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arXiv 2019年

作者： Xu, Kai Wen, Longyin Li, Guorong Bo, Liefeng Huang, Qingming School of Computer Science and Technology UCAS Beijing China JD Digits Mountain View CA United States Key Laboratory of Big Data Mining and Knowledge Management CAS Beijing China Inst. of Computi. Tech. CAS China

In this paper, we present a unified, end-to-end trainable spatiotemporal CNN model for VOS, which consists of two branches, i.e., the temporal coherence branch and the spatial segmentation branch. Specifically, the temporal coherence branch pretrained in an adversarial fashion from unlabeled video data, is designed to capture the dynamic appearance and motion cues of video sequences to guide object segmentation. The spatial segmentation branch focuses on segmenting objects accurately based on the learned appearance and motion cues. To obtain accurate segmentation results, we design a coarse-to-fine process to sequentially apply a designed attention module on multi-scale feature maps, and concatenate them to produce the final prediction. In this way, the spatial segmentation branch is enforced to gradually concentrate on object regions. These two branches are jointly fine-tuned on video segmentation sequences in an end-to-end manner. Several experiments are carried out on three challenging datasets (i.e., DAVIS2016, DAVIS-2017 and Youtube-Object) to show that our method achieves favorable performance against the stateof-the-arts. Code is available at https://***/longyin880815/STCNN. Copyright © 2019, The Authors. All rights reserved.

关键词： Video recording

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Fair electronic voting via bitcoin deposits 5th

Fair electronic voting via bitcoin deposits

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5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Wu, Xijuan Wei, Baodian Tian, Haibo Du, Yusong Ma, Xiao School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Information Security Technology Guangzhou China Chongqing Key Lab of Computer Network and Communication Technology Chongqing China

ISBN: (纸本)9789811308956

Bitcoin is the most popular decentralized digital currency now in use. Block chain is the basic technology of Bitcoin, providing a trustable ledger that can be publicly verified. Research on distributed applications based on block chain has become a new trend. We propose an electronic voting scheme based on block chain and prime numbers, which can support voting situations for multiple candidates. We design protocols for the Bitcoin voting situation, in which there are n voters and k candidates. Each voter will vote for one candidate. The proposed protocols could guarantee that the candidate who gets the majority voting wins the game and no individual voting information is disclosed. Due to the nature of the block chain, the voting results could not be tampered. It is transparent since the block chain is open to the public for verification. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Deposits

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Equivalence of f ( Q ) cosmology with quintom-like scenario: The phantom field as effective realization of the non-trivial connection

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Physics Letters B 2025年 868卷

作者： Spyros Basilakos Andronikos Paliathanasis Emmanuel N. Saridakis National Observatory of Athens Lofos Nymfon 11852 Athens Greece Academy of Athens Research Center for Astronomy and Applied Mathematics Soranou Efesiou 4 11527 Athens Greece School of Sciences European University Cyprus Diogenes Street Engomi 1516 Nicosia Cyprus Department of Mathematics Faculty of Applied Sciences Durban University of Technology Durban 4000 South Africa School for Data Science and Computational Thinking Stellenbosch University 44 Banghoek Rd Stellenbosch 7600 South Africa Departamento de Matemáticas Universidad Católica del Norte Avda. Angamos 0610 Casilla 1280 Antofagasta Chile National Institute for Theoretical and Computational Sciences (NITheCS) Stellenbosch South Africa CAS Key Laboratory for Researches in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Hefei Anhui 230026 PR China

We show that f ( Q ) cosmology with a non-trivial connection, namely the Connection II of the literature, is dynamically equivalent with a quintom-like model. In particular, we show that the scalar field arising from the non-linear f ( Q ) form, and the scalar field associated to the non-trivial connection, are combined to provide one canonical and one phantom field in the minisuperspace Lagrangian. Hence, the combination of two well-behaved fields appears effectively as a phantom field. This is fundamentally different from the usual approach in phantom and quintom cosmology, in which the phantom field is introduced ad hoc, and thus it may open a new way to handle the phantom fields, namely as effective realizations of the connection-related canonical fields.

