Clinical and Laboratory Manifestations of Yemeni Patients with Systemic Lupus Erythematosus

Objectives: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterised by multi-systemic involvement. This is the first study undertaken to determine the relationships between serological marker positivity and age, gender, signs and symptoms, risk factors and the treatment of SLE in Yemen. Methods: We investigated the cases of 149 patients with SLE admitted to Al-Thawra Hospital in Sana’a city between November 2009 and November 2010. Of the 149 patients, females represented 75.2% and males, 24.8%. Results: The most frequent presenting signs and symptoms were fatigue (84.6%), fever (81.9%), arthropathy (81.2%), anaemia (64.4%), photosensitivity (54.4%), renal involvement (53%), malar rash (52.3%), and alopecia (49%). Antinuclear antibodies (ANA) were detected in 95.3% of the patients and were associated significantly with most clinical presentations, except weight loss, hypertension and serositis. Anti-ds deoxyribonucleic acid (anti-dsDNA) was detected in 59.7% of the patients, and was associated significantly with fever and fatigue. Anti-Smith (anti-Sm) antibodies were detected in 27.5% of the patients, but were not significantly associated with all clinical presentations. Social stress was the most important risk factor for inducing SLE, with an odds ratio (OR) of 6.0, followed by common exposure to sunlight (OR = 2.2). Conclusion: In this study, SLE was more prevalent among females and young adults. The clinical presentation was characterised by a high incidence of fatigue and fever, and a low incidence of oral ulcers and serositis. ANA was associated with most clinical presentations except weight loss, hypertension, and serositis. AntidsDNA antibodies were most frequently associated with fever, fatigue and hypertension. There was no significant association of the anti-Sm antibodies with any clinical presentations

Fuzzy Fractional-Order PID Controller for Fractional Model of Pneumatic Pressure System

This article presents a fuzzy fractional-order PID (FFOPID) controller scheme for a pneumatic pressure regulating system. The industrial pneumatic pressure systems are having strong dynamic and nonlinearity characteristics; further, these systems come across frequent load variations and external disturbances. Hence, for the smooth and trouble-free operation of the industrial pressure system, an effective control mechanism could be adopted. The objective of this work is to design an intelligent fuzzy-based fractional-order PID control scheme to ensure a robust performance with respect to load variation and external disturbances. A novel model of a pilot pressure regulating system is developed to validate the effectiveness of the proposed control scheme. Simulation studies are carried out in a delayed nonlinear pressure regulating system under different operating conditions using fractional-order PID (FOPID) controller with fuzzy online gain tuning mechanism. The results demonstrate the usefulness of the proposed strategy and confirm the performance improvement for the pneumatic pressure system. To highlight the advantages of the proposed scheme a comparative study with conventional PID and FOPID control schemes is made

Numerical estimation and experimental verification of optimal parameter identification based on modern optimization of a three phase induction motor

The parameters of electric machines play a substantial role in the control system which, in turn, has a great impact on machine performance. In this paper, a proposed optimal estimation method for the electrical parameters of induction motors is presented. The proposed method uses the particle swarm optimization (PSO) technique. Further, it also considers the influence of temperature on the stator resistance. A complete experimental setup was constructed to validate the proposed method. The estimated electrical parameters of a 3.8-hp induction motor are compared with the measured values. A heat run test was performed to compare the effect of temperature on the stator resistance based on the proposed estimation method and the experimental measurements at the same conditions. It is shown that acceptable accuracy between the simulated results and the experimental measurements has been achieved

Knowledge and Attitude of Saudi Arabian School Teachers with Regards to Emergency Management of Dental Trauma

Injury to both the primary and the permanent dentitions and their supporting structures is one of the most common dental problems seen in children.  School is one of the locations with greatest prevalence of occurrence of traumatic dental injuries.  School teachers play important role in prevention of dental trauma and improving its prognosis. The present study was undertaken to assess knowledge and attitudes regarding emergency management of dental trauma, first aid for avulsed tooth and influence of dental education among school teachers in Abha city. METHODS: The participants were 100 school teachers from Abha city and were interviewed using a questionnaire regarding management of dental trauma.  The completed proformas was collected and the result was statistically analyzed to know the knowledge and attitudes regarding emergency management of dental trauma. CONCLUSIONS: Majority of school staff had little knowledge related to handling of traumatic dental injuries and emergency management of avulsed permanent teeth in school children. Majority of school teachers were eager to have knowledge regarding dental trauma through continues dental education programs and workshops.  First aid training increases knowledge about dental trauma and should be included in the course curriculum of teachers training program

Fuel cell as an effective energy storage in reverse osmosis desalination plant powered by photovoltaic system

A hybrid renewable energy systems (HRESs) comprises of photovoltaic (PV), and self-charging fuel cells (SCFC) is designed for securing electrical energy required to operate brackish water pumping (BWP) and reverse osmosis desalination (RO) plant of 150 m3 d-1 for irrigation purposes in remote areas. An optimal configuration of the proposed design is determined based on minimum cost of energy (COE) and the minimum total net present cost (NPC). Moreover, a comparison with a stand-alone diesel generation (DG) or grid extension is carried out against the optimal configuration of PV/SCFC HRES. The modeling, simulation, and techno-economic evaluation of the different proposed systems, including the PV/SCFC system are done using HOMER software. Results show that PV array (66 kW), FC (9 kW), converter (25 KW) –Electrolyzer (15 kW), Hydrogen cylinder (70 kg) are the viable economic option with a total NPC of $115,649 and$0.062 unit cost of electricity. The COE for the stand-alone DG system is 0.206 $/kWh, which is 69.90% higher than that of the PV/SCFC system. The PV/SCFC system is cheaper than grid extension. This study opens the way for using a fuel cell as an effective method for solving the energy intermittence/storage problems of renewable energy sources

