Search

In this article, we probe the trilinear R-parity violating (RPV) supersymmetric (SUSY) scenarios with specific non-zero interactions in the light of neutrino oscillation, Higgs, and flavor observables. We attempt to fit the set of observables using a state-of-the-art Markov Chain Monte Carlo (MCMC) set-up and study its impact on the model parameter space. Our main objective is to constrain the trilinear couplings individually, along with some other SUSY parameters relevant to the observables. We present the constrained parameter regions in the form of marginalized posterior distributions on different two-dimensional parameter planes. We perform our analyses with two different scenarios characterized by our choices for the lightest SUSY particle (LSP), bino, and stop. Our results indicate that the lepton number violating trilinear couplings $\lambda_{i33}$ ($i$=1,2) and $\lambda_{j33}^{\prime}$ ($j$=1,2,3) can be at most of the order of $10^{-4}$ or even smaller while $\tan\beta$ is restricted to below 15 even when $3\sigma$ allowed regions are considered. We further comment on the possible LHC signatures of these LSPs focusing on and around the best-fit regions., Comment: 41 pages, 9 figures and 8 tables

We study the asymmetric interaction of wave-like velocity perturbation with a coronal current sheet (CS) in the presence of resistivity, thermal conduction (TC) and radiative cooling (RC). We analyze the dynamics and energetics of CS in four cases, namely, (i) no energy loss, (ii) TC only, (iii) RC only and, (iv) TC+RC. Before fragmentation, thinning and elongation of the CS are found to be identical in all four cases and therefore independent of presence or absence of energy loss effects. Onset times, corresponding Lundquist numbers and aspect ratios suggest that TC advances the onset of fragmentation while RC has the opposite effect in comparison to absence of energy losses. Reconnection takes place at a higher rate in presence of TC and TC+RC in the tearing unstable CS. The speed of plasmoids are also found to be higher under the effect of TC and TC+RC. In presence of TC and TC+RC, average density becomes higher within the tearing unstable CS than in other two cases. As expected, estimated average temperature is increasing with highest and lowest rate in absence of energy losses and in presence of both TC and RC respectively. After the onset of fragmentation, the rate of decrement of average magnetic energy density and increment of average kinetic energy density becomes higher in presence of TC and TC+RC than in other two cases. Thus we conclude that presence of energy loss mechanisms critically influence the dynamics, energetics, and plasmoid formation within a reconnecting coronal CS., Comment: 17 pages, 7 figures, Accepted for publication in The Astrophysical Journal

The observable cosmos exhibits sizable baryon asymmetry, small active neutrino masses, and the presence of dark matter (DM). To address these phenomena together, we propose a two component DM scenario in an extension of Scotogenic model, imposing $\mathbb{Z}_2 \otimes \mathbb{Z}_2^{\prime}$ symmetry. The electroweak sphaleron process converts the $\rm Y_{B-L}^{}$ yield, generated through the Leptogenesis mechanism, into the baryon asymmetry ($\rm Y_{\Delta B}^{}$) at $T_{\rm sph}\sim 131.7$ GeV, the sphalerons decoupling temperature. In this framework, the CP asymmetry as well as the radiative neutrino mass generation explicitly involve the two DM particles, thus establishing a correlation between the baryon asymmetry, DM and observed active neutrino masses. We study in details the allowed parameter space available after considering all the constraints from the three phenomena as well as from the collider search limits, and outline the region which could potentially be tested in future DM detection experiments through direct or indirect detection searches, lepton flavor-violating decays, etc., Comment: 30 pages, 14 figures

We provide a possible interpretation of excesses reported by ATLAS and CMS at around 95GeV, 650GeV and possibly 320GeV, in terms of CP-even scalars. In particular, the combined {\sl global} statistical significances of independent indications for a 650GeV object reach the $4\sigma$ level! While this seems sufficient incentive for a further investigation, this object cannot be fitted in tradional singlet or doublet extensions of the Standard Model. It requires by itself a larger extension with doubly-charged scalars, that naturally fits the two other excesses on top of the SM-like 125~GeV Higgs. We describe the minimal model and give some numerical illustrations., Comment: To appear in the proceedings of the 29th International Symposium on Particles, Strings and Cosmology (PASCOS 2024) in Quy Nhon, Vietnam, 7-13 July, 2024

Nanoflares are believed to be key contributors to heating solar non-flaring active regions, though their individual detection remains challenging. This study uses a data-driven field-aligned hydrodynamic model to examine nanoflare properties throughout the lifecycle of AR12758. We simulate coronal loop emissions, where each loop is heated by random nanoflares depending on the loop parameters derived from photospheric magnetograms observed by SDO/HMI. Simulated X-ray flux and temperature can reproduce the temporal variations observed by Chandrayaan-2/XSM. Our findings show that high-frequency nanoflares contribute to cool emissions across the AR, while low- and intermediate- frequency primarily contribute to hot emissions. During the emerging phase, energy deposition is dominated by low-frequency events. Post-emergence, energy is deposited by both low- and intermediate-frequency nanoflares, while as the AR ages, the contribution from intermediate- and high-frequency nanoflares increases. The spatial distribution of heating frequencies across the AR reveals a clear pattern: the core of the active region spends most of its time in a low-frequency heating state, the periphery is dominated by high-frequency heating, and the region between the core and periphery experiences intermediate-frequency heating., Comment: Accepted for publication in the Astrophysical Journal (ApJ)

We present a measurement of the branching fraction and fraction of longitudinal polarization of $B^0 \to \rho^+ \rho^-$ decays, which have two $\pi^0$'s in the final state. We also measure time-dependent $CP$ violation parameters for decays into longitudinally polarized $\rho^+ \rho^-$ pairs. This analysis is based on a data sample containing $(387\pm6) \times 10^6$ \BBbar pairs collected with the Belle~II detector at the SuperKEKB asymmetric-energy $e^+e^-$ collider in 2019-2022. We obtain ${B}(B^0\to\rho^+\rho^-) = (2.88 ^{+0.23}_{-0.22} {}^{+0.29}_{-0.27}) \times 10^{-5}, f_{L} = 0.921 ^{+0.024}_{-0.025} {}^{+0.017}_{-0.015}$, $S = -0.26\pm0.19\pm0.08$, and $C = -0.02\pm0.12^{+0.06}_{-0.05}$, where the first uncertainties are statistical and the second are systematic. We use these results to perform an isospin analysis to constrain the CKM angle $\phi_2$ and obtain two solutions; the result consistent with other Standard Model constraints is $\phi_2 = (92.6^{+4.5}_{-4.8})^\circ$.

