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We study the spectral properties of a class of random matrices of the form $S_n^{-} = n^{-1}(X_1 X_2^* - X_2 X_1^*)$ where $X_k = \Sigma_k^{1/2}Z_k$, $Z_k$'s are independent $p\times n$ complex-valued random matrices, and $\Sigma_k$ are $p\times p$ positive semi-definite matrices that commute and are independent of the $Z_k$'s for $k=1,2$. We assume that $Z_k$'s have independent entries with zero mean and unit variance. The skew-symmetric/skew-Hermitian matrix $S_n^{-}$ will be referred to as a random commutator matrix associated with the samples $X_1$ and $X_2$. We show that, when the dimension $p$ and sample size $n$ increase simultaneously, so that $p/n \to c \in (0,\infty)$, there exists a limiting spectral distribution (LSD) for $S_n^{-}$, supported on the imaginary axis, under the assumptions that the joint spectral distribution of $\Sigma_1, \Sigma_2$ converges weakly and the entries of $Z_k$'s have moments of sufficiently high order. This nonrandom LSD can be described through its Stieltjes transform, which satisfies a system of Mar\v{c}enko-Pastur-type functional equations. Moreover, we show that the companion matrix $S_n^{+} = n^{-1}(X_1X_2^* + X_2X_1^*)$, under identical assumptions, has an LSD supported on the real line, which can be similarly characterized., Comment: arXiv admin note: substantial text overlap with arXiv:2409.16780

Large Language Models (LLMs) are increasingly used as chatbots, yet their ability to personalize responses to user preferences remains limited. We introduce PrefEval, a benchmark for evaluating LLMs' ability to infer, memorize and adhere to user preferences in a long-context conversational setting. PrefEval comprises 3,000 manually curated user preference and query pairs spanning 20 topics. PrefEval contains user personalization or preference information in both explicit and implicit forms, and evaluates LLM performance using a generation and a classification task. With PrefEval, we evaluated the aforementioned preference following capabilities of 10 open-source and proprietary LLMs in multi-session conversations with varying context lengths up to 100k tokens. We benchmark with various prompting, iterative feedback, and retrieval-augmented generation methods. Our benchmarking effort reveals that state-of-the-art LLMs face significant challenges in proactively following users' preferences during conversations. In particular, in zero-shot settings, preference following accuracy falls below 10% at merely 10 turns (~3k tokens) across most evaluated models. Even with advanced prompting and retrieval methods, preference following still deteriorates in long-context conversations. Furthermore, we show that fine-tuning on PrefEval significantly improves performance. We believe PrefEval serves as a valuable resource for measuring, understanding, and enhancing LLMs' preference following abilities, paving the way for personalized conversational agents. Our code and dataset are available at https://prefeval.github.io/., Comment: Accepted at ICLR 2025 as oral presentation. Code and data at: https://prefeval.github.io/

Context. We use the Southern Photometric Local Universe Survey (S-PLUS) Fourth Data Release (DR4) to identify and classify H$\alpha$-excess point sources in the Southern Sky, combining photometric data from 12 S-PLUS filters with machine learning to improve classification of H$\alpha$-related phenomena. Aims. Our goal is to classify H$\alpha$-excess point sources by distinguishing Galactic and extragalactic objects, particularly those with redshifted emission lines, and identifying variability phenomena like RR Lyrae stars. Methods. We selected H$\alpha$-excess candidates using the ($r - J0660$) vs. ($r - i$) colour-colour diagram from the S-PLUS main survey (MS) and Galactic Disk Survey (GDS). UMAP for dimensionality reduction and HDBSCAN clustering were used to separate source types. Infrared data was incorporated, and a Random Forest model was trained on clustering results to identify key colour features. New colour-colour diagrams from S-PLUS MS and infrared data offer a preliminary classification. Results. Combining multiwavelength data with machine learning significantly improved H$\alpha$-excess source classification. We identified 6956 sources with excess in the $J0660$ filter. Cross-matching with SIMBAD explored object types, including emission-line stars, young stellar objects, nebulae, stellar binaries, cataclysmic variables, QSOs, AGNs, and galaxies. Using S-PLUS colours and machine learning, we separated RR Lyrae stars from other sources. The separation of Galactic and extragalactic sources was clearer, but distinguishing cataclysmic variables from QSOs at certain redshifts remained challenging. Infrared data refined the classification, and the Random Forest model highlighted key colour features for future follow-up spectroscopy., Comment: 23 pages, 20 figures, 3 tables, accepted to be published in A&A

