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1,546 results on '"Zhang, Shuyang"'

1. Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion

Author

He, Jinhao, Huang, Huaiyang, Zhang, Shuyang, Jiao, Jianhao, Liu, Chengju, and Liu, Ming

Subjects
Computer Science - Robotics
Abstract

Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread adoption in mass-market applications. In this paper, we aim to use only a monocular camera to achieve comparable onboard localization performance by tracking deep-learning visual features on a LiDAR-enhanced visual prior map. Experiments show that the proposed algorithm can provide centimeter-level global positioning results with scale, which is effortlessly integrated and favorable for low-cost robot system deployment in real-world applications., Comment: ICRA 2024

Published
2024

2. RareBench: Can LLMs Serve as Rare Diseases Specialists?

Author

Chen, Xuanzhong, Mao, Xiaohao, Guo, Qihan, Wang, Lun, Zhang, Shuyang, and Chen, Ting

Subjects
Computer Science - Computation and Language
Abstract

Generalist Large Language Models (LLMs), such as GPT-4, have shown considerable promise in various domains, including medical diagnosis. Rare diseases, affecting approximately 300 million people worldwide, often have unsatisfactory clinical diagnosis rates primarily due to a lack of experienced physicians and the complexity of differentiating among many rare diseases. In this context, recent news such as "ChatGPT correctly diagnosed a 4-year-old's rare disease after 17 doctors failed" underscore LLMs' potential, yet underexplored, role in clinically diagnosing rare diseases. To bridge this research gap, we introduce RareBench, a pioneering benchmark designed to systematically evaluate the capabilities of LLMs on 4 critical dimensions within the realm of rare diseases. Meanwhile, we have compiled the largest open-source dataset on rare disease patients, establishing a benchmark for future studies in this domain. To facilitate differential diagnosis of rare diseases, we develop a dynamic few-shot prompt methodology, leveraging a comprehensive rare disease knowledge graph synthesized from multiple knowledge bases, significantly enhancing LLMs' diagnostic performance. Moreover, we present an exhaustive comparative study of GPT-4's diagnostic capabilities against those of specialist physicians. Our experimental findings underscore the promising potential of integrating LLMs into the clinical diagnostic process for rare diseases. This paves the way for exciting possibilities in future advancements in this field., Comment: KDD2024

Published
2024

3. CANAMRF: An Attention-Based Model for Multimodal Depression Detection

Author

Wei, Yuntao, Zhang, Yuzhe, Zhang, Shuyang, and Zhang, Hong

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Multimodal depression detection is an important research topic that aims to predict human mental states using multimodal data. Previous methods treat different modalities equally and fuse each modality by na\"ive mathematical operations without measuring the relative importance between them, which cannot obtain well-performed multimodal representations for downstream depression tasks. In order to tackle the aforementioned concern, we present a Cross-modal Attention Network with Adaptive Multi-modal Recurrent Fusion (CANAMRF) for multimodal depression detection. CANAMRF is constructed by a multimodal feature extractor, an Adaptive Multimodal Recurrent Fusion module, and a Hybrid Attention Module. Through experimentation on two benchmark datasets, CANAMRF demonstrates state-of-the-art performance, underscoring the effectiveness of our proposed approach., Comment: 6 pages, 3 figures. Pacific Rim International Conference on Artificial Intelligence. Singapore: Springer Nature Singapore, 2023

Published
2024
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4. Experimental Study of the Nematic Transition in Granular Spherocylinder Packings under Tapping

Author

Yu, Haitao, Zeng, Zhikun, Yuan, Ye, Zhang, Shuyang, Xia, Chengjie, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

Using x-ray tomography, we experimentally investigate the nematic transition in granular spherocylinder packings induced by tapping. Upon the validation of the Edwards ensemble framework in spherocylinders, we introduce an empirical free energy that accounts for the influence of gravity and the mechanical stability requirements specific to granular systems. This free energy can predict not only the correct phase transition behavior of the system from a disordered state to a nematic phase, but also a phase coexistence range and nucleation energy barriers that agree with experimental observations., Comment: 19 pages, 5 figures

Published
2023

5. Outram: One-shot Global Localization via Triangulated Scene Graph and Global Outlier Pruning

Author

Yin, Pengyu, Cao, Haozhi, Nguyen, Thien-Minh, Yuan, Shenghai, Zhang, Shuyang, Liu, Kangcheng, and Xie, Lihua

Subjects
Computer Science - Robotics
Abstract

One-shot LiDAR localization refers to the ability to estimate the robot pose from one single point cloud, which yields significant advantages in initialization and relocalization processes. In the point cloud domain, the topic has been extensively studied as a global descriptor retrieval (i.e., loop closure detection) and pose refinement (i.e., point cloud registration) problem both in isolation or combined. However, few have explicitly considered the relationship between candidate retrieval and correspondence generation in pose estimation, leaving them brittle to substructure ambiguities. To this end, we propose a hierarchical one-shot localization algorithm called Outram that leverages substructures of 3D scene graphs for locally consistent correspondence searching and global substructure-wise outlier pruning. Such a hierarchical process couples the feature retrieval and the correspondence extraction to resolve the substructure ambiguities by conducting a local-to-global consistency refinement. We demonstrate the capability of Outram in a variety of scenarios in multiple large-scale outdoor datasets. Our implementation is open-sourced: https://github.com/Pamphlett/Outram., Comment: 8 pages, 5 figures

Published
2023

6. Experimental Study of Granular Clogging in Two-Dimensional Hopper

Author

Zhang, Shuyang, Zeng, Zhikun, Yuan, Houfei, Xu, Zihang, Ai, Xinyu, He, Lewei, Li, Zhifeng, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

We experimentally investigate the clogging process of granular materials in a two-dimensional hopper, and present a self-consistent physical mechanism of clogging based on preformed dynamic chain structures in the flow. We found that these chain structures follow a specific modified restricted random walk, and clogging occurs when they are mechanically stable enough to withstand the flow fluctuations, resulting in the formation of an arch at the outlet. We introduce a simple model which can explain the clogging probability by incorporating an analytical expression for chain formation and its transition into an arch. Our results provide insight into the microscopic mechanism of clogging in hopper flow., Comment: 22 pages, 8 figures

Published
2023

9. Thrust Control of Scramjet Based on BP Neural Network

Author

Zhao, Zhelong, Li, Jialin, Zhang, Shuyang, Dai, Shasha, Zhang, Jiansheng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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10. Analysis Method of Spacecraft Telemetry Translation Information Based on XML

Author

Sun, Hao, Zhang, Yue, Zhang, Shuyang, Zhang, Jiansheng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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15. Segregator: Global Point Cloud Registration with Semantic and Geometric Cues

Author

Yin, Pengyu, Yuan, Shenghai, Cao, Haozhi, Ji, Xingyu, Zhang, Shuyang, and Xie, Lihua

Subjects
Computer Science - Robotics
Abstract

This paper presents Segregator, a global point cloud registration framework that exploits both semantic information and geometric distribution to efficiently build up outlier-robust correspondences and search for inliers. Current state-of-the-art algorithms rely on point features to set up putative correspondences and refine them by employing pair-wise distance consistency checks. However, such a scheme suffers from degenerate cases, where the descriptive capability of local point features downgrades, and unconstrained cases, where length-preserving (l-TRIMs)-based checks cannot sufficiently constrain whether the current observation is consistent with others, resulting in a complexified NP-complete problem to solve. To tackle these problems, on the one hand, we propose a novel degeneracy-robust and efficient corresponding procedure consisting of both instance-level semantic clusters and geometric-level point features. On the other hand, Gaussian distribution-based translation and rotation invariant measurements (G-TRIMs) are proposed to conduct the consistency check and further constrain the problem size. We validated our proposed algorithm on extensive real-world data-based experiments. The code is available: https://github.com/Pamphlett/Segregator., Comment: 6 pages, 5 figures. Accepted to ICRA2023

Published
2023

16. From creep to flow: Granular materials under cyclic shear

Author

Yuan, Ye, Zeng, Zhikun, Xing, Yi, Yuan, Houfei, Zhang, Shuyang, Kob, Walter, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Materials Science, Condensed Matter - Statistical Mechanics
Abstract

Granular materials such as sand, powders, and grains are omnipresent in daily life, industrial applications, and earth-science [1]. When unperturbed, they form stable structures that resemble the ones of other amorphous solids like metallic and colloidal glasses [2]. It is commonly conjectured that all these amorphous materials show a universal mechanical response when sheared slowly, i.e., to have an elastic regime, followed by yielding [3]. Here we use X-ray tomography to determine the microscopic dynamics of a cyclically sheared granular system in three dimensions. Independent of the shear amplitude $\Gamma$, the sample shows a cross-over from creep to diffusive dynamics, indicating that granular materials have no elastic response and always yield, in stark contrast to other glasses. The overlap function [4] reveals that at large $\Gamma$ yielding is a simple cross-over phenomenon, while for small $\Gamma$ it shows features of a first order transition with a critical point at $\Gamma\approx 0.1$ at which one finds a pronounced slowing down and dynamical heterogeneity. Our findings are directly related to the surface roughness of granular particles which induces a micro-corrugation to the potential energy landscape, thus creating relaxation channels that are absent in simple glasses. These processes must be understood for reaching an understanding of the complex relaxation dynamics of granular systems.

