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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!

Variational U-Net with Local Alignment for Joint Tumor Extraction and Registration (VALOR-Net) of Breast MRI Data Acquired at Two Different Field Strengths

Background: Multiparametric breast MRI data might improve tumor diagnostics, characterization, and treatment planning. Accurate alignment and delineation of images acquired at different field strength...

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The study addresses a common challenge in medical imaging involving breast tumors, specifically the alignment and segmentation of MRI data from different field strengths. The method presented shows promising results in maintaining accuracy across varying imaging conditions, which is crucial for clinical applications in diagnostics and treatment planning. The novelty of combining segmentation and registration using a Variational U-Net adds to its potential impact, although the small sample size may limit generalizability.

Revealing turbulent Dark Matter via merging of self-Gravitating condensates

Self-gravitating condensates have been proposed as potential candidates for modelling dark matter. In this paper, we numerically investigate the dynamics of dark matter utilizing the merging of self-g...

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The article presents a novel approach in understanding dark matter dynamics through self-gravitating condensates, employing rigorous numerical methods to explore turbulent regimes. The exploration of dark soliton-mediated instabilities coupled with classic turbulence scaling adds theoretical depth, increasing its importance in astrophysics. Its interdisciplinary nature, bridging condensed matter physics and cosmology, enhances its potential to influence subsequent studies in dark matter characterization.

Exploring the interplay between small and large scales movements in a neotropical small mammal

We record and analyze the movement patterns of the marsupial {\it Didelphis aurita} at different temporal scales. Animals trajectories are collected at a daily scale by using spool-and-line techniques...

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This article presents a novel approach to analyzing movement patterns in small mammals by illustrating the transition between different types of movement dynamics (Lévy flight vs. Brownian motion) depending on the scale of observation. The methodological rigor is strong, utilizing advanced tracking and modeling techniques. The implications of its findings extend beyond a single species, suggesting broader applications in movement ecology and behavioral studies across various taxa.

Question Answering on Patient Medical Records with Private Fine-Tuned LLMs

Healthcare systems continuously generate vast amounts of electronic health records (EHRs), commonly stored in the Fast Healthcare Interoperability Resources (FHIR) standard. Despite the wealth of info...

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This article presents a novel application of large language models in healthcare, directly addressing a critical challenge in extracting relevant information from EHRs. The proposed approach is innovative, demonstrating improvements over established models in both size and performance. It also emphasizes privacy, a significant issue in health tech, which enhances its applicability. The rigorous evaluation against benchmark models indicates methodological rigor and relevance to real-world healthcare contexts.

Learning in Conjectural Stackelberg Games

We extend the formalism of Conjectural Variations games to Stackelberg games involving multiple leaders and a single follower. To solve these nonconvex games, a common assumption is that the leaders c...

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The paper presents a novel approach to Stackelberg games, particularly addressing the practical limitations of leaders' knowledge. The introduction of the Conjectural Stackelberg Equilibrium adds depth to game theory, particularly in its application to multi-player strategic interactions. The theoretical contributions are significant, and the algorithmic innovations show promise for real-world applicability. Numerical illustrations further bolster the argument for its effectiveness.

Numerical solutions of random mean square Fisher-KPP models with advection

This paper deals with the construction of numerical stable solutions of random mean square Fisher-KPP models with advection. The construction of the numerical scheme is performed in two stages. Firstl...

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The article presents a novel approach to solving random mean square Fisher-KPP models incorporating advection through a well-structured numerical scheme. Its methodological rigor, especially the use of random differential equations and stability proofs, adds significant value. The focus on random aspects and computational complexity positions this work as both innovative and practical for advancing studies on stochastic processes in biological modeling.

Effective string description of the reconfined phase in the trace deformed $\mathrm{SU}(2)$ Yang-Mills theory in (2+1) dimensions

We study the behaviour of the flux tube in the reconfined phase of the trace deformed $\mathrm{SU}(2)$ Yang-Mills theory in (2 + 1) dimensions. In this phase the Polyakov loop has a vanishing ...