This paper examines the thermodynamic properties and stability of deformed AdS-Schwarzschild black holes, focusing on the effects of deformation ($\alpha$) and thermal correction parameters ($\beta_1$, $\beta_2$) on phase transitions and heat capacity. The results show that higher $\alpha$ values raise the Hawking-Page critical temperature, enhancing thermal stability. Thermal corrections significantly affect smaller black holes but minimally impact larger ones, leaving second-order phase transitions unchanged. Heat capacity analysis identifies stability regions, with sign changes marking instability. These findings highlight the role of deformation and thermal corrections in black hole stability, offering insights for extending our understanding of black hole thermodynamics., Comment: 17 pages, 15 figures

Building on top of the success in AI-based atmospheric emulation, we propose an AI-based ocean emulation and downscaling framework focusing on the high-resolution regional ocean over Gulf of Mexico. Regional ocean emulation presents unique challenges owing to the complex bathymetry and lateral boundary conditions as well as from fundamental biases in deep learning-based frameworks, such as instability and hallucinations. In this paper, we develop a deep learning-based framework to autoregressively integrate ocean-surface variables over the Gulf of Mexico at $8$ Km spatial resolution without unphysical drifts over decadal time scales and simulataneously downscale and bias-correct it to $4$ Km resolution using a physics-constrained generative model. The framework shows both short-term skills as well as accurate long-term statistics in terms of mean and variability.

The paper introduces the development of a modular compiler for a subset of a C-like language, which addresses the challenges in constructing a compiler for high-level languages. This modular approach will allow developers to modify a language by adding or removing subsets as required, resulting in a minimal and memory-efficient compiler. The development process is divided into small, incremental steps, where each step yields a fully functioning compiler for an expanding subset of the language. The paper outlines the iterative developmental phase of the compiler, emphasizing progressive enhancements in capabilities and functionality. Adherence to industry best practices of modular design, code reusability, and documentation has enabled the resulting compiler's functional efficiency, maintainability, and extensibility. The compiler proved to be effective not only in managing the language structure but also in developing optimized code, which demonstrates its practical usability. This was also further assessed using the compiler on a tiny memory-deficient single-board computer, again showing the compiler's efficiency and suitability for resource-constrained devices.

This paper seeks to establish a connection between the cosmological constant and Renyi entropy within the framework of Kalb-Raymond(K-R) gravity. Our analysis is supported by evidence showing the equivalence of the thermodynamic topology of K-R AdS black holes in the Gibbs-Boltzmann (GB) statistical framework and K-R flat black holes in the Renyi statistical framework. We begin by exploring the thermodynamic topology of K-R black holes in flat spacetimes, focusing on the topological characteristics and phase transition behavior in both statistical frameworks. We find that K-R flat black holes in Renyi statistics exhibit equivalent global and local topological properties to K-R AdS black holes in GB statistics. This equivalence points to a potential connection between the cosmological constant and the Renyi parameter. We derive an approximate relationship between the Renyi parameter and the cosmological constant, which is consistent with similar findings in the literature from a cosmological perspective., Comment: 14 pages, 13 figures, Prepared for submission to the PANE Journal of Physics(PJP)

Let $\Fm$ be finite fields of order $q^m$, where $m\geq 2$ and $q$, a prime power. Given $\F$-affine hyperplanes $A_1,\ldots, A_m$ of $\Fm$ in general position, we study the existence of primitive element $\alpha$ of $\Fm$, such that $f(\alpha)$ is also primitive, where $ax^2+bx+c\in \Fm[x]$ ($a\neq 0$ and $b^2\neq 4ac$) in $\Fm$ and the primitive pair $(\alpha, f(\alpha))$ avoids each $A_i$. We establish results for fields of higher order., Comment: 12 pages