Published
2023

17. Directed Acyclic Graph Structure Learning from Dynamic Graphs

Author

Fan, Shaohua, Zhang, Shuyang, Wang, Xiao, and Shi, Chuan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Estimating the structure of directed acyclic graphs (DAGs) of features (variables) plays a vital role in revealing the latent data generation process and providing causal insights in various applications. Although there have been many studies on structure learning with various types of data, the structure learning on the dynamic graph has not been explored yet, and thus we study the learning problem of node feature generation mechanism on such ubiquitous dynamic graph data. In a dynamic graph, we propose to simultaneously estimate contemporaneous relationships and time-lagged interaction relationships between the node features. These two kinds of relationships form a DAG, which could effectively characterize the feature generation process in a concise way. To learn such a DAG, we cast the learning problem as a continuous score-based optimization problem, which consists of a differentiable score function to measure the validity of the learned DAGs and a smooth acyclicity constraint to ensure the acyclicity of the learned DAGs. These two components are translated into an unconstraint augmented Lagrangian objective which could be minimized by mature continuous optimization techniques. The resulting algorithm, named GraphNOTEARS, outperforms baselines on simulated data across a wide range of settings that may encounter in real-world applications. We also apply the proposed approach on two dynamic graphs constructed from the real-world Yelp dataset, demonstrating our method could learn the connections between node features, which conforms with the domain knowledge., Comment: Accepted by AAAI23

Published
2022

18. Study on Drug List and Accessibility of Rare Diseases Based on the China′s Second List of Rare Diseases

Author

LIU Qingyang, LIU Xin, ZUO Wei, WANG Shaohong, ZHANG Bo, and ZHANG Shuyang

Subjects
rare diseases, orphan drugs, accessibility, the china′s second list of rare diseases, Medicine
Abstract

Objective This study aims to sort out the rare disease drugs in the China′s Second List of Rare Diseases, to provide reference for the management of rare disease drug treatment. Methods Up to December 31, 2023, based on the China′s Second List of Rare Diseases, we sorted out the drugs approved in China with the drug label, or approved by the U.S. Food and Drug Administration(FDA) and the European Medicines Agency (EMA) for the treatment of the above diseases, and developed the second batch of rare disease drug catalog in China. The accessibility, localization and coverage of the national medical insurance were also analyzed. Results From the point of view of diseases, a total of 37 diseases in the China′s Second List of Rare Diseases have drug indications approved in China, and 10 diseases have drugs listed by the U.S. FDA/EMA and approved in China, but for off-label use. From the point of view of drugs, there are 55 drug indications approved for the treatment of the China′s Second List of Rare Diseases, and 22 drugs listed in the U.S. FDA/EMA and approved in the China, but for off-label use. Among the above-mentioned drugs with domestic approved rare disease indications or approved numbers, 39 drugs have at least one domestic approval number for a dosage form, covering 30 rare diseases; 37 drugs used for at least one rare disease are included in the national medical insurance catalog and are covered by reimbursement, covering 29 rare diseases. Conclusions The list of rare disease drugs in the China′s Second List of Rare Diseases was established. The number of rare disease drugs and covered diseases approved by China and the U.S. FDA/EMA has increased, and the number of rare disease drugs and covered diseases that are localized and included in the medical insurance catalog has also continued to increase.

Published
2024
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19. Current Status and Challenges of Guarantee for Rare Disease Drugs

Author

ZUO Wei, ZHANG Bo, and ZHANG Shuyang

Subjects
rare diseases, orphan drugs, guarantee for drugs, drug paymemnt, audit and approve, Medicine
Abstract

In the past few years, China has pushed forward the availability of diagnosis and treatment of rare diseases. However, only 5% of patients receive effective treatment in the world. In China, the difficulties in having access to drugs against rare disease is still one of the major problems in medical service and the main cause of patients complaints for " difficulties in getting treatment" and " difficulties in getting drugs". The availability of the medication for rare disease is a coordinating mechanism involving multiple such points in the chain as in research and development, production, circulation, usage, way of payment, technology innovation and so forth. It also relates to the actors in supply, demand, and policy decision-makers. The complexity is different from that of common drugs. This article provides a brief overview of the current status of availability policies of medication for rare diseases in China and in other countries, as well as the technology in drug development. In addition, the article points out the problems, challenges and expectations for future possibilities.

Published
2024
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20. Preliminary Exploration on the Establishment of the Department of Rare Diseases at Peking Union Medical College Hospital

Author

SHEN Min and ZHANG Shuyang

Subjects
rare diseases, department of rare diseases, multidisciplinary team, Medicine
Abstract

The establishment of the Department of Rare Diseases at Peking Union Medical College Hospital (PUMCH) is a landmark in the disciplinary development of the rare diseases. The establishment of the department will booster the prominence of the influence and leading position of the PUMCH in the field of rare diseases. In addition, the department is instrumental in the development of the hospital of high-quality. The department aims at delivery of better medical care for patients with rare diseases, the training of specialists in rare diseases, and avancement of the preventing and treating rare diseases in China.This paper preliminarily discusses the working basis, significance and discipline development plan of the department of rare diseases at PUMCH.

Published
2024
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21. Thoughts on Selection of Rare Diseases and Prioritized Research Topics

Author

LI Kexin, CHEN Jingdan, ZHANG Dingding, GUO Wudong, ZHENG Jiayin, LI Linkang, ZHAO Kun, and ZHANG Shuyang

Subjects
rare diseases, disease selection, prioritized topics, multi-criteria decision analysis, Medicine
Abstract

This article combs and summarizes the entire process of rare disease selection and priority theme determination, including the application and preliminary review of rare diseases, standardization of disease theme information, the evaluation methods of evidence sorting and disease selection for priority selection of disease themes, and other aspects of the content were analyzed in depth. It is expected to provide reference for the subsequent selection of rare diseases, improve the fairness, rationality and scientificity of rare disease selection, and further promote research and decision-making in China′s rare disease-related fields.

Published
2024
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22. Equivalence of fluctuation-dissipation and Edwards' temperature in cyclically sheared granular systems

Author

Zeng, Zhikun, Zhang, Shuyang, Zheng, Xu, Xia, Chengjie, Kob, Walter, Yuan, Ye, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

Using particle trajectory data obtained from x-ray tomography, we determine two kinds of effective temperatures in a cyclically sheared granular system. The first one is obtained from the fluctuation-dissipation theorem which relates the diffusion and mobility of lighter tracer particles immersed in the system. The second is the Edwards compactivity defined via the packing volume fluctuations. We find robust excellent agreement between these two temperatures, independent of the type of the tracers, cyclic shear amplitudes, and particle surface roughness. We further elucidate that in granular systems the viscous-like drag force is due to the broken symmetry of the local contact geometry., Comment: 19 pages, 6 figures

Published
2022
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25. ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell transcriptomics

Author

Hao, Yajing, Zhang, Shuyang, Shao, Changwei, Li, Junhui, Zhao, Guofeng, Zhang, Dong-Er, and Fu, Xiang-Dong

Subjects
Cancer, Human Genome, Biotechnology, Networking and Information Technology R&D (NITRD), Genetics, Generic health relevance, Genomics, High-Throughput Screening Assays, RNA Interference, Single-Cell Analysis, Software, Transcriptome, Zeta statistics, two-dimensional RNAi screening, Single-cell RNA-seq, Cancer dependency, Cancer checkpoint, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

Two-dimensional high-throughput data have become increasingly common in functional genomics studies, which raises new challenges in data analysis. Here, we introduce a new statistic called Zeta, initially developed to identify global splicing regulators from a two-dimensional RNAi screen, a high-throughput screen coupled with high-throughput functional readouts, and ZetaSuite, a software package to facilitate general application of the Zeta statistics. We compare our approach with existing methods using multiple benchmarked datasets and then demonstrate the broad utility of ZetaSuite in processing public data from large-scale cancer dependency screens and single-cell transcriptomics studies to elucidate novel biological insights.

