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An Efficient Boron Source Activation Strategy for the Low‑Temperature Synthesis of Boron Nitride Nanotubes

Nano-Micro Letters 2025年第1期17卷 548-558页

作者： Ying Wang Kai Zhang Liping Ding Liyun Wu Songfeng E Qian He Nanyang Wang Hui Zuo Zhengyang Zhou Feng Ding Yue Hu Jin Zhang Yagang Yao National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional Materialsand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093People’s Republic of China School of Electronic Information and Artificial Intelligence Shaanxi University of Science&TechnologyXian 710000People’s Republic of China college of Bioresources Chemical and Materials Engineering Shaanxi University of Science&TechnologyXian 710000People’s Republic of China Key Laboratory of Carbon Materials of Zhejiang Province College of Chemistry and Materials EngineeringWenzhou UniversityWenzhou 325000People’s Republic of China Shenzhen Institutes of Advanced technology Chinese Academy of SciencesShenzhen 518000People’s Republic of China college of Chemical and Molecular Engineering Peking UniversityBeijing 100871People’s Republic of China

Lowering the synthesis temperature of boron nitride nanotubes(BNNTs)is crucial for their *** primary reason for adopting a high temperature is to enable the effective activation of highmelting-point solid *** this study,we developed a novel approach for efficiently activating boron by introducing alkali metal compounds into the conventional MgO–B *** approach can be adopted to form various low-melting-point AM–Mg–B–O growth *** growth systems have improved catalytic capability and reactivity even under low-temperature conditions,facilitating the synthesis of BNNTs at temperatures as low as 850℃.In addition,molecular dynamics simulations based on density functional theory theoretically demonstrate that the systems maintain a liquid state at low temperatures and interact with N atoms to form BN *** findings offer novel insights into the design of boron activation and are expected to facilitate research on the low-temperature synthesis of BNNTs.

关键词： Boron nitride nanotubes Low-temperature Boron activation Density functional theory

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Breaking new ground in photocatalysis: lutetium texaphyrin as a trigger for pyroptosis through biomolecular photoredox reactions

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science China Chemistry 2025年第1期 1-2页

作者： Qihang Ding Mengrong He Meijia Gu Department of Chemistry Korea University Department of Ultrasound Medicine Union Hospital Tongji Medical College Huazhong University of Science and Technology Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (MOE) School of Pharmaceutical Sciences Wuhan University

Malignant neoplasms consistently pose a significant threat to global public health [1,2]. In recent years, immunotherapy has demonstrated remarkable clinical success; however, its efficacy is limited by the scarcity of immune cell infiltration within tumor microenvironments. Cell pyroptosis, a gasdermin-mediated process characterized by cellular swelling,rupture, and the release of intracellular contents such as IL-1β, IL-18, ATP, HMGB1, plays a crucial role in this context[3,4].

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Rough Set Model for Cognitive Expectation Embedded Interval-Valued Decision Systems

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Chinese Journal of Electronics 2018年第4期27卷 675-679页

作者： DAI Jianhua LIU Zhenbo HU Hu SHI Hong School of computer science and technology Tianjin University college of computer science and technology Zhejiang University

Interval-valued information system is a kind of knowledge representation model for uncertain information. An interval-valued attribute has an expectation by experience or background knowledge, called cognitive expectation. There are few studies aiming at intervalvalued attributes with cognitive expectations. We propose the concept of Interval-valued decision system with expectations(IDSE). A new dominance relation based on the distances between expectations and interval values is constructed. Based on the constructed dominance relation, a rough set model for IDSE is investigated. Attribute reduction in IDSE is also examined by using discernibility matrices and discernibility functions.

关键词： Rough set Interval-valued decision system with cognitive expectation Attribute reduction

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A spotlight on dosage and subject selection for effective neuroprotection: exploring the central role of mitochondria

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Neural Regeneration Research 2025年第4期20卷 1081-1082页

作者： John Mitrofanis Jonathan Stone Michael R.Hamblin Pierre Magistretti Alim-Louis Benabid Glen Jeffery Fonds Clinatec UniversitéGrenoble AlpesGrenobleFrance School of Medical science University of SydneySydneyAustralia Faculty of Health sciences University of JohannesburgJohannesburgSouth Africa King Abdullah University of science and technology ThuwalSaudi Arabia Institute of Ophthalmology University College LondonLondonUK

Neurons are notoriously vulnerable cell *** the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological conditions,including stroke,head trauma,and neurodegenerative disease,can generate stress in neurons,affecting their survival and proper *** most neural pathologies,mitochondria become dysfunctional and this plays a pivotal role in the process of cell *** challenge over the last few decades has been to develop effective interventions that improve neuronal homeostasis under pathological *** interventions,often referred to as disease-modifying or neuroprotective,have,however,proved frustratingly elusive,at both preclinical and,in particular,clinical *** this perspective,we highlight two factors that we feel are key to the development of effective neuroprotective *** are:firstly,the choice of dose of intervention and method of application,and secondly,the selection of subjects,whether they be patients or the animal model.