Context. Spectroscopic surveys like APOGEE, GALAH, and LAMOST have significantly advanced our understanding of the Milky Way by providing extensive stellar parameters and chemical abundances. Complementing these, photometric surveys with narrow/medium-band filters, such as the Southern Photometric Local Universe Survey (S-PLUS), offer the potential to estimate stellar parameters and abundances for a much larger number of stars. Aims. This work develops methodologies to extract stellar atmospheric parameters and selected chemical abundances from S-PLUS photometric data, which spans ~3000 square degrees using seven narrowband and five broadband filters. Methods. Using 66 S-PLUS colors, we estimated parameters based on training samples from LAMOST, APOGEE, and GALAH, applying Cost-Sensitive Neural Networks (NN) and Random Forests (RF). We tested for spurious correlations by including abundances not covered by the S-PLUS filters and evaluated NN and RF performance, with NN consistently outperforming RF. Including Teff and log g as features improved accuracy by ~3%. We retained only parameters with a goodness-of-fit above 50%. Results. Our approach provides reliable estimates of fundamental parameters (Teff, log g, [Fe/H]) and abundance ratios such as [{\alpha}/Fe], [Al/Fe], [C/Fe], [Li/Fe], and [Mg/Fe] for ~5 million stars, with goodness-of-fit >60%. Additional ratios like [Cu/Fe], [O/Fe], and [Si/Fe] were derived but are less accurate. Validation using star clusters, TESS, and J-PLUS data confirmed the robustness of our methodology. Conclusions. By leveraging S-PLUS photometry and machine learning, we present a cost-effective alternative to high-resolution spectroscopy for deriving stellar parameters and abundances, enabling insights into Milky Way stellar populations and supporting future classification efforts., Comment: 23 pages, 14 Figures

In this work, we propose a novel formalism for the thermodynamics of flat black holes, inspired by the Restricted Phase Space Thermodynamics (RPST) framework. Our construction is motivated by the observed similarities in the thermodynamic behavior of flat black holes within the R\'enyi entropy framework and that of AdS black holes described by the Bekenstein entropy regime. The RPST framework is, by construction, exclusive to AdS black holes because it depends on the cosmological constant $\Lambda$, which is linked to the central charge $C$ of the dual conformal field theory (CFT). However, for non-AdS black holes, where $\Lambda$ is absent, we introduce a deformation parameter $\lambda$ to replace the central charge $C$. This RPST-inspired formalism incorporates $\lambda$ and its conjugate variable, the response potential $\zeta$, as a new pair of thermodynamic variables, analogous to the central charge $C$ and chemical potential $\mu$ in the AdS case. To illustrate the applicability of this formalism, we analyze two examples: the Reissner-Nordstr\"om (RN) flat black hole and the Kerr black hole., Comment: 11 pages, 8 figures

This study explores the use of virtual reality (VR) as an innovative tool to enhance awareness, acceptance, and understanding of accessibility for persons with vision loss (VL). Through a VR-based workshop developed in collaboration with New York City's Department Of Transportation, participants experienced immersive simulations of VL and and related immersive mobility challenges. The methodology included pre- and post-intervention questionnaires, assessing changes in participants' knowledge, confidence, and perception. Participants included urban planners, designers, and architects. Results showed a significant increase in awareness of VL-related challenges that affect design guidelines, as well as improved confidence in addressing such challenges. Participants also expressed strong support for VR as a pedagogical tool, noting its potential for reshaping professional practices, improving capacity building, and enhancing inclusive design. The study demonstrates the effectiveness of VR as an experiential learning platform, fostering empathy and a long-term commitment to integrating VL considerations into urban design. These findings highlight the transformative potential of VR in advancing equity and accessibility in urban environments.

