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AR-SFQ: Asynchronous Reset Library Using α-Cell Design

Rapid Single Flux Quantum (RSFQ) circuits are the most evolved superconductor logic family. However, the need to clock each cell and the deep pipeline causes a complex clock network with a large skew....

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The article presents a novel approach to address the challenges associated with Rapid Single Flux Quantum circuits by introducing an asynchronous reset cell library. The concept of the α-cell to facilitate bidirectional signal paths is innovative, and the reduction of the need for complex clock networks could significantly advance the efficiency and scalability of RSFQ technologies. The demonstrated improvements in reliability and efficiency bolster the robustness of the results, making this work a potential catalyst for future research in superconductor logic circuits and high-performance computing.

The Reconstruction of Theaetetus' Theory of Ratios of Magnitudes

In the present chapter, we obtain the reconstruction of Theaetetus' theory of ratios of magnitudes based, according to Aristotle's Topics 158b, on the definition of proportion in terms of equa...

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This article emphasizes a novel reconstruction of Theaetetus' ratio theory, challenging existing interpretations and providing a more refined approach based on historical texts. Its focus on the anthyphairesis offers a unique perspective in the philosophy of mathematics, which could influence future studies in mathematical philosophy and ancient mathematics.

Auslander regular algebras and Coxeter matrices

We show that Iyama's grade bijection for Auslander-Gorenstein algebras coincides with the bijection introduced by Auslander-Reiten. This result uses a new characterisation of Auslander-Gorenstein ...

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This article presents significant advancements in the understanding of Auslander-Gorenstein algebras by linking them to Coxeter matrices through a novel characterization, which enhances the simplicity of calculating grade bijections. The findings are methodologically rigorous and have broad implications in both theoretical mathematics and applied combinatorics, indicating potential for further exploration in related fields.

Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness

This paper investigates the robustness of vision-language models against adversarial visual perturbations and introduces a novel ``double visual defense" to enhance this robustness. Unl...

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This paper presents a novel approach to enhancing the robustness of vision-language models through a two-tiered defense mechanism against adversarial attacks. The methodological innovation of large-scale adversarial vision-language pre-training from scratch is both rigorous and intuitive, addressing a significant gap in existing models. The results demonstrate substantial improvements over prior models, setting a new state-of-the-art, which indicates high applicability and potential for future advancements in both research and practical implementations.

The flux of electron antineutrinos from supernova SN1987A data

By adopting a state-of-the-art parameterized model of electron antineutrino emission, we have made some steps forward in the analysis of the thermodynamical properties and temporal structure of neutri...

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This article offers novel insights into the neutrino emission characteristics from SN1987A using advanced modeling techniques. Its substantial confidence level findings and thorough statistical validation contribute significantly to our understanding of core collapse supernovae. The integration of arrival times, energies, and angles denotes methodological rigor and presents implications for both particle physics and astrophysics, making it quite impactful for future research.

Solving the unsolvable: Translating case law in Hong Kong

This paper addresses the challenges translating case law under Hong Kong's bilingual legal system. It highlights the initial success of translating all written statutes into Chinese before the 199...

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The paper presents a critical issue regarding the bilingual legal system in Hong Kong with a novel and pragmatic solution using advanced AI technologies. Its interdisciplinary approach, involving law, linguistics, and AI, indicates its high potential impact on both legal practices and translation studies. The critique of current governmental and judicial practices highlights the gaps that future research can address. The proposed multi-agent system offers a fresh perspective on legal translations, which is particularly relevant in an increasingly globalized context.

On the number of atomic configurations in hot plasmas

We propose approximate and accurate formulas for the number of electron configurations in hot plasmas. Such a quantity is an ingredient of algorithms devoted to the generation of configurations or sup...

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The article addresses a significant gap in the understanding of atomic configurations within hot plasmas, which is critical for opacity calculations relevant in astrophysics and fusion research. The introduction of Bessel functions of fractional order in this context suggests a novel approach, enhancing its methodological rigor. Additionally, the advancements proposed in the article could lead to improved models in plasma physics, making it impactful for future investigations.

