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The role of asymmetric nuclear medium on the properties of kaon is investigated at zero and finite temperature employing a hybrid approach integrating the light cone quark model (LCQM) and the chiral SU(3) quark mean field (CQMF) model. The in-medium quark masses are calculated within the CQMF model and are used as inputs to study the medium modifications in the kaon properties. In particular, we have analysed the impact of baryonic density, isospin asymmetry and temperature on the weak decay constant, distribution amplitudes (DAs) and parton quark distributions (PDFs) of valence quark structure of kaons. The effects of isospin asymmetry on the kaon doublet $K =\left(\begin{array}{c} K^{+} \\ K^{0} \end{array} \right)$ and antikaon doublet $\bar{K}$= ($K^-, \bar{K}^0$) are also studied. In order to compare with future experiments, we have also evolved the in-medium DAs and PDFs of kaons to $Q^2=16$ GeV$^2$. As compared to the temperature and isospin asymmetry, change in baryonic density of the nuclear medium makes more significant changes to the DAs and PDFs of kaons., Comment: 33 pages, 16 figures

The present paper introduces the geometry of screen generic lightlike submanifolds of a locally bronze semi-Riemannian manifolds endowed with an (l,m)-type connection. The characterization theorems on geodesicity of such submanifolds with respect to the integrability and parallelism of the distributions are provided. It is proved that there exists no coisotropic , isotropic or totally proper screen generic lightlike submanifold of a locally bronze semi-Riemannian manifold. Assertions for the smooth transversal vector fields in totally umbilical proper screen generic lightlike submanifold are obtained. The structure of a minimal screen generic lightlike submanifold of a locally bronze semi-Riemannian manifold is detailed with an example.

Agricultural landscapes are quite complex, especially in the Global South where fields are smaller, and agricultural practices are more varied. In this paper we report on our progress in digitizing the agricultural landscape (natural and man-made) in our study region of India. We use high resolution imagery and a UNet style segmentation model to generate the first of its kind national-scale multi-class panoptic segmentation output. Through this work we have been able to identify individual fields across 151.7M hectares, and delineating key features such as water resources and vegetation. We share how this output was validated by our team and externally by downstream users, including some sample use cases that can lead to targeted data driven decision making. We believe this dataset will contribute towards digitizing agriculture by generating the foundational baselayer., Comment: 34 pages, 7 tables, 15 figs

In this work, we study an Ericsson cycle whose working substance is a charged (quantum) oscillator in a magnetic field that is coupled to a heat bath. The resulting quantum Langevin equations with built-in noise terms encapsulate a thermodynamic structure and allow for the computation of the efficiency of the cycle. We numerically compute the efficiency of the cycle in the quasi-static regime using the steady-state thermodynamic functions of the system. Interestingly, it is found that by increasing the system-bath coupling strength, the efficiency of the cycle can be enhanced although it falls off for larger values of the coupling strength. We also explore the behavior of the efficiency as a function of the pair of magnetic-field values between which the cycle is operated., Comment: Preliminary version

In this paper, we present a dynamic semantic clustering approach inspired by the Chinese Restaurant Process, aimed at addressing uncertainty in the inference of Large Language Models (LLMs). We quantify uncertainty of an LLM on a given query by calculating entropy of the generated semantic clusters. Further, we propose leveraging the (negative) likelihood of these clusters as the (non)conformity score within Conformal Prediction framework, allowing the model to predict a set of responses instead of a single output, thereby accounting for uncertainty in its predictions. We demonstrate the effectiveness of our uncertainty quantification (UQ) technique on two well known question answering benchmarks, COQA and TriviaQA, utilizing two LLMs, Llama2 and Mistral. Our approach achieves SOTA performance in UQ, as assessed by metrics such as AUROC, AUARC, and AURAC. The proposed conformal predictor is also shown to produce smaller prediction sets while maintaining the same probabilistic guarantee of including the correct response, in comparison to existing SOTA conformal prediction baseline.

The FAIR data principles advocate for making scientific and research datasets 'Findable' and 'Accessible'. Yet, the sheer volume and diversity of these datasets present significant challenges. Despite advancements in data search technologies, techniques for representing search results are still traditional and inadequate, often returning extraneous results. To address these issues, we developed a knowledge graph based visual search application designed to enhance data search for Earth System Scientists. This application utilizes various chart widgets and a knowledge graph at the backend, connecting two disparate data repositories.

Mild cognitive impairment (MCI), often linked to early neurodegeneration, is characterized by subtle cognitive declines and disruptions in brain connectivity. The present study offers a detailed analysis of topological changes associated with MCI, focusing on two subtypes: Early MCI and Late MCI. This analysis utilizes fMRI time series data from two distinct populations: the publicly available ADNI dataset (Western cohort) and the in-house TLSA dataset (Indian Urban cohort). Persistent Homology, a topological data analysis method, is employed with two distinct filtration techniques - Vietoris-Rips and graph filtration-for classifying MCI subtypes. For Vietoris-Rips filtration, inter-ROI Wasserstein distance matrices between persistent diagrams are used for classification, while graph filtration relies on the top ten most persistent homology features. Comparative analysis shows that the Vietoris-Rips filtration significantly outperforms graph filtration, capturing subtle variations in brain connectivity with greater accuracy. The Vietoris-Rips filtration method achieved the highest classification accuracy of 85.7\% for distinguishing between age and gender matched healthy controls and MCI, whereas graph filtration reached a maximum accuracy of 71.4\% for the same task. This superior performance highlights the sensitivity of Vietoris-Rips filtration in detecting intricate topological features associated with neurodegeneration. The findings underscore the potential of persistent homology, particularly when combined with the Wasserstein distance, as a powerful tool for early diagnosis and precise classification of cognitive impairments, offering valuable insights into brain connectivity changes in MCI., Comment: 17 pages, 5 figures, 4 tables

