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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!

Spectro-polarimetry of GRB 180427A: evidence for distinct emission sites with varying polarisation

The dynamics of the origin of gamma-ray emissions in gamma-ray bursts (GRBs) remains an enigma. Through a joint analysis of GRB 180427A, observed by the Fermi Gamma-ray Space Telescope and AstroSat...

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This article presents novel findings related to the dynamics of gamma-ray emissions in GRBs, a critical area in high-energy astrophysics. The methodological rigor and the combination of spectro-polarimetry with time-resolved analysis offer significant insights into the nature of gamma-ray emissions and their polarisation properties. The distinction between emission sites indicates an innovative approach to understanding the underlying mechanisms, showcasing both robustness and applicability to current theories. This work is poised to inspire further investigations into GRB mechanisms and polarisation studies.

The quantum relative entropy of the Schwarzschild black-hole and the area law

The area law obeyed by the thermodynamic entropy of black holes is one of the fundamental results relating gravity to statistical mechanics. In this work we provide a derivation of the area law for th...

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This article presents a significant advancement in the understanding of the relationship between quantum mechanics and general relativity through the lens of entropy. The derivation of the area law for the quantum relative entropy of Schwarzschild black holes introduces novel concepts that could inspire new theoretical approaches in both quantum gravity and statistical mechanics. Its methodological rigor, particularly in generalizing established definitions in the context of quantum operators, adds to its robustness.

Comparison of Various SLAM Systems for Mobile Robot in an Indoor Environment

This article presents a comparative analysis of a mobile robot trajectories computed by various ROS-based SLAM systems. For this reason we developed a prototype of a mobile robot with common sensors: ...

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This article provides a comprehensive comparative analysis of various SLAM systems, which is crucial for the development and optimization of mobile robotics in indoor environments. The methodological rigor of using a standardized dataset across multiple systems enhances its reliability and relevance. The encouraging results for specific methods also suggest practical implications for future robotics applications.

Higher Sobolev regularity on the mixed local and nonlocal p-Laplace equations

We develop a systematic study of the interior Sobolev regularity of weak solutions to the mixed local and nonlocal $p$ -Laplace equations. To be precise, we show that the weak solution $u&#...

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This article presents novel findings in the area of mixed local and nonlocal p-Laplace equations, revealing insights into the Sobolev regularity of weak solutions. Its methodological rigor, evidenced by advanced techniques such as finite difference quotients and energy methods, supports its relevance. Furthermore, the work proposes results that bridge different existing theories in nonlinear analysis, making it valuable for researchers in the field.

Local boundedness and higher integrability for the sub-critical singular porous medium system

The gradient of weak solutions to porous medium-type equations or systems possesses a higher integrability than the one assumed in the pure notion of a solution. We settle the critical and sub-critica...

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This article addresses a significant gap in the understanding of weak solutions to singular porous medium equations. Its focus on local boundedness and higher integrability can advance theoretical frameworks and applications in mathematical fluid dynamics. The rigorous approach and resolution of both critical and sub-critical cases highlight its methodological strength, making it a valuable contribution to the field.

The Devil is in the Details: Simple Remedies for Image-to-LiDAR Representation Learning

LiDAR is a crucial sensor in autonomous driving, commonly used alongside cameras. By exploiting this camera-LiDAR setup and recent advances in image representation learning, prior studies have shown t...

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This article provides valuable insights into the effective integration of camera and LiDAR data for 3D task performance, pinpointing critical design oversights that enhance model outcomes. Its findings could reorient current research focus towards foundational design elements, rather than solely advanced loss functions. The methodological rigor demonstrated through empirical validation on significant datasets further supports its relevance in enhancing segmentation and detection performance. The novel approach to optimizing data utilization also has broader implications for other sensor integration studies.

Exploring the Inquiry-Diagnosis Relationship with Advanced Patient Simulators

Online medical consultation (OMC) restricts doctors to gathering patient information solely through inquiries, making the already complex sequential decision-making process of diagnosis even more chal...