关键词： protective dosage distress

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A multiscale-contour-based interpolation framework for generating a time-varying quasi-dense point cloud sequence

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Frontiers of Information technology & Electronic Engineering 2016年第5期17卷 422-434页

作者： Chu-hua HUANG Dong-ming LU Chang-yu DIAO college of computer science and technology Zhejiang University college of computer science and technology Guizhou University Academy of Cultural Heritage Zhejiang University

To speed up the reconstruction of 3D dynamic scenes in an ordinary hardware platform, we propose an efficient framework to reconstruct 3D dynamic objects using a multiscale-contour-based interpolation from multi-view videos. Our framework takes full advantage of spatio-temporal-contour consistency. It exploits the property to interpolate single contours, two neighboring contours which belong to the same model, and two contours which belong to the same view at different times, corresponding to point-, contour-, and model-level interpolations, respectively. The framework formulates the interpolation of two models as point cloud transport rather than non-rigid surface deformation. Our framework speeds up the reconstruction of a dynamic scene while improving the accuracy of point-pairing which is used to perform the interpolation. We obtain a higher frame rate, spatio-temporal-coherence, and a quasi-dense point cloud sequence with color information. Experiments with real data were conducted to test the efficiency of the framework.

关键词： Multi-view video Free-viewpoint video Point-pair Multiscale-contour-based interpolation Spatio-temporal-contour Consistency Time-varying point cloud sequence

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STDNet: A Spatio-Temporal Decomposition Neural Network for Multivariate Time Series Forecasting

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Tsinghua science and technology 2024年第4期29卷 1232-1247页

作者： Zhuolun Jiang Zefei Ning Hao Miao Li Wang college of computer science and technology(college of Data science) Taiyuan University of TechnologyJinzhong 030600China

Long-term multivariate time series forecasting is an important task in engineering applications. It helps grasp the future development trend of data in real-time, which is of great significance for a wide variety of fields. Due to the non-linear and unstable characteristics of multivariate time series, the existing methods encounter difficulties in analyzing complex high-dimensional data and capturing latent relationships between multivariates in time series, thus affecting the performance of long-term prediction. In this paper, we propose a novel time series forecasting model based on multilayer perceptron that combines spatio-temporal decomposition and doubly residual stacking, namely Spatio-Temporal Decomposition Neural Network (STDNet). We decompose the originally complex and unstable time series into two parts, temporal term and spatial term. We design temporal module based on auto-correlation mechanism to discover temporal dependencies at the sub-series level, and spatial module based on convolutional neural network and self-attention mechanism to integrate multivariate information from two dimensions, global and local, respectively. Then we integrate the results obtained from the different modules to get the final forecast. Extensive experiments on four real-world datasets show that STDNet significantly outperforms other state-of-the-art methods, which provides an effective solution for long-term time series forecasting.

关键词： time series forecasting multivariate time series spatio-temporal decomposition

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A sensor transaction scheduling algorithm for maintaining real-time data temporal validity

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Journal of Central South University 2011年第6期18卷 2068-2073页

作者：白天李国徽刘云生 college of computer science and technology Huazhong University of Science and Technology

A new scheduling algorithm called deferrable scheduling with time slice exchange (DS-EXC) was proposed to maintain the temporal validity of real-time data. In DS-EXC, the time slice exchange method was designed to further defer the release time of transaction instances derived by the deferrable scheduling algorithm (DS-FP). In this way, more CPU time would be left for lower priority transactions and other transactions. In order to minimize the scheduling overhead, an off-line scheme was designed. In particular, the schedule for a transaction set is generated off-line until a repeating pattern is found, and then the pattern is used to construct the schedule on-line. The performance of DS-EXC was evaluated by sets of experiments. The results show that DS-EXC outperforms DS-FP in terms of increasing schedulable ratio. It also provides better performance under mixed workloads.

