arXiv subjects

Kiran Sharma

Publications and source records attributed to Kiran Sharma.

At least 19 recordsLinked to original sources

arXiv2026

Probing T and CP Violation at DUNE and T2HK

We study the sensitivity of the DUNE and T2HK long-baseline experiments to time reversal (T) violation in neutrino oscillations. Rather than the conventional approach of exchanging initial and final neutrino flavors, we search for T violation through the $L$-dependence of the $\nu_\mu \to \nu_e$ transition probability at fixed neutrino energy using neutrino data only. Within the standard three-flavour framework, we show that the DUNE and T2HK together can establish the presence of an $L$-odd component in the oscillation probability at up to $\sim 4\sigma$ significance, with the optimal sensitivity in the energy range $E_\nu \in [0.68, 0.92]$ GeV. The second oscillation maximum of DUNE plays a crucial role in this analysis. We further show that DUNE is more sensitive to T violation that is running in neutrino-only mode, whereas T2HK provides better sensitivity in the conventional neutrino versus anti-neutrino comparison, making the two experiments complementary to each other in search of the CP phase $\delta_{\rm CP}$.

hep-ph↗

arXiv2026

RetraLytix: An Integrated Analytics Dashboard for Mapping Global Trends in Scientific Retractions

Retraction is a correction to scientific literature when there is a major flaw, fraud or misuse of ethical practices in the published work. With the increasing growth of research output, number of retracted studies has also increased, which raises concerns about the issue of research ethics and transparency. Moreover, retraction data coming from several platforms or databases limits its scope in tracking the time-to-time retraction trends. To address this, we propose a web-based integrated platform, called RetraLytix, for easy analysis of distributed retraction data. It automatically integrates retraction data from major databases like Crossref, Retraction Watch and Open Alex and visualizes data in a user interactive centralized platform. It offers a real-time dashboard, comparative analysis, and benchmarking of entities such as countries, institutions, authors, journals and main research areas. RetraLytix helps users to detect trends, retraction patterns, and assess research environment to make data-driven decisions. The system has a potential to become a research integrity tracking and governance tool for researchers, administrators and policymakers.

cs.DL↗

arXiv2026

Automated Classification of Research Papers Toward Sustainable Development Goals: A Boolean Query-Based Computational Framework

The rapid expansion of scholarly publications across diverse disciplines has made it increasingly difficult to systematically evaluate how research contributes to the United Nations Sustainable Development Goals (SDGs). Domain classification of research articles done manually through research experts is extremely impractical because of the number of publications, expensive in time and may not be consistent when done by human beings. This paper proposes an automated and rule-based computational model of classifying research papers based on SDGs with expert curated Boolean query mappings to overcome these challenges. The proposed system has a web-based interface to input data and display results, a backend application programming interface to do high throughput processing, and a Python-based classification engine which uses structured Boolean expressions to process bibliographic metadata (titles, abstracts, and keywords). The framework can be used to support single-paper-based classification and batch-based classification as well as offer clear and understandable outputs that clearly show what query parts motivated each SDG assignment. The experimental testing on massive bibliographic data sets has shown that the system can process thousands of research records in an hour with reproducible and consistent results. The proposed approach provides a viable solution to institutions, researchers and policymakers who are interested in analysis of research alignment with the goal of sustainability in a systematic fashion that would not involve the use of machine learning models whose inputs and outputs are not easily understandable.

cs.DL↗

arXiv2025

Identification of phase correlations in Financial Stock Market Turbulence

The basis of arbitrage methods depends on the circulation of information within the framework of the financial market. Following the work of Modigliani and Miller, it has become a vital part of discussions related to the study of financial networks and predictions. The emergence of the efficient market hypothesis by Fama, Fisher, Jensen and Roll in the early 1970s opened up the door for discussion of information affecting the price in the market and thereby creating asymmetries and price distortion. Whenever the micro and macroeconomic factors change, there is a high probability of information asymmetry in the market, and this asymmetry of information creates turbulence in the market. The analysis and interpretation of turbulence caused by the differences in information is crucial in understanding the nature of the stock market using price patterns and fluctuations. Even so, the traditional approaches are not capable of analyzing the cyclical price fluctuations outside the realm of wave structures of securities prices, and a proper and effective technique to assess the nature of the Financial market. Consequently, the analysis of the price fluctuations by applying the theories and computational techniques of mathematical physics ensures that such cycles are disintegrated, and the outcome of decomposed cycles is elucidated to understand the impression of the information on the genesis and discovery of price and to assess the nature of stock market turbulence. In this regard, the paper will provide a framework of Spectrum analysis that decomposes the pricing patterns and is capable of determining the pricing behavior, eventually assisting in examining the nature of turbulence in the National Stock Exchange of India.

