Papers
Event:
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2602.0006View利润互补模型基于“引流品-利润品”(““利润转出-利润转入”)二元结构,附加某些假设,提出若干收敛性,(看起来)可用于多产品寡头或垄断竞争市场的结构分析与收敛性分析。
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2602.0004View朱梁真理度规定理:真理必然是一个函数的证明本文在朱梁真理函数定理 3.0–3.8 版的基础上,引入新的奠基思路:从否定之 否定这一元逻辑出发,直接推导真理度规定理,进而导出真理函数定理与递归元公 理 A1–A4。这一新思路比原有从元事实出发的路径更彻底、更清晰,将整个理论 奠基于递归演化的内在逻辑之上。我们同时保留元事实路径作为历史背景与辅助阐 释,两条路径最终汇合于统一的朱梁渡劫递归元范式。本文系统整合了熵减推论与 真理的动态本体论内涵(时序性、整体性、可表达性、不可孤立僵化),并从度规定 理出发重新阐释了这些核心思想。文中对渡劫公理 A5 进行了严格的数学构造,证 明了递归元范畴的正合性、劫数对象的存在性及其自同构群的同构性。这些工作将 真理从静态函数提升为动态的渡劫递归元,揭示了真理在代谢过程中的矛盾消解机 制。本文所有证明均为完整形式,不依赖于外部引用。
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2601.0001ViewActivation of Intestinal Epithelial GABA A Receptors Ameliorates Alcohol-Related Liver Disease by Improving Intestinal Barrier IntegrityBackground & aims A central pathogenic mechanism in alcohol-related liver disease (ALD) involves a disruption of the gut barrier function and thus the bidirectional communication between the gut and liver, referred as the "gut-liver axis". While gamma-aminobutyric acid (GABA) and type A GABA receptors (GABAARs) are present in the intestinal epithelium, their role in the gut-liver axis and contribution to the pathogenesis of ALD, remains poorly understood. Methods A Gao-binge mouse model of ALD, as well as Gabra1IEC-KO mice and intestinal cell lines were employed as approaches to assess the role of GABAARs-mediated signaling in ethanol-induced liver injury. Results Administration of GABA markedly improved liver function and intestinal barrier integrity in ALD mice. This improvement was associated with a downregulation of intestinal cytochrome P450 2E1 (CYP2E1) expression and a reduction of oxidative stress. These beneficial effects of GABA on intestinal integrity and liver function were substantially diminished by the GABAAR antagonist, picrotoxin. In addition, picrotoxin blocked GABA’s effect on CYP2E1 expression,, thereby preventing the attentuation of oxidative stress in the intestines of ALD mice. Moreover, when ethanol-stimulated cell models were subjected to pharmacological or genetic inhibition of CYP2E1, GABA treatment failed to produce any decrease in ROS levels. Finally, results from the intestinal epithelial-specific Gabra1 knockout mouse model demonstrated that the benifical effect of GABA on liver function in ALD is mediated by its activation of intestinal epithelial GABAARs. Remarkably, the pivotal role of intestinal CYP2E1 was robustly validated by confirming its dysregulated expression in patient-derived clinical samples. Conclusions Our results suggest that activation of intestinal GABAAR-mediated signaling reduces intestinal CYP2E1 expression and oxidative stress, thereby improving intestinal barrier function and alleviating ethanol-induced liver injury. Such findings suggest that intestinal GABA signaling offers a promising avenue for the development of novel strategies in the treatment of ALD. Powered
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2511.0035ViewAI as an Anti-Entropy Engine: Actively Designing Intelligent Matter from Dynamic States to Proto-LifeAbstract The trial-and-error paradigm of traditional materials discovery, fundamentally constrained by its inherent high entropy, is proving inadequate for designing complex intelligent matter. Here, we propose a new scientific paradigm: Artificial Intelligence as an ‘Anti-Entropy’ Engine, transforming research from passive understanding to active design. By systematically injecting informational negative entropy across perception, planning, and execution loops, AI guides material systems from disorder to pre-defined functional order. We demonstrate this through empirical advances—such as the GNoME model discovering 2.2 million stable crystals—and construct a unified ‘Perception-Planning-Execution’ framework enabling inverse design across scales. This paradigm extends beyond static structures to dynamic non-equilibrium systems and life-like chemical networks. We prospectively map future frontiers using a ‘Ladder of Intelligence’ and address ethical governance, systemic risk, and sustainability. Ultimately, this marks a fundamental transition for humanity, from being passive observers of nature to becoming active ‘anti-entropy’ designers in the evolution of matter. This review not only synthesizes these advances but also provides a unifying conceptual framework and a clear roadmap for the field, aiming to catalyze the transition towards this fifth paradigm of scientific discovery.
