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Safety-efficiency trade-offs in the cotton xylem：acclimatization to different soil textures

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Journal of Arid Land 2016年第3期8卷 443-452页

作者： wang zhongyuan XIE Jiangbo LI Yan State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi 830011 China University of Chinese Academy of Sciences Beijing 100049 China

The acclimatization of plant xylem to altered environmental conditions has attracted considerable attention from researchers over several decades. Plants growing in natural environments must seek a balance between water uptake and the water loss of leaves from evaporation. Thus, the adaptation of xylem to different soil textures is important in maintaining plant water balance. In this study, we investigated the xylem changes of cotton（Gossypium herbaceum L.） xylem in sandy, clay and mixed soils. Results showed that soil texture had a significant effect on xylem vessel diameter and length of stems and roots. Compared with G. herbaceum growing in the clay soil, those plants growing in the sandy soil developed narrower and shorter xylem vessels in their roots, and had a higher percentage of narrow vessels in their stems. These changes resulted in a safer（i.e. less vulnerable to cavitation）, but less-efficient water transport system when soil water availability was low, supporting the hydraulic safety versus efficiency trade-off hypothesis. Furthermore, in sandy and mixed soils, the root： shoot ratio of G. herbaceum increased twofold, which ensures the same efficiency of leaves. In summary, our finding indicates that the morphological plasticity of xylem structure in G. herbaceum has a major role in the acclimatization of this plant species to different soil textures.

关键词： acclimatization soil texture xylem structure hydraulic acclimation safety vs. efficiency

An end-to-end network for co-saliency detection in one single image

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Science China(Information Sciences) 2023年第11期66卷 5-22页

作者： Yuanhao YUE Qin ZOU Hongkai YU Qian wang zhongyuan wang Song wang School of Cyber Science and Engineering Wuhan University School of Computer Science Wuhan University Department of Electrical Engineering and Computer Science Cleveland State University Department of Computer Science and Engineering University of South Carolina

Co-saliency detection within a single image is a common vision problem that has not yet been well addressed. Existing methods often used a bottom-up strategy to infer co-saliency in an image in which salient regions are firstly detected using visual primitives such as color and shape and then grouped and merged into a co-saliency map. However, co-saliency is intrinsically perceived complexly with bottom-up and top-down strategies combined in human vision. To address this problem, this study proposes a novel end-toend trainable network comprising a backbone net and two branch nets. The backbone net uses ground-truth masks as top-down guidance for saliency prediction, whereas the two branch nets construct triplet proposals for regional feature mapping and clustering, which drives the network to be bottom-up sensitive to co-salient regions. We construct a new dataset of 2019 natural images with co-saliency in each image to evaluate the proposed method. Experimental results show that the proposed method achieves state-of-the-art accuracy with a running speed of 28 fps.

关键词： saliency detection convolutional neural network regional feature mapping co-saliency detection deep learning

Multi-Attention Fusion and Fine-Grained Alignment for Bidirectional Image-Sentence Retrieval in Remote Sensing

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1532-1535页

作者： Qimin Cheng Yuzhuo Zhou Haiyan Huang zhongyuan wang School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China School of Computer Science Wuhan UniversityWuhan 430079China

Dear editor,Cross-modal retrieval in remote sensing(RS) data has inspired increasing enthusiasm due to its merit in flexible input and efficient query. In this letter, we address to establish semantic relationship bet... 详细信息

关键词： editor Remote Image

Robust Background Subtraction Method via Low-Rank and Structured Sparse Decomposition

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China Communications 2018年第7期15卷 156-167页

作者： Minsheng Ma Ruimin Hu Shihong Chen Jing Xiao zhongyuan wang National Engineering Research Center for Multimedia Software School of Computer ScienceWuhan UniversityWuhan 430072China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan UniversityWuhan 430072China Collaborative Innovation Center of Geospatial Technology Wuhan 430079China

Background subtraction is a challenging problem in surveillance scenes. Although the low-rank and sparse decomposition(LRSD) methods offer an appropriate framework for background modeling, they fail to account for image's local structure, which is favorable for this problem. Based on this, we propose a background subtraction method via low-rank and SILTP-based structured sparse decomposition, named LRSSD. In this method, a novel SILTP-inducing sparsity norm is introduced to enhance the structured presentation of the foreground region. As an assistance, saliency detection is employed to render a rough shape and location of foreground. The final refined foreground is decided jointly by sparse component and attention map. Experimental results on different datasets show its superiority over the competing methods, especially under noise and changing illumination scenarios.

