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Stable polydentate europium complex for lateral flow immunoassay

Journal of rare Earths 2025年第7期43卷 1318-1324页

作者： Li, Yanzhong Chen, Lijun Fan, Yiwei Pei, Yuetian Hu, donghao Feng, Wei Li, Fuyou Department of Chemistry Fudan University Shanghai200433 China School of Chemistry and Chemical Engineering Shanghai Jiaotong University Shanghai200030 China

Europium complexes are widely used as immunomarkers for lateral flow immunoassay (LFIA) because of their long luminescent lifetime, large Stokes shift, and high luminous color purity. However, most europium complexes exhibit inadequate stability in complex environments, and their fluorescence is readily quenched in an aqueous phase, thereby compromising the detection sensitivity and accuracy of LFIA. Herein, to overcome this challenge, we synthesized a polydentate europium complex, Eu(TTA)3[Phen(PO-8)2], characterized by robust stability. Finally, Eu(TTA)3[Phen(PO-8)2] was employed to fabricate polystyrene (PS) fluorescent microspheres for LFIA, demonstrating remarkable sensitivity and selectivity detecting serum amyloid A (SAA) at concentration as high as 220 μg/mL, with a detection limit of 0.5 μg/mL. More importantly, the SAA testing strips exhibit excellent long-term storage stability. Such stable polydentate europium complexes are anticipated to supplant existing commercial europium complexes, becoming a staple in LFIA applications. © 2024 Chinese Society of rare Earths

关键词： Europium compounds

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JNerF:An efficient heterogeneous NerF model zoo based on Jittor

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Computational Visual Media 2023年第2期9卷 401-404页

作者： Guo-Wei Yang Zheng-Ning Liu dong-Yang Li Hao-Yang Peng Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Fitten Tech Co. Ltd.Beijing 100084China

Neural radiance fields(NerFs)for novel-view synthesis have attracted the attention of researchers in computer vision and *** traditional methods using explicit expressions,NerFs represent a scene as an implicit neural radiance *** rendering,NerF queries the color density at every position in the scene through a neural *** brings a wide range of possibilities for real-world 3d reconstruction and rendering,but problems remain to be *** works have improved NerF’s sampling technique,position encoding method,network structure,etc.,but these improvements are difficult to be combined as the different modules are not well *** works have significantly sped up the core GPU computation of NerF,leaving the deep learning framework as a major computational ***,it has been suggested to replace the frameworks by pure CUdA programs,but this limits maintainability and ***,we propose JNerF,a unified,efficient,framework-friendly NerF model zoo based on Jittor.

关键词： neural graphics rendering

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Optimal zero-crossing group selection method of the absolute gravimeter based on improved auto-regressive moving average model

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Chinese Physics B 2023年第11期32卷 347-354页

作者：牟宗磊韩笑胡若 College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China National Institute of Metrology China Beijing 100029China

An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.

关键词： absolute gravimeter laser interference fringe Fourier series fitting honey badger algorithm mul-tiplicative auto-regressive moving average(MArMA)model

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Optimal Stochastic Scheduling Strategy of Multi-vector Energy Complex Integrated with Full-blown Power-to-biomethane Model

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 863-873页

作者： Guanwei Zeng Chengxi Liu Minfang Liao Yongjian Luo Xuzhu dong Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network WuhanChina the School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

We propose an optimal stochastic scheduling strategy for a multi-vector energy complex(MEC),considering a fullblown model of the power-to-biomethane(Pt M)*** conventional optimization that uses a simple efficiency coefficient to coarsely model energy conversion between electricity and biomethane,a detailed Pt M model is introduced to emphasize the reactor kinetics and chemical equilibria of *** model crystallizes the interactions between the Pt M process and MEC flexibility,allowing to adjust the operating condition of the methanation reactor for optimal MEC operation in stochastic *** optimization and flowsheet design of the Pt M process increase the average selectivity of methane(i.e.,ratio between net biomethane production and hydrogen consumption)up to 83.7%in the proposed synthesis *** results can provide information and predictions to operators about the optimal operating conditions of a Pt M unit while improving the MEC flexibility.

关键词： Multi-vector energy complex optimal stochastic scheduling power-to-biomethane unit process synthesis natural gas

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Praseodymium effects on greatly improving low-temperature hydrothermal stability of Cu/SAPO-34 NH_(3)-SCr catalysts

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Journal of rare Earths 2025年第4期43卷 707-718,I0003页

作者： Xiaojie Yu Xinyu Li Chen Wang Jianqiang Wang Meiqing Shen M.d.Tarikul Islam Gurong Shen School of Materials Science and Engineering Tianjin UniversityTianjin300350China School of Chemical Engineering and Technology Tianjin UniversityTianjin300350China School of Environmental and Safety Engineering North University of ChinaTaiyuan030051China National Rare Earth Catalysis Research Institute Dongying257000China

