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Author Correction: π-HuB: the proteomic navigator of the human body

Nature 2025年第8046期637卷 E22页

作者： Fuchu He Ruedi Aebersold Mark S Baker Xiuwu Bian Xiaochen Bo Daniel W Chan Cheng Chang Luonan Chen Xiangmei Chen Yu-Ju Chen Heping Cheng Ben C Collins Fernando Corrales Jürgen Cox Weinan E Jennifer E Van Eyk Jia Fan Pouya Faridi Daniel Figeys George Fu Gao Wen Gao Zu-Hua Gao Keisuke Goda Wilson Wen Bin Goh Dongfeng Gu Changjiang Guo Tiannan Guo Yuezhong He Albert J R Heck Henning Hermjakob Tony Hunter Narayanan Gopalakrishna Iyer Ying Jiang Connie R Jimenez Lokesh Joshi Neil L Kelleher Ming Li Yang Li Qingsong Lin Cui Hua Liu Fan Liu Guang-Hui Liu Yansheng Liu Zhihua Liu Teck Yew Low Ben Lu Matthias Mann Anming Meng Robert L Moritz Edouard Nice Guang Ning Gilbert S Omenn Christopher M Overall Giuseppe Palmisano Yaojin Peng Charles Pineau Terence Chuen Wai Poon Anthony W Purcell Jie Qiao Roger R Reddel Phillip J Robinson Paola Roncada Chris Sander Jiahao Sha Erwei Song Sanjeeva Srivastava Aihua Sun Siu Kwan Sze Chao Tang Liujun Tang Ruijun Tian Juan Antonio Vizcaíno Chanjuan Wang Chen Wang Xiaowen Wang Xinxing Wang Yan Wang Tobias Weiss Mathias Wilhelm Robert Winkler Bernd Wollscheid Limsoon Wong Linhai Xie Wei Xie Tao Xu Tianhao Xu Liying Yan Jing Yang Xiao Yang John Yates Tao Yun Qiwei Zhai Bing Zhang Hui Zhang Lihua Zhang Lingqiang Zhang Pingwen Zhang Yukui Zhang Yu Zi Zheng Qing Zhong Yunping Zhu State Key Laboratory of Medical Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing) Beijing Institute of Lifeomics Beijing China. hefc@***. International Academy of Phronesis Medicine (Guangdong) Guangdong China. hefc@***. Department of Biology Institute of Molecular Systems Biology ETH Zurich Zurich Switzerland. aebersold@imsb.biol.ethz.ch. Macquarie Medical School Macquarie University Sydney New South Wales Australia. Institute of Pathology and Southwest Cancer Center Southwest Hospital Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology Ministry of Education of China Chongqing China. Institute of Health Service and Transfusion Medicine Beijing China. Department of Pathology and The Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University Baltimore MD USA. State Key Laboratory of Medical Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing) Beijing Institute of Lifeomics Beijing China. Key Laboratory of Systems Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Shanghai China. Department of Nephrology First Medical Center of Chinese PLA General Hospital Nephrology Institute of the Chinese People's Liberation Army State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Beijing Key Laboratory of Kidney Disease Research Beijing China. Institute of Chemistry Academia Sinica Taipei China. National Biomedical Imaging Center State Key Laboratory of Membrane Biology Institute of Molecular Medicine Peking-Tsinghua Center for Life Sciences College of Future Technology Peking University Beijing China. School of Biological Sciences Queen's University of Belfast Belfast UK. Functional Proteomics Laboratory Centro Nacional de Biotecnología-CSIC Madrid Spain. Computational Systems Biochemistry Research Group Ma

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Fabrication & HCI: Hobbyist making, industrial production, and beyond

Fabrication & HCI: Hobbyist making, industrial production, a...

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34th Annual CHI Conference on human Factors in Computing Systems, CHI EA 2016

作者： Fuchsberger, Verena Murer, Martin Tscheligi, Manfred Lindtner, Silvia Bardzell, Shaowen Bardzell, Jeffrey Reiter, Andreas Bjørn, Pernille Center for Human-Computer Interaction University of Salzburg Austria School of Information University of Michigan Ann Arbor United States Indiana University Bloomington United States Mixed Reality Laboratory School of Computer Science University of Nottingham United Kingdom Computer Science Department University of Copenhagen Denmark

ISBN: (纸本)9781450340823

This one-day workshop seeks to advance the discussion around making and fabrication in HCI research, including notions of hobbyist making and industrial production. These different fabrication cultures are the starting point for the workshop, which attempts to contour the landscape of fabrication and how it influences and is influenced by HCI (research). The proposed workshop extends from two prior efforts in this space: a workshop held at the 5th Decennial Aarhus Conference and a three-day summit in Austria in September 2015 on "Rethinking Technology Innovation: Factories, Fabrication & Design Research". © 2016 Authors.