Kidney stones are a common and debilitating health issue, and genetic factors play a crucial role in determining susceptibility. While Genome-Wide Association Studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) linked to kidney stone risk, translating these findings into effective clinical tools remains a challenge. In this study, we explore the potential of deep learning techniques, particularly Convolutional Neural Networks (CNNs), to enhance Polygenic Risk Score (PRS) models for predicting kidney stone susceptibility. Using a curated dataset of kidney stone-associated SNPs from a recent GWAS, we apply CNNs to model non-linear genetic interactions and improve prediction accuracy. Our approach includes SNP selection, genotype filtering, and model training using a dataset of 560 individuals, divided into training and testing subsets. We compare our CNN-based model with traditional machine learning models, including logistic regression, random forest, and support vector machines, demonstrating that the CNN outperforms these models in terms of classification accuracy and ROC-AUC. The proposed model achieved a validation accuracy of 62%, with an ROC-AUC of 0.68, suggesting its potential for improving genetic-based risk prediction for kidney stones. This study contributes to the growing field of genomics-driven precision medicine and highlights the promise of deep learning in enhancing PRS models for complex diseases.

We present the first search for the lepton flavor-violating decay modes $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp~(\ell=\mu, e)$ using the 711 fb$^{-1}$ and 365 fb$^{-1}$ data samples recorded by the Belle and Belle II detectors, respectively. We use a hadronic $B$-tagging technique, and search for the signal decay in the system recoiling against the fully reconstructed $B$ meson. We find no evidence for $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp$ decays and set 90\% confidence level upper limits on the branching fractions in the range of $[0.8,\,3.6]\times10^{-5}$.

Gender diversity enhances research by bringing diverse perspectives and innovative approaches. It ensures equitable solutions that address the needs of diverse populations. However, gender disparity persists in research where women remain underrepresented, which might limit diversity and innovation. Many even leave scientific careers as their contributions often go unnoticed and undervalued. Therefore, understanding gender-based contributions and collaboration dynamics is crucial to addressing this gap and creating a more inclusive research environment. In this study, we analyzed 2,000 articles published over the past decade in the Journal of Systems and Software (JSS). From these, we selected 384 articles that detailed authors' contributions and contained both female and male authors to investigate gender-based contributions. Our contributions are fourfold. First, we analyzed women's engagement in software systems research. Our analysis showed that only 32.74% of the total authors are women and female-led or supervised studies were fewer than those of men. Second, we investigated female authors' contributions across 14 major roles. Interestingly, we found that women contributed comparably to men in most roles, with more contributions in conceptualization, writing, and reviewing articles. Third, we explored the areas of software systems research and found that female authors are more actively involved in human-centric research domains. Finally, we analyzed gender-based collaboration dynamics. Our findings revealed that female supervisors tended to collaborate locally more often than national-level collaborations. Our study highlights that females' contributions to software systems research are comparable to those of men. Therefore, the barriers need to be addressed to enhance female participation and ensure equity and inclusivity in research.

The BL Lacertae object VER J0521+211 underwent a notable flaring episode in February 2020. A short-term monitoring campaign, led by the MAGIC (Major Atmospheric Gamma Imaging Cherenkov) collaboration, covering a wide energy range from radio to very-high-energy (VHE, 100 GeV < E < 100 TeV) gamma rays was organised to study its evolution. These observations resulted in a consistent detection of the source over six consecutive nights in the VHE gamma-ray domain. Combining these nightly observations with an extensive set of multiwavelength data made modelling of the blazar's spectral energy distribution (SED) possible during the flare. This modelling was performed with a focus on two plausible emission mechanisms: i) a leptonic two-zone synchrotron-self-Compton scenario, and ii) a lepto-hadronic one-zone scenario. Both models effectively replicated the observed SED from radio to the VHE gamma-ray band. Furthermore, by introducing a set of evolving parameters, both models were successful in reproducing the evolution of the fluxes measured in different bands throughout the observing campaign. Notably, the lepto-hadronic model predicts enhanced photon and neutrino fluxes at ultra-high energies (E > 100 TeV). While the photon component, generated via decay of neutral pions, is not directly observable as it is subject to intense pair production (and therefore extinction) through interactions with the cosmic microwave background photons, neutrino detectors (e.g. IceCube) can probe the predicted neutrino component. Finally, the analysis of the gamma-ray spectra, as observed by MAGIC and the Fermi-LAT telescopes, yielded a conservative 95\% confidence upper limit of z \leq 0.244 for the redshift of this blazar., Comment: Accepted for publication in A&A

The study involves characterizations of dual pairs of frames which are optimal to handle erasures among all dual pairs for a finite dimensional Hilbert space. A new optimality measure using the Frobenius norm of the error operator has been introduced and the corresponding optimal dual pairs have been analyzed for any number of erasures. Also, other measures of the error operator, namely the spectral radius and the numerical radius, have been considered for the analysis. Besides, explicit construction of certain optimal dual pairs has been provided.

Detecting and tracking code clones can ease various software development and maintenance tasks when changes in a code fragment should be propagated over all its copies. Several deep learning-based clone detection models have appeared in the literature for detecting syntactic and semantic clones, widely evaluated with the BigCloneBench dataset. However, class imbalance and the small number of semantic clones make BigCloneBench less ideal for interpreting model performance. Researchers also use other datasets such as GoogleCodeJam, OJClone, and SemanticCloneBench to understand model generalizability. To overcome the limitations of existing datasets, the GPT-assisted semantic and cross-language clone dataset GPTCloneBench has been released. However, how these models compare across datasets remains unclear. In this paper, we propose a multi-step evaluation approach for five state-of-the-art clone detection models leveraging existing benchmark datasets, including GPTCloneBench, and using mutation operators to study model ability. Specifically, we examine three highly-performing single-language models (ASTNN, GMN, CodeBERT) on BigCloneBench, SemanticCloneBench, and GPTCloneBench, testing their robustness with mutation operations. Additionally, we compare them against cross-language models (C4, CLCDSA) known for detecting semantic clones. While single-language models show high F1 scores for BigCloneBench, their performance on SemanticCloneBench varies (up to 20%). Interestingly, the cross-language model (C4) shows superior performance (around 7%) on SemanticCloneBench over other models and performs similarly on BigCloneBench and GPTCloneBench. On mutation-based datasets, C4 has more robust performance (less than 1% difference) compared to single-language models, which show high variability., Comment: Accepted at the 40th IEEE International Conference on Software Maintenance and Evolution (ICSME 2024)

We measure the branching fraction and $\it CP$-violating flavor-dependent rate asymmetry of $B^{0} \to \pi^{0} \pi^{0}$ decays reconstructed using the Belle II detector in an electron-positron collision sample containing $387 \times 10^{6}$ $B\overline{B}$ pairs. Using an optimized event selection, we find $126\pm 20$ signal decays in a fit to background-discriminating and flavor-sensitive distributions. The resulting branching fraction is $(1.25 \pm 0.23)\times 10^{-6}$ and the $\it CP$-violating asymmetry is $0.03 \pm 0.30$.

