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arXiv 2025年

作者： Riechers, Keno Morr, Andreas Lehnertz, Klaus Lind, Pedro G. Boers, Niklas Witthaut, Dirk Gorjão, Leonardo Rydin Climate Physics Max Planck Institute for Meteorology Germany Earth System Modelling School of Engineering & Design Technical University of Munich Germany Research Domain IV – Complexity Science Potsdam Institute for Climate Impact Research Potsdam14473 Germany Department of Epileptology University of Bonn Medical Center Bonn53105 Germany Helmholtz Institute for Radiation and Nuclear Physics University of Bonn Bonn53115 Germany Interdisciplinary Centre for Complex Systems University of Bonn Bonn53175 Germany Department of Computer Science OsloMet – Oslo Metropolitan University Oslo0130 Norway OsloMet Artificial Intelligence lab OsloMet Oslo0166 Norway Global Systems Institute Department of Mathematics University of Exeter United Kingdom Jülich52428 Germany Institute for Theoretical Physics University of Cologne Köln50937 Germany Faculty of Science and Technology Norwegian University of Life Sciences Ås1432 Norway

Paleoclimate proxy records from Greenland ice cores, archiving e.g. δ18O as a proxy for surface temperature, show that sudden climatic shifts called Dansgaard–Oeschger events (DO) occurred repeatedly during the last glacial interval. They comprised substantial warming of the Arctic region from cold to milder conditions. Concomitant abrupt changes in the dust concentrations of the same ice cores suggest that sudden reorganisations of the hemispheric-scale atmospheric circulation have accompanied the warming events. Genuine bistability of the North Atlantic climate system is commonly hypothesised to explain the existence of stadial (cold) and interstadial (milder) periods in Greenland. However, the physical mechanisms that drove abrupt transitions from the stadial to the interstadial state, and more gradual yet still abrupt reverse transitions, remain debated. Here, we conduct a one-dimensional data-driven analysis of the Greenland temperature and atmospheric circulation proxies under the purview of stochastic processes. We take the Kramers–Moyal equation to estimate each proxy’s drift and diffusion terms within a Markovian model framework. We then assess noise contributions beyond Gaussian white noise. The resulting stochastic differential equation (SDE) models feature a monostable drift for the Greenland temperature proxy and a bistable one for the atmospheric circulation proxy. Indicators of discontinuity in stochastic processes suggest to include higher-order terms of the Kramers–Moyal equation when modelling the Greenland temperature proxy’s evolution. This constitutes a qualitative difference in the characteristics of the two time series, which should be further investigated from the standpoint of climate dynamics. © 2025, CC BY-NC-SA.

关键词： Stochastic systems

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A Temperature Ratio Heat Pulse (Trhp) Method for Measuring Sap Flow

SSRN

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SSRN 2022年

作者： Ma, Yuchen Ren, Ruiqi Fu, Han Si, Bingcheng Kinar, Nicholas J. Kamai, Tamir Steppe, Kathy College of Resources and Environmental Engineering Ludong University Yantai264025 China Department of Soil Science University of Saskatchewan SaskatoonSKS7N 5A8 Canada Global Institute for Water Security Centre for Hydrology Smart Water Systems Lab University of Saskatchewan Canada Institute of Soil Water and Environmental Sciences Agricultural Research Organization Volcani Institute Rishon LeZion Israel Laboratory of Plant Ecology Department of Plants and Crops Faculty of Bioscience Engineering Ghent University Coupure links 653 Gent9000 Belgium

The compensation heat pulse (CHP) method has a limited measurement range and can often underestimate daily transpiration in plants. A temperature ratio heat pulse (TRHP) method is proposed for extending the measurement range of the CHP method to low and reverse sap flows. The TRHP method with CHP configuration for sap flow measurements follows advances made using this method for measuring soil flux density, by utilizing the ratio of temperature changes associated with downstream and upstream probes (∆ T down /∆ T up ). Sand column experiments show that the TRHP method successfully measures low and reverse flows, and the reverse sap flux density can be measured as low as -10.4 cm 3 cm -2 h -1 . Compared to field deployments involving the traditional CHP method, the TRHP method described in this paper can more accurately monitor nocturnal sap flow. This study thereby extends the capabilities of the sap flow method, and provides for measuring low and reverse sap flows that could be applied in the context of monitoring plant species where low and reverse sap flows are prevalent. © 2022, The Authors. All rights reserved.

