Al Rafidain University College

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.

Fluid flow applications to improve water resource management towards sustainable irrigation are one of the main targets of engineers nowadays, especially with global climate change. The performance assessment of the irrigation system is an important area of research to improve water resource management. Through drip irrigation systems, this review evaluated the application uniformity of water and nutrients to sustain agricultural production and protect the environment’s natural resources. To achieve these goals, the adequate use of nutrients and water must be emphasized by utilizing sufficient water and nutrient management approaches, including a drip irrigation system that supplies the inputs immediately to the crop’s root zone. The process operating pressure and the drip line length are the two most crucial aspects that affect the uniformity of the water and nutrient distribution in fields. Inconsistent or inadequate applications of fertilizers and water in the fields contribute to the incorrect supply of useful water and nutrients in the soil profile along the drip line length resulting in a significant decrease in crop yields and poor product quality. The main cause behind the operating pressures in a “micro-irrigation system” is the inadequate distribution of fertilizers and water in the fields. Therefore, the effects of such non-uniform distribution must be carefully quantified and studied to understand the reasons behind soil degradation and groundwater contamination, which occurs due to excess nutrient leaching from the crop’s root zone. Data on the distribution and movement of water and nutrients in the soil is essential for designing efficient fertilization systems. Drip irrigation can reduce water exposure and input costs, making agribusiness more resilient, profitable, and successful. This paper discusses the uniformity of the nutrients and water application for crops grown in various agro-climatic regions. In addition, an effort was made to compare the findings’ quality of various commonly used methods of water and nutrient application under different climatic conditions.

It has been proven that mechanical elements display size-dependent behavior in structural and thermal fields at microscales. It has also been found that thermoelastic damping (TED) is one of the dominant reasons in confining the quality factor (Q-factor) of such elements. This paper aims to develop a novel formulation for evaluating TED in microbeams by accounting for the size effect on the mechanical and thermal areas via the nonclassical theory of modified strain gradient (MSG) and the non-Fourier heat conduction model of Moore-Gibson-Thompson (MGT). In the first step, the heat equation for beams is derived within the framework of MGT model. Through this equation, the function of temperature fluctuation can be obtained. Then, the constitutive relations of the beam according to MSG theory (MSGT) are extracted. By using the temperature distribution and nonclassical constitutive relations obtained, the maximum amounts of potential and wasted thermal energies during one cycle of beam vibration are calculated. Finally, by placing the value of these energies in the existing relationship for computing the value of TED, an explicit expression for TED is presented. With the aim of clarifying the sensitivity of TED value to the characteristic parameters of MSGT and MGT model, a variety of numerical data are provided. According to the obtained outcomes, the inclusion of size effect in the structural and thermal equations can cause a remarkable difference compared to the classical model. The dependency of TED on some factors like beam thickness and aspect ratio, vibration mode number and material of the beam is also investigated numerically.

Numerous techniques have been proposed in the literature to improve the performance of high-gain observers with noisy measurements. One such technique is the linear extended state observer, which is used to estimate the system's states and to account for the impact of internal uncertainties, undesirable nonlin-earities, and external disturbances. This observer's primary purpose is to eliminate these disturbances from the input channel in real-time. This enables the observer to precisely track the system states while compensating for the various sources of uncertainty that can influence the system's behaviour. So, in this paper, a novel nonlinear higher-order extended state observer (NHOESO) is introduced to enhance the performance of high-gain observers under noisy measurement conditions. The NHOESO is designed to observe the system states and total disturbance while eliminating the latter in real time from the input channel. It is capable of handling disturbances of higher-order derivatives, including internal uncertainties, undesirable nonlinearities, and external disturbances. The paper also presents two innovative schemes for parametrizing the NHOESO parameters in the presence of measurement noise. These schemes are named time-varying bandwidth NHOESO (TVB-NHOESO) and online adaptive rule update NHOESO (OARU-NHOESO). Numerical simulations are conducted to validate the effectiveness of the proposed schemes, using a nonlinear uncertain system as a test case. The results demonstrate that the OARU technique outperforms the TVB technique in terms of its ability to sense the presence of noise components in the output and respond accordingly. However, it is noted that the OARU technique is slower than the TVB technique and requires more complex parameter tuning to adaptively account for the measurement noise.