Effects of Social Contextual Variation Using Partner Avatars on Memory Acquisition and Retention

This study investigates how partner avatar design affects learning and memory when an avatar serves as a lecturer. Based on earlier research on the environmental context dependency of memory, we hypot...

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This study presents a novel investigation into the impact of social context, specifically through partner avatars, on learning and memory retention. Its methodological approach of contrasting varied versus constant avatars provides valuable insights into the optimization of immersive virtual learning environments. The findings hold implications for designing more effective educational tools.

Mixed atomic-scale electronic configuration as a strategy to avoid cocatalyst utilization in photocatalysis by high-entropy oxides

To enhance the activity of photocatalysts for hydrogen production and CO2 conversion, noble metal cocatalysts as electron traps and/or acceptors such as platinum or gold are usually utilized. This stu...

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The article presents a novel strategy for enhancing photocatalytic performance by eliminating the need for noble metal cocatalysts, a significant advancement in the field. The rigorous examination of high-entropy oxides as a flexible system for electronic configurations adds methodological strength, suggesting a strong potential for practical applications in photocatalysis. The findings may encourage further exploration into alternative materials and design strategies, emphasizing their interdisciplinary relevance.

A multi-class non-local macroscopic model with time delay for mixed autonomous / human-driven traffic

In this paper, we present a class of systems of non-local conservation laws in one space-dimension incorporating time delay, which can be used to investigate the interaction between autonomous and hum...

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The article presents a novel approach to modeling traffic that integrates both autonomous and human-driven vehicles, which is increasingly relevant as cities look to incorporate automated technologies. The incorporation of time delay and non-local interactions offers a new perspective on traffic dynamics, making this research both innovative and timely. The methodological rigor demonstrated through rigorous proofs of solution existence and stability, alongside practical numerical simulations, underlines its scientific validity. This could lead to advancements in smart transportation systems and urban planning.

Observable Signatures of RN Black Holes with Dark Matter Halos via Strong Gravitational Lensing and Constraints from EHT Observations

We investigate the impact of dark matter halos on the gravitational lensing produced by electrically charged, spherically symmetric black holes in the strong-field regime. The study focuses on two dar...

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The article tackles the intersection of charged black holes and dark matter halos, exploring novel implications through strong gravitational lensing. Its quantitative analysis and observational constraints position it as a seminal contribution with a high potential impact on black hole physics and dark matter research. The methodological rigor, particularly in deriving coefficients for the strong deflection limit and applying EHT data, enhances its robustness and utility for future investigations in astrophysics.

Testing Born's rule via photoionization of helium

It is shown how state-of-the-art attosecond photoionization experiments can test Born's rule -- a postulate of quantum mechanics -- via the so-called Sorkin test. A simulation of the Sorkin test u...

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This article presents a novel experimental approach to testing a fundamental postulate of quantum mechanics, which is significant for both theoretical and practical advancements in the field. The use of state-of-the-art attosecond photoionization techniques demonstrates methodological rigor and potential for high precision, elevating the discussion around Born's rule. Its implications for experimental quantum mechanics and foundational studies indicate a strong relevance for ongoing research.

$L$ -smooth factorization for Noetherian $F$ -finite rings

We show that any homomorphism between Noetherian $F$ -finite rings can be factored into a regular morphism between Noetherian $F$ -finite rings followed by a surjection. This result esta...

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This article presents significant advances in the understanding of morphisms between Noetherian $F$-finite rings, which has implications for the classification of ring maps and structures. The equivalence of regularity and formal smoothness with $L$-smoothness introduces a novel perspective in commutative algebra and algebraic geometry. The rigorous mathematical framework and connection to existing theorems enhance its impact and applicability, particularly for those studying algebraic structures and homomorphisms.

Scaling up self-supervised learning for improved surgical foundation models

Foundation models have revolutionized computer vision by achieving vastly superior performance across diverse tasks through large-scale pretraining on extensive datasets. However, their application in...

