in the acquired data to obtain a model capable of early prediction of earthquakes. The proposed work achieved higher accuracy, F1_score, recall, and precision (0.94, 0.92, 0.94, 0.92), respectively.

Due to the unique properties of a heterocyclic compound, it gained attention in the field of materials science. This study aims to provide a comprehensive synthesis of new co-polymers containing 1,3,4-thiadiazole. For this, a thorough search of electronic databases was conducted to identify relevant articles published from 2010 to 2021, using appropriate keywords and inclusion criteria. The selected studies were critically evaluated, and data was extracted and synthesized. The review includes a discussion of the various approaches used to prepare copolymers containing 1,3,4-thiadiazole, such as oxidative polymerization, electrochemical polymerization, and other methods. The properties and applications of the synthesized copolymers were also analyzed, including their thermal stability, electrical conductivity, and optical properties. The review concludes with an outlook on the prospects of co-polymers containing 1,3,4-thiadiazole and their potential applications in various fields, such as optoelectronics, sensors, and energy storage devices. The findings provide a valuable resource for researchers and engineers interested in the synthesis and properties of co-polymers containing 1,3,4-Thiadiazole.

This research deals with the three types of COVID-19 vaccines (AstraZeneca vaccine, Sinopharma, and Pfizer-Biontech) in terms of manufacturing, producing companies, and the countries in which the tests were conducted, in addition to the teams that provided the researchers with these vaccines. In this research, a statistical study about the effectiveness of these vaccines is presented and the extent of their impact on the vaccinator if he was healthy or carrying some other diseases. After that, a statistical study is presented, comparing it between the types of vaccines and which one is the most used, by taking a sample from the State of Iraq, Maysan Governorate, consisting of 60 individuals who took the vaccine. a special questionnaire was used for this purpose and the results were, another questionnaire about the acceptance of the local community results were analyzed using an SPSS program (Table 5, 6 and 7). Another questionnaire about the acceptance of the local community representing Maysan Governorate to obtain the vaccine for the emerging coronavirus, COVID-19. The questionnaire was also delivered to statistical specialists before submitting the questionnaire. Important results were obtained, including the most received vaccine Pfizer-BioNTech and Sinopharm, by 40% and all those who received the vaccine were not infected after taking the vaccine.

A Tc-99m thyroid scanning is one of the most common diagnostic modalities in nuclear medicine for the evaluation of various thyroid dysfunctions and anomalies. Therefore, this review study will delve into the various dimensions related to patient exposure during Tc-99m thyroid scanning. Various subjects are covered, such as radiation risks from the procedure, methods for reducing patient exposures, imaging technology developments, and the importance of an effective radiation safety program. In this review, some new developments in and possible ways toward better safety for the patient and diagnostic accuracy of the thyroid imaging methods are also discussed.

Food is necessary for all living humans to survive. Numerous nutrients, including proteins, lipids, carbs, vitamins, and minerals, are found in food. An organism consumes and breaks down these nutrients to create energy needed to support development and preserve regular bodily functions.
Food products can deteriorate due to microbiological, enzymatic, or chemical reactions to their surroundings. Preservatives extend the expiration of food and are also inserted into food goods to preserve quality; however, they may also have adverse side effects. Additionally, safety concerns are increasing as the need for cosmetics for teenagers and adults worldwide rises.
This review article\'s primary topic is the adverse effects of some specific preservatives commonly used in food and cosmetics, such as [sodium benzoate, parabens, and sulfites], to preserve or enhance their quality.

This research includes estimating the drug (Tramadol Hydrochloride, TR) using the potentiometric method by constructing selective electrodes for TR drug with the active ingredient (Ammonium Reinackate, AR) using a plasticizer (Nitro benzene, NB) and adding nanomaterials (Multi wall carbon nanotube (MWCNT), Nanosilica) for carbon paste electrodes to increase selectivity and sensitivity towards the material to be estimated. The results showed that the manufactured electrodes were able to estimate tramadol hydrochloride in the pharmaceutical preparation (tramadol tablets) at very low concentrations (trace amounts) up to 5.0×10-6 M using the direct and standard methods and proved to have a wide linear range up to 1.010-8 - 1.010-2 M. The Nernstatine slope of the prepared TR-AR-NB electrodes is (58.027, 58.251, and 58.694 mV/decade) for Carbon Paste Electrodes (CPE), MCPE (MWCNTs) and MCPE (MWCNTs+ nanosilica), respectively. The lower detection limit (LDL) is 2.39×10-7 M for the CPE and 4.98×10-8 M for the MCPE (MWCNTs) and 4.7384×10-9 M for the electrode MCPE (MWCNTs+ nanosilica) which makes it eligible for the estimation of tramadol hydrochloride in very low concentrations. The study included measuring the selectivity of these electrodes with the presence of interferers where the values of Ki,jpot for all studied species were less than 1. The drug was identified in both urine and blood plasma, with a recovery of at least 99.309 for urine and 97.6593 for blood plasma.

Refrigeration is one of the most widely used methods to control the growth of microorganisms in food products. A number of isolates was 433, including 363 isolates from refrigeration and 70 isolates from freezers. The fungus Cladosporium sp. is the large number in both refrigeration and freezer, 187 and 28, respectively, and the lowest numbers of fungi such as Rhizopus stolonifer, Rhizoctonia solani, and Fusarium sp., many fungi were isolated from refrigeration, while fungal isolates from freezing were less numerous and less diverse. Molecular identification of Cladosporium sp. because it is the most frequent among the fungal isolated from refrigeration and freezing by using polymerase chain reaction, it has been shown that Cladosporium sphaerospermum strain HKA in the gene bank. The aim of the study is to recognize the fungi that contaminate the refrigerator both domestically and commercially.

