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Thesis Tide

Thesis Tide ranks papers based on their relevance to the fields, with the goal of making it easier to find the most relevant papers. It uses AI to analyze the content of papers and rank them!

Breathless: An 8-hour Performance Contrasting Human and Robot Expressiveness

This paper describes the robot technology behind an original performance that pairs a human dancer (Cuan) with an industrial robot arm for an eight-hour dance that unfolds over the timespan of an Amer...

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This article presents a unique interdisciplinary approach that merges robotics with performance art, showcasing innovation in robotics and deep learning applications for expressive motion. The methodology is rigorous, combining pre-recorded and improvised elements which enhance its applicability to performance, robotics, and human-computer interaction. The long duration of the performance provides a significant scope for observational analysis.

An Affine Equivalence Algorithm for S-boxes based on Matrix Invariants

We investigate the affine equivalence (AE) problem of S-boxes. Given two S-boxes denoted as $S_1$ and $S_2$ , we aim to seek two invertible AE transformations $A,B$ such that &#...

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The article addresses the well-established and significant problem of affine equivalence of S-boxes, essential in modern cryptography. Its novelty lies in the introduction of the zeroization on S-boxes and the use of the standard orthogonal spatial matrix to optimize algorithmic complexity. The proposed AE_SOSM_DFS algorithm shows significant improvements in efficiency, making it applicable to widely used S-boxes, thus enhancing its impact on both theory and practical applications in cryptography.

TactV: A Class of Hybrid Terrestrial/Aerial Coaxial Tilt-Rotor Vehicles

To enhance the obstacle-crossing and endurance capabilities of vehicles operating in complex environments, this paper presents the design of a hybrid terrestrial/aerial coaxial tilt-rotor vehicle, Tac...

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The article presents a novel design for a hybrid vehicle that could significantly advance both aerial and terrestrial vehicle technology. The integration of coaxial rotors with a versatile movement system is innovative, and the focus on energy efficiency and maneuverability ensures practical applications. The experimental validation strengthens its credibility.

Anisotropic gravastar as horizonless regular black hole spacetime and its images illuminated by thin accretion disk

A connection between regular black holes and horizonless ultracompact objects was proposed in~\cite{Carballo-Rubio:2022nuj}. In this paper, we construct a model of a horizonless compact object, specif...

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This article presents a novel model of horizonless compact objects that deepens our understanding of gravitational phenomena without singularities, which may significantly influence theoretical astrophysics and our comprehension of black hole alternatives. The methodology used in mapping the spacetime structure and the implications of the images produced by the thin accretion disk are rigorously described, making this research robust and highly applicable in the field. Additionally, the connections to existing models such as the QHCO signal the potential for interdisciplinary dialogue and further theoretical exploration.

A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems

Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled widespread adoption, ev...

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The article presents a novel layered architecture specifically designed for the development of Large Language Model-based systems, addressing a current gap in effectively utilizing LLM capabilities. The focus on engineering complexities, scalability, and operational costs is highly relevant for practitioners in the field. The use of case studies enriches the applicability of the framework, making the research both actionable and theoretically robust. Overall, this may inspire further work in enhancing AI model architectures and software development practices.

Design of Dual-Band Plasmonic Absorber for Biomedical Sensing and Environmental Monitoring

This study introduces a dual-band plasmonic absorber designed for simultaneous sensing applications in the near-infrared (NIR) and mid-infrared (MIR) regions. The absorber, composed of silver nanostru...

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The article presents a novel design of a dual-band plasmonic absorber that targets crucial applications in biomedical sensing and environmental monitoring. The methodology, involving FDTD simulations, shows rigor in theoretical design, and the demonstrated sensitivity to various biomolecules suggests significant practical applicability. Its interdisciplinary nature could lead to innovations in sensor technology across health and environmental science, boosting its impact.

DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding

The challenge in LLM-based video understanding lies in preserving visual and semantic information in long videos while maintaining a memory-affordable token count. However, redundancy and corresponden...

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The article introduces a novel framework for dynamic video understanding using cooperative networks, which addresses significant issues in existing LLM-based video analysis. Its emphasis on balancing detailed encoding with memory efficiency is highly relevant given the growing complexity of visual information processing. The rigorous evaluation across multiple benchmarks showcases methodological strength, although the operational implications in real-world scenarios need further exploration.