q-fin.ST↗

arXiv2025

T versus CP effects in DUNE and T2HK

Time reversal (T) symmetry violations in neutrino oscillations imply the presence of an $L$-odd component in the transition probability at fixed neutrino energy, with $L$ denoting the distance between neutrino source and detector. Within the standard three-flavour framework, we show that the combination of the transition probabilities determined at the DUNE and T2HK experiments can establish the presence of an $L$-odd component, and therefore provide sensitivity to T violation, up to $4\sigma$ significance. The optimal neutrino energy window is from 0.68 to 0.92 GeV, and therefore a crucial role is played by the low-energy part of the DUNE event spectrum covering the second oscillation maximum. We compare the sensitivity to T violation based on this energy range using neutrino data only with the more traditional search for charge-parity (CP) violation based on the comparison of neutrino versus anti-neutrino beam data. We show that for DUNE it is advantageous to run in neutrino mode only, i.e., searching for T violating effects, whereas T2HK is more sensitive to CP violation, comparing neutrino and anti-neutrino data. Hence, the two experiments offer complementary methods to determine the complex phase in the PMNS mixing matrix.

hep-ph↗

arXiv2025

An analysis of capital market through the lens of integral transforms: exploring efficient markets and information asymmetry

Post Modigliani and Miller (1958), the concept of usage of arbitrage created a permanent mark on the discourses of financial framework. The arbitrage process is largely based on information dissemination amongst the stakeholders operating in the financial market. The advent of the efficient market Hypothesis draws close to the M&M hypothesis. Giving importance to the arbitrage process, which effects the price discovery in the stock market. This divided the market as random and efficient cohort system. The focus was on which information forms a key factor in deciding the price formation in the market. However, the conventional techniques of analysis do not permit the price cycles to be interpreted beyond its singular wave-like cyclical movement. The apparent cyclic measurement is not coherent as the technical analysis does not give sustained result. Hence adaption of theories and computation from mathematical methods of physics ensures that these cycles are decomposed and the effect of the broken-down cycles is interpreted to understand the overall effect of information on price formation and discovery. In order to break the cycle this paper uses spectrum analysis to decompose and understand the above-said phenomenon in determining the price behavior in National Stock Exchange of India (NSE).

q-fin.ST↗

arXiv2025

Signals of eV-scale sterile neutrino at long baseline neutrino experiments

While most of the results of the neutrino oscillation experiments can be accommodated within the standard paradigm of three active flavor, there are tantalizing hints of an light eV-scale sterile neutrino from anomalous results of a few short baseline experiments. This additional light sterile neutrino is expected to leave an imprint on the physics observables pertaining to standard unknowns such as determination of the Dirac-type leptonic $CP$ phase, $δ_{13}$, the question of neutrino mass hierarchy and the octant of $θ_{23}$. The upcoming long baseline neutrino experiments such as T2HK, DUNE and P2O will be sensitive to active - sterile mixing. In the present work, we examine and assess the capability of these long baseline experiments to probe the sterile neutrino at the level of probabilities and event rates. We perform a detailed study by taking into account the values of parameters that are presently allowed and (a) study the impact on $CP$ violation by examining the role played by various appearance and disappearance channels, (b) address the question of disentangling the intrinsic effects from extrinsic effects in the standard paradigm as well as three active plus one light sterile neutrino, and finally (c) assess the ability of these long baseline experiments to distinguish between the two scenarios. Our results indicate that for the true values of sterile parameters and for all values of $δ_{13}$, the sensitivity of P2O is the lowest while the sensitivity of T2HK is modest ($<3\,σ$) and the sensitivity of DUNE is $> 3\,σ$. For larger values of the sterile mixing angles, there is an improvement in the sensitivity for all the three considered experiments.

hep-ph↗

arXiv2025

Assessing Research Impact in Indian Conference Proceedings: Insights from Collaboration and Citations

