A Health Needs Assessment of Arab-Americans in the Washington, DC Area

Although Arab-Americans often face various health challenges due to the stress associated with immigration, cultural conflict in the U.S., and limited knowledge of the complex U.S. health system, there is a paucity of research examining health risks and behaviors among this ethnic group. This cross-sectional study assessed the health needs among Arabs living in the Washington, DC metropolitan area. Participants were recruited to take the survey online, reporting on health care access and utilization, risk behaviors, and health status. It also measured for associations between reported depression, discrimination, acculturation, and health. Quantitative analysis showed correlations between age and current tobacco use, however no differences between men and women. Depression was significantly correlated with gender, age, and place of birth. Men were more likely to report having diabetes, high cholesterol, and hypertension than women. Results suggest that health promotion programs for Arabs in the DC area may help reduce health risks

Damping Factor Estimation of a Flexible-Matrix-Composite Body Pump

Abstract Two very important factors which determine the effectiveness of a pump are its volumetric and power efficiencies. Yin and Ghoneim constructed a prototype of a Flexible-Matrix-Composite (FMC) body pump with a very high volumetric efficiency or pumping potential (the relative volume reduction due to a relative input stroke). The high volumetric efficiency is attributed to the geometry of the pump's structure (hyperboloid) as well as the high negative effective Poisson's ratio of the 3-layer [θ/β/θ] flexible-matrix-composite (carbon/polyurethane) laminate adopted for the body of the pump. However, the power efficiency of the pump was not evaluated. It is the objective of the current paper to obtain an estimate of the power efficiency of the pump. The viscoelastic properties of the 3-layer FMC (carbon/polyurethane) laminate are evaluated experimentally using the Dynamic Mechanical Analyzer (DMA) as well as analytically by applying the correspondence principle together with the micro-mechanics approach. In order to obtain an estimate of the power efficiency of the FMC body pump, the axial and shear loss factors of a laminated infinitely long cylindrical tube as functions of β and θ fiber orientation angles are determined employing the Adam and Bacon approach. The analysis engenders high loss factors (greater than 0.4), which suggests that the power efficiency of the proposed pump using the 3-layer carbon/polyurethane laminate may be low

Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators

Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.Вступ. Система перетворення енергії вітру потребує алгоритму відстеження точки максимальної потужності. У літературі є кілька робіт, присвячених пошуку системи перетворення енергії вітру із точкою максимальної потужності. Як правило, їх метою є оптимізація механічного обертання або моменту, що крутить, генератора і перемикачів постійного струму або робочого циклу. Вихідна потужність системи перетворення енергії вітру залежить від точності контролера стеження за максимальною потужністю, оскільки швидкість вітру постійно змінюється протягом дня. Системи стеження за точками з максимальною потужністю, яким не потрібні механічні датчики для вимірювання швидкості вітру, мають ряд переваг у порівнянні з системами, що використовують механічні датчики. Новизна. Пропонована робота представляє інтелектуальний метод відстеження точки максимальної потужності, заснований на нечіткій моделі та багатопараметричному прогнозуючому контролері, для отримання максимальної енергії для маломасштабної системи перетворення енергії вітру, підключеної до електричної мережі. Пропонований алгоритм не вимагає вимірювання швидкості вітру або знання параметрів турбіни. Мета. Побудова інтелектуального алгоритму відстеження точки максимальної потужності, який не використовує механічні датчики для вимірювання швидкості вітру та витягує максимально можливу потужність з вітрогенератора, а також простий та зручний у реалізації. Методи. У цьому підході до управління нечітка система в основному використовується для генерування еталонного постійного струму, що відповідає точці максимальної потужності, на основі змін потужності постійного струму та постійної випрямленої напруги. Навпаки, багатопараметричний прогнозуючий регулятор на основі нечіткої моделі слідує за результуючим еталонним струмом з мінімальною помилкою, що встановилася. Істотні проблеми запропонованого методу відстеження точки максимальної потужності, такі як процес детального проектування та реалізація двох контролерів, були ретельно досліджені та представлені. Розглянутий підхід до відстеження точки максимальної потужності був застосований до вітрової системи, що приводить у дію синхронний генератор з постійними магнітами потужністю 5 кВт у режимі змінної швидкості за допомогою моделювання. Практична цінність. Для підтвердження результатів моделювання було виконано практичну реалізацію на випробувальному стенді потужністю 5 кВт, що складається з плати контролера dSPACEds1104, синхронного генератора з постійними магнітами та електроприводів з двигунами постійного струму. Порівняльні експериментальні результати при різній швидкості вітру підтвердили значні поліпшення продуктивності з максимального вироблення енергії вітру і загального відгуку системи при використанні запропонованого методу управління в порівнянні з традиційним пропорційно-інтегральним контролером спостереження за точкою максимальної потужності

An unusual presentation of hemoglobin SD Punjab in a Saudi Arabian adult

HbDPunjab is an uncommon variant hemoglobin that does not result in significant pathology when inherited as a homozygous disorder. When inherited with other hemoglobinopathies, it may result in varying disease phenotypes. HbSDPunjab has been rarely reported in Saudi Arabia, coexisting with alpha or beta thalassemia. In this report, we discuss the case of a 39 years old male who presented with severe anemia and renal injury and was later diagnosed with HbSDPunjab through electropheresis and genetic testing

