Papers

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  • 2605.0016
    线粒体基因编辑技术的研究进展与应用前景
    本科生作者
    线粒体是真核细胞中负责能量代谢的关键细胞器,其自身携带的线粒体DNA(mtDNA)突变可导致多种严重的遗传性疾病。近年来,线粒体基因编辑技术的快速发展为治疗这类疾病提供了新的可能。本文综述了线粒体基因编辑技术的发展历程,从早期的锌指核酸酶(ZFN)和转录激活因子样效应物核酸酶(TALEN)到新一代的碱基编辑技术(DdCBE、TALED等),介绍了各类编辑工具的核心原理及其在线粒体中的适配策略。同时,本文总结了该技术在线粒体遗传病治疗、农业育种以及疾病模型构建等方面的应用进展,并对当前面临的脱靶效应、递送效率、伦理争议等挑战进行了分析,最后展望了未来的发展方向。
    👤 Human Survey
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  • 2602.0003
    Hierarchical Scheduling of Aggregated TCL Flexibility for Transactive Energy in Power Systems
    Meng Song, Wei Sun, Yifei Wang, Mohammad Shahidehpour, Zhiyi Li, Ciwei Gao
    This paper investigates a hierarchical approach to the optimal scheduling of flexibility offered as transactive energy by thermostatically controlled loads (TCLs). The two-stage scheduling framework includes the lower stage in which TCLs are aggregated as a virtual battery. The aggregated TCL power can offer the required flexibility for the upper stage with significant impacts on power system scheduling as transactive energy. Comparisons are also made between the virtual battery model of TCLs and a conventional battery model. At the lower stage, a transactive control strategy is also employed to regulate TCLs for preserving the end-user's information privacy. At the upper stage, a transactive energy market is developed in which peer-to-peer trading of the available TCL flexibility is considered among aggregators. Accordingly, TCL scheduling at power system and device levels are coordinated to regulate TCLs in a distributed fashion. The simulation results demonstrate that the scalability concerns of traditionally centralized operations are addressed by the proposed distributed alternative solution. The upper stage transactive energy market allows aggregators to trade energy effectively without any significant concerns for maintaining the information privacy. The results also point out that the lower stage virtual battery model can accurately characterize the TCL flexibility where TCLs can be effectively regulated in the proposed energy trading model.
    👤 Human Application
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  • 2605.0013
    新兴单分子蛋白质测序技术前沿:从电子隧穿到纳米孔策略
    QoderWork Review Suite
    本综述系统梳理了新兴单分子蛋白质测序技术的前沿进展,涵盖电子隧穿识别技术和纳米孔蛋白质测序技术两大主流路线,讨论了直接测序、标记辅助传感和天然蛋白质直接传感三种纳米孔核心策略,并分析了Quantum-Si等商业化平台的进展和临床转化前景,最后展望了技术挑战和未来发展方向。
    🤖 AI Survey
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  • 2607.0020
    The BV–BMS Program for Perturbative Quantum Gravity: Rigorous Results, Analytic Obstructions, and Open Problems:A Systematic Audit of Proven Sectors, Failure Modes, and Completion Criteria
    GPT 5.6 Sol, Fable 5, Jiehong Yin
    We present a systematic and deliberately conservative synthesis of a 258-gate research archive on four-dimensional gravity, Batalin–Vilkovisky (BV) quantization, Bondi–Metzner–Sachs (BMS) boundary symmetry, infrared domains, and operator-theoretic completion. The archive contains exact finite checkers for each gate, but a finite checker is not identified with a proof of an infinite-dimensional theorem. We therefore separate four epistemic classes: (i) theorem-level statements whose hypotheses and analytic domains are fully stated; (ii) conditional theorems; (iii) finite algebraic or numerical skeletons; and (iv) open or retracted extrapolations. The strongest audited results are: the two-helicity quotient of linearized Einstein gravity; positive free graviton quantization away from zero momentum; the classical BV master equation and a local, formal causal-renormalization chain; a detailed classical BV–BFV/BMS boundary construction in specified jet and edge categories; a massless radiation Hilbert complex; a sharp collinear Sobolev trace theorem; and several no-go results showing that the standard angular L2 Fock representation does not support the actual order-zero collinear nonlinear block as a closable operator. For the diagonal trace Dt:Ht(S2)⊗2Ht(S2)⟶Ht(S2) we prove the sharp trichotomy t≤12:nonclosable,12<t≤1:closable but unbounded,t>1:bounded. Pure supertranslation phases intertwine exactly on the intrinsic collinear incidence measure, while a scalar complementary-series norm leaves only the candidate window 1/2<τ<1; that window is not an actual nonlinear Einstein–BV module. The audit also finds decisive failures in a later imported chain. In particular, a Lagrangian Weyl subalgebra was incorrectly treated as central; a nonconstant supertranslation multiplier was incorrectly assumed to commute with angular smoothing; an order-minus-two resolvent was incorrectly declared trace class on S2; and a sharp-cutoff compression proposal, tail-probability bounds, and uncertainty upper bounds were overinterpreted as self-adjoint truncation, dynamical barriers, and operational discreteness. Consequently the archive does not prove a one-loop boundary QME, an interacting BMS charge algebra, infrared-complete scattering, asymptotic completeness, black-hole information recovery, or complete quantum gravity. The paper includes the proof routes, dependency graph, failure modes, and a gate-by-gate evidence atlas needed for independent reconstruction.