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This article addresses a critical gap in online medical consultations by focusing on the inquiry aspect of the diagnostic process, which is often overlooked. It employs advanced methodologies, such as real patient interaction strategies and large language models, enhancing its innovation and applicability. The findings have practical implications for improving medical diagnostics in telemedicine and health tech, making it relevant for future studies in these areas.

Semiparametrics via parametrics and contiguity

Inference on the parametric part of a semiparametric model is no trivial task. On the other hand, if one approximates the infinite dimensional part of the semiparametric model by a parametric function...

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The paper presents a novel approach to semiparametric inference by rigorously establishing a connection between parametric and semiparametric frameworks, which is significant for statisticians. It offers a method of translating results from familiar parametric settings to complex semiparametric cases, aiding in broader applicability and potentially simplifying analysis in empirical research. The use of canonical examples also enhances the practical relevance of the methodology.

Building Bridges across Papua New Guinea's Digital Divide in Growing the ICT Industry

Papua New Guinea (PNG) is an emerging tech society with an opportunity to overcome geographic and social boundaries, in order to engage with the global market. However, the current tech landscape, dom...

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The article effectively addresses important issues such as the digital divide and the impact of algorithmic bias on emerging economies, particularly in Papua New Guinea. Its focus on open-source software as a potential solution provides a fresh perspective and practical implications for enhancing ICT capabilities in the region. The methodological approach is less about empirical validation and more about conceptual frameworks, which may limit its immediate applicability but still offers a valuable foundation for future research.

MonoSOWA: Scalable monocular 3D Object detector Without human Annotations

Detecting the three-dimensional position and orientation of objects using a single RGB camera is a foundational task in computer vision with many important applications. Traditionally, 3D object detec...

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The article presents a novel approach for training 3D object detectors without human annotations, significantly advancing the field of computer vision. The method is highly applicable to real-world scenarios where human annotation is impractical. Its performance on standard datasets indicates methodological rigor and broad applicability across various camera setups, which should inspire further research in this domain.

Utilizing AI Language Models to Identify Prognostic Factors for Coronary Artery Disease: A Study in Mashhad Residents

Abstract: Background: Understanding cardiovascular artery disease risk factors, the leading global cause of mortality, is crucial for influencing its etiology, prevalence, and treatment. This study ai...

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The article presents a novel approach to identifying prognostic factors for coronary artery disease through the utilization of various AI algorithms. Its methodological rigor in comparing multiple models for efficiency highlights its contribution to both clinical practice and research. Additionally, the specific focus on a regional population adds unique insights into the epidemiology of CAD, although broader applicability may be limited. This work has the potential to inspire future research on AI applications in cardiovascular disease.

Connectivity for AI enabled cities -- A field survey based study of emerging economies

The impact of Artificial Intelligence (AI) is transforming various aspects of urban life, including, governance, policy and planning, healthcare, sustainability, economics, entrepreneurship, etc. Alth...

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This article addresses a critical topic at the intersection of AI, urban studies, and telecommunications, highlighting the challenges faced in emerging economies. Its investigative approach on connectivity and its implications for AI applications is novel and necessary, particularly in addressing the digital divide. The case study in Kathmandu serves as a concrete example that adds empirical weight to its claims, making it relevant for practitioners and researchers alike.

Detecting Many-Body Scars from Fisher Zeros

The far-from-equilibrium dynamics of interacting quantum systems still defy precise understanding. One example is the so-called quantum many-body scars (QMBSs), where a set of energy eigenstates evade...

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This article presents a novel approach for detecting quantum many-body scars (QMBS) using Fisher zeros, advancing the understanding of non-equilibrium dynamics in quantum systems. The introduction of Fisher zeros as diagnostic tools is innovative and could lead to significant theoretical developments in identifying and analyzing QMBS. The methodology appears robust, as it is validated against known models, and its broader applicability in quantum statistical mechanics could stimulate further research in both QMBS and ergodicity breaking.

From Complexification to Self-Similarity: New Aspects of Quantum Criticality

Quantum phase transitions are a fascinating area of condensed matter physics. The extension through complexification not only broadens the scope of this field but also offers a new framework for under...

