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Charged scalars appear in many motivated extensions beyond the Standard Model. We analyze the constraints on charged scalar pair production via the Drell-Yan process at the Large Hadron Collider and interpret them in terms of weak isospin quantum numbers. Leveraging the experimental limits from existing LHC data and phenomenological recast analyses, we place bounds on the branching ratio of the charged scalar, as a function of its mass, electric charge, and isospin. This approach enables to determine limits on the branching ratios directly from experimental data, without appealing to a specific model. We provide a detailed analysis for singly and doubly charged scalars across various weak isospin scenarios, focusing on decays into leptonic and bosonic final states, and validate this approach in extended Higgs sectors such as the Higgs triplet model and Georgi-Machacek model., Comment: 16 pages, 7 captioned figures. Comments are welcome

The impact of Artificial Intelligence (AI) is transforming various aspects of urban life, including, governance, policy and planning, healthcare, sustainability, economics, entrepreneurship, etc. Although AI immense potential for positively impacting urban living, its success depends on overcoming significant challenges, particularly in telecommunications infrastructure. Smart city applications, such as, federated learning, Internet of Things (IoT), and online financial services, require reliable Quality of Service (QoS) from telecommunications networks to ensure effective information transfer. However, with over three billion people underserved or lacking access to internet, many of these AI-driven applications are at risk of either remaining underutilized or failing altogether. Furthermore, many IoT and video-based applications in densely populated urban areas require high-quality connectivity. This paper explores these issues, focusing on the challenges that need to be mitigated to make AI succeed in emerging countries, where more than 80% of the world population resides and urban migration grows. In this context, an overview of a case study conducted in Kathmandu, Nepal, highlights citizens' aspirations for affordable, high-quality internet-based services. The findings underscore the pressing need for advanced telecommunication networks to meet diverse user requirements while addressing investment and infrastructure gaps. This discussion provides insights into bridging the digital divide and enabling AI's transformative potential in urban areas.

Federated learning (FL) is vulnerable to backdoor attacks, where adversaries alter model behavior on target classification labels by embedding triggers into data samples. While these attacks have received considerable attention in horizontal FL, they are less understood for vertical FL (VFL), where devices hold different features of the samples, and only the server holds the labels. In this work, we propose a novel backdoor attack on VFL which (i) does not rely on gradient information from the server and (ii) considers potential collusion among multiple adversaries for sample selection and trigger embedding. Our label inference model augments variational autoencoders with metric learning, which adversaries can train locally. A consensus process over the adversary graph topology determines which datapoints to poison. We further propose methods for trigger splitting across the adversaries, with an intensity-based implantation scheme skewing the server towards the trigger. Our convergence analysis reveals the impact of backdoor perturbations on VFL indicated by a stationarity gap for the trained model, which we verify empirically as well. We conduct experiments comparing our attack with recent backdoor VFL approaches, finding that ours obtains significantly higher success rates for the same main task performance despite not using server information. Additionally, our results verify the impact of collusion on attack performance., Comment: This paper is currently under review in the IEEE/ACM Transactions on Networking Special Issue on AI and Networking

The Masked Autoencoder (MAE) has recently demonstrated effectiveness in pre-training Vision Transformers (ViT) for analyzing natural images. By reconstructing complete images from partially masked inputs, the ViT encoder gathers contextual information to predict the missing regions. This capability to aggregate context is especially important in medical imaging, where anatomical structures are functionally and mechanically linked to surrounding regions. However, current methods do not consider variations in the number of input images, which is typically the case in real-world Magnetic Resonance (MR) studies. To address this limitation, we propose a 3D Adaptive Masked Autoencoders (AMAE) architecture that accommodates a variable number of 3D input contrasts per subject. A magnetic resonance imaging (MRI) dataset of 45,364 subjects was used for pretraining and a subset of 1648 training, 193 validation and 215 test subjects were used for finetuning. The performance demonstrates that self pre-training of this adaptive masked autoencoders can enhance the infarct segmentation performance by 2.8%-3.7% for ViT-based segmentation models., Comment: 5 pages, ISBI 2025 accepted

We study the classical scheduling problem of minimizing the makespan of a set of unit size jobs with precedence constraints on parallel identical machines. Research on the problem dates back to the landmark paper by Graham from 1966 who showed that the simple List Scheduling algorithm is a $(2-\frac{1}{m})$-approximation. Interestingly, it is open whether the problem is NP-hard if $m=3$ which is one of the few remaining open problems in the seminal book by Garey and Johnson. Recently, quite some progress has been made for the setting that $m$ is a constant. In a break-through paper, Levey and Rothvoss presented a $(1+\epsilon)$-approximation with a running time of $n^{(\log n)^{O((m^{2}/\epsilon^{2})\log\log n)}}$[STOC 2016, SICOMP 2019] and this running time was improved to quasi-polynomial by Garg[ICALP 2018] and to even $n^{O_{m,\epsilon}(\log^{3}\log n)}$ by Li[SODA 2021]. These results use techniques like LP-hierarchies, conditioning on certain well-selected jobs, and abstractions like (partial) dyadic systems and virtually valid schedules. In this paper, we present a QPTAS for the problem which is arguably simpler than the previous algorithms. We just guess the positions of certain jobs in the optimal solution, recurse on a set of guessed subintervals, and fill in the remaining jobs with greedy routines. We believe that also our analysis is more accessible, in particular since we do not use (LP-)hierarchies or abstractions of the problem like the ones above, but we guess properties of the optimal solution directly., Comment: Published in ESA 2022 (Track S)

We experimentally study nonlinear generation of the second harmonic by backward volume spin waves propagating in microscopic magnonic waveguides fabricated from a low-loss magnetic insulator with a thickness of several tens of nanometers. We show that highly efficient resonant second harmonic generation is possible in the inter-mode regime at microwave powers of the order of 10^-4 W. In contrast to previously observed second harmonic generation processes, the generation by backward waves is characterized by the nonlinearly generated waves propagating opposite to the initial waves, and can be realized at zero bias magnetic field.

