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1. Diffusion Models for Intelligent Transportation Systems: A Survey

Author

Peng, Mingxing, Chen, Kehua, Guo, Xusen, Zhang, Qiming, Lu, Hongliang, Zhong, Hui, Chen, Di, Zhu, Meixin, and Yang, Hai

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Intelligent Transportation Systems (ITS) are vital in modern traffic management and optimization, significantly enhancing traffic efficiency and safety. Recently, diffusion models have emerged as transformative tools for addressing complex challenges within ITS. In this paper, we present a comprehensive survey of diffusion models for ITS, covering both theoretical and practical aspects. First, we introduce the theoretical foundations of diffusion models and their key variants, including conditional diffusion models and latent diffusion models, highlighting their suitability for modeling complex, multi-modal traffic data and enabling controllable generation. Second, we outline the primary challenges in ITS and the corresponding advantages of diffusion models, providing readers with a deeper understanding of the intersection between ITS and diffusion models. Third, we offer a multi-perspective investigation of current applications of diffusion models in ITS domains, including autonomous driving, traffic simulation, trajectory prediction, and traffic safety. Finally, we discuss state-of-the-art diffusion model techniques and highlight key ITS research directions that warrant further investigation. Through this structured overview, we aim to provide researchers with a comprehensive understanding of diffusion models for ITS, thereby advancing their future applications in the transportation domain., Comment: 7 figures

Published
2024

2. How to predict on-road air pollution based on street view images and machine learning: a quantitative analysis of the optimal strategy

Author

Zhong, Hui, Chen, Di, Wang, Pengqin, Wang, Wenrui, Shen, Shaojie, Liu, Yonghong, and Zhu, Meixin

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

On-road air pollution exhibits substantial variability over short distances due to emission sources, dilution, and physicochemical processes. Integrating mobile monitoring data with street view images (SVIs) holds promise for predicting local air pollution. However, algorithms, sampling strategies, and image quality introduce extra errors due to a lack of reliable references that quantify their effects. To bridge this gap, we employed 314 taxis to monitor NO, NO2, PM2.5 and PM10 dynamically and sampled corresponding SVIs, aiming to develop a reliable strategy. We extracted SVI features from ~ 382,000 streetscape images, which were collected at various angles (0{\deg}, 90{\deg}, 180{\deg}, 270{\deg}) and ranges (buffers with radii of 100m, 200m, 300m, 400m, 500m). Also, three machine learning algorithms alongside the linear land-used regression (LUR) model were experimented with to explore the influences of different algorithms. Four typical image quality issues were identified and discussed. Generally, machine learning methods outperform linear LUR for estimating the four pollutants, with the ranking: random forest > XGBoost > neural network > LUR. Compared to single-angle sampling, the averaging strategy is an effective method to avoid bias of insufficient feature capture. Therefore, the optimal sampling strategy is to obtain SVIs at a 100m radius buffer and extract features using the averaging strategy. This approach achieved estimation results for each aggregation location with absolute errors almost less than 2.5 {\mu}g/m^2 or ppb. Overexposure, blur, and underexposure led to image misjudgments and incorrect identifications, causing an overestimation of road features and underestimation of human-activity features, contributing to inaccurate NO, NO2, PM2.5 and PM10 estimation.

Published
2024

3. Unified study of nucleon and $\Delta$ baryon spectra and their strong decays with chiral dynamics

Author

Zhong, Hui-Hua, Liu, Ming-Sheng, Ni, Ru-Hui, Chen, Mu-Yang, Zhong, Xian-Hui, and Zhao, Qiang

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment, Nuclear Experiment, Nuclear Theory
Abstract