Published
2022

27. Factors Associated With Coronary Angiography Performed Within 6 Months of Randomization to the Conservative Strategy in the ISCHEMIA Trial

Author

Pracoń, Radosław, Spertus, John A., Broderick, Samuel, Bangalore, Sripal, Rockhold, Frank W., Ruzyllo, Witold, Demchenko, Elena, Nageh, Thuraia, Grossman, Gabriel Blacher, Mavromatis, Kreton, Manjunath, Cholenahally N., Smanio, Paola E.P., Stone, Gregg W., Mancini, G.B. John, Boden, William E., Newman, Jonathan D., Reynolds, Harmony R., Hochman, Judith S., Maron, David J., Doan, John, Linefsky, Jason, Lee, Raven, Patel, Risha, Miller, Todd, Yang Cho, So, Milbrandt, Susan, Shelstad, Dawn, Banerjee, Subhash, Kamath, Preeti, Tejani, Ishita, Cobos, Stanley E., Quiles, Kirsten J., Dwyer, Raven R., Donnino, Robert M., Espinosa, Dalisa, Phillips, Lawrence M., Saric, Muhamed, Abdul-Nour, Khaled, Schley, Allison, Golden, Heather, Stone, Peter H., Osseni, Hermine, Wiyarand, Charlene, Douglass, Peter, Pomeroy, Hayley, Craft, Alexandra, Harvey, Bethany, Jang, James J., Anaya, Olivia, Yee, Gennie, Goold, Phoebe, Weitz, Steven, Giovannone, Steven, Pritchard, Lori, Arnold, Suzanne, Gans, Rosann, Henry O’Keefe, Jr, James, Kennedy, Paul, Shapiro, Michael D., Ganesan, Shobana, Schlichting, David, Naher, Aynun, El-Hajjar, Mohammad, Sidhu, Mandeep S., Fein, Steven A., Stewart, Wendy L., Torosoff, Mikhail T., Salmi, Kristin M., Lyubarova, Radmila, Mookherjee, Sulagna, Drzymalski, Krzysztof, McFalls, Edward O., Garcia, Santiago A., Bertog, Stefan C., Johnson, Debra K., Siddiqui, Rizwan A., Herrmann, Rebekah R., Ishani, Areef, Hansen, Ronnell A., Georges Khouri, Michel, Arges, Kristine, LeFevre, Melissa, Tomfohr, Jennifer, Goldberg, Jonathan L., Ann Byrne, Kimberly, Zappernick, Taissa, Goldweit, Richard, Canada, Sallie, Kakade, Meghana, Mieses, Patricia, Cobos, Stanley E., Dwyer, Raven R., Cohen, Ronny A., Espinosa, Dalisa, Mirrer, Brooks, Quiles, Kirsten J., Navarro, Victor, Rantinella, Magdalena, Rodriguez, Jessica, Mancilla, Olivia, Winchester, David E., Stinson, Susan, Kronenberg, Marvin, Weyand, Terry, Rogal, Philip, Crook, Sherron C., McFarren, Christopher, Heitner, John F., Ho, Jean, Khan, Saadat, Mohamed, Mahmoud, Dauber, Ira M., Soltau, Mary R., Rose, Delsa K., Wimmer, Rebecca J., Siegel, Kathy E., Derbyshire, Susan, Cannan, Charles, Dixon, Michelle, Leonard, Gerald, Sudarshan, Sriram, Heard, Ciarra, Gabriel, Viviana, Desire, Sukie, Mehta, Puja K., McDaniel, Michael, Rashid, Fauzia, Lerakis, Stamatios, Asier, Senait, Quyyumi, Arshed, Patel, Keyur, Wenger, Nanette K., Hedgepeth, Chester M., Gillis, Jennifer, Hurlburt, Heather, Manocchia, Megan, Rosen, Alan, Moore, Susan, Congdon, Elizabeth, Sahul, Zakir, Brandt, Gail, Marchelletta, Nora, Wippler, Kristina, Booth, David, Taul, Yvonne, Leung, Steve, Isaacs, Jennifer, Abdel-Latif, Ahmed, Bulkley, Viktoria, Reda, Hassan, Rodgers, Caroline, Ziada, Khaled, Setty, Sampoornima, Halverson, Kimberly E., Roraff, Christine, Thorsen, Jonean, Barua, Rajat S., Ojajuni, Amarachi, Olurinde, Oni, Surineni, Kamalakar, Hage, Fadi, Valaiyapathi, Badhma, Caldeira, Christiano, Davies, James E., Leesar, Massoud, Heo, Jaekyeong, Iskandrian, Amy, Al Solaiman, Firas, Singh, Satinder, Dajani, Khaled, Kartje, Carol M., El-Hajjar, Mohammad, Mesropian, Paul Der, Sacco, Joseph, Rawlins, Michele, McCandless, Brian, Thomson, Jennifer, Orgera, Marisa, Sidhu, Mandeep S., Colleen Rogge, Mary, Arif, Imran, Bunke, Julie, Kerr, Hanan, Unterbrink, Kendra, Fannon, Jacqueline, Burman, Cynthia, Trejo, Jorge F., Dubin, Marcia F., Fletcher, Gerald, Lane, Gary E., Neeson, Lynn M., Parikh, Pragnesh P., Pollak, Peter M., Shapiro, Brian P., Landolfo, Kevin, Gemignani, Anthony, Beaudry, Sarah, O’Rourke, Daniel, Meadows, Judith L., Tirado, Stephanie A., Halliday, Janet, Julian, Pamela, Call, Jason T., Lane, Stephanie M., Stanford, Jennifer L., Hannan, Joseph, Bojar, Robert, Arsenault, Patricia, Kumar, Deepti, Sigel, Pamela, Mukai, John, Martin, Edward T., Brooks, Miriam, Vorobiof, Gabriel, Douangvila, Ladda, Gevorgyan, Rubine, Moorman, Alec, Ranjbaran, Fatima, Smith, Bryn, Ohmart, Carly, Kinlay, Scott, Hamburger, Robert J., Rocco, Thomas P., Ly, Samantha, Bhatt, Deepak L., Quinn, Margot C., Croce, Kevin, Temiyasathit, Sara, Quin, Jacquelyn A, Do, Jacquelyn, Anumpa, Jati, Tobin, Desiree, Zenati, Marco, Faxon, David P, Rayos, Glenn, Langdon, Jennifer, Werner Bayer, Marcia, Seedhom, Ashraf, O’Malley, Amanda, Sullenberger, Lance, Orvis, Erin, Kumkumian, Gregory, Murphy, Mandy, Greenberg, Ann, Iraola, Margaret, Sedlis, Steven P., Maranan, Leandro C., Donnino, Robert M., Lorin, Jeffrey, Tamis-Holland, Jacqueline E., Malinay, Ammy, Kornberg, Robert, Leber, Robert, Saba, Souheil, Edillo, Candice P., Lee, Michael W., Small, Delano R., Nona, Wassim, Alexander, Patrick B., Rehman, Iram, Badami, Umesh, Ostrander, Ann, Wasmiller, Stephanie, Marzo, Kevin, Drewes, Wendy, Patel, Dipti, Robbins, Inga H., Levite, Howard A., White, Jackie M, Shetty, Sanjay, Hallam, Alison, Patel, Mayuri, Hamroff, Glenn S., Spooner, Benjamin J, Hollenweger, Linda M, Little, Raymond W., Little, Holly, Zimbelman, Brandi D., Little, Tiffany, Lui, Charles Y., Eskelson, Nona A, Smith, Brigham R., Vezina, Daniel P., Khor, Lillian L., Abraham, Josephine D., Bull, David A., McKellar, Stephen H., Booth, David, Taul, Yvonne, Kotter, John, Rodgers, Caroline, Abdel-Latif, Ahmed, Isaacs, Jennifer, Bulkley, Viktoria, Hu, Bob, Kaneshiro, Renee, Labovitz, Arthur J., Berlowitz, Michael, Kirby, Bonnie J., Rogal, Philip, Tran, Nhi N., McFarren, Christopher, Jahrsdorfer, Catherine, Matar, Fadi, Caldeira, Christiano, Rodriguez, Fatima, Yunis, Reem, Schnittger, Ingela, Patro, Jhina, Fearon, William F., Deedwania, Prakash, Vega, Antonia, Reddy, Kiran, Sweeny, Joseph, Bloise-Adames, Hugo, Jimenez, Santa, Saint Vrestil, Nicole, Bhandari, Reyna, Spizzieri, Christopher, Schade, Danielle, Yost, Roxanne, Hochberg, Claudia P, Beardsley, Paula, Fine, Denise, Salerno, William D., Tancredi, Jana, Arakelian, Patricia, Mathus, Susan, O’Neill, Deborah, Wyman, Ray, Burkhardt, Joy, Hosino, Suellen, Lubyanaya, Oksana A., Salas, Jose D., Zarka, Amer, Aguirre, Maria, Shah, Anil V., Dhawan, Manu, Parra, Diana, Tran, Tri, Haldis, Thomas, Weick, Catherine, Fowler-Lehman, Katie, Spitzer, Natalie, Riedberger, Casey, Weick, Catherine, Kohn, Jeffrey A., Cobos, Stanley E., Dwyer, Raven