In deep-inelastic positron-proton scattering, the lepton-jet azimuthal angular asymmetry is measured using data collected with the H1 detector at HERA. When the average transverse momentum of the lepton-jet system, $\lvert \vec{P}_\perp \rvert $, is much larger than the total transverse momentum of the system, $\lvert \vec{q}_\perp \rvert$, the asymmetry between parallel and antiparallel configurations, $\vec{P}_\perp$ and $\vec{q}_\perp$, is expected to be generated by initial and final state soft gluon radiation and can be predicted using perturbation theory. Quantifying the angular properties of the asymmetry therefore provides an additional test of the strong force. Studying the asymmetry is important for future measurements of intrinsic asymmetries generated by the proton's constituents through Transverse Momentum Dependent (TMD) Parton Distribution Functions (PDFs), where this asymmetry constitutes a dominant background. Moments of the azimuthal asymmetries are measured using a machine learning method for unfolding that does not require binning., Comment: 15 pages, 4 figures, 2 tables, updated affiliations and acknowledgements

Let $E$ be an elliptic curve with $j$-invariant $0$ or $1728$ and let $\widetilde{E}$ be a $k^{th}$ twist of $E$. We show that for any prime $p$ of good reduction of $\widetilde{E}$, a degree $k$ relative $p$-class group and the root number of $\widetilde{E}$ determines the dimension of the $p$-Selmer group of $\widetilde{E}$. As a consequence, we construct families of large rank $p$-class group. We also relate congruent number and cube sum problem with relative $p$-class group.

We measure the branching fraction of the decay $B^0 \to J/\psi \omega$ using data collected with the Belle II detector at the SuperKEKB collider. The data contain $(387 \pm 6) \times 10^6$ $B\overline{B}$ meson pairs produced in energy-asymmetric $e^+e^-$ collisions at the $\Upsilon (4S)$ resonance. The measured branching fraction $\mathcal{B}(B^0 \to J/\psi \omega) = \left( 2.16 \pm 0.30 \pm 0.14 \right) \times 10^{-5}$, where the first uncertainty is statistical and the second is systematic, is more precise than previous results and constitutes the first observation of the decay with a significance of $6.5$ standard deviations.

Probing higgsinos remains a challenge at the LHC owing to their small production cross-sections and the complexity of the decay modes of the nearly mass degenerate higgsino states. The existing limits on higgsino mass are much weaker compared to its bino and wino counterparts. This leaves a large chunk of sub-TeV supersymmetric parameter space unexplored so far. In this work, we explore the possibility of probing higgsino masses in the 400 - 1000 GeV range. We consider a simplified supersymmetric scenario where R-Parity is violated through a baryon number violating trilinear coupling. We adopt a machine learning-based top tagger to tag the boosted top jets originating from higgsinos, and for our collider analysis, we use a BDT classifier to discriminate signal over SM backgrounds. We construct two signal regions characterized by at least one top jet and different multiplicities of $b$-jets and light jets. Combining the statistical significance obtained from the two signal regions, we show that higgsino mass as high as 925 GeV can be probed at the high luminosity LHC., Comment: 18 pages, 8 Figures, 3 Tables

The second Hot QCD Matter 2024 conference at IIT Mandi focused on various ongoing topics in high-energy heavy-ion collisions, encompassing theoretical and experimental perspectives. This proceedings volume includes 19 contributions that collectively explore diverse aspects of the bulk properties of hot QCD matter. The topics encompass the dynamics of electromagnetic fields, transport properties, hadronic matter, spin hydrodynamics, and the role of conserved charges in high-energy environments. These studies significantly enhance our understanding of the complex dynamics of hot QCD matter, the quark-gluon plasma (QGP) formed in high-energy nuclear collisions. Advances in theoretical frameworks, including hydrodynamics, spin dynamics, and fluctuation studies, aim to improve theoretical calculations and refine our knowledge of the thermodynamic properties of strongly interacting matter. Experimental efforts, such as those conducted by the ALICE and STAR collaborations, play a vital role in validating these theoretical predictions and deepening our insight into the QCD phase diagram, collectivity in small systems, and the early-stage behavior of strongly interacting matter. Combining theoretical models with experimental observations offers a comprehensive understanding of the extreme conditions encountered in relativistic heavy-ion and proton-proton collisions., Comment: Compilation of the 19 contributions in Bulk Matter presented at the second 'Hot QCD Matter 2024 Conference' held from July 1-3, 2024, organized by IIT Mandi, Himachal Pradesh, India

We discuss the structure of microcanonical ensembles in inertial and non-inertial frames attached to a confined system of positive energy particles in curved spacetime. Under certain physically reasonable assumptions that ensure the existence of such ensembles, we derive two generic characteristics of the leading curvature corrections: (1) they are characterized by Ricci and Einstein tensors, and (2) their contribution is proportional to the boundary area of the system. We also obtain exact analytical results for microcanonical ensembles in de Sitter spacetime, which reproduce the perturbative results in the limit $\Lambda \to 0$, but have interesting limits when the size of the system is comparable to ${\Lambda}^{-1/2}$. We give a general argument to highlight two distinct sources of divergences in the phase space volume, coming from redshift and spatial geometry, and illustrate this by comparing and contrasting the results for (i) geodesic box in de Sitter, (ii) geodesic box in Schwarzschild, and (iii) uniformly accelerated box in Minkowski. Finally, we extend these results to $N$ particle systems in the massless (ultra-relativistic) limit for certain restricted class of spacetimes., Comment: 26 pages

