University of Mosul

The aim of this paper is to better understand the dynamics of crystallogenic and starting activity in biological fluids of patients throughout surgery and the late postoperative phase in alveococcosis. Samples of saliva from 22 individuals with alveococcosis were included in the research. Biological fluid samples were taken at the time of admission and before the patient was discharged. Following that, slides were made utilizing the teziocrystalloscopy method, which incorporates the investigation of the crystal forming activity of mixed saliva with its starting characteristics using a 0.9 percent sodium chloride solution as the foundation ingredient. Using our own set of criteria, we evaluated the outcomes of crystalloscopic and tezigraphic experiments. Specrophotometric examination of tezigraphic and crystalloscopic facies was done using a PowerWave XS microplate spectrophotometer at wavelengths of 400, 350, and 300 nm to augment the results from ocular morphometry of dried saliva micro slides. Surgical therapy results in a partial normalization of physical and chemical parameters, as well as the composition of the patient's biological fluids after the patient is discharged from the hospital.

Nanoparticles (NPs) are insoluble particles with a diameter of fewer than 100 nanometers. Two main methods have been utilized in orthodontic therapy to avoid microbial adherence or enamel demineralization. Certain NPs are included in orthodontic adhesives or acrylic resins (fluorohydroxyapatite, fluorapatite, hydroxyapatite, SiO2, TiO2, silver, nanofillers), and NPs (i.e., a thin layer of nitrogen-doped TiO2 on the bracket surfaces) are coated on the surfaces of orthodontic equipment. Although using NPs in orthodontics may open up modern facilities, prior research looked at antibacterial or physical characteristics for a limited period of time, ranging from one day to several weeks, and the limits of in vitro studies must be understood. The long-term effectiveness of nanotechnology‑based orthodontic materials has not yet been conclusively confirmed and needs further study, as well as potential safety concerns (toxic effects) associated with NP size.

Over the last decade, paper-based biosensing has attracted considerable attention in numerous fields due to several advantages of them. To elaborate, using paper as a substrate of sensing approaches can be considered an affordable sensing approach owing to low cost of paper, and alongside that, the ability to operate without requiring external equipment. In many cases, cost-effective fabrication techniques such as screen printed and drop casting can be supposed as other benefits of these platforms. Despite the portability and affordability of paper-based assay, two important limitations including sensitivity and selectivity can decrease the application of these sensing approaches. Initially, decoration of paper substrate with nanomaterials (NMs) can improve the properties of paper due to high surface area and conductivity of them. Secondly, the presence of bioreceptors can provide a selective detection platform. Among different bioreceptors, deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) can play a significant role. From this perspective, paper-based biosensors can be used for the detection of various gens which related to biomedical or food safety. In this review, we attempted to summarize recent trends and applications of paper-based genosensor, along with critical arguments in terms of NMs role in signal amplification. Furthermore, the lack of paper-based genosensors in field the of biomedical and food safety will be discussed in the following.

The interaction of three dimensions forms the theoretical and field framework for this study, namely (market orientation, neuromarketing, and customer satisfaction), as market orientation represents the development of market intelligence about the current and future needs and desires of customers to satisfy those needs, with the distribution of this information to all departments of the organization and the creation of a response comprehensive. In contrast, neuromarketing is represented as researching brain patterns and some physiological consumer responses to marketing stimuli represented by electroencephalography, skin galvanic responses, eye tracking, work services, and facial coding. Therefore, this research represents great importance by identifying three important facts in the science of marketing management, which represent goals that organizations of all kinds seek to achieve and apply to keep pace with competition and confront it. on her, Asia Cell Company was a field for conducting the field side of the study, and the researchers sought to include several questions expressing the problem of the study, which were the basis for building the field side of the study, including (i)Is there a significant effect of market orientation on customer satisfaction and neuromarketing? (ii)Is there an indirect, significant effect of market orientation on customer satisfaction through neuromarketing? To answer these questions, a hypothetical scheme for the study was formulated that reflects the relationships and influences between the two dimensions of the study, which resulted in a set of main and sub-hypotheses that were tested using a number of statistical methods for the data collected in the questionnaire, which numbered (150), and all of them were retrieved. A set of conclusions that were distributed in terms of the theoretical side and the field side, the most important of which are: The increase in the interest of the researched company in customer satisfaction came when the organization adopted the market orientation as its approach. Neuromarketing reinforced these results when it entered a mediating variable, as we note that relying on market orientation and building appropriate strategies. In the light of this approach and through the techniques adopted by the company and provided by neuromarketing, will lead to increased customer satisfaction with the services provided by the researched company. Based on the conclusions reached by the study, both theoretical and field, proposals were presented that are consistent with these conclusions.