关键词： Flow measurement

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A perspective on meta-boundaries

arXiv

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arXiv 2022年

作者： Zhang, Xinyan Chen, Jialin Chen, Ruoxi Wang, Chan Cai, Tong Chen, Hongsheng Lin, Xiao Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa32000 Israel Air and Missile Defense College Air Force Engineering University Xi’an710051 China

The judicious design of electromagnetic boundary provides a crucial route to control light-matter interactions, and it is thus fundamental to basic science and practical applications. General design approaches rely on the manipulation of bulk properties of superstrate or substrate and on the modification of boundary geometries. Due to the recent advent of metasurfaces and low-dimensional materials, the boundary can be flexibly featured with a surface conductivity, which can be rather complex but provide an extra degree of freedom to regulate the propagation of light. In this perspective, we denote the boundary with a non-zero surface conductivity as the meta-boundary. The meta-boundaries are categorized into four types, namely isotropic, anisotropic, biisotropic and bianisotropic meta-boundaries, according to the electromagnetic boundary conditions. Accordingly, the latest development for these four kinds of meta-boundaries are reviewed. Finally, an outlook on the research tendency of meta-boundaries is provided, particularly on the manipulation of light-matter interactions by simultaneously exploiting meta-boundaries and metamaterials. © 2022, CC BY.

关键词： Degrees of freedom (mechanics)

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Bearing-Only Formation Control of Multi-Agent System Without Leader’s Velocity Information ⁎

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IFAC-PapersOnLine 2020年第2期53卷 11044-11049页

作者： Hongyu Ji Quan Yuan Cong Li Xiang Li Adaptive Networks and Control Lab Electronic Engineering Department Fudan University Shanghai 200433 China Research Center of Smart Networks and Systems School of Information Science and Engineering Fudan University MOE Frontiers Center for Brain Science Institute of Brain Science Fudan University

This paper studies formation control of multi-agent systems with an underlying network constructed by defined the follower Henneberg construction. We propose a bearing-only formation control law of multi-agent systems, where a leader moves at a constant velocity, and the followers are unaware of the leader’s velocity. We prove that the system can asymptotically reach its desired position and form the target formation. The proposed control law scales the formation to avoid obstacles, where the formation robustness is also analysed. Numerical simulations are provided to further support our findings.

关键词： Formation control bearing-only multi-agent systems

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External-memory Dictionaries in the Affine and PDAM Models

External-memory Dictionaries in the Affine and PDAM Models

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作者： Bender, Michael A. Conway, Alex Farach-Colton, Martín Jannen, William Jiao, Yizheng Johnson, Rob Knorr, Eric McAllister, Sara Mukherjee, Nirjhar Pandey, Prashant Porter, Donald E. Yuan, Jun Zhan, Yang Department of Computer Science Stony Brook University Stony BrookNY11794-2424 United States VMware Research 3425 Hillview Avenue Palo AltoCA94304 United States Department of Computer Science Rutgers University PiscatawayNJ08855 United States Department of Computer Science Williams College 47 Lab Campus Drive WilliamstownMA01276 United States Department of Computer Science University of North Carolina at Chapel Hill Campus Box 3175 Brooks Computer Science Building Chapel HillNC27599-3175 United States School of Engineering and Applied Sciences Harvard University Science and Engineering Complex 150Western Avenue BostonMA02134 United States Computer Science Department Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213-3891 United States Lawrence Berkeley National Lab University of California Berkeley 1 Cyclotron Road BerkeleyCA94720 United States Seidenberg School of Computer Science and Information Systems Pace University One Pace Plaza New YorkNY10038-2613 United States Brooks Computer Science Building University of North Carolina at Chapel Hill 201 S. Columbia Street Chapel HillNC27599-3175 United States