In this article, we prove that the nonlinear Kawahara equation on the periodic domain \(\mathbb{T}\) (the unit circle in the plane) is globally approximately controllable in \(H^s(\mathbb{T})\) for \(s \in \mathbb{N}\), at any time \(T > 0\), using a two-dimensional control force. The proof is based on the Agrachev-Sarychev approach in geometric control theory., Comment: 20 pages, 1 figure

Automatic detection of prominence at the word and syllable-levels is critical for building computer-assisted language learning systems. It has been shown that prosody embeddings learned by the current state-of-the-art (SOTA) text-to-speech (TTS) systems could generate word- and syllable-level prominence in the synthesized speech as natural as in native speech. To understand the effectiveness of prosody embeddings from TTS for prominence detection under nonnative context, a comparative analysis is conducted on the embeddings extracted from native and non-native speech considering the prominence-related embeddings: duration, energy, and pitch from a SOTA TTS named FastSpeech2. These embeddings are extracted under two conditions considering: 1) only text, 2) both speech and text. For the first condition, the embeddings are extracted directly from the TTS inference mode, whereas for the second condition, we propose to extract from the TTS under training mode. Experiments are conducted on native speech corpus: Tatoeba, and non-native speech corpus: ISLE. For experimentation, word-level prominence locations are manually annotated for both corpora. The highest relative improvement on word \& syllable-level prominence detection accuracies with the TTS embeddings are found to be 13.7% & 5.9% and 16.2% & 6.9% compared to those with the heuristic-based features and self-supervised Wav2Vec-2.0 representations, respectively.

Large language models (LLMs) like ChatGPT have shown the potential to assist developers with coding and debugging tasks. However, their role in collaborative issue resolution is underexplored. In this study, we analyzed 1,152 Developer-ChatGPT conversations across 1,012 issues in GitHub to examine the diverse usage of ChatGPT and reliance on its generated code. Our contributions are fourfold. First, we manually analyzed 289 conversations to understand ChatGPT's usage in the GitHub Issues. Our analysis revealed that ChatGPT is primarily utilized for ideation, whereas its usage for validation (e.g., code documentation accuracy) is minimal. Second, we applied BERTopic modeling to identify key areas of engagement on the entire dataset. We found that backend issues (e.g., API management) dominate conversations, while testing is surprisingly less covered. Third, we utilized the CPD clone detection tool to check if the code generated by ChatGPT was used to address issues. Our findings revealed that ChatGPT-generated code was used as-is to resolve only 5.83\% of the issues. Fourth, we estimated sentiment using a RoBERTa-based sentiment analysis model to determine developers' satisfaction with different usages and engagement areas. We found positive sentiment (i.e., high satisfaction) about using ChatGPT for refactoring and addressing data analytics (e.g., categorizing table data) issues. On the contrary, we observed negative sentiment when using ChatGPT to debug issues and address automation tasks (e.g., GUI interactions). Our findings show the unmet needs and growing dissatisfaction among developers. Researchers and ChatGPT developers should focus on developing task-specific solutions that help resolve diverse issues, improving user satisfaction and problem-solving efficiency in software development., Comment: Accepted in SANER 2025

The present manuscript is concerned with component-wise estimation of the positive power of ordered restricted standard deviation of two normal populations with certain restrictions on the means. We propose several improved estimators under a general scale invariant bowl-shaped loss function. Also, we proposed a class of improved estimators. It has been shown that the boundary estimator of this class is a generalized Bayes. As an application, the improved estimators are obtained with respect to quadratic loss, entropy loss, and a symmetric loss function. We have conducted extensive Monte Carlo simulations to study and compare the risk performance of the proposed estimators. Finally, a real life data analysis is given to illustrate our findings.

Federated Learning (FL) marks a transformative approach to distributed model training by combining locally optimized models from various clients into a unified global model. While FL preserves data privacy by eliminating centralized storage, it encounters significant challenges such as performance degradation, slower convergence, and reduced robustness of the global model due to the heterogeneity in client data distributions. Among the various forms of data heterogeneity, label skew emerges as a particularly formidable and prevalent issue, especially in domains such as image classification. To address these challenges, we begin with comprehensive experiments to pinpoint the underlying issues in the FL training process. Based on our findings, we then introduce an innovative dual-strategy approach designed to effectively resolve these issues. First, we introduce an adaptive loss function for client-side training, meticulously crafted to preserve previously acquired knowledge while maintaining an optimal equilibrium between local optimization and global model coherence. Secondly, we develop a dynamic aggregation strategy for aggregating client models at the server. This approach adapts to each client's unique learning patterns, effectively addressing the challenges of diverse data across the network. Our comprehensive evaluation, conducted across three diverse real-world datasets, coupled with theoretical convergence guarantees, demonstrates the superior efficacy of our method compared to several established state-of-the-art approaches.

The thermal Sunyaev-Zel'dovich (tSZ) effect arises from inverse Compton scattering of low energy photons onto thermal electrons, proportional to the integrated electron pressure, and is usually observed from galaxy clusters. However, we can expect that the Epoch of Reionization (EoR) also contributes to this signal, but that contribution has not been previously evaluated. In this work we analyse a suite of fully-coupled radiation-hydrodynamics simulations based on RAMSES-CUDATON to calculate and study the tSZ signal from the Reionization Epoch. We construct lightcones of the electron pressure in the intergalactic medium for $6

Magnetic relaxation in coordination compounds is largely dominated by the interaction of the spin with phonons. Large zero-field splitting and exchange coupling values have been empirically found to strongly suppress spin relaxation and have been used as the main guideline for designing new molecular compounds. Although a comprehensive understanding of spin-phonon relaxation has been achieved for mononuclear complexes, only a qualitative picture is available for polynuclear compounds. Here we fill this critical knowledge gap by providing a full first-principle description of spin-phonon relaxation in an air-stable Co(II) dimer with both large single-ion anisotropy and exchange coupling. Simulations reproduce the experimental relaxation data with excellent accuracy and provide a microscopic understanding of Orbach and Raman relaxation pathways and their dependency on exchange coupling, zero-field splitting, and molecular vibrations. Theory and numerical simulations show that increasing cluster nuclearity to just four cobalt units would lead to a complete suppression of Raman relaxation. These results hold a general validity for single-molecule magnets, providing a deeper understanding of their relaxation and revised strategies for their improvement.