State-of-the-art of the most commonly adopted wave energy conversion systems

Copyright © 2023 The Authors. The vast diversity of wave energy conversion systems (WECSs) in the literature makes selecting the suitable WECS for wave energy harvest a stubborn process. This work summarizes six of the most widely adopted WECSs used heavily in previous research assessments and practical projects. This includes the Archimedes Wave Swing (AWS), the Wave Dragon (WD), Pelamis Wave Power (PWP), Aquabouy (AB), the Oyster, and the Oscillating Water Column (OWC). The work includes the mathematical modeling of these WECSs and the different projects and prototypes that involve these WECSs. Moreover, the latest research development in each of these WECSs is presented. Also, the wave energy potential in the world is discussed. Besides, the wave energy potential in Egypt, including that of the Mediterranean and the Red Sea, is discussed in detail. Furthermore, the steps required to perform a future feasibility study in Egypt and suggestions for the enhancement of an older study are provided. Finally, some suggestions and required equations are presented to explore the site power density and the most suitable WECS to be utilized in Egypt

Multicomponent Domino Synthesis, Anticancer Activity and Molecular Modeling Simulation of Complex Dispirooxindolopyrrolidines

A series of spirooxindolopyrrolidine fused N -styrylpiperidone heterocyclic hybrids has been synthesized in excellent yield via a domino multicomponent protocol that involves one-pot three component 1,3-dipolar cycloaddition and concomitant enamine reactions performed in an inexpensive ionic liquid, namely 1-butyl-3-methylimidazolium bromide ([bmim]Br). Compounds thus synthesized were evaluated for their cytotoxicity against U-937 tumor cells. Interestingly; compounds 5i and 5m exhibited a better cytotoxicity than the anticancer drug bleomycin. In ddition; the effect of the synthesized compounds on the nuclear morphology of U937 FaDu cells revealed that treatment with compounds 5a–m led to their apoptotic cell death

Hammerstein Box-Jenkins System Identification of the Cascaded Tanks Benchmark System

A common process control application is the cascaded two-tank system, where the level is controlled in the second tank. A nonlinear system identification approach is presented in this work to predict the model structure parameters that minimize the difference between the estimated and measured data, using benchmark datasets. The general suggested structure consists of a static nonlinearity in cascade with a linear dynamic filter in addition to colored noise element. A one-step ahead prediction error-based technique is proposed to estimate the model. The model is identified using a separable least squares optimization, where only the parameters that appear nonlinearly in the output of the predictor are solved using a modified Levenberg–Marquardt iterative optimization approach, while the rest are fitted using simple least squares after each iteration. Finally, MATLAB simulation examples using benchmark data are included

Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources

This paper presents a multi-objective economic-environmental dispatch (MOEED) model for integrated thermal, natural gas, and renewable energy systems considering both pollutant emission levels and total fuel or generation cost aspects. Two cases are carried out with the IEEE 30-bus system by replacing thermal generation units into natural gas units to minimize the amount of toxin emission and fuel cost. Equality, inequality like active, reactive powers, prohibited operating zones (POZs) which represents poor operation in the generation cost function, and security constraints are considered as system constraints. Natural gas units (NGUs) are modeled in detail. Therefore, the flow velocity of gas and pressure pipelines are also considered as system constraints. Multi-objective optimization algorithms, namely multi-objective Harris hawks optimization (MOHHO) and multi-objective flower pollination algorithm (MOFPA) are employed to find Pareto optimal solutions of fuel or generation cost and emission together. Furthermore, the technique for order preference by similarity to ideal solution (TOPSIS) is proposed to obtain the best value of Pareto optimal solutions. Three scenarios are investigated to validate the effectiveness of the proposed model applied to the IEEE 30-bus system with the integration of variable renewable energy sources (VRESs) and natural gas units. The results obtained from Scenario III with NGUs installed instead of two thermal units reveal that the economic dispatching approach presented in this work can greatly minimize emission levels as 0.421 t/h and achieve lower fuel cost as 796.35 $/h. Finally, the results obtained show that the MOHHO outperforms the MOFPA in solving the MOEED problem

Reinforcement Learning-Based Control Strategy for Multi-Agent Systems Subjected to Actuator Cyberattacks During Affine Formation Maneuvers

In this research, we investigate the reinforcement learning-based control strategy for second-order continuous-time multi-agent systems (MASs) subjected to actuator cyberattacks during affine formation maneuvers. In this case, a long-term performance index is created to track the MASs tracking faults using a leader-follower structure. In order to approximate the ideal solution, which is challenging to find for systems vulnerable to cyberattacks during time-varying maneuvers, a critical neural network is used. The distributed control protocol is obtained, and the long-term performance index is minimized, using an actor neural network strengthened with critic signals. The actor-critic neural networks calculate unknown dynamics and the severity of attacks on the MAS actuators. The Nussbaum functions are applied to address this issue since attacks can result in a loss of control direction. The stability of the closed-loop system has been emphasized with the use of a Lyapunov candidate function. The performance of the suggested strategy is then supported by a numerical simulation