In this work we systematically study both the mass spectra and strong decays of the nucleon and $\Delta$ resonances up to the $N=2$ shell within a unified quark model framework with chiral dynamics. In this framework we achieve a good description of the strong decay properties of the well-established nucleon and $\Delta$ resonances. Meanwhile, the mass reversal between $N(1440)1/2^{+}$ as the first radial excitation state and the $1P$-wave nucleon resonances can be explained. We show that the three-body spin-orbit potential arising from the one-gluon exchange can cause a large configuration mixing between $N(1520)3/2^-$ and $N(1700)3/2^-$, and is also responsible for the large splitting between $\Delta(1600)1/2^-$ and $\Delta(1700)3/2^-$. Some of these baryon resonances turn to weakly couple to the $N\pi$, $N\eta$, $K\Lambda$, and $K\Sigma$ channels, which may answer the question why they have not been established in these channels via the $\pi N$ and $\gamma N$ scatterings. It shows that these ``missing resonances" may have large potentials to be established in the $N\pi\pi$ final state due to their large decay rates into either the $\Delta(1232)$ or $1P$-wave nucleon resonances via the pionic decays. Further experimental search for their signals in charmonium decays at BESIII is thus strongly recommended., Comment: 26 pages, 7 figures, 12 tables

Published
2024

5. EcoFollower: An Environment-Friendly Car Following Model Considering Fuel Consumption

Author

Zhong, Hui, Chen, Xianda, Tiu, PakHin, Lu, Hongliang, and Zhu, Meixin

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

To alleviate energy shortages and environmental impacts caused by transportation, this study introduces EcoFollower, a novel eco-car-following model developed using reinforcement learning (RL) to optimize fuel consumption in car-following scenarios. Employing the NGSIM datasets, the performance of EcoFollower was assessed in comparison with the well-established Intelligent Driver Model (IDM). The findings demonstrate that EcoFollower excels in simulating realistic driving behaviors, maintaining smooth vehicle operations, and closely matching the ground truth metrics of time-to-collision (TTC), headway, and comfort. Notably, the model achieved a significant reduction in fuel consumption, lowering it by 10.42\% compared to actual driving scenarios. These results underscore the capability of RL-based models like EcoFollower to enhance autonomous vehicle algorithms, promoting safer and more energy-efficient driving strategies.

Published
2024

6. Running Coupling and Running Quark Mass Effects on the Elastic Form Factors of Nucleons

Author

Yang, Bao-Yi, Zhong, Hui-Hua, and Chen, Muyang

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We study the elastic electric and magnetic form factors of the proton, neutron and the charged roper resonance ($G_E^p$, $G_M^p$, $G_E^n$, $G_M^n$, $G_E^R$ and $G_M^R$) systematically in a constituent quark model. Three ingredients are crucial in this study: i) the mixing between the pure S-wave and other components which produces a nonzero neutron electric form factor. ii) a running coupling constant that soften the form factors. iii) the running quark mass function, $M_q(p^2)$, which is responsible for the decreasing of the $\mu_p G_E^p(Q^2)/G_M^p(Q^2)$ as $Q^2$ increases. The produced elastic form factors of the proton and neutron match the corresponding observed values fairly well. Our study shows that $\mu_p G_E^p(Q^2)/G_M^p(Q^2) \approx M_q(Q^2/9)/M_q(0)$ upto $Q^2 \approx 4 \text{ GeV}^2$. We give predictions on the elastic form factors of the roper resonance, the electric charge and the magnetic momentum radius ratios of the roper resonance to the proton are $r^R_{E}/r^p_{E} \approx r^R_{M}/r^p_{M} \approx 1.5$., Comment: 13 pages, 8 figures

Published
2024

7. Bridging Quantum Computing and Differential Privacy: Insights into Quantum Computing Privacy

Author

Zhao, Yusheng, Zhong, Hui, Zhang, Xinyue, Li, Yuqing, Zhang, Chi, and Pan, Miao

Subjects
Quantum Physics, Computer Science - Cryptography and Security
Abstract

While quantum computing has strong potential in data-driven fields, the privacy issue of sensitive or valuable information involved in the quantum algorithm should be considered. Differential privacy (DP), which is a fundamental privacy tool widely used in the classical scenario, has been extended to the quantum domain, i.e., quantum differential privacy (QDP). QDP may become one of the most promising approaches toward privacy-preserving quantum computing since it is not only compatible with classical DP mechanisms but also achieves privacy protection by exploiting unavoidable quantum noise in noisy intermediate-scale quantum (NISQ) devices. This paper provides an overview of the various implementations of QDP and their performance in terms of privacy parameters under the DP setting. Specifically, we propose a taxonomy of QDP techniques, categorizing the literature on whether internal or external randomization is used as a source to achieve QDP and how these implementations are applied to each phase of the quantum algorithm. We also discuss challenges and future directions for QDP. By summarizing recent advancements, we hope to provide a comprehensive, up-to-date review for researchers venturing into this field., Comment: To be published in QCE24 (IEEE Quantum Week 2024)

