Markov Chain Modelling-Based Approach to Reserve Electric Vehicles in Parking Lots for Distribution System Energy Management

Integration of renewable energy resources in distribution networks with intermittent behaviour increases the challenge of power balance in transmission systems. To mitigate the undesired impacts, transmission operator involves distribution operators to get local contribution from their flexible resources. In this paper, we address the flexibility offered by some electric car sharing agents which can serve some reserve capacity to distribution system. A Markov Chain modelling based approach is proposed to support system operator to properly estimate the number of electric vehicles required to be booked in advance as reserve. Underestimation would result in imperfect demand correction, and overestimation would imply extra costs. Using a realistic case under a near future scenario of high PV integration and EV accommodation, we demonstrate the contribution of our approach to this problem of planning or scheduling. Obtained results quantifies the performance of the proposed method in terms of average energy difference based on number of EVs. The results can be used as a basis to decide the appropriate number of EV reservations

Failure of Scattering Interference in the Pseudogap State of Cuprate Superconductors

We calculate scattering interference patterns for various electronic states proposed for the pseudogap regime of the cuprate superconductors. The scattering interference models all produce patterns whose wavelength changes as a function of energy, in contradiction to the energy-independent wavelength seen by scanning tunneling microscopy (STM) experiments in the pseudogap state. This suggests that the patterns seen in STM local density of states measurements are not due to scattering interference, but are rather the result of some form of ordering.Comment: To be submitted to Phys. Rev.

Annihilation of singlet fermionic dark matter into two photons via pseudo-scalar mediator

We consider the indirect detection of dark matter within an extension of the standard model (SM) including a singlet fermion as cold dark matter (CDM) and a singlet pseudo-scalar as a mediator between dark matter and the SM particles. The annihilation cross section of the CDM into two monochromatic photons is calculated and compared with the latest H.E.S.S. data. Although for dark matter masses below 1 TeV the predicted observable cross sections are far from the sensitivity of the recent gamma-ray experiments, it can be comparable to the strongest H.E.S.S. upper bounds for some models with more massive CDM.Comment: 9 pages, 5 figures, typo is fixed, references update

The effect of dietary dextrin levels on growth performance, body composition and hepatosomatic index in juvenile Siberian sturgeon, Acipenser baerii

The present study was carried out to determine the ability of Acipenser baerii in utilizing carbohydrate (dextrin) as a non protein energy source substituted with animal oil. A total of 65 juveniles A. baerii with an initial mean weight of 689 ± 62 g were distributed in 15 fiber glass tanks. Five diets were formulated including 0, 5, 10, 15 and 20% of dextrin and fed for 8 weeks. Fish were weighed monthly and growth was evaluated in each treatment. At the end of experiment, body composition and hepatosomatic index were analyzed. There was no significant differences in body weight increase (BWI) and final weight (FW) among different groups (p>0.05). Increase of dextrin levels in diets led to an increase in feed conversation ratio (FCR) in fish fed diets containing 15 and 20% dextrin as compared to that in the control group and in fish fed the diet containing 10% dextrin although the differences were not significant (p>0.05). The specific growth rate (SGR) in all treatments were the same (p>0.05). The highest body protein and lipid were observed in fish fed diets containing 10 and 20% dextrin, respectively (p0.05). In conclusion, juvenile A. baerii can be fed diets with high levels of dietary dextrin as a non protein energy source with no deleterious effects and a partial replacement of cheap carbohydrate with lipid is suggested to obtain the necessary energy in commercial diets

In-depth description of Electrohydrodynamic conduction pumping of dielectric liquids: physical model and regime analysis

In this work, we discuss the fundamental aspects of Electrohydrodynamic (EHD) conduction pumping of dielectric liquids. We build a mathematical model of conduction pumping that can be applied to all sizes, down to microsized pumps. In order to do this, we discuss the relevance of the Electrical Double Layer (EDL) that appears naturally on nonmetallic substrates. In the process, we identify a new dimensionless parameter related to the value of the zeta potential of the substrate-liquid pair, which quantifies the influence of these EDLs on the performance of the pump. This parameter also describes the transition from EHD conduction pumping to electro-osmosis. We also discuss in detail the two limiting working regimes in EHD conduction pumping: ohmic and saturation. We introduce a new dimensionless parameter, accounting for the electric field enhanced dissociation that, along with the conduction number, allows us to identify in which regime the pump operates.Ministerio de Ciencia, Innovación y Universidades PGC2018-099217-B-I0

Detection of icaAD gene and biofilm formation in Staphylococcus aureus isolates from wound infections