关键词： background subtraction LRSD structured sparse SILTP

Action Recognition with Temporal Scale-Invariant Deep Learning Framework

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China Communications 2017年第2期14卷 163-172页

作者： Huafeng Chen Jun Chen Ruimin Hu Chen Chen zhongyuan wang State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China National Engineering Research Center for Multimedia Software Computer School of Wuhan University Wuhan 430072 China Center for Research in Computer Vision University of Central Florida Orlando FL 32816 USA

Recognizing actions according to video features is an important problem in a wide scope of applications. In this paper, we propose a temporal *** deep learning framework for action recognition, which is robust to the change of action speed. Specifically, a video is firstly split into several *** clips and a keyframe is selected from each *** clip. The spatial and motion features of the keyframe are extracted separately by two Convolutional Neural Networks(CNN) and combined in the convolutional fusion layer for learning the relationship between the features. Then, Long Short Term Memory(LSTM) networks are applied to the fused features to formulate *** temporal clues. Finally, the action prediction scores of the LSTM network are combined by linear weighted summation. Extensive experiments are conducted on two popular and challenging benchmarks, namely, the UCF.101 and the HMDB51 Human Actions. On both benchmarks, our framework achieves superior results over the *** methods by 93.7% on UCF.101 and 69.5% on HMDB51, respectively.

关键词： action recognition CNN LSTM

Microsoft Concept Graph:Mining Semantic Concepts for Short Text Understanding

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Data Intelligence 2019年第3期1卷 238-270页

作者： Lei Ji Yujing wang Botian Shi Dawei Zhang zhongyuan wang Jun Yan Microsoft Research Asia Haidian DistrictBeijing 100080China Institute of Computing Technology Chinese Academy of SciencesHaidian DistrictBeijing 100049China Beijing Institute of Technology Haidian DistrictBeijing 100081China MIX Labs Haidian DistrictBeijing 100080China Meituan NLP Center Chaoyang DistrictBeijing 100020China AI Lab of Yiducloud Inc. Huayuan North RoadHaidian DistrictBeijing 100089China

Knowlege is important for text-related *** this paper,we introduce Microsoft Concept Graph,a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human *** Concept Graph is built upon Probase,a universal probabilistic taxonomy consisting of instances and concepts mined from the *** start by introducing the construction of the knowledge graph through iterative semantic extraction and taxonomy construction procedures,which extract 2.7 million concepts from 1.68 billion Web *** then use conceptualization models to represent text in the concept space to empower text-related applications,such as topic search,query recommendation,Web table understanding and Ads *** the release in 2016,Microsoft Concept Graph has received more than 100,000 pageviews,2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.

关键词： Knowledge extraction Conceptualization Text understanding

Super-Resolution for Face Image with an Improved K-NN Search Strategy

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China Communications 2016年第4期13卷 151-161页

作者： QU Shenming HU Ruimin CHEN Shihong JIANG Junjun wang zhongyuan ZHANG Maosheng National Engineering Research Center for Multimedia Software Computer School of Wuhan University China Collaborative Innovation Center of Geospatial Technology China School of Software Henan University China

Recently, neighbor embedding based face super-resolution(SR) methods have shown the ability for achieving high-quality face images, those methods are based on the assumption that the same neighborhoods are preserved in both low-resolution(LR) training set and high-resolution(HR) training set. However, due to the "one-to-many" mapping between the LR image and HR ones in practice, the neighborhood relationship of the LR patch in LR space is quite different with that of the HR counterpart, that is to say the neighborhood relationship obtained is not true. In this paper, we explore a novel and effective re-identified K-nearest neighbor(RIKNN) method to search neighbors of LR patch. Compared with other methods, our method uses the geometrical information of LR manifold and HR manifold simultaneously. In particular, it searches K-NN of LR patch in the LR space and refines the searching results by re-identifying in the HR space, thus giving rise to accurate K-NN and improved performance. A statistical analysis of the influence of the training set size and nearest neighbor number is given, experimental results on some public face databases show the superiority of our proposed scheme over state-of-the-art face hallucination approaches in terms of subjective and objective results as well as computational complexity.