Published
2024

9. Tuning Quantum Computing Privacy through Quantum Error Correction

Author

Zhong, Hui, Ju, Keyi, Sistla, Manojna, Zhang, Xinyue, Qin, Xiaoqi, Fu, Xin, and Pan, Miao

Subjects
Quantum Physics, Computer Science - Emerging Technologies
Abstract

Quantum computing is a promising paradigm for efficiently solving large and high-complexity problems. To protect quantum computing privacy, pioneering research efforts proposed to redefine differential privacy (DP) in quantum computing, i.e., quantum differential privacy (QDP), and harvest inherent noises generated by quantum computing to implement QDP. However, such an implementation approach is limited by the amount of inherent noises, which makes the privacy budget of the QDP mechanism fixed and uncontrollable. To address this issue, in this paper, we propose to leverage quantum error correction (QEC) techniques to reduce quantum computing errors, while tuning the privacy protection levels in QDP. In short, we gradually decrease the quantum noise error rate by deciding whether to apply QEC operations on the gate in a multiple single qubit gates circuit. We have derived a new calculation formula for the general error rate and corresponding privacy budgets after QEC operation. Then, we expand to achieve further noise reduction using multi-level concatenated QEC operation. Through extensive numerical simulations, we demonstrate that QEC is a feasible way to regulate the degree of privacy protection in quantum computing.

Published
2023

10. Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning

Author

Ju, Keyi, Qin, Xiaoqi, Zhong, Hui, Zhang, Xinyue, Pan, Miao, and Liu, Baoling

Subjects
Quantum Physics, Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

Quantum computing revolutionizes the way of solving complex problems and handling vast datasets, which shows great potential to accelerate the machine learning process. However, data leakage in quantum machine learning (QML) may present privacy risks. Although differential privacy (DP), which protects privacy through the injection of artificial noise, is a well-established approach, its application in the QML domain remains under-explored. In this paper, we propose to harness inherent quantum noises to protect data privacy in QML. Especially, considering the Noisy Intermediate-Scale Quantum (NISQ) devices, we leverage the unavoidable shot noise and incoherent noise in quantum computing to preserve the privacy of QML models for binary classification. We mathematically analyze that the gradient of quantum circuit parameters in QML satisfies a Gaussian distribution, and derive the upper and lower bounds on its variance, which can potentially provide the DP guarantee. Through simulations, we show that a target privacy protection level can be achieved by running the quantum circuit a different number of times., Comment: 6 pages, 4 figures

Published
2023

11. Differential Privacy Preserving Quantum Computing via Projection Operator Measurements

Author

Li, Yuqing, Zhao, Yusheng, Zhang, Xinyue, Zhong, Hui, Pan, Miao, and Zhang, Chi

Subjects
Quantum Physics
Abstract

Quantum computing has been widely applied in various fields, such as quantum physics simulations, quantum machine learning, and big data analysis. However, in the domains of data-driven paradigm, how to ensure the privacy of the database is becoming a vital problem. For classical computing, we can incorporate the concept of differential privacy (DP) to meet the standard of privacy preservation by manually adding the noise. In the quantum computing scenario, researchers have extended classic DP to quantum differential privacy (QDP) by considering the quantum noise. In this paper, we propose a novel approach to satisfy the QDP definition by considering the errors generated by the projection operator measurement, which is denoted as shot noises. Then, we discuss the amount of privacy budget that can be achieved with shot noises, which serves as a metric for the level of privacy protection. Furthermore, we provide the QDP of shot noise in quantum circuits with depolarizing noise. Through numerical simulations, we show that shot noise can effectively provide privacy protection in quantum computing.