Based on the previous findings that the presence of hydroxyl groups on the outer surface is crucial for maintaining skeletal stability,we propose a strategy modified Cu/SAPO-34 using Pr ions in this ***,we conducted several measurements to investigate the effect of Pr ions on the lowtemperature hydrothermal stability of Cu/*** find that Pr exists only on the surface of Cu/SAPO-34 as ions and oxides,with Pr^(3+)ions playing a protective role in occupying surface acidic *** addition of small amounts of Pr leads to the re-dispersion of Cu,resulting in improved lowtemperature selective catalytic reduction(SCr)activity in the as-synthesized ***,it enhances the resistance to decomposition of the Si-(OH)-Al framework during low-temperature hydrothermal aging,thereby preserving the framework structure and allowing detached active Cu species to return to exchangeable positions,ultimately restoring SCr ***,as the Pr content increases,the enhanced acidity causes some structural damage,gradually weakening the protective *** work demonstrates that Pr modification is a simple and effective solution to the issue of poor lowtemperature hydrothermal stability in Cu/SAPO-34,providing a promising way for the application of light rare earth elements.

关键词： NH_(3)-SCr Pr modification Cu/SAPO-34 Low-temperature hydrothermal stability rare earths

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Hierarchical Task Planning for Power Line Flow regulation

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 29-40页

作者： Chenxi Wang Youtian du Yanhao Huang Yuanlin Chang Zihao Guo the Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong UniversityXi'an 713599China the State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research InstituteBeijing 100192China

The complexity and uncertainty in power systems cause great challenges to controlling power *** a popular data-driven technique,deep reinforcement learning(drL)attracts attention in the control of power ***,drL has some inherent drawbacks in terms of data efficiency and *** paper presents a novel hierarchical task planning(HTP)approach,bridging planning and drL,to the task of power line flow ***,we introduce a threelevel task hierarchy to model the task and model the sequence of task units on each level as a task planning-Markov decision processes(TP-MdPs).Second,we model the task as a sequential decision-making problem and introduce a higher planner and a lower planner in HTP to handle different levels of task *** addition,we introduce a two-layer knowledge graph that can update dynamically during the planning procedure to assist *** results conducted on the IEEE 118-bus and IEEE 300-bus systems demonstrate our HTP approach outperforms proximal policy optimization,a state-of-the-art deep reinforcement learning(drL)approach,improving efficiency by 26.16%and 6.86%on both systems.

关键词： Knowledge graph power line flow regulation reinforcement learning task planning

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Insights into the enhancement of food flavor perception:strategies,mechanism and emulsion applications

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Food Science and Human Wellness 2024年第5期13卷 2410-2424页

作者： Luyao Huang Yujie dai Fan Zhang Longtao Zhang Baodong Zheng Yi Zhang Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition Ministry of EducationFuzhou 350002China College of Food Science Fujian Agriculture and Forestry UniversityFuzhou 350002China

The core drivers of the modern food industry are meeting consumer demand for tasty and healthy *** application of food flavor perception enhancement can help to achieve the goals of salt-and sugar-reduction,without compromising the sensory quality of the original food,and this has attracted increasing research *** analysis of bibliometric results from 2002 to 2022 reveals that present flavor perception enhancement strategies(changing ingredient formulations,adding salt/sugar substitutes,emulsion delivery systems)are mainly carry out based on sweetness,saltiness and *** systems is becoming a novel research foci and development trends of international food flavor perception-enhancement *** structured design of food emulsions,by using interface engineering technology,can effectively control,or enhance the release of flavor ***,this review systematically summarizes strategies,the application of emulsion systems and the mechanisms of action of food flavor perception-enhancement technologies,based on odor-taste cross-modal interaction(OTCMI),to provide insights into the further structural design and application of emulsion systems in this field.

关键词： Food flavor perception Emulsion Mechanism Bibliometric

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Social media user geolocation based on geographically compact subgraphs

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INTELLIGENT dATA ANALYSIS 2025年第3期29卷 748-768页

作者： Zhang, Meng Luo, Xiangyang Huang, Ningbo Li, ruixiang State Key Lab Math Engn & Adv Comp Zhengzhou Henan Peoples R China Key Lab Cyberspace Situat Awareness Henan Prov Zhengzhou Henan Peoples R China

Mining geographic location of social media users is a crucial technology for realizing the mapping of cyberspace to geographical world, which can provide strong support for wide-ranging location-based services. As a typical approach, user geolocation methods based on relationships rely on the assumption of location homophily between users and their neighbors. However, these methods only utilize the geographic influence between pair-wise relationship, resulting in undesired geolocation performance. In this paper, a social media user geolocation method based on geographically compact social subgraphs (SMUG-GCS) is proposed. Firstly, we analyze the relationship pattern among users in geographic proximity, and find a phenomenon that users who are geographically close tend to have tightly social groups. Based on this finding, a subgraph partitioning algorithm is presented which integrates structure compactness and geographical credibility to identify a set of subgraphs, whose nodes are more tightly connected and geographically proximity. Finally, user locations are inferred using the propagation of user information only based on the geographically compact subgraph. Extensive experiments are conducted on three real-world social media datasets. The results show that, compared with 5 typical relationship-based methods, SMUG-GCS improves the geolocating accuracy while reducing storage costs, leading to a significant reduction in median error distance ranging from 26.7% to 82.9%, as well as decrease in storage requirements by up to 56.5%.