Air pollution kills 7 million people annually. The brick kiln sector significantly contributes to economic development but also accounts for 8-14\% of air pollution in India. Policymakers have implemented compliance measures to regulate brick kilns. Emission inventories are critical for air quality modeling and source apportionment studies. However, the largely unorganized nature of the brick kiln sector necessitates labor-intensive survey efforts for monitoring. Recent efforts by air quality researchers have relied on manual annotation of brick kilns using satellite imagery to build emission inventories, but this approach lacks scalability. Machine-learning-based object detection methods have shown promise for detecting brick kilns; however, previous studies often rely on costly high-resolution imagery and fail to integrate with governmental policies. In this work, we developed a scalable machine-learning pipeline that detected and classified 30638 brick kilns across five states in the Indo-Gangetic Plain using free, moderate-resolution satellite imagery from Planet Labs. Our detections have a high correlation with on-ground surveys. We performed automated compliance analysis based on government policies. In the Delhi airshed, stricter policy enforcement has led to the adoption of efficient brick kiln technologies. This study highlights the need for inclusive policies that balance environmental sustainability with the livelihoods of workers.

Molecular clouds fragment under the action of supersonic turbulence & gravity which results in a scale-free hierarchical distribution of star formation (SF) within galaxies. Recent studies suggest that the hierarchical distribution of SF in nearby galaxies shows a dependence on host galaxy properties. In this context, we study the nature of hierarchical SF from a few tens of pc up to several kpc in 4 nearby spiral galaxies NGC1566, NGC5194, NGC5457 & NGC7793, by leveraging the large FoV & high resolution FUV+NUV observations from the UltraViolet Imaging Telescope (UVIT). Using the two-point correlation function, we infer that the young star-forming clumps (SFCs) in the galaxies are arranged in a fractal-like hierarchical distribution, but only up to a maximum scale ($l_{corr}$) & it ranges from 0.5 kpc to 3.1 kpc. The flocculent spiral NGC7793 has $\sim$5 times smaller $l_{corr}$ than the 3 grand design spirals, possibly due to its lower mass, low pressure environment & lack of strong spiral arms. $l_{corr}$ being much smaller than the galaxy size suggests that the SF hierarchy does not extend to the full galaxy size & it is likely an effect set by multiple physical mechanisms in the galaxy. The hierarchical distribution of SFCs dissipates within 10 to 50 Myr, signifying their migration away from their birthplaces over time. Our results suggest that the global hierarchical properties of SF in galaxies are not universal & significant variations exist in the local & global hierarchy parameters of a galaxy. This study also demonstrates the capabilities of UVIT in characterizing the SF hierarchy in nearby galaxies. In the future, a bigger sample can be employed to further understand the role of large-scale galaxy properties (morphology, environment) & physical processes (feedback, turbulence, shear & ISM conditions) on determining the non-universal hierarchical properties of SF in galaxies., Comment: 18 pages, 11 figures, Accepted for publication in Astronomy and Astrophysics (A&A), after language correction

Under the assumption that the various evidences of a `95 GeV' excess, seen in data at the Large Electron Positron (LEP) collider as well as the Large Hadron Collider (LHC), correspond to actual signals of new physics Beyond the Standard Model (BSM), we characterise the underlying particle explaining these in terms of its Charge/Parity (CP) quantum numbers in a model independent way. In doing so, we assume the new object having spin-0 and test the CP-even (scalar) and CP-odd (pseudoscalar) hypotheses as well superpositions of these in its $\tau^+\tau^-$ decays. We prove that the High Luminosity LHC (HL-LHC) will be in a position to disentangle the CP nature of such a new particle., Comment: 14 pages and 2 figures

Consider two simple graphs, G1 and G2, with their respective vertex sets V(G1) and V(G2). The Kronecker product forms a new graph with a vertex set V(G1) X V(G2). In this new graph, two vertices, (x, y) and (u, v), are adjacent if and only if xu is an edge in G1 and yv is an edge in G2. While the adjacency spectrum of this product is known, the distance spectrum remains unexplored. This article determines the distance spectrum of the Kronecker product for a few families of distance regular graphs. We find the exact polynomial, which expresses the distance matrix D as a polynomial of the adjacency matrix, for two distance regular graphs, Johnson and Hamming graphs. Additionally, we present families of distance integral graphs, shedding light on a previously posted open problem given by Indulal and Balakrishnan in (AKCE International Journal of Graphs and Combinatorics, 13(3); 230 to 234, 2016)., Comment: 19 pages

Indium phosphide is the leading material for commercial applications of colloidal quantum dots. To date, however, the community has failed to achieve successful operation under strong excitation conditions, contrasting sharply with other materials. Here, we report how the unusual photophysics of state-of-the-art InP-based quantum dots make them unattractive as a gain material. A combination of ensemble-based time-resolved spectroscopy over timescales from femtoseconds to microseconds and single-quantum-dot spectroscopy reveals ultrafast trapping of hot charge carriers. This process leads to charge-carrier losses, thereby reducing the achievable population inversion which limits amplification of light in a gain material. Interestingly, fluorescence is only delayed, not quenched, by hot charge-carrier trapping, explaining why InP-based quantum dots are successful as bright luminescent colour convertors for low-intensity applications. Comparison with other popular quantum-dot materials, such as CdSe, Pb-halide perovskites, and CuInS2, indicate that the hot-carrier dynamics observed are unique to InP.

The Hercules kinematic group is a kinematic anomaly of stars observed in the solar neighbourhood (SNd). In this series of papers, we present a comprehensive study of this structure. This paper focuses on its chemical signatures over several groups of elements. The next paper discusses its kinematical properties. While studies suggested a non-native origin of Hercules stars due to the distinct chemical and kinematic features, previous studies focussed mainly on the Fe abundances. We adopt chemical data with abundances of elements from APOGEE and GALAH to seek further chemical evidence of the origin. Our analysis reveals that the low alpha population of the low angular momentum Hercules group is significantly enhanced in iron-peak (Fe, Ni, Mn) and odd-Z (Na, Al) elements, and slightly deficient in alpha elements (O, Ca, Ti) compared to kinematically local stars. The super enhancement in iron-peak elements and deficiency in alpha elements support their origin from the outer thin bar in the inner Galaxy. Moreover, the enhancement in Na and Al indicates these stars as the youngest stars in the old sequence from the inner thick disc. Hence, the origin of these stars can be related to the outer bar region. These chemical signatures require the underlying dynamical mechanism that forms the Hercules group to be capable of transporting stars in the inner Galaxy out to the SNd. The next paper will consider the Trojan orbits as the favoured mechanism., Comment: 14 pages, 11 figures, submitted to MNRAS