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This article presents novel insights into the behavior of flux tubes in a specific phase of Yang-Mills theory, incorporating theoretical and numerical approaches. The exploration of the reconfined phase and its implications for the Polyakov loop is an important contribution, as it challenges existing paradigms of confinement in gauge theories. The unique focus on the rigid string model adds significant depth and could inspire further theoretical developments. However, its applicability may be somewhat limited by the specific context of (2+1) dimensions, which might restrict broader applicability in higher-dimensional models.

Unlearning Clients, Features and Samples in Vertical Federated Learning

Federated Learning (FL) has emerged as a prominent distributed learning paradigm. Within the scope of privacy preservation, information privacy regulations such as GDPR entitle users to request the re...

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This article tackles the significant issue of privacy in Federated Learning (FL), particularly in the less explored area of Vertical Federated Learning (VFL). The approaches presented (VFU-KD and VFU-GA) are novel and could effectively advance practical implementations of FL while maintaining compliance with privacy regulations such as GDPR. The critical exploration of unlearning clients, features, and samples indicates substantial originality and potential applicability in real-world scenarios. The methodological rigor in testing against various datasets and benchmarking methods strengthens its relevance.

Collective Memory and Narrative Cohesion: A Computational Study of Palestinian Refugee Oral Histories in Lebanon

This study uses the Palestinian Oral History Archive (POHA) to investigate how Palestinian refugee groups in Lebanon sustain a cohesive collective memory of the Nakba through shared narratives. Ground...

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The article presents a novel approach by combining computational methods with oral history, addressing a significant gap in research on collective memory and identity among diasporic communities. Methodological rigor is showcased in the statistical analysis of narratives, while the findings contribute substantially to understanding gendered experiences and the dynamics of memory formation within a sociopolitical context. However, further implications for broader applications beyond this specific case could be explored.

A projection method for particle resampling

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase space due to their better scalability than continuum approaches with respect to...

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The article presents a novel method for particle resampling that addresses significant challenges in high-dimensional kinetic models. Its focus on scalability and the preservation of moments is particularly relevant for advancing particle discretization techniques. The methodological rigor demonstrated through the combination of sparse linear algebra and finite element techniques adds to its credibility and potential impact. In addition, the open accessibility of evaluation codes and data enhances reproducibility, crucial for the advancement of the field.

Projecting dynamical systems via a support bound

For a polynomial dynamical system, we study the problem of computing the minimal differential equation satisfied by a chosen coordinate (in other words, projecting the system on the coordinate). This ...

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The article addresses a significant problem in the field of dynamical systems and contributes to advancing methodologies in differential equation analysis. The novelty lies in providing a sharp bound and designing an algorithm that improves computational capabilities, which is valuable for both theoretical research and practical applications in modeling and control. The methodological rigor is strong, particularly due to its experimental validation against state-of-the-art techniques.

On thermodynamics of charged and accelerating black holes

We reconsider various C-metric spacetimes describing charged and (slowly) accelerating AdS black holes in different theories of (non-linear) electrodynamics and revisit their thermodynamic properties....

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The article addresses important aspects of thermodynamics in black hole physics, specifically the complexities arising from charged and accelerating black holes. It presents novel insights by re-evaluating previous models and methodologies, contributing to a deeper understanding of their thermodynamic properties. The work demonstrates methodological rigor through its comprehensive approach and tackles outstanding issues in the field, signaling a potential pathway for future investigations.

Exploring gravitational impulse via quantum Boltzmann equation

We investigate the gravitational impulse by using the generalized formulation of the quantum Boltzmann equation (QBE), wherein the initial states are taken as wave packets rather than plane waves. The...

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The article presents a novel application of the quantum Boltzmann equation (QBE) to gravitational impulse, which is a unique intersection of quantum mechanics and gravity. This approach to analyzing gravitational scattering through wave packets rather than conventional methods introduces a fresh perspective. The methodological rigor is demonstrated through consistency with prior findings while also extending the theoretical framework. The study's implications for understanding fundamental interactions in open quantum systems are significant, particularly in gravitational contexts. However, its applicability may be limited to specific scenarios, thus not universally transformative.

HumorReject: Decoupling LLM Safety from Refusal Prefix via A Little Humor

Large Language Models (LLMs) commonly rely on explicit refusal prefixes for safety, making them vulnerable to prefix injection attacks. We introduce HumorReject, a novel data-driven approach that fund...

