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A luminescent folded S-shaped high-nuclearity Eu19-oxo-cluster embedded polyoxoniobate for information encryption

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Chinese Chemical Letters 2025年第2期36卷 526-530页

作者： Wen-Jun Xia yong-jiang Wang Yun-Fei Cao Cai Sun Xin-Xiong Li Yan-Qiong Sun Shou-Tian Zheng College of Chemistry Fuzhou University

Ln-containing polyoxoniobates （PONbs） have appealing applications in luminescence,information encryption and magnetic fields,but the synthesis of PONbs containing high-nuclearity Ln-O clusters is challenging due to the easy hydrolysis of Ln3+ions in alkaline *** this paper,we are able to integrate CO32-and high-nuclearity Ln-O clusters into PONb to construct an inorganic giant Eu19-embedded PONb H49K16Na13（H2O）63[Eu21O2（OH）7（H2O）5(Nb7O22)10（Nb2O6）2（CO3）18]·91H2O （1）,which contains the highest nuclearity Eu-O clusters and the largest number of Eu3+ions among *** addition,the film that was prepared by mixing 1 with gelatin and glycerol,exhibits reversible luminescence switching behavior under acid/alkali stimulation and has been used to create a fluorescence-encoded information *** work paves a feasible strategy for the construction of high-nuclearity Ln-O cluster-containing PONbs and the expansion of the application of Ln-containing PONbs in information encryption.

关键词： Acid/alkali stimulation Information encryption Lanthanide Luminescence Polyoxoniobate

Feedback processing in the primate brain and in AI systems

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Science China(Technological Sciences) 2024年第8期67卷 2297-2309页

作者： jiang yong HE Sheng Institute of Biophysics Chinese Academy of SciencesBeijing 100101China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China University of Chinese Academy of Sciences Beijing 100049China

The primate brain and artificial intelligence(AI) can both be conceptualized as information processing systems, each with its own distinct biological and computational architectures. While there are parallels between them, their respective structural and functional connections show significant differences. In this paper, we examine the central role of feedback processing in both the primate brain and AI systems, which has been shown to be crucial in shaping neural processing. By reviewing the key features of feedback processes in the primate brain, which allows the brain to incorporate prior knowledge, contextual information, and taskdemands into early-stage processing, we highlight the divergence in goals and functions between biological and AI *** these differences is crucial for elucidating the cognitive capabilities of the primate brain and for addressing computational challenges in AI. In advocating “Cognition-Inspired-Computation”, we suggest that integrating insights from feedback processing in the primate brain into AI research will offer potentially significant improvements for the advancement of AI systems.

关键词： cognitive neuroscience artificial intelligence feedback processing attention learning

Fluid Approximation and Its Convergence Rate for GI/G/1 Queue with Vacations

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Acta Mathematicae Applicatae Sinica 2011年第1期27卷 43-58页

作者： yong-jiang Guo School of Science Beijing University of Posts and Telecommunications Beijing 100876 China

A GI/G/1 queue with vacations is considered in this paper. We develop an approximating technique on max function of independent and identically distributed （i.i.d.） random variables, that is max{ηi, 1 ≤ i ≤ n}. The approximating technique is used to obtain the fluid approximation for the queue length, workload and busy time processes. Furthermore, under uniform topology, if the scaled arrival process and the scaled service process converge to the corresponding fluid processes with an exponential rate, we prove by the approximating technique that the scaled processes characterizing the queue converge to the corresponding fluid limits with the exponential rate only for large N. Here the scaled processes include the queue length process, workload process and busy time process.

关键词： GI/G/1 queue with vacations fluid approximation exponential rate of convergence

Asymptotic Variability Analysis for Multi-Server Generalized Jackson Network in Overloaded

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Acta Mathematicae Applicatae Sinica 2016年第3期32卷 713-730页

作者： yong-jiang GUO School of Science Beijing University of Posts and Telecommunications

The asymptotic variability analysis is studied for multi-server generalized Jackson network. It is characterized by law of the iterated logarithm （LIL）, which quantifies the magnitude of asymptotic stochastic fluctuations of the stochastic processes compensated by their deterministic fluid limits. In the overloaded （OL） case, the asymptotic variability is studied for five performance measures： queue length, workload, busy time, idle time and number of departures. The proof is based on strong approximations, which approximate discrete performance processes with （reflected） Brownian motions. We conduct numerical examples to provide insights on these LIL results.

关键词： Asymptotic variability generalized Jackson network (GJN) law of the iterated logarithm (LIL) strong approximation (SA)

On the Fluid Approximation for a Multiclass Queue under Non-Preemptive SBP Service Discipline

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Acta Mathematica Sinica,English Series 2012年第2期28卷 379-404页

作者： yong jiang GUO School of Science Beijing University of Posts and TelecommunicationsBeijing 100876P.R.China

A multi-class single server queue under non-preemptive static buffer priority （SBP） service discipline is considered in this paper. Using a bounding technique, we obtain the fluid approximation for the queue length and busy time processes. Furthermore, we prove that the convergence rate of the fluid approximation for the queue length and busy time processes is exponential for large N. Additionally, a sufficient condition for stability is obtained.