Wound infections are a common cause of staphylococcal infections. An ability of S.aureus is to adhere and form biofilm on host surfaces. Biofilm is an exopolysaccharide, a slime matrix around multiple layers of cells and is mediated by expression of the icaADBC operon. The present study evaluated the biofilm forming capacity and the presence of icaAD gene among S.aureus isolated from wound infections. Slime production assay was performed by cultivation on Congo Red Agar plate. In addition, Quantitative biofilm formation determined by microtiter plate assay PCR method used for detection of icaAD gene. Fifty strains were identified, 54 of the isolates produced black colonies on CRA plate, 52 were positive biofilm forming, and all strains carried the icaAD gene. Regarding the ability of Saureus to form biofifms helps the bacterium to survive hostile environments within the host, suggests that biofilm production is a risk factor for infection. It is important in rapid diagnosis and treatment biofilm forming strains, because biofilm formation may lead to increased antimicrobial resistance and create a significant impediment to wound healing

Evolution of the Density of States Gap in a Disordered Superconductor

It has only recently been possible to study the superconducting state in the attractive Hubbard Hamiltonian via a direct observation of the formation of a gap in the density of states N(w). Here we determine the effect of random chemical potentials on N(w) and show that at weak coupling, disorder closes the gap concurrently with the destruction of superconductivity. At larger, but still intermediate coupling, a pseudo-gap in N(w) remains even well beyond the point at which off-diagonal long range order vanishes. This change in the elementary excitations of the insulating phase corresponds to a crossover between Fermi- and Bose-Insulators. These calculations represent the first computation of the density of states in a finite dimensional disordered fermion model via the Quantum Monte Carlo and maximum entropy methods.Comment: 4 pages, 4 figure

Comparison of health-related quality of life after percutaneous coronary intervention and coronary artery bypass surgery

BACKGROUND: Health-related quality of life (HRQOL) evaluation is an important measure of the impact of the disease. As more people with coronary heart disease (CHD) live longer, doctors and researchers want to know how they manage in day to day life. It looked like adults with CHD had a decrease QOL. The aim of this study was to comparison of HRQOL of patients who underwent percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) and to assess its main determinants in the whole sample of coronary artery disease (CAD) patients. METHODS: The study was carried out to estimate HRQOL of 109 patients who underwent invasive coronary revascularization PCI (n = 75) and CABG (n = 34). We applied HRQOL after 6 months and 2 years in both groups and scores were compared. The HRQOL data were obtained using MacNew Heart Disease questionnaire with dimensions emotional, physical and social that estimated. Data entry and analysis were performed by SPSS 16.0. RESULTS: A total MacNew scale in CABG and PCI group in 6 months after treatment were 45.32 ± 13.75 and 53.52 ± 15.63, respectively (P = 0.0100). After 2 years HRQOL mean changed to 51.176 ± 14.80 and 49.55 ± 16.22, respectively, in CABG and PCI group (P = 0.4280). Our results in within-group analysis showed total MacNew scale and its subscales were changed significantly after 2 years in CABG and PCI group�s scores were detected. We found in the whole sample of CAD patients those who had a higher level of income and education and were not either overweight or obese experienced better HRQOL. CONCLUSION: Our results showed that patients who underwent PCI experienced significantly higher HRQOL in 6 months after revascularization but over 24 months follow-up no difference was observed between the two groups. © 2016, Isfahan University of Medical Sciences(IUMS). All rights reserved

Artificial intelligence-based models for reconstructing the critical current and index-value surfaces of HTS tapes

For modelling superconductors, interpolation and analytical formulas are commonly used to consider the relationship between the critical current density and other electromagnetic and physical quantities. However, look-up tables are not available in all modelling and coding environments, and interpolation methods must be manually implemented. Moreover, analytical formulas only approximate real physics of superconductors and, in many cases, lack a high level of accuracy. In this paper, we propose a new approach for addressing this problem involving artificial intelligence (AI) techniques for reconstructing the critical surface of high temperature superconducting (HTS) tapes and predicting their index value known as n-value. Different AI models were proposed and implemented, relying on a public experimental database for electromagnetic specifications of HTS tapes, including artificial neural networks (ANN), eXtreme Gradient Boosting (XGBoost), and kernel ridge regressor (KRR). The ANN model was the most accurate in predicting the critical current of HTS materials, performing goodness of fit very close to 1 and extremely low root mean squared error. The XGBoost model proved to be the fastest method, with training computational times under 1 s; whilst KRR could be used as an alternative solution with intermediate performance