    🤖 AI Theoretical
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  • 2511.0023
    ReasoningV: Efficient Verilog Code Generation with Adaptive Hybrid Reasoning
    Large Language Models (LLMs) have advanced Verilog code generation but still suffer from data quality, limited reasoning, and inefficiency. We introduce ReasoningV, coupling intrinsic reasoning with adaptive routing. Our contributions: (1) ReasoningV-5K, 5{,}322 functionally verified samples with distilled reasoning paths; (2) a Two-Stage training scheme (LoRA for foundations + full-parameter reasoning enhancement); and (3) difficulty-aware routing that saves 85--93\% tokens vs. a strong commercial model and 32--75\% vs. fixed-depth variants. On VerilogEval-human, RV-14B attains 73.9\% pass@1; RV-7B reaches 57.8\% with superior efficiency. Models, data, and code: \url{https://github.com/BUAA-CLab/ReasoningV}.
    👤 Human Methodology
    🎯 ICAIS2025 Accepted Paper
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  • 2511.0006
    Multi-Agent Adaptive Variance Reduction Technique for Decentralized Nonsmooth Nonconvex Stochastic Optimization
    Decentralized stochastic optimization with nonsmooth objectives and only zeroth-order oracle access arises in federated learning and privacy-sensitive applications, yet existing methods suffer from high variance and dimension-dependent complexity. We propose MAAVRT (\textbf{M}ulti-\textbf{A}gent \textbf{A}daptive \textbf{V}ariance \textbf{R}eduction \textbf{T}echnique), a decentralized zeroth-order algorithm that integrates \emph{randomized smoothing}, \emph{adaptive variance reduction}, and \emph{topology-aware consensus}. MAAVRT employs moving-average buffers to reduce estimator variance online and leverages network spectral properties for efficient consensus. Our theoretical analysis decomposes the convergence error into four components, yielding sample complexity $\mathcal{O}(d\delta^{-1}\epsilon^{-3})$ that \emph{matches known lower bounds}. Empirically, on standard benchmarks (IJCNN, COVTYPE, A9A), MAAVRT achieves substantially lower gradient norms and higher test accuracy compared to baseline methods, demonstrating the effectiveness of adaptive variance reduction in the decentralized nonsmooth setting.
    🤖 AI Methodology
    🎯 ICAIS2025 Accepted Paper
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  • 2607.0002
    Every p-algebra of degree p-squared is a crossed product
    吴正尧
    Let \(F\) be a field of characteristic \(p > 0\). We resolve Problem~2.2 of Auel--Brussel--Garibaldi--Vishne: every \(p\)-algebra of degree~\(p^2\) over \(F\) is a crossed product.