Scalable and Effective Negative Sample Generation for Hyperedge Prediction

Hyperedge prediction is crucial in hypergraph analysis for understanding complex multi-entity interactions in various web-based applications, including social networks and e-commerce systems. Traditio...

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The paper presents a novel framework (SEHP) that addresses a significant challenge in hyperedge prediction with innovative methodological advancements, including the use of diffusion models and a boundary-aware loss function. The focus on negative sample generation, scalability, and efficiency contributes meaningfully to the field, making the findings particularly impactful for future research in hypergraph analysis and related applications.

Service Restoration for Distribution Systems Based on Semi-Analytical Metamodeling of Decision-Dependent Interruption Cost and Cold Load Pickup

Developing optimized restoration strategies for power distribution systems (PDSs) is essential to meet the pressing demand for enhanced resilience. Prior knowledge of customer interruption cost (CIC) ...

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This article tackles a significant challenge within power distribution systems by modeling complex decision-dependent interactions involving customer interruption costs and cold load pickup. Its innovative use of semi-analytical metamodeling addresses a gap in the understanding of restoration strategies, making it highly relevant for current and future research. The methodology is robust, leveraging limited data effectively, which adds to its applicability in real-world scenarios.

Perfecting Imperfect Physical Neural Networks with Transferable Robustness using Sharpness-Aware Training

AI models are essential in science and engineering, but recent advances are pushing the limits of traditional digital hardware. To address these limitations, physical neural networks (PNNs), which use...

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The article introduces a novel training technique (Sharpness-Aware Training) that significantly improves the training and deployment of physical neural networks (PNNs). Its focus on addressing both offline and online training limitations is crucial for advancing PNNs, which are increasingly relevant given the current limits of traditional digital hardware. The robustness against perturbations and the ability to transfer models between devices are particularly noteworthy, enhancing real-world applicability. The methodological rigor and universal applicability of the introduced SAT indicate substantial potential for future research.

Multipacking in Euclidean Plane

We initiate the study of multipacking problems for geometric point sets with respect to their Euclidean distances. We consider a set of $n$ points $P$ and define $N_s[v]$ as th...

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The article presents a novel approach to multipacking problems within geometric contexts, introducing unique definitions and theoretical constructs that could influence future research in computational geometry and optimization. The combination of computational complexity results, polynomial-time algorithms, and approximation solutions adds substantial methodological rigor, making the findings relevant for both theoretical exploration and practical applications. The identification of the NP-completeness of the 2-multipacking problem indicates significant implications for computing in geometric areas, enhancing its importance.

DiM: $f$ -Divergence Minimization Guided Sharpness-Aware Optimization for Semi-supervised Medical Image Segmentation

As a technique to alleviate the pressure of data annotation, semi-supervised learning (SSL) has attracted widespread attention. In the specific domain of medical image segmentation, semi-supervised me...

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The article introduces a novel approach combining sharpness-aware optimization with $f$-divergence minimization, specifically addressing the challenges in semi-supervised medical image segmentation. This method enhances model stability and adaptability, which are critical in medical applications where data variability is significant. Its focus on improving performance with minimal labeled data is particularly relevant in the medical field, where annotated data can be scarce. The methodological rigor and potential for real-world applicability provide a strong basis for high impact in the field.

Spin-density wave and superconductivity in La $_4$ Ni $_3$ O $_{10}$ under ambient pressure

We investigate the spin-density wave (SDW) behavior and the potential for superconductivity (SC) in La $_4$ Ni $_3$ O $_{10}$ under ambient pressure using a multi-orbital random-pha...

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This article presents a detailed investigation into the phenomena of spin-density waves and superconductivity in a specific material, La₄Ni₃O₁₀, under ambient pressure using advanced theoretical methods. Its focus on the intricate interplay between Hubbard interactions and magnetic ordering mechanisms is novel and has significant implications for understanding high-temperature superconductors. The methodological rigor, especially in applying a multi-orbital RPA model, strengthens the paper's contributions to theoretical condensed matter physics. The findings may inspire future experimental and theoretical work on related materials, particularly in the context of emergent superconductivity and magnetic properties under various conditions.

Environmental variability promotes the evolution of cooperation among geographically dispersed groups on dynamic networks

The evolutionary process that led to the emergence of modern human behaviors during the Middle Stone Age in Africa remains enigmatic. While various hypotheses have been proposed, we offer a new perspe...