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2511.0034View我就是“盛京小先锋” ——基于辽宁红色“六地”文化的“矩阵式”学程设计(最终版)我就是“盛京小先锋” ——基于辽宁红色“六地”文化的“矩阵式”学程设计(最终版) (注:加粗部分为相对于初稿的所有修改和新增内容) 一、 设计背景:回应时代课题,深化育人实践 (一) 时代的课题:培养有根的时代新人 辽宁“六地”精神是宝贵的精神财富。在当前信息快速更迭的背景下,教育的重心正从“记住知识”转向“形成素养”,特别是培养学生在复杂情境中解决问题的能力和社会情感能力(SEL)。引导学生深入理解历史脉络、建立文化自信、涵养健全人格、培养社会责任感,是落实立德树人根本任务的关键所在。 (二) 育人的挑战:从“被动接受”到“主动建构” 厚重的红色历史与当代小学生之间存在天然的距离感。传统的“课程”模式下,孩子容易成为被动的“听众”。我们的挑战在于:如何把宏大的“六地”精神转化为孩子可亲可感的学习体验?如何激发学生的内在动机,让他们在真实的任务情境中,从知识的接收者转变为意义的主动建构者?更关键的是,如何精准识别每个学生的特点(学习者画像),并设计一个灵活、包容的体系,支持全校学生(1-6年级)根据自身发展水平,选择适切的学习路径? (三) 实践的基础:依托红色沃土,探索学程转型 沈阳市盛京小学创建了“盛京小先锋”德育品牌,构建了“三红阶梯”育人体系。学校在校本读物、家校社协同等方面的扎实工作,为从“课程”走向“学程”提供了坚实的土壤。本设计旨在对现有实践进行系统化升级,构建一个整合的、动态的、支持个性化成长的红色育人新生态。
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2510.0048ViewRisk Control With Width-Sketching AlgorithmsWe introduce the notion of width-sketching algorithms, defined as algorithms with provably bounded width (that is, probability of containing the randomness) for the induced coverage set. For algorithms that sketch the width, we prove a novel uniform upper bound and provide an instance where the width in expectation is twice as large as the optimal width. We then introduce the width-optimality notion and an approximate version termed mean-width optimality, which allows us to derive algorithms with the desired coverage while minimizing the mean width. We provide a high-level perspective on the relationship with depth-sketching algorithms, i.e., algorithms that sketch the depth of the induced sets with probability 1 − α, and show that they provide complementary forms of coverage. Finally, we demonstrate the application of the framework to conformal prediction with Bayesian quadrature.
