The generalized q-operator rɸs and its applications in q-identities

Based on the basic hypergeometric series rφs, we construct a new generalized q-operator rɸs (a1, . . . , ar b1, . . . , bs ; q, −cθ) and obtain some of its identities. Using these identities, we generalize several well-known q-identities, such as the q-Gauss sum, the q-Chu-Vandermonde sum, and the q-Pffaf-Saalschütz sum.Publisher's Versio

Determining Self-Efficacy and Its Related Factors in Adolescents with Major β-Thalassemia Referring to Selected Hospital in Tehran

AbstractIntroduction: Major β-Thalassemia is one of the most common hereditary anemias in the world and is a health problem associated with the absence or reduction of globin chain production. Self-efficacy helps adolescents with chronic illness to strength their ability to handle the routine tasks and to achieve treatment goals. Because of the importance Major β-Thalassemia in adolescents and its effects on their quality of life, we decided to do this study with the aim of “Determining self-efficacy and its related factors in adolescents Major β-Thalassemia referring to selected hospital in Tehran”.Methods: The present study used a descriptive comparative cross-sectional design on 100 adolescents with Major β-Thalassemia referring to Shohadaye Tajrish hospital in Tehran in 2022. We used a census design to collect data in a fixed duration and in three work shifts in the morning, evening and night in the relevant units. The data collection tools included of demographic and Self-Efficacy Questionnaire for Children (SEQ-C). The collected data were analysed by SPSS Software version 20 via statistical tests included of Pearson or Spearman coefficient, t test and ANOVA test.Results: The average age of the participant adolescents were 15.40 ± 2.22. The results of the study showed that the mean score of academic, social and emotional self-efficacy were 26.17±3.91, 24.83±5.33 and 24.49±4.75 respectively. The score of self-efficacy of the participants were approximately in the average range in the three dimensions of the SEQ-C. However, the score of academic self-efficacy was slightly higher than the average range. There are not any significant relationships between the demographic variables and any dimensions of self-efficacy (P-value>0.05). However, the results of T-Test showed significant relationships between the social self-efficacy score and positive history of splenectomy (P-value=0.018).Conclusions: Based on the results of the study, the self-efficacy score of participants in this study were approximately in the average range, therefore, these results showed that, health staffs such as nurses should promote the self-efficacy of adolescents with Major β-Thalassemia through health education

Effect of Body Weight on Pattern of Coronary Lesions in Patients Undergoing Coronary Angiography at Sohag University Hospital

Background: Obesity is related to multiple risk factors of cardiovascular disease (CVD) including hypertension, diabetes mellitus (DM), metabolic syndrome, and dyslipidemia, while also likely being an independent risk factor for CVD. Through multiple pathways including increased angiotensin, circulating blood volume, and total peripheral resistance, excess weight increases hypertension (HTN) risk.Objective: This study aimed to reveal the relationship between body weight and the severity of coronary artery disease (CAD) in patients referred for coronary angiography at Sohag University Hospital.Patients and methods: This was a cross-sectional hospital-based study performed on 200 patients, at Sohag University Hospital. Mean age was 56.94 ± 10.30 years. Among them, there were 175 patients (87.5%) who were overweight or obese with higher prevalence of HTN, hyperlipidemia, and diabetes. Normal weight patients were 25 (12.5%) with lower prevalence of HTN, hyperlipidemia, and diabetes.Results: According to BMI in our study, 175 patients (87.5 %) were overweight or obese, 162 patients (92.57%) of the overweight had significant coronary artery disease. 162 patients (81%) had significant coronary angiography findings (> 70% stenosis in any of the coronary arteries). They were classified to 63 patients (31.5%) had single vessel diseased, 53 patients (26.5%) had two vessels diseased, and 46 patients (23%) had three vessels diseased.Conclusion: Obesity, diabetes, hypertension, hyperlipidemia, aging and male gender were correlated with severity of CAD. Thus, reduction of weight, stoppage of smoking and control of diabetes, hypertension and hyperlipidemia will improve outcome of coronary artery disease

Machine Learning Algorithms in Analysis, Diagnosing and Predicting COVID-19: A Systematic Literature Review

