arXiv subjects

Raj Shah

Publications and source records attributed to Raj Shah.

6 recordsLinked to original sources

arXiv2026

Charge-dependent atmospheric muon flux at 17 GV geomagnetic cutoff measured with the mini-ICAL prototype

The Iron CALorimeter (ICAL) detector at the India-Based Neutrino Observatory (INO) was conceived as an underground experiment designed to measure atmospheric neutrino oscillation parameters. As part of the R\&D programme, a scaled prototype (mini-ICAL), 85\,ton, approximately 1/600$^{\mathrm{th}}$ the mass of the full detector, was constructed at the IICHEP Transit Campus, Madurai (altitude 150\,m; latitude 9.9372$^\circ$\,N; longitude 78.013$^\circ$\,E; geomagnetic latitude 1.44$^\circ$\,N; vertical cutoff rigidity 17\,GV) and operated between 2018 and 2022. The prototype enabled measurements of charge-dependent cosmic muon spectra in the vicinity of the geomagnetic equator and provided an important validation of detector performance, reconstruction algorithms, and simulation frameworks for the ICAL experiment. Differential fluxes of $\mu^{-}$ and $\mu^{+}$ were measured over the momentum range $\sim$\,1--5\,GeV/c. The obtained momentum spectra are systematically lower than those reported at sites with smaller geomagnetic cutoff rigidities, consistent with the suppression of low- and intermediate-rigidity primary cosmic rays at the 17\,GV cutoff. The measurements are compared with predictions from different hadronic interaction models available in CORSIKA simulations.

hep-ex↗

arXiv2024

Charge ratio of cosmic ray muons in momentum range ~ 1 to 3 GeV/c

This work presents the measurements of the cosmic muon charge ratio as a function of full azimuthal angle and momentum within the range of 0.8 to 3.0 GeV/c, using the mini-ICAL detector. The detector, comprising 10 layers of RPCs, has collected cosmic muon data since August 2018 till recent time, at an altitude of 160 m above sea level at the Inter-Institutional Center for High Energy Physics in Madurai, India $(9^\circ56'\,N, 78^\circ00'\,E)$. The muon charge identification is achieved through the use of a magnetic field of strength 1.4 T. The analysis shows that the cosmic muon charge ratio, $R_\mu = N_{\mu^+}/N_{\mu^-}$, ranges from 1.1 to 1.2 and has small dependency on the zenith angle. The charge ratio's dependence on momentum and azimuthal angle is thoroughly examined for a wide range of zenith angle upto $50^\circ$. These measurements are compared with the predictions from various combinations of different hadronic models in CORSIKA extensive air shower simulations.

hep-ex↗

arXiv2024

Expected Performance of Cosmic Muon Veto Detector

The India-Based Neutrino Observatory (INO) collaboration houses the miniICAL detector, at the transit campus of IICHEP, Madurai, India, which serves as a prototype-detector of the larger Iron-Calorimeter detector (ICAL). The purpose of miniICAL lies in unraveling the intricate engineering challenges inherent in constructing a substantial ICAL-type detector. To explore the feasibility of building a large-scale neutrino experiment at shallow depths the collaboration has embarked upon the construction of a Cosmic Muon Veto Detector (CMVD) around the miniICAL detector. The primary objective of this endeavor revolves around attaining a veto efficiency surpassing $99.99\%$, while simultaneously maintaining a false-positive rate lower than $10^{-5}$. The CMVD system is based on extruded plastic scintillators (EPS) and utilizes wavelength-shifting fibers to collect scintillation photons and uses silicon photomultipliers (SiPMs) as photo-transducers. The expected performance of the CMVD is estimated using simulated muon tracks in the miniICAL stack taking into account efficiency, multiplicity of RPC detectors from the miniICAL data as well as the noise of SiPM, observed SiPM spectra and time resolution due to cosmic muon along the whole length of EPS etc. The CMVD experiment is a crucial step in the larger context of neutrino research, by increasing the veto efficiency of cosmic muons, the CMVD experiment helps to pave the way for future large-scale shallow-depth neutrino experiments, providing valuable insights into the study of neutrinos and their properties.

hep-ex↗

arXiv2022

VaultDB: A Real-World Pilot of Secure Multi-Party Computation within a Clinical Research Network

Electronic health records represent a rich and growing source of clinical data for research. Privacy, regulatory, and institutional concerns limit the speed and ease of sharing this data. VaultDB is a framework for securely computing SQL queries over private data from two or more sources. It evaluates queries using secure multiparty computation: cryptographic protocols that evaluate a function such that the only information revealed from running it is the query answer. We describe the development of a HIPAA-compliant version of VaultDB on the Chicago Area Patient Centered Outcomes Research Network (CAPriCORN). This multi-institutional clinical research network spans the electronic health records of nearly 13M patients over hundreds of clinics and hospitals in the Chicago metropolitan area. Our results from deploying at three health systems within this network show its efficiency and scalability for distributed clinical research analyses without moving patient records from their site of origin.

cs.DB↗

arXiv2022

JARVix at SemEval-2022 Task 2: It Takes One to Know One? Idiomaticity Detection using Zero and One-Shot Learning

Large Language Models have been successful in a wide variety of Natural Language Processing tasks by capturing the compositionality of the text representations. In spite of their great success, these vector representations fail to capture meaning of idiomatic multi-word expressions (MWEs). In this paper, we focus on the detection of idiomatic expressions by using binary classification. We use a dataset consisting of the literal and idiomatic usage of MWEs in English and Portuguese. Thereafter, we perform the classification in two different settings: zero shot and one shot, to determine if a given sentence contains an idiom or not. N shot classification for this task is defined by N number of common idioms between the training and testing sets. In this paper, we train multiple Large Language Models in both the settings and achieve an F1 score (macro) of 0.73 for the zero shot setting and an F1 score (macro) of 0.85 for the one shot setting. An implementation of our work can be found at https://github.com/ashwinpathak20/Idiomaticity_Detection_Using_Few_Shot_Learning.

cs.CL↗

arXiv2019

Targeting glutamate metabolism in melanoma

The glutamate metabotropic receptor 1 (GRM1) drives oncogenesis when aberrantly activated in melanoma and several other cancers. Metabolomics reveals that patient-derived xenografts with GRM1-positive melanoma tumors exhibit elevated plasma glutamate levels associated with metastatic melanoma in vivo. Stable isotope tracing and GCMS analysis determined that cells expressing GRM1 fuel a substantial fraction of glutamate from glycolytic carbon. Stimulation of GRM1 by glutamate leads to activation of mitogenic signaling pathways, which in turn increases the production of glutamate, fueling autocrine feedback. Implementing a rational drug-targeting strategy, we critically evaluate metabolic bottlenecks in vitro and in vivo. Combined inhibition of glutamate secretion and biosynthesis is an effective rational drug targeting strategy suppressing tumor growth and restricting tumor bioavailability of glutamate.

q-bio.QM↗