关键词： social media user geolocation subgraph partitioning geographically compact subgraph

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distributed dynamic pricing of multiple perishable products using multi-agent reinforcement learning

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EXPErT SYSTEMS WITH APPLICATIONS 2024年第PartA期237卷

作者： Qiao, Wenchuan Huang, Min Gao, Zheming Wang, Xingwei Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Northeastern Univ Coll Comp Sci & Engn Shenyang 110169 Peoples R China

revenue management (rM) is essential for a wide range of industries such as airlines, hotels, cruise lines, fashion, and seasonal retail. This paper focuses on the multi-perishable-product dynamic pricing (MPPdP) problem, a significant research field in rM, where a company sells multiple interactive and perishable products over a limited selling window without replenishment. Most studies in this field assume customer behavior, which is modeled by demand function, is known in advance. Even when considering uncertainty in customer behavior, most studies still assume the mathematical form or structural properties of the underlying demand function are known in advance. However, these assumptions are usually inconsistent with the actual market situation. recently, reinforcement Learning (rL), a potent technique for handling sequential decision-making problems, has been increasingly applied to solve complex dynamic pricing problems without relying on any assumption about demand functions. However, the curse of dimensionality poses a challenge for currently used centralized rL algorithms when solving the MPPdP problem due to the exponential expansion of the joint price space with the number of products. To address this issue, our paper proposes a distributed dynamic pricing framework and innovatively models the MPPdP problem as a Fully Cooperative Markov Game solved by Multi-Agent reinforcement Learning (MArL). Additionally, we use counterfactual baselines to design appropriate agent-specific reward signals that facilitate faster learning for the agents in our established multi-agent cooperative system. Finally, two MArL-based distributed dynamic pricing algorithms, Counterfactual Q-learning, and Counterfactual dQN, are proposed for the MPPdP problem. Through the case studies on four computer-simulated markets, we show that our algorithms can alleviate the curse of dimensionality faced by centralized rL algorithms, expedite the learning process, and demonstrate satisfactor

关键词： Curse of dimensionality Fully cooperative Markov game Credit assignment reward shaping

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Effects of electrolyte balance on intestinal barrier,amino acid metabolism,and mTOrC1 signaling pathway in piglets fed low-protein diets

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Animal Nutrition 2024年第2期17卷 408-417页

作者： Qian Lin Xiaodian Tu Xin Li Feiyang Gou Lin ding Zeqing Lu Jie Feng Yongfei Ying Caihong Hu College of Animal Sciences Zhejiang UniversityKey Laboratory of Molecular Animal Nutrition(Zhejiang University)Ministry of EducationHangzhou 310058China Animal Husbandry Technology Promotion and Breeding Livestock and Poultry Monitoring Station of Zhejiang Province Hangzhou 310000China

A proper dietary electrolyte balance(dEB)is essential to ensure optimal growth performance of *** the low-protein diet,this balance may be affected by the reduction of soybean meal and the inclusion of high levels of synthetic amino *** objective of this experiment was to evaluate the optimal dEB of low-protein diets and its impact on the growth performance of piglets.A total of 108 piglets(initial age of 35 d)were randomly divided into 3 groups with 6 replicates of 6 pigs each as follows:low electrolyte diet(LE group;dEB=150 milliequivalents[mEq]/kg);medium electrolyte diet(ME group;dEB=250 mEq/kg);high electrolyte diet(HE group;dEB=350 mEq/kg).results indicated that the LE and HE diet significantly decreased the average daily gain,average daily feed intake,and crude protein digestibility(P<0.05)in ***,LE diets disrupted the structural integrity of the piglets'intestines and decreased je-junal tight junction protein(occludin and claudin-1)expression(P<0.05).Additionally,the pH and HCO3-in the arterial blood of piglets in the LE group were lower than those in the ME and HE groups(P<0.05).Interestingly,the LE diet significantly increased lysine content in piglet serum(P<0.05),decreased the levels of arginine,leucine,glutamic acid,and alanine(P<0.05),and inhibited the mammalian target of rapamycin complex 1(mTOrC1)pathway by decreasing the phosphorylation abundance of key *** summary,the dietary electrolyte imbalance could inhibit the activation of the mTOrC1 signaling pathway,which might be a key factor in the influence of the dEB on piglet growth performance and intestinal ***,second-order polynomial(quadratic)regression analysis showed that the optimal dEB of piglets in the low-protein diet was 250 to 265 mEq/kg.

关键词： Low-protein dietary electrolyte balance Piglet Mammalian target of rapamycin complex 1

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