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Reconstructing Quantitative Cerebral Perfusion Images Directly From Measured Sinogram Data Acquired Using C-arm Cone-Beam CT

To shorten the door-to-puncture time for better treating patients with acute ischemic stroke, it is highly desired to obtain quantitative cerebral perfusion images using C-arm cone-beam computed tomog...

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The article presents a novel approach combining time-resolved image reconstruction and perfusion parametric estimation into a single optimization problem. This methodological innovation directly addresses significant challenges in the field of acute ischemic stroke treatment, aiming to improve patient outcomes. The use of a subject-specific generative model suggests high applicability in clinical settings. The study demonstrates strong results indicating potential for widespread use in relevant medical imaging applications, which significantly impacts the field.

Tensor-product vertex patch smoothers for biharmonic problems

We discuss vertex patch smoothers as overlapping domain decomposition methods for fourth order elliptic partial differential equations. We show that they are numerically very efficient and yield high ...

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The article presents novel methods in numerical analysis for solving biharmonic problems, specifically focusing on tensor-product vertex patch smoothers. The strong emphasis on computational efficiency, convergence rates, and low-rank tensor approximations suggests significant advancements in this area. The thorough experimental validation enhances its credibility, showcasing practicality in real-world applications. The discussion on mixed-precision computations reflects an understanding of modern computational needs, indicating that this research could influence future methods in numerical simulations and computational fluid dynamics.

Spinal ligaments detection on vertebrae meshes using registration and 3D edge detection

Spinal ligaments are crucial elements in the complex biomechanical simulation models as they transfer forces on the bony structure, guide and limit movements and stabilize the spine. The spinal ligame...

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The article presents a novel methodology for detecting spinal ligament attachment points on 3D vertebrae meshes, which is essential for creating accurate biomechanical models of the spine. Its methodological rigor is evident in the integration of fast registration and edge detection techniques. The high accuracy of landmark identification and the significant reduction in processing time represent major advancements over existing methods, increasing its relevance for clinical applications in spinal biomechanics. However, further validation in diverse patient populations could enhance its impact.

An example of potential density on $Hilb^3$ of a K3 surface

We give a new example of potential density of rational points on the third punctual Hilbert scheme of a K3 surface.

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This article presents a new example related to potential density of rational points in a specific mathematical structure, which is of significant interest in algebraic geometry. The novelty lies in providing fresh insights into rational points on the Hilbert scheme, a topic of increasing relevance. The methodological rigor might not be fully assessed without further detail on proofs or approaches taken, but it suggests utility for both theoretical advancements and practical applications in K3 surfaces, which are a critical area of study in the intersection of algebra and geometry.

Approximations of the Iterative Stockholder Analysis scheme using exponential basis functions

In this work, we introduce several approximations of the Iterative Stockholder Analysis (ISA) method based on exponential basis functions. These approximations are categorized into linear and non-line...

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The article presents novel approximations to a significant method in the analysis of electronic structure, specifically the Iterative Stockholder Analysis (ISA). The introduction of LISA and NLIS models enhances the existing framework with effective computational strategies. The rigorous benchmarking against diverse molecular systems suggests strong methodological robustness and provides valuable insights for future research in electronic structure analysis.

An Experimental Framework for Implementing Decentralized Autonomous Database Systems in Rust

This paper presents an experimental framework for implementing Decentralized Autonomous Database Systems (DADBS) using the Rust programming language. As traditional centralized databases face challeng...

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The article presents a novel and timely contribution to the field of decentralized database systems, especially by utilizing Rust—a language known for its performance and safety. The methodological rigor in evaluating key performance metrics gives it practical importance. The work not only addresses existing challenges but also sets a foundation for future research in DADBS, making it highly relevant.

On Convergents of Proper Continued Fractions

Proper continued fractions are generalized continued fractions with positive integer numerators $a_i$ and integer denominators with $b_i\geq a_i$ . In this paper we study the strength o...