Blind spectroscopy of massive lensing galaxy clusters with MUSE has revealed large numbers of gravitationally-lensed Lyman-$ \alpha $ emitters exhibiting asymmetric profiles at $ 2.9 \leq z \leq 6.7 $, suggesting abundant outflows from low-mass star-forming galaxies in the early universe. Are these primaeval galaxies experiencing their first bursts of star formation, or established galaxies experiencing rejuvenation? With JWST rest-frame optical/NIR continuum imaging now available for many of these objects, we can search for older stellar populations. Here, we search for spectroscopic confirmation of outflows from these galaxies, finding a few high-signal-to-noise cases in which blueshifted interstellar absorption lines are detected. Next, we analyse the star formation histories with combined HST + JWST photometry. We find most them to be well characterised by very young, low metallicity stellar populations. However, despite the rest-frame optical/NIR coverage of JWST, we cannot place strict upper bounds on the mass in old stars (age $ > 100\,\text{Myr} $)., Comment: 10 pages, 3 figures. Submitted to Proceedings of the International Astronomical Union 2024 (Symposium 391 - The first chapters of our cosmic history with JWST)

Scallop-shell stars, a recently discovered class of young M dwarfs, show complex optical light curves that are characterized by periodic dips as well as other features that are stable over tens to hundreds of rotation cycles. The origin of these features is not well-understood. 2MASS J05082729$-$2101444 is a $\sim$25 Myr old scallop-shell star that was identified using TESS data; it has a photometric period of 6.73h that has been attributed to rotation. Of the $\sim$50 recently confirmed scallop-shell stars, it is one of the few detected at radio frequencies between 1 and 8 GHz. We observed this rare system with the upgraded Giant Meterwave Radio Telescope at 575--720 MHz, covering 88% of the photometric period in each of the two observations scheduled almost a month apart in 2023. We detected $\sim$millijansky emission from the target in both epochs, with a significant circular polarization fraction: $|V/I|\sim$20--50%. The 3.5-min phase-folded light curves reveal unique variability in circular polarization, showing an $\sim$hour-long helicity reversal in both epochs, similar in amplitude, length, and (possibly) phase. These results suggest two emission components: The first is a persistent, moderately polarized component possibly ascribable to gyro-synchrotron emission driven by centrifugal breakout events. The second is a highly polarized, short burst-like component, likely due to an electron cyclotron maser (ECM), indicative of auroral emission and potentially responsible for the helicity reversal. To explain this, we discuss the different origins of the plasma responsible for the radio emission, including the possibility that the occulting material is acting as a plasma source. Future coordinated multifrequency radio and optical observations can further constrain the underlying scenario, as well as the magnetic geometry of the system, if we assume an ECM-like auroral emission., Comment: 9 pages, 5 figures, 1 table, Accepted for publication in Astronomy & Astrophysics Letters

As nations and organisations worldwide intensify their efforts and investments to commercialise quantum technologies and explore practical applications across various industries, there is a burgeoning demand for skilled professionals to support this rapidly growing ecosystem. With an expanding array of stakeholders from diverse professions beginning to engage with this ecosystem, there is an urgent need for innovative educational methodologies. These methodologies must not only convey the intricate principles of quantum mechanics effectively to varied professionals, enabling them to make informed decisions but also spark interest among students to delve into and pursue careers within this cutting-edge field. In response, we introduce the Experience-Name-Speak-Apply-Repeat (ENSAR) methodology, coupled with its hands-on implementation through the Qureka Box - an innovative tool designed to demystify quantum computing for a diverse audience by emphasising a pedagogical approach rooted in experiential learning, conceptual understanding, and practical application. We present the results of deploying the ENSAR methodology using the Qureka Box across a diverse group to validate our claims. The findings suggest a significant enhancement in the participants' grasp of foundational quantum computing concepts, thereby showcasing the potential of this approach to equip individuals from diverse professional backgrounds with the knowledge and skills to bridge the workforce demand.

Laser-Wakefield Accelerators (LWFA) running at kHz repetition rates hold great potential for applications. They typically operate with low-energy, highly compressed laser pulses focused in high-pressure gas targets. Experiments have shown that the best-quality electron beams are achieved using Hydrogen gas targets. However, continuous operation with Hydrogen requires a dedicated pumping system. This work presents the design of a differential pumping system, enabling, for the first time, continuous operation of our kHz LWFA using a high-pressure Hydrogen gas jet. The system successfully maintained a pressure below 3e-4 mbar, even with a free-flowing gas jet operating at 140 bar backing pressure. Numerical fluid dynamics and optical simulations were used to guide and validate the system's design., Comment: 10 pages, 9 figures

Distance-2-Dispersion (D-2-D) problem aims to disperse $k$ mobile agents starting from an arbitrary initial configuration on an anonymous port-labeled graph $G$ with $n$ nodes such that no two agents occupy adjacent nodes in the final configuration, though multiple agents may occupy a single node if there is no other empty node whose all adjacent nodes are also empty. In the existing literature, this problem is solved starting from a rooted configuration for $k(\geq 1)$ agents using $O(m\Delta)$ synchronous rounds with a total of $O(\log n)$ memory per agent, where $m$ is the number of edges and $\Delta$ is the maximum degree of the graph. The existing work that solves the problem of D-2-D from scattered initial configuration considers $n+1$ agents to begin with. In this work, we start with $n$ mobile agents that start from an arbitrary initial configuration. They achieve D-2-D configuration that is also a maximal independent set of the graph and terminate in $O(max\{n\log^2 n, m\})$ rounds using $O(\log n)$ memory per agent. The agents do not have any prior knowledge of any graph parameters. This is a significant improvement over the existing works that solve D-2-D on arbitrary graphs.