Each individual possesses a unique signature that is primarily employed to verify personal identity and authenticate legally binding documents or facilitate significant transactions, a method commonly utilized for verifying their identity. The utilization of this technology is restricted to the authentication of biometric recognition in a range of financial, legal, banking, insurance, and various other business documents. Techniques for recognizing signatures are employed to determine the specific user associated with a particular signature. In recent years, a significant number of researchers have focused on the implementation of novel approaches in this area, with a notable increase in the prevalence of deep learning techniques. To enhance the understanding of the evolution of offline handwritten signature recognition among researchers, this manuscript adopts a structured methodology to categorize this research, drawing primarily from studies found in set major databases. This study assesses methodologies for offline handwritten signature recognition by implementing predetermined inclusion and exclusion criteria. It explores various aspects, such as feature extraction and challenges in classification. In recent years, there have been noticeable advances and new developments. The paper accentuates the dominance of deep learning research directions in this specific domain. Differing from existing surveys, this paper does not confine itself to a particular research phase but meticulously outlines each stage, aspiring to guide future researchers in their investigations.

The automated division of brain developments using multimodal MR images is essential in the assessment and seeing improvement of sickness. Gliomas are compromising and amazing, fruitful and definite division strategies are used to help in the development of partition into intratumorally gathered classes. Significant learning computations beat standard setting-based PC vision approaches in conditions requiring semantic division. Convolutional Cerebrum Associations are by and large used in clinical image division. They have conclusively additionally evolved accuracy by and by in the division of brain tumours. In this investigation, we propose the ResNet (Waiting Association) a blend of two association divisions uses areas of strength for a clear combinative methodology to convey all the more endlessly definite assumptions. The models were ready on the (Devils 20) test data and later analyzed to make segments. Among the different methods of reasoning examined,( RESNET) produces the most solid results when diverged from (U-Net) and was in this manner organized in various ways to appear at the keep going assessment on the endorsement set, the get-together had the choice to get dice scores of 0.80, 0.85 for the development of development, hard and fast sickness, and disease focus, independently, showing more critical execution stood out from the momentum advancement being utilized.

A review of the existing body of literature about azo compounds and their practical applications. Azo compounds, which include a (-N=N-) group, serve as the fundamental structure for several produced compounds in different fields of chemistry, particularly coordination chemistry. These compounds are extensively utilized as coloring agents, as they account for around fifty percent of synthetic colors. Azo compounds are a significant class of chemicals with different applications in various fields of life. Due to the wide variety of their applications, it is essential to possess different synthesis techniques in order to get new azo derivatives with high yields. The main viable techniques for synthesizing azo compounds are diazotization and azo coupling reactions. Azo compounds have diverse uses in areas including anticancer, antifungal, antioxidant, anti-inflammatory, and anti-bacterial activities. In addition, it has several additional uses such as coloring fiber, printing systems, photo-electronics, polymer additives, and storage, and providing resistance to solvents, water, light, and weather.

Let R be a finite commutative ring with a non-zero unit, and L be an ideal of R. focuses on expanding the notation of the Zero Divisor Graph to create what is known as the Ideal-Based Zero Divisor Graph. The main goal is to classify rings using the ideal-based Zero divisor graph that consists of 9 vertices and symbolizes (ГL(R)) by using the properties |V(ГL(R))|=|L|.|V((Г (R /L))|, |L|≥2.

In this study, 15 isolates of Escherichia coli were isolated from patients with urinary tract infections from Al-Khansa'a Teaching Hospital Nineveh/Iraq from May 2023 to July 2023. The isolates were studied and diagnosed biochemically. The result of microscopic tests showed isolates that are short Gram-negative bacilli, and the result of biochemical tests was that the isolates were positive for catalase, triple sugar iron, indole, methyl red, coagulation enzyme, fermentation of the following sugars maltose, sucrose, galactose and glucose, while Escherichia coli isolates showed negative results for urease, Voges-Proskauer, and citrate tests. The isolates also showed resistance to all antibiotics used, with high resistance to both ampicillin 100%, erythromycin 100% and cephalothin 100%. 60% for nalidixic, 53.33% for azithromycin and 53.33% levofloxacin and the lowest resistance rate shown by the isolates to gentamicin was 46.7%.

Gabapentin is a medication commonly used in the treatment of epilepsy and sciatic neuropathy. Histology, biochemistry, immunohistochemical changes, body, kidneys, and brain weights were investigated in this study, where 15 male albino rats were used. The animals were split into 3 sets: A, B, and C (5 rats/set). Set A was administrated in distilled water (control set). Gabapentin was administrated orally to both B and C sets at doses 21.8 and 43.6 mg/kg, respectively. The dosing period was 30 days. The findings showed glomerular atrophy and changes in renal tissue in the B and C sets. Brain sections of B and C sets showed necrotic and degenerative changes. The findings showed insignificant body and brain weight increases in B and C sets, while set B significantly decreased kidney weight. Biochemical analysis showed an insignificant increase in the urea and creatinine in both experimental sets. Both B and C sets showed insignificant increases in the cholinesterase enzyme activity in the brain. Immunohistochemical assessment of the kidney tissue showed positive and strong positive immunoreactivity of both caspases 3 and 8. Both B and C sets showed weakly positive and positive Glial Fibrillary Acidic Protein (GAFP) immunoreactivity in the brain. It was obvious that gabapentin caused the induction of apoptosis in the kidney through the overexpression of caspases 3&8. The medication also induced various lesions in the brain, especially in the axons
of the neurons. The severity of its effect depended on the given dose and duration of treatment.