Rainfall forecasting addresses several challenges in water resource management and socioeconomic development, despite its complexity and non-linearity. To overcome this issue, machine learning and advanced time series data statistical approaches have been used. Water scarcity in the Nineveh Governorate in northern Iraq leads to significant ecological and economic issues, and the lack of a comprehensive rainfall forecasting system could exacerbate this problem. This study utilizes the Prophet model to present long-term rainfall forecasting up to 2030 on a daily scale for Nineveh, based on time series data from five rain stations from 1981 to 2021. The results demonstrate that the Prophet model yields high accuracy for daily rainfall forecasting and effectively captures seasonal variations, as evidenced by the evaluation metrics and trend analysis. We found that rain station locations, elevations, and local climatic conditions influenced long-term rainfall forecasting. Our findings also revealed that annual rainfall is predicted to decline by approximately 314 to 191 mm (39%), 160 to 120 mm (25%), 200 to 160 mm (20%), and 297 to 253 mm (14.8%) at Rabbia, Haddar, Sinjar, and Mosul stations, respectively, by 2030. However, Shekhan station is projected to receive a 20% increase in rainfall from 370 to 447 mm by 2030. Moreover, lower rainfall zones in the southeast and southwest will expand towards the central and southwestern regions, with a concentration of increased rainfall in the northeast areas of the governorate. These findings highlight the need for proper management and consideration of the consequences of climate change, which are likely to have debilitating impacts on local hydrological systems.

A series of batch assays have been conducted to investigate the optimal factors that can be adopted to improve the anaerobic digestion (AD) performance of Phragmites australis and increase biogas production. The assays were carried out using 125 mL microcosm reactors with a working volume of 80 mL and incubated at mesophilic conditions (37 ± 1ºC). The effect of particle size (10, 5, 2, and < 1 mm) and alkaline pre-treatment of P. australis using various concentrations of sodium hydroxide (0.5, 1, 2, and 4%) on biogas production was examined. Furthermore, the best pre-treatment incubation time (12, 24, 48, 72, 96, and 120 h) and the optimal inoculum to substrate ratio (ISR: 4:1, 2:1, 1:1, 1:2 and 1:4) were also assessed. The results revealed that the highest biogas production from P. australis was achieved at particle size < 1 mm (27.97 ± 0.07 and 16.67 ± 0.09 mL/g VS added, for pre-treated and untreated P. australis respectively); 2% and 4% NaOH concentration for pre-treatment (70.01 ± 3.75 and 76.14 ± 2.62 mL/g VS added, respectively); pre-treatment incubation time of 72, 96, and 120 h (71.18 ± 1.79, 72.46 ± 1.08, and 73.78 ± 1.87 mL/g VS added, respectively); and ISR of 1:2 for pre-treated P. australis (78.21 ± 0.36 mL/g VS added) and ISR 1:4 for untreated P. australis (28.93 ± 1.55 mL/g VS added). Determining optimal parameters in this work would guide further development of process configurations, such as continuous AD systems.

The specific objective of this study is to find a suitable artificial neural network model for estimating the operation indicators (disturbed soil volume, effective field capacity, draft force, and energy requirement) of ploughing units (tractor disc) in various soil conditions. The experiment involved two different factors, i.e., (Ι) soil texture index and (ΙΙ) field work index, and included soil moisture content, tractor engine power, soil bulk density, tillage speed, tillage depth, and tillage width, which were linked to one dimensionless index. We assessed the effectiveness of artificial neural network and multiple linear regression models between the values predicted and the actual values using the mean absolute error criterion to test data points. When the artificial neural network model was applied, the mean absolute error values for disturbed soil volume, effective field capacity, draft force, and energy requirement were 69.41 m ³ ·hr ⁻¹ , 0.04 ha·hr ⁻¹ , 1.24 kN, and 1.95 kw·hr·ha ⁻¹ , respectively. In order to evaluate the behaviour of new models, the coefficient R ² was used as a criterion, where R ² values in artificial neural network were 0.9872, 0.9553, 0.9948, and 0.9718, respectively, for the aforementioned testing dataset. Simultaneously, R ² values in multiple linear regression were 0.7623, 0.696, 0.492, and 0.5572, respectively, for the same testing dataset. Based on these comparisons, it was clear that predictions using the artificial neural network models proposed are very satisfactory.