The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech. The terms and expressions related to hate speech gets updated with changing times which poses an obstacle to policy-makers and researchers in case of hate speech identification. With growing number of individuals using their native languages to communicate with each other, hate speech in these low-resource languages are also growing. Although, there is awareness about the English-related approaches, much attention have not been provided to these low-resource languages due to lack of datasets and online available data. This article provides a detailed survey of hate speech detection in low-resource languages around the world with details of available datasets, features utilized and techniques used. This survey further discusses the prevailing surveys, overlapping concepts related to hate speech, research challenges and opportunities., Comment: 34 pages, 12 figures

We consider the group G and construct its power graph, whose vertex set consists of the elements of G. Two distinct vertices (elements) are adjacent in the graph if and only if one element can be expressed as an integral power of the other. In the paper (Indagationes Mathematicae 29(2) (2018), pp 730 t0 737), Chattopadhyay et al. gave spectral radius bounds of the power graph of certain finite groups. In this article, we improved the bounds of the spectral radius of the power graphs of the above results. Furthermore, we provide bounds for the distance spectral radius of the power graph of the cyclic group Cn, the dihedral group D2n, and the dicyclic group Q4n. For some cases, we find the bounds are exact if and only if they pertain to a particular family of graphs.

We report on the results of X-ray observations (XMM-Newton, INTEGRAL and Swift) of two hard X-ray sources, IGR J17503-2636 and IGR J17507-2647, whose nature is not fully elucidated in the literature. Three XMM-Newton observations covered the field of IGR J17503-2636, in 2020 and twice in 2023. The analysis of the two XMM-Newton observations performed in September 2023, six days apart, did not detect IGR J17503-2636, allowing us to pose the most stringent 3sigma upper limit on the source flux to date (~9.5x10^-14 erg/cm2/s, 2-10 keV, flux corrected for absorption). This value implies that the amplitude of the X-ray flux variability exceeds a factor of ~2100, compared with the discovery outburst in 2018. A candidate X-ray periodicity at 0.335397(3) seconds has been barely detected (significance of about 3.8sigma) from IGR J17503-2636 with XMM-Newton (pulsed fraction of (10+/-1) per cent). The new data, put into the context of previous literature, allow us to propose a new classification of IGR J17503-2636 as a symbiotic X-ray binary, rather than a candidate supergiant fast X-ray transient. IGR J17507-2647 was formerly reported below 10 keV only during Chandra observations performed in 2009. We report here on two XMM-Newton observations that serendipitously covered the source field in 2020 and in 2023, finding a stable X-ray emission, both in X-ray flux and spectral shape. The long-term, persistent X-ray emission has also been probed by several Swift/XRT short observations and by INTEGRAL data spanning several years. We have detected an iron line in the emission (with centroid energy in the range of 6.3-6.6 keV), never reported before in the IGR J17507-2647 spectrum. The source properties favor the identification with a cataclysmic variable., Comment: Accepted for publication in Astronomy & Astrophysics (received on 18 July 2024, accepted on 21 November 2024)

Subarachnoid hemorrhage (SAH), typically due to intracranial aneurysms, demands precise imaging for effective treatment. Digital Subtraction Angiography (DSA), despite being the gold standard, broadly visualizes cerebral blood flow, potentially masking key details in areas. This study introduces an approach integrating a 3D vascular atlas with 2D DSA images to allow targeted quantitative analysis in these crucial regions, thus enhancing diagnostic accuracy during interventions. Initially, DSA data was examined to ascertain the injection site. Following this, the appropriate viewing angle was determined to align accurately with the 3D vascular atlas. Utilizing this atlas, regions corresponding to the areas indicated as perfused were selected. Concurrently, a mask representing the perfused areas was created from the DSA sequence. This mask facilitated the initial coarse alignment of the projected 3D atlas to the DSA perfused territory deformable registration techniques, ensuring a precise overlay with the DSAs perfused territories. The performance of each overlay was measured using the Structural Similarity Index Measure (SSIM). The coregistration process revealed that deformable registrations was essential to achieve precise overlays of the 3D atlas projections with the 2D DSA perfused areas. This approach enabled the extraction of targeted quantitative angiography parameters, essential for detailed vascular assessment in subarachnoid hemorrhage cases. The integration of 3D atlas registration with 2D DSA projections facilitates a more precise and targeted diagnostic process for SAH during critical interventions. This image processing strategy enhances the visualization of affected arterial territories, potentially improving the accuracy of diagnostics and supporting better informed clinical decisions at the time of intervention, Comment: 5 pages, 2 figures, to be published in SPIE Medical Imaging 2025 conference proceeds

Optomechanical cavities, with nonlinear photon-phonon interactions, offer a more compact approach to chaos generation than conventional feedback-based optical systems. However, proper study on long-distance chaos synchronization of two optomechanical cavities connected by a long optical fiber is still unexplored. In this work, we theoretically investigate all-optical complete synchronization between unidirectionally coupled optomechanical cavities. Traditionally, achieving complete synchronization in nonlinear coupled oscillators and in optical systems necessitates identical systems. Our findings, which arise naturally from the fundamental mathematical properties of optomechanical cavities, demonstrate that parameter heterogeneity can, in fact, not only enable complete synchronization but make it stable.

In 2023 October-November, the blazar BL Lacertae underwent a very large-amplitude submm outburst. The usual single-zone leptonic model with the lower energy peak of the spectral energy distribution (SED) fit by the synchrotron emission from one distribution of relativistic electrons in the jet and inverse-Compton (IC) scattering of lower energy photons from the synchrotron radiation in the jet itself (synchrotron self-Compton or SSC) or those from the broad line region and torus by the same distribution of electrons cannot satisfactorily fit the broadband SED with simultaneous data at submm--optical--X-ray--GeV energies. Furthermore, simultaneous observations with IXPE indicate the X-ray polarization is undetected. We consider two different synchrotron components, one for the high flux in the submm wavelengths and another for the data at the optical band, which are supposedly due to two separate distributions of electrons. In that case, the optical emission is dominated by the synchrotron radiation from one electron distribution while the X-rays are mostly due to SSC process by another, which may result in low polarization fraction due to the IC scattering. We show that such a model can fit the broadband SED satisfactorily as well as explain the low polarization fraction at the X-rays., Comment: Accepted for publication in Astrophysical Journal (ApJ) on November 14, 2024, 13 pages with 4 figures and 6 tables