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The article presents a significant advancement in surgical computer vision through the introduction of a novel foundation model, SurgeNetXL. Its extensive training on the largest surgical dataset to date underscores its methodological rigor. The performance improvements reported are notable, as is the open-access availability of models and data, which enhances reproducibility and community engagement. The insights provided for further research also suggest strong applicability in future studies, positioning this work as a potential benchmark in the field.

A cluster theory approach from mutation invariants to Diophantine equations

In this paper, we define and classify the sign-equivalent exchange matrices. We give a Diophantine explanation for the differences between rank 2 cluster algebras of finite type and affine type based ...

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This article provides a novel perspective by connecting mutation invariants to Diophantine equations through cluster algebra theory. The approach showcases methodological rigor in classification tasks and provides significant insights into both finite and affine types of cluster algebras. The application to Diophantine equations further enhances its importance, potentially opening new avenues for research in algebra and number theory.

Agile System Development Lifecycle for AI Systems: Decision Architecture

Agile system development life cycle (SDLC) focuses on typical functional and non-functional system requirements for developing traditional software systems. However, Artificial Intelligent (AI) system...

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The article presents a significant advancement by addressing the gap in agile system development for AI systems, particularly focusing on decision architecture—a crucial aspect in AI development. Its innovative approach emphasizes the necessity of adapting traditional methodologies to accommodate the unique characteristics of AI, thus potentially influencing future methodologies in the field. The practical application in insurance claims processing enhances its relevance, demonstrating real-world applicability.

CaPa: Carve-n-Paint Synthesis for Efficient 4K Textured Mesh Generation

The synthesis of high-quality 3D assets from textual or visual inputs has become a central objective in modern generative modeling. Despite the proliferation of 3D generation algorithms, they frequent...

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The article presents a novel approach (CaPa) to 3D mesh generation, addressing key challenges in the field, such as multi-view consistency and texture quality. Its methodological rigor, including the decoupling of geometry and texture generation and the introduction of Spatially Decoupled Attention, showcases innovative advancements. The practical implications and efficient generation times further enhance its relevance, suggesting significant utility in commercial applications and potential to inspire future research in generative modeling.

On a Gelfand-Tsetlin representation of $\mathfrak{sl}_3$ in the space of sections of a local system with two monodromy parameters

We construct a Gelfand-Tsetlin representation of $\mathfrak{sl}_3$ in the space of sections of a local system. The local system lives on an open part of the flag variety given by the intersect...

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This article presents a significant advancement in the representation theory of Lie algebras, specifically $ ext{sl}_3$, through the construction of a Gelfand-Tsetlin representation. This is particularly relevant due to the introduction of two monodromy parameters and the application to sections of a local system, suggesting potential robustness in applicability. The rigorous analysis of the representation structure adds methodological strength, which can influence future research in both representation theory and related algebraic geometry fields.

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy

While large language models (LLMs) present significant potential for supporting numerous real-world applications and delivering positive social impacts, they still face significant challenges in terms...

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The article offers a thorough survey that addresses critical risks associated with large language models (LLMs) and provides a unified framework for their responsible development and deployment. The novelty lies in its comprehensive approach that integrates various mitigation strategies across all phases of LLM usage, making it a vital resource for both researchers and practitioners. Its methodological rigor and focus on real-world applications also enhance its relevance for future research in the field.

HpC: A Calculus for Hybrid and Mobile Systems -- Full Version

Networked cybernetic and physical systems of the Internet of Things (IoT) immerse civilian and industrial infrastructures into an interconnected and dynamic web of hybrid and mobile devices. The key f...

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The article introduces a new calculus (HpC) specifically designed for hybrid and mobile systems, which is increasingly relevant in the context of growing IoT applications. Its conservative extension approach to the π-calculus ensures it retains established theoretical benefits while expanding applicability to dynamic environments. This research is methodologically robust, as it uses formal frameworks to ensure correctness and reliability, critical in fast-evolving technological fields. The showcase of a practical handover protocol example demonstrates real-world relevance.