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Highly Selective Electrocatalytic Olefin Hydrogenation in Aqueous Solution

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Angewandte Chemie 2023年第41期135卷

作者： Chengyu Xing Prof. Yurui Xue Xuchen Zheng Dr. Yang Gao Siao Chen Prof. Yuliang Li Beijing Advanced Innovation Centre for Soft Matter Science and Engineering Beijing University of Chemical Technology Beijing 100029 P. R. China CAS Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences Beijing 100190 P. R. China Contribution: Data curation (lead) Formal analysis (lead) Methodology (lead) Validation (lead) Writing - original draft (equal) Shandong Provincial Key Laboratory for Science of Material Creation and Energy Conversion Science Center for Material Creation and Energy Conversion Science School of Chemistry and Chemical Engineering Shandong University Jinan 250100 P. R. China Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Methodology (lead) Supervision (lead) Writing - original draft (lead) University of Chinese Academy of Sciences Beijing 100190 P. R. China Contribution: Formal analysis (lead) Methodology (lead) Contribution: Formal analysis (equal) Methodology (equal)

Selective hydrogenation of olefins with water as the hydrogen source at ambient conditions is still a big challenge in the field of catalysis. Herein, the electrocatalytic hydrogenation of purely aliphatic and functionalized olefins was achieved by using graphdiyne based copper oxide quantum dots (Cu x O/GDY) as cathodic electrodes and water as the hydrogen source, with high activity and selectivity in aqueous solution at high current density under ambient temperature and pressure. In particular, the sp-/sp 2 -hybridized graphdiyne catalyst allows the selective hydrogenation of cis-trans isomeric olefins. The chemical and electronic structure of the GDY results in the incomplete charge transfer between GDY and Cu atoms to optimize the adsorption/desorption of the reaction intermediates and results in high reaction selectivity and activity for hydrogenation reactions.

关键词： Atomic Active Sites Electrocatalysis Graphdiyne Highly Selectivity Hydrogenation

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MQGrad: Reinforcement learning of gradient quantization in parameter server

arXiv

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arXiv 2018年

作者： Cui, Guoxin Xu, Jun Zeng, Wei Lan, Yanyan Guo, Jiafeng Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of ComputingTechnology Chinese Academy of Sciences Beijing100190 China

One of the most significant bottleneck in training large scale machine learning models on parameter server (PS) is the communication overhead, because it needs to frequently exchange the model gradients between the workers and servers during the training iterations. Gradient quantization has been proposed as an effective approach to reducing the communication volume. One key issue in gradient quantization is setting the number of bits for quantizing the gradients. Small number of bits can significantly reduce the communication overhead while hurts the gradient accuracies, and vise versa. An ideal quantization method would dynamically balance the communication overhead and model accuracy, through adjusting the number bits according to the knowledge learned from the immediate past training iterations. Existing methods, however, quantize the gradients either with fixed number of bits, or with predefined heuristic rules. In this paper we propose a novel adaptive quantization method within the framework of reinforcement learning. The method, referred to as MQGrad, formalizes the selection of quantization bits as actions in a Markov decision process (MDP) where the MDP states records the information collected from the past optimization iterations (e.g., the sequence of the loss function values). During the training iterations of a machine learning algorithm, MQGrad continuously updates the MDP state according to the changes of the loss function. Based on the information, MDP learns to select the optimal actions (number of bits) to quantize the gradients. Experimental results based on a benchmark dataset showed that MQGrad can accelerate the learning of a large scale deep neural network while keeping its prediction accuracies. Copyright © 2018, The Authors. All rights reserved.