关键词： Multi-class queue non-preemptive SBP service discipline fluid approximation stability,exponential rate of convergence

Empirical Likelihood Confidence Intervals for the Differences of Quantiles with Missing Data

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Acta Mathematicae Applicatae Sinica 2009年第1期25卷 105-116页

作者： yong-song Qin yong-jiang Qian School of Mathematical Sciences Guangxi Normal University Guilin Guangxi 541004 China

Suppose that there are two nonparametric populations x and y with missing data on both of them. We are interested in constructing confidence intervals on the quantile differences of x and y. Random imputation is used.... 详细信息

关键词： Empirical likelihood confidence Interval quantile missing data imputation

Robust Unsupervised Discriminative Dependency Parsing

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Tsinghua Science and Technology 2020年第2期25卷 192-202页

作者： yong jiang Jiong Cai Kewei Tu School of Information Science and Technology Shanghai Tech UniversityShanghai 201210China Shanghai Institute of Microsystem and Information Technology Chinese Academy of SciencesShanghai 200050 University of Chinese Academy of Sciences Beijing 100049China

Discriminative approaches have shown their effectiveness in unsupervised dependency ***,due to their strong representational power,discriminative approaches tend to quickly converge to poor local optima during unsupervised *** this paper,we tackle this problem by drawing inspiration from robust deep learning ***,we propose robust unsupervised discriminative dependency parsing,a framework that integrates the concepts of denoising autoencoders and conditional random field *** this framework,we propose two types of sentence corruption mechanisms as well as a posterior regularization method for robust *** tested our methods on eight languages and the results show that our methods lead to significant improvements over previous work.

关键词： unsupervised learning dependency parsing autoencoders

考虑出力随机性下的风光火联合调度-控制优化模型

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电气开关 2025年第1期63卷 15-18页

作者：江勇王绍帅辽港控股(营口)有限公司水电分公司辽宁营口115007

针对风电和光伏出力的随机性,提出一种日前优化和日内优化相结合的风光火调度模型。该模型以不同时段风电、光电出力和负荷的预测值作为日前优化调度的基础,运用混合整数线性规划对各机组出力进行优化配置,找到满足约束条件的最优出力,... 详细信息

针对风电和光伏出力的随机性,提出一种日前优化和日内优化相结合的风光火调度模型。该模型以不同时段风电、光电出力和负荷的预测值作为日前优化调度的基础,运用混合整数线性规划对各机组出力进行优化配置,找到满足约束条件的最优出力,并将该出力作为日内调度的计划值。日内优化调度通过模型预测控制建立日内滚动优化模型,实现对风电和光电出力实时控制,达到风电出力和光电出力跟踪计划值。火电作为备用电源,满足供电对负荷的功率平衡要求。仿真结果表明,双层优化下的调度-控制模型,在满足经济调度的同时,也能有效平抑可再生能源的出力波动,为含可再生能源的优化调度提供一种策略。

关键词：风光火出力波动日前优化日内优化模型预测控制

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基于复合指纹法解析西南岩溶小流域泥沙来源

中国环境科学 2025年第2期45卷 954-965页

作者：戴涛蒋勇军田兴刘芳韩莎罗淑娥西南大学地理科学学院岩溶环境重庆市重点实验室重庆400715

以重庆市中梁山凤凰村岩溶洼地为研究区,基于复合指纹识别技术,选取最佳指纹因子组合,利用多元线性混合模型(IsoSource)与贝叶斯混合模型(MixSIAR、SIMMR、SIAR)量化潜在泥沙源地对洼地沉积物的贡献率,并使用均方根误差(RMSE),结合前人... 详细信息

以重庆市中梁山凤凰村岩溶洼地为研究区,基于复合指纹识别技术,选取最佳指纹因子组合,利用多元线性混合模型(IsoSource)与贝叶斯混合模型(MixSIAR、SIMMR、SIAR)量化潜在泥沙源地对洼地沉积物的贡献率,并使用均方根误差(RMSE),结合前人的观测结果,评估模型的适用性.研究结果表明:沉积物总碳(TC)含量、砂粒含量、70%频度下土壤粒径(D70)、土壤有机碳(SOC)含量、硫元素(S)含量5种指纹因子的累积判别正确率为89.5%,可以作为最佳指纹因子组合.4个模型的RMSE为:MixSIAR(2.05)、SIMMR(2.05)、SIAR(2.07)、IsoSource(2.34),其中所有贝叶斯混合模型的RMSE均小于IsoSource模型,说明使用贝叶斯混合模型量化洼地沉积物泥沙来源比例的适用性高于多元线性混合模型.其中MixSIAR模型与SIMMR模型的准确性最高,两者的计算结果类似,均表明耕地是洼地沉积物主要的泥沙来源地,沟壁是仅次于耕地的第二大泥沙来源地,而林草地的侵蚀产沙量最低.本研究利用复合指纹识别技术揭示了西南典型岩溶槽谷区洼地沉积物的泥沙来源,以期为类似泥沙来源研究提供模型选择的参考.

关键词：土壤侵蚀复合指纹岩溶槽谷区泥沙来源模型