This paper mainly aims to solve the Anti deSitter Black Holes (AdS BH) under the Barrow entropy under polytropic gas fluid, especially the Chaplygin Gas. First, we develop this last polytropic model in detail to then obtain the possible solutions and thermodynamic conditions on the Energy-Momentum and the Barrow Entropy for spacetimes of spatial dimension $D>3$. Then, we focus on thermidynamic solutions and the different impacts on the Barrow entropy of the black hole, the temperature profile, the mass and the various physical quantities involved. Afterwards, we focus on the specific cases of the solutions of dimensions $D=4$ and $5$ in order to concretely test the models, especially from the point of view of the thermodynamic topology. Finally, we generalize everything by elaborating and testing the stability of the models to arrive at the thermal geometry of the AdS BH., Comment: 55 pages, 22 figures

Self-anthropomorphism in robots manifests itself through their display of human-like characteristics in dialogue, such as expressing preferences and emotions. Our study systematically analyzes self-anthropomorphic expression within various dialogue datasets, outlining the contrasts between self-anthropomorphic and non-self-anthropomorphic responses in dialogue systems. We show significant differences in these two types of responses and propose transitioning from one type to the other. We also introduce Pix2Persona, a novel dataset aimed at developing ethical and engaging AI systems in various embodiments. This dataset preserves the original dialogues from existing corpora and enhances them with paired responses: self-anthropomorphic and non-self-anthropomorphic for each original bot response. Our work not only uncovers a new category of bot responses that were previously under-explored but also lays the groundwork for future studies about dynamically adjusting self-anthropomorphism levels in AI systems to align with ethical standards and user expectations., Comment: Findings of EMNLP 2024, 19 pages

In this paper, we explore two $f(R,T)$ gravity models and derive black hole solutions within these models. We focus on investigating how the $f(R,T)$ model influences the thermodynamic characteristics of black holes by studying their thermodynamic topology and thermodynamic geometry. We consider five specific values of the thermodynamic parameter $\omega$, which signify five different classes of black hole solutions in general relativity (GR). We observe significant changes in the local topological properties of these black holes compared to GR, depending on the model parameters. Notably, we identify an additional topological class $W=0$ for some values of $\omega$ that is absent in the GR framework. We also study the thermodynamic geometry of the black hole using the Geometrothermodynamics (GTD) formalism. Our analysis demonstrates that the singular point, where the GTD scalar curvature diverges, corresponds exactly to the point where the heat capacity changes sign. Additionally, we constrain the model parameters of both models considered by utilizing black hole shadow data from the Sgr A* black hole, measured by the Event Horizon Telescope (EHT)., Comment: 34 pages, 96 figures

We study the spectral properties of a class of random matrices of the form $S_n^{-} = n^{-1}(X_1 X_2^* - X_2 X_1^*)$ where $X_k = \Sigma^{1/2}Z_k$, for $k=1,2$, $Z_k$'s are independent $p\times n$ complex-valued random matrices, and $\Sigma$ is a $p\times p$ positive semi-definite matrix, independent of the $Z_k$'s. We assume that $Z_k$'s have independent entries with zero mean and unit variance. The skew-symmetric/skew-Hermitian matrix $S_n^{-}$ will be referred to as a random commutator matrix associated with the samples $X_1$ and $X_2$. We show that, when the dimension $p$ and sample size $n$ increase simultaneously, so that $p/n \to c \in (0,\infty)$, there exists a limiting spectral distribution (LSD) for $S_n^{-}$, supported on the imaginary axis, under the assumptions that the spectral distribution of $\Sigma$ converges weakly and the entries of $Z_k$'s have moments of sufficiently high order. This nonrandom LSD can be described through its Stieltjes transform, which satisfies a coupled Mar\v{c}enko-Pastur-type functional equations. In the special case when $\Sigma = I_p$, we show that the LSD of $S_n^{-}$ is a mixture of a degenerate distribution at zero (with positive mass if $c > 2$), and a continuous distribution with a symmetric density function supported on a compact interval on the imaginary axis. Moreover, we show that the companion matrix $S_n^{+} = \Sigma_n^\frac{1}{2}(Z_1Z_2^* + Z_2Z_1^*)\Sigma_n^\frac{1}{2}$, under identical assumptions, has an LSD supported on the real line, which can be similarly characterized.