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The article presents a novel perspective by linking environmental variability directly to the evolution of cooperative behavior, utilizing rigorous stochastic modeling. Its exploration of multiple variability models uniquely contributes to understanding human evolutionary processes, potentially impacting both theoretical frameworks and empirical studies in evolutionary biology.

Leveraging NFTs for Spectrum Securitization in 6G Networks

Dynamic Spectrum Sharing can enhance spectrum resource utilization by promoting the dynamic distribution of spectrum resources. However, to effectively implement dynamic spectrum resource allocation, ...

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The article presents a novel application of NFTs in the realm of dynamic spectrum sharing, addressing a critical challenge in 6G networks. The utilization of established blockchain standards like ERC404 adds methodological rigor, while the focus on incentivizing primary users for spectrum sharing expands the potential for enhanced resource utilization. Implementing the model on Ethereum testnet demonstrates practical applicability in a real-world context, further underscoring its relevance.

A computational model for inelastic behaviour and fracture of refractory industrial components under high-temperature conditions, application to slide gate plates

This work aims to provide a computational model that can describe the complex behaviour of refractory industrial components under working conditions. Special attention is given to the asymmetric tensi...

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The article presents a novel computational model that integrates continuum mechanics with phase-field fracture theory to address a significant issue in the materials science and engineering domain, specifically concerning high-temperature industrial components. Its methodological rigor is strong, as it employs Finite Element analysis and validates the framework through practical applications. Furthermore, the focus on refractory materials in steel production is pertinent given the industry's demand for innovative materials that withstand extreme conditions. The implications for future research in failure analysis and materials design enhance its relevance further.

Combinatorics of generalized orthogonal polynomials of type $R_{II}$

In 1995, Ismail and Masson introduced orthogonal polynomials of types $R_I$ and $R_{II}$ , which are defined by specific three-term recurrence relations with additional conditions. Recently, Ki...

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This article presents a significant advancement in the combinatorial interpretation and generalization of orthogonal polynomials, particularly focusing on type R_{II}. The introduction of a master theorem is novel as it expands the combinatorial framework to a broader class of orthogonal polynomials, potentially impacting various fields within mathematics. The methodological rigor displayed in developing new combinatorial models enhances its relevance. Overall, the paper's contributions are likely to inspire new research directions in both the theory and applications of orthogonal polynomials, warranting a high score.

Neutrino Oscillation Tomography of the Earth with the Hyper-Kamiokande Detector

Using PREM as a reference model for the Earth density distribution we investigate the sensitivity of Hyper-Kamiokande (HK) detector to deviations of the Earth i) core average density $\barρ_C$ ...

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The study presents a novel approach to using neutrino oscillation data to infer detailed information about Earth’s density structure, which is relevant to both geophysics and particle physics. The use of the Hyper-Kamiokande detector is a cutting-edge methodology that adds robustness to the findings. Furthermore, the analysis of systematic errors and resolution counts shows methodological rigor. The implications of the results could enhance our understanding of Earth’s internal structure, a significant area in geophysics, thus advancing the field significantly. However, the reliance on certain models (e.g., PREM) limits the novelty somewhat, preventing a perfect score.

The age of the Methuselah star in light of stellar evolution models with tailored abundances

Context. HD140283, or the Methuselah star, is a well-known reference object in stellar evolution. Its peculiar chemical composition, proximity and absence of reddening makes it an interesting case-stu...

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This article provides novel insights into the age determination of HD140283, a key object in stellar evolution studies. The methodological approach using tailored abundance models and the incorporation of modern observational data (e.g., Gaia parallax) enhances the rigor and relevance of the findings. The tension with the cosmic age adds a significant dimension to the research, prompting further investigation in stellar astrophysics. Additionally, it addresses the implications of mixing length parameters, demonstrating the complexity of stellar evolution models.

Temperature-Aware Phase-shift Design of LC-RIS for Secure Communication

Liquid crystal (LC) technology enables low-power and cost-effective solutions for implementing the reconfigurable intelligent surface (RIS). However, the phase-shift response of LC-RISs is temperature...

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This article addresses a critical issue in the application of LC-RIS technology to secure communications, bringing forth a novel algorithm that directly impacts performance by accounting for temperature variations. The methodology appears to be rigorous and applicable, making it a significant contribution to the field. Its focus on secure communications adds to its relevance, given the increasing need for secure data transmission technologies in various sectors.