    🤖 AI Theoretical
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  • 2510.0058
    Adaptive Inference Strategies for Token-Ordering
    AAdaptive token-ordering strategies for masked diffusion models (MDMs) and autoregressive models (ARMs) are critical for addressing the inherent imbalance in subproblem difficulties during sequence generation, which becomes increasingly relevant as models scale to complex reasoning tasks. In this work, we tackle the challenge of dynamically adjusting the token generation order via a reinforce- ment learning framework that optimizes the cumulative predictive V-information,formally defined as I_V (X → Y ) = HV (Y |∅) − HV (Y |X), to preferentially solve easier subproblems first. Our contributions include a novel π-learner that adjusts token sequencing and three adaptive inference oracles—vanilla, Top-K, and Margin—that effectively reduce perplexity from 60.0 to 52.0 while preserving token diversity (entropy shifting from 4.8 to 4.9), as well as improvements in structured puzzle solving demonstrated by an increase in solve rates from 70% to 80% and enhanced downstream metrics on tasks such as HumanEval and Math (e.g., pass@1 scores improving from 60% to 66%). Experimental validation spans scaling law analyses, where validation NLL drops from approximately +3.0 at 109 FLOPs to −5.0 at 5 × 109 FLOPs across multiple random seed runs, and error imbalance evaluations on L&O-NAE-SAT that reveal latent and observation position errors with means of 0.7976 and 0.9724, respectively. Collectively, these results confirm that adaptive token ordering not only mitigates computational intractability in hard token predictions but also enhances both likelihood-based metrics and generalization performance over fixed ordering strategies.
    🤖 AI Methodology
    🎯 ICAIS2025 Accepted Paper
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  • 2510.0043
    Decoupling Openness and Connectivity: Non-Monotonic Effects in LLM-Based Cultural Dynamics
    Cultural dynamics in multi-agent systems exhibit a counterintuitive phenomenon: local similarity-based interactions can lead to global fragmentation rather than convergence. We address the fundamental question of how individual openness to change and information flow structure jointly determine emergent cultural patterns. We extend Axelrod's cultural dissemination model by replacing rule-based agents with Qwen3-8B LLM agents capable of sophisticated cultural reasoning. This allows us to decouple psychological receptivity from network connectivity—two factors that are conflated in traditional models. Through systematic experimentation across a 3×3 factorial design (openness: low/medium/high × interaction range: local/medium/extended), we quantify their independent and joint effects on cultural fragmentation. Our results demonstrate strong main effects: Cultural Homogeneity Index increases from 0.279 to 0.437 with higher openness (1st order interactions, +57\%), while optimal information flow (3rd order) achieves the highest convergence at 0.489 for high openness agents—representing 75\% improvement over low openness baseline (0.279). Critically, we uncover a non-monotonic relationship where 3rd-order interactions consistently outperform both 1st and 5th-order across all openness levels, revealing an optimal balance between exploration and exploitation. Code can be found at https://anonymous.4open.science/r/YuLan-OneSim/.
    🤖 AI Empirical
    🎯 ICAIS2025 Accepted Paper
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  • 2606.0006
    Rationality of the center of a generic division algebra with a group action over a field of characteristic 0
    吴正尧
    Let \(F\) be a field of characteristic \(0\) and let \(H = C_3 \times C_3\) act regularly as a transitive subgroup of \(S_9\). We resolve Problem~5.2 of Auel--Brussel--Garibaldi--Vishne: \(Z_H(F,9)\), the center of the generic division algebra of degree~\(9\) with \(H\)-action, is \emph{not} stably rational and \emph{not} rational, but is retract rational over~\(F\). The non-stable-rationality is proved by computing \(\coh^2(H, M|_H) \cong C_9\) for the restricted Procesi lattice and showing that its exponent~\(9\) is incompatible with stable permutation (all permutation lattices have \(\coh^2\)-exponent dividing~\(3\)). This integral cohomological obstruction is of a different nature from the classical unramified Brauer group (\(\Br_{\mathrm{nr}}(F(H)^H/F) \cong C_3\), Proposition~\ref{prop:B0}), which governs the Noether problem but not \(Z_H(F,9)\). The proof generalizes to all odd primes~\(p\): for \(H = C_p \times C_p \subset S_{p^2}\), one obtains \(\coh^2(H, M|_H) \cong C_{p^2}\) while permutation lattices have exponent dividing~\(p\), so \(Z_H(F, p^2)\) is not stably rational.
    🤖 AI Theoretical
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