关键词： Markov processes

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Barrow and Tsallis entropies after the DESI DR2 BAO data

arXiv

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arXiv 2025年

作者： Luciano, Giuseppe Gaetano Paliathanasis, Andronikos Saridakis, Emmanuel N. Department of Chemistry Physics and Environmental and Soil Sciences Escola Politecnica Superior Universidad de Lleida Av. Jaume II 69 Lleida25001 Spain School for Data Science and Computational Thinking Stellenbosch University 44 Banghoek Rd Stellenbosch7600 South Africa Centre for Space Research North-West University Potchefstroom2520 South Africa Departamento de Matemàticas Universidad Catòlica del Norte Avda. Angamos 0610 Casilla Antofagasta1280 Chile National Observatory of Athens Lofos Nymfon 11852 Greece CAS Key Laboratory for Research in Galaxies and Cosmology School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Departamento de Matemáticas Universidad Católica del Norte Avda. Angamos 0610 Casilla Antofagasta1280 Chile

Modified cosmology based on Barrow entropy arises from the gravity–thermodynamics conjecture, in which the standard Bekenstein–Hawking entropy is replaced by the Barrow entropy of quantum-gravitational origin, characterized by the Barrow parameter ∆. Interestingly, this framework exhibits similarities with cosmology based on Tsallis δ-entropy, which, although rooted in a non-extensive generalization of Boltzmann–Gibbs statistics, features the same power-law deformation of the holographic scaling present in the Barrow case. We use observational data from Supernova Type Ia (SNIa), Cosmic Chronometers (CC), and Baryonic acoustic oscillations (BAO), including the recently released DESI DR2 data, in order to extract constraints on such scenarios. As we show, the best-fit value for the Barrow exponent ∆ is found to be negative, while the zero value, which corresponds to ΛCDM paradigm, is allowed only in the range of 2σ for three out of four datasets. Additionally, for the case of the SN0+OHD+BAO dataset, for the current Hubble function we obtain a value of H0 = 72.2+0−0.99, which offers an alleviation for the H0 tension. Finally, by applying information criteria such as the Akaike Information Criterion and the Bayes evidence, we compare the fitting efficiency of the scenario at hand with ΛCDM cosmology, showing that the latter is slightly favoured. © 2025, CC BY.

关键词： Dark Matter

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2025年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Department of Geography Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Geography South China Normal University Shipai Campus Guangzhou510631 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2025, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Structured Information Extraction of Pathology Reports with Attention-based Graph Convolutional network

Structured Information Extraction of Pathology Reports with ...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jialun Wu Kaiwen Tang Haichuan Zhang Chunbao Wang Chen Li School of Computer Science and Technology Xi’an Jiaotong University Xi’an Shaanxi China National Engineering Lab for Big Data Analytics Xi’an Jiaotong University Xi’an Shaanxi China Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech.R&D Xi’an Jiaotong University Xi’an Shaanxi China School of Computer Science and Technology Qian Xuesen College Xi’an Jiaotong University Xi’an Shaanxi China the First Affiliated Hospital of Xi’an Jiaotong University Xi’an Shaanxi China

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Electronic medical data contains biochemical, imaging, pathological information during diagnosis and treatment. The pathology report is a kind of highly liberalized unstructured textual data, which is the basis and gold standard of cancer diagnosis and is very important for the prognosis and treatment of patients. The application of information extraction technology to pathological reports can obtain structured data that can be understood and analyzed by computers, helping pathologists make appropriate decisions. In this work, we proposed an attention-based graph convolutional network (GCN) for converting unstructured pathological reports into a structured form suitable for computer analysis to improve the current pathologist's workflow, collected medical data from different platforms, and provided more accurate assistance for diagnosis and treatment. We used pathology reports data from TCGA (The Cancer Genome Atlas) database with fine-grained annotations on 3632 pathology reports including four types of cancers. Our method performs better in our pathology report dataset with higher F1 score than traditional methods and deep learning methods. The results indicate that our method is robust, thus may work with other types of cancer pathology report.