Since the COVID-19 corona virus first appeared at the end of 2019, in Wuhan province, China, the analysis, diagnosis, and prognosis of COVID-19 (SARS-CoV-2) has attracted the greatest attention. Since then, every part of the world needs some sort of system or instrument to assist judgments for prompt quarantine and medical treatment. For a variety of uses, including prediction, classification, and analysis, machine learning (MLR) have demonstrated their accuracy and efficiency in the fields of education, health, and security. In this paper, three main questions will be answered related to COVID-19 analysis, predicting, and diagnosing. The performance evaluation, fast process and identification, quick learning, and accurate results of MLR algorithms make them as a base for all models in analyzing, diagnosing, and predicting COVID-19 infection. The impact of using supervised and unsupervised MLR can be used for estimating the spread level of COVID-19 to make the proper strategic decisions. The researchers next compared the effects of various datatypes on diagnosing, forecasting, and assessing the severity of COVID-19 infection in order to examine the effects of MLRs. Three fields are associated with COVID-19, according to the analysis of the chosen study (analysis, diagnosing, and predicting). The majority of researches focus on the subject of COVID-19 diagnosis, where they use their models to identify the infection. In the selected studies, several algorithms are employed, however, a study revealed that the neural network is the most used method when compared to other algorithms. The most used method for identifying, forecasting, and evaluating COVID-19 infection is supervised MLR

The effect of adding natural materials waste on the mechanical properties and water absorption of epoxy composite using grey relations analysis

Recently, there has been a tendency for scientific studies to deal with natural materials as fillers and reinforcement for polymer composites, which are used in many different applications due to their environmentally friendly properties when compared to synthetic materials. The current study aims to preserve the environment by dealing with natural materials and their influence on the mechanical properties and water absorption property of the polymer composites. In this study, epoxy composites were produced from local natural sourced non-hazardous raw natural materials using grey relational analysis (GRG). The materials used for fabrication include micro-filler of pollen palm 50 μm, seashell 75 μm and epoxy resin. Nine different composites were prepared using pollen palm and seashell as reinforcement material by varying the wt % of the micro-filler. Rule of the mixture was used for formulation and wt % of (0.5, 1 and 1.5) % reinforcement and 99.5, 99 and 98.5 % epoxy (binder) were used for composites. Grey relational analysis was conducted in order to scale the multi-response performance to a single response. The results indicate that optimum performance can be achieved with the addition of 1.5 wt % micro-filler of seashell, which achieved the first rank, while the second rank achieved by 0.5 wt % micro-filler of palm pollen and seashell when compared to other composites. The addition of micro-fillers has improved greatly the mechanical properties of epoxy composites. The loading of micro-fillers has influenced the water absorption property of composites based epoxy in ascending orde

Bridging the diagnostic gap: liver function tests and IL-6 as potential early predictors of non-alcoholic fatty liver disease in psoriasis

Background: Psoriasis goes beyond skin, intertwining with body systems, notably connecting to nonalcoholic fatty liver disease (NAFLD). This study aims to explore the predictive potential: liver function tests and IL-6 as early markers for non-alcoholic fatty liver disease in psoriasis patients.  Methods: From March to November 2023, a case-control study was performed at the dermatological outpatient clinic of Baquba Teaching Hospital, Iraq. Individuals with confirmed psoriasis and those without underwent comprehensive clinical history and overall health examinations. The diagnosis of non-alcoholic fatty liver disease (NAFLD) was established using the Fatty Liver Index (FLI). Results: Among the 290 participants in this study, 103 with confirmed psoriasis displayed a Fatty Liver Index (FLI) score >60, indicative of non-alcoholic fatty liver disease (NAFLD). The control group, comprising 101 individuals without psoriasis or NAFLD, provided a baseline for comparison. The mean ages were 32.5 ± 16.2 and 31.5 ± 14.3 years for the case and control groups, respectively. Notably, the case group exhibited significantly higher mean ± SD levels of ALT and AST (61 ± 29 vs. 33 ± 17 U/L, p < 0.0001) and (55 ± 27 vs. 25 ± 15 U/L, p < 0.0001), respectively. Moreover, FLI criteria were markedly elevated in the case group (p = 0.0007, p = 0.0005, p < 0.0001, and p < 0.0001, respectively), and IL-6 levels were significantly higher (p = 0.0003). Conclusion: The results proposed that liver function tests and IL-6 could act as early predictors for the detection of non-alcoholic fatty liver disease among individuals grappling with psoriasis