R., Espinosa, Dalisa, Quiles, Kirsten J., Girotra, Saket, Drum, Carrie, Miller-Cox, Kimberly, Ollinger, Amy, Almousalli, Omar, Capasso-Gulve, Elizabeth, Melanie Loehr, Alaine, Mosley, Marlowe, Krishnam, Mayil S., Heydari, Shirin, Milliken, Jeffrey C., Lundeen, Andrea M., Patel, Pranav M., Karanjah, Edgar, Seto, Arnold H., Marfori, Wanda C., Harley, Kevin T., Hernandez-Rangel, Eduardo, Gibson, Michael A., Singh, Pam, Allen, Byron J., Coram, Rita, Marie Webb, Anne, Fridell, Ellie, Wilson, Heidi, Thomas, Sabu, Kim, Angela, Schwartz, Ronald G, Wilmot, Patrick, Chen, Wei, El Shahawy, Mahfouz, Stevens, Ramona, Stafford, James, Black, Loriane, Abernethy, William B., Hull, Amber B., Lim, Olivia J., Tucker, Helen C., Putnam, Natasha C., Hall, Linda L., Cauthren, Tia, Tucker, Trish, Zurick, Andrew, Horton, Hollie, Orga, Jan, Meyer, Thomas M., White, Joyce R., Morford, Ronald G., Baumann, Cynthia, Rutkin, Bruce, Seeratan, Vidya, Bokhari, Sabahat, Jimenez, Magnolia, Sokol, Seth I., Schultz, Cidney, Meisner, Jay, Russo, Jeanne, Hamzeh, Ihab, Misra, Arunima, Huda, Zohra, Wall, Matthew, Boan, Araceli, Lenges De Rosen, Veronica, Alam, Mahboob, Turner, Michael C., Hinton, Christine R, Mulhearn, Thomas J., Good, Arnold P., Archer, Beth A., Dionne, Julia S., Allardyce, Cheryl A., Sikora, Lindsey N., Czerniak, Jennifer H., Mull, Jennifer A., Ferguson, Elizabeth, Laube, Frances, Shammas, Nicolas W., Shammas, Gail A, Christensen, Lori, Park, Holly, Chilton, Robert, Hecht, Joan, Nguyen, Patricia K., Vo, Davis, Hirsch, James, Jezior, Matthew, Bindeman, Jody, Salkind, Sara, Espinosa, Dalisa, Desimone, Lori-Ann, Gordon, Paul C., Felix-Stern, Lina, Crain, Thomas, Gomes, Jassira, Gordon, Catherine, Stenberg, Robert, Mann, Aimee, McCreary, Theresa, Pedalino, Ronald P., Cobos, Stanley E., Dwyer, Raven R., Espinosa, Dalisa, Quiles, Kirsten J., Wiesel, Joseph, Cobos, Stanley E., Dwyer, Raven R., Espinosa, Dalisa, Quiles, Kirsten J., Juang, George J., Gopaul, Candace, Hultberg, Karen, Huk, Tauqir, Hussain, Afshan, Al-Amoodi, Mohammed, Zambrano, Yesenia, Medina Rodriguez, Sarah, Milner, Trudie, Wohns, David, Mulder, Abbey, Van Oosterhout, Stacie, Lader, Ellis W., Meyer, Martha, Mumma, Michael, Clapp, Nancy L., Barrentine, Heather, Dharmarajan, Lekshmi, Jose, Jenne M., Cobos, Stanley E., Dwyer, Raven R., Espinosa, Dalisa, Quiles, Kirsten J., Manchery, Jenne, McGarvey Jr, Joseph F.X., McKinney, Vera, Schwarz, Linda, Downes, Thomas R., Kaczkowski, Scott M., Luckasen, Gary J., Jaskowiak, Adam J., Klitch, Joel, Cheong, Benjamin, Dees, Debra, Potluri, Srinivasa, Vasquez, Precilia, Mastouri, Ronald A., Breall, Jeffery A., Hannemann, Elise L., Revtyak, George E., Mae Foltz, Judy, Bazeley, Jonathan W., Li, Dayuan, DeRosa, Emily, Jorgenson, Beth, Riestenberg-Smith, Joyce, Giedd, Kenneth, Old, Wayne, Bariciano, Rebecca, Burt, Francis, Sokhon, Kozhaya, Waldron, Jessica, Mayon, Michelle, Gopal, Deepika, Valeti, Uma S., Ann Peichel, Gretchen, Kobashigawa, Jon, Starks, Brandy, Garcia, Lucilla, Thottam, Maria, Bhargava, Balram, Anand, Anjali, Chakanalil Govindan, Sajeev, Raj, Janitha, Gopalan Nair, Rajesh, Ravindran, Reshma, Rajalekshmi, VS, Nataraj, Nandita, Moorthy, Nagaraja, Nayak, Soundarya, Mylarappa, Mahevamma, Narayanappa, Suryaprakash, Pandit, Neeraj, Bajaj, Sheromani, Kumar Nath, Ranjit, Yadav, Vandana, Mishra, Girish, Dwivedi, S.K., Tewari, Roma, Narain, V.S., Mishra, Meenakshi, Chandra, Sharad, Patel, Shivali, Singh, Suman, Wander, Gurpreet S., Tandon, Rohit, Ralhan, Sarju, Kaur, Baljeet, Aslam, Naved, Gupta, Sonika, Goyal, Abhishek, Bhargava, Balram, Suvarna, Chandini, Karthikeyan, G., Ramakrishnan, S., Seth, Sandeep, Yadav, Rakesh, Singh, Sandeep, Roy, Ambuj, Parakh, Neeraj, Kumar Verma, Sunil, Narang, Rajiv, Mishra, Sundeep, Naik, Nitish, Sharma, Gautam, Kumar Choudhary, Shiv, Patel, Chetan, Gulati, Gurpreet, Sharma, Sanjeev, Bahl, V K, Mathew, Anoop, Mannekkattukudy Kurian, Binoy, Punnoose, Eapen, Avdhoot Gadkari, Milind, Rupesh Karwa, Sheetal, Gadage, Siddharth, Kolhe, Suvarna, Umesh Pillay, Tapan, Satheesh, Santhosh, Vindhya, R. J., Jain, Peeyush, Seth, Ashok, Singh Meharwal, Zile, Mathur, Atul, Verma, Atul, Kaul, Upendra, Bhatia, Mona, Sachdeva, Ankush, Indira Devi, Thounaojam, Jungla, Nungshi, Christopher, Johann, Manjula Rani, K., Menon, Rajeev, Sowjanya Reddy, M., Kumar, Nirmal, Preethi, K., Oomman, Abraham, sidh, Rinu R, Mao, Robert, Ramakrishnan, T., Solomon, Hilda, Francis, Rajesh, Naik, Sudhir, Vamshi, Priya P., Parveen Khan, Sajeeda, Christopher, Johann, Preethi, Kotiboinna, Kumar, Nirmal, Grant, Purvez, Hande, Shweta, Sonawane, Poonam, Kachru, Ranjan, Dubey, Abhishek, Rawat, Kavita, Kumar, Ajit, Ganapathi, Sanjay, K, Jayakumar, CP, Vineeth, Sivadasanpillai, Harikrishnan, Chacko, Manas, Sasidharan, Bijulal, Babu, Suresh, TR, Kapilamoorthy, Christopher, Johann, Reddy, Sowjanya, Polamuri, Praneeth, Rani, Manjula, Kaul, Upendra, Arambam, Priyadarshani, Singh, Bebek, Senior, Roxy, Fox, Keith AA, Young, Grace M., Carruthers, Kathryn, Senior, Roxy, Elghamaz, Ahmed, Gurunathan, Sothinathan, Karogiannis, Nikolaos, Young, Grace M., Shah, Benoy N, Kinsey, Christopher, Trimlett, Richard HJ, Kavalakkat, Raisa, Rubens, Michael B, Evans, Jo, Nicol, Edward D, Hassan, Ikraam, Mittal, Tarun K, Hampson, Reinette, Andreas Gamma, Reto, Williams, Sarah, Holland, Kim, Swan, Karen, de Belder, Mark A, Atkinson, Bev, Thambyrajah, Jeet, Kunhunny, Swapna, Davies, John R, Lindsay, Steven J., Atkinson, Craig, Kurian, John, Krannila, Carita, Jamil, Haqeel, Vinod, Manitha, Raheem, Osama, Hoye, Angela, Chaytor, Lisa, Cox, Leanne, Morrow, Julie, Rowe, Kay, Donnelly, Patrick, Kelly, Stephanie, Valecka, Bernardas, Regan, Susan, Turnbull, Dawn, Chauhan, Anoop, Fleming, Catherine, Ghosh, Arijit, Gratrix, Karen, Preston, Stephen, Barr, Craig, Cartwright, Anne, Alfakih, Khaled, Knighton, Abigail, Byrne, Jonathan, Martin, Katherine, Webb, Ian, Henriksen, Peter, Flint, Laura, Harrison, James, OKane, Peter, Lakeman, Nicki, Ljubez, Anja, de Silva, Ramesh, Conway, Dwayne S. G., Wright, Judith, Exley, Donna, Sirker, Alexander A, Andiapen, Mervyn, Richards, Amy J., Hoole, Stephen P, Wong, Lisa, Witherow, Fraser N., Munro, Melanie