关键词： face hallucination K-NN re-identify super-resolution manifold learning

Advanced Electro-active Dry Adhesive Actuated by an Artificial Muscle Constructed from an Ionic Polymer Metal Composite Reinforced with Nitrogen-doped Carbon Nanocages

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Journal of Bionic Engineering 2017年第3期14卷 567-578页

作者： Qingsong He Xu Yang zhongyuan wang Jin Zhao Min Yu Zhen Hu Zhendong Dai Institute of Bio-inspired Structure and Surface Engineering Jiangsu Provincial Key Laboratory of Bionic Functional Materials Col- lege of Astronautics Nanjing University of Aeronautics & Astronautics Nanjing 210016 China College of Mechanical and Electrical Engineering Nanjing University of Aeronautics & Astronautics Nanjing 210016 China Key Laboratory of Mesoscopic Chemistry of MOE Jiangsu Provincial Lab for Nanotechnology School of Chemistry and Chemical Engineering Nanjing University Nanjing 210093 China

An advanced electro-active dry adhesive, which was composed of a mushroom-shaped tibrillar dry adhesive array actuated by an Ionic Polymer Metal Composite （IPMC） artificial muscle reinforced with nitrogen-doped carbon nanocages （NCNCs）, was developed to imitate the actuation of a gecko＇s toe. The properties of the NCNC-reinforced Nation membrane, the electro- mechanical properties of the NCNC-reinforced IPMC, and the related electro-active adhesion ability were investigated. The NCNCs were uniformly dispersed in the 0.1 wt% NCNC/Nafion membrane, and there was a seamless connection with no clear interface between the dry adhesive and the IPMC. Our 0.1 wt% NCNC/Nation-IPMC actuator shows a displacement and force that are 1.6 - 2 times higher than those of the recast Nafion-IPMC. This is due to the increased water uptake （25.39%） and tensile strength （24.5 MPa） of the specific 3D hollow NCNC-reinforced Nation membrane, as well as interactions between the NCNCs and the sulfonated groups of the Nation. The NCNC/Nation-IPMC was used to effectively actuate the mushroom-shaped dry adhesive. The normal adhesion forces were 7.85 raN, 12.1 mN, and 51.7 mN at sinusoidal voltages of 1.5 V, 2.5 V, and 3.5 V, respectively, at 0.1 Hz. Under the bionic leg trail, the normal and shear forces were approximately 713.5 mN （159 mN·cm^-2） and 1256.6 mN （279 mN·cm^-2）, respectively, which satisfy the required adhesion. This new electro-active dry adhesive can be applied for active, distributed actuation and flexible grip in robots.

关键词： electro-active dry adhesive bionic ionic polymer metal composite Nation membrane carbon nanocage

Drought-induced proline is mainly synthesized in leaves and transported to roots in watermelon under water deficit

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Horticultural Plant Journal 2022年第5期8卷 615-626页

作者： zhongyuan wang Yongchao Yang Vivek Yadav Wei Zhao Yaping He Xian Zhang Chunhua Wei College of Horticulture State Key Laboratory of Crop Stress Biology in Arid AreasNorthwest A&F UniversityYangling 712100ShaanxiChina College of Biological and Agricultural Sciences Honghe UniversityMengzi 661100YunnanChina State Key Laboratory of Vegetable Germplasm Innovation Tianjin Kernel Agricultural Corporation LtdTianjin 300384China

Proline accumulation has been shown to occur in plants in response to various environmental *** proline metabolismrelated genes have been functionally characterized,the inter-organ transport of proline in stressed plants remains *** this study,free proline was detected with significant accumulations in the roots,stems,and leaves of watermelon drought-tolerant germplasm M08 and drought-susceptible line Y34 under drought *** profiling and enzyme activity measurements revealed that ClP5CS1 gene,rather than its paralog ClP5CS2,mainly contributes to the proline synthesis in leaves via the Glu ***,over-expression of the ClP5CS genes significantly enhanced the drought tolerance of transgenic Arabidopsis ***,we confirmed that proline is mainly synthesized in leaves and transported to roots in watermelon under drought *** and expression analyses revealed that the genes involved in proline metabolism exhibited different expression ***,ClP5CS1 was upregulated in leaves and roots,while ClP5CS2 was downregulated under drought ***,415 and 362 differently expressed TFs were identified in roots and leaves,respectively,with the majority upregulated in the ***,a model for proline metabolism was *** findings of this study provided new insights into the biosynthesis,transport,and regulatory mechanism of drought-induced proline in plants.

关键词： Watermelon Drought stress Proline Inter-organ transport