Storage devices have complex performance profiles, including costs to initiate IOs (e.g., seek times in hard drives), parallelism and bank conflicts (in SSDs), costs to transfer data, and firmware-internal *** Disk-access Machine (DAM) model simplifies reality by assuming that storage devices transfer data in blocks of size B and that all transfers have unit cost. Despite its simplifications, the DAM model is reasonably accurate. In fact, if B is set to the half-bandwidth point, where the latency and bandwidth of the hardware are equal, then the DAM approximates the IO cost on any hardware to within a factor of ***, the DAM model explains the popularity of B-trees in the 1970s and the current popularity of BI -trees and log-structured merge trees. But it fails to explain why some B-trees use small nodes, whereas all BI -trees use large nodes. In a DAM, all IOs, and hence all nodes, are the same *** this article, we show that the affine and PDAM models, which are small refinements of the DAM model, yield a surprisingly large improvement in predictability without sacrificing ease of use. We present benchmarks on a large collection of storage devices showing that the affine and PDAM models give good approximations of the performance characteristics of hard drives and SSDs, *** show that the affine model explains node-size choices in B-trees and BI -trees. Furthermore, the models predict that B-trees are highly sensitive to variations in the node size, whereas BI -trees are much less sensitive. These predictions are born out ***, we show that in both the affine and PDAM models, it pays to organize data structures to exploit varying IO size. In the affine model, BI -trees can be optimized so that all operations are simultaneously optimal, even up to lower-order terms. In the PDAM model, BI -trees (or B-trees) can be organized so that both sequential and concurrent workloads are handled *** conclude that the

关键词： Bandwidth

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Challenges and Opportunities in Open Data Collaboration – a focus group study

Challenges and Opportunities in Open Data Collaboration – a...

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Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Per Runeson Thomas Olsson Dept. of Computer Science Lund University Lund Sweden Software and Systems Engineering Lab RISE Research Institutes of Sweden Lund Sweden

ISBN: (数字)9781728195322

ISBN: (纸本)9781728195339

Data-driven software is becoming prevalent, especially with the advent of machine learning and artificial intelligence. With data-driven systems come both challenges - to keep collecting and maintaining high quality data - and opportunities - open innovation by sharing data with others. We propose Open Data Collaboration (ODC) to describe pecuniary and non-pecuniary sharing of open data, similar to Open Source Software (OSS) and in contrast to Open Government Data (OGD), where public authorities share data. To understand challenges and opportunities with ODC, we organized five focus groups with in total 27 practitioners from 22 companies, public organizations, and research institutes. In the discussions, we observed a general interest in the subject, both from private companies and public authorities. We also noticed similarities in attitudes to open innovation practices, i.e. initial resistance which gradually turned into interest. While several of the participants were experienced in open source software, no had shared data openly. Based on the findings, we identify challenges which we set out to continue addressing in future research.

关键词： Organizations Technological innovation Ecosystems Conferences Software Collaboration Government

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Dual-Consistency semi-supervised learning with uncertainty quantification for covid-19 lesion segmentation from CT images

arXiv

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arXiv 2021年

作者： Li, Yanwen Luo, Luyang Lin, Huangjing Chen, Hao Heng, Pheng-Ann Imsight AI Research Lab Shenzhen China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

The novel coronavirus disease 2019 (COVID-19) characterized by atypical pneumonia has caused millions of deaths worldwide. Automatically segmenting lesions from chest Computed Tomography (CT) is a promising way to assist doctors in COVID-19 screening, treatment planning, and follow-up monitoring. However, voxel-wise annotations are extremely expert-demanding and scarce, especially when it comes to novel diseases, while an abundance of unlabeled data could be available. To tackle the challenge of limited annotations, in this paper, we propose an uncertainty-guided dual-consistency learning network (UDC-Net) for semi-supervised COVID-19 lesion segmentation from CT images. Specifically, we present a dual-consistency learning scheme that simultaneously imposes image transformation equivalence and feature perturbation invariance to effectively harness the knowledge from unlabeled data. We then quantify the segmentation uncertainty in two forms and employ them together to guide the consistency regularization for more reliable unsupervised learning. Extensive experiments showed that our proposed UDC-Net improves the fully supervised method by 6.3% in Dice and outperforms other competitive semi-supervised approaches by significant margins, demonstrating high potential in real-world clinical practice. 2 © 2021, CC BY-NC-ND.