The boundary of a billiard system dictates its dynamics, which can be integrable, mixed, or fully chaotic. Despite the significant implications of chaotic billiard systems with mixed curvatures, those whose boundaries feature both positive and negative curvature remain relatively under-explored. This study introduces two such billiards: a bean-shaped billiard and a peanut-shaped billiard, the latter being a variant of Cassini ovals. Unlike traditional chaotic billiards, these systems incorporate both focusing and defocusing regions along their boundaries, with no neutral segments. We examine both classical and quantum dynamics of these billiards and observe a strong alignment between the two perspectives. For classical analysis, the billiard flow diagram and billiard map reveal sensitivity to initial conditions, a hallmark of classical chaos. In the quantum domain, we use nearest-neighbour spacing distribution and spectral complexity as statistical measures to characterise chaotic behaviour. Both classical and quantum mechanical analysis are in firm agreement with each other. One of the most striking quantum phenomena we observe is the eigenfunction scarring (both scars and super-scars). Scarring phenomena serve as a rich visual manifestation of quantum and classical correspondence, and highlight quantum suppression chaos at a local level. This research contributes to a deeper understanding of chaos, especially in billiard systems with mixed curvature boundaries., Comment: 26 pages, 20 figures

A circular von Karman plate is considered bonded at its boundary to a circular Kirchhoff rod via a hinge like junction. There is a mismatch of dimension between the rod and the plate boundary in their respective stress free configurations. The process of gluing of the inextensible circular rod to the edge of the extensible plate causes the system to develop internal stress in the natural planar configuration. For some critical values of this mismatch the rod plate system, as expected, shows buckling behaviour in the interior or at the boundary of plate. In this paper, the corresponding bifurcation problem is formulated using the mismatch parameter as a bifurcation parameter. The non linear equations of equilibrium are linearized near the homogeneously deformed state and necessary conditions of bifurcation are solved for the critical geometric mismatch that is when non trivial solutions of the linearized equations exist. These critical points are candidates to be classified as bifurcation points. Additionally, the semi analytic nature of the analysis is exploited to perform a parametric study, relative to structure parameters in the problem formulation, of the critical points in the problem and the characteristic features are summarised. It is found that the rod plays an important role in determining the buckling behaviour when the plate's dimension is smaller than the looped rod, as in that case the rod buckles and the plate can bend or stretch depending on the planar or non planar nature of buckled mode of the rod. When the plate is larger, the rod effectively stimulates a rigid Dirichlet boundary condition due to its inextensibility; the critical points in this case are found to coincide with the case when buckling in the sole plate as a system is considered., Comment: 45 pages, 13 figures

We present a detailed study of the interacting triple active galactic nuclear system NGC 7733-34, focusing on stellar kinematics, ionised gas characteristics and star formation within the central region and stellar bars of both galaxies. We performed a comprehensive analysis using archival data from MUSE, HST/ACS, and DECaLS, complemented by observations from UVIT and IRSF. We identified a disc-like bulge in both NGC 7733 and NGC 7734 through 2-D decomposition. A central nuclear structure, with a semi-major axis of $\sim$1.113 kpc, was detected in NGC 7733 via photometric and kinematic analysis, confirmed by the strong anti-correlation between $V/\sigma$ and $h_{3}$, indicative of circular orbits in the centre. NGC 7734 lacks a distinct nuclear structure. The presence of disc-like bulge results in an anti-correlation between $V/\sigma$ and $h_{3}$ along with diffuse light. However, it does show higher central velocity dispersion, possibly attributed to an interaction with a smaller clump, which is likely a fourth galaxy within the system. Both galaxies demonstrate ongoing star formation, evidenced by $FUV$ and $H\alpha$ observations. NGC 7734 shows recent star formation along its bar, while NGC 7733 experiences bar quenching. The star formation rate (SFR) analysis of NGC 7734 reveals that the bar region's SFR dominates the galaxy's overall SFR. Conversely, in NGC 7733, the lack of star formation along the bar and the presence of a Seyfert 2 active galactic nuclei at the galaxy centre leave the possibility of a connection between both facts. However, it does not affect the galaxy's overall star formation. Our findings provide valuable insights into the stellar and gas kinematics, star formation processes, and active galactic nuclear feedback mechanisms in interacting galaxies hosting stellar bars., Comment: 15 pages, 11 figures, accepted for publication in A&A

The rapid rise in inverter-based renewable resources has heightened concerns over subsynchronous resonance and oscillations, thereby challenging grid stability. This paper reviews approaches to identify and mitigate these issues, focusing on frequency scanning methods for stability assessment. It categorizes white-, black-, and gray-box modeling techniques, compares positive-sequence, dq-frame, and alpha-beta domain scanning, and examines perturbation shapes like step, ramp, and chirp. A comparative study highlights their strengths, limitations, and suitability for specific scenarios. By summarizing past events and surveying available tools, this work guides operators and researchers toward more effective, reliable stability analysis methods in grids with high renewable penetration.

We theoretically consider disorder and temperature effects on the integer quantum Hall effect (IQHE) using a variety of distinct and complementary analytical and numerical techniques. In particular, we address simple, physical, and experimentally relevant questions: How does disorder and/or temperature affect the IQHE plateau width? Does the plateau width increase or decrease with disorder and/or temperature? What happens to the peak in the longitudinal conductance with increasing disorder/temperature? Does the longitudinal conductance obey any universal scaling property? Is there "floating" with increasing disorder and/or decreasing magnetic field? Can disorder destroy the IQHE? Is there an IQHE to localization transition? What is the Landau level dependence of the plateau width? Our detailed theory provides answers to these and other related experimentally relevant questions. We discuss our results in the context of existing experimental results and suggest future experiments arising from our work. A key finding is that disorder and temperature are intrinsically connected in affecting IQHE, and there is an intricate interplay between them leading to nonmonotonicity in how the IQHE plateau width behaves as a function of increasing disorder. Both must be considered on an equal footing in understanding IQHE experiments., Comment: 24 pages, 18 figures

