A crystallographic and theoretical study of an (E)-2-Hydroxyiminoethanone derivative: prediction of cyclooxygenase inhibition selectivity of stilbenoids by MM-PBSA and the role of atomic charge

We recently reported that a hydroxyiminoethanone derivative behaves as a highly selective COX-1 inhibitor (COX-1 SI= 833), and also an interesting scaffold with unique characteristics. In the current study, a comprehensive crystallographic and computational study was performed to elucidate its conformational stability and pharmacological activity. Its conformational energy was studied at the B3LYP/6-311G** level of theory and compared to the single-crystal X-ray data. In addition, computational studies of three structurally different stilbenoid derivatives used as selective COX-1 or COX-2 inhibitors were performed to predict their COX selectivity potentials. Flexible docking was performed for all compounds at the active site of both COX-1 and COX-2 enzymes by considering some of the key residues as flexible during the docking operation. In the next step, molecular dynamic simulation and binding free energy calculations were performed by MM-PBSA. Final results were found to be highly dependent on the atomic charges of the inhibitors and the choice of force field used to calculate the atomic charges. The binding conformation of the hydroxyiminoethanone derivative is highly correlated with the type of COX isoform inhibited. Our predictive approach can truly predict the cyclooxygenase inhibition selectivity of stilbenoid inhibitors

Load Frequency Control for Hydropower Plants using PID Controller

Many development republics began to get rid of conventional energy and towards to use renewable energy like hydropower system, solar cells and wind turbines as soon as possible. Load Frequency Control (LFC) problem is coming to be the main topics for mentioning schemes due to not corresponding between main power system inputs such as change load demand and change in speed turbine settings. This paper illustrates a selftuning control of hydropower system that suggested and confirmed under Automatic Generation Control (AGC) in power scheme. The suggested power system involves one single area. The suggested self-tuning control system is employed in performing the automatic generation control for load frequency control request and compared it with conventional control structure. The power system dynamic modeling has regularly built in several essential parameters which have a significant influence According to frequency limitation. The main problem with all controllers is an exaggerated reaction to minor errors, producing the system to oscillate. The output response results for hydropower system obviously proved the benefit of using maximum load demand by tuning PID controller. Whereas, tuning PID controller has got properly more rapid output response and minimal overshoot

Synthesis of Bioactive Yttrium-Metal–Organic Framework as Efficient Nanocatalyst in Synthesis of Novel Pyrazolopyranopyrimidine Derivatives and Evaluation of Anticancer Activity

Novel Yttrium-metal–organic framework (Y-MOF) was synthesized under optimal conditions of microwave with a power of 20 W, the temperature of 30 degrees of centigrade, and time duration of 10 min. The products were characterized by SEM (morphology and size distribution), TGA (thermal stability), BET technique (surface area), and FTIR (characterization of the related group). The Yttrium-metal–organic framework (Y-MOF) synthesized in this study, after identifying and confirming the structure, was used as an efficient and recyclable catalyst in the synthesis of new pyrazolopyranopyrimidine derivatives. Following the study of the properties and applications of Y-MOF, its anticancer properties on breast cancer cells based on the MTT method were evaluated, and significant results were observed. In addition, the anticancer properties of the pyrazolopyranopyrimidine derivatives were investigated

Danish study of Non-Invasive testing in Coronary Artery Disease 2 (Dan-NICAD 2): study design for a controlled study of diagnostic accuracy

Background: Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICA) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has three equivalent main aims: 1) to examine the diagnostic precision of a sound based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. 2) to compare the diagnostic accuracy of 3 Tesla cardiac magnetic resonance imaging (3T CMRI), 82Rubidium positron emission tomography (82Rb-PET) and CT-derived fractional flow reserve (FFRCT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. 3) to compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82Rb-PET as reference standard. Methods/design: Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule-out obstructive CAD, patients will be examined by both 3T CMRI, 82Rb-PET, FFRCT, ICA and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90 % diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion. Discussion: The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in three different steps; risk-stratification prior to coronary CTA, diagnostic strategy after coronary CTA and invasive wireless QFR analysis as an alternative to ICA-FFR. Study registration: Clinicaltrials.gov identifier, NCT03481712. Registered on January 25th 2018.Aarhus UniversityHealth Research Fund of Central Denmark RegionAcarix A/

Pseudouridylation defect due to DKC1 and NOP10 mutations causes nephrotic syndrome with cataracts, hearing impairment, and enterocolitis