The dielectric properties of a bulk dipolar liquid have been subjects of intense interest during the past decades. A surprising result was the discovery of a strong wavenumber dependence in the bulk homogeneous state. Such behaviour seems to suggest the possibility of a strong system size dependence of the dielectric constant (DC) of a nanoconfined liquid, although details have been revealed only recently. Dielectric properties of nanoconfined water indeed show marked sensitivity not only to the size and shape (dielectric boundaries) of confinement but also to the nature of surface-water interactions. For geometries widely studied, namely, water confined in a narrow slit, nanocylinder, and nanospherical cavity, the asymptotic approach to the bulk value of the DC with the increase in confinement size, is found to be surprisingly slow. This seems to imply the appearance of a dipolar cross-correlation length, much larger than the molecular length-scale of water. In narrow slit and narrow cylinder, the dielectric function becomes both inhomogeneous and anisotropic, and the longitudinal and transverse components display markedly different system size dependencies. This sensitivity can be traced back to the dependence of the DC on the ratio of the mean square dipole moment fluctuation to the volume of the system. The observed sensitivity of collective dipole moment fluctuations to the length scale of confinement points to the possibility of using DC to estimate orientational correlation length scale which has been an elusive quantity. Furthermore, the determination of volume also requires special consideration when the system size is in nanoscale. We discuss these and several other interesting issues along with several applications that have emerged in recent years.

We consider hypergraph visualizations that represent vertices as points in the plane and hyperedges as curves passing through the points of their incident vertices. Specifically, we consider several different variants of this problem by (a) restricting the curves to be lines or line segments, (b) allowing two curves to cross if they do not share an element, or not; and (c) allowing two curves to overlap or not. We show $\exists\mathbb{R}$-hardness for six of the eight resulting decision problem variants and describe polynomial-time algorithms in some restricted settings. Lastly, we briefly touch on what happens if we allow the lines of the represented hyperedges to have bends - to this we generalize a counterexample to a long-standing result that was sometimes assumed to be correct., Comment: 21 pages, 11 figures

This study evaluates a multimodal machine learning framework for predicting treatment outcomes in intracranial aneurysms (IAs). Combining angiographic parametric imaging (API), patient biomarkers, and disease morphology, the framework aims to enhance prognostic accuracy. Data from 340 patients were analyzed, with separate deep neural networks processing quantitative and categorical data. These networks' pre decision layers were concatenated and inputted into a final predictive network. Various data augmentation strategies, including Synthetic Minority Oversampling Technique for Nominal and Continuous data (SMOTE NC), addressed dataset imbalances. Performance metrics, evaluated through Monte Carlo cross validation, showed significant improvements with augmentation, particularly in intermediate fusion models. This study validates the framework's efficacy in accurately predicting IA treatment outcomes, demonstrating that data augmentation techniques can substantially enhance model performance., Comment: 6 pages

There have been indications of several new resonances at the Large Hadron Collider (LHC). Two of them, at about 95 GeV and 650 GeV, have been indicated by more than one experiments and have reached statistical significance worthy of a serious investigation. Conservatively using only the numbers given by the experimental collaborations, we find combined global significances around 3$\sigma$ and 4$\sigma$ respectively for the 95 GeV and 650 GeV putative resonances. There are some more which may soon become very significant. We show that the data on only the 650 GeV resonance, assuming they stand the test of time, predict the existence of a doubly-charged scalar, and make the extensions of the scalar sector like those by gauge singlet scalars, the 2-Higgs doublet models or the Georgi-Machacek model, highly disfavored. We provide the readers with a minimalistic model that can explain all the indications. Such a model can also accommodate the hints of a singly charged scalar at about 375 GeV, and a doubly charged scalar at about 450 GeV, as found by both the major LHC Collaborations, the combined global significance for each of them being above $2.5\sigma$. Our analysis comes with the obvious caveat that the allowed parameter space that we find depends on the available data on all the new resonances, and may change in future., Comment: 24 pages, 14 figure files, uses Revtex

We report measurements of the absolute branching fractions $\mathcal{B}(B_s^0 \to D_s^{\pm} X)$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X)$, and $\mathcal{B}(B_s^0 \to D^{\pm} X)$, where the latter is measured for the first time. The results are based on a 121.4\,fb$^{-1}$ data sample collected at the $\Upsilon(10860)$ resonance by the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We reconstruct one $B_s^0$ meson in $e^+e^- \to \Upsilon(10860) \to B_s^{*} \bar{B}_s^{*}$ events and measure yields of $D_s^+$, $D^0$, and $D^+$ mesons in the rest of the event. We obtain $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (68.6 \pm 7.2 \pm 4.0)\%$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (21.5 \pm 6.1 \pm 1.8)\%$, and $\mathcal{B}(B_s^0 \to D^{\pm} X) = (12.6 \pm 4.6 \pm 1.3)\%$, where the first uncertainty is statistical and the second is systematic. Averaging with previous Belle measurements gives $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (63.4 \pm 4.5 \pm 2.2)\%$ and $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (23.9 \pm 4.1 \pm 1.8)\%$. For the $B_s^0$ production fraction at the $\Upsilon(10860)$, we find $f_s = (21.4^{+1.5}_{-1.7})\%$., Comment: 23 pages, 9 figures, submitted to JHEP

Phagocytosis is the process by which cells, which are 5 to 10 times larger than the particle size, engulf particles, holding substantial importance in various biological contexts ranging from the nutrient uptake of unicellular organisms to immune system of humans, animals etc. While the previous studies focused primarily on the mechanism of phagocytosis, in this study we have a taken a different route by studying the dynamics of the phagocytes in a system consisting of many bacteria and a small number of phagocytes. We put forward a minimalist framework that models bacteria and phagocytes as active and passive circular disks, respectively. The interactions are governed by directional forces: phagocytes are attracted toward bacteria, while bacteria experience a repulsive force in proximity to phagocytes. Bacteria are capable of reproduction at a fixed rate, and the balance between bacterial reproduction and phagocytic engulfment is governed by the interplay of the two opposing forces. In attraction dominated regimes, bacterial populations decrease rapidly, while in repulsion dominated regimes, bacterial clusters grow and impede phagocytes, often resulting in phagocyte trapping. Conversely, in attraction-dominated scenarios, only a few bacteria remain at later times, rendering the motion of the phagocytes diffusive. Further, the transition between the two regimes occurs through a regime of bi-stability. Our study further describes the dynamics of both species using the tools of statistical analysis, offering insights into the internal dynamics of this system., Comment: 9 pages, 6 figures