We investigate the relativistic, viscous, advective, neutrino-dominated accretion flows (NDAFs) around rotating stellar mass black holes, incorporating neutrino cooling. By adopting an effective potential to describe the spacetime geometry around the rotating black holes, we self-consistently solve the governing NDAF equations to obtain global transonic accretion solutions. Our findings indicate that, depending on the model parameters, namely energy ($\varepsilon$), angular momentum ($\lambda$), accretion rate ($\dot{m}$), viscosity ($\alpha$) and black hole spin ($a_{\rm k}$), NDAFs may harbor standing shocks where the Rankine-Hugoniot shock conditions (RHCs) are satisfied. Utilizing these shock-induced NDAF solutions, we compute the neutrino luminosity ($L_{\nu}$) and neutrino annihilation luminosity ($L_{\nu \bar{\nu}}$) across a wide range of model parameters. We further calculate maximum neutrino luminosity ($L_{\nu}^{\rm max}$) and neutrino annihilation luminosity ($L_{\nu \bar{\nu}}^{\rm max}$) resulting in $L_{\nu}^{\rm max} \sim 10^{51-53}$ erg s$^{-1}$ ($10^{48-51}$ erg s$^{-1}$) and $L_{\nu \bar{\nu}}^{\rm max} \sim 10^{48-52}$ erg s$^{-1}$ ($10^{42-49}$ erg s$^{-1}$) for $a_{\rm k}=0.99$ (0.0). These findings suggest that shocked NDAF solutions are potentially promising to explain the energy output of gamma-ray bursts (GRBs). We employ our NDAF model formalism to elucidate $L^{\rm obs}_{\nu \bar{\nu}}$ for five GRBs with known redshifts and estimate their accretion rate (${\dot m}$) based on the spin ($a_{\rm k}$) of the central source of GRBs under consideration., Comment: 13 pages, 7 figures, 1 table, To appear in the Astrophysical Journal

Incorporating cells within active biomaterial scaffolds is a promising strategy to develop forefront materials that can autonomously sense, respond, and alter the scaffold in response to environmental cues or internal cell circuitry. Using dynamic biocompatible scaffolds that can self-alter their properties via crosslinking and motor-driven force-generation opens even greater avenues for actuation and control. However, the design principles associated with engineering active scaffolds embedded with cells are not well established. To address this challenge, we design a dynamic scaffold material of bacteria cells embedded within a composite cytoskeletal network of actin and microtubules that can be passively or actively crosslinked by either biotin-streptavidin or multimeric kinesin motors. Using quantitative microscopy, we demonstrate the ability to embed cells of volume fractions 0.4 to 2% throughout the network without compromising the structural integrity of the network or inhibiting crosslinking or motor-driven dynamics. Our findings suggest that both passive and active crosslinking promote entrainment of cells within the network, while depletion interactions play a more important role in uncrosslinked networks. Moreover, we show that large-scale structures emerge with the addition of cell fractions as low as 0.4%, but these structures do not influence the microscale structural lengthscale of the materials. Our work highlights the potential of our composite biomaterial in designing autonomous materials controlled by cells, and provides a roadmap for effectively coupling cells to complex composite materials with an eye towards using cells as in situ factories to program material modifications.

The goal of the project QLEAP (2022-24), funded by Business Finland and participating organizations, was to study using containers as elements of architecture design. Such systems include containerized AI systems, using containers in a hybrid setup (public/hybrid/private clouds), and related security concerns. The consortium consists of four companies that represent different concerns over using containers (Bittium, M-Files, Solita/ADE Insights, Vaadin) and one research organization (University of Jyv\"askyl\"a). In addition, it has received support from two Veturi companies - Nokia and Tietoevry - who have also participated in steering the project. Moreover, the SW4E ecosystem has participated in the project. This document gathers the key lessons learned from the project.

A generalized Sellmeier model, also referred to as the Lorentz-Dirac model, has been used for the description of the dielectric function of a number of technologically important materials in the literature. This model represents the frequency-dependent dielectric function as a sum over Green functions of classical damped harmonic oscillators, much in analogy with the functional form used for the dynamic polarizability of an atom, but with one important addition, namely, a complex-valued oscillator strength in the numerator. Here, we show that this generalized functional form can be justified based on the response function of coupled damped oscillators. The encountered analogies suggest an explanation for the generally observed success of the Lorentz--Dirac model in describing the dielectric function of crystals of consummate technological significance., Comment: 9 pages; RevTeX

Due to traits of CMOS compatibility and scalability, HfO2-based ferroelectrics are promising candidates for next-generation memory devices. However, their commercialization has been greatly hindered by reliability issues, with fatigue being a major impediment. We report the fatigue-free behavior in interface-designed Hf0.5Zr0.5O2-based heterostructures. A coherent CeO2-x/Hf0.5Zr0.5O2 heterointerface is constructed, wherein CeO2-x acts as an oxygen sponge, capable of reversibly accepting and releasing oxygen vacancies. This design effectively alleviates defect aggregation at the electrode-ferroelectric interface, enabling improved switching characteristics. Further, a symmetric capacitor architecture is designed to minimize the imprint, thereby suppressing the cycling-induced oriented defect drift. The two-pronged technique mitigates oxygen-voltammetry-generated chemical/energy fluctuations, suppressing the formation of paraelectric phase and polarization degradation. The design ensures a fatigue-free feature exceeding 10^11 switching cycles and an endurance lifetime surpassing 10^12 cycles for Hf0.5Zr0.5O2-based capacitors, along with excellent temperature stability and retention. These findings pave the way for developing ultra-stable hafnia-based ferroelectric devices., Comment: 20 pages, 4 figures

Speech enhancement (SE) aims to improve the clarity, intelligibility, and quality of speech signals for various speech enabled applications. However, air-conducted (AC) speech is highly susceptible to ambient noise, particularly in low signal-to-noise ratio (SNR) and non-stationary noise environments. Incorporating multi-modal information has shown promise in enhancing speech in such challenging scenarios. Electromyography (EMG) signals, which capture muscle activity during speech production, offer noise-resistant properties beneficial for SE in adverse conditions. Most previous EMG-based SE methods required 35 EMG channels, limiting their practicality. To address this, we propose a novel method that considers only 8-channel EMG signals with acoustic signals using a modified SEMamba network with added cross-modality modules. Our experiments demonstrate substantial improvements in speech quality and intelligibility over traditional approaches, especially in extremely low SNR settings. Notably, compared to the SE (AC) approach, our method achieves a significant PESQ gain of 0.235 under matched low SNR conditions and 0.527 under mismatched conditions, highlighting its robustness., Comment: Accepted by ICASSP 2025

Frequency-dependence of specific heat in supercooled hard sphere liquid is computed using quantum mode-coupling theory (QMCT). Mode-coupling equations are solved using recently proposed perturbative method that allows to study relaxation in the moderate quantum regime where quantum effects assist liquid to glass transition. Zwanzig's formulation is used to compute the frequency-dependent specific heat in supercooled state using dynamical information from QMCT. Specific heat shows strong variation as the quantumness of the liquid is changed, which becomes more significant as density is increased. It is found that, near the transition point, different dynamical modes contribute to the specific heat in the classical and the quantum liquids.