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This article presents significant advancements in the understanding of proper continued fractions and their convergents, particularly through its classification of types and the introduction of the ergodic two-dimensional Gauss map. The methodological rigor in classification and the introduction of new concepts enhance its impact on the field. The potential applications in number theory are notable, especially in approximation theory, adding to its relevance for future research.

Improving analytical color and texture similarity estimation methods for dataset-agnostic person reidentification

This paper studies a combined person reidentification (re-id) method that uses human parsing, analytical feature extraction and similarity estimation schemes. One of its prominent features is its low ...

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This article presents a novel dataset-agnostic approach to person re-identification, which enhances accessibility and practical application, particularly in real-world environments like security systems. The low computational demands for edge devices are particularly valuable given the growing interest in deploying AI on mobile and localized systems. The use of novel analytical techniques in color and texture feature extraction adds to the paper's methodological rigor and originality. Its comparison against established deep learning methods gives it a solid foundation for potential adoption.

Towards the interoperability of low-code platforms

With the promise of accelerating software development, low-code platforms (LCPs) are becoming popular across various industries. Nevertheless, there are still barriers hindering their adoption. Among ...

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This article addresses a significant barrier to the adoption of low-code platforms, specifically the issue of vendor lock-in and interoperability. The proposed solution of using automatic migration methods and leveraging large language models (LLM) for image recognition is novel and technically innovative. The approach has the potential to greatly facilitate transitions between platforms, which is vital for improving LCP adoption. The methodological rigor in analyzing LCPs and defining transformation pathways adds robustness to the research, making it particularly relevant for both practitioners and researchers in the field.

LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking

Wi-Fi localization and tracking has shown immense potential due to its privacy-friendliness, wide coverage, permeability, independence from lighting conditions, and low cost. Current methods can be br...

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The article presents a novel approach to generating ground truth data for Wi-Fi localization using vision, addressing critical limitations in current data-driven methods. Its applicability to practical data collection is a significant advancement, potentially improving model performance in real-world settings. The methodological rigor appears sound, and the commitment to sharing resources for future research enhances its value.

Coherent Axion Production through Laser Crystal Interaction

We investigate the interaction between an optical laser and an ionic crystal, revealing a coherent enhancement in axion production when the laser is incident at specific angles. Additional enhancement...

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The article presents a novel approach to axion production, showcasing a significant increase in transition probabilities compared to existing methods. The investigation into laser-crystal interactions introduces an innovative angle to axion detection and generation, emphasizing practicality in terrestrial experiments. The methodological approach is rigorous, with clearly defined experimental setups and expected outcomes that could substantially impact the field of particle physics.

Black hole with a de Sitter core: classical and quantum features

This work examines the implications of a black hole featuring a de Sitter core. We begin by analyzing the spacetime and event horizon in the presence of de Sitter core. Then the partial wave equation ...

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The article presents a novel approach to understanding black holes that incorporate features of de Sitter spacetime, which is significant as it merges classical and quantum considerations in a complex arena. The study's methodological rigor in deriving the partial wave equation and exploring the implications of quasinormal modes indicates thorough research, making it useful for ongoing studies in gravitational physics and quantum gravity. Moreover, the practical exploration of accretion disks and emission rates enhances its applicability to observational astrophysics.

A Motivic Riemann-Roch Theorem for Deligne-Mumford Stacks

We develop a motivic cohomology theory, representable in the Voevodsky's triangulated category of motives, for smooth separated Deligne-Mumford stacks and show that the resulting higher Chow group...

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This article introduces a significant advancement in the field of algebraic geometry by extending classical theorems to the realm of Deligne-Mumford stacks, which are vital in modern geometric studies. The methodology appears rigorous, leveraging established theories like Voevodsky's triangulated category and providing valuable insights into the interplay between motivic cohomology and higher K-theory. The result has implications for current research and opens avenues for future exploration in motivic theories.