The possible existence of axions in the universe introduces the intriguing possibility of photon-axion conversion in strong magnetic fields, particularly near compact objects like supermassive black holes or even naked singularity. In this study, we investigate the conversion of photons into axions in the vicinity of a Janis-Newman-Winicour (JNW) spacetime, a well-known naked singularity solution. Our analysis reveals that photons can efficiently convert into axions with masses less than $100 \rm \ neV$. We calculate the conversion probability and find that it is significantly influenced by the characteristic parameter of the JNW spacetime. The potential observational signatures of this conversion, would be the dimming of photon ring in the X-ray and gamma-ray spectrum. Our findings suggest that compact objects like M87* could be prime candidates for detecting photon-axion conversion effects, provided future advances in high-resolution observations., Comment: Published in Physical Review D, 17 figures, 24 pages

The presence of Dark matter (DM) within a neutron star (NS) can substantially influence the macroscopic properties. It is commonly assumed that the pressure inside an NS is isotropic, but in reality, pressure is locally anisotropic. This study explores the properties of anisotropic NS with a subfraction of DM (isotropic) trapped inside. Implementing a two-fluid formalism with three Equations of State (EOS): AP3 (a realistic nucleon-nucleon interaction model), BSk22 (modeling atomic nuclei and neutron-matter), and MPA1 (considering relativistic effects in nuclear interactions). The properties of NS, such as mass ($M$), radius ($R$), and dimensionless tidal deformability ($\Lambda$), for various DM-anisotropic configurations, have been rigorously tested against observational constraints. These constraints include data from the binary NS merger GW170817, NICER x-ray measurements, and pulsar mass-radius observations. We observe that with increasing DM subfraction, higher anisotropies could also satisfy the observational constraints. Furthermore, increasing the coupling ($g$) between DM and its mediator leads to the formation of a core-halo structure, with a DM halo surrounding the baryonic matter (BM). Specifically, for coupling values of $g = 10^{-4}$, $10^{-3.7}$, and $10^{-3.5}$, we observe that the maximum radius ($R_{max}$) decreases with increasing anisotropy, which contrasts with the behavior at $g = 10^{-5}$ and in scenarios with no DM. Our analysis indicates that binary pulsar systems could potentially constrain the extent of admixed anisotropic NS or, more optimistically, provide evidence for the existence of DM-admixed anisotropic NS., Comment: 29 pages, 12 figures, 6 tables

In this study, we advance the understanding of thermodynamic properties and phase transitions in rotating anti-de Sitter (AdS) black holes by applying the Kaniadakis(KD) entropy framework. This framework represents a non-extensive generalization of classical statistical mechanics, inspired by the symmetries of relativity and offering a novel perspective on black hole thermodynamics. Our focus is on investigating how Kaniadakis entropy modifies the thermodynamic phase space of rotating AdS black holes. To achieve this, we analyze three prominent rotating AdS black hole systems: the Kerr AdS black hole, the Kerr-Sen AdS black hole, and the Kerr-Newman AdS black hole. We assess their thermodynamic quantities, phase transitions, thermodynamic topology and thermodynamic geometry within the Kaniadakis statistical framework. Our analysis reveals notable deviations from the behaviour predicted by traditional Gibbs-Boltzmann(GB) statistics., Comment: 47 page, 155 figures

The accuracy of a recently-developed closed-form GN nonlinear interference model is evaluated in experimental 1065 km S+C+L band WDM transmission with backward Raman pumping. The model accurately estimates the nonlinear interference and ASE with total SNR error of less than 0.6 dB., Comment: 3 pages plus 1 page reference, 4 figures, submitted to ECOC 2024