We analyze dynamics of quantum supercooled liquids in terms of tagged particle dynamics. Unlike the classical case, uncertainty in the position of a particle in quantum liquid leads to qualitative changes. We demonstrate these effects in the dynamics of the first two moments of displacements, namely, the mean-squared displacement, $\langle \Delta r^2(t)\rangle$, and $\langle \Delta r^4(t)\rangle$. Results are presented for a hard sphere liquid using mode-coupling theory (MCT) formulation and simulation on a binary Lennard-Jones liquid. As the quantumness (controlled by the de-Broglie thermal wavelength) is increased, a non-zero value of the moments at zero time leads to significant deviations from the classical behavior in the initial dynamics. Initial displacement shows ballistic behavior $\langle \Delta r^2(t)\rangle\sim t^2$, but, as a result of large uncertainty in the position, the dynamical effects become weaker with increasing quantumness over this time scale.

Action detection in real-world scenarios is particularly challenging due to densely distributed actions in hour-long untrimmed videos. It requires modeling both short- and long-term temporal relationships while handling significant intra-class temporal variations. Previous state-of-the-art (SOTA) Transformer-based architectures, though effective, are impractical for real-world deployment due to their high parameter count, GPU memory usage, and limited throughput, making them unsuitable for very long videos. In this work, we innovatively adapt the Mamba architecture for action detection and propose Multi-scale Temporal Mamba (MS-Temba), comprising two key components: Temporal Mamba (Temba) Blocks and the Temporal Mamba Fuser. Temba Blocks include the Temporal Local Module (TLM) for short-range temporal modeling and the Dilated Temporal SSM (DTS) for long-range dependencies. By introducing dilations, a novel concept for Mamba, TLM and DTS capture local and global features at multiple scales. The Temba Fuser aggregates these scale-specific features using Mamba to learn comprehensive multi-scale representations of untrimmed videos. MS-Temba is validated on three public datasets, outperforming SOTA methods on long videos and matching prior methods on short videos while using only one-eighth of the parameters.

Let $G$ be a group and $L(G)$ be the set of all subgroups of $G$. The subgroup generating bipartite graph $\mathcal{B}(G)$ defined on $G$ is a bipartite graph whose vertex set is partitioned into two sets $G \times G$ and $L(G)$, and two vertices $(a, b) \in G \times G$ and $H \in L(G)$ are adjacent if $H$ is generated by $a$ and $b$. In this paper, we deduce expressions for first and second Zagreb indices of $\mathcal{B}(G)$ and obtain a condition such that $\mathcal{B}(G)$ satisfy Hansen-Vuki{\v{c}}evi{\'c} conjecture [Hansen, P. and Vuki{\v{c}}evi{\'c}, D. Comparing the Zagreb indices, {\em Croatica Chemica Acta}, \textbf{80}(2), 165-168, 2007]. It is shown that $\mathcal{B}(G)$ satisfies Hansen-Vuki{\v{c}}evi{\'c} conjecture if $G$ is a cyclic group of order $2p, 2p^2, 4p$, $4p^2$ and $p^n$; dihedral group of order $2p$ and $2p^2$; and dicyclic group of order $4p$ and $4p^2$ for any prime $p$. While computing Zagreb indices of $\mathcal{B}(G)$ we have computed $\deg_{\mathcal{B}(G)}(H)$ for all $H \in L(G)$ for the above mentioned groups. Using these information we also compute Randic Connectivity index, Atom-Bond Connectivity index, Geometric-Arithmetic index, Harmonic index and Sum-Connectivity index of $\mathcal{B}(G)$., Comment: 17 pages

Purpose: Diabetic retinopathy (DR) is a major cause of vision loss, particularly in India, where access to retina specialists is limited in rural areas. This study aims to evaluate the Artificial Intelligence-based Diabetic Retinopathy Screening System (AIDRSS) for DR detection and prevalence assessment, addressing the growing need for scalable, automated screening solutions in resource-limited settings. Approach: A multicentric, cross-sectional study was conducted in Kolkata, India, involving 5,029 participants and 10,058 macula-centric retinal fundus images. The AIDRSS employed a deep learning algorithm with 50 million trainable parameters, integrated with Contrast Limited Adaptive Histogram Equalization (CLAHE) preprocessing for enhanced image quality. DR was graded using the International Clinical Diabetic Retinopathy (ICDR) Scale, categorizing disease into five stages (DR0 to DR4). Statistical metrics including sensitivity, specificity, and prevalence rates were evaluated against expert retina specialist assessments. Results: The prevalence of DR in the general population was 13.7%, rising to 38.2% among individuals with elevated random blood glucose levels. The AIDRSS achieved an overall sensitivity of 92%, specificity of 88%, and 100% sensitivity for detecting referable DR (DR3 and DR4). These results demonstrate the system's robust performance in accurately identifying and grading DR in a diverse population. Conclusions: AIDRSS provides a reliable, scalable solution for early DR detection in resource-constrained environments. Its integration of advanced AI techniques ensures high diagnostic accuracy, with potential to significantly reduce the burden of diabetes-related vision loss in underserved regions., Comment: 22 pages, 5 figures