Conferences serve as a crucial avenue for scientific communication. However, the increase in conferences and the subsequent publication of proceedings have prompted inquiries regarding the research quality being showcased at such events. This investigation delves into the conference publications indexed by Springer's Lecture Notes in Networks and Systems Series. Among the 570 international conferences held worldwide in this series, 177 were exclusively hosted in India. These 177 conferences collectively published 11,066 papers as conference proceedings. All these publications, along with conference details, were sourced from the Scopus database. The study aims to evaluate the research impact of these conference proceedings and identify the primary contributors. The results reveal a downward trend in the average number of citations per year. The collective average citation for all publications is 1.01. Papers co-authored by Indian and international authors (5.6%) exhibit a higher average impact of 1.44, in contrast to those authored solely by Indian authors (84.9%), which have an average impact of 0.97. Notably, Indian-collaborated papers, among the largest contributors, predominantly originate from private colleges and universities. Only 19% of papers exhibit collaboration with institutes of different prestige, yet their impact is considerably higher as compared to collaboration with institutes of similar prestige. This study highlights the importance of improving research quality in academic forums.

cs.IR↗

arXiv2025

Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors

Medical image classification is a vital research area that utilizes advanced computational techniques to improve disease diagnosis and treatment planning. Deep learning models, especially Convolutional Neural Networks (CNNs), have transformed this field by providing automated and precise analysis of complex medical images. This study introduces a hybrid deep learning model that integrates a pre-trained ResNet101 with a custom CNN to classify kidney CT images into four categories: normal, stone, cyst, and tumor. The proposed model leverages feature fusion to enhance classification accuracy, achieving 99.73% training accuracy and 100% testing accuracy. Using a dataset of 12,446 CT images and advanced feature mapping techniques, the hybrid CNN model outperforms standalone ResNet101. This architecture delivers a robust and efficient solution for automated kidney disease diagnosis, providing improved precision, recall, and reduced testing time, making it highly suitable for clinical applications.

eess.IV↗

arXiv2025

Self-Citations in Academic Excellence: Analysis of the Top 1% Highly Cited India-Affiliated Research Papers

Citations demonstrate the credibility, impact, and connection of a paper with the academic community. Self-citations support research continuity but, if excessive, may inflate metrics and raise bias concerns. The aim of the study is to examine the role of self-citations towards the research impact of India. To study this, 3.58 million papers affiliated with India from 1947 to 2024 in the Scopus database were downloaded, and 2.96 million were filtered according to document type and publication year up to 2023. Further filtering based on high citation counts identified the top 1% of highly cited papers, totaling 29,556. The results indicate that the impact of Indian research, measured by highly cited papers, has grown exponentially since 2000, reaching a peak during the 2011-2020 decade. Among the citations received by these 29,556 papers, 6% are self-citations. Papers with a high proportion of self-citations (>90%) are predominantly from recent decades and are associated with smaller team sizes. The findings also reveal that smaller teams are primarily domestic, whereas larger teams are more likely to involve international collaborations. Domestic collaborations dominate smaller team sizes in terms of both self-citations and publications, whereas international collaborations gain prominence as team sizes increase. The results indicate that while domestic collaborations produce a higher number of highly cited papers, international collaborations are more likely to generate self-citations. The top international collaborators in highly cited papers are the USA, followed by UK, and Germany.

cs.DL↗

arXiv2024

Exploring Structural Dynamics in Retracted and Non-Retracted Author's Collaboration Networks: A Quantitative Analysis

Retractions undermine the reliability of scientific literature and the foundation of future research. Analyzing collaboration networks in retracted papers can identify risk factors, such as recurring co-authors or institutions. This study compared the network structures of retracted and non-retracted papers, using data from Retraction Watch and Scopus for 30 authors with significant retractions. Collaboration networks were constructed, and network properties analyzed. Retracted networks showed hierarchical and centralized structures, while non-retracted networks exhibited distributed collaboration with stronger clustering and connectivity. Statistical tests, including $t$-tests and Cohen's $d$, revealed significant differences in metrics like Degree Centrality and Weighted Degree, highlighting distinct structural dynamics. These insights into retraction-prone collaborations can guide policies to improve research integrity.