Aim Using data from the Global Burden of Disease (GBD) research from 1990 to 2019, this study intends to examine the prevalence of mental health problems related to COVID-19 in the Central Asia. Anxiety, depression, and post-traumatic stress disorder (PTSD) are the primary study topics. Materials and Methods The prevalence of different mental health diseases was investigated by means of a meta-analysis and comprehensive literature review. For each nation, we calculated the age-standardized prevalence rate and the DALYs lost due to impairment. The research also looked at what factors could be at play, such as demographics, income, and the structure of the healthcare system. Results During and after the COVID-19 pandemic, there was a 32% rise in mental health issues in the Central Asia, with wide variations across nations. Socioeconomic inequalities, demographic changes, and the constraints of the healthcare system have all been identified as major contributors to the rising prevalence of mental health problems. Conclusion To combat the potentially catastrophic effects of the COVID-19 pandemic, the study's key results highlight the critical need of developing comprehensive mental health policies and treatments in the Central Asia. Improving the availability of mental health treatment, addressing the underlying socioeconomic and demographic causes, and adapting interventions to the unique requirements of each nation are all essential in tackling this serious problem. This study aids in clarifying the state of mental health in the Central Asia and guiding policymaking to lessen the impact on mental health of the current COVID-19 epidemic.

Although the autograft is regarded as the gold standard bone graft, β-TCP artificial alloplastic is widely used in bone defect healing and has been accepted in human and animal studies to be resorbed and interchanged by vital bone. The active form of vitamin D3 is calcitriol, on mesenchymal stem cells (MSCs) it has a direct influence on encouraging their osteogenic differentiation which is identified as osteoinductive. The need for osteoinductive ability is a demanding issue regarding medical and dental care. RUNX2 regards an essential transcriptional factor for osteoblast differentiation. Adult male New Zealand rabbits (Twenty-four) with an average weight of (1.5-2 kg) were elected in this study. Four holes were made intra-bone in both tibias of each animal. The experimental groups divide as follows: Group C: Bone defect will be left to heal naturally as control; Group TCP: Bone defect will be occupied with β-TCP. Group vitamin D3: Bone defect will be filled with vitamin D3; Group TCPD: Bone defect will be filled with a combination of β-TCP and vitamin D3. Animals sacrificed at (1 and 3 weeks). Purification of total RNA from formalin fixed paraffin embedded (FFPE), The cDNA of RUNX2 and VDR amplify in RT-PCR and detected with sybr green. One-way Analysis of Variance (ANOVA) and least significant difference (LSD) was used as a tool for statistical analysis. Results at 7 days highest mean value of mRNA RUNX2 gene expression Fold Change estimated in TCP followed by TCPD experimental group while at 21 days, the highest mean value in TCPD. All measured parameters showed highly significant differences in the course of healing periods from 7 days to 21 days. In mRNA VDR gene expression parameters showed a highly significant difference in 7days and 21 days durations among experimental groups and the highest mean value of mRNA VDR gene expression Fold Change is recorded in TCPD followed by vitamin D3 groups in both durations. These findings suggest positive inductive effects of local application of vitamin D3 combined with β-TCP as well as vitamin D3 on osteoblast cells and induced bone defect healing.

The study of anaemia is a well-developed discipline where the concepts of precision medicine have, in part, been researched extensively. This review discusses the treatment of erythropoietin (EPO) deficiency anaemia and resistance in cases of chronic kidney disease (CKD). Traditionally, erythropoietin-stimulating agents (ESAs) and iron supplementation have been used to manage anaemia in cases of CKD. However, these treatments pose potential risks, including cardiovascular and thromboembolic events. Newer treatments have emerged to address these risks, such as slow-release and low-dosage intravenous iron, oral iron supplementation, and erythropoietin–iron combination therapy. Another novel approach is the use of hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs). This review highlights the need for precision medicine targeting the genetic components of EPO deficiency anaemia in CKD and discusses individual variability in genes such as the erythropoietin gene (EPO), the interleukin-β gene (IL-β), and the hypoxia-inducible factor gene (HIF). Pharmacogenetic testing aims to provide targeted therapies and interventions that are tailored to the specific characteristics of an individual, thus optimising treatment outcomes and minimising resistance and adverse effects. This article concludes by suggesting that receptor modification has the potential to revolutionise the treatment outcomes of patients with erythropoietin deficiency anaemia through the integration of the mentioned approach.