J., Johnston, Nicola, Harbinson, Mark, McEvoy, Michelle, Walsh, Simon, Brown, Caroline, Douglas, Hanna, Luckie, Matthew, Charles, Thabitha, Kolakaluri, Laurel, Phillips, Hannah, Sobolewska, Jolanta, Morby, Louise, Hallett, Karen, Corbett, Carolyn, Winstanley, Lynne, Jeetley, Paramjit, Smit, Angelique, Patel, Niket, Kotecha, Tushar, Travill, Christopher, Gent, Susan, Karimullah, Iqbal, Hussain, Nafisa, Al-Bustami, Mahmud, Braganza, Denise, Haines, Fiona, Taaffe, Joanne, Henderson, Robert, Burton, Jane, Pointon, Kate, Colton, Maria, Naik, Surendra, King, Rachel, Mathew, Thomas, Brown, Ammani, Docherty, Andrew, Berry, Colin, McCloy, Lisa, Collison, Damien, Robb, Kate, Roditi, Giles, Paterson, Craig, Crawford, Wenda, Kelly, Joanne, McGregor, Lorraine, Moriarty, Andrew J, Mackin, Anne, Glover, Jason D., Knight, Janet P, Pradhan, Jiwan, Mikhail, Ghada, Bose, Tuhina, Francis, Darrel P., Dzavik, Vladimir, Goodman, Shaun, Gosselin, Gilbert, Gosselin, Gilbert, Proietti, Anna, Brousseau, Myriam, Corfias, Magalie, Blaise, Patricia, Harvey, Luc, Diaz, Ariel, Rheault, Philippe, Barrero, Miguel, Gagné, Carl-Éric, Alarie, Patricia, Pépin-Dubois, Yanek, Arcand, Linda, Costa, Ricardo, Roy, Isabelle, Tung Sia, Ying, Montpetit, Estelle, Lemay, Catherine, Gisbert, Alejandro, Gervais, Pierre, Rheault, Alain, Drouin, Katia, Carl Phaneuf, Denis, Bergeron, Christine, Gosselin, Gilbert, Shelley, Christine, Masson, Christine, Garg, Pallav, Carr, Sandy, Bone, Catherine, Chow, Benjamin J.W., Moga, Ermina, Hessian, Renee C., Kourzenkova, Janetta, Beanlands, Rob S., Walter, Olga, Davies, Richard F., Bainey, Kevin R., Hogg, Norma, Welsh, Suzanne, Cheema, Asim N., Bagai, Akshay, Wald, Ron, Goodman, Shaun, Kushniriuk, Khrystyna, Joseph Graham, John, Hussain, Mohammed, Peterson, Mark, Bello, Olugbenga, Chow, Chi-Ming, Abramson, Beth, Nazir Cheema, Asim, Syed, Ishba, Hussain, Mohammed, Kushniriuk, Khrystyna, Cha, James, Otis, Judy, Otis, Rebecca, Howarth, Andrew G, Seib, Michelle M, Rivest, Sandra M, Sandonato, Rosa, Wong, Graham, Chow, Jackie, Starovoytov, Andrew, Uchida, Naomi, Meadows, Ngaire, Uxa, Amar, Asif, Nadia, Tavares, Suzana, Galiwango, Paul, Bozek, Bev, Kassam, Saleem, Shier, Maria, Mukherjee, Ashok, Larmand, Lori-Ann, Ricci, A. Joseph, Janmohamed, Amir, Hart, Brenda, Lam, Andy, Marucci, Jane, Tai, Sharon, Mehta, Shamir, Brons, Sonya, Beck, Chris, Wong, Glenda, Etherington, Krystal, Arumairajah, Thippeekaa, Udell, Jacob, Aprile, Maria, Karlsson, Sara, Webber, Susan, Généreux, Philippe, Mercure, Chantale, Hameed, Adnan, Aedy, Nancy, Daba, Ledjalem, Farquharson, Fran, Siddiqui, Anam, Carlos Carvalho, Antonio, Lopes, Renato D., Hueb, Whady, Emy Takiuti, Myrthes, Cury Rezende, Paulo, Eustáquio Ribeiro Silva, Expedito, Ciappina Hueb, Alexandre, Pizzol Caetano, Leonardo, Schaan de Quadros, Alexandre, Abdala Karam Kalil, Renato, Peixoto Deiro, Aline, Luiz da Costa Vieira, José, Manica Muller, Alice, Antonieta Pereira de Moraes, Maria, Píccaro de Oliveira, Pedro, Maria Ascoli, Bruna, Bridi, Leonardo, Zottis Poletti, Sílvia, Savaris, Simone, Vitola, João V, Cerci, Rodrigo J, Zier, Sandra S., Farias, Fabio R, Veiga Jr, Vilmar, Fernandes, Miguel M, Antonio Marin-Neto, José, Schmidt, André, de Oliveira Lima Filho, Moysés, Franca da Cunha, Diego, Mendes Oliveira, Ricardo, Reynaldo Abbud Chierice, João, Polanczyk, Carísi A., Rucatti, Guilherme G, Furtado, Mariana V., Igansi, Fernanda, Smidt, Luis F., Haeffner, Mauren P, Carlos Carvalho, Antonio, Almeida, Viviane, Pucci, Gustavo, Sanchez de Souza, Gabriela, Lyra, Flavio, Rabelo Alves Junior, Alvaro, Almeida, Mayana, dos Santos, Viviane, Dracoulakis, Marianna D. 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Marin, Valdés Chávarri, M., Quintana Giner, M., Tello Montolliu, A., Romero Aniorte, A.I., Pinar Bermudez, E., Rivera Caravaca, JM., De La Morena, G., Gracida Blancas, Montserrat, Cañavate, Olga, Guerrero, Sonia, Riera, Silvia, Enrique Castillo Luena, Jose, Enrique Castillo Luena, Jose, Lasala, Maria, Fernandez-Aviles, Francisco, Lorenzo, Maria, Sobrino, Olga, Vazquez, Alexandra, Jiang, Lixin, Chen, Jiyan, Dong, Haojian, He, Peiyu, Xia, Chunli, Yang, Junqing, Zhong, Qi, Wu, Yongjian, Tian, Yanmeng, Li, Dongze, Ma, Yitong, Li, Xiaomei, Yang, Yining, Ma, Xiang, Yu, Zixiang, Zhao, Qian, Ji, Zheng, Li, Chunguang, Zhang, Lei, Zhao, Yu, Zhu, Bolin, Yang, Xinchun, Chen, Mulei, Chi, Hongjie, Wang, Yang, Zhang, Jing, Lin, Wenhua, Jing, Rui, Liu, Jingjing, Zeng, Hesong, Zhou, Qiang, Xu, Chang, Li, Zhuxi, Li, Junhua, Xiong, Luyang, Fu, Xin, Gao, Dan, Jiang, Dengke, Leng, Ran, Wang, Xutong, Yuan, Qianqian, Zhang, Lili, Yang, Bin, Bai, Ziliang, Li, Jianhua, Qi, Jie, Wang, Fei, Wang, Haitao, Yang, Bin, Yue, Zhou, Zhang, Zhulin, Wang, Songtao, Dong, Yumei, Mao, Jiajia, Zhang, Bin, Cheng, Gong, Li, Xiuhong, Yao, Xiaowei, Zhong, Nier, Zhou, Ning, Zhao, Yulan, Huang, Yaping, Zhou, Panpan, Fang, Xuehua, Su, Wei, Zeng, Qiutang, Kunwu, Yu, Peng, Yudong, Su, Xin, Su, Xi, Wang, Chen, Zhao, Yunhai, Li, Qingxian, Geng, Yaming, Wang, Yanfu, Nie, Shao-ping, Fan, Jing-yao, Feng, Si-ting, Wang, Xiao, Yan, Yan, Zhang, Hui-min, Yu, Qin, Chi, Lingping, Liu, Fang, Wang, Jian’an, Chen, Han, Jiang, Jun, Li, Huajun, Wang, Jian’an, Han, Yechen, Xu, Lihong, Zhang, Shuyang, Liu, Zhenyu, Liu, Zhenyu, Chen, Gang, Hu, Rongrong, Maggioni, Aldo P., Piero Perna, Gian, Pietrucci, Francesca, Marini, Marco, Gabrielli, Gabriele, Provasoli, Stefano, Di Donato, Anna, Verna, Edoardo, Monti, Lorenzo, Nardi, Barbara, Di Chiara, Antonio, Pezzetta, Francesca, Mortara, Andrea, Casali, Valentina, Galvani, Marcello, Attanasio, Chiara, Ottani, Filippo, Sicuro, Marco, Leone, Gianpiero, Pisano, Francesco, Bare, Cristina, Calabro, Paolo, Fimiani, Fabio, Formisano, Tiziana, Tarantini, Giuseppe, Barioli, Alberto, Cucchini, Umberto, Ramani, Federica, Luigi Andres, Anto, Racca, Emanuela, Rolfo, Fabrizio, Goletto, Cecilia, Briguori, Carlo, De Micco, Francesca, Amati, Roberto, Di Marco, Stefano, Vergoni, William, Tricoli, Martina, Russo, Aldo, Villella, Massimo, Fanelli, Raffaele, Douglas White, Harvey, Alsweiler, Caroline, Poh, Kian-Keong, Chai, Ping, Lau, Titus, Loh, Joshua P., Tay, Edgar L., Teoh, Kristine, Tan, Sik-Yin V, Teo, Lynette L., Sia, Winnie C, Ong, Ching-Ching, Leong, Audrey W, Wong, Raymond C., Loh, Poay-Huan, Kofidis, Theodoros, Xian Chan, Wan, Hui Chan, Koo, Foo, David, Hai Yan, Li, Loh Kwok Kong, Jason, Min Er, Ching, Haider Jafary, Fahim, Chua, Terrance, Ismail, Nasrul, Tun