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The article presents a novel approach to understanding quantum criticality through the lens of complexification, which may redefine existing theories in condensed matter physics. The emphasis on self-similar phenomena and the connection to finite temperature transitions broadens the applications of quantum phase transition models. However, the impact may depend on further empirical validation of the proposed frameworks and concepts.

Void spin distribution as a powerful probe of $σ_{8}$

We present a numerical proof of the concept that the void spin distributions can in principle provide a tight constraint on the amplitude of matter density fluctuation on the scale of $8\,h^{-1}{\...

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This article presents a novel method for probing $σ_{8}$ through void spin distributions, which appears to be a unique and rigorous approach given the challenges related to other cosmic density parameters. The methodological rigor is demonstrated through extensive simulations, and the results suggest a strong and exclusive dependence on $σ_{8}$. This could potentially fill a gap in the current understanding of cosmic structures and inflationary parameters, making it pivotal for future cosmic research. Additionally, the insights on observational feasibility extend its applicability to real-world data, further enhancing its relevance.

Guided Debugging of Auto-Translated Code Using Differential Testing

Large Language Models (LLMs) hold great promise in the task of code translation. However, the lack of explainability complicates the identification of the inevitable translation errors. In this paper,...

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This article presents a novel debugging tool that directly addresses a pressing problem in the integration of large language models for code translation. The use of fuzzing and a heuristic algorithm for error identification showcases methodological rigor and innovativeness. The promising experimental results demonstrate practical applicability and potential for widespread adoption, making it a substantial contribution to the field.

Geometry and symmetries of Hermitian-Einstein and instanton connection moduli spaces

We investigate the geometry of the moduli spaces $\mathscr{M}_{HE}^*(M^{2n})$ of Hermitian-Einstein irreducible connections on a vector bundle $E$ over a Kähler with torsion (KT) manif...

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This article presents a robust analysis of the geometric structures of Hermitian-Einstein and instanton connection moduli spaces, offering significant theoretical advancements and potential practical applications in fields like algebraic geometry and mathematical physics. The focus on Kähler manifolds and their properties is particularly relevant for ongoing research due to the evident connection to string theory and gauge theory contexts. The methods employed are rigorous, and the results could inspire further studies on symmetry actions in these complex geometrical settings.

An Asymptotic Analysis of Bivalent Monoclonal Antibody-Antigen Binding

Ligand-receptor interactions are fundamental to many biological processes. For example in antibody-based immunotherapies, the dynamics of an antibody binding with its target antigen directly influence...

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The article presents a novel mathematical approach to understanding the complex dynamics of bivalent monoclonal antibody-antigen interactions, which is critical for the advancement of antibody-based therapies. The methodological rigor is evident through the combination of asymptotic analysis with numerical simulations. This research could significantly influence future studies by providing a deeper understanding of how these interactions relate to therapeutic efficacy in cancer treatments.

Very soft microgels at the interface behave and flow as Hertzian-like spheres

Soft pair potentials predict a reentrant liquid phase for high concentrations, a behavior not observed experimentally. Here, very soft microgels confined at an oil-water interface are used as a model ...

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This article presents novel findings on very soft microgels at the oil-water interface, exploring flow behavior and elastic properties that are relatively underexplored areas. The use of molecular dynamics simulations to support experimental results demonstrates methodological rigor while revealing a potentially significant mechanism related to fluid-phase behavior not previously observed. Its implications on soft matter physics and material science make it impactful for future research, despite needing further exploration into application contexts.

Justification logics with counterfactual and relevant conditionals

The purpose of this paper is to introduce justification logics based on conditional logics. We introduce a new family of logics, called conditional justification logics, which incorporates a counterfa...

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This article presents a novel approach by introducing conditional justification logics that combine counterfactuals with justification logics, showcasing methodological rigor through the development of relational models and their application to significant philosophical problems like Nozick's conditions and Gettier cases. The depth of analysis and connections made to existing philosophical literature highlight both its relevance and potential to inspire future research in formal epistemology and logic.