Cancer is a genetic and complex disorder, resulting from several events associated with onset, development, and metastasis. Tumor suppressors and oncogenes are among the main regulators of tumor progression, contributing to various cancer-related behaviors like cell proliferation, invasion, migration, epithelial-mesenchymal transition (EMT), cell cycle, and apoptosis. Transcription factors (TFs) could act as tumor suppressors or oncogenes in cancer progression. E-twenty-six/E26 (ETS) family of TFs have a winged helix-turn-helix (HLH) motif, which interacted with specific DNA regions with high levels of purines and GGA core. ETS proteins act as transcriptional repressors or activators to modulate the expression of target genes. ETS transcription factor ELK3 (ELK3), as a type of ETS protein, was shown to enhance in various cancers, suggesting that it may have an oncogenic role. These studies indicated that ELK3 promoted invasion, migration, cell cycle, proliferation, and EMT, and suppressed cell apoptosis. In addition, these studies demonstrated that ELK3 could be a promising diagnostic and prognostic biomarker in human cancer. Moreover, accumulating data proved that ELK3 could be a novel chemoresistance mediator in human cancer. Here, we aimed to explore the overall change of ELK3 and its underlying molecular mechanism in human cancers. Moreover, we aimed to investigate the potential role of ELK3 as a prognostic and diagnostic biomarker as well as its capability as a chemoresistance mediator in cancer.

Background: As the largest demographic group utilizing primary healthcare facilities, older adults often face the challenge of managing multiple chronic illnesses, leading to numerous medications. Objective: The present study aims to assess medication use problems among older adults and explore the factors affecting them in primary healthcare settings. Methods: A mixed-method study was conducted to establish a baseline understanding of the perspectives and challenges faced by older adults, with regards to medication use. Translated Medication Use Questionnaire (MedUseQ), a patient-centered tool, was distributed to older adults above 60 in primary healthcare settings to assess their frequency of problems related to medication use. Fifteen semi-structured interviews were conducted to explore this topic in depth. Descriptive and inferential analyses were conducted with quantitative data. Interviews were transcribed verbatim, and thematic analysis was conducted. Quantitative and qualitative findings data were triangulated. Results: The study involved 393 participants. The most common problems with regards to medication use were polypharmacy (55.4%), administration difficulties (48.4%), limited awareness about adverse drug events (47.3%), issues with adherence (46.5%), and accessibility to primary healthcare (42.7%). Approximately 55% were satisfied with the older adult-centered medication use services by pharmacist and doctors. The qualitative findings showed that major factors affecting medication use were forgetfulness, language barriers, lack of awareness, transportation problems, long waiting times, and multiple visits to healthcare facilities. Conclusion: The findings of this study reveal that a significant proportion, around 50%, of the older adult population face challenges with medication use in Penang. These difficulties mainly stem from medication administration, adherence, accessibility, polypharmacy, and inadequate medication knowledge. The qualitative analysis further highlighted several factors that contribute to such medication-related problems. Given the rapidly aging Association of Southeast Asian Nations (ASEAN) population, it is essential to devise effective solutions and strategies to tackle medication use-related issues among older adults.

Veterinary pharmaceuticals have been recently recognized as newly emerging environmental contaminants. Indeed, because of their uncontrolled or overused disposal, we are now facing undesirable amounts of these constituents in foodstuff and its related human health concerns. In this context, developing a well-organized environmental and foodstuff screening toward antibiotic levels is of paramount importance to ensure the safety of food products as well as human health. In this case, with the development and progress of electric/photo detecting, nanomaterials, and nucleic acid aptamer technology, their incorporation-driven evolving electrochemiluminescence aptasensing strategy has presented the hopeful potentials in identifying the residual amounts of different antibiotics toward sensitivity, economy, and practicality. In this context, we reviewed the up-to-date development of ECL aptasensors with aptamers as recognition elements and nanomaterials as the active elements for quantitative sensing the residual antibiotics in foodstuff and agriculture-related matrices, dissected the unavoidable challenges, and debated the upcoming prospects.

This study investigates the effect of health risk factors on apical periodontitis in fitted endodontically and non-endodontically treated teeth in army soldiers (environmental risk factor) and diabetic patients (biomedical risk factor). This cross-sectional study included patients aged 25–40 years. After participants were filtered based on exclusion criteria and questionnaire (DASS-21) responses, 108 males were chosen and divided into three groups of 36 participants each (G1: soldiers, G2: diabetic, G3: healthy). The periapical status of the participants’ teeth according to OPG X-ray outcomes was independently evaluated using a periapical index. The healthy group showed a higher ratio of fitted teeth to both non-endodontically and endodontically treated teeth (98.8%,70%) than diabetic patients (98.6%,52.1%) and soldiers (95.6%,35.3%). Meanwhile, soldiers showed higher apical defects of both non-endodontically and endodontically treated teeth (7.8%,33.3%) than diabetic patients (6.4%,12%) and healthy individuals (5.7%,7.1%). There was a statistically non-significant relationship between being healthy and experiencing apical defects for all fitted non-endodontically and endodontically treated teeth among all groups. The higher prevalence of apical periodontitis in soldiers and diabetic patients suggests a positive relationship between worsened apical area of teeth and health risk factors, such as diabetes mellitus disease and environmental stress.