关键词： Pathology Cancer Task analysis Annotations Information retrieval Medical diagnostic imaging data mining

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SELWasm: A Code Protection Mechanism for WebAssembly

SELWasm: A Code Protection Mechanism for WebAssembly

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IEEE International Conference on Big data and Cloud Computing (BdCloud)

作者： Jian Sun DingYuan Cao XiMing Liu ZiYi Zhao WenWen Wang XiaoLi Gong Jin Zhang College of Computer Science Nankai University Tianjin China College of Cyber Science Nankai University Tianjin China Department of Computer Science University of Georgia Athens GA USA Tianjin Key Laboratory of Network and Data Security Technology Tianjin China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

WebAssembly is a novel front-end programming technology that has been wildly supported by most web browsers. The high-level language can be compiled into WebAssembly binary code, and executed by the browser at almost native speed. With the help of WebAssembly, the complex business logic and algorithms can be integrated into the webpage and migrate the computation overhead to the browsers. However, due to the limit of browsers, it is very difficult for developers to ensure that the intellectual property embedded in the front-end code is well protected. Even though the WebAssembly code is a compiler-generated binary file, it is easy to obtain it from the website for reuse or reverse engineering. This paper proposed a new framework, SELWasm, to protect the WebAssembly code. In the framework, three major mechanisms are provided. The Environment Self-checking mechanism can protect the source code from illegally reusing by any unauthorized website. The Encryption&Decryption mechanism can protect the WebAssembly code from being distributed as plaintext. The Lazy-loading mechanism can improve the performance of page loading, mitigate the overhead introduced by the previous mechanisms. Comprehensive experiments are conducted to measure the effectiveness and efficiency of SELWasm. The results show that the behaviors considered from web attackers can be resisted and the overhead involved is negligible.

关键词： Browsers Encryption Servers Runtime Intellectual property Loading

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Seamless maps of major elements of the Moon: Results from high-resolution geostationary satellite

arXiv

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arXiv 2020年

作者： Lu, Yu Wu, Yun-Zhao Li, Cui Ma, Jin-Song Qi, Wen-Wen Tan, Wei Li, Xiao-Man Shi, Zhi-Cheng He, Hong-Yan Dai, Shu-Wu Li, Guo Liu, Feng-Jing Wang, Jing-Qiao Wang, Xiao-Yan Wang, Qi Meng, Ling-Jie Key Laboratory of Planetary Sciences Purple Mountain Observatory Chinese Academy of Sciences Nanjing210034 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China CAS Center for Excellence in Comparative Planetology Hefei230026 China Space Science Institute Macau University of Science and Technology China School of Geography and Ocean Science Nanjing University Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023 China Beijing Institute of Space Mechanics and Electricity Beijing China Beijing Institute of Spacecraft System Engineering Beijing China China Centre for Resources Satellite Data and Application Beijing China Earth Observation System and Data Center China National Space Administration Beijing China

Major elements such as Fe, Ti, Mg, Al, Ca, and Si play very important roles in understanding the origin and evolution of the Moon. Previous maps of these major elements derived from orbital data are based on mosaic images or low-resolution Gamma ray data. The hue variations and gaps among orbital boundaries in the mosaic images are not conducive to geological studies. This paper aims to produce seamless and homogenous distribution maps of major elements using the single-exposure image of the whole lunar disk obtained by China's high-resolution geostationary satellite, Gaofen-4, with a spatial resolution of ~500 m. The elemental contents of soil samples returned by Apollo and Luna missions were used as ground truth, and were correlated with the reflectance of the sampling sites extracted from Gaofen-4 data. The final distribution maps of these major oxides are generated with the statistical regression model. With these products the average contents and proportions of the major elements for maria and highlands were estimated and compared. The results showed that SiO2 and TiO2 have the highest and lowest fractions in mare and highland areas, respectively. Besides, the relative concentrations of these elements could serve as indicators of geologic processes, e.g., the obviously asymmetric distributions of Al2O3, CaO, and SiO2 around Tycho crater may suggest that Tycho crater was formed by an oblique impact from the southwest direction. Copyright © 2020, The Authors. All rights reserved.

关键词： Silica

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