Kyaw, Min, Yip, Deborah, Doerr, Rolf, Doerr, Rolf, Stumpf, Juergen, Grahl, Dorit, Matschke, Klaus, Guenther, Franziska, Simonis, Gregor, Bonin, Kerstin, Kadalie, Clemens T., Sechtem, Udo, Wenzelburger, Ina, Ong, Peter, Gruensfelder, Susanne, Christian Schulze, P., Goebel, Bjoern, Lenk, Karsten, Nickenig, Georg, Sinning, Jan-Malte, Weber, Marcel, Werner, Nikos, Marthe Lang, Irene, Huber, Kurt, Schuchlenz, Herwig, Steinmaurer, Gudrun, Weikl, Stefan, Marthe Lang, Irene, Winter, Max-Paul, Andric, Tijana, Huber, Kurt, Tscharre, Maximilian, Jakl-Kotauschek, Gabriele, Wegmayr, Claudia, Jäger, Bernhard, Egger, Florian, Keltai, Matyas, Vertes, Andras, Sebo, Judit, Davidovits, Zoltan, Matics, Laszlone, Varga, Albert, Ágoston, Gergely, Fontos, Geza, Dekany, Gabor, Merkely, Bela, Bartykowszki, Andrea, Maurovich-Horvat, Pal, Kerecsen, Gabor, Jakal, Agnes, Hinic, Sasa, Djokic, Jelena, Zdravkovic, Marija, Mudrenovic, Vladan, Crnokrak, Bogdan, Beleslin, Branko D., Boskovic, Nikola N., Djordjevic-Dikic, Ana D., Petrovic, Marija T., Giga, Vojislav L., Dobric, Milan R., Stepanovic, Jelena J., Markovic, Zeljko Z., Mladenovic, Ana S., Cemerlic-Adjic, Nada, Velicki, Lazar, Kamenica, Sremska, Pupic, Ljiljana, Davidović, Goran, Simović, Stefan M., Vučić, Rada, Dekleva, Milica Nikola, Martinovic, Miroslav Stevo, Stevanovic, Gordana, Stankovic, Goran, Dobric, Milan, Apostolovic, Svetlana, Martinovic, Sonja Salinger, Stanojevic, Dragana, Escobedo, Jorge, Jesús-Pérez, Ramon de, Juarez, Benito, Baleón-Espinosa, Rubén, Campos-Santaolalla, Arturo S, Durán-Cortés, Elihú, Flores-Palacios, José M, García-Rincón, Andrés, Jiménez-Santos, Moisés, Peñafiel, Joaquín V, Ortega-Ramírez, José A, Valdespino-Estrada, Aquiles, Rosas, Erick Alexánderson, Canales Brassetti, María Fernanda, Vences Anaya, Diego Adrián, García, María Pérez, Carvajal Juarez, Isabel Estela, Rovalo, Magdalena Madero, Morales Rodríguez, Erick Donato, Selvanayagam, Joseph B., Rankin, Jamie, Murphy, Deirdre, Selvanayagam, Joseph B., Lee, Sau, Joseph, Majo X., Thomas, Prince, Thambar, Suku T., Chaplin, Melissa D, Boer, Stephanie C, Beltrame, John F., Stansborough, Jeanette K., Black, Marilyn, Hillis, Graham S., Bonner, Michelle M., Ireland, Kim F., Venn-Edmonds, Clare, Steg, Philippe-Gabriel, Abergel, Helene, Juliard, Jean-Michel, Thobois, Corine, Pasteur, C.H. Louis, Thuaire, Christophe, Tachot, Emilie, Dutoiu, Téodora, Laure, Christophe, Vassaliere, Christel, Steg, Philippe Gabriel, Abergel, Helene, Juliard, Jean-Michel, Fuentes, Axelle, Slama, Michel S., Eliahou, Ludivine, Cedex, Clamart, El Mahmoud, Rami, Dubourg, Olivier, Michaud, Pierre, Nicollet, Eric, Hadjih, Sarah, Cedex, Corbeil-Essonnes, Goube, Pascal, Brito, Patricia, Barone-Rochette, Gilles, Barone-Rochette, Gilles, Furber, Alain, Cornet, Charles, Bière, Loïc, Rautureau, Jeremy, Juceviciene, Agne, Kalibataite-Rutkauskiene, Irma, Keinaite, Laura, Laucevicius, Aleksandras, Laukyte, Monika, Celutkiene, Jelena, Mikolaitiene, Gelmina, Smigelskaite, Akvile, Tamasauskiene, Ilona, Urboniene, Agne, Kedhi, Elvin, Klinieken, Isala, Timmer, Jorik, Bouwhuis, Ilse, Hermanides, Rik, Nijmeijer, Lia, Kaplan, Eliza, Riezebos, Robert K., Samadi, Pouneh, Schoep Jeannette, J. M., Dongen, Elise van, Janzen, Elisabeth M., Niehe, Sander R., Suryapranata, Harry, Ahoud, Sandra, Vugt, Stijn van, Ramos, Ruben, Santa Marta, Hospital de, Cacela, Duarte, Santana, Ana, Fiarresga, Antonio, Sousa, Lidia, Marques, Hugo, Patricio, Lino, Selas, Mafalda, Bernanrdes, Luis, Silva, Filipa, Rio, Pedro, Freixo, Cláudia, Carvalho, Ramiro, Ferreira, Rui, Silva, Tiago, Rodrigues, Ines, Modas, Pedro, Portugal, Guilherme, Fragata, Jose, Pinto, Fausto J., Cabrita, Inês Zimbarra, Menezes, Miguel Nobre, Rocha, Andreia, Lopes, Guilhermina Cantinho, Figueiras, Francisca Patuleia, Almeida, Ana Gomes, Coelho, Andreia, CanVas Silva, Pedro, Capinha, Marta, Nobre, Angelo, Caetano, Maria Inês, Francisco, Ana Rita, Silva, Susana, Ferreira, Nuno, de Gaia, Vila Nova, Lopes, Ricardo L., Diaz, Rafael, Guzman, Luis, Tinnirello, Veronica, Figal, Julio César, Nicolás Mungo, Matías, Buenos Aires, Ciudad Autonoma de, Méndiz, Oscar, Cortés, Claudia, Favaloro, Roberto René, Alvarez, Carlos, Garcia, Marina, Blanca, Bahia, Courtis, Javier, Godoy, Valeria, Zeballos, Gabriela, Schiavi, Lilia, Actis, Maria Victoria, Rubio, Mariano, Scaro, Graciela, White, Harvey Douglas, Alsweiler, Caroline, Devlin, Gerard Patrick, Low, Liz, Fisher, Raewyn, Scales, Jayne, Abercrombie, Kirsty, Stewart, Ralph Alan Huston, Howell, Leah, White, Harvey Douglas, Patten, Cathrine, Benatar, Jocelyne, Kedev, Sasko, Mitevska, Irena Peovska, Kostovska, Elizabeta Srbinovska, Pejkov, Hristo, Held, Claes, Held, Claes, Eggers, Kai, Frostfelt, Gunnar, Björklund, Christina, Johnston, Nina, Andreasson, Maria, Olsowka, Maciej, Essermark, Marie, Åkerblom, Axel, Soveri, Inga, Aspberg, Johannes, Persson, Liselotte, Beyar, Rafael, Sharir, Tali, Nikolsky, Eugenia, Sharir, Tali, Harel, Or, Elian, Dan, Kerner, Arthur, Bentzvi, Margalit, Massalha, Samia, Helmer, Ludmila, Kohsaka, Shun, Fukuda, Keiichi, Ueda, Ikuko, Kohsaka, Shun, Fujita, Jun, Yasuda, Satoshi, Furukawa, Akemi, Hirase, Kanae, Nagai, Toshiyuki, Otsuka, Fumiyuki, Nishimura, Shigeyuki, Nakano, Shintaro, de Werf, Frans Van, Goetschalckx, Kaatje, Goetschalckx, Kaatje, Robesyn, Valerie, de Werf, Frans Van, Claes, Kathleen, White, Harvey Douglas, Alsweiler, Caroline, Hung, Chung-Lieh, Yang, Yi-Hsuan, Yun, Chun-Ho, Hou, Charles Jia-Yin, Kuo, Jen-Yuan, Yeh, Hung-I, Hung, Ta-Chuan, Li, Jiun-Yi, Chien, Chen-Yen, Tsai, Cheng-Ting, Liu, Chun-Chieh, Yu, Fa-Chang, Lin, Yueh-Hung, Lan, Wei-Ren, Yen, Chih-Hsuan, Tsai, Jui-Peng, Sung, Kuo-Tzu, Ntsekhe, Mpiko, Pandie, Shaheen, Philander (Nee Talliard), Constance, Viljoen, Charle A, Mtana, Noloyiso, De Andrade, Marianne, Maggioni, Aldo P., Moccetti, Tiziano, Anesini, Adriana, Rossi, M.Grazia, Maspoli, Simona, Mombelli, Manuela, Abdelhamid, Magdy, Talaat, Ahmed, Adel, Ahmed, Kamal, Ahmed, Mahrous, Hossam, Kaffas, Sameh El, Fishawy, Hussien El, Pop, Calin, Claudia, Matei, Popescu, Bogdan A., Ginghina, Carmen, Rosca, Monica, Deleanu, Dan, Beladan, Carmen C., Iliescu, Vlad A., Al-Mallah, Mouaz H., Zahrani, Sarah, Aljzeeri, Ahmed, Najm, Hani, Alghamdi, Ali, Mogrovejo Ramos, Walter Enrique, Monsalve Davila, Marco Antonio, White, Harvey