Leptoquarks meet ε′/ε\varepsilon'/\varepsilon and rare Kaon processes

We analyse for the first time the CP violating ratio $\varepsilon'/\varepsilon$ in $K\to \pi\pi$ decays in leptoquark (LQ) models. Assuming a mass gap to the electroweak (EW) scale, the main mechanism for LQs to contribute to $\varepsilon'/\varepsilon$ is EW gauge-mixing of semi-leptonic into non-leptonic operators, which we treat in the Standard Model effective theory (SMEFT). We perform also the one-loop decoupling for scalar LQs, finding that in all models with both left-handed and right-handed LQ couplings box-diagrams generate numerically strongly enhanced EW-penguin operators $Q_{8,8'}$ already at the LQ scale. We then investigate correlations of $\varepsilon'/\varepsilon$ with rare Kaon processes ($K_L\to\pi^0\nu\bar\nu$, $K^+\to\pi^+\nu\bar\nu$, $K_L\to\pi^0\ell\bar\ell$, $K_S\to\mu\bar\mu$, $\Delta M_K$ and $\varepsilon_K$) and find that even imposing only a moderate enhancement of $(\varepsilon'/\varepsilon)_{\rm NP} = 5 \times 10^{-4}$ to explain the current anomaly hinted by the Dual QCD approach and RBC-UKQCD lattice QCD calculations leads to conflicts with experimental upper bounds on rare Kaon processes. They exclude all LQ models with only a single coupling as an explanation of the $\varepsilon'/\varepsilon$ anomaly and put strong-to-serious constraints on parameter spaces of the remaining models. Future results on $K^+\to\pi^+\nu\bar\nu$ from the NA62 collaboration, $K_L\to\pi^0\nu\bar\nu$ from the KOTO experiment and $K_S\to\mu\bar\mu$ from LHCb will even stronger exhibit the difficulty of LQ models in explaining the measured $\varepsilon'/\varepsilon$, in case the $\varepsilon'/\varepsilon$ anomaly will be confirmed by improved lattice QCD calculations. Hopefully also improved measurements of $K_L\to\pi^0\ell\bar\ell$ decays will one day help in this context.Comment: 53 pages, 9 figures; v2: minor extensions, matches published version; v3: corrected eq.(B.10) and figure 2 (right plot U_1,L), conclusions not affecte

Identification and Classification of Power System Faults using Ratio Analysis of Principal Component Distances

Power system reliability operation has been one of the most vital topics under research. The power system network, mostly the long transmission lines is often subjected to different types of faults leading to maloperation of power flow. The idea of a reliable protection system is to most accurately and efficiently identifying the fault, classifying and the locating of fault. This paper represents the application of dynamic phasors in the form of Principal Component Analysis (PCA) to identify fault in a three phase one end fed 150 km long radial power system transmission line. In the proposed work, (1/4) cycle pre-fault and (1/2) cycle post fault line voltages have been extracted from Electromagnetic Transient Programming (EMTP) simulation. The proposed algorithm is trained using only one set of receiving end data carrying out fault only at the midpoint of the line to generate fault signatures using PCA. The eigenvectors and the score matrix thus obtained corresponding to the three phases using the above analysis have been utilized to construct the component distances, which have been analyzed using ratio analysis to extract the similar features of any particular fault individually

Power system fault identification and localization using multiple linear regression of principal component distance indices

This paper is focused on the application of principal component analysis (PCA) to classify and localize power system faults in a three phase, radial, long transmission line using receiving end line currents taken almost at the midpoint of the line length. The PCA scores are analyzed to compute principal component distance index (PCDI) which is further analyzed using a ratio based analysis to develop ratio index matrix (R) and ratio error matrix (RE) and ratio error index (REI) which are used to develop a fault classifier, which produces a 100% correct prediction. The later part of the paper deals with the development of a fault localizer using the same PCDI corresponding to six intermediate training locations, which are analyzed with tool like Multiple Linear Regression (MLR) in order to predict the fault location with significantly high accuracy of only 87 m for a 150 km long radial transmission line

The correct structures of the ortho-cyclized products in the cycloalkylations of 1-m-methoxybenzyl-4,4a,5,6,7,8-hexahydronaphthalen-2(3H)-one and 1-m-methoxybenzyl-octalins: X-ray structure determination of (±)-4-methoxy-9a-carbamorphinan-16-one

The previously assigned (ref.1) ortho-cycloalkylated product from the reaction of 1 and 2 respectively, with ortho-phosphosphoric acid and polyphosphoric acid, has been corrected to (±)-4-methoxy-9a-carbamorphinan-16-one (6) and the respective ether 7 by a single crystal X-ray structure determination of 6

A Comparative Analysis of Application of Genetic Algorithm and Particle Swarm Optimization in Solving Traveling Tournament Problem (TTP)