Self-assembled nano and micro-structures, particularly those capable of responsive erasure and regeneration, have garnered significant interest for their applications in smart photonics and electronics. However, current techniques for modulating these architectures largely depend on network rearrangement, posing challenges for in situ regeneration. Furthermore, their common fabrication techniques are complex and uncontrolled with the structures formed not being amenable for large area applications, thus compromising their economic viability. Herein, we present a controlled thermal process strategy for fabricating large-area, dynamically tunable, 1D,2D and 3D micro and nanostructures on a wide range of compatible materials including metals, semiconductors and polymers. By tuning the temperature changes in the system, thermal expansion coefficients of thin films and substrates, surface energy, Youngs modulus and thickness of the thin films we achieve robust, uniform, periodic structures over extensive areas on soft and stretchable substrates. The process is further supported by a theoretical model that we developed and validated by experiments and simulations. To showcase the robustness of our approach, we present prototypes of dynamically tunable diffraction gratings, optical diffusers, large-area reflective displays, camouflage devices, out-coupling efficiency enhancers, wearable devices and mechanochromic sensors., Comment: The legend to figure 1 was missing in the previous version

Large Vision Language Models (LVLMs) have demonstrated impressive capabilities in video understanding, yet their adoption for Activities of Daily Living (ADL) remains limited by their inability to capture fine-grained interactions and spatial relationships. This limitation is particularly evident in ADL tasks, where understanding detailed human-object interaction and human-centric motion is crucial for applications such as elderly monitoring and cognitive assessment. To address this, we aim to leverage the complementary nature of egocentric views to enhance LVLM's understanding of exocentric ADL videos. Consequently, we propose an online ego2exo distillation approach to learn ego-augmented exo representations in LVLMs. While effective, this approach requires paired ego-exo training data, which is impractical to collect for real-world ADL scenarios. Consequently, we develop EgoMimic, a skeleton-guided method that can generate mimicked ego views from exocentric videos. We find that the exo representations of our ego-augmented LVLMs successfully learn to extract ego-perspective cues, demonstrated through comprehensive evaluation on six ADL benchmarks and our proposed EgoPerceptionMCQ benchmark designed specifically to assess egocentric understanding from exocentric videos. Code, models, and data will be open-sourced at https://github.com/dominickrei/EgoExo4ADL.

Phonon modes and their association with the electronic states have been investigated for the metallic EuCu$_{2}$As$_{2}$ system. In this work, we present the Raman spectra of this pnictide system which clearly shows the presence of seven well defined peaks above $100$~cm$^{-1}$ that is consistent with the locally non-centrosymmetric {\it P4/nmm} crystal structure, contrary to that what is expected from the accepted symmorphic {\it I4/mmm} structure. Lattice dynamics calculations using the {\it P4/nmm} symmetry attest that there is a commendable agreement between the calculated phonon spectra at the $\Gamma$ point and the observed Raman mode frequencies, with the most intense peak at $\sim 232$~cm$^{-1}$ being ascribed to the A$_{1g}$ mode. Temperature dependent Raman measurements show that there is a significant deviation from the expected anharmonic behaviour around $165$~K for the A$_{1g}$ mode, with anomalies being observed for several other modes as well, although to a lesser extent. Attempts are made to rationalize the observed anomalous behavior related to the hardening of the phonon modes, with parallels being drawn from metal dichalcogenide and allied systems. Similarities in the evolution of the Raman peak frequencies with temperature seem to suggest a strong signature of a subtle electronic density wave instability below $165$~K in this compound.

Achieving uniform nanowire size, density, and alignment across a wafer is challenging, as small variations in growth parameters can impact performance in energy harvesting devices like solar cells and photodetectors. This study demonstrates the in-depth characterization of uniformly grown GaAs/AlGaAs core-shell nanowires on a two-inch Si(111) substrate using Ga-induced self-catalyzed molecular beam epitaxy. By integrating Scanning Electron Microscopy and Time Correlated Single-Photon Counting, we establish a detailed model of structural and optoelectronic properties across wafer and micron scales. While emission intensity varies by up to 35%, carrier lifetime shows only 9% variation, indicating stable material quality despite structural inhomogeneities. These findings indicate that, for the two-inch GaAs/AlGaAs nanowire wafer, achieving uniform nanowire coverage had a greater impact on consistent optoelectronic properties than variations in material quality, highlighting its significance for scalable III-V semiconductor integration on silicon in advanced optoelectronic devices such as solar cells and photodetectors.

In this study, the intermittency behavior of emitted particles produced in heavy ion collisions has been studied using both modes (default $\&$ string melting) of A Multi Phase Transport (AMPT) model-generated data. We adopted one of the most conventional and successful techniques, the Scaled Factorial Moment (SFM) method, using Monte Carlo (MC) data for 10 AGeV Au+Au collisions in search of intermittency in the model-generated data. Our interest is to search for intermittency behavior of particles that leads to multiplicity fluctuations and that would reveal a phase transition from hadronic matter to QGP. In this article, the intermittency values for both modes of AMPT data are presented. The results obtain some insight into the dynamics of heavy ion collisions and the formation of QGP., Comment: A complete article with eight figures

The excitation of bound states in the continuum (BICs) in two- or multi-qubit systems lies at the heart of entanglement generation and harnessing in waveguide quantum electrodynamics platforms. However, the generation of qubit pair BICs through single-photon scattering is hindered by the fact that these states are effectively decoupled from propagating photons. We prove that scattering of a parity-invariant single photon on a qubit pair, combined with a properly engineered time variation of the qubit detuning, is not only feasible, but also more effective than strategies based on the relaxation of the excited states of the qubits. The use of tensor network methods to simulate the proposed scheme enables to include photon delays in collision models, thus opening the possibility to follow the time evolution of the full quantum system, including qubits and field, and to efficiently implement and characterize the dynamics in non-ideal cases, which turn out to be optimal for the BIC generation strategy., Comment: 10 pages, 4 figures. For associated video, see http://drive.google.com/file/d/1DJSWkWYcf8sV5oVKmoLxkNXZ-26SuPhJ/view

