Operation cost reduction in unit commitment problem using improved quantum binary PSO algorithm

Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary Quantum Binary Particle Swarm Optimization (QBPSO) algorithm

Power quality improvement based on hybrid coordinated design of renewable energy sources for DC link channel DSTATCOM

This paper presents a comprehensive analysis of power quality for static synchronous compensator on the distribution power system (DSTATCOM) when a different types of energy sources are used to supply the dc link channel of DSTATCOM. These types of power supplies have a different effect on the compensation of DSTATCOM due to operation nature of these sources. The dynamic response of the DSTATCOM has been investigated that produced by individual and hybrid energy sources to evaluate the influence of these sources in terms of time response, compensation process and reduce the harmonics of current for source. Three cases have been considered in this study. First the photovoltaic (PV) cells alone second the battery storage alone and third a hybrid coordinated design between (PV cells with battery storage) is used. A boost Dc-Dc circuit has been connected to a photovoltaic cell with Maximum Power Point Tracking (MPPT) while a Dc-Dc buck-boost circuit is used with a battery. High coordination between PV and battery circuits in the hybrid system is used in order to improve the performance. A synchronous reference frame (SRF) with unit vector has been used to control the STATCOM circuit. The simulation results show that the hybrid design has the superiority response compared to the individual sources

Optimum reactive power compensation for distribution system using dolphin algorithm considering different load models

The distribution system represents the connection between consumers and the entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. The electrical distribution system suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to improve the voltage profile and to reduce the electrical distribution system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. In this paper, different models of electrical loads such as constant power(P), constant current(I), constant impedance(Z), and composite (ZIP) model are implemented with comparisons between them in order to identify the most effective load type that produces the optimal settlement for alleged loss reduction ,enhancement of the voltage profile, and cost savings. To minimize search space, Dolphin Optimization Algorithm (DOA) is applied for selecting the size and location of capacitors. Two case studies (IEEE 16- bus and 33- bus) are employed to evaluate the different load models with optimal reactive power compensation. The results of comparison between the different load models show that ZIP model is the best to produce the optimum solution for capacitor position and size. In addition, comparison of results with literature works are done and showed that DOA is the most robust among other algorithms to achieve the optimum solution for voltage profile enhancement significant reduction of losses, and saving cost

Dual techniques of load shedding and capacitor placement considering load models for optimal distribution system

Voltage stability represents one of the main issues in electrical power system. Under voltage load shedding (UVLS) has long been regarded as one of the most successful techniques to prevent the voltage collapse. However, the ordinary load shedding schemes do not consider the different load models and decreasing in the ‎economic cost that resulted from load disconnection, so the dual techniques of load shedding with reactive compensation are needed. Usually loads being modeled as constant power, while in fact of load flow the various load models are utilized. An investigation of optimal dual load shedding with reactive compensation for distribution system based on direct backward forward sweep method (DBFSM) load flow along with a comparison among the other load models are presented in this paper. The teaching learning-based optimization (TLBO) algorithm is executed in order to reduce power losses and enhance the voltage profile. This algorithm is tested and applied to IEEE-16 bus distribution test system to find the optimal superior capacitor size and placement while minimizing load shading for the network. Five different load shedding sequences are considered and the optimization performance of load models demonstrated the comparison through MATLAB program

Dual technique of reconfiguration and capacitor placement for distribution system

Radial Distribution System (RDS) suffer from high real power losses and lower bus voltages. Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) techniques are ones of the most economic and efficient approaches for loss reduction and voltage profile improvement while satisfy RDS constraints. The advantages of these two approaches can be concentrated using of both techniques together. In this study two techniques are used in different ways. First, the DSR technique is applied individually. Second, the dual technique has been adopted of DSR followed by OCP in order to identify the technique that provides the most effective performance. Three optimization algorithms have been used to obtain the optimal design in individual and dual technique. Two IEEE case studies (33bus, and 69 bus) used to check the effectiveness of proposed approaches. A Direct Backward Forward Sweep Method (DBFSM) has been used in order to calculate the total losses and voltage of each bus. Results show the capability of the proposed dual technique using Modified Biogeography Based Optimization (MBBO) algorithm to find the optimal solution for significant loss reduction and voltage profile enhancement. In addition, comparisons with literature works done to show the superiority of proposed algorithms in both techniques

Assessment of Children's Oral Health-Related Knowledge and Self-Efficacy in Expectant Mothers of Najran, Saudi Arabia

Objective: To assess the knowledge of pregnant women regarding their child’s oral health. Material and Methods:  A questionnaire was developed and the 1st section comprised sociodemographic variables. The second section contained questions about the eruption of teeth, fluoride importance, cariogenic food, and dental visits. The questionnaire was shared electronically via a link to the receptionist of the gynaecologist at different health centres of Najran to be filled by expectant mothers. The convenient sampling method was used to collect the responses. Data were presented using descriptive statistics. Results: A total of 572 pregnant women participated in this survey. Three hundred and fifteen (55.1%) knew that 1st primary tooth erupts at the age of 6 months. The majority of the respondents (n=332) agreed that toothbrushes and toothpaste could be used to clean a child's teeth; only 5.4%, 10%, and 24.5% preferred miswak, mouthwash, and toothbrush, respectively. Participants were well familiar with cariogenic food and occasionally allowed their children to take it. They have enough knowledge about fluoride toothpaste, but they were not familiar with the benefits of fluoride varnish. Almost 50% of the respondents agreed that the child should visit the dentist within six months, and 27.4% said they should visit the dentist whenever there is a problem. Conclusion:  Almost 50% of participants showed a positive attitude towards most questions. However, there is a need to improve their  behaviour and knowledge about many aspects of dental care