We present the study of an end-to-end multi-track reconstruction algorithm for the central drift chamber of the Belle II experiment at the SuperKEKB collider using Graph Neural Networks for an unknown number of particles. The algorithm uses detector hits as inputs without pre-filtering to simultaneously predict the number of track candidates in an event and and their kinematic properties. In a second step, we cluster detector hits for each track candidate to pass to a track fitting algorithm. Using a realistic full detector simulation including beam-induced backgrounds and detector noise taken from actual collision data, we find significant improvements in track finding efficiencies for tracks in a variety of different event topologies compared to the existing baseline algorithm used in Belle II. For events with a hypothetical long-lived massive particle with a mass in the GeV-range decaying uniformly along its flight direction into two charged particles, the GNN achieves a combined track finding and fitting efficiency of 85.4% with a fake rate of 2.5%, compared to 52.2% and 4.1% for the baseline algorithm. This is the first end-to-end multi-track machine learning algorithm for a drift chamber detector that has been utilized in a realistic particle physics environment.

Dimerization and subsequent aggregation of polymers and biopolymers often occur under nonequilibrium conditions. When the initial state of the polymer is not collapsed or the final folded native state, the dynamics of dimerization can follow a course sensitive to both the initial conditions and the conformational dynamics. Here we study the dimerization process by using computer simulations and analytical theory where both the two monomeric polymer chains are in the elongated state and are initially placed at a separation distance, d0. Subsequent dynamics lead to the concurrent processes of collapse, dimerization and/or escape. We employ Langevin dynamics simulations with a coarse-grained model of the polymer to capture certain aspects of the dimerization process. At separations d0 much shorter than the length of the monomeric polymer, the dimerization could happen fast and irreversibly, from the partly extended polymer state itself. At an initial separation larger than a critical distance, dc, the polymer collapse precedes dimerization and a significant number of single polymers do not dimerize within the time scale of simulations. To quantify these competition, we introduce several time-dependent order parameters, namely, (i) the time-dependent radius of gyration of individual polymers describing the conformational state of the polymer, (ii) a centre-to-centre of mass distance parameter RMM, and (iii) a time dependent overlap function Q(t) between the two monomeric polymers, mimicking contact order parameter popular in protein folding. In order to better quantify the findings, we perform a theoretical analysis to capture the stochastic processes of collapse and dimerization by using dynamical disorder model., Comment: 32 pages, 11 Figures, 1 table

In intracranial aneurysm (IA) treatment, digital subtraction angiography (DSA) monitors device-induced hemodynamic changes. Quantitative angiography (QA) provides more precise assessments but is limited by hand-injection variability. This study evaluates correction methods using in vitro phantoms that mimic diverse aneurysm morphologies and locations, addressing the 2D and temporal limitations of DSA. We used a patient-specific phantom to replicate three distinct IA morphologies at various Circle of Willis points: the middle cerebral artery (MCA), anterior communicating artery (ACA), and the internal carotid artery (ICA), each varying in size and shape. The diameters of the IA at MCA, ACA and ICA are 10.1, 10 and 7 millimeters, respectively. QA parameters for both non-stenosed and stenosed conditions were measured with 5ml and 10ml boluses over various injection durations to generate time density curves (TDCs). To address the variability in injection, several singular value decomposition (SVD) variants, standard SVD (sSVD) with Tikhonov regularization, block-circulant SVD (bSVD), and oscillation index SVD (oSVD) were applied. These methods enabled the extraction of IA impulse response function (IRF), peak height (PHIRF), area under the curve (AUCIRF), and mean transit time (MTT). We evaluated the robustness of bias-reducing methods by observing the invariance of these parameters with respect to the injection conditions, and the location and size of the aneurysm. The application of SVD variants, sSVD, bSVD, and oSVD, significantly reduced QA parameter variability due to injection techniques., Comment: arXiv admin note: text overlap with arXiv:2411.03655

A \emph{conforming partition} of a rectilinear $ n $-gon\bastien{I change from ``a polygon'', otherwise $ n $ is not defined.} $ P $ is a partition of $ P $ into rectangles without using Steiner points (i.e., all corners of all rectangles must lie on\bastien{Maybe add: the boundary of} $ P $). The stabbing number of such a partition is the maximum number of rectangles intersected by an axis-aligned segment lying in the interior of $ P $. In this paper, we examine the problem of computing conforming partitions with low stabbing number. We show that computing a conforming partition with stabbing number at most~$ 4 $ is $ NP $-hard, which strengthens a previously known hardness result [Durocher \& Mehrabi, Theor. Comput. Sci. 689: 157-168 (2017)] and eliminates the possibility for fixed-parameter-tractable algorithms parameterized by the stabbing number unless $ P = NP $. In contrast, we give (i) an $ O ( n \log n ) $-time\bastien{Reviewer request: changed from "linearithmic".} algorithm to decide whether a conforming partition with stabbing number~$ 2 $ exists, (ii) a fixed-parameter-tractable algorithm parameterized by both the stabbing number and treewidth of the pixelation of the polygon, and (iii) a fixed-parameter-tractable algorithm parameterized by the stabbing number for simple polygons in general position., Comment: 29 pages, 17 figures, accepted to WALCOM 2025

Connecting incompatibility in measurements with the violation of local realism is one of the fundamental avenues of research. For two qubits, any incompatible pair of projective measurements can violate Clauser-Horne-Shimony-Holt (CHSH) inequality for some states, and there is a monotonic relationship between the level of measurement incompatibility (projective) and the violation. However, in the case of two qutrits, we exhibit that the violation of the Collins-Gisin-Linden-Massar-Popescu (CGLMP) inequality responds non-monotonically with the amount of incompatibility; we term this more nonlocality with less incompatibility. Furthermore, unlike in the CHSH case, the maximally violating state in higher dimensions depends on the amount of measurement incompatibility. We illustrate that similar patterns can also be observed in an experimentally viable interferometric measuring technique. In such a measurement scenario, we provide an explicit example of incompatible (not jointly measurable) measurements that do not violate the CGLMP inequality for any shared quantum state. We extend our study of incompatibility in the prepare and measure scenario, focusing on quantum random access codes (QRACs). Surprisingly, we show that the monotonicity of average success probability with measurement incompatibility does not hold for higher dimensions, as opposed to two dimensions, even though the maximum probability of QRAC behaves monotonically with incompatibility., Comment: 16 pages, 6 figures