Jet Identification with Zest

We present a new observable zest and demonstrate its potential to differentiate between jets originated by gluons, top quark and vector bosons. Zest has salient properties such as boost invariance, stability against global color flow of partons and inclusion or exclusion of a few soft particles to the jet. For a gluon jet, zest distribution is also insensitive to the jet mass. We show that when zest is used in conjunction with other observables, it can yield high gluon rejection while retaining high signal sample.Comment: 3 pages, 5 figures, XXII DAE-BRNS Symposium Proceeding

Experimental demonstration of 25 GHz wideband chaos in symmetric dual port EDFRL

We study dynamics of chaos in dual port erbium-doped fiber ring laser (EDFRL). The laser consists of two erbium-doped fibers, intracavity filters at 1549.30 nm, isolators, and couplers. At both ports, the laser transitions into the chaotic regime for pump currents greater than 100 mA via period doubling route. We calculate the Lyapunov exponents using Rosenstein’s algorithm. We obtain positive values for the largest Lyapunov exponent (≈0.2) for embedding dimensions 5, 7, 9 and 11 indicating chaos. We compute the power spectrum of the photocurrents at the output ports of the laser. We observe a bandwidth of ≈ 25 GHz at both ports. This ultra wideband nature of chaos obtained has potential applications in high speed random number generation and communication

One-loop Angularity Distributions with Recoil using Soft-Collinear Effective Theory

Angularities are event shapes whose sensitivity to the splitting angle of a collinear emission is controlled by a continuous parameter $b$, with $-1 < b < \infty$. When measured with respect to the thrust axis, this class of QCD observables includes thrust ($b=1$) and jet broadening ($b=0$), the former being insensitive to the recoil of soft against collinear radiation, while the latter being maximally sensitive to it. Presently available analytic results for angularity distributions with $b \neq 0$ can be applied only close to the thrust limit since recoil effects have so far been neglected. As a first step to establish a comprehensive theoretical framework based on Soft-Collinear Effective Theory valid for all recoil-sensitive angularities, we compute for the first time angularity distributions at one-loop order in $\alpha_s$ for all values of $b$ taking into account recoil effects. In the differential cross section, these amount to novel sub-leading singular contributions and/or power corrections, where the former are characterized by fractional powers of the angularity and contribute appreciably close to the peak region, also for $b \gtrsim 0.5$. Our calculations are checked against various limits known in the literature and agree with the numerical output of the Event2 generator.Comment: 45 pages, 7 figures, v2: improved discussion, version accepted for publication in JHE

Feed Forward Artificial Neural Network: Tool for Early Detection of Ovarian Cancer

Pathological changes in an organ or tissue may be reflected in proteomic patterns in serum. The early detection of cancer is crucial for successful treatment. Some cancers affect the concentration of certain molecules in the blood, which allows early diagnosis by analyzing the blood mass spectrum. It is possible that exclusive serum proteomic patterns could be used to differentiate cancer samples from non-cancer ones. Several techniques have been developed for the analysis of mass-spectrum curve, and use them for the detection of prostate, ovarian, breast, bladder, pancreatic, kidney, liver, and colon cancers. In present study, we applied data mining to the diagnosis of ovarian cancer and identified the most informative points of the mass-spectrum curve, then used student t-test and neural networks to determine the differences between the curves of cancer patients and healthy people. Two serum SELDI MS data sets were used in this research to identify serum proteomic patterns that distinguish the serum of ovarian cancer cases from non-cancer controls. Statistical testing and genetic algorithm-based methods are used for feature selection respectively. The results showed that (1) data mining techniques can be successfully applied to ovarian cancer detection with a reasonably high performance; (2) the discriminatory features (proteomic patterns) can be very different from one selection method to another

Optimization of Cultural Conditions for the Production of Antibiotic by Streptomyces sp. VRY-1

Streptomyces sp. VRY-1 was screened for its bioactive potentials against various pathogenic microorganisms and was found to possess antibacterial activity against Salmonella typhimurium&nbsp; (drug resistant strain of bacteria) and various other pathogenic bacteria and fungi. Optimization of cultural conditions for production of antibiotic showed that maximum antibiotic production occurred on 10th day in stationary cultural, 28Ëš C, 8.0 pH, liver extract, 1.5%(w/v) glucose. The bioactive compound was found to be soluble in water and ethyl acetate