Published
2023

12. Orbital angular momentum-enhanced phase estimation using non-Gaussian state with photon loss

Author

Chen, Yong-Jian, Gao, Jin-Wei, Han, Jin-Xuan, Yuan, Zhong-Hui, Li, Ruo-Qi, Jiang, Yong-Yuan, and Song, Jie

Subjects
Quantum Physics
Abstract

This study investigates the use of orbital angular momentum (OAM) to enhance phase estimation in Mach-Zehnder interferometers (MZIs) by employing non-Gaussian states as input resources in the presence of noise. Our research demonstrates that non-Gaussian states, particularly the photonsubtraction-then-addition (PSA) state, exhibit the best sensitivity in the presence of symmetric noise. Additionally, higher-order of Bose operator of non-Gaussian states provide better sensitivity for symmetric noise. OAM can mitigate the deterioration of noise, making it possible to estimate small phase shifts theta close to 0. OAM enhances the resolution and sensitivity of all input states and mitigating the deterioration caused by photon loss. Additionally, OAM enhances the resolution and sensitivity of all input states, enabling the sensitivity to approach the 1/N limit even under significant photon loss (e.g.,50% symmetric photon loss). These results hold promise for enhancing the sensitivity and robustness of quantum metrology, particularly in the presence of significant photon loss., Comment: 14 pages, 18 figures

Published
2023
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15. BEVGPT: Generative Pre-trained Large Model for Autonomous Driving Prediction, Decision-Making, and Planning

Author

Wang, Pengqin, Zhu, Meixin, Lu, Hongliang, Zhong, Hui, Chen, Xianda, Shen, Shaojie, Wang, Xuesong, and Wang, Yinhai

Subjects
Computer Science - Robotics
Abstract

Prediction, decision-making, and motion planning are essential for autonomous driving. In most contemporary works, they are considered as individual modules or combined into a multi-task learning paradigm with a shared backbone but separate task heads. However, we argue that they should be integrated into a comprehensive framework. Although several recent approaches follow this scheme, they suffer from complicated input representations and redundant framework designs. More importantly, they can not make long-term predictions about future driving scenarios. To address these issues, we rethink the necessity of each module in an autonomous driving task and incorporate only the required modules into a minimalist autonomous driving framework. We propose BEVGPT, a generative pre-trained large model that integrates driving scenario prediction, decision-making, and motion planning. The model takes the bird's-eye-view (BEV) images as the only input source and makes driving decisions based on surrounding traffic scenarios. To ensure driving trajectory feasibility and smoothness, we develop an optimization-based motion planning method. We instantiate BEVGPT on Lyft Level 5 Dataset and use Woven Planet L5Kit for realistic driving simulation. The effectiveness and robustness of the proposed framework are verified by the fact that it outperforms previous methods in 100% decision-making metrics and 66% motion planning metrics. Furthermore, the ability of our framework to accurately generate BEV images over the long term is demonstrated through the task of driving scenario prediction. To the best of our knowledge, this is the first generative pre-trained large model for autonomous driving prediction, decision-making, and motion planning with only BEV images as input., Comment: AAAI2024

Published
2023

16. Metaverse CAN: Embracing Continuous, Active, and Non-intrusive Biometric Authentication

Author

Zhong, Hui, Huang, Chenpei, Zhang, Xinyue, and Pan, Miao

Subjects
Computer Science - Cryptography and Security
Abstract

The Metaverse is a virtual world, an immersive experience, a new human-computer interaction, built upon various advanced technologies. How to protect Metaverse personal information and virtual properties is also facing new challenges, such as new attacks and new expectations of user experiences. While traditional methods (e.g., those employed in smartphone authentication) generally pass the basic design considerations, they are repeatedly reported to be either unsafe or inconvenient in the Metaverse. In this paper, we address this discrepancy by introducing CAN: a new design consideration especially for the Metaverse. Specifically, we focus on the legacy and novel biometric authentication systems and evaluate them thoroughly with basic and CAN considerations. We also propose an ear-based method as one example of CAN systems. To conclude, a continuous, active and non-intrusive biometric system is suggested for Metaverse authentication for its capability in continuous sessions, against imposters, and immersive experience., Comment: 6 pages, 3 figures

Published
2023

17. Eve Said Yes: AirBone Authentication for Head-Wearable Smart Voice Assistant

Author

Huang, Chenpei, Zhong, Hui, Lian, Jie, Prakash, Pavana, Shi, Dian, Xu, Yuan, and Pan, Miao

Subjects
Computer Science - Cryptography and Security, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Signal Processing
Abstract