The aim of this paper is to explore the thermodynamic topology of topological charged dilatonic black holes. To achieve this, our study will begin by examining the characteristics of topological charged black holes in dilaton gravity. Specifically, we will concentrate on the impact of the topological constant on the event horizon of these black holes. Subsequently, we will analyze these black holes, considering their thermodynamic and conserved quantities, in order to assess the validity of the first law of thermodynamics. We explore the thermodynamic topology of these black holes by treating them as thermodynamic defects. For our study, we examine two types of thermodynamic ensembles: the fixed $q$ ensemble and the fixed $\phi$ ensemble. To study the impact of the topological constant ($% k$) on thermodynamic topology, we consider all possible types of curvature hypersurfaces that can form in these black holes. By calculating the topological charges at the defects within their thermodynamic spaces, we analyze both the local and global topology of these black holes. We also investigate how the parameters of dilaton gravity affect the thermodynamic topology of black holes and highlight the differences compared to charged black holes in the General Relativity., Comment: 20 pages, 16 figures, 3 tables

In the present work, we extend the $f(Q)$ symmetric teleparallel gravity by introducing an arbitrary coupling between the non-metricity $Q$ and matter Lagrangian $L_m$ in the Lagrangian density $f$ of the theory, which thus leads to the $f\left(Q,L_m\right)$ theory. This generalisation encompasses Coincident General Relativity (CGR), and the Symmetric Teleparallel Equivalent to GR (STEGR). Using the metric formalism, we derive the field equation of the theory, which generalizes the field equations of $f(Q)$ gravity. From the study of the covariant divergence of the field equations, it follows that the presence of the geometry-matter coupling leads to the non-conservation of the matter energy-momentum tensor. The cosmological implications of the theory are investigated in the case of a flat, homogeneous, and isotropic Friedmann-Lemaitre-Robertson-Walker geometry. As a first step in this direction, we obtain the modified Friedmann equations for the $f(Q,L_m)$ gravity in a general form. Specific cosmological models are investigated for several choices of $f(Q,L_m)$, including $f(Q,L_m)=-\alpha Q + 2L_m + \beta$, and $f(Q,L_m)=- \alpha Q + (2L_m)^2 + \beta$, respectively. Comparative analyses with the standard $\Lambda$ CDM paradigm are carried out, and the observational implications of the models are investigated in detail.

This study introduces a novel framework to apply Artifact Subspace Reconstruction (ASR) algorithm on single-channel Electroencephalogram (EEG) data. ASR, renowned for its automated capability to effectively eliminate various artifacts like eye-blinks and eye movements from EEG signals. Importantly it has been implemented on android smartphones, but relied on multiple channels for principal component subspace calculations. To overcome this limitation, we incorporate the established dynamical embedding approach into the algorithm, naming it Embedded-ASR (E-ASR). In our proposed method, an embedded matrix is first constructed from a single-channel EEG data using series of delay vectors. ASR is then applied to this embedded matrix, and the resulting cleaned single-channel EEG is reconstructed by removing the time lag and concatenating the rows of the embedded matrix. Data was collected from four subjects in resting states with eyes open from pre-frontal (Fp1 and Fp2) electrodes using CameraEEG app. To assess the effectiveness of the E-ASR algorithm on an EEG dataset with artifacts, we employed performance metrics such as relative root mean square error (RRMSE), correlation coefficient (CC), average power ratio as well as estimated the number of eye-blinks with and without the E-ASR approach. E-ASR was able to reduce artifacts from the semi-simulated EEG data, with an RRMSE of 45.45% and a CC of 0.91. For real EEG data, the counted eye-blinks were manually cross-checked with ground truth obtained from CameraEEG video data across all subjects for individual Fp1 and Fp2 electrodes. In conclusion, our study suggests E-ASR framework can remove artifacts from single channel EEG data. This promising algorithm might have potential for smartphone-based natural environment EEG applications, where minimal number of electrodes is a critical factor.

