Magnetic moments of spin {1/2}^+ and spin {3/2}^+ charmed baryons

The magnetic moments of spin ${1/2}{^+}$ and spin ${3/2}{^+}$ charmed baryons have been calculated in chiral constituent quark model ($\chi$CQM). The effects of configuration mixing and quark masses have also been investigated. The results are not only in good agreement with existing experimental data but also show improvement over other phenomenological models.Comment: 5 pages, 2 tables. Presented at the XIII International Conference on Hadron Spectroscopy, Florida State University, Florida, USA, November 29-December 4, 200

Primary Fallopian Tube Cancer - An Incidental Finding in a Young Patient

No Abstract

Bladder Saving Hysterectomy for Placenta Praevia Percreta

Background: Placenta accreta is an abnormally firm attachment of  placental villi to the uterine wall, which may cause postpartum hemorrhage. Placenta Percreta with invasion of the urinary bladder is a rare condition, which carries a high morbidity and mortality risk for mother and fetus.Case Report: The present case is of 26 year old female who was diagnosed as a case of placenta percreta invading bladder during surgery. She was treated by cesarean hysterectomy with bilateral anterior branch of internal iliac artery ligation. The part of placenta adherent to wall of uterus and bladder was left in situ to save bladder. Overall 7 units of blood and 7 units of FFP given to patient preoperatively. Postoperatively methotrexate was given to the patient and followed with HCG levels.Conclusion: A multidisciplinary approach for preoperative, intraoperative, and postoperative management of placenta previa percreta optimizes maternal outcome

SAAGs: Biased stochastic variance reduction methods for large-scale learning

Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, caused by the noisy approximations of the gradients. In this paper, we have proposed novel variants of SAAG-I and II (Stochastic Average Adjusted Gradient) (Chauhan et al. 2017), called SAAG-III and IV, respectively. Unlike SAAG-I, starting point is set to average of previous epoch in SAAG-III, and unlike SAAG-II, the snap point and starting point are set to average and last iterate of previous epoch in SAAG-IV, respectively. To determine the step size, we have used Stochastic Backtracking-Armijo line Search (SBAS) which performs line search only on selected mini-batch of data points. Since backtracking line search is not suitable for large-scale problems and the constants used to find the step size, like Lipschitz constant, are not always available so SBAS could be very effective in such cases. We have extended SAAGs (I, II, III and IV) to solve non-smooth problems and designed two update rules for smooth and non-smooth problems. Moreover, our theoretical results have proved linear convergence of SAAG-IV for all the four combinations of smoothness and strong-convexity, in expectation. Finally, our experimental studies have proved the efficacy of proposed methods against the state-of-art techniques

Faster learning by reduction of data access time

Nowadays, the major challenge in machine learning is the Big Data challenge. The big data problems due to large number of data points or large number of features in each data point, or both, the training of models have become very slow. The training time has two major components: Time to access the data and time to process (learn from) the data. So far, the research has focused only on the second part, i.e., learning from the data. In this paper, we have proposed one possible solution to handle the big data problems in machine learning. The idea is to reduce the training time through reducing data access time by proposing systematic sampling and cyclic/sequential sampling to select mini-batches from the dataset. To prove the effectiveness of proposed sampling techniques, we have used Empirical Risk Minimization, which is commonly used machine learning problem, for strongly convex and smooth case. The problem has been solved using SAG, SAGA, SVRG, SAAG-II and MBSGD (Mini-batched SGD), each using two step determination techniques, namely, constant step size and backtracking line search method. Theoretical results prove the same convergence for systematic sampling, cyclic sampling and the widely used random sampling technique, in expectation. Experimental results with bench marked datasets prove the efficacy of the proposed sampling techniques and show up to six times faster training

Magnetic moments of the low-lying JP= 1/2−J^P=\,1/2^-, 3/2−3/2^- Λ\Lambda resonances within the framework of the chiral quark model

The magnetic moments of the low-lying spin-parity $J^P=$ $1/2^-$, $3/2^-$ $\Lambda$ resonances, like, for example, $\Lambda(1405)$ $1/2^-$, $\Lambda(1520)$ $3/2^-$, as well as their transition magnetic moments, are calculated using the chiral quark model. The results found are compared with those obtained from the nonrelativistic quark model and those of unitary chiral theories, where some of these states are generated through the dynamics of two hadron coupled channels and their unitarization

Population dynamics of natural enemies on bt / non bt cotton and their correlation with weather parameters

The field study was carried out at Research Farm of cotton section, Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India to determine the effect of environmental factors and seven cotton genotypes (Bt and non Bt) on three natural enemies namely chrysoperla, coccinellids beetle and spi-ders. Natural enemies remained active throughout the crop season (with two peaks) with little differences among them. Chrysoperla and coccinellids both were remained active from 25th to 40th SMW (June to October, 2014) while spiders were active from 25th to 41st. It was observed that highest population of Chrysoperla (1.17 eggs/plant) and spiders (1.59 adult/plant) was observed on Bt cotton cultivar namely RCH-134 and JK-1947 respectively. However, coccinellids preferred non Bt genotype (HHH-223) for their population build-up. Chrysoperla and coccinellids popula-tion was significantly negatively correlated with maximum temperature (r = -0.527 at 5% and r = -0.626 at 1% re-spectively); positively correlated with RHm, RHe; negatively correlated with minimum temperature and wind speed without significance. While, spiders population showed negative correlation with all weather parameters except sun-shine hours. It was observed that population of the natural enemies fluctuated under different environmental conditions during cotton season

RECOMMENDATION OF DISTRIBUTION CHANNELS FOR MERCHANT

The present disclosure provides a system and a method for generating recommendations for a new merchant 108 or a seller. The disclosure proposes a recommendation system 110 which collects data from different sources to generate recommendations related to one or more parameters of the new merchant’s interest. In particular, the recommendation system 110 may apply one or more filters such as collaborative filtering and content-based filtering to analyze customer patterns, behaviors and product attributes to generate recommendations regarding best possible locations 112 and distribution channels 114 to the new merchant