关键词： temporal validity real-time database sensor transaction

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Metrics in Sharing Video Relationship-Networks

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Chinese Journal of Electronics 2014年第3期23卷 598-603页

作者： GAO Wen QIAN Yaguan WU Chunming college of computer science & technology Zhejiang University college of science Zhejiang University of Science and Technology

At present the video sharing service has gradually became one of the Internet killer applications. It is crucial to the service providers that understand the intrinsic nature of Sharing video relationship-networks(SVRNs) formed by video related list. This paper investigates the relationships between sharing videos using complex networks theory. New metrics are introduced to model and characterize the SVRN from topological view. Through extensive study on You Tube, a set of key findings are revealed. The results show that the node indegree of SVRNs follows the power-law distribution and its entropy remains stable over time. The topology also exhibits an assortative property and obvious clustering phenomenon. But the rich-club phenomenon is not evident compared with the Internet AS-level topology. This research will enable the service providers to optimally plan and operate their video-based services.

关键词： Video sharing services Video relationship-networks Topological characteristics Complex networks

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Visual salience guided feature-aware shape simplification

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Journal of Zhejiang University-science C(computers and Electronics) 2014年第9期15卷 744-753页

作者： Yong-wei MIAO Fei-xia HU Min-yan CHEN Zhen LIU Hua-hao SHOU college of computer science and technology Zhejiang University of Technology college of science Zhejiang University of Technology

In the area of 3D digital engineering and 3D digital geometry processing, shape simplification is an important task to reduce their requirement of large memory and high time complexity. By incorporating the content-aware visual salience measure of a polygonal mesh into simplification operation, a novel feature-aware shape simplification approach is presented in this paper. Owing to the robust extraction of relief heights on 3D highly detailed meshes, our visual salience measure is defined by a center-surround operator on Gaussian-weighted relief heights in a scale-dependent manner. Guided by our visual salience map, the feature-aware shape simplification algorithm can be performed by weighting the high-dimensional feature space quadric error metric of vertex pair contractions with the weight map derived from our visual salience map. The weighted quadric error metric is calculated in a six-dimensional feature space by combining the position and normal information of mesh vertices. Experimental results demonstrate that our visual salience guided shape simplification scheme can adaptively and effectively re-sample the underlying models in a feature-aware manner, which can account for the visually salient features of the complex shapes and thus yield better visual fidelity.

关键词： Visual salience Shape simplification Content-aware Weighted quadric error metric Feature-aware

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通过低浓度混合有机二硒化物和有机二碲化物有序串联促进安时级高能量密度锂硫电池中的硫氧化还原动力学（英文）

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science China Materials 2025年第1期 207-216页

作者：周江奇舒程勇张千玉唐伟吴宇平 School of Chemical Engineering and technology Xi'an Jiaotong University School of Chemical Engineering Kunming University of Science and Technology college of Materials science and Engineering Sichuan University School of Energy and Environment Southeast University

均相氧化还原介质可以有效缓解多硫化锂在锂硫电池中的穿梭效应和缓慢的氧化还原动力学,但由于多硫化锂的多步转化需要串联催化的多功能活性位点,因此无法实现多硫化物锂的完美性能.基于氧化还原共介导原理,本文提出了一种混合有机二硒...

均相氧化还原介质可以有效缓解多硫化锂在锂硫电池中的穿梭效应和缓慢的氧化还原动力学,但由于多硫化锂的多步转化需要串联催化的多功能活性位点,因此无法实现多硫化物锂的完美性能.基于氧化还原共介导原理,本文提出了一种混合有机二硒化物和有机二碲化物（混合-Se/Te）的促进剂,以诱导串联催化并提升多硫化锂的有效电化学转化.具体而言,二苯二硒化物促进了多硫化锂与硫之间的固-液和液-液转化,而二苯二碲化物则改善了硫化锂沉积的固-液转化.因此,即使在6.5 mg cm-2的高硫负载和5.88μL mg-1的低电解液/硫比下,10 mM的低浓度混合-Se/Te促进剂也提供了6.6 mAh cm-2的高放电容量和在0.5 C下4.1 mAh cm-2的良好倍率性能.此外,组装的1.5 Ah级锂硫软包电池在0.05 C时提供了332 Wh kg-1的能量密度和良好的循环稳定性.我们的研究展示了利用分离活性位点推动连续硫转化反应的适用性，并预计将激发针对能量相关氧还原反应的动力学促进剂的深度分子设计.

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