We study the in-medium properties of kaons and antikaons in isospin asymmetric hot and dense resonance matter within the chiral SU(3) hadronic mean field model. Along with nucleons and hyperons, the interactions of $K$ and $\bar K$ mesons with all decuplet baryons ($\Delta^{++,+,0,-}, \Sigma^{*\pm,0},\Xi^{*0,-}, \Omega^{-}$) are explicitly considered in the dispersion relations. The properties of mesons in the chiral SU(3) model are modified at finite density and temperature of asymmetric resonance matter through the exchange of scalar fields $\sigma, \zeta$ and $\delta$ and the vector fields $\omega, \rho$ and $\phi$. The presence of resonance baryons in the medium at finite temperature is observed to modify significantly the effective masses of $K$ and $\bar{K}$ mesons. We also calculated the optical potentials of kaons and antikaons as a function of momentum in resonance matter. The present study of in-medium masses and optical potentials of kaons and antikaons will be important for understanding the experimental observables from the heavy-ion collision experiments where hot and dense matter may be produced. Our results indicate that when resonance baryons are present within the medium at finite baryonic density, the mass reduction of kaons and antikaons becomes more pronounced as the temperature of the medium increases from zero to 100 and 150 MeV. The study of the optical potentials of kaons and antikaons reveals a stronger correlation with strangeness fraction compared to isospin asymmetry., Comment: 46 pages and 19 figures

We report on continuous high-harmonic generation at 1 kHz repetition rate from a liquid-sheet plasma mirror driven by relativistic-intensity near-single-cycle light transients. Through precise control of both the surface plasma density gradient and the driving light waveform, we can produce highly stable and reproducible extreme ultraviolet spectral quasi-continua, corresponding to the generation of stable kHz-trains of isolated attosecond pulses in the time domain. This confirms the exciting potential of liquid sheet targets as one of the building blocks of future high-power attosecond lasers.

Herbs and spices each contain about 3000 phytochemicals on average and there is much traditional knowledge on their health benefits. However, there is a lack of systematic study to understand the relationship among herbs and spices, their phytochemical constituents, their potential health benefits, and their usage in regional cuisines. Here we use a network-based approach to elucidate established relationships and predict novel associations between the phytochemicals present in herbs and spices with health indications. Our top 100 inferred indication-phytochemical relationships rediscover 40% known relationships and 20% that have been inferred via gene-chemical interactions with high confidence. The remaining 40% are hypotheses generated in a principled way for further experimental investigations. We also develop an algorithm to find the minimum set of spices needed to cover a target group of health conditions. Drawing on spice usage patterns in several regional Indian cuisines, and a copy-mutate model for regional cuisine evolution, we characterize the spectrum of health conditions covered by existing regional cuisines. The spectrum of health conditions can expand through the nationalization/globalization of culinary practice.

Financial decision-making hinges on the analysis of relevant information embedded in the enormous volume of documents in the financial domain. To address this challenge, we developed FinQAPT, an end-to-end pipeline that streamlines the identification of relevant financial reports based on a query, extracts pertinent context, and leverages Large Language Models (LLMs) to perform downstream tasks. To evaluate the pipeline, we experimented with various techniques to optimize the performance of each module using the FinQA dataset. We introduced a novel clustering-based negative sampling technique to enhance context extraction and a novel prompting method called Dynamic N-shot Prompting to boost the numerical question-answering capabilities of LLMs. At the module level, we achieved state-of-the-art accuracy on FinQA, attaining an accuracy of 80.6%. However, at the pipeline level, we observed decreased performance due to challenges in extracting relevant context from financial reports. We conducted a detailed error analysis of each module and the end-to-end pipeline, pinpointing specific challenges that must be addressed to develop a robust solution for handling complex financial tasks., Comment: Accepted in ICAIF 2024, 8 pages, 5 figures, 4 tables

Quantum computing presents a double-edged sword: while it has the potential to revolutionize fields such as artificial intelligence, optimization, healthcare, and so on, it simultaneously poses a threat to current cryptographic systems, such as public-key encryption. To address this threat, post-quantum cryptography (PQC) has been identified as the solution to secure existing software systems, promoting a national initiative to prepare the next generation with the necessary knowledge and skills. However, PQC is an emerging interdisciplinary topic, presenting significant challenges for educators and learners. This research proposes a novel active learning approach and assesses the best practices for teaching PQC to undergraduate and graduate students in the discipline of information systems. Our contributions are two-fold. First, we compare two instructional methods: 1) traditional faculty-led lectures and 2) student-led seminars, both integrated with active learning techniques such as hands-on coding exercises and Kahoot games. The effectiveness of these methods is evaluated through student assessments and surveys. Second, we have published our lecture video, slides, and findings so that other researchers and educators can reuse the courseware and materials to develop their own PQC learning modules. We employ statistical analysis (e.g., t-test and chi-square test) to compare the learning outcomes and students' feedback between the two learning methods in each course. Our findings suggest that student-led seminars significantly enhance learning outcomes, particularly for graduate students, where a notable improvement in comprehension and engagement is observed. Moving forward, we aim to scale these modules to diverse educational contexts and explore additional active learning and experiential learning strategies for teaching complex concepts of quantum information science., Comment: 23 pages, 8 figures