Recent advances in machine learning and natural language processing have fostered the enormous prosperity of smart voice assistants and their services, e.g., Alexa, Google Home, Siri, etc. However, voice spoofing attacks are deemed to be one of the major challenges of voice control security, and never stop evolving such as deep-learning-based voice conversion and speech synthesis techniques. To solve this problem outside the acoustic domain, we focus on head-wearable devices, such as earbuds and virtual reality (VR) headsets, which are feasible to continuously monitor the bone-conducted voice in the vibration domain. Specifically, we identify that air and bone conduction (AC/BC) from the same vocalization are coupled (or concurrent) and user-level unique, which makes them suitable behavior and biometric factors for multi-factor authentication (MFA). The legitimate user can defeat acoustic domain and even cross-domain spoofing samples with the proposed two-stage AirBone authentication. The first stage answers \textit{whether air and bone conduction utterances are time domain consistent (TC)} and the second stage runs \textit{bone conduction speaker recognition (BC-SR)}. The security level is hence increased for two reasons: (1) current acoustic attacks on smart voice assistants cannot affect bone conduction, which is in the vibration domain; (2) even for advanced cross-domain attacks, the unique bone conduction features can detect adversary's impersonation and machine-induced vibration. Finally, AirBone authentication has good usability (the same level as voice authentication) compared with traditional MFA and those specially designed to enhance smart voice security. Our experimental results show that the proposed AirBone authentication is usable and secure, and can be easily equipped by commercial off-the-shelf head wearables with good user experience., Comment: 13 pages, 12 figures

Published
2023

19. Assessment of iron metabolism and iron deficiency in incident patients on incident continuous ambulatory peritoneal dialysis

Author

Yin Qinghua, Guo Na, Fu Ping, and Zhong Hui

Subjects
peritoneal dialysis, serum ferritin, ferritin saturation, iron deficiency, inflammation, Medicine
Abstract

The aim of this study was to investigate iron status and iron deficiency in incident continuous ambulatory peritoneal dialysis (CAPD) patients and identify influencing factors.

Published
2024
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20. FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling

Author

Chen, Xianda, Zhu, Meixin, Chen, Kehua, Wang, Pengqin, Lu, Hongliang, Zhong, Hui, Han, Xu, and Wang, Yinhai

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Car-following is a control process in which a following vehicle (FV) adjusts its acceleration to keep a safe distance from the lead vehicle (LV). Recently, there has been a booming of data-driven models that enable more accurate modeling of car-following through real-world driving datasets. Although there are several public datasets available, their formats are not always consistent, making it challenging to determine the state-of-the-art models and how well a new model performs compared to existing ones. In contrast, research fields such as image recognition and object detection have benchmark datasets like ImageNet, Microsoft COCO, and KITTI. To address this gap and promote the development of microscopic traffic flow modeling, we establish a public benchmark dataset for car-following behavior modeling. The benchmark consists of more than 80K car-following events extracted from five public driving datasets using the same criteria. These events cover diverse situations including different road types, various weather conditions, and mixed traffic flows with autonomous vehicles. Moreover, to give an overview of current progress in car-following modeling, we implemented and tested representative baseline models with the benchmark. Results show that the deep deterministic policy gradient (DDPG) based model performs competitively with a lower MSE for spacing compared to traditional intelligent driver model (IDM) and Gazis-Herman-Rothery (GHR) models, and a smaller collision rate compared to fully connected neural network (NN) and long short-term memory (LSTM) models in most datasets. The established benchmark will provide researchers with consistent data formats and metrics for cross-comparing different car-following models, promoting the development of more accurate models. We open-source our dataset and implementation code in https://github.com/HKUST-DRIVE-AI-LAB/FollowNet.