Traveling Tournament Problem (TTP) has been a major area of research due to its huge application in developing smooth and healthy match schedules in a tournament. The primary objective of a similar problem is to minimize the travel distance for the participating teams. This would incur better quality of the tournament as the players would experience least travel; hence restore better energy level. Besides, there would be a great benefit to the tournament organizers from the economic point of view as well. A well constructed schedule, comprising of diverse combinations of the home and away matches in a round robin tournament would keep the fans more attracted, resulting in turnouts in a large number in the stadiums and a considerable amount of revenue generated from the match tickets. Hence, an optimal solution to the problem is necessary from all respects; although it becomes progressively harder to identify the optimal solution with increasing number of teams. In this work, we have described how to solve the problem using Genetic algorithm and particle swarm optimization

Robust certification of unsharp instruments through sequential quantum advantages in a prepare-measure communication game

Communication games are one of the widely used tools that are designed to demonstrate quantum supremacy over classical resources in which two or more parties collaborate to perform an information processing task to achieve the highest success probability of winning the game. We propose a specific two-party communication game in the prepare-measure scenario that relies on an encoding-decoding task of specific information. We first demonstrate that quantum theory outperforms the classical preparation noncontextual theory and the optimal quantum success probability of such a communication game enables the semi-device-independent certification of qubit states and measurements. Further, we consider the sequential sharing of quantum preparation contextuality and show that, at most, two sequential observers can share the quantum advantage. The suboptimal quantum advantages for two sequential observers form an optimal pair which certifies a unique value of the unsharpness parameter of the first observer. Since the practical implementation inevitably introduces noise, we devised a scheme to demonstrate the robust certification of the states and unsharp measurement instruments of both the sequential observers

Abnormality Detection in ECG Signal applying Poincare and Entropy-based Approaches

Detection of abnormality in heart is of major importance for early and appropriate clinical medication. In this work, we have proposed two models for detection of abnormality in ECG signals. The normal ECG signals are closely repetitive in nature to a large extent, whereas ECG signals with abnormalities tend to differ from cycle to cycle. Hence, repetitive plot like the Poincare is efficient to detect such non-repetitiveness of the signal; thereby, indicating abnormalities. Hence, we have used Poincare plot to develop the two proposed models. One of the models uses direct analysis of the binary image of the plot to detect the difference in retracing, between the healthy and unhealthy samples. The other model uses entropy of the Poincare plot to detect the difference in randomness of plots between the two classes. Most importantly, we have used only lead II ECG signal for analysis. This ensures ease of computation as it uses signal of only a single lead instead of the 12 leads of the complete ECG signal. We have validated the proposed models using ECG signals from the ‘ptb database’. We have observed that the entropy analysis of the Poincare plots gives the best results with 90% accuracy of abnormality detection. This high accuracy of classification, combined with less computational burden enables its practical implementation for the development of a real life abnormality detection schem

Phytochemicals of “Magahi Pan” (Piper betle L. var. magahi) as Potential H+/K+-ATPase Inhibitors: In-Silico Study and ADME Profile

Background and objectives:  in India, peptic ulcer is most prevalent gastrointestinal disease. Historically Piper betle has been used to treat stomach problems. In order to identify the phytochemicals present in Piper betle. L. var magahi LC/MS spectroscopic analysis was performed, following which, potential phytomolecules with H+/K+-ATPase inhibitory activity were chosen using in-silico evaluation. Methods: Phytochemicals in ‘Magahi pan” were investigated and potential H+/K+-ATPase inhibitor phytochemicals that were screened through in-silico analysis and ADME profile of selected phytochemicals were evaluated. Phytochemical characterization was done with the help of LC/MS followed by molecular docking against enzyme H+/K+-ATPase (PDBID:5YLV) using Autodock4.2 and Swiss ADME. The binding affinity, free energy, physicochemical property, saturation of carbon atoms, number of hydrogen bond acceptors-donors, molar refractivity, lipophilicity, water solubility, and drug likeliness property were evaluated in-silico for their predicted bioactivity against H+/K+-ATPase. Results: A total of 67 phytoconstituents were identified through LC/MS positive and negative ionization mode spectral analysis and six were selected on the basis of binding energy. Molecular docking results revealed that the isolated compounds interacted with target protein H+/K+-ATPase with minimum binding energy ranging from (1) netilmicin (-9.29 kcal/mol); (2) benztropine (-9.07 kcal/mol); (3) 5,6,7,3’,4’ pentahydroxyisoflavone (-8.45 kcal/mol); (4) 2-O-acetylpseudolycorine (-8.02 kcal/mol);  (5) R-95913 (-7.73 kcal/mol) and (6) luteolin (-6.93 kcal/mol), respectively. Conclusion: The ADME profile analysis and docking studies revealed 5,6,7,3’,4’ pentahydroxy-isoflavone and luteolin as potential molecules for inhibiting H+/K+-ATPase