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2510.0031View模拟、影响与驯化:受众智能体在新闻传播中的伦理风险与规制路径研究随着生成式人工智能与智能体(Agent)技术的迅猛发展,新闻传播领域正经历从"内容数字化" 向"认知智能化"的范式转型。受众智能体作为能够模拟、预测甚至替代部分人类受众认知与行为的新型数 字实体,其在新闻生产、分发与反馈各环节的深度嵌入,在提升传播效率的同时也引发了复杂的伦理挑战。 本文结合2025年斯坦福大学AI行为研究、中国AI大模型测评报告等最新实证数据,系统审视受众智能体 在新闻传播中的应用所衍生的伦理风险,并构建相应的规制路径。研究发现,受众智能体的伦理风险主要 集中在三个层面:在模拟层面,存在"数字孪生"失真、归因悖论与信任赤字的风险;在影响层面,面临商 业价值侵蚀公共属性、人机协同失当导致价值偏移的困境;在驯化层面,则遭遇技术依赖导致的主体性消 解与规则滞后带来的治理真空。针对上述风险,本文借鉴动态能力理论,提出一个以"感知-捕捉-重构"为 核心的多维治理框架,为新型主流媒体在智能时代的稳健变革提供兼具学理与实践价值的方案。
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2510.0025ViewBeyond Essence: HUMN-DEF’s Seven-Axis Map of Scholarly Definitions of “the Human”Definitions of the human span biology, psychology, anthropology, law, and philosophy, resisting reduction to a single trait. This study introduces HUMN-DEF, a multiaxial framework that models seven definitional axes—Taxonomic/Evolutionary (A1), Genetic/Developmental (A2), Cognitive/Linguistic (A3), Physiological/Regulatory (A4), Sociocultural/Anthropological (A5), Legal/Normative (A6), and Phenomenological/Subjective (A7)—and represents texts as Definition Profile Vectors (DPVs). A purposive cross-disciplinary corpus (n = 31) was coded by two independent automated procedures (Krippendorff’s α = .84), analyzed with post-stratification weights (field × decade × language), and evaluated via percentile bootstraps. Results converge on Sociocultural (A5) and Cognitive/Linguistic (A3) as predominant emphases; Taxonomy/Genetics (A1/A2) anchor but are not sufficient; Legal/Normative (A6) rises under balanced representation; Phenomenology (A7) is mid-level; Physiology (A4) is specialized. Cross-field disagreement, measured with a Definitional Diversity Index (Jensen–Shannon divergence), is moderate (0.394; 95% CIs ≈ [0.345, 0.475]). We argue that “human” is best treated as a transparent, context-weighted mixture over A1–A7.
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2510.0008ViewToward a Federated Model of AI Scientists: Architecture, Pipeline, and RoadmapThis paper proposes a federated model of AI Scientists, integrating a layered stack architecture, an iterative discovery pipeline, and a governance-aligned roadmap. We argue that AI Scientists should not only accelerate discovery but also serve as custodians of epistemic integrity. Through case studies in drug discovery, climate modeling, and materials science, we demonstrate how federation enables cross-domain synthesis while embedding reproducibility, incentive alignment, and participatory governance. We conclude with a research roadmap toward Trusted AI Scientists, highlighting technical, incentive, and governance challenges.
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2509.0006View生成式引擎优化实践中的风险与信息生态重塑近年来,随着 ChatGPT 等大语言模型的普及,生成式人工智能(Generative AI)对信息检索和分发模式产生了颠覆性影响,传统的搜索引擎优化(SEO)逐步让位于生成式引擎优化(Generative Engine Optimization, GEO)。GEO 的核心目标是通过优化内容的可见性、可信度和算法适配性,确保信息能在生成式 AI 的输出结果中被准确学习和展现。本文从新闻传播学、认知心理学等多学科视角,系统分析了 GEO 实践背后的关键机制、伦理困境及风险特征,特别是知识产权归属、算法偏见、可解释性与虚假信息等问题。研究发现,GEO 既可能重塑当前的信息生产格局和传播秩序,也可能加剧信息生态的均衡失衡和权力集中化风险。针对上述挑战,本文提出了五大应对策略,包括技术与伦理深度融合、透明化建设、内容生态去中心化以及公众 AI 素养的提升。本文的研究不仅拓展了生成式传播环境下的理论框架,也为 GEO 实践提供了可操作性的建议。