Human regulatory T cells (Tregs) are essential in pathogenesis of several diseases such as autoimmune diseases and cancers, and their imbalances may be promoting factor in these disorders. The development of the proinflammatory T cell subset TH17 and its balance with the generation of regulatory T cells (Treg) is linked to autoimmune disease and cancers. Long non-coding RNAs (lncRNAs) have recently emerged as powerful regulatory molecules in a variety of diseases and can regulate the expression of significant genes at multiple levels through epigenetic regulation and by modulating transcription, post-transcriptional processes, translation, and protein modification. They may interact with a wide range of molecules, including DNA, RNA, and proteins, and have a complex structural makeup. LncRNAs are implicated in a range of illnesses due to their regulatory impact on a variety of biological processes such as cell proliferation, apoptosis, and differentiation. In this regard, a prominent example is lncRNA NEAT1 which several studies have performed to determine its role in the differentiation of immune cells. Many other lncRNAs have been linked to Treg cell differentiation in the context of immune cell differentiation. In this study, we review recent research on the various roles of lncRNAs in differentiation of Treg cell and regulation of the Th17/Treg balance in autoimmune diseases and tumors in which T regs play an important role.

Natural fibres (NFRs) composite materials are acquiring popularity in the modern world due to their eco-friendliness and superior mechanical properties. Although it has been shown that determining this is a herculean endeavour in the literature, the water absorption (WA) qualities of the natural fibre (NFR) are crucial in the progressive degradation of the features of the resulting composites. This article seeks to report exhaustively on studies pertaining to the WA attributes of polymer composites reinforced with NFRs. This article provides an overview of NFR, its characterization, and the issues related to its addition to the matrix. The primary purpose of this research study is to investigate existing studies on the problems associated with the creation of cellulosic fibre hybrid composites, water absorption, and its impact on the tensile (TS), flexural (FS), and impact strength (IS) of NFR reinforced composites. We reviewed various surface treatments (ST) applied to NFR, including alkali treatment, silane treatment, acetylation, as well as recent advancements aimed at mitigating WA, enhancing hydrophobicity, and improving the interfacial bonding (IB) between NFR and the polymer matrix (PM). Additionally, we assessed the effectiveness of utilizing nanoparticles (NAPs) in specific ST of NFR to minimize water absorption.

In order to increase the robustness of natural fiber (NFR), hybridization with synthetic fibers is crucial. The widespread usage of hybrid composites (HCs) in modern structural applications reflects their increasing popularity. When compared to non-hybrid composites, hybridization offers additional advantages due to its combination of inexpensive, high-quality fibers that enhance the properties of a composite without a significant increase in cost. Although the mechanical properties (MP) of various HCs have not yet been explored in depth, it is one of the benefits brought by hybridization. This article reviews and analyzes the latest information on the MP of HCs composed of synthetic and natural fibers. It also conducts a critical analysis of the important information that can be gleaned from published research on the factors that influence the morphological characteristics, physical-mechanical attributes, benefits, and challenges associated with NFR-reinforced composites. As a result, this compilation provides an in-depth critical analysis of innovative treatment techniques that are suitable for enhancing interfacial bonding (IB) between NF and polymer matrix (PM) and their MP. Additionally, each category of HCs, including thermoset and thermoplastic polymers as well as bionanocomposites, is discussed. Overall, this comprehensive study demonstrates that lignocellulosic fibers are widely employed in composite reinforcement and confirms that the hybridization of various reinforcing fibers has synergistic impacts on the mechanical properties of HCs.