Squint Among Adult Population in Hail City, Saudi Arabia

Background: Strabismus, also known as crossed eyes, is a condition in which the eyes do not properly align with each other when looking at an object. If present during a large part of childhood, it may result in amblyopia. If onset is during adulthood, it is more likely to result in double vision. Objective: The aim of the study was to estimate the prevalence of squint, types and treatment characteristics in the studied adults in Hail city, Saudi Arabia. Methods: A cross-sectional study conducted in Hail city, Saudi Arabia. The study included 294 participants; 95 male and 199 female adults aged >20 years. The study period was from 1 January to 30 April 2018. Data collected by personal interview using a pre-designed questionnaire, which distributed among the participants to be self-reported. Results: The prevalence of squint among the studied population was 9.9%. it was more common in females than males. Squint was right sided in 24.1% of the cases, left sided in 51.7% and in both eyes in 24.1% of the studied cases. About half (44.8%) of cases had inward squint (esotropia) and 10.3% outward squint (exsotropia), 24.1% of the cases had Intermittent squint and 6.9% had permanent squint. Most (55.2%) of squint cases use glasses and 34.5% of cases squint affected their visual acuity. In 6.9%, squint causes psychological troubles. As regards treatment, 20.7% received medical treatment and 17.2% received surgical treatment but 62.1% do not seek medical care. Only 10.3% of cases completely cured and 13.8% had recurrence. There was insignificant relation with age, sex, education, squint in parents, chronic diseases, consanguinity or hereditary diseases (P>0.05). Conclusion: in this study, the prevalence of squint in the adult participants in Hail city, Saudi Arabia was 9.9% but 62.1% do not seek medical care. After treatment, only 10.3% of cases completely cured and 13.8% had recurrence. Health education of the public about importance of early treatment is highly recommended. Keywords: Squint; strabismus; adult population; prevalence; types; Hail; Saudi Arabia

Quality of Life of Patients with Chronic Kidney Disease

This study aimed at exploring the assessment of Quality of Life (QOL) in patients with Chronic Kidney Disease (CKD), and aiming at assessing the QOL of patients with stages 1–5 Chronic Kidney Disease CKD on conservative treatment in order to identify a possible association between Quality Of Life QOL and progression of kidney insufficiency. The results were compared with those obtained for patients on hemodialysis. Sociodemographic, clinical and laboratory data were also evaluated. And the study concluded that research efforts have expanded significantly to determine the state of pediatric CKD patient HRQOL and the factors that impact HRQOL across all stages of CKD and all modalities of renal replacement therapy. Data from all studies suggest that children with a renal transplant fare better with respect to HRQOL than those receiving dialysis

Visual Twin for Pipeline Leak Detection

We describe a visual digital twin system to allow for both operation and training of a data-driven pipeline leak detection system. We show system design in terms of its data inputs and the software system which incorporates this data in real time. This system allows visualization of pipeline data and machine learning-driven leak detection in a pipeline sitting in a subsea context. The intended purpose of the system is to both train operators of the leak detection system in its use and also provide high situational awareness to those tasked with monitoring pipeline deployments. The visual digital twin system uses gaming engine technology to achieve high visual quality. We also construct a novel software system enhancement to incorporate live data streams into the gaming engine environment. This allows real-time driving of gaming engine visualization elements with which we may augment the gaming engine environment. In terms of visualization, we focus on addressing problems of large ranges of multiple scales and providing high situational awareness which minimize operator fatigue and cognitive load. We show how multiple camera views in combination with a convenient user interface can help to address these issues. We demonstrate a digital twin system for leak detection. We show its realtime operation in a gaming engine environment with the ability to instantaneously incorporate outside data sources into the visualizations. We demonstrate using simulated pipeline flow data from sensors such as pressure, temperature, etc. This is visualized in the context of a subsea pipeline on a sea floor. Given the large range of scales, we demonstrate how we can view both the full kilometer scale pipeline and smaller subsections in the context of specific sensor data streams. The overall system demonstrates a novel combination of advanced software systems which incorporates real-time data stream with visualization using a high-fidelity gaming engine. The data used represents a leak detection scenario where both operator training and situational awareness are key desired outcomes