Magnetite, a naturally abundant mineral, frequently interacts with water in both natural settings and various technical applications, making the study of its surface chemistry highly relevant. In this work, we investigate the hydrogen bonding dynamics and the presence of hydroxyl species at the magnetite-water interface using a combination of neural network potential-based molecular dynamics simulations and sum frequency generation vibrational spectroscopy. Our simulations, which involved large water systems, allowed us to identify distinct interfacial species, such as dissociated hydrogen and hydroxide ions formed by water dissociation. Notably, water molecules near the interface exhibited a preference for dipole orientation towards the surface, with bulk-like water behavior only re-emerging beyond 60 {\AA} from the surface. The vibrational spectroscopy results aligned well with the simulations, confirming the presence of a hydrogen bond network in the surface ad-layers. The analysis revealed that surface-adsorbed hydroxyl groups orient their hydrogen atoms towards the water bulk. In contrast, hydrogen-bonded water molecules align with their hydrogen atoms pointing towards the magnetite surface.

We report on the nonlinear temporal post-compression of 7 mJ sub-40 fs pulses from a commercial kHz Ti:Sapphire laser down to a record 4 fs duration (1.5 optical cycle) in a compact single-stage gas-filled multipass cell, with 60% overall compression efficiency.

Following the wealth of new results enabled by multimessenger observations of the binary neutron star (BNS) merger GW170817, the next goal is increasing the number of detections of electromagnetic (EM) counterparts to gravitational wave (GW) events. Here, we study the detectability of the prompt emission and afterglows produced by the relativistic jets launched by BNS mergers that will be detected by LIGO-Virgo-KAGRA (LVK) during their fifth observing run (O5), and by next generation (XG) GW detectors (Einstein Telescope and Cosmic Explorer). We quantify the impact of various BNS merger and jet afterglow parameters on the likelihood of detection for a wide range of telescopes, focusing on the impact of the observer's viewing angle $\theta_\textrm{v}$ and the jet's core half-opening angle $\theta_\textrm{c}$. We find that during the LVK O5 run, the James Webb Space Telescope (JWST) is expected to reach the largest number of afterglow detections, up to $32\%$ of BNS mergers with $27\%$ detectable on timescales $>10$ d. Overall the detection of $20-30\%$ of events is possible across the EM spectrum with the available instruments, including the Chandra X-ray Observatory, the Nancy Grace Roman Space Telescope, the Square Kilometer Array (SKA), and the Very Large Array (VLA). In the XG era, afterglows for $20-25\%$ of events will be detectable with AXIS, Athena, Lynx, UVEX, JWST and the next generation VLA (ngVLA), reaching beyond redshift $z \gtrsim 1$. We also find that the majority of detected afterglows are expected to accompany prompt gamma-ray emission detectable by the Neil Gehrels Swift Observatory, the Space-based multi-band astronomical Variable Objects Monitor (SVOM), and the Transient High-Energy Sky and Early Universe Surveyor (THESEUS), with at least $\sim 6\%$ of afterglows being orphan., Comment: Submitted to Physical Review D, 36 pages, 13 figures

The use of tunable pre-pulse is a common technique to enhance the high-order harmonic generation from surface plasma. The shape and dynamic of the electron density, the degree of ionization and its rate, and the plasma heating are influenced by the pre-pulse properties. Non-uniform pre-pulse could cause a spatially varying density map to the pre-plasma region, which serves as the spectrally up-conversion and reflection surface. The corresponding geometrical feature and plasma nature under laser field will affect the harmonic emission properties. In this study, the variation in harmonic beam pointing due to the electron density shape was investigated. Particle-in-cell simulations demonstrated that both plasma hydrodynamics and geometrical optical effect induce the deviation of harmonic beam from specular reflection. This research contributes to the understanding of the surface plasma dynamics during high harmonic generation process.

In this work, we have investigated the transverse and spatial structure of light ($\pi^+ (u\bar d)$, $K^+(u\bar s)$) and heavy ($\eta_c(c\bar c)$, $\eta_b (b\bar b)$, $B$ and $D$) pseudoscalar mesons using the light-cone quark model. The transverse structure of these particles have been studied using the transverse momentum dependent parton distribution (TMDs). The leading twist unpolarized $f_1(x, \mathbf{k}_\perp^2)$ TMD has been solved using the quark-quark correlator. We have predicted the average momenta carried by the quark and antiquark of the considered mesons. For a complete description of mesons, we have also computed the leading twist unpolarized $H(x,0,-t)$ generalized parton distribution (GPD). Further, electromagnetic form factors (EMFFs), along with gravitational form factors (GFFs) have been derived by taking the zeroth and first moments of the unpolarized GPD. These EMFFs are found to be compatible with available lattice simulation results. Further, we have also calculated the parton distribution functions (PDFs) for both the quarks and the antiquarks of these mesons. The PDF sum rule has also been verified., Comment: 32 pages and 17 figures

