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Altered trends in carbon uptake in China's terrestrial ecosystems under the enhanced summer monsoon and warming hiatus

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National science Review 2019年第3期6卷 505-514页

作者： Honglin He Shaoqiang Wang Li Zhang Junbang Wang Xiaoli Ren Lei Zhou Shilong Piao Hao Yan Weimin Ju Fengxue Gu Shiyong Yu Yuanhe Yang Miaomiao Wang Zhongen Niu Rong Ge Huimin Yan Mei Huang Guoyi Zhou Yongfei Bai Zongqiang Xie Zhiyao Tang Bingfang Wu Leiming Zhang Nianpeng He Qiufeng Wang Guirui Yu Synthesis Research Center of China's Ecosystem Research Network Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences College of Resources and Environment University of Chinese Academy of Sciences Sino-French Institute for Earth System Science College of Urban and Environment Sciences Peking University Key Laboratory of Alpine Ecology and Biodiversity Institute of Tibetan Plateau Research CAS Center for Excellence in Tibetan Plateau Earth Science Chinese Academy of Sciences National Meteorological Center China Meteorological Administration International Institute for Earth System Science and Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Nanjing University Key Laboratory of Dryland Agriculture MOA Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences School of Geography Geomatics and Planning Jiangsu Normal University State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical Garden Chinese Academy of Sciences Department of Ecology College of Urban and Environmental Science Key Laboratory for Earth Surface Processes of the Ministry of Education Peking University Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes. Over the past decade, China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming. However, the changes in the trends of terrestrial net ecosystem production（NEP） in China under climate changes are not well documented. Here, we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982–2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country. Our results revealed a decadal-scale shift in NEP from a downtrend of–5.95 TgC/yr2（reduced sink） during 1982–2000 to an uptrend of 14.22 TgC/yr2（enhanced sink） during 2000–10. This shift was essentially induced by the strengthened summer monsoon, which stimulated carbon uptake, and the warming hiatus, which lessened the decrease in the NEP trend. Compared to the contribution of 56.3% by the climate effect, atmospheric CO2concentration and nitrogen deposition had relatively small contributions（8.6 and 11.3%, respectively） to the shift. In conclusion, within the context of the global-warming hiatus, the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration. Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades, but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas.

关键词： climate change Asian summer monsoon warming hiatus biogeochemical modeling ecosystem carbon dynamics

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Sea-land Segmentation of Synthetic Aperture Radar Imagery Using Deep Neural network Models

Sea-land Segmentation of Synthetic Aperture Radar Imagery Us...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yinfei Zhou Gang Zheng Jingsong Yang Xiaofeng Li Bin Liu Jingliang Shao Han Jiang Ren Ren Peng Chen Lin Ren Bin Zhang Ocean College Zhejiang University Zhoushan China Ministry of Natural Resources State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Hangzhou China Chinese Academy of Sciences CAS Key Laboratory of Ocean Circulation and Waves Big Data Center Institute of Oceanology Qingdao China Chinese Academy of Sciences Center for Ocean Mega-Science Institute of Oceanology Qingdao China College of Marine Sciences Shanghai Ocean University Shanghai China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665409889

The waterline is the transient boundary between land and sea, and the waterline extraction is of great significance for coastal research and monitoring. Spaceborne synthetic aperture radar (SAR) has the ability to penetrate clouds and thus can image large coastal areas with high-resolution under all-weather and all-day conditions. These advantages make SAR well complement the waterline observations by optical satellites. However, SAR images of coastal areas usually have complex patterns because of the diverse topography and geomorphology, and the SAR-imaging mechanism also results in large coherent speckle noise in the images. The above poses challenges to the waterline extraction from SAR imagery. Traditional manual annotation is highly accurate, but is laborious and time-consuming. Therefore, a more efficient method is urgent. The procedure of waterline extraction is sea-land segmentation followed by boundary-extraction where accurate segmentation is critical. From the perspective of the computer vision, sea-land segmentation can be viewed as the image semantic segmentation task. In recent years, deep neural network (DNN) models have achieved great success in the semantic segmentation task. The U-Net, named for its U-shape architecture, is one of the most popular DNN models for the task. Compared with others, the U-Net has a lighter structure that efficiently extract and fuse the multi-scale image features. In this study, we applied the U-Net and its variants to sea-land segmentation and systematically investigated the models’ performances. All models can segment the sea and land efficiently, and the results are overall consistent with the manual annotation. Our study demonstrates the application potential of DNN technology in waterline monitoring from SAR imagery.