Published
2023

25. Generative learning facilitated discovery of high-entropy ceramic dielectrics for capacitive energy storage

Author

Wei Li, Zhong-Hui Shen, Run-Lin Liu, Xiao-Xiao Chen, Meng-Fan Guo, Jin-Ming Guo, Hua Hao, Yang Shen, Han-Xing Liu, Long-Qing Chen, and Ce-Wen Nan

Subjects
Science
Abstract

Abstract Dielectric capacitors offer great potential for advanced electronics due to their high power densities, but their energy density still needs to be further improved. High-entropy strategy has emerged as an effective method for improving energy storage performance, however, discovering new high-entropy systems within a high-dimensional composition space is a daunting challenge for traditional trial-and-error experiments. Here, based on phase-field simulations and limited experimental data, we propose a generative learning approach to accelerate the discovery of high-entropy dielectrics in a practically infinite exploration space of over 1011 combinations. By encoding-decoding latent space regularities to facilitate data sampling and forward inference, we employ inverse design to screen out the most promising combinations via a ranking strategy. Through only 5 sets of targeted experiments, we successfully obtain a Bi(Mg0.5Ti0.5)O3-based high-entropy dielectric film with a significantly improved energy density of 156 J cm−3 at an electric field of 5104 kV cm−1, surpassing the pristine film by more than eight-fold. This work introduces an effective and innovative avenue for designing high-entropy dielectrics with drastically reduced experimental cycles, which could be also extended to expedite the design of other multicomponent material systems with desired properties.

Published
2024
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27. Neural mechanism underlying the beneficial effect of Theory of Mind psychotherapy on early-onset schizophrenia: a randomized controlled trial

Author

Liu, Siyu, Zhong, Hui, Qian, Yinfeng, Cai, Huanhuan, Jia, Yan-Bin, and Zhu, Jiajia

Subjects
Medical research -- Health aspects, Medicine, Experimental -- Health aspects, Schizophrenia in children -- Health aspects, Psychotherapy -- Health aspects, Clinical trials -- Health aspects, Medical imaging equipment -- Health aspects, Health, Psychology and mental health
Abstract

Background: Psychosocial interventions have emerged as an important component of a comprehensive therapeutic approach in early-onset schizophrenia, typically representing a more severe form of the disorder. Despite the feasibility and efficacy of Theory of Mind (ToM) psychotherapy for schizophrenia, relatively little is known regarding the neural mechanism underlying its effect on early-on-set schizophrenia. Methods: We performed a randomized, active controlled trial in patients with early-onset schizophrenia, who were randomly allocated into either an intervention (ToM psychotherapy) or an active control (health education) group. Diffusion tensor imaging data were collected to construct brain structural networks, with both global and regional topological properties measured using graph theory. Results: We enrolled 28 patients with early-onset schizophrenia in our study. After 5 weeks of treatment, both the intervention and active control groups showed significant improvement in psychotic symptoms, yet the improvement was greater in the intervention group. Importantly, in contrast with no brain structural network change after treatment in the active control group, the intervention group showed increased nodal centrality of the left insula that was associated with psychotic symptom improvement. Limitations: We did not collect important information concerning the participants' cognitive abilities, particularly ToM performance. Conclusion: These findings suggest a potential neural mechanism by which ToM psychotherapy exerts a beneficial effect on early-onset schizophrenia via strengthening the coordination capacity of the insula in brain structural networks, which may provide a clinically translatable biomarker for monitoring or predicting responses to ToM psychotherapy. Clinical trial registration: NCT05577338; ClinicalTrials.gov, Introduction Schizophrenia is a chronic mental disorder expressed as a complex behavioural syndrome with a heterogeneous combination of psychotic symptoms (e.g., delusions, hallucinations and disorganization) and cognitive dysfunctions, which may [...]

Published
2023
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28. Further understanding the nature of $\Omega(2012)$ within a chiral quark model

Author

Zhong, Hui-Hua, Ni, Ru-Hui, Chen, Mu-Yang, Zhong, Xian-Hui, and Xie, Ju-Jun

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment, Nuclear Theory
Abstract