The dispersion involves the coordination of $k \leq n$ agents on a graph of size $n$ to reach a configuration where at each node at most one agent can be present. It is a well-studied problem. Also, this problem is studied on dynamic graphs with $n$ nodes where at each discrete time step the graph is a connected sub-graph of the complete graph $K_n$. An optimal algorithm is provided assuming global communication and 1-hop visibility of the agents. How this problem pans out on Time-Varying Graphs (TVG) is an open question in the literature. In this work we study this problem on TVG where at each discrete time step the graph is a connected sub-graph of an underlying graph $G$ (known as a footprint) consisting of $n$ nodes. We have the following results even if only one edge from $G$ is missing in the connected sub-graph at any time step and all agents start from a rooted initial configuration. Even with unlimited memory at each agent and 1-hop visibility, it is impossible to solve dispersion for $n$ co-located agents on a TVG in the local communication model. Furthermore, even with unlimited memory at each agent but without 1-hop visibility, it is impossible to achieve dispersion for $n$ co-located agents in the global communication model. From the positive side, the existing algorithm for dispersion on dynamic graphs with the assumptions of global communication and 1-hop visibility works on TVGs as well. This fact and the impossibility results push us to come up with a modified definition of the dispersion problem on TVGs, as one needs to start with more than $n$ agents if the objective is to drop the strong assumptions of global communication and 1-hop visibility. Then, we provide an algorithm to solve the modified dispersion problem on TVG starting with $n+1$ agents with $O(\log n)$ memory per agent while dropping both the assumptions of global communication and 1-hop visibility.

Wireless communication has evolved significantly, with 6G offering groundbreaking capabilities, particularly for IoT. However, the integration of IoT into 6G presents new security challenges, expanding the attack surface due to vulnerabilities introduced by advanced technologies such as open RAN, terahertz (THz) communication, IRS, massive MIMO, and AI. Emerging threats like AI exploitation, virtualization risks, and evolving attacks, including data manipulation and signal interference, further complicate security efforts. As 6G standards are set to be finalized by 2030, work continues to align security measures with technological advances. However, substantial gaps remain in frameworks designed to secure integrated IoT and 6G systems. Our research addresses these challenges by utilizing tree-based machine learning algorithms to manage complex datasets and evaluate feature importance. We apply data balancing techniques to ensure fair attack representation and use SHAP and LIME to improve model transparency. By aligning feature importance with XAI methods and cross-validating for consistency, we boost model accuracy and enhance IoT security within the 6G ecosystem.

Quantum Machine Learning (QML) is a red-hot field that brings novel discoveries and exciting opportunities to resolve, speed up, or refine the analysis of a wide range of computational problems. In the realm of biomedical research and personalized medicine, the significance of multi-omics integration lies in its ability to provide a thorough and holistic comprehension of complex biological systems. This technology links fundamental research to clinical practice. The insights gained from integrated omics data can be translated into clinical tools for diagnosis, prognosis, and treatment planning. The fusion of quantum computing and machine learning holds promise for unraveling complex patterns within multi-omics datasets, providing unprecedented insights into the molecular landscape of lung cancer. Due to the heterogeneity, complexity, and high dimensionality of multi-omic cancer data, characterized by the vast number of features (such as gene expression, micro-RNA, and DNA methylation) relative to the limited number of lung cancer patient samples, our prime motivation for this paper is the integration of multi-omic data, unique feature selection, and diagnostic classification of lung subtypes: lung squamous cell carcinoma (LUSC-I) and lung adenocarcinoma (LUAD-II) using quantum machine learning. We developed a method for finding the best differentiating features between LUAD and LUSC datasets, which has the potential for biomarker discovery., Comment: 27 pages, 17 figures

Unmanned Aerial Vehicles (UAVs) play an increasingly critical role in Intelligence, Surveillance, and Reconnaissance (ISR) missions such as border patrolling and criminal detection, thanks to their ability to access remote areas and transmit real-time imagery to processing servers. However, UAVs are highly constrained by payload size, power limits, and communication bandwidth, necessitating the development of highly selective and efficient data transmission strategies. This has driven the development of various compression and optimal transmission technologies for UAVs. Nevertheless, most methods strive to preserve maximal information in transferred video frames, missing the fact that only certain parts of images/video frames might offer meaningful contributions to the ultimate mission objectives in the ISR scenarios involving moving object detection and tracking (OD/OT). This paper adopts a different perspective, and offers an alternative AI-driven scheduling policy that prioritizes selecting regions of the image that significantly contributes to the mission objective. The key idea is tiling the image into small patches and developing a deep reinforcement learning (DRL) framework that assigns higher transmission probabilities to patches that present higher overlaps with the detected object of interest, while penalizing sharp transitions over consecutive frames to promote smooth scheduling shifts. Although we used Yolov-8 object detection and UDP transmission protocols as a benchmark testing scenario the idea is general and applicable to different transmission protocols and OD/OT methods. To further boost the system's performance and avoid OD errors for cluttered image patches, we integrate it with interframe interpolations.