关键词： Deep learning Image segmentation Neural networks Semantics Sea measurements Manuals Radar polarimetry

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DeepkeyGen: A deep learning-based stream cipher generator for medical image encryption and decryption

arXiv

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arXiv 2020年

作者： Ding, Yi Tan, Fuyuan Qin, Zhen Cao, Mingsheng Choo, Kim-Kwang Raymond Qin, Zhiguang Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China ChengduSichuan610054 China Institute of Electronic and Information Engineering of UESTC in Guangdong Guangdong523808 China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China ChengduSichuan610054 China Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States

The need for medical image encryption is increasingly pronounced, for example to safeguard the privacy of the patients’ medical imaging data. In this paper, a novel deep learning-based key generation network (DeepkeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images. In DeepkeyGen, the generative adversarial network (GAN) is adopted as the learning network to generate the private key. Furthermore, the transformation domain (that represents the "style" of the private key to be generated) is designed to guide the learning network to realize the private key generation process. The goal of DeepkeyGen is to learn the mapping relationship of how to transfer the initial image to the private key. We evaluate DeepkeyGen using three datasets, namely: the Montgomery County chest X-ray dataset, the Ultrasonic Brachial Plexus dataset, and the BraTS18 dataset. The evaluation findings and security analysis show that the proposed key generation network can achieve a high-level security in generating the private key. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Species turnover drives grassland community to phylogenetic clustering over long-term grazing disturbance

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Journal of Plant Ecology 2020年第2期13卷 157-164页

作者： Juntao Zhu Yangjian Zhang Wenfeng Wang Xian Yang Ning Chen Ruonan Shen Li Wang Lin Jiang Lhasa Plateau Ecosystem Research Station Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of Biological Sciences Georgia Institute of TechnologyAtlantaGA 30332USA CAS Center for Excellence in Tibetan Plateau Earth Sciences Beijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China Tibet Academy of Agricultural and Animal Husbandry Science Lhasa 850032China Shenzhen Graduate School Peking UniversityShenzhen 518000China

Aims Grazing exerts profound effects on grassland ecosystem service and functions by regulating species composition and diversity,and structuring community assembly ***,adaptions of phylogenetic diversity and phylogenetic community structure to long-term grazing disturbance remain poorly studied,especially for ecosystems distributed in extreme *** Here,we conducted an experiment with multigrazing intensities to explore the impacts of grazing disturbance on plant phylogenetic diversity and community structure in an alpine grassland of the Tibetan *** Findings Grazing disturbance enriched plant species richness(SR),and stimulated species turnover from regional species pool,consequently changing community species *** low intensities,grazing exerted no obvious effects on phylogenetic diversity and community structure,whereas communities changed from overdispersion to clustering under high grazing *** grazing intensity resulted in stronger environmental filtering,which consequently selected those species with high resilience to grazing *** observed clustering structure was associated with the colonizing species which were closely related to resident species,and locally extinct species,and distantly related to *** the plant functional trait level,high grazing intensity increased species colonization largely by altering the effect of root depth on species colonization compared to light *** results highlight that solely utilization of SR and diversity cannot fully represent grassland communities responses to *** effects of species turnover on community phylogenetic diversity and structure are entailed to be explored in the future grazing studies.

关键词： alpine grassland grazing phylogenetic diversity phylogenetic community structure species richness

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Microfiber Assisted Bidirectional Wavelength-Locked Ultrafast Erbium-Doped Fiber Laser

SSRN

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SSRN 2022年

作者： Mou, Chengbo Dai, Lilong Huang, Zinan Huang, Qianqian AlAraimi, Mohammed Rozhin, Aleksey Liang, Xindong Key Lab of Specialty Fiber Optics and Optical Access Network Shanghai Institute for Advanced Communication and Data Science Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China Department of Engineering University of Technology and Applied Sciences Higher College of Tech-nology PO Box 74 Al-Khuwair Postal Code 133 Oman Aston Institute of Photonic Technologies Aston University BirminghamB4 7ET United Kingdom Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou Institute for Advanced Study UCAS Hangzhou310024 China Zhejiang Lab Hangzhou311100 China