The congestion problem has driven many researchers to address it, among other networking issues. In a packet-switched network, congestion is essential; it leads to a high response time to deliver packets due to heavy traffic, which eventually causes packet loss. Hence, congestion control mechanisms are utilized to prevent such cases. Several interesting algorithms are proposed to focus on this dilemma, such as the Self-Clocked Rate Adaptation for Multimedia (SCReAM) designed for interactive real-time video streaming applications. One of the main issues of SCReAM is the high design complexity due to the large size of its documentation and coding. Furthermore, there is a considerable number of parameters that can be adjusted to accomplish the desired performance. This study proposes a guided parameters’ tuning approach to assess and optimize the SCReAM algorithm in an emulated 5G environment through a detailed exploration of its parameters. The proposed approach consists of three phases, namely, the initialization phase, the standalone experimentation phase, and the hybrid experimentation phase. In the first phase, we illustrate the method of initializing and implementing the environment, followed by specifying the investigated parameters’ settings, testing, and validation. The second phase aims to investigate SCReAM parameters in isolation to identify the effect on the performance in relation to network queue delay, smoothed Round Trip Time (sRTT), and throughput. The final phase discusses the possibility of achieving the optimum performance by combining various sets to provide researchers with clear and explicit guidelines to establish an adequate SCReAM behavior for the desired application. To the best of our knowledge, this is the first study that proposes a preliminary and comprehensive analysis of the SCReAM algorithm. Based on the proposed approach, when L4S/ECN is disabled, we reduced the network queue delay by 63.36% and increased the network throughput by 48.6% as compared to the results generated by the original design. In L4S/ECN-enabled mode, the network queue delay is reduced by 16.17% while the network throughput increased by 93%.

Background This study measured fluoride release from a light-cured orthodontic adhesive resin (Vega type) at three time intervals (one day, one week, and one month), investigated the rechargeability of the resin, and assessed its impact on shear bond strength in demineralized tooth surfaces. Methods This study used 30 recently extracted upper premolar teeth to explore the effects of fluoride release over specific time intervals. The teeth underwent demineralization and were categorized into groups based on time intervals: one day, one week, and one month. Subgroups within each interval underwent fluoride recharging through fluoride varnish application. Fluoride release and shear bond strength were assessed after etching with phosphoric acid gel, applying the orthodontic adhesive, and curing. The samples were stored in deionized water. Fluoride quantification used a selective electrode, while shear bond strength assessment employed a universal testing machine. Finally, statistical analysis of the data was performed using SPSS 22. Results The study found that after one month, the adhesive had the highest fluoride release and shear bond strength mean values. There were significant differences in fluoride release and shear bond strength between the various groups studied. Conclusion The application of fluoride varnish around the orthodontic bracket resulted in a positive effect on the shear bond strength of the bracket.

The Sumudu transform is presented in this paper in a modified form which is aimed at improving its performance and employing it along with a modified iteration method in order to determine the solution to a system of nonlinear partial differential equations. This includes a theoretical analysis of the associated modified Sumudu transform. It also includes an explanation of the mathematical method for utilizing the transform in conjunction with the modified iteration technique. The iteration method is employed to determine the nonlinear terms of the equations. The research is valuable in the sense that it allows approximate and exact solution configurations to be determined by combining the modified Sumudu transform with a modified iteration method. As another benefit, the modified Sumudu transform can be developed and enhanced to be applicable to a wide range of equations, making it an effective solution tool. By combining techniques, a final advantage is that the solutions can be derived quickly and easily as a result of the combined approach. Finally, an old transformation which has been modified from the Sumudu transform is combined with the modified iteration method to examine its capability of yielding convergent solutions by incorporating the modified iteration method into it.

This chapter provides critical details on the anatomy of the fourth ventricle, encompassing its boundaries and the structures in its vicinity.