关键词： human computer interaction

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Corrigendum to “Bodily sensation maps: exploring a new direction for detecting emotions from user self-reported data” [International Journal of human - computer Studies (2018) 113, 32–47]

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International Journal of human-computer Studies 2018年 120卷 125-125页

作者： Iván García-Magariño Luca Chittaro Inmaculada Plaza Department of Computer Science and Engineering of Systems Escuela Universitaria Politécnica de Teruel University of Zaragoza c/ Atarazana 2 44003 Teruel Spain Instituto de Investigación Sanitaria Aragón University of Zaragoza Zaragoza Spain Human-Computer Interaction Lab Department of Mathematics Computer Science and Physics University of Udine Via delle Scienze 206 33100 Udine Italy Department of Electronics Engineering and Communications Escuela Universitaria Politécnica de Teruel University of Zaragoza c/ Atarazana 2 44003 Teruel Spain

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Natural supervised hashing 25

Natural supervised hashing

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25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Liu, Qi Lu, Hongtao Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai Jiao Tong University China

Among learning-based hashing methods, supervised hashing tries to find hash codes which preserve semantic similarities of original data. Recent years have witnessed much efforts devoted to design objective functions and optimization methods for supervised hashing learning, in order to improve search accuracy and reduce training cost. In this paper, we propose a very straightforward supervised hashing algorithm and demonstrate its superiority over several state-of-the-art methods. The key idea of our approach is to treat label vectors as binary codes and to learn target codes which have similar structure to label vectors. To circumvent direct optimization on large n × n Gram matrices, we identify an inner-product-preserving transformation and use it to bring close label vectors and hash codes without changing the structure. The optimization process is very efficient and scales well. In our experiment, training 16-bit and 96-bit code on NUS-WIDE cost respectively only 3 and 6 minutes.

关键词： Hash functions

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Accelerated distance computation with encoding tree/forest for high dimensional data

Accelerated distance computation with encoding tree/forest f...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Liu, Shicong Shao, Junru Lu, Hongtao Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781509003891

Vector quantization based methods are important tools for large scale search. They perform lossy compression on the dataset, then the distance between an uncompressed vector and compressed dataset can be efficiently computed via asymmetric distance computation (ADC). We show that for large datasets, ADC conducts excessive computations on vectors sharing the same prefix. To this end, we propose encoding tree (E-Tree) to avoid the excessive computations by storing the encodings on a radix-tree like data-structure. The memory consumption is also lowered. We then propose encoding forest (E-Forest) to further lower the computation cost. E-Tree and E-Forest are compatible with any quantization-based methods. Furthermore, unlike ordinary tree structures, our E-Tree and E-Forest essentially store the encoded vectors linearly in the memory, thus they are easy to implement and compute efficiently. We show by experiments that our methods bring significant speed-up compared to the vanilla ADC method. Therefore, E-Tree and E-Forest offer a practical and useful solution for real-world problems. © 2016 IEEE.

关键词： Vectors

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LSOD: Local sparse orthogonal descriptor for image matching 16

LSOD: Local sparse orthogonal descriptor for image matching

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24th ACM Multimedia Conference, MM 2016

作者： Zhao, Yiru Li, Yaoyi Shao, Zhiwen Lu, Hongtao Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781450336031

We propose a novel method for feature description used for image matching in this paper. Our method is inspired by the autoencoder, an artificial neural network designed for learning efficient codings. Sparse and orthogonal constraints are imposed on the autoencoder and make it a highly discriminative descriptor. It is shown that the proposed descriptor is not only invariant to geometric and photometric transformations (such as viewpoint change, intensity change, noise, image blur and JPEG compression), but also highly efficient. We compare it with existing state-of-the-art descriptors on standard benchmark datasets, the experimental results show that our LSOD method yields better performance both in accuracy and eficiency. © 2016 ACM.

关键词： Image matching

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What can doodles on the arm teach us about on-body interaction?

What can doodles on the arm teach us about on-body interacti...