Acute Liver Failure and the Neurological Complications: Theoretical Review

This study aimed at theoretically reviewing the Acute Liver Failure (ALF) and the Neurological Complications by reviewing the related studies in this area. As the problem of this study lies in exploring the neurological complications caused by Acute Liver Failure, and defining the causes of Acute Liver Failure, besides Diagnosing of Acute Liver Failure and the treatment processes of Acute Liver Failure. And the study concluded that the management of acute liver failure addresses the individual pathophysiological processes that occur in this condition. It improves chances of survival in patients awaiting liver transplantation and dramatically reduces the risk of death from neurological complications

CONCOMITANT USE OF NON-STEROIDAL ANTI-INFLAMMATORY DRUGS (NSAIDS) WITH WARFARIN

Introduction: Oral anticoagulation with warfarin is the accepted technique for treatment and prophylaxis of thromboembolic diseases. Nonsteroidal anti-inflammatory drugs (NSAIDs) are the most broadly administered medications to control musculoskeletal pain or inflammation. besides to their antiplatelet work, NSAIDs can influence the pharmacologic activity of warfarin through their immediate interaction. High protein binding and the cytochrome P450 (CYP)- dependent clearance systems of NSAIDs can influence the serum levels of warfarin. Aim of work: In this review, we will discuss whether using warfarin with NSAID has any effect on the pharmacokinetics and pharmacodynamics of both drugs. Methodology: We conducted this review using a comprehensive search of MEDLINE, PubMed, and EMBASE, January 1985, through February 2017. The following search terms were used: Non-steroidal anti-inflammatory drug mechanism, warfarin mechanism, adverse effects of NSAID, adverse effect of warfarin, NSAID-warfarin interaction Conclusions: Co-administration of NSAIDs and Warfarin is a topic of debate. However, there are reasons for concern. Some NSAIDs alter hemostasis and, when combined with warfarin, may lead to an increase in bleeding time. There is also a risk of increased hepatic and renal toxicity which complicates things further. Balancing the pros and cons of this drug combination should be carefully done on a case to case basis to avoid any negative consequences. Key words: NSAID, warfarin, Aspirin, drug-drug interaction, bleedin

An Intelligent Early Flood Forecasting and Prediction Leveraging Machine and Deep Learning Algorithms with Advanced Alert System

Flood disasters are a natural occurrence around the world, resulting in numerous casualties. It is vital to develop an accurate flood forecasting and prediction model in order to curb damages and limit the number of victims. Water resource allocation, management, planning, flood warning and forecasting, and flood damage mitigation all benefit from rain forecasting. Prior to recent decades’ worth of research, this domain demonstrated to be promising prospects in time series prediction tasks. Therefore, the main aim of this study is to build a forecasting model based on the exponential smoothing-long-short term memory (ES-LSTM) structure and recurrent neural networks (RNNs) for predicting hourly precipitation seasons; and classify the precipitation using an artificial neural network (ANN) model and decision tree (DT) algorithm. We employ the dataset from the Australian commonwealth office of meteorology named Historical Daily Weather dataset to test the effectiveness of the proposed model. The findings showed that the ES-LSTM and RNN had achieved 3.17 and 6.42 in terms of mean absolute percentage error (MAPE), respectively. Meanwhile, the ANN and DT models obtained a prediction accuracy rate of 96.65% and 84.0%, respectively. Finally, the outcomes revealed that ES-LSTM and ANN had achieved the best results compared to other models

The Potential Role of Renin Angiotensin System (RAS) and Dipeptidyl Peptidase-4 (DPP-4) in COVID-19: Navigating the Uncharted

Novel coronavirus (COVID-19) led to infected pneumonia and acute respiratory distress syndrome (ARDS) and acute kidney injury (AKI). The entry-point receptor for COVID-19 is angiotensin-converting enzyme 2 (ACE2) at lung, and dipeptidyl peptidase-4 (DPP-4) is a receptor for Middle East respiratory syndrome coronavirus (MERS-CoV). There is 80% similarity between MERS-CoV and COVID-19. This study was planned to review the potential link between the incidence and severity of COVID-19 regarding the modulation of DPP-4 and ACE2 by DPP-4 and renin angiotensin system (RAS). In COVID-19, SARS-CoV2 binds ACE2 which is highly expressed by the epithelial cells of the blood vessel, intestine, and lung. However, pulmonary ACE2 seems to be a protective defense pathway during ARDS. DPP-4 is not concerned with the entry of COVID-19 but mediates the inflammatory reactions and cytokine storm that induced ARDS and AKI by COVID-19. The interaction between DPP4i and RAS inhibitors seem to augment the expression of AT2 receptor and ACE2 which are under extensive researches to find the pathophysiological pathway of COVID-19 infection. This beneficial interaction between DPP4i and RAS shed light for possible attenuation of COVID-19-induced ARDS and AKI mainly in critically ill patients with systemic hypertension