As large language models (LLMs) become increasingly advanced, their ability to exhibit compositional generalization -- the capacity to combine learned skills in novel ways not encountered during training -- has garnered significant attention. This type of generalization, particularly in scenarios beyond training data, is also of great interest in the study of AI safety and alignment. A recent study introduced the SKILL-MIX evaluation, where models are tasked with composing a short paragraph demonstrating the use of a specified $k$-tuple of language skills. While small models struggled with composing even with $k=3$, larger models like GPT-4 performed reasonably well with $k=5$ and $6$. In this paper, we employ a setup akin to SKILL-MIX to evaluate the capacity of smaller models to learn compositional generalization from examples. Utilizing a diverse set of language skills -- including rhetorical, literary, reasoning, theory of mind, and common sense -- GPT-4 was used to generate text samples that exhibit random subsets of $k$ skills. Subsequent fine-tuning of 7B and 13B parameter models on these combined skill texts, for increasing values of $k$, revealed the following findings: (1) Training on combinations of $k=2$ and $3$ skills results in noticeable improvements in the ability to compose texts with $k=4$ and $5$ skills, despite models never having seen such examples during training. (2) When skill categories are split into training and held-out groups, models significantly improve at composing texts with held-out skills during testing despite having only seen training skills during fine-tuning, illustrating the efficacy of the training approach even with previously unseen skills. This study also suggests that incorporating skill-rich (potentially synthetic) text into training can substantially enhance the compositional capabilities of models., Comment: Accepted to NeurIPS 2024

The advancement in deep learning and internet-of-things have led to diverse human sensing applications. However, distinct patterns in human sensing, influenced by various factors or contexts, challenge generic neural network model's performance due to natural distribution shifts. To address this, personalization tailors models to individual users. Yet most personalization studies overlook intra-user heterogeneity across contexts in sensory data, limiting intra-user generalizability. This limitation is especially critical in clinical applications, where limited data availability hampers both generalizability and personalization. Notably, intra-user sensing attributes are expected to change due to external factors such as treatment progression, further complicating the challenges. This work introduces CRoP, a novel static personalization approach using an off-the-shelf pre-trained model and pruning to optimize personalization and generalization. CRoP shows superior personalization effectiveness and intra-user robustness across four human-sensing datasets, including two from real-world health domains, highlighting its practical and social impact. Additionally, to support CRoP's generalization ability and design choices, we provide empirical justification through gradient inner product analysis, ablation studies, and comparisons against state-of-the-art baselines., Comment: 31 pages, 10 figues and 13 tables

In the current article, we establish a distinct version of the operators defined by Berwal \emph{et al.}, which is the Kantorovich type modification of $\alpha$-Bernstein operators to approximate Lebesgue's integrable functions. We define its modification that can preserve the linear function and analyze its characteristics. Additionally, we construct the bivariate of blending type operators by Berwal \emph{et al.}. We analyze both its the convergence and error of approximation properties by using the conventional tools of approximation theory. Finally, we demonstrate our results by presenting examples that highlight graphical visuals using MATLAB.

The spectroscopic redshift measurement of BL Lac, a class of blazar, is challenging because its spectrum has no or weak emission lines ($\leqslant5\AA$). We estimate the redshift by the photometric dropout technique for a sample of 64 blazars (59 BL Lacs and five blazar candidates of uncertainty type). Two telescopes are utilized to observe the sample: the {\it Swift} space telescope observes sources in $uvw2,\ uvm2,\ uvw1,\ u,\ b,\ v$ filters, while the ground-based telescopes SARA-CT/RM observed sources in $g',\ r,' \ i',\ z'$ filters. The photometric data are obtained using the {\it photozpy} package. We fit the photometric data by the LePhare package and report four new high-$z$ ($z>1.3$) BL Lacs at $2.03^{+0.07}_{-0.05}$, $1.84^{+0.10}_{-0.03}$, $2.04^{+0.16}_{-0.14}$, $2.93^{+0.01}_{-0.04}$ as well as upper limits for 50 sources. The work increased the number of high-$z$ BL Lacs found by this method up to 23. The high-$z$ sources are discussed in the context of the cosmic gamma-ray horizon, blazar sequence, Fermi blazar divide, and masquerading BL Lacs., Comment: Updated the CGRH plot

The fusion cross-sections of $^{126}$Ba, $^{127,126,125}$Cs, $^{125,123,122}$Xe and $^{124,123}$I residues, populated via $x$n, p$x$n, $\alpha$$x$n, and $\alpha$p$x$n channels, have been measured in $^{12}$C+$^{118}$Sn system at E$_{\textrm{lab}}$ $\approx$ 65-85 MeV. For an insight into the formation and decay modes of these residues, experimentally measured cross-sections have been analyzed in the framework of theoretical model codes PACE4 and EMPIRE. The cross-sections of p$x$n ($^{127,126,125}$Cs), $\alpha$xn ($^{125}$Xe), and $\alpha$p$x$n ($^{123}$I) channels have been found to be substantially fed from their higher charge isobars via $\beta^+$ decay and electron capture. In order to deduce the contribution of higher charge isobars in the population of these residues, the independent cross-sections of evaporation residues have been calculated using the prescription of Cavinato $et$ $al.$ and compared with that calculated using theoretical model codes. It has been found that the PACE4 and EMPIRE calculations fairly reproduce the independent cross-sections of evaporation residues within the experimental uncertainties. Interestingly, it has been found that the $\alpha$-emitting channels, contrary to established findings in reactions involving $\alpha$ cluster projectiles (e.g., $^{12}$C, $^{16}$O, etc.) at low incident energies, display negligible contribution of incomplete fusion (ICF). A comparison of incomplete fusion fraction as a function of entrance channel mass-asymmetry for reactions involving $^{12}$C projectile with nearby targets indicates dissimilar behavior of $^{118}$Sn target.