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34th Annual CHI Conference on human Factors in Computing Systems, CHI EA 2016

作者： Strohmeier, Paul Carrascal, Juan Pablo Hornbæk, Kasper Department of Computer Science University of Copenhagen Denmark Human Media Lab Queen's University KingstonON Canada

ISBN: (纸本)9781450340823

The use of the skin as interaction surface is gaining popularity in the HCI community. To offer an alternative perspective on how we might design on-body interactions, we conducted a questionnaire asking if, how, and why people mark their skin. We found that visibility and ease of access were important factors for choosing to mark the body. We also found that while some participants consider marking the body as a private activity, most participants perceive such markings as a public display. This tension between the personal nature of on-body interaction and the skin as a public display, as well as hedonic uses of body markings, present interesting design challenges. © 2016 Authors.

关键词： human engineering

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Beyond web content accessibility guidelines. Expert accessibility reviews 2016

Beyond web content accessibility guidelines. Expert accessib...

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7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-Exclusion, DSAI 2016

作者： Calvo, Rocio Seyedarabi, Faezeh Savva, Andreas AbilityNet Department of Accessibility Services LondonEC1V 2PT United Kingdom Human-Computer Interaction Research Group University of York Department of Computer Science YorkYO10 5GH United Kingdom

ISBN: (纸本)9781450347488

Despite the existence of web accessibility guidelines - e.g. Web Content Accessibility Guidelines - to help developers and designers to create more accessible websites, many websites are still not accessible. Studies showed that guidelines do not cover all the problems encounter by users with disabilities. This study investigates the problems found by seven accessibility experts in 62 accessibility evaluation reviews of mobile and desktop websites as well as mobile applications. Each evaluation conducted an accessibility review using Web Content Accessibility Guidelines 2.0 AA. In addition, experts highlighted potential issues which were not covered by these guidelines but could be potential issues encountered by people with disabilities. The study depicts those issues that were raised by experts during those audits but were not covered by the WCAG 2.0 guidelines. Finally, the study provides additional knowledge into potential problems as identified by experts and recommends techniques that developers and designers can use to create more accessible websites. © 2016 ACM.

关键词： Websites

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Towards automatic semantic segmentation in volumetric ultrasound 20th

Towards automatic semantic segmentation in volumetric ultra...

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20th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2017

作者： Yang, Xin Yu, Lequan Li, Shengli Wang, Xu Wang, Na Qin, Jing Ni, Dong Heng, Pheng-Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong Department of Ultrasound Affliated Shenzhen Maternal and Child Healthcare Hospital of Nanfang Medical University Shenzhen China National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China School of Nursing Centre for Smart Health The Hong Kong Polytechnic University Hong Kong Hong Kong Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783319661810

3D ultrasound is rapidly emerging as a viable imaging modality for routine prenatal examinations. However, lacking of efficient tools to decompose the volumetric data greatly limits its widespread. In this paper, we are looking at the problem of volumetric segmentation in ultrasound to promote the volume-based, precise maternal and fetal health monitoring. Our contribution is threefold. First, we propose the first and fully automatic framework for the simultaneous segmentation of multiple objects, including fetus, gestational sac and placenta, in ultrasound volumes, which remains as a rarely-studied but great challenge. Second, based on our customized 3D Fully Convolutional Network, we propose to inject a Recurrent Neural Network (RNN) to flexibly explore 3D semantic knowledge from a novel, sequential perspective, and therefore significantly refine the local segmentation result which is initially corrupted by the ubiquitous boundary uncertainty in ultrasound volumes. Third, considering sequence hierarchy, we introduce a hierarchical deep supervision mechanism to effectively boost the information flow within RNN and further improve the semantic segmentation results. Extensively validated on our in-house large datasets, our approach achieves superior performance and presents to be promising in boosting the interpretation of prenatal ultrasound volumes. Our framework is general and can be easily extended to other volumetric ultrasound segmentation tasks. © 2017, Springer International Publishing AG.

关键词： Ultrasonics

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Correction for: Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data

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JMIR research protocols 2018年第1期7卷 e10页

作者： Floor Sieverink Saskia Kelders Mannes Poel Lisette van Gemert-Pijnen Centre for eHealth and Wellbeing Research Department of Psychology Health and Technology University of Twente Enschede Netherlands. Optentia Research Focus Area North-West University Vanderbijlpark South Africa. Human Media Interaction Group Department of Computer Science University of Twente Enschede Netherlands.

[This corrects the article DOI: .].

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