Research UK Innovation and Project; Cancer Research U

Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling

The fundamental requirement of power system hydro scheduling is to determine the optimal amount of generated powers for the hydro unit of the system in the scheduling horizon of 1 year or few years while satisfying the constraints of the hydroelectric system. Long-Term Hydro Generation Scheduling (LHGS) is a complicated nonlinear, non-convex and nonsmooth optimization problem with discontinuous solution space. The model considers daily water inflows, limits on reservoir level, power generation depends on the available head of hydro units caused by power variations, start-up, and shut-down of hydro units. To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. The SDM is to make a division on the Swarm Intelligence (SI) algorithm which is to be a number of particles searching collections that properly can be regarded as divisions. Whereas, each division is a developmental algorithm which used to get the global point. The extent of the SDM is often offered a quicker convergence so as to accomplish the best initial operation to swarm's algorithm research. The proposed SDM are tested on two test systems actual observed system operator (AOSO) and Standard System Operation (SSO) and compared with some recent research works in the area. The results point out the Series Division Firefly Algorithm (SDFA) is robust and has good efficiency and superiority

Optimal Long-Term Hydro Generation Scheduling of Small Hydropower Plant (SHP) using Metaheuristic Algorithm in Himreen Lake Dam

This study focuses on the improvement of optimization model by applying particle swarm optimization and firefly algorithm methods to get a stable power production utility at its maximum level. Furthermore, it investigates on the minimization of utility loss in power production from the hydropower system, which is done by optimizing the variables of operation control in the hydropower plant at Lake Himreen - Diyala Dam. The variables mentioned are net turbine head, the rate of water flow and power production which had been gathered in the data during a research throughout a 10-year period. The results obtained from these two methods, namely Firefly Algorithm (FA) and Particle Swarm Optimization, (PSO) are compared. The inferences for general comparisons are created through several behavior indicators. The behavior indicators illustrate that FA's performance is better than PSO's performance, in some fields. At the end, the results show the strength of FA, as well as its efficiency and superiority

Prediction of small hydropower plant power production in Himreen Lake dam (HLD) using artificial neural network

In developing countries, the power production is properly less than the request of power or load, and sustaining a system stability of power production is a trouble quietly. Sometimes, there is a necessary development to the correct quantity of load demand to retain a system of power production steadily. Thus, Small Hydropower Plant (SHP) includes a Kaplan turbine was verified to explore its applicability. This paper concentrates on applying on Artificial Neural Networks (ANNs) by approaching of Feed-Forward, Back-Propagation to make performance predictions of the hydropower plant at the Himreen lake dam-Diyala in terms of net turbine head, flow rate of water and power production that data gathered during a research over a 10 year period. The model studies the uncertainties of inputs and output operation and there’s a designing to network structure and then trained by means of the entire of 3570 experimental and observed data. Furthermore, ANN offers an analyzing and diagnosing instrument effectively to model performance of the nonlinear plant. The study suggests that the ANN may predict the performance of the plant with a correlation coefficient (R) between the variables of predicted and observed output that would be higher than 0.96

Priority of Kaplan Turbine and Small Hydropower Plants Over Other Resources: An Overview

Many developed countries gradually begin to dispense traditional energy origins plants that built on oil, coal usual gas owing to oil prices increment, fossil fuel cost, thermal pollution, and the crisis of worldwide energy. Large hydropower plants (LHP) and Mini (MHP) are less feasible than a small hydropower plant (SHP). Up to now, the Mechanism of appropriated turbine selection for a specific purpose is undefined obviously. Classification of hydropower schemes generally depends on the capacity of production. An installed plant capacity of up to 25 MW is regarded as an SHP. The capability of the SHP and future production and its economic operating option like run-of-river and clean development mechanism (CDM) making it's desirable. Moreover, in order to achieve dependable and reasonable production. Turbines classification divided according to turbines' net head and flow water rate. In this article, we provide analyzing and surveying on categories of the hydropower plant to show characteristics of each one, different SHP technology, properties for appropriated turbine and evaluate the economic potential of the feasible power plant

Optimum Power Production of Small Hydropower Plant (SHP) Using Firefly Algorithm (FA) in Himreen Lake Dam (HLD), Eastern Iraq

In developing countries, the amount of electrical power production is lower than the request of power or load. Therefore, sustaining the stability of optimum power production system becomes a problem. Sometimes, the development of the correct quantity of load demand is necessary in order to keep the system of power production steady. Thus, the addition of Kaplan turbine into Small Hydropower Plant (SHP) is verified to explore its applicability. This study focuses on the improvement of optimization model by applying particle swarm optimization and firefly algorithm methods in order to get a stable power production utility at its maximum level. Furthermore, it investigates on the minimization of utility loss in power production from the hydropower system, which is done by optimizing the variables of operation control in the hydropower plant at Lake Himreen - Diyala Dam. The variables mentioned are net turbine head, rate of water flow and power production which had been gathered in the data during a research throughout a 10-year period. Moreover, this study investigates the uncertainties of input and output operation of small hydropower plant, the designing of the entire 3570 experiments, and the data collected from the observation on the performance of the nonlinear plant model. The results obtained from these two methods, namely Firefly Algorithm (FA) and Particle Swarm Optimization, (PSO) are compared. The inferences for general comparisons are created through several behavior indicators. The behavior indicators illustrate that FA’s performance is better than PSO’s performance, in some fields. At the end, the results show the strength of FA, as well as its efficiency and superiority