In order to include the effect of high energy and topological parameters on black holes in $F(R)$ gravity, we consider two corrections to this gravity: energy-dependent spacetime with different topological constants, and a nonlinear electrodynamics field. In other words, we combine $F(R)$ gravity's rainbow with ModMax nonlinear electrodynamics theory to see the effects of high energy and topological parameters on the physics of black holes. For this purpose, we first extract topological black hole solutions in $F(R)$% -ModMax gravity's rainbow. Then, by considering black holes as thermodynamic systems, we obtain thermodynamic quantities and check the first law of thermodynamics. The effect of the topological parameter on the Hawking temperature and the total mass of black holes is obvious. We also discuss the thermodynamic topology of topological black holes in $F(R)$-ModMax gravity's rainbow using the off-shell free energy method. In this formalism, black holes are assumed to be equivalent to defects in their thermodynamic spaces. For our analysis, we consider two different types of thermodynamic ensembles. These are: fixed $q$ ensemble and fixed $\phi$ ensemble. We take into account all the different types of curvature hypersurfaces that can be constructed in these black holes. The local and global topology of these black holes are studied by computing the topological charges at the defects in their thermodynamic spaces. Finally, in accordance with their topological charges, we classify the black holes into three topological classes with total winding numbers corresponding to $-1, 0$, and $1$. We observe that the topological classes of these black holes are dependent on the value of the rainbow function, the sign of the scalar curvature, and the choice of ensembles., Comment: 24 pages, 17 figures, 1 table

Data gloves play a crucial role in study of human grasping, and could provide insights into grasp synergies. Grasp synergies lead to identification of underlying patterns to develop control strategies for hand exoskeletons. This paper presents the design and implementation of a data glove that has been enhanced with instrumentation and fabricated using 3D printing technology. The glove utilizes flexible sensors for the fingers and force sensors integrated into the glove at the fingertips to accurately capture grasp postures and forces. Understanding the kinematics and dynamics of human grasp including reach-to-grasp is undertaken. A comprehensive study involving 10 healthy subjects was conducted. Grasp synergy analysis is carried out to identify underlying patterns for robotic grasping. The t-SNE visualization showcased clusters of grasp postures and forces, unveiling similarities and patterns among different GTs. These findings could serve as a comprehensive guide in design and control of tendon-driven soft hand exoskeletons for rehabilitation applications, enabling the replication of natural hand movements and grasp forces.

The emerging paradigm of Non-Conventional Internet of Things (NC IoT), which is focused on the usefulness of information as opposed to the notion of high volume data collection and transmission, will be an important and dominant part of human life in the near future. This paper proposes a novel semantic-based approach for addressing the unique challenges posed by underwater NC IoT. We present an intelligent sensing strategy for exploring the semantics of the underwater environment by judiciously selecting the data to transmit, thereby minimizing redundancy for utmost relevant data transmission. We introduce an evolutionary function for the selection of the semantic-empowered messages relevant to the specific task within a minimum Age of Information (AoI), a freshness metric of the collected information, and for monitoring the underwater environment for performance optimization. A DNN-empowered Bayesian integrated with an adaptive surrogate model optimization will determine the optimal placement strategy of the sensors and the uncertainty level of the underwater landscape. An Adaptive Expected Improvement (AEI) mechanism is introduced to predict the optimal arrival rate for enabling a synchronized data sensing and transmission ecosystem, ensuring efficiency and timeliness. Simulation results show that the proposed solution outperforms conventional approaches.

In the evolving era of Unmanned Aerial Vehicles (UAVs), the emphasis has moved from mere data collection to strategically obtaining timely and relevant data within the Internet of Drones (IoDs) ecosystem. However, the unpredictable conditions in dynamic IoDs pose safety challenges for drones. Addressing this, our approach introduces a multi-UAV framework using spatial-temporal clustering and the Frechet distance for enhancing reliability. Seamlessly coupled with Integrated Sensing and Communication (ISAC), it enhances the precision and agility of UAV networks. Our Multi-Agent Reinforcement Learning (MARL) mechanism ensures UAVs adapt strategies through ongoing environmental interactions and enhancing intelligent sensing. This focus ensures operational safety and efficiency, considering data capture and transmission viability. By evaluating the relevance of the sensed information, we can communicate only the most crucial data variations beyond a set threshold and optimize bandwidth usage. Our methodology transforms the UAV domain, transitioning drones from data gatherers to adept information orchestrators, establishing a benchmark for efficiency and adaptability in modern aerial systems.