Some microscopic dynamics are also macroscopically irreversible, dissipating energy and producing entropy. For many-particle systems interacting with deterministic thermostats, the rate of thermodynamic entropy dissipated to the environment is the average rate at which phase space contracts. Here, we use this identity and the properties of a classical density matrix to derive upper and lower bounds on the entropy flow rate with the spectral properties of the local stability matrix. These bounds are an extension of more fundamental bounds on the Lyapunov exponents and phase space contraction rate of continuous-time dynamical systems. They are maximal and minimal rates of entropy production, heat transfer, and transport coefficients set by the underlying dynamics of the system and deterministic thermostat. Because these limits on the macroscopic dissipation derive from the density matrix and the local stability matrix, they are numerically computable from the molecular dynamics. As an illustration, we show that these bounds are on the electrical conductivity for a system of charged particles subject to an electric field., Comment: Published in J. Phys. A: Math. Theor., unnecessary autolinking in the abstract removed

Contributions from the Indian gravity community have played a significant role in shaping several branches of astronomy and astrophysics. This document reviews some of the most important contributions and presents a vision for gravity research in the context of astronomy \& astrophysics in India. This is an expanded version of one of the chapters in the recently released Vision Document of the Astronomical Society of India., Comment: Published in JoAA special issue "Indian Astronomy in the Global Context: A compendium of white papers submitted towards the Astronomical Society of India Vision Document (2024"

Although the star formation process has been studied for decades, many important aspects of the physics involved remain unsolved. Recent advancement of instrumentation in the infrared, far-infrared and sub-millimetre wavelength regimes have contributed to a significantly improved understanding of processes in the interstellar medium (ISM) leading to star formation. The future of research on the ISM and star formation looks exciting with instruments like the JWST, ALMA, etc., already contributing to the topic by gathering high-resolution high-sensitivity data and with several larger ground- and space-bound facilities either being planned or constructed. India has a sizable number of astronomers engaged in research on topics related to the ISM and star formation. In this white paper invited by the Astronomical Society of India to prepare a vision document for Indian astronomy, we review the Indian contributions to the global understanding of the star formation process and suggest areas that require focused efforts both in creating observing facilities and in theoretical front in India, in order to improve the impact of our research in the coming decades., Comment: Accepted for publication in The Journal of Astrophysics and Astronomy Special Issue: Indian Astronomy in the Global Context: A compendium of white papers submitted towards the Astronomical Society of India Vision Document (2024)

We study the possibility of producing axion dark matter (DM) via misalignment mechanisms in a non-standard cosmological era dominated by ultra-light primordial black holes (PBH). While the effect of PBH domination on the production of axion via vacuum misalignment is known assuming the PBH evaporation to proceed according to Hawking's semi-classical (SC) approximation, we go beyond these simplest possibilities to include kinetic misalignment of axion and backreaction effect of emitted particles on the PBH themselves, referred to as the memory-burden (MB) effect. We show that, depending upon the type of misalignment mechanism and PBH evaporation regime, the axion as well as PBH parameter space consistent with the observed DM relic changes significantly having interesting implications for axion detection experiments. PBH also offer complementary detection prospects via gravitational wave due to PBH density fluctuations and excess radiation due to emission of hot axions within reach of future cosmic microwave background experiments., Comment: 32 pages, 14 captioned figures

We study the geometric optics limit of the electrodynamics in the presence of Lorentz violating Chern-Simons term in (3+1) dimensions. The Chern-Simons term couples the dual electromagnetic tensor to an external four-vector and the electromagnetic gauge field. For a fixed external four-vector, such a Chern-Simons term violates Lorentz invariance while maintaining the gauge invariance of the theory. In this analysis, we look into the consequences of Lorentz symmetry violating Chern-Simons term within the geometric optics limit of light rays propagating from a source to an observation point. We argue that the Ricci tensor and the Lorentz-violating term modify the dynamical equation for the gauge vector field. However, in the geometric optics limit, neither the space-time curvature nor the Chern-Simons term influences the intensity of light. Unlike the intensity, the polarization of light, on the other hand, can be influenced by the Lorentz-violating Chern-Simons term. Due to such an effect in the presence of Chern-Simons term, the photon emitting from astrophysical objects can undergo a change in polarization as it propagates in space., Comment: 5 pages, no figures, comments and suggestions are welcome

Vesel\'y (1997) studied Banach spaces that admit $f$-centers for finite subsets of the space. In this work, we introduce the concept of $\mr{F}$-simultaneous approximative $\tau$-compactness property ($\tau$-$\mr{F}$-SACP in short) for triplets $(X, V,\mf{F})$, where $X$ is a Banach space, $V$ is a $\tau$-closed subset of $X$, $\mf{F}$ is a subfamily of closed and bounded subsets of $X$, $\mr{F}$ is a collection of functions, and $\tau$ is the norm or weak topology on $X$. We characterize reflexive spaces with the Kadec-Klee property using triplets with $\tau$-$\mr{F}$-SACP. We investigate the relationship between $\tau$-$\mr{F}$-SACP and the continuity properties of the restricted $f$-center map. The study further examines $\tau$-$\mr{F}$-SACP in the context of $CLUR$ spaces and explores various characterizations of $\tau$-$\mr{F}$-SACP, including connections to reflexivity, Fr\'echet smoothness, and the Kadec-Klee property.

We introduce FACTS Grounding, an online leaderboard and associated benchmark that evaluates language models' ability to generate text that is factually accurate with respect to given context in the user prompt. In our benchmark, each prompt includes a user request and a full document, with a maximum length of 32k tokens, requiring long-form responses. The long-form responses are required to be fully grounded in the provided context document while fulfilling the user request. Models are evaluated using automated judge models in two phases: (1) responses are disqualified if they do not fulfill the user request; (2) they are judged as accurate if the response is fully grounded in the provided document. The automated judge models were comprehensively evaluated against a held-out test-set to pick the best prompt template, and the final factuality score is an aggregate of multiple judge models to mitigate evaluation bias. The FACTS Grounding leaderboard will be actively maintained over time, and contains both public and private splits to allow for external participation while guarding the integrity of the leaderboard. It can be found at https://www.kaggle.com/facts-leaderboard.