PROGNOSTIC VALUE OF HISTOLOGY AND LYMPH NODE STATUS IN BILHARZIASIS-BLADDER CANCER: OUTCOME PREDICTION USING NEURAL NETWORKS

Abstract -In this paper, the evaluation of two features in predicting the outcomes of patients with bilharziasis bladder cancer has been investigated using an RBF neural network. Prior to prediction, the feature subsets were extracted from the whole set of features for the purpose of providing a high performance of the network. Throughout the analysis of the prognostic feature combinations, two features, histological type and lymph node status, have been identified as the important indicators for outcome prediction of this type of cancer. The highest predictive accuracy reached 85.0% in this study

leveraging artificial intelligence to improve voice disorder identification through the use of a reliable mobile app

The evolution of the Internet of Things, cloud computing and wireless communication has contributed to an advance in the interconnectivity, efficiency and data accessibility in smart cities, improving environmental sustainability, quality of life and well-being, knowledge and intellectual capital. In this scenario, the satisfaction of security and privacy requirements to preserve data integrity, confidentiality and authentication is of fundamental importance. In particular, this is essential in the healthcare sector, where health-related data are considered sensitive information able to reveal confidential details about the subject. In this regard, to limit the possibility of security attacks or privacy violations, we present a reliable mobile voice disorder detection system capable of distinguishing between healthy and pathological voices by using a machine learning algorithm. This latter is totally embedded in the mobile application, so it is able to classify the voice without the necessity of transmitting user data to or storing user data on any server. A Boosted Trees algorithm was used as the classifier, opportunely trained and validated on a dataset composed of 2003 voices. The most frequently considered acoustic parameters constituted the inputs of the classifier, estimated and analyzed in real time by the mobile application

Dysphonia Detection Index (DDI): A New Multi-Parametric Marker to Evaluate Voice Quality

The rapid diffusion of voice disorders and the lack of appropriate knowledge about the problem have prompted the search for novel and reliable approaches to detect dysphonia, through easy and accessible instruments such as mobile devices. These systems represent, in fact, valid instruments to improve the patient care not only to facilitate the monitoring of symptoms of any diseases but also supporting the correct diagnosis of pathology, such as the dysphonia. In this paper, we propose a new marker, namely the dysphonia detection index, able to support the evaluation of voice disorders, which can be embedded in a mobile health solution. Four acoustic parameters are combined in a single marker to globally evaluate the state of the health of the voice and to assess the presence or not of a voice disorder. A model tree regression algorithm has been applied to define the relationship between these parameters, and the Youden analysis has been used to define the threshold value to distinguish a pathological from a healthy voice. The reliability of the proposed index has been tested in terms of correct classification of accuracy, sensitivity, and specificity. A dataset of 2003 voices has been used to evaluate the performance of our proposed index, composed of samples selected from three different databases: the Massachusetts Eye and Ear Infirmary, the Saarbruecken Voice, and the VOice ICar fEDerico II databases. Our approach achieved the best performances in comparison with other algorithms, and accuracy equals to 82.2%, while sensitivity and specificity are 82% and 82.6%, respectively

Comparative effects of different supplemented dietary doses of chlorophyll on blood parameters of experimental male rats

Abstract Chlorophylls are organic pigments that are a part of our daily diet, particularly in light of the increased popularity of more eco-friendly and healthy practices. Since altering oxidative equilibrium seems to be connected to the emergence of numerous illnesses, the antioxidant capacities of both groups of lipophilic compounds have been studied. The objective was to evaluate adding dietary chlorophyll at two concentrations—30 and 60 mg/ml—would improve blood characteristics in rats. Supplemented dietary chlorophyll showed significantly increased WBCs, RBCs, granulocytes, lymphocytes, HGB, HCT MCHC, and Platelets. it nonsignificant effect on RDW, MPV, and Eosinophil. These findings support a significant rise in critical hematological parameters at two separate time intervals, 14 and 28 days following dietary chlorophyll supplementation, at dosages of 30 and 60 mg/ml. After 30 and 60 mg/ml, platelet count, PCT, lymphocytes, and monocytes substantially (p0.001) rose. In light of these findings, critical hematological indicators markedly rise in response to exogenous dietary chlorophyll. To strengthen blood parameters and enhance blood features and prevent anemia, dietary chlorophyll is advised

A Single DC Source Nine-Level Switched-Capacitor Boost Inverter Topology with Reduced Switch Count

This paper presents a new boost inverter topology with nine level output voltage waveform using a single dc source and two switched capacitors. The capacitor voltages are self-balancing and thus is devoid of any sensors and auxiliary circuitry. The output voltage is twice higher than the input voltage, which eliminates the need for an input dc boost converter especially when the inverter is powered from a renewable source. The merits of the proposed topology in terms of the number of devices and cost are highlighted by comparing the recent and conventional inverter topologies. In addition to this, the total voltage stress of the proposed topology is lower and have a maximum efficiency of 98.25%. The operation and dynamic performance of the proposed topology have been simulated using PLECS software and are validated using an experimental setup considering a different dynamic operation.This work was supported in part by the Scientific Research Deanship, Taif University, Saudi Arabia, under Grant 1-439 - 6072.Scopu