Pion-kaon femtoscopy in Pb−-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}}=2.76 TeV measured with ALICE

Femtoscopic correlations between charged pions and kaons for different charge combinations are measured in Pb$-$Pb collisions at $\sqrt{s_{\rm NN}}=2.76$ TeV with ALICE at the LHC. The three-dimensional pion-kaon ($\pi-{\rm K}$) correlation functions and double ratios in the out-side-long pair rest frame are studied in different centrality bins. The $\pi-{\rm K}$ femtoscopic source size parameter ($R_{\rm out}$) and emission asymmetry ($\mu_{\rm out}$) are extracted. It is observed that the average source size of the system and the emission asymmetry between pions and kaons increase from peripheral to central events.Comment: 4 pages, 4 figures, Proceedings of XXVIIth International Conference on Ultrarelativistic Nucleus-Nucleus Collisions (Quark Matter 2018

Non-identical particle femtoscopy in Pb−-Pb collisions at sNN=2.76 \mathbf{\sqrt{{\textit s}_{\rm NN}}}=2.76 TeV measured with ALICE

Two-particle femtoscopic correlations between non-identical charged particles for different charge combinations are measured in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 2.76 TeV with ALICE at the LHC. The three-dimensional two-particle correlation functions are studied in different centrality bins. The femtoscopic source size parameter ($R_{Out}$) and emission asymmetry ($\mu$) are extracted. It is observed that the average source size of the system and emission asymmetry between particles increase from peripheral to central events.Comment: 3 pages, 2 figures, Proceedings of XXXIX International Conference on High Energy Physics (ICHEP 2018

Functional Analysis of Genomic Variation and Impact on Molecular and Higher Order Phenotypes

Reverse genetics methods, particularly the production of gene knockouts and knockins, have revolutionized the understanding of gene function. High throughput sequencing now makes it practical to exploit reverse genetics to simultaneously study functions of thousands of normal sequence variants and spontaneous mutations that segregate in intercross and backcross progeny generated by mating completely sequenced parental lines. To evaluate this new reverse genetic method we resequenced the genome of one of the oldest inbred strains of mice—DBA/2J—the father of the large family of BXD recombinant inbred strains. We analyzed ~100X wholegenome sequence data for the DBA/2J strain, relative to C57BL/6J, the reference strain for all mouse genomics and the mother of the BXD family. We generated the most detailed picture of molecular variation between the two mouse strains to date and identified 5.4 million sequence polymorphisms, including, 4.46 million single nucleotide polymorphisms (SNPs), 0.94 million intersections/deletions (indels), and 20,000 structural variants. We systematically scanned massive databases of molecular phenotypes and ~4,000 classical phenotypes to detect linked functional consequences of sequence variants. In majority of cases we successfully recovered known genotype-to-phenotype associations and in several cases we linked sequence variants to novel phenotypes (Ahr, Fh1, Entpd2, and Col6a5). However, our most striking and consistent finding is that apparently deleterious homozygous SNPs, indels, and structural variants have undetectable or very modest additive effects on phenotypes

Weibull Distribution and the multiplicity moments in pp (ppˉ)pp\,(p\bar{p}) collisions

A higher moment analysis of multiplicity distribution is performed using the Weibull description of particle production in $pp\,(p\bar{p})$ collisions at SPS and LHC energies. The calculated normalized moments and factorial moments of Weibull distribution are compared to the measured data. The calculated Weibull moments are found to be in good agreement with the measured higher moments (up to 5$^{\rm{th}}$ order) reproducing the observed breaking of KNO scaling in the data. The moments for $pp$ collisions at $\sqrt{s}$ = 13 TeV are also predicted.Comment: 5 pages, 3 figure

Response surface and artificial neural network simulation for process design to produce L-lysine by Corynebacterium glutamicum NCIM 2168

269-279The L-lysine is one of the most important essential amino acid used in food and pharmaceutical industries. The present investigation was conducted to optimize the L-lysine production by Corynebacterium glutamicum (NCIM 2168). The production parameters such as the temperature, pH and glucose concentration (g/l) were optimised and evaluated by simulation method to develop a suitable model. The experimental design was done using central composite design (CCD). Total 20 set of experiments were performed according to the CCD. The factors and their responses were analysed by using the statistical tools: response surface methodology (RSM) and artificial neural network (ANN) linked with genetic algorithm (GA). The predicted optimum production of L-lysine was 19.003 g/l and 28.363 g/l by CCD-RSM and ANN-GA respectively. During validation by GA under optimized conditions, the L-lysine production was found to be 27.25 ± 1.15 g/l, which was significantly high than that obtained using CCD-RSM optimization method. The ANN coupled with GA was found to be a powerful tool for optimizing production parameters with high level of accuracy. This technique may be used for other fermentation products to optimize the important process parameters before scaling up the process to industrial level

Efficacy of Fungicides for Control of White Mold (Sclerotinia sclerotiorum Lib.) De Bary in Lima Bean

White mold of lima bean (Phaseolous lunatus) caused by Sclerotinia sclerotiorum is a major disease in India. Isolates of the pathogen from different region of Uttar Pradesh were assayed both in vitro and in the greenhouse (in vivo) for their sensitivity to eight commercially available fungicides, viz., dithiocarbamic acid, carbendazim, ziram, phenylthiourea, carboxin + dithiocarbamic acid, difenoconazole, hydrogen sulphide, and mancozeb. Phenylthiourea and difenoconazole were found to be most effective and these inhibited radial growth of the test organism a level of to 71.5% and 70.5%, respectively. These two fungicides were also found as most promising in controlling the disease under greenhouse conditions, reducing disease severity to 0.14% and 0.22%, respectively compared to the control where it was 18.9%

Time-domain Ad-hoc Array Speech Enhancement Using a Triple-path Network

Deep neural networks (DNNs) are very effective for multichannel speech enhancement with fixed array geometries. However, it is not trivial to use DNNs for ad-hoc arrays with unknown order and placement of microphones. We propose a novel triple-path network for ad-hoc array processing in the time domain. The key idea in the network design is to divide the overall processing into spatial processing and temporal processing and use self-attention for spatial processing. Using self-attention for spatial processing makes the network invariant to the order and the number of microphones. The temporal processing is done independently for all channels using a recently proposed dual-path attentive recurrent network. The proposed network is a multiple-input multiple-output architecture that can simultaneously enhance signals at all microphones. Experimental results demonstrate the excellent performance of the proposed approach. Further, we present analysis to demonstrate the effectiveness of the proposed network in utilizing multichannel information even from microphones at far locations.Comment: Accepted for publication in INTERSPEECH 202