The rapid rise of large language models (LLMs) has unlocked many applications but also underscores the challenge of aligning them with diverse values and preferences. Direct Preference Optimization (DPO) is central to alignment but constrained by fixed divergences and limited feature transformations. We propose DPO-Kernels, which integrates kernel methods to address these issues through four key contributions: (i) Kernelized Representations with polynomial, RBF, Mahalanobis, and spectral kernels for richer transformations, plus a hybrid loss combining embedding-based and probability-based objectives; (ii) Divergence Alternatives (Jensen-Shannon, Hellinger, Renyi, Bhattacharyya, Wasserstein, and f-divergences) for greater stability; (iii) Data-Driven Selection metrics that automatically choose the best kernel-divergence pair; and (iv) a Hierarchical Mixture of Kernels for both local precision and global modeling. Evaluations on 12 datasets demonstrate state-of-the-art performance in factuality, safety, reasoning, and instruction following. Grounded in Heavy-Tailed Self-Regularization, DPO-Kernels maintains robust generalization for LLMs, offering a comprehensive resource for further alignment research.

Mesoscopic active systems exhibit various unique behaviours - absent in passive systems - due to the forces generated by the corresponding constituents by converting their available free energies. However, finding out these forces - which are also stochastic and remain intertwined with the thermal noise - is especially non-trivial. Here, we introduce a technique to extract such fluctuating active forces, with statistical accuracy, acting on a passive particle immersed in an active bath by filtering out the related thermal noise. First, we test the efficacy of our method under numerical scenarios and then apply it to the experimental trajectories of a microscopic particle (optically) trapped inside an active bath consisting of motile E.Coli. bacteria. We believe that our approach would be rather effective in the actual measurement of unknown active forces, which are a crucial component in processes involving living matter., Comment: 9 pages, 5 figures

With the largest population of the world and one of the highest enrolments in higher education, India needs efficient and effective means to educate its learners. India started focusing on open and digital education in 1980's and its efforts were escalated in 2009 through the NMEICT program of the Government of India. A study by the Government and FICCI in 2014 noted that India cannot meet its educational needs just by capacity building in brick and mortar institutions. It was decided that ongoing MOOCs projects under the umbrella of NMEICT will be further strengthened over its second (2017-21) and third (2021-26) phases. NMEICT now steers NPTEL or SWAYAM (India's MOOCs) and several digital learning projects including Virtual Labs, e-Yantra, Spoken Tutorial, FOSSEE, and National Digital Library on India - the largest digital education library in the world. Further, India embraced its new National Education Policy in 2020 to strongly foster online education. In this chapter, we take a deep look into the evolution of MOOCs in India, its innovations, its current status and impact, and the roadmap for the next decade to address its challenges and grow. AI-powered MOOCs is an emerging opportunity for India to lead MOOCs worldwide.

Customer Lifetime Value (CLV) is an important metric that measures the total value a customer will bring to a business over their lifetime. The Beta Geometric Negative Binomial Distribution (BGNBD) and Gamma Gamma Distribution are two models that can be used to calculate CLV, taking into account both the frequency and value of customer transactions. This article explains the BGNBD and Gamma Gamma Distribution models, and how they can be used to calculate CLV for NFT (Non-Fungible Token) transaction data in a blockchain setting. By estimating the parameters of these models using historical transaction data, businesses can gain insights into the lifetime value of their customers and make data-driven decisions about marketing and customer retention strategies., Comment: 10 pages, 8 figures

Given an analytic function $f=u+iv$ in the unit disk $\mathbb{D}$, Zygmund's theorem gives the minimal growth restriction on $u$ which ensures that $v$ is in the Hardy space $h^1$. This need not be true if $f$ is a complex-valued harmonic function. However, we prove that Zygmund's theorem holds if $f$ is a harmonic $K$-quasiregular mapping in $\ID$. Our work makes further progress on the recent Riesz-type theorem of Liu and Zhu (Adv. Math., 2023), and the Kolmogorov-type theorem of Kalaj (J. Math. Anal. Appl., 2025), for harmonic quasiregular mappings. We also obtain a partial converse, thus showing that the proposed growth condition is the best possible. Furthermore, as an application of the classical conjugate function theorems, we establish a harmonic analogue of a well-known result of Hardy and Littlewood., Comment: 12 pages

For the first time, we present the model-independent two-loop effective action up to dimension six after integrating out heavy scalar(s) employing the Heat-Kernel method. We compute the effective operators that emerge at two-loop for two example models: heavy electroweak complex Triplet and Doublet scalars. We present our results on the SILH basis. We also capture the effect in the fermion sector. For these two scenarios, we compute all the fermionic effective operators up to dimension six., Comment: 36 pages, 1 figure, 5 tables

We study the evolution of the progenitors of the present-day Green Valley (GV) galaxies across redshift $z=10-0$ using data from the EAGLE simulations. We identify the present-day green valley galaxies using entropic thresholding and track the evolution of the physical properties of their progenitors up to $z=10$. Our study identifies three distinct phases in their evolution: (i) an early growth phase ($z=10-6$), where progenitors are gas-rich, efficiently form stars, and experience AGN feedback regulating star formation in massive galaxies, (ii) a transition phase ($z=6-2$), marked by frequent interactions and mergers in higher-density environments, driving starbursts, depleting gas reservoirs, and strengthening correlations between cold gas and halo properties, and (iii) a quenching phase ($z=2-0$), dominated by environmental and mass-dependent processes that suppress star formation and deplete cold gas. Our analysis shows that at $z<1$, environmental factors and cold gas depletion dominate quenching, with tighter correlations between stellar mass, SFR, and cold gas content. The interplay between mass and environmental density during this period drives diverse and distinct evolutionary pathways. Low-mass progenitors evolve gradually in low-density regions due to secular processes and slow gas depletion, while those in high-density environments quench rapidly via environmental mechanisms. High-mass progenitors in low-density environments exhibit prolonged green valley phases driven by internal processes. In contrast, those in dense environments undergo quenching more quickly due to the combined effects of internal and external processes. Our findings provide a comprehensive view of the mechanisms shaping the GV population across cosmic time., Comment: 27 pages, 15 figures, comments are welcome

Localization is the challenge of determining the robot's pose in a mapped environment. This is done by implementing a probabilistic algorithm to filter noisy sensor measurements and track the robot's position and orientation. This paper focuses on localizing a robot in a known mapped environment using Adaptive Monte Carlo Localization or Particle Filters method and send it to a goal state. ROS, Gazebo and RViz were used as the tools of the trade to simulate the environment and programming two robots for performing localization., Comment: 9 pages, 11 figures