In our previous works, we have analyzed the two-body strong decays of the low-lying $\Omega$ baryon states within a chiral quark model. The results show that the $\Omega(2012)$ resonance favors the three-quark state with $J^P=3/2^-$ classified in the quark model. With this assignment, in the present work we further study the three-body strong decay $\Omega(2012)\to \Xi^*(1530)\bar{K} \to \Xi\pi\bar{K}$ and coupled-channel effects on $\Omega(2012)$ from nearby channels $\Xi \bar{K}$, $\Omega\eta$ and $\Xi^*(1530)\bar{K}$ within the chiral quark model as well. It is found that the $\Omega(2012)$ resonance has a sizeable decay rate into the three-body final state $\Xi\pi\bar{K}$. The predicted ratio $R_{\Xi\bar{K}}^{\Xi\pi\bar{K}}=\mathcal{B}[\Omega(2012)\to \Xi^*(1530)\bar{K}\to \Xi\pi\bar{K}]/\mathcal{B}[\Omega(2012)\to \Xi\bar{K}]\simeq 12\%$ is close to the up limit $11\%$ measured by the Belle Collaboration in 2019, however, our predicted ratio is too small to be comparable with the recent data $0.97\pm 0.31$. Furthermore, our results show that the coupled-channel effects on the $\Omega(2012)$ is not large, its components should be dominated by the bare three-quark state, while the proportion of the molecular components is only $\sim 16\%$. To clarify the nature of $\Omega(2012)$, the ratio $R_{\Xi\bar{K}}^{\Xi\pi\bar{K}}$ is expected to be tested by other experiments., Comment: 7 pages, 3 figures

Published
2022
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32. Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning

Author

Wang, Huijuan, Dai, Siming, Su, Weiyue, Zhong, Hui, Fang, Zeyang, Huang, Zhengjie, Feng, Shikun, Chen, Zeyu, Sun, Yu, and Yu, Dianhai

Subjects
Computer Science - Computation and Language
Abstract

Relational graph neural networks have garnered particular attention to encode graph context in knowledge graphs (KGs). Although they achieved competitive performance on small KGs, how to efficiently and effectively utilize graph context for large KGs remains an open problem. To this end, we propose the Relation-based Embedding Propagation (REP) method. It is a post-processing technique to adapt pre-trained KG embeddings with graph context. As relations in KGs are directional, we model the incoming head context and the outgoing tail context separately. Accordingly, we design relational context functions with no external parameters. Besides, we use averaging to aggregate context information, making REP more computation-efficient. We theoretically prove that such designs can avoid information distortion during propagation. Extensive experiments also demonstrate that REP has significant scalability while improving or maintaining prediction quality. Notably, it averagely brings about 10% relative improvement to triplet-based embedding methods on OGBL-WikiKG2 and takes 5%-83% time to achieve comparable results as the state-of-the-art GC-OTE., Comment: Accepted by IJCAI 2022

Published
2022

33. Emergence of functionally aberrant and subsequent reduction of neuromuscular connectivity and improved motor performance after cervical spinal cord injury in Rhesus

Author

Wai, Gregory, Zdunowski, Sharon, Zhong, Hui, Nielson, Jessica L, Ferguson, Adam R, Strand, Sarah C, Moseanko, Rod, Hawbecker, Stephanie, Nout-Lomas, Yvette S, Rosenzweig, Ephron S, Beattie, Michael S, Bresnahan, Jacqueline C, Tuszynski, Mark H, Roy, Roland R, and Edgerton, V Reggie

Subjects
Health Sciences, Sports Science and Exercise, Rehabilitation, Traumatic Head and Spine Injury, Spinal Cord Injury, Neurosciences, Physical Injury - Accidents and Adverse Effects, Neurological, muscle activity patterns, motor performance, spinal plasticity, spinal cord injury, EMG
Abstract

IntroductionThe paralysis that occurs after a spinal cord injury, particularly during the early stages of post-lesion recovery (∼6 weeks), appears to be attributable to the inability to activate motor pools well beyond their motor threshold. In the later stages of recovery, however, the inability to perform a motor task effectively can be attributed to abnormal activation patterns among motor pools, resulting in poor coordination.MethodWe have tested this hypothesis on four adult male Rhesus monkeys (Macaca mulatta), ages 6-10 years, by recording the EMG activity levels and patterns of multiple proximal and distal muscles controlling the upper limb of the Rhesus when performing three tasks requiring different levels of skill before and up to 24 weeks after a lateral hemisection at C7. During the recovery period the animals were provided routine daily care, including access to a large exercise cage (5' × 7' × 10') and tested every 3-4 weeks for each of the three motor tasks.ResultsAt approximately 6-8 weeks the animals were able to begin to step on a treadmill, perform a spring-loaded task with the upper limb, and reaching, grasping, and eating a grape placed on a vertical stick. The predominant changes that occurred, beginning at ∼6-8 weeks of the recovery of these tasks was an elevated level of activation of most motor pools well beyond the pre-lesion level.DiscussionAs the chronic phase progressed there was a slight reduction in the EMG burst amplitudes of some muscles and less incidence of co-contraction of agonists and antagonists, probably contributing to an improved ability to selectively activate motor pools in a more effective temporal pattern. Relative to pre-lesion, however, the EMG patterns even at the initial stages of recovery of successfully performing the different motor tasks, the level of activity of most muscle remained higher. Perhaps the most important concept that emerges from these data is the large combinations of adaptive strategies in the relative level of recruitment and the timing of the peak levels of activation of different motor pools can progressively provide different stages to regain a motor skill.