The increasing levels of carbon dioxide (CO2) in the atmosphere may dissolve into the ocean and affect the marine ecosystem. It is crucial to determine the level of dissolved CO2 in the ocean to enable suitable mitigation actions to be carried out. The conventional electrode materials are expensive and susceptible to chloride ion attack. Therefore, there is a need to find suitable alternative materials. This novel study investigates the electrochemical behaviour of dissolved CO2 on roughened molybdenum (Mo) microdisk electrodes, which were mechanically polished using silicon carbide paper. Pits and dents can be seen on the electrode surface as observed using scanning electron microscopy. X-ray diffraction spectra confirm the absence of abrasive materials and the presence of defects on the electrode surface. The electrochemical surface for the roughened electrodes is higher than that for the smoothened electrodes. Our findings show that the roughened electrodes exhibit a significantly higher electrocatalytic activity than the smoothened electrodes for the reduction of dissolved CO2. Our results reveal a linear relationship between the current and square root of scan rate. Furthermore, we demonstrate that saturating the electrolyte solution with CO2 using a bubbling time of just 20 minutes at a flow rate of 5 L min⁻¹ for a 50 mL solution is sufficient. This study provides new insights into the electrochemical behaviour of dissolved CO2 on roughened Mo microdisk electrodes and highlights their potential as a promising material for CO2 reduction and other electrochemical applications. Ultimately, our work contributes to the ongoing efforts to mitigate the effects of climate change and move towards a sustainable future.

Any solid, unprotected, and undefended surface in the aquatic environment will be fouled. Fouling, on the other hand, can affect a wide range of species that can tolerate some epibiosis. Several others, on the other hand, aggressively keep the epibionts off their body surface (antifouling). Antifouling defenses are built into marine plants like seaweed and seagrass. They do have a distinctive surface structure with tightly packed needle-like peaks and antifouling coverings, which may hinder settling bacteria's ability to cling. Chemical antifouling resistance is most probably a biological reaction to epibiosis' ecological drawbacks, especially for organisms capable of performing photosynthesis. The goal of this study was to see how effective natural compounds derived from littoral seaweeds were in preventing fouling. The brown mussel, an important fouling organism, was evaluated in laboratory bioassays against fifty-one populations' crude organic extracts including fort-two macroalgae species. Antifouling activity, exhibited a distinct phylogenetic pattern, with red macroalgae having the largest share of active species, subsequently brown macroalgae. Antifouling action in green seaweeds has never been significant. Seven species showed some level of induced antifouling defense. Our findings appear to back up previous findings about secondary metabolite synthesis in seaweeds, indicating that in the hunt for novel antifoulants, researchers should concentrate their efforts on tropical red macroalgae.

Background Borrelia burgdorferi is a Gram-negative bacterium that causes Lyme disease or borreliosis in domestic and wild animals, including dogs, with the possible transmission to humans. Aim This study was conducted to investigate the infection rate of Spirochetes and B. burgdorferi in stray dogs in Nineveh province, Iraq. Methods During the period from May to October (2022), a total of 55 stray dogs were selected randomly from different areas in Nineveh province, Iraq. Blood samples were collected from cephalic venous and tested molecularly using the conventional polymerase chain reaction technique. Results The present study revealed that the total infection rates of Spirochetes and B. burgdorferi were 41.82% and 27.27%, respectively. Concerning age, values of infection rate, odds ratio, and relative risk of B. burgdorferi were increased significantly in dogs aged ? 4 months (42.86%, 3.505%, and 2.438%, respectively), while decreased in dogs of ? 1–3 (12.5%, 0.337% and 0.42%, respectively) and ? 3 (13.33%, 0.32% and 0.409%) years old when compared to dogs aged 5–12 months (27.27%, 1% and 1%, respectively). While concerning dogs sex, a significantly higher infection rate, odds ratio, and relative risk of B. burgdorferi were shown in females (32.56%, 5.495% and 6.792%, respectively) compared to males (8.33%, 0.182% and 0.147%, respectively). Conclusion To the best of our knowledge, this represents the first Iraqi study on the prevalence of spirochetes, in particular B. burgdorferi, in stray dogs in Nineveh province (Iraq). However, additional studies of B. burgdorferi infection in other animals as well as vectors such as ticks in different geographic areas, appear necessary to detect variation in the distribution patterns of infection. In addition, owners and veterinarians should be aware of zoonotic diseases transmitted from wild and domestic animals, in particular those with tick-bite histories.