For $t\geq 2$, the $t$-independence complex of a graph $G$ is the collection of all $A\subseteq V(G)$ such that each connected component of the induced subgraph $G[A]$ has at most $t-1$ vertices. The Stanley-Reisner ideal $I_{t}(G)$ of the $t$-independence complex of $G$, called $t$-connected ideal, is generated by monomials in a polynomial ring $R$ corresponding to all $A\subseteq V(G)$ of size $t$ such that $G[A]$ is connected. This class of ideals is a natural generalization of the edge ideals of graphs. In this paper, we investigate the $t$-connected ideals of chordal graphs. In particular, we prove that for a chordal graph $G$ and for all $t$ \[ \mathrm{reg}(R/I_{t}(G))=(t-1)\nu_{t}(G) \text{ and } \mathrm{pd}(R/I_{t}(G))=\mathrm{bight}(I_{t}(G)), \] where $\nu_{t}(G)$ denotes the induced matching number of the corresponding hypergraph of $I_{t}(G)$, and $\mathrm{reg}$, $\mathrm{pd}$ and $\mathrm{bight}$ stand for the regularity, projective dimension, and big height, respectively. As a consequence of the above results, we completely characterize when the $t$-connected ideal of a chordal graph has a linear resolution as well as when it satisfies the Cohen-Macaulay property. The above formulas and their consequences can be seen as a nice generalization of the classical results corresponding to the edge ideals of chordal graphs., Comment: 14 pages, 1 figure

Diabetic Retinopathy (DR) is a leading cause of preventable blindness. Early detection at the DR1 stage is critical but is hindered by a scarcity of high-quality fundus images. This study uses StyleGAN3 to generate synthetic DR1 images characterized by microaneurysms with high fidelity and diversity. The aim is to address data scarcity and enhance the performance of supervised classifiers. A dataset of 2,602 DR1 images was used to train the model, followed by a comprehensive evaluation using quantitative metrics, including Frechet Inception Distance (FID), Kernel Inception Distance (KID), and Equivariance with respect to translation (EQ-T) and rotation (EQ-R). Qualitative assessments included Human Turing tests, where trained ophthalmologists evaluated the realism of synthetic images. Spectral analysis further validated image quality. The model achieved a final FID score of 17.29, outperforming the mean FID of 21.18 (95 percent confidence interval - 20.83 to 21.56) derived from bootstrap resampling. Human Turing tests demonstrated the model's ability to produce highly realistic images, though minor artifacts near the borders were noted. These findings suggest that StyleGAN3-generated synthetic DR1 images hold significant promise for augmenting training datasets, enabling more accurate early detection of Diabetic Retinopathy. This methodology highlights the potential of synthetic data in advancing medical imaging and AI-driven diagnostics., Comment: 13 pages, 11 figures

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 report a sequential two-step vapor deposition process for growing mixed-dimensional van der Waals (vdW) materials, specifically Te nanowires (1D) and MoS$_2$ (2D), on a single SiO$_2$ wafer. Our growth technique offers a unique potential pathway to create large scale, high-quality, defect-free interfaces. The assembly of samples serves a twofold application: first, the as-prepared heterostructures (Te NW/MoS$_2$) provide insights into the atomically thin depletion region of a 1D/2D vdW diode, as revealed by electrical transport measurements and density functional theory-based quantum transport calculations. The charge transfer at the heterointerface is confirmed using Raman spectroscopy and Kelvin probe force microscopy (KPFM). We also observe modulation of the rectification ratio with varying applied gate voltage. Second, the non-hybrid regions on the substrate, consisting of the as-grown individual Te nanowires and MoS$_2$ microstructures, are utilized to fabricate separate p- and n-FETs, respectively. Furthermore, the ionic liquid gating helps to realize low-power CMOS inverter and all basic logic gate operations using a pair of n- and p- field-effect transistors (FETs) on Si/SiO$_2$ platform. This approach also demonstrates the potential for unifying diode and CMOS circuits on a single platform, opening opportunities for integrated analog and digital electronics.

Applying pseudo labeling techniques has been found to be advantageous in semi-supervised 3D object detection (SSOD) in Bird's-Eye-View (BEV) for autonomous driving, particularly where labeled data is limited. In the literature, Exponential Moving Average (EMA) has been used for adjustments of the weights of teacher network by the student network. However, the same induces catastrophic forgetting in the teacher network. In this work, we address this issue by introducing a novel concept of Reflective Teacher where the student is trained by both labeled and pseudo labeled data while its knowledge is progressively passed to the teacher through a regularizer to ensure retention of previous knowledge. Additionally, we propose Geometry Aware BEV Fusion (GA-BEVFusion) for efficient alignment of multi-modal BEV features, thus reducing the disparity between the modalities - camera and LiDAR. This helps to map the precise geometric information embedded among LiDAR points reliably with the spatial priors for extraction of semantic information from camera images. Our experiments on the nuScenes and Waymo datasets demonstrate: 1) improved performance over state-of-the-art methods in both fully supervised and semi-supervised settings; 2) Reflective Teacher achieves equivalent performance with only 25% and 22% of labeled data for nuScenes and Waymo datasets respectively, in contrast to other fully supervised methods that utilize the full labeled dataset.

We propose a hybrid scotogenic inverse seesaw framework in which the Majorana mass term is generated at the one-loop level through the inclusion of a singlet fermion. This singlet Majorana fermion also serves as a viable thermal relic dark matter candidate due to its limited interactions with other fields. To construct the model, we adopt an $A_4$ flavour symmetry in a modular framework, where the odd modular weight of the fields ensures their stability, and the specific modular weights of the couplings yield distinctive modular forms, leading to various phenomenological consequences. The explicit flavour structure of the mass matrices produces characteristic correlation patterns among the parameters. Furthermore, we examine several testable implications of the model, including neutrinoless double beta decay ($0\nu\beta\beta$), charged lepton flavour violation (cLFV), and direct detection prospects for the dark matter candidate. These features make our model highly testable in upcoming experiments., Comment: 28 Pages, 11 Figures and 02 tables