cs.IR↗

arXiv2024

Quantitative Analysis of IITs' Research Growth and SDG Contributions

The Indian Institutes of Technology (IITs) are vital to India's research ecosystem, advancing technology and engineering for industrial and societal benefits. This study reviews the research performance of top IITs-Bombay, Delhi, Madras, Kharagpur, and Kanpur based on Scopus-indexed publications (1952-2024). Research output has grown exponentially, supported by increased funding and collaborations. IIT-Kanpur excels in research impact, while IIT-Bombay and IIT-Madras are highly productive but show slightly lower per-paper impact. Internationally, IITs collaborate robustly with the USA, Germany, and the UK, alongside Asian nations like Japan and South Korea, with IIT-Madras leading inter-IIT partnerships. Research priorities align with SDG 3 (Health), SDG 7 (Clean Energy), and SDG 11 (Sustainable Cities). Despite strengths in fields like energy, fluid dynamics, and materials science, challenges persist, including limited collaboration with newer IITs and gaps in emerging fields. Strengthening specialization and partnerships is crucial for addressing global challenges and advancing sustainable development.

cs.IR↗

arXiv2024

Hindi audio-video-Deepfake (HAV-DF): A Hindi language-based Audio-video Deepfake Dataset

Deepfakes offer great potential for innovation and creativity, but they also pose significant risks to privacy, trust, and security. With a vast Hindi-speaking population, India is particularly vulnerable to deepfake-driven misinformation campaigns. Fake videos or speeches in Hindi can have an enormous impact on rural and semi-urban communities, where digital literacy tends to be lower and people are more inclined to trust video content. The development of effective frameworks and detection tools to combat deepfake misuse requires high-quality, diverse, and extensive datasets. The existing popular datasets like FF-DF (FaceForensics++), and DFDC (DeepFake Detection Challenge) are based on English language.. Hence, this paper aims to create a first novel Hindi deep fake dataset, named ``Hindi audio-video-Deepfake'' (HAV-DF). The dataset has been generated using the faceswap, lipsyn and voice cloning methods. This multi-step process allows us to create a rich, varied dataset that captures the nuances of Hindi speech and facial expressions, providing a robust foundation for training and evaluating deepfake detection models in a Hindi language context. It is unique of its kind as all of the previous datasets contain either deepfake videos or synthesized audio. This type of deepfake dataset can be used for training a detector for both deepfake video and audio datasets. Notably, the newly introduced HAV-DF dataset demonstrates lower detection accuracy's across existing detection methods like Headpose, Xception-c40, etc. Compared to other well-known datasets FF-DF, and DFDC. This trend suggests that the HAV-DF dataset presents deeper challenges to detect, possibly due to its focus on Hindi language content and diverse manipulation techniques. The HAV-DF dataset fills the gap in Hindi-specific deepfake datasets, aiding multilingual deepfake detection development.

cs.SD↗

arXiv2024

Imprints of LGI violation in Mesons

Quantum mechanics has always proven emphatically as one of the main cornerstones in all of science since its inception. Initially, it has also faced many skeptics from many scientific proponents of its complete description of reality. However, John Bell once devised a theorem on quantitative grounds to show how local realism is expressed in quantum mechanics. As Bell's inequality claims the non-existence of local hidden variable theories, on the same footing, we have Leggett-Garg's Inequality (LGI), which sets a quantum-classical limit for temporally correlated quantum systems. In the context of particle physics, specially in the field of neutrino and meson oscillations, one can conveniently implement LGI to test the quantum foundations at the probability level. Here, we discuss the significant LGI violation characteristics in B- and K- meson oscillations, taking into account their decoherence, CP violation, and decay parameters. We have emphasized the fact that \textit{Tsirelson} bounds can be achieved under certain conditions. Our focal point is to show the signature of these bounds that appears only to specific alterations of decay and decoherence effects. Also, we discuss and comment on the behavior or effect of decoherence and decay widths playing out from the perspective of LGI by taking their available values from various experiments. This may help us to understand the underlying principles and techniques of neutral meson open quantum systems.

hep-ph↗

arXiv2024

Model-independent search for T violation with T2HK and DUNE

We consider the time reversal (T) transformation in neutrino oscillations in a model-independent way by comparing the observed transition probabilities at two different baselines at the same neutrino energy. We show that, under modest model assumptions, if the transition probability $P_{\nu_\mu\to\nu_e}$ around $E_\nu \simeq 0.86$ GeV measured at DUNE is smaller than the one at T2HK the T symmetry has to be violated. Experimental requirements needed to achieve good sensitivity to this test for T violation are to obtain enough statistics at DUNE for $E_\nu \lesssim 1$ GeV (around the 2nd oscillation maximum), good energy resolution (better than 10%), and near-detector measurements with a precision of order 1% or better.