In this work, fatty alcohol ethoxylation surfactant PALMEROL 1214 (lauryl myristyl alcohol C 12 –C 14 ) designated as LMA-EO-30 and novel surface-active monomer (surfethoxymers) such as Hemi Ester Lauryl Myristyl Alcohol Malate designated as HELMEM, HELMEI (itaconate) and HELMES (succinate) have been synthesized. These types of non-ionic surfactant have been characterized for their structures using spectroscopic measurements. In addition, their surface-active properties like surface tension, critical micelle concentration (CMC), HLB, the cloud point and foaming properties were investigated. The results indicated that the novel surfethoxymers HELMEM, HELMEI and HELMES exhibit an excellent surface activity and a high performance in the mentioned industrial applications.

This study focused on determining the effect of the inoculum to substrate ratio (ISR) on biogas production efficiency from the anaerobic co-digestion of two substrates: synthetic food waste and common reeds (Phragmites australis) that were ground and pre-treated using sodium hydroxide at a concentration of 2% to increase access to their cellulose. It also studied the role of different mixing ratios of the two substrates in improving the stability of the digestion process and increasing biogas production. A series of batch tests were carried out under mesophilic conditions using three ratios of ISR: 1:4, 1:2, and 1:1, and five substrate mixing ratios (synthetic food waste: pre-treated P. australis): 25:75, 50:50, 75:25, 100:0, and 0:100. The results showed low biogas production at the ISR 1:4 (21.58±0.00–44.46±0.01 mL/g volatile solid (VS) added), and the reactors suffered from acidification at the different substrates mixing ratios, while the biogas production increased at an ISR of 1:2, where the reactors with the substrate mixing ratio of 25:75 presented the highest biogas production (82.17±0.62 mL/g VS added), and the digestion process was stable. However, the reactors with substrate mixing ratios of 50:50, 75:25, and 100:0 suffered from acidification effects at this ISR. In contrast, at ISR of 1:1, the reactors did not expose to acidification inhibition at all the substrates mixing ratios, and the highest biogas production was found at synthetic food waste: pre-treated P. australis mixing ratios of 75:25 and 100:0 (76.15±1.85 and 82.47±1.85 mL/g VS added, respectively).

Deep learning algorithms, especially Convolution Neural Networks (CNN), have been rapidly developed due to their flexibility and scalability to be adopted in several fields for modeling real-world applications like object detection, image classification, etc. However, their high accuracy incurs intensive computations. Therefore, it is crucial to carefully choose a suitable computer platform and implementation methodology for CNN network architectures while achieving increased efficiency. Parallel architectures are prevalent in CNN implementation. Herein, we present a new Single Instruction Multi Data (SIMD) parallel implementation of the proposed CNN to speed up the execution process and make it suitable to deploy on low-cost, low-power consumption platforms. The proposed implementation produces an improved model of deep CNN executable on a cost-efficient platform and portability to work autonomously with multi-core processing units while maintaining working accuracy. Raspberry Pi 3 B is a low-power target device for implementing our model. The proposed approach is characterized by high diagnostic accuracy of up to 96.35 % while incurring power consumption of 3.65 Watts, achieving power reduction between 19.17 % and 68.45 % compared to the prior work. Meanwhile, it has a fine inference time for the selected platform. The outstanding results of this study reflect the success of employing parallel architectures to utilize the quad courses of the ARM processor on the target platform. The presented model can be an efficient medical assistant to provide automated detection and diagnosis for myopia ocular disease. Thus, it can be a promising healthcare toolkit that reduces the effort of the medical staff and increases the quality of the provided medical services for myopia patients

Background Human papillomavirus (HPV) is considered to be responsible for 95% of virus-related cancers in many organs. Oropharyngeal carcinoma (OC) is distinguished by the transformation of the healthy epithelium into precancerous cells. Aim The current study sought to examine the uneven gene expression of 20 genes among those scanned by microarray for oropharyngeal cancer patients. Materials and Methods The GSE56142 dataset was extracted from the Gene Expression Omnibus of the National Center for Biotechnology Information; 24 specimens were evaluated. Gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes, and the protein–protein interaction (PPI) were used to depict the biological roles of the genes under investigation using types of software. Results Six genes out of 20 in patients with invasive OC had a binding correlation with high expression (PDGFRS, COL6A3, COL1A1, COL3A1, COL2A1, and COL4A1), and only two genes with low expression (CRCT1 and KRT78). The expression levels of 20 genes were examined for patients with OC versus head and neck squamous cell carcinoma (HNSCC). The correlation coefficient between highly expressed genes of the OC group was statistically significant at the P<0.05 level. Conclusions High expression levels of specific genes may serve as diagnostic tumor markers, particularly in the early stages of cancer, and testing should be performed in OC and HNSCC patients.