Enhancing Fourier pricing with machine learning

Fourier pricing methods such as the Carr-Madan formula or the COS method are classic tools for pricing European options for advanced models such as the Heston model. These methods require tuning param...

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This article addresses a notable gap in Fourier pricing methods by proposing a novel approach that utilizes machine learning to estimate tuning parameters more efficiently. Its methodological rigor, including comprehensive numerical experiments, adds credibility, and the ability to control error without retraining enhances its applicability in real-world scenarios. The integration of machine learning with established pricing theories presents significant interdisciplinary opportunities.

Open string field theory in lightcone gauge

We study covariant open bosonic string field theory in lightcone gauge. When lightcone gauge is well-defined, we find two results. First, the vertices of the gauge-fixed action consist of Mandelstam d...

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This article provides significant insights into the structure of open string field theory within lightcone gauge, addressing both theoretical and methodological aspects. The findings regarding the relationship between gauge-fixed vertices and moduli spaces add depth to existing theoretical frameworks, highlighting the nuances of vertex construction in string theory. Additionally, the exploration of longitudinal degrees of freedom introduces a potentially novel perspective on scattering processes. The clarity and rigor of the methodology further bolster its contribution to the field, making it beneficial for researchers seeking to advance theoretical physics, particularly in string theory.

On constant mean curvature surfaces satisfying integrable boundary conditions

We consider the local theory of constant mean curvature surfaces that satisfy one or two integrable boundary conditions and determine the corresponding potentials for the generalized Weierstrass repre...

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This article addresses a specialized area within differential geometry and minimal surface theory by exploring constant mean curvature surfaces under specific boundary conditions. The focus on integrable conditions and their implications for the Weierstrass representation contributes novel insights, which could serve as a basis for further mathematical exploration and application in related fields.

Exotic newforms constructed from a linear combination of eta quotients

K{ö}hler, in [1], presented a weight 1 newform on $Γ_0(576)$ constructed from a linear combination of weight 1 eta quotients and asked, ``What would be a suitable $L$ and rep...

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This article contributes to the ongoing research in number theory, particularly in the study of newforms and their properties in relation to Galois representations. The novelty of constructing exotic newforms using eta quotients, along with a clear focus on the Deligne-Serre correspondence, indicates a significant advancement in this area. The methodological rigor is evidenced through the detailed study of Galois extensions and the implications for splitting primes, which could have further applications in arithmetic geometry and related fields.

BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects

We present BimArt, a novel generative approach for synthesizing 3D bimanual hand interactions with articulated objects. Unlike prior works, we do not rely on a reference grasp, a coarse hand trajector...

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BimArt introduces a novel methodology for simulating bimanual interactions that addresses previous limitations in reference usage and separate mode handling. Its methodological rigor and emphasis on actionable insights regarding feature representation and contact priors make it a significant contribution to the field. The quantitative experiments further demonstrate its superiority in generating realistic hand-object interactions, which could transform animation practices and robotics.

Reconstruction of 3D lumbar spine models from incomplete segmentations using landmark detection

Patient-specific 3D spine models serve as a foundation for spinal treatment and surgery planning as well as analysis of loading conditions in biomechanical and biomedical research. Despite advancement...

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The study presents a novel and efficient method for reconstructing 3D lumbar spine models from incomplete data, addressing a significant challenge in spine diagnostics and treatment. Its methodological rigor, demonstrated accuracy, and clinical relevance highlight its potential to impact both clinical practice and future research in the field.

Sample path central limit theorem for the occupation time of the voter model on a lattice

In this paper, we extend the central limit theorem of the occupation time of the voter model on the lattice $\mathbb{Z}^d$ given in \cite{Cox1983} to the sample path case for $d\geq 3$ ...

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The extension of the central limit theorem for occupation time to sample paths represents a significant advancement in the understanding of voter models, particularly in higher dimensions. The methodology utilizing established strategies adds robustness to the findings, while the conjecture provides a promising direction for future research. The novelty in addressing the sample path aspect enhances its applicability in both theoretical and applied contexts.