Douglas, Alsweiler, Caroline, Kuanprasert, Srun, Mai, Chiang, Prommintikul, Arintaya, Nawarawong, Weerachai, Khwakhong, Supatchara, Woragidpoonpol, Surin, Chaiyasri, Anong, Tepsuwan, Thitipong, Mekara, Warangkana, Taksaudom, Noppon, Kulthawong, Supap, Rimsukcharoenchai, Chataroon, Amaritakomol, Anong, Euathrongchit, Juntima, Wannasopha, Yutthaphan, Yamwong, Sukit, Panpunuan, Pachara, Sritara, Piyamitr, Aramcharoen, Suthara, Meemuk, Krissada, White, Harvey Douglas, Alsweiler, Caroline, Khairuddin, Ahmad, Mokhtar, Noor Syamira, Hadi, Hafidz Abd, Basri, Nor Asiah, Yahaya, Shaiful Azmi, Yusnida, Irni, Hashim, Humayrah, Harrington, Robert, Williams, David, Alexander, Karen P., Berger, Jeffrey, Harrington, Robert, Mark, Daniel, O’Brien, Sean M., Rosenberg, Yves, Shaw, Leslee J., Ballantyne, Christie, Berman, Daniel, Beyar, Rafael, Bhargava, Balram, Buller, Chris, (Tony) Carvalho*, Antonio, Chaitman, Bernard R., Diaz, Rafael, Doerr, Rolf, Dzavik, Vladimir, Goodman, Shaun, Gosselin, Gilbert, Hachamovitch, Rory, Hamm, Christian, Held, Claes, Helm, Malte, Huber, Kurt, Jiang, Lixin, Keltai, Matyas, Kohsaka, Shun, Lang, Irene, Lopes, Renato, Lopez-Sendon, Jose, Maggioni, Aldo, Bairey Merz, C. Noel, Min, James, Peterson, Eric, Picard, Michael H., Selvanayagam, Joseph, Senior, Roxy, Sharir, Tali, Steg, Gabriel, Szwed, Hanna, de Werf, Frans Van, Weintraub, William, White, Harvey, Williams, David, Ballantyne, Christie, Calfas*, Karen, Chaitman, Bernard R., Champagne, Mary Ann, Davidson, Michael, Fleg, Jerome, McCullough, Peter A., Stone, Peter, Menasche, Philippe, Davidson*, Michael, Fremes, Stephen, Guyton, Robert, Mack, Michael, Mohr, Fred, Rao, Anupama, Sabik, Joe, Shapira, Oz, Taggart, David, Tatoulis, James, Williams, David, Blankenship, Jim, Brener, Sorin, Buller, Chris, Colombo, Antonio, Bruyne, Bernard de, Généreux, Philippe, Harrington, Robert, Kereiakes, Dean, Lefevre, Thierry, Moses, Jeffrey, Chaitman, Bernard R., Alexander, Karen P., Mahaffey, Ken, White, Harvey, Chaitman, Bernard R., Cruz-Flores, Salvador, Danchin, Nicholas, Feen, Eli, Garcia, Mario J., Hauptman, Paul, Laddu, Abhay A., Passamani, Eugene, Pina, Ileana L., Simoons, Maarten, Skali, Hicham, Thygesen, Kristian, Waters, David, Alexander, Karen P., Endsley, Patricia, Esposito, Gerard, Kanters, Jeffrey, Pownall, John, Stournaras, Dimitrios, Shaw, Leslee J., Berman, Daniel, Friedrich, Matthias, Hachamovitch, Rory, Kwong, Raymond, Min, James, Oliver, Dana, Picard, Michael H., Harrell, Frank, Blume, Jeffrey, Lee, Kerry, O’Brien, Sean M., Berger, Jeffrey, Held, Claes, Kullo, Iftikhar, McManus, Bruce, Newby, Kristin, Mark, Daniel, Cohen, David, Weintraub, William, Merz, C. Noel Bairey, Bugiardini, Raffaele, Celutkiene, Jelena, Escobedo, Jorge, Hoye, Angela, Lyubarova, Radmila, Mattina, Deirdre, Peteiro, Jesus, Alexander, Karen P., Berger, Jeffrey, Harrington, Robert, O’Brien, Sean M., Rosenberg, Yves, Mark, Daniel, Mark, Daniel, Shaw, Leslee J., Berman, Dan, Chaitman, Bernard R., Fleg, Jerome, Kwong, Raymond, Picard, Michael H., Senior, Roxy, Min, James, Leipsic, Jonathan, Ali, Ziad, Williams, David, Fleg, Jerome, Berger, Jeffrey, Chaitman, Bernard R., Alexander, Karen P., Alexander, Karen P., Fleg, Jerome, Mathew, Roy, O’Brien, Sean M., Sidhu, Mandeep, Friedman, Lawrence, Anderson, Jeffrey, Berg, Jessica, DeMets, David, Gibson, C. Michael, Lamas, Gervasio, Deming, Nicole, Himmelfarb, Jonathan, Ouyang, Pamela, Woodard, Pamela, Harrell, Frank, Nwosu, Samuel, Rosenberg, Yves, Fleg, Jerome, Kirby, Ruth, Jeffries, Neal, Berger, Jeffrey, Sidhu, Mandeep, Denaro*, Jean E., Mavromichalis, Stephanie, Chan, Kevin, Cobb, Gia, Contreras, Aira, Cukali, Diana, Ferket, Stephanie, Gabriel, Andre, Hansen, Antonietta, Roberts, Arline, Chang, Michelle, Islam, Sharder, Wayser, Graceanne, Yakubov, Solomon, Yee, Michelle, Callison, Caroline, Hogan, Isabelle, Qelaj, Albertina, Pirro, Charlotte, Loo, Kerrie Van, Wisniewski, Brianna, Gilsenan, Margaret, Lang, Bevin, Mohamed, Samaa, Esquenazi-Karonika, Shari, Mathews, Patenne, Naumova, Anna, Lyo, Jihyun, Setang, Vincent, Xavier, Mark, O’Brien, Sean M., Alexander, Karen P., Mark, Daniel B., Anstrom, Kevin, Baloch, Khaula, Blount, Janet, Cowper, Patricia, Davidson-Ray, Linda, Drew, Laura, Harding, Tina, Knight, J David, Liu, Diane Minshall, O’Neal, Betsy, Redick, Thomas, Jones, Philip, Nugent, Karen, Wang, Grace Jingyan, Shaw, Leslee J., Phillips, Lawrence, Goyal, Abhinav, Hetrick, Holly, Oliver, Dana, Berman, Daniel, Hayes, Sean W., Friedman, John D., Gerlach, R. James, Hyun, Mark, Miranda-Peats, Romalisa, Slomka, Piotr, Thomson, Louise, Kwong, Raymond Y., Friedrich, Matthias, Mongeon, Francois Pierre, Michael, Steven, Picard, Michael H., Hung, Judy, Scherrer-Crosbie, Marielle, Zeng, Xin, Chaitman, Bernard R., Eckstein, Jane, Guruge, Bandula, Streif, Mary, Ali, Ziad, Genereux, Philippe, Alfonso, Maria A., Corral, Maria P., Garcia, Javier J., Horst, Jennifer, Jankovic, Ivana, Konigstein, Maayan, Lustre, Mitchel B., Peralta, Yolayfi, Sanchez, Raquel, Min, James, Arsanjani, Reza, Budoff, Matthew, Elmore, Kimberly, Gomez, Millie, Hague, Cameron, Hindoyan, Niree, Leipsic, Jonathan, Nakanishi, Rine, Srichai-Parsia, M. Barbara, Yeoh, Eunice, Youn, Tricia, Maggioni, Aldo P., Bianchini, Francesca, Ceseri, Martina, Lorimer, Andrea, Magnoni, Marco, Orso, Francesco, Sarti, Laura, Tricoli, Martinia, Carvalho, Antonio, Lopes, Renato, Barbosa, Lilian Mazza, Duarte, Tauane Bello, Soares, Tamara Colaiácovo, Aveiro Morata, Julia de, Carvalho, Pedro, Carvalho Maffei, Natalia de, Egydio, Flávia, Kawakami, Anelise, Oliveira, Janaina, Piloto, Elissa Restelli, Pozzibon, Jaqueline, Goodman, Shaun, Camara, Diane, Mowafy, Neamat, Spindler, Caroline, Jiang, Lixin, Dai, Hao, Feng, Fang, Li, Jia, Li, Li, Liu, Jiamin, Xie, Qiulan, Zhang, Haibo, Zhang, Jianxin, Zhang, Lihua, Zhang, Liping, Zhang, Ning, Zhong, Hui, Diaz, Rafael, Escobar, Claudia, Martin, Maria Eugenia, Pascual, Andrea, Lopez-Sendon, José, Moraga, Paloma, Hernandez, Victoria, Castro, Almudena, Posada, Maria, Fernandez, Sara, Villanueva, José Luis Narro, Selgas, Rafael, Steg, Gabriel, Abergel, Helene, Juliard, Jean Michel, White, Harvey, Alsweiler, Caroline, de Werf, Frans Van, Claes, Kathleen, Goetschalckx, Kaatje, Luyten, Ann, Robesyn, Valerie, Selvanayagam, Joseph B., Murphy, Deirdre, Ahmed, Asker, Bhatt, Richa, Chadha, Nitika, Kumar, Vijay, Lubna, Sadath, Naik, Pushpa, Pandey, Shruti, Ramasamy, Karthik, Saleem, Mohammed, Sharma, Pratiksha, and Siddaram, Hemalata