关键词： Coronavirus

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Task-wise Sampling Convolutions for Arbitrary Oriented Object Detection in Aerial Images

arXiv

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arXiv 2022年

作者： Huang, Zhanchao Li, Wei Xia, Xiang-Gen Wang, Hao Tao, Ran The Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education The Academy of Digital China China Fuzhou University Fuzhou350108 China The National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology Fuzhou University Fuzhou350108 China The School of Information and Electronics Beijing Institute of Technology Beijing Key Lab of Fractional Signals and Systems Beijing100081 China The Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States

Arbitrary-oriented object detection (AOOD) has been widely applied to locate and classify objects with diverse orientations in remote sensing images. However, the inconsistent features for the localization and classification tasks in AOOD models may lead to ambiguity and low-quality object predictions, which constrains the detection performance. In this paper, an AOOD method called task-wise sampling convolutions (TS-Conv) is proposed. TS-Conv adaptively samples task-wise features from respective sensitive regions and maps these features together in alignment to guide a dynamic label assignment for better predictions. Specifically, sampling positions of the localization convolution in TS-Conv is supervised by the oriented bounding box (OBB) prediction associated with spatial coordinates. While sampling positions and convolutional kernel of the classification convolution are designed to be adaptively adjusted according to different orientations for improving the orientation robustness of features. Furthermore, a dynamic task-aware label assignment (DTLA) strategy is developed to select optimal candidate positions and assign labels dynamicly according to ranked task-aware scores obtained from TS-Conv. Extensive experiments on several public datasets covering multiple scenes, multimodal images, and multiple categories of objects demonstrate the effectiveness, scalability and superior performance of the proposed TS-Conv. © 2022, CC BY-NC-ND.

关键词： Convolution

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OXnet: Deep omni-supervised thoracic disease detection from chest X-rays

arXiv

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arXiv 2021年

作者： Luo, Luyang Chen, Hao Zhou, Yanning Lin, Huangjing Heng, Pheng-Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Imsight AI Research Lab Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Chest X-ray (CXR) is the most typical diagnostic X-ray examination for screening various thoracic diseases. Automatically localizing lesions from CXR is promising for alleviating radiologists' reading burden. However, CXR datasets are often with massive image-level annotations and scarce lesion-level annotations, and more often, without annotations. Thus far, unifying different supervision granularities to develop thoracic disease detection algorithms has not been comprehensively addressed. In this paper, we present OXnet, the first deep omni-supervised thoracic disease detection network to our best knowledge that uses as much available supervision as possible for CXR diagnosis. We first introduce supervised learning via a one-stage detection model. Then, we inject a global classification head to the detection model and propose dual attention alignment to guide the global gradient to the local detection branch, which enables learning lesion detection from image-level annotations. We also impose intra-class compactness and inter-class separability with global prototype alignment to further enhance the global information learning. Moreover, we leverage a soft focal loss to distill the soft pseudo-labels of unlabeled data generated by a teacher model. Extensive experiments on a large-scale chest X-ray dataset show the proposed OXnet outperforms competitive methods with significant margins. Further, we investigate omni-supervision under various annotation granularities and corroborate OXnet is a promising choice to mitigate the plight of annotation shortage for medical image diagnosis.2 © 2021, CC BY-NC-ND.

关键词： Deep learning

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Inferring FOLLOW Relationship from Repost Relationship between Users on Sina Weibo

引用

IFAC-PapersOnLine 2020年第2期53卷 2874-2879页

作者： Xu Hao Xiang Li Adaptive Networks and Control Lab Department of Electronic Engineering and Research Center of Smart Networks and Systems School of Information Science and Engineering Fudan University Shanghai 200433 China MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai 200433 China

In recent years, online social platforms such as sina weibo have been playing an increasingly important role in our lives. With the improvement of public awareness of privacy protection, however, it is increasingly difficult to obtain exhaustive direct data of FOLLOW relationship between users, which restricts the analysis and research on real online social networks. In the context of incomplete disclosure of information, we have to consider inferring from limited public data to more unknown information before further analysis and research with network topology. To overcome this obstacle, we try to recover the FOLLOW relationship by repost relationship. We collect repost data of six different bloggers on sina weibo to generate six independent networks, and propose an effective method to recover FOLLOW relationship between users. Our method is superior to other existing methods, and helps us draw a conclusion that two users establishing an indirect repost relationship with other two users, compared to other indirect relationship, are of greater possibility to maintain the FOLLOW relationship. At the same time, we also extend our method to greatly improve the recovering accuracy.

关键词： Network inference Sina weibo data protection

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