In this study, we investigate the thermodynamic topology of the Kerr-Sen-Ads black hole in restricted phase space. In the restricted phase space, a new parameter, central charge $C$, and its conjugate parameter $\mu$ are introduced, omitting the well-known $PdV$ term in the first law of black hole thermodynamics. We study the local and global topology of the black hole by considering the black hole solution as topological defects in the free energy landscape. We compute the winding number and the total topological number at the thermodynamic defects. For our analysis, we have considered five ensembles of Kerr-Sen-Ads black holes in restricted phase space: fixed $(Q, J, C)$, fixed $(\phi, J, C)$, fixed $(Q,\Omega, C)$, fixed $(Q, J, \mu)$, and fixed $(\phi,\Omega, C)$, where $Q$ is the electric charge, $J$ is the angular momentum, $C$ is the central charge, $\phi$ is the electric potential conjugate to charge, $\Omega$ is the angular frequency conjugate to $J$, and finally, $\mu$ is the chemical potential. In the fixed $(Q, J, C)$, fixed $(\phi, J, C)$, and fixed $(Q, J, \mu)$ ensembles, we find a topological charge of $+1$. In the fixed $(Q,\Omega, C)$ and fixed $(\phi, \Omega, C)$ ensembles, depending on the values of the thermodynamic parameters, we find topological charges of $-1$, $0$, and $+1$. Interestingly, in ensembles where we find the topological charge to be $0$, we observe both Hawking-Page and Davies type phase transitions. We show that both types of these phase transitions can be studied using a common vector field, and the topological charges associated with Davies type and Hawking-Page phase transitions are $-1$ and $+1$, respectively., Comment: 24 pages, 39 figures

Resonant tunneling diode (RTD) oscillators possess the highest oscillation frequency among all electronic THz emitters. However, the emitted power from RTDs remains limited. Here, we propose linear RTD-oscillator arrays capable of supporting coherent emission from both odd and even coupled modes. Both modes exhibit constructive interference in the far field, enabling high power emission. Experimental demonstrations of coherent emission from 11-RTD-oscillator linear arrays are presented. The odd mode oscillates at approximately 450 GHz, emitting about 0.5 mW, while the even mode oscillates at around 750 GHz, emitting about 1 mW. Moreover, certain RTD-oscillator arrays demonstrate dual-band oscillation under different biases, allowing for controllable switching between two coupled modes. In addition, during bias sweeping in both directions, a notable hysteresis feature is observed in the switching bias for the odd and even modes. Our linear RTD-oscillator array represents a significant step forward in the realization of high-power large RTD-oscillator arrays and enables large-scale applications of RTD devices., Comment: 7 pages, 6 figures

In this work, we propose a common vector field to study the thermodynamic topology of the Davies type and Hawking-Page phase transitions. Existing literature has shown that studying these two types of phase transitions typically requires defining two separate vector fields . In our approach, we adopt Duan's $\phi$-mapping topological current theory to define a novel vector field, denoted as $\phi$, whose critical points exactly correspond to the Davies point and the Hawking-Page phase transition point. More importantly, we can differentiate between these two points by their topological charge. While, the topological charge for the critical point corresponding to the Davies-type phase transition is found to be $-1$, the same for the Hawking-Page phase transition point, it is $+1$. Although our analysis is applicable to all black hole systems where both types of phase transitions are found, we illustrate it using three simple systems as examples: the Schwarzschild AdS black hole, the Reissner-Nordstr\"om AdS black hole in the grand canonical ensemble, and finally the Kerr AdS black holes in the grand canonical ensemble. It is wellknown that these black holes exhibit both Davies and Hawking-Page phase transitions. With our proposed vector $\phi$, the critical points obtained for these three systems exactly match the Davies-type and Hawking-Page phase transition points, and the associated topological charges are found to be $-1$ for the Davies point and $+1$ for the Hawking-Page phase transition point., Comment: 13 pages, 18 figures