Bidirectional mode-locked fiber lasers are promising media to implement intracavity phase interferometry (IPI) due to the ability to produce ultrashort pulses in a compact design. A typical bidirectional ultrafast fiber laser will generate counter-propagating pulses with different repetition rates due to the asymmetric constructure. In this paper, by using the filtering effect of microfiber, an asymmetric bidirectional fiber laser that emits two pulses with same operation wavelength is demonstrated. The utilization of microfiber in locking output wavelength from two directions may directly simplify the design of laser cavity suitable for IPI applications. Moreover, continuous wavelength tuning in a single-cavity bidirectional ultrafast fiber laser has been realized for the first time by applying strain on the microfiber. In the clockwise (CW) direction, wavelength tuning ranges from 1558.95 nm to 1567.3 nm and from 1558.93 nm to 1567.25 nm in the counter clockwise (CCW) direction. The counter-circulating pulses maintain spectral locking state during the whole wavelength tuning process with a good linear sensitivity of 0.2 nm/µm. Such features may further expand the scope and field of fiber lasers for sensing. © 2022, The Authors. All rights reserved.

关键词： Carbon nanotubes

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DAMIA: Leveraging domain adaptation as a defense against membership inference attacks

arXiv

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arXiv 2020年

作者： Huang, Hongwei Luo, Weiqi Zeng, Guoqiang Weng, Jian Zhang, Yue Yang, Anjia College of Informatin Science and Technology College of Cyber security National Joint Engineering Research Center of Network Security Detection and Protection Technology Guangdong Key Laboratory of Data Security and Privacy Preserving Jinan University Guangzhou510632 China

Deep Learning (DL) techniques allow one to train a model from a dataset, and the model can be adopted to solve tasks. DL has attracted much interest given its fancy performance and potential market value, while security issues are amongst the most colossal concerns. Being a core engine of DL, models may be prone to the membership inference attack, where an attacker determines whether a given sample is from the dataset the model trained on. Efforts have been made to hinder the attack but unfortunately, they may be subject to a major overhead or impaired usability. In this paper, we propose and implement DAMIA, leveraging Domain Adaptation (DA) as a defense to counter membership inference attacks. Our observation is that during the training process, DA obfuscates the dataset to be protected using another related dataset, and derives a model that underlyingly extracts the features from both the original dataset and the introduced dataset. Seeing that the model is obfuscated, membership inference fails, while the extracted common features provide supports for usability. Extensive experiments have been conducted, which validates our intuition. The model counters the membership inference attacks and has a negligible footprint to the usability. Our experiment also excludes a few factors that may hinder the performance of DAMIA, providing a potential guideline that instructs the vendors and researchers to benefit from our solution in a timely manner. Copyright © 2020, The Authors. All rights reserved.

关键词： network security

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引用

International Conference on networking and network Applications (NaNA)

作者： Zhongmin Wang Rui Zhou Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi'an Shaanxi China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an Shaanxi China

ISBN: (数字)9781728189543

ISBN: (纸本)9781728189550

The information interaction when the brain processes emotional activities is intricate. Therefore, it is very necessary for us to explore the mechanisms of the functional coordination of various brain regions. Recent studies have demonstrated that there are hub regions in the brain that are highly connected and highly central, and are responsible for coordinating dynamic interactions between brain regions. This study aims to construct the dynamic brain networks related to emotions and examine the structure of the hubs of these networks that reflect functional connectivity. In this paper, we demonstrate that a combination of network hubs set a closely connected collective called “rich-club”,which can be used as the core network architecture for identifying different emotions. According to the phase synchronization relationship of the Electroencephalogram (EEG) in three time periods to construct the corresponding brain networks in different sub-states, we found that the dynamic connection patterns produced by different emotions are different, which is manifested in the different rich-club organization. The discovery of rich-club structure related to emotions in this study is of great significance for studying the brain mechanisms behind human emotional processes.

关键词： Emotion recognition Organizations Color network architecture Electroencephalography Synchronization

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Distance variety preserving hashing for large-scale retrieval

Distance variety preserving hashing for large-scale retrieva...