hep-ph↗

arXiv2024

Two Decades of Scientific Misconduct in India: Retraction Reasons and Journal Quality among Inter-country and Intra-country Institutional Collaboration

Research stands as a pivotal factor in propelling the progress of any nation forward. However, if tainted by misconduct, it poses a significant threat to the nation's development. This study aims to scrutinize various cases of deliberate scientific misconduct by Indian researchers. A comprehensive analysis was conducted on 3,244 retracted publications sourced from the Retraction Watch database. The upward trend in retractions is alarming, although the decreasing duration of retractions indicates proactive measures by journals against misconduct. Approximately 60% of retractions stem from private institutions, with fake peer reviews identified as the primary cause of misconduct. This trend could be attributed to incentivizing publication quantity over quality in private institutions, potentially fostering unfair publishing practices. Retractions due to data integrity issues are predominantly observed in public and medical institutions, while retractions due to plagiarism occur in conference proceedings and non-Scopus-indexed journals. Examining retractions resulting from institutional collaborations reveals that 80% originate from within the country, with the remaining 20% being international collaborations. Among inter-country collaborations, one-third of retractions come from the top two journal quartiles, whereas, in intra-country collaborations, half of the retractions stem from Q1 and Q2 journals. Clinical studies retracted from intra-country collaborations are mostly from Q3 and Q4 journals, whereas in inter-country collaborations, they primarily come from Q1 journals. Regarding top journals by the number of retractions in intra-country collaborations, they belong to the Q2 and Q4 categories, whereas in inter-country collaborations, they are in Q1.

cs.DL↗

arXiv2024

Unraveling Retraction Dynamics in COVID-19 Research: Patterns, Reasons, and Implications

Amid the COVID-19 pandemic, while the world sought solutions, some scholars exploited the situation for personal gains through deceptive studies and manipulated data. This paper presents the extent of 400 retracted COVID-19 papers listed by the Retraction Watch database until February 2024. The primary purpose of the research was to analyze journal quality and retraction trends. For all stakeholders involved, such as editors, relevant researchers, and policymakers, evaluating the journal's quality is crucial information since it could help them effectively stop such incidents and their negative effects in the future. The present research results imply that one-fourth of publications were retracted within the first month of their publication, followed by an additional 6\% within six months of publication. One-third of the retractions originated from Q1 journals, with another significant portion coming from Q2 (29.8). A notable percentage of the retracted papers (23.2\%) lacked publishing impact, signifying their publication as conference papers or in journals not indexed by Scopus. An examination of the retraction reasons reveals that one-fourth of retractions were due to numerous causes, mostly in Q2 journals, and another quarter were due to data problems, with the majority happening in Q1 publications. Elsevier retracted 31 of the papers, with the majority published in Q1, followed by Springer (11.5), predominantly in Q2. Retracted papers were mainly associated with the USA, China, and India. In the USA, retractions were primarily from Q1 journals followed by no-impact publications; in China, it was Q1 followed by Q2, and in India, it was Q2 followed by no-impact publications. The study also examined author contributions, revealing that 69.3 were male contributors, with females (30.7) mainly holding middle author positions.

cs.DL↗

arXiv2023

Geometrical Interpretation of Neutrino Oscillation with decay

The geometrical representation of two-flavor neutrino oscillation represents the neutrino's flavor eigenstate as a magnetic moment-like vector that evolves around a magnetic field-like vector that depicts the Hamiltonian of the system. In the present work, we demonstrate the geometrical interpretation of neutrino in a vacuum in the presence of decay, which transforms this circular trajectory of neutrino into a helical track that effectively makes the neutrino system mimic a classical damped driven oscillator. We show that in the absence of the phase factor $ξ$ in the decay Hamiltonian, the neutrino exactly behaves like the system of nuclear magnetic resonance(NMR); however, the inclusion of the phase part introduces a $CP$ violation, which makes the system deviate from NMR. Finally, we make a qualitative discussion on under-damped, critically-damped, and over-damped scenarios geometrically by three different diagrams. In the end, we make a comparative study of geometrical picturization in vacuum, matter, and decay, which extrapolates the understanding of the geometrical representation of neutrino oscillation in a more straightforward way.

hep-ph↗