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The article presents a novel and innovative approach to enhancing the safety of Large Language Models (LLMs) through humor, addressing a significant issue with current refusal prefix methods which are susceptible to attacks. The discussion on how humor can disarm potentially harmful instructions while preserving the quality of interactions adds a unique perspective to the conversation about LLM safety. The methodological rigor is evident in the validation against various attack vectors, suggesting a practical applicability that could influence future research in AI safety protocols.

Certified Robustness Under Bounded Levenshtein Distance

Text classifiers suffer from small perturbations, that if chosen adversarially, can dramatically change the output of the model. Verification methods can provide robustness certificates against such a...

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The article presents a novel method, LipsLev, which significantly improves the efficiency of verification methods for text classifiers against adversarial perturbations while addressing the challenge of Levenshtein distance. Its methodological rigor, demonstrated results, and potential to influence future research in text classification robustness are key factors for the high score.

Meson thermalization with a hot medium in the open Schwinger model

Quantum field theories treated as open quantum systems provide a crucial framework for studying realistic experimental scenarios, such as quarkonia traversing the quark-gluon plasma produced at the La...

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The article addresses the thermalization processes of mesons in a hot medium using a novel approach via tensor network algorithms in an open quantum system framework. Its focus on quarkonia in quark-gluon plasma is highly relevant to current experimental studies in particle physics. The methodological rigor and scalability of the simulations enhance the robustness of the findings, making this research significant for advancing theoretical understanding and practical applications in high-energy physics. However, while the results are impactful, they may have limited immediate applicability to broader fields outside theoretical physics.

Antiquity, Dark Ages and Renaissance of Light-Front Higher Spin Theory

These notes contain -- apart from some physics -- scattered reminiscences of everyday life at the Institute for Theoretical Physics in Göteborg in the early eighties. The text has been in the making f...

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The article presents a historical perspective on light-front higher spin theory and reflects on its development and recent revival. While it has elements of nostalgia and personal insights, the impact on advancing physics is limited by the lack of comprehensive, new findings or methodologies. However, it may be important for contextual understanding and encouraging scholarly reflection about the evolution of ideas in theoretical physics.

Estimating the Poynting flux of Alfvénic waves in polar coronal holes across Solar Cycle 24

Alfvénic waves are known to be prevalent throughout the corona and solar wind. Determining the Poynting flux supplied by the waves is required for constraining their role in plasma heating and acceler...

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The article provides novel insights into the role of Alfvénic waves in the solar wind and their implications for energy transfer and plasma heating. Its systematic approach and methodical data analysis broaden the understanding of wave behavior in relation to solar activity, which is critical for theories of solar dynamics. The rigorous comparison of findings with existing models and observational data adds robustness to the work, potentially influencing future studies on solar wind physics and coronal heating mechanisms.

Solutions of differential equations in Freud-weighted Sobolev spaces

We lay some mathematically rigorous foundations for the resolution of differential equations with respect to semi-classical bases and topologies, namely Freud-Sobolev polynomials and spaces. In this q...

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The article presents a novel approach to solving differential equations within the context of Freud-weighted Sobolev spaces, integrating various established mathematical theories and methodologies. Its rigorous foundations and exploration of topics like Sobolev orthogonal polynomials and Painlevé equations highlight its methodological rigor. The application to the Gross-Pitaevskii equation also demonstrates a clear relevance to practical problems in mathematical physics, enhancing its impact in the field.

Combined Routing Protocol (CRP) for ad hoc networks: Combining strengths of location-based and AODV-based schemes

The work proposes a new Combined Routing Protocol (CRP) for ad hoc networks that combines the benefits and annihilates the shortcomings of two well-known on-demand routing protocols in ad hoc networks...

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The proposed Combined Routing Protocol (CRP) addresses the limitations of established ad hoc networking protocols by innovatively integrating elements from AODV and GPSR. This dual method not only enhances routing efficiency but also targets latency-sensitive applications, indicating strong practical relevance and applicability. The work demonstrates methodological rigor through thorough analysis of both protocols and their integration, showcasing improved packet delivery and route stability.