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作者： Zhai, Sheping School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi'an710121 China

Hashing techniques have been seen huge adoption in large-scale retrieval owing to the computational and storage efficiencies of binary codes. However, the binary codes might not preserve the semantic similarity powerfully and lead to poor accuracy. To evade binary limitation but remain hashing superiority, this paper introduces a novel asymmetric hashing framework for distance variety preserving, which yields preferable performance via real-valued query and multi-valued database with shorter code length. Concretely, a binary sparse representation is proposed for multivalued database encoding to make computation and storage complexity tolerable. By exploiting the supervised information, we learn a projective matrix that project data onto a sub-space in which the similarity between realvalued query and multi-valued database can be measured. Due to the discrete constraints, for different discrete variables, we present different meticulous discrete solutions for their sub-problems. Exhaustive experiments on three multilabel datasets demonstrate our approach outperforms most state-of-the-art hashing methods. © 2018 John Wiley & Sons, Ltd.

关键词： database systems

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Roles of four feedback loops in mitochondrial permeability transition pore opening induced by Ca2+ and reactive oxygen species

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Physical Review E 2020年第6期102卷 062422-062422页

作者： Hong Qi Guoping Xu Xiao-Long Peng Xiang Li Jianwei Shuai Rui Xu Complex Systems Research Center Shanxi University Taiyuan 030006 China Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Shanxi University Taiyuan 030006 China Department of Physics College of Physical Science and Technology Xiamen University Xiamen 361005 China State Key Laboratory of Cellular Stress Biology Innovation Center for Cell Signaling Network Xiamen University Xiamen 361102 China National Institute for Data Science in Health and Medicine Xiamen University Xiamen 361102 China

Transient or sustained permeability transition pore (PTP) opening is important in normal physiology or cell death, respectively. These are closely linked to Ca2+ and reactive oxygen species (ROS). The entry of Ca2+ into mitochondria regulates ROS production, and both Ca2+ and ROS trigger PTP opening. In addition to this feedforward loop, there exist four feedback loops in the Ca2+-ROS-PTP system. ROS promotes Ca2+ entering (F1) and induces further ROS generation (F2), forming two positive feedback loops. PTP opening results in the efflux of Ca2+ (F3) and ROS (F4) from the mitochondria, forming two negative feedback loops. Owing to these complexities, we construct a mathematical model to dissect the roles of these feedback loops in the dynamics of PTP opening. The qualitative agreement between simulation results and recent experimental observations supports our hypothesis that under physiological conditions the PTP opens in an oscillatory state, while under pathological conditions it opens in a high steady state. We clarify that the negative feedback loops are responsible for producing oscillations, wherein F3 plays a more prominent role than F4; whereas the positive feedback loops are beneficial for maintaining oscillation robustness, wherein F1 has a more dominant role than F2. Furthermore, we manifest that the proper increase in negative feedback strength or decrease in positive feedback strength not only facilitates the occurrence of oscillations and thus protects the system against a high steady state, but also assists in lowering the oscillation peak. This study may provide potential therapeutic strategies in treating neurodegenerative diseases due to PTP dysfunction.

关键词： Bifurcations Calcium signaling Dynamical systems

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Real-time Semantic Segmentation via Spatial-detail Guided Context Propagation

arXiv

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arXiv 2020年

作者： Hao, Shijie Zhou, Yuan Guo, Yanrong Hong, Richang Cheng, Jun Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Chinese University of Hong Kong Hong Kong

Nowadays, vision-based computing tasks play an important role in various real-world applications. However, many vision computing tasks, e.g. semantic segmentation, are usually computationally expensive, posing a challenge to the computing systems that are resource-constrained but require fast response speed. Therefore, it is valuable to develop accurate and real-time vision processing models that only require limited computational resources. To this end, we propose the Spatial-detail Guided Context Propagation network (SGCPNet) for achieving real-time semantic segmentation. In SGCPNet, we propose the strategy of spatial-detail guided context propagation. It uses the spatial details of shallow layers to guide the propagation of the low-resolution global contexts, in which the lost spatial information can be effectively reconstructed. In this way, the need for maintaining high-resolution features along the network is freed, therefore largely improving the model efficiency. On the other hand, due to the effective reconstruction of spatial details, the segmentation accuracy can be still preserved. In the experiments, we validate the effectiveness and efficiency of the proposed SGCPNet model. On the Citysacpes dataset, for example, our SGCPNet achieves 69.5% mIoU segmentation accuracy, while its speed reaches 178.5 FPS on 768×1536 images on a GeForce GTX 1080 Ti GPU card. In addition, SGCPNet is very lightweight and only contains 0.61 M parameters. The code will be released at https://***/zhouyuan888888/SGCPNet. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

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