In order to speed up convolutional neural networks (CNNs), this study gives a complete overview of the use of FPGA-based pipelining for hardware acceleration of CNNs. These days, most people use convolutional neural networks (CNNs) to perform computer vision tasks like picture categorization and object recognition. The processing and memory demands of CNNs, however, can be excessive, especially for real-time applications. In order to speed up CNNs, FPGA-based pipelining has emerged as a viable option thanks to its parallel processing capabilities and low power consumption. The examination describes the fundamentals of FPGA-based pipelining and the basic structure of convolutional neural networks (CNNs). The current best practises for developing pipelined accelerators for CNNs on FPGAs are then reviewed, covering topics like partitioning and pipelining. Area and power limits, memory needs, and latency considerations are only some of the difficulties and trade-offs discussed in the article. In addition, the survey evaluates and contrasts the various pipelined FPGA accelerators for CNNs in terms of performance, energy consumption, and resource utilisation. Future directions and potential research areas are also discussed in the paper, such as the use of approximate computing techniques, the integration of reconfigurable architectures with emerging memory technologies, and the exploration of hybrid architectures that combine FPGAs and other hardware accelerators. This survey was created to aid researchers and practitioners in developing efficient and effective hardware accelerators for neural networks by providing a thorough overview of current trends and issues in FPGA-based pipelining for CNNs.

Aims: This scoping review aimed to conduct an assessment of the current literature on specific ecological changes in the oral microbiota of individuals living with cleft lip and/or palate. Methods: All studies that assess oral microbiota and ecological changes distinct of individuals living with cleft lip and/or palate were included. Ovid MEDLINE and EMBASE databases were used, using planned search keywords. Included articles were grouped into cohort, cross-sectional, case-control, and retrospective reviews. Results: A total of 164 eligible title articles were recognized. Of these, 32 full-text studies were included in the present review. All the included articles were published between 1992 and 2022. These studies were two retrospective studies, two review studies, and the remaining (n = 28) were observational studies. Conclusion: The oral flora of cleft lip and/or palate patients has been shown in scientific studies to have an increased frequency of potentially pathogenic fungal and bacterial colonization, particularly Candida species, Staphylococcus aureus, Lactobacili and Streptococci mutans. This may influence oral diseases and post-operative repair complications, potentially necessitating further surgical intervention.

The relevance of the subject is conditioned upon the fact that large park plantations have a great positive impact on the climate of Mediterranean cities, which increases the comfort of living in them. Such weather conditions as abnormal heat are increasingly manifested in Mediterranean cities due to global warming and other causes. In addition, there is air pollution in cities with solid particles and other impurities harmful to human health. The analysis of scientific literature has demonstrated that in the cities of the Mediterranean, these problems can be solved through urban park plantings and other types of landscaping. The purpose of this study is to assess the effectiveness of the costs of maintaining large urban park spaces in Barcelona. The leading method to explore this problem is the empirical method, namely, the study of urban landscaping programmes and budget expenditures. The research examines the sources of financing the costs of maintaining urban park spaces and considers urban programmes for the development of landscaping, and their financing. In addition, the influence of green spaces on the comfort of living in the city of Barcelona is explored. As a result of the study, it was found that landscaping in the city of Barcelona is financed for the most part from the city budget, while spending increases annually. It has been identified that the city of Barcelona receives a significant positive effect from investments in green spaces, namely, air pollution decreases, its temperature decreases, people get places for hiking, sports, and other types of activity, the psychological and physiological health of the population improves, the urban environment becomes more comfortable to live in. It is the large park plantings that allow reducing the air temperature, which improves the quality of life in the city

A subset of artificial intelligence (AI) known as "machine learning" (ML) allows computer systems to learn from experience and advance without explicit programming. Environmental DNA (eDNA) metabarcoding is a rapidly expanding scientific method for determining species' existence in the environment. It includes sequencing DNA from environmental samples. This work investigates how machine learning (ML) could be used in eDNA metabarcoding to enhance biodiversity estimates. Reviewing current work on the use of ML in eDNA metabarcoding, this paper focuses on the various ML algorithms utilized, the varied kinds of data inputs, and the advances in biodiversity assessment that occur. In 23 investigations, machine learning (ML) was used for Environmental DNA (eDNA) metabarcoding. In terms of increasing the precision and effectiveness of eDNA metabarcoding for biodiversity assessments, ML has shown encouraging outcomes. In addition to accurately classifying and predicting species from eDNA sequences, ML algorithms may uncover uncommon or invasive species often overlooked by conventional techniques. According to the research we looked at, compared to conventional approaches, there was an average increase of 20% in detection sensitivity and 14% in species richness. Adding ML to eDNA metabarcoding has enormous promise for enhancing ecological monitoring and biodiversity assessments. Nonetheless, it is essential to choose suitable ML algorithms, ensure there are enough training datasets, and assess the accuracy of the predictions made by ML. This research underscores the need for more investigation to fully fulfill ML's potential for ecological monitoring and conservation while providing a thorough review of its possible uses in eDNA metabarcoding.