In this work, fission of moderately excited compound nucleus $^{220}$Ra${^\star}$ produced in $^{12}$C+$^{208}$Pb reaction at E$_{\rm lab}$ = 81.9, 75.8, and 67.5 MeV has been studied. 28 fission fragments, within the mass range 60$\leq$A$\leq$141, have been identified based on their characteristic decay $\gamma$-lines and half-lives. The yields of different fission fragments have been analyzed to generate isotopic and isobaric yield distributions. The value of the mass dispersion parameter, $\sigma^2_A$, is found to be 2.93 and 2.65 for Antimony (Sb) isotope at excitation energy E$^{\star}$ = 45.4 and 39.6 MeV, and 1.24 for Indium (In) isotope at E$^{\star}$ = 45.4 MeV. The charge dispersion parameter $\sigma_z$ for Sb is estimated to be 0.769 and 0.714 at E$^{\star}$ = 45.4 and 39.6 MeV, respectively. For In isotopes, the value of $\sigma_z$ is estimated to be 0.430 at E$^{\star}$ = 45.4 MeV. The value of mass and charge dispersion parameters for Sb and In isotopes display good agreement with the values reported in the literature for similar systems. It has been found that $^{99m}$Tc and $^{111}$In, medically important isotopes, populate in this system. The present investigations suggest that fission is a dominating mode of deexcitation of the compound nucleus, even at entrance channel energies slightly above the Coulomb barrier.

We investigate the potential of epitaxial (001)p-NiO/(0001)n-ZnO heterostructures grown on (0001)sapphire substrates by pulsed laser deposition technique for ultraviolet photodetector application. Our study reveals that in the self-powered mode, these devices can serve as effective photodetectors for the UV-A band (320-400 nm) with response time as short as 400 microseconds. Peak responsivity as high as 5mA/W at zero bias condition have been achieved. These devices also show a very high level of stability under repeated on/off illumination cycles over a long period of time. Furthermore, we find that the response time of these detectors can be controlled from several microseconds to thousands of seconds by applying bias both in the forward and the reverse directions. This persistent photoconductivity effect has been explained in terms of the field induced change in the capture barrier height associated with certain traps located at the junction., Comment: 10 Pages

The mechanical response of amorphous solids to external strains is riddled with plastic events that create topological charges in the resulting displacement field. It was recently shown that the latter leads to screening phenomena that are accompanied by the breaking of both translational and Chiral symmetries. The screening effects are quantified by two screening parameters $\kappa_e$ and $\kappa_o$, which are inverse characteristic lengths that do not exist in classical elasticity. The screening parameters (and the associated lengths) are emergent, and it is important to understand how they are selected. This Letter explores the mechanism of selection of these characteristic lengths in two examples of strain protocols that allow analytic scrutiny.

Extreme-mass ratio inspirals (EMRIs) of stellar-mass black holes (BHs) are among the main targets for upcoming low-frequency gravitational wave (GW) detectors such as the Laser Interferometer Space Antenna (LISA). In the classical scenario, EMRIs are formed when BHs scatter off each other and are driven onto highly eccentric orbits that gradually inspiral due to GW emission. If the cluster is in a state of strong mass segregation, the BHs are expected to reside in a steep cusp around the central massive black hole (MBH), which would facilitate more efficient EMRI formation. However, strong mass segregation may also lead to an increased rate of ejections due to close encounters between the BHs. Here, we test the relevance of such ejections for EMRI formation by numerically solving a two-dimensional Fokker-Planck equation. Our formalism includes the effects of two-body relaxation, GW dissipation, and ejections. We find that the EMRI formation rate can be suppressed due to ejections by more than an order of magnitude for strongly segregated BH cusps with density index $\gamma\gtrsim 2.25$ around central MBHs of mass $M_{\bullet} \lesssim 10^6 M_\odot $. The EMRI formation rate levels off up to a maximum value of $\simeq 200~{\rm Gyr}^{-1}$ due to ejections, which is roughly an order of magnitude lower than the usual scenarios ignoring ejections for steep BH cusps around low mass MBHs. Our analysis brings forth the significance of strong scatterings for EMRI formation in galactic nuclei., Comment: Submitted to ApJ; 15 pages, 7 figures; comments are welcome

We calculate the valence quark transverse momentum-dependent parton distributions (TMDs) of the lightest pseudoscalar meson, pions, in isospin asymmetric nuclear matter at zero temperature by employing a light-cone quark model. The medium modifications in the pion unpolarized TMDs are induced through the effective quark masses computed using the chiral SU($3$) quark mean field model. The spin densities at different momentum fraction ($x$) have also been calculated at different baryonic densities., Comment: 7 pages and 4 figures

Analysis of normalised C-moments of multiplicity distribution calculated from the different phenomenological models, the Bialas-Praszalowics~(BP) model, modified negative binomial and the superposed SGD at different center of mass~(cms) energies is presented.~The analysis covers a range of energies~(200-900 GeV) of $\bar{p}p$ collisions in restricted phase space slices.~A comparison of different models to the experimental data on charged particle multiplicity spectra from the $\bar{p}p$ annihilation in five pseudorapidity windows is reported.~The comparison shows that the two approaches other than the BP model are in better agreement to the data.~Results on variation of moments with pseudorapidity window size and with center of mass energy and observations from such a study in $\bar{p}p$ annihilation and $pp$ interactions at the same cms energy are also presented., Comment: 10 pages, 6 figures