Published
2023

49. 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. A., Oliveira, Natalia S, Lima, Rodolfo G. S. D, Figueiredo, Estevao, Edilena Paulino Azevedo, Bruna, Ricardo Caramori, Paulo, Bizzaro Santos, Marco, Germann, Amanda, Gomes, Vitor, Homem, Rosa, Magedanz, Ellen, Tumelero, Rogerio, Laimer, Rosane, Tognon, Alexandre, Dall’Orto, Frederico, Mesquita, Claudio T., Santos, Roberta P, Colafranseschi, Alexandre S., Oliveira, Amarino C., Carvalho, Luiz A., Palazzo, Isabella C., Sousa, Andre S., Eustáquio Ribeiro da Silva, Expedito, Gabriel Melo de Barros e Silva, Pedro, Yumi Okada, Mariana, de Pádua Silva Baptista, Luciana, Paula Batista, Ana, Jamus Rodrigues, Marcelo, Nogueira Rabaça, Aline, Valério Coimbra de Resende, Marcos, Francisco Saraiva, Jose, Miranda Trama, Larissa, Silva, Talita, Thais de Souza Ormundo, Camila, Vicente, Carla, Costantini, Costantino, Pinheiro, Caroline, Komar, Daniele, Szwed, Hanna, Demkow, Marcin, Kepka, Cezary, Teresinska, Anna, Walesiak, Olga, Kryczka, Karolina, Malinowska, Katarzyna, Henzel, Jan, Solecki, Mateusz, Kaczmarska, Edyta, Mazurek, Tomasz, Maksym, Jakub, Wojtera, Karolina, Fojt, Anna, Szczerba, Ewa, Drozdz, Jaroslaw, Czarniak, Bartosz, Frach, Malgorzata, Szymczyk, Konrad, Niedzwiecka, Iwona, Sobczak, Sebastian, Ciurus, Tomasz, Jakubowski, Piotr, Misztal-Teodorczyk, Magdalena, Teodorczyk, Dawid, Swiderek, Marta, Fratczak, Aleksandra, Wojtala, Ewelina, Szkopiak, Marcin, Lebioda, Patrycja, Wlodarczyk, Michal, Plachcinska, Anna, Kusmierek, Jacek, Miller, Magdalena, Marciniak, Halina, Wojtczak-Soska, Karolina, Łuczak, Katarzyna, Tarchalski, Tomasz, Cichocka-Radwan, Anna, Szwed, Hanna, Karwowski, Jaroslaw, Anna Szulczyk, Grazyna, Witkowski, Adam, Kukuła, Krzysztof, Celińska-Spodar, Małgorzta, Zalewska, Joanna, Gajos, Grzegorz, Bury, Krzysztof, Pruszczyk, Piotr, Łabyk, Andrzej, Roik, Marek, Szramowska, Agnieszka, Zdończyk, Olga, Łoboz-Grudzień, Krystyna, Jaroch, Joanna, Sokalski, Leszek, Brzezińska, Barbara, Lesiak, Maciej, Łanocha, Magdalena, Reczuch, Krzysztof W., Kolodziej, Adam, Kalarus, Zbigniew, Swiatkowski, Andrzej, Szulik, Mariola, Musial, Wlodzimierz J., Marcinkiewicz-Siemion, Marta, Bockeria, Olga, Bockeria, Leo, Bockeria, Olga, Petrosyan, Karen, Kudzoeva, Zalina, Trifonova, Tatiana, Aripova, Nodira, Chernyavskiy, Alexander M., Naryshkin, Ivan A., Kretov, Evgeniy I., Kuleshova, Alena, Grazhdankin, Igor O., Malaev, Dastan, Bershtein