Published
2024
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28. Professional Competence for Clinicians: Assessment Methods and Research Progress

Author

ZHANG Hanlin, HE Zitang, LI Yue, LUO Linzhi, and ZHANG Shuyang

Subjects
physician, professional competence, medical education, position evaluation, Medicine
Abstract

Professional competence is defined as the habitual and judicious use of communication, knowledge, technical skills, clinical reasoning, emotions, values, and reflection in daily clinical practice. At present, many studies focus on the application of professional competence to medical education and job evaluation in China. However, further theoretical and empirical research is still needed to facilitate Chinese medical education and physician career development in the future. This article reviews the assessment methods and dimensions of professional competence, as well as the research progress of professional competence in China, with the aim of providing reference for Chinese medical education and physician career development.

Published
2023
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39. Influence of Roughness on Granular Avalanches

Author

Zheng, Jie, Xing, Yi, Yuan, Ye, Li, Zhifeng, Zeng, Zhikun, Zhang, Shuyang, Yuan, Houfei, Tong, Hua, Xia, Chengjie, Kob, Walter, Jia, Xiaoping, Zhang, Jie, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Disordered Systems and Neural Networks
Abstract

Combining X-ray tomography with simultaneous shear force measurement, we investigate shear-induced granular avalanches using spherical particles with different surface roughness. We find that systems consisting of particles with large surface roughness display quasi-periodic avalanches interrupted by crackling-like small ones. In contrast, systems consisting of particles with small roughness display no detectable avalanches. The stress drop of quasi-periodic avalanche shows a linear relation with the correlation length of particle non-affine displacement, suggesting that roughness enhances inter-particle locking and hence particle-level dynamic correlation length. However, the nonaffine displacement is two orders of magnitude smaller than particle size, indicating that stress is mainly released on the length scale of roughness. The correlation length of non-affine displacements abruptly increases when a quasi-periodic avalanche occurs, suggesting that quasi-periodic avalanches can be interpreted as a spinodal nucleation event in a first-order phase transition., Comment: 22 pages, 7 figures

Published
2021

46. Experimental Test on Edwards Volume Ensemble of Tapped Granular Packings

Author

Yuan, Ye, Xing, Yi, Zheng, Jie, Li, Zhifeng, Yuan, Houfei, Zhang, Shuyang, Zeng, Zhikun, Xia, Chengjie, Tong, Hua, Kob, Walter, Zhang, Jie, and Wang, Yujie

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics
Abstract

Using X-ray tomography, we experimentally investigate granular packings subject to mechanical tapping for three types of beads with different friction coefficients. We validate Edwards volume ensemble in these three-dimensional granular systems and establish a granular version of thermodynamic zeroth law. Within Edwards framework, we also explicitly clarify how friction influences granular statistical mechanics as modifying the density of states, which allows us to determine the entropy as a function of packing fraction and friction subsequently. Additionally, we obtain a granular jamming phase diagram based on geometric coordination number and packing fraction., Comment: 20 pages, 7 figures

Published
2021
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47. A Partitioned Detection Architecture for Oriented Objects

Author

Zhang, Shuyang, Wei, Yuntao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Iliadis, Lazaros, editor, Papaleonidas, Antonios, editor, Angelov, Plamen, editor, and Jayne, Chrisina, editor

Published
2023
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48. The Development of Guidelines for Rare Diseases: Past, Present and Future

Author

ZHOU Qi, LI Qinyuan, LIU Yali, LUO Zhengxiu, ZHANG Weishe, CHEN Tong, LI Guobao, SHANG Hongcai, YANG Kehu, ZHANG Bo, CHEN Yaolong, and ZHANG Shuyang

Subjects
rare diseases, clinical practice guideline, guideline development, Medicine
Abstract

Although the incidence of rare diseases is extremely low, 6% to 8% of the global population are affected by more than 7000 rare diseases. Rare diseases guidelines are playing an increasingly important role as guiding documents in improving the health outcomes of patients with rare diseases. Therefore, we aim to systematically elaborate on the status quo, challenges and opportunities of rare disease guidelines at home and abroad, and put forward thoughts and suggestions on promoting the development of rare diseases guidelines in the future.

Published
2023
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50. Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation

Author

Zhang, Jingyang, Wang, Guotai, Xie, Hongzhi, Zhang, Shuyang, Huang, Ning, Zhang, Shaoting, and Gu, Lixu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The segmentation of coronary arteries in X-ray angiograms by convolutional neural networks (CNNs) is promising yet limited by the requirement of precisely annotating all pixels in a large number of training images, which is extremely labor-intensive especially for complex coronary trees. To alleviate the burden on the annotator, we propose a novel weakly supervised training framework that learns from noisy pseudo labels generated from automatic vessel enhancement, rather than accurate labels obtained by fully manual annotation. A typical self-paced learning scheme is used to make the training process robust against label noise while challenged by the systematic biases in pseudo labels, thus leading to the decreased performance of CNNs at test time. To solve this problem, we propose an annotation-refining self-paced learning framework (AR-SPL) to correct the potential errors using suggestive annotation. An elaborate model-vesselness uncertainty estimation is also proposed to enable the minimal annotation cost for suggestive annotation, based on not only the CNNs in training but also the geometric features of coronary arteries derived directly from raw data. Experiments show that our proposed framework achieves 1) comparable accuracy to fully supervised learning, which also significantly outperforms other weakly supervised learning frameworks; 2) largely reduced annotation cost, i.e., 75.18% of annotation time is saved, and only 3.46% of image regions are required to be annotated; and 3) an efficient intervention process, leading to superior performance with even fewer manual interactions.

Published
2020
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