NiO/ZnO heterostructures are grown on c-sapphire substrates using pulsed laser deposition (PLD) technique. X-ray diffraction study shows that the ZnO layer epitaxially grows along [0001]-direction on (0001)sapphire surface as expected. While, the epitaxial NiO film is found to be deposited along [001]-direction on the (0001)ZnO surface. Moreover, the presence of three (001)NiO domains laterally rotated by 30{\deg} with respect to each other, has also been observed in our NiO films. The study reveals the continuous nature of the NiO film, which also possesses a very smooth surface morphology. In a sharp contrast, ZnO films are found to grow along [0001]-direction when deposited on (111)NiO layers. These films also show columnar morphology. (001)NiO/(0001)ZnO layers exhibit the rectifying current-voltage characteristics that suggests the existence of p-n junction in these devices. However, the behavior could not be observed in (0001)ZnO/(111)NiO heterojunctions. The reason could be the columnar morphology of the ZnO layer. Such a morphology can facilitate the propagation of the metal ions from the contact pads to the underlying NiO layer and suppress the p-n junction effect., Comment: 6 pages and 6 figures (main manuscript), 6 pages and 6 figures (supplemental material)

High-dimensional quantum entanglement is an important resource for emerging quantum technologies such as quantum communication and quantum computation. The scalability of metres-long experimental setups limits high-dimensional entanglement in bulk optics. Advancements in quantum technology hinge on reproducible, and reconfigurable quantum devices -- including photon sources, which are challenging to achieve in a scalable manner using bulk optics. Advances in nanotechnology and CMOS-compatible integration techniques have enabled the generation of entangled photons on millimeter-scale chips, significantly enhancing scalability, stability, replicability, and miniaturization for real-world quantum applications. In recent years we have seen several chip-scale demonstrations with different degrees of freedom including path, frequency-bin, time-bin, and transverse modes, on many material platforms. A complete quantum photonic integrated circuit requires the generation, manipulation, and detection of qudits, involving various active and passive quantum photonic components which further increase the degree of complexity. Here, we review and introduce the nonlinear optical processes that facilitate on-chip high-dimensional entangled photon sources and the currently used material platforms. We discuss a range of current implementations of on-chip high-dimensional entangled photon sources and demonstrated applications. We comment on the current challenges due to the limitations of individual material platforms and present future opportunities in hybrid and heterogeneous integration strategies for the next generation of integrated quantum photonic chips., Comment: 32 pages, 8 figures

Excitation functions of several evaporation residues populated via complete and/or incomplete fusion in $^{12}$C+$^{193}$Ir system have been measured at energies $\approx$ 64-84 MeV, and analyzed in the framework of theoretical model code PACE4. It has been found that the $xn$ channels are predominantly populated via complete fusion; however, some of the $pxn$ channels decay via their precursor. A significant enhancement has been observed in the case of $\alpha$-emitting channels over PACE4 calculations, indicating the onset of a reaction mechanism not included in this code, e.g., incomplete fusion. For better insights into the onset and influence of incomplete fusion, the percentage fraction of incomplete fusion has been deduced and analyzed in terms of different entrance-channel parameters. The findings of the present study underline the importance of projectile energy, entrance-channel mass-asymmetry, and the Coulomb factor of interacting partners. The impact of projectile break-up on complete fusion has also been discussed in the framework of the Universal Fusion Function, where suppression of $\approx$ 12$\%$ has been observed in the fusion function. The finding of the present work reinstates that the fusion suppression is affected by the projectile $\alpha$-break-up threshold.

High-order difference operators with the summation-by-parts (SBP) property can be used to build stable discretizations of hyperbolic conservation laws; however, most high-order SBP operators require a conforming, high-order mesh for the domain of interest. To circumvent this requirement, we present an algorithm for building high-order, diagonal-norm, first-derivative SBP operators on point clouds over complex geometries. The algorithm is not mesh-free, since it uses a Cartesian cut-cell mesh to define the sparsity pattern of the operators and to provide intermediate quadrature rules; however, the mesh is generated automatically and can be discarded once the SBP operators have been constructed. Using this temporary mesh, we construct local, cell-based SBP difference operators that are assembled into global SBP operators. We identify conditions for the existence of a positive-definite diagonal mass matrix, and we compute the diagonal norm by solving a sparse system of linear inequalities using an interior-point algorithm. We also describe an artificial dissipation operator that complements the first-derivative operators when solving hyperbolic problems, although the dissipation is not required for stability. The numerical results confirm the conditions under which a diagonal norm exists and study the distribution of the norm's entries. In addition, the results verify the accuracy and stability of the point-cloud SBP operators using the linear advection equation., Comment: 45 pages, 39 figures

Understanding electrical characteristics and corresponding transport models at single molecular junctions is crucial. There have been many reports on organic compounds-based single molecular junctions. However, organometallic compounds-based single molecular junctions have not been explored yet. Re(I) organometallic compounds are known to exhibit intriguing photophysical properties scrutinized for photocatalysis, and light-emitting diodes but have not been explored in molecular electronics. In this work, a theoretical model study on the I-V characteristics of two Re(I)-carbonyl complexes bearing Re-P and Re-N-N linkage has been meticulously chosen. Tunneling and hopping transport in Au/Re(I)-complex/Au single-molecule junctions are governed by Landauer-formalism and the Marcus theory, respectively. Interestingly, variations in molecular architecture culminate in notable variations in junction functionality and mechanism of charge conduction. Physical parameters influencing the device characteristics such as dipole moment, molecule-electrode coupling strength, voltage division factor, and temperature have been extensively studied which offers modulation of the characteristics and device design. The dominant hopping current in Re complex bearing bipyridine linkage was found to be responsible for the observed asymmetric electrical (I-V) behavior. Our work paves the way for constructing various organometallic compounds-based molecular junctions to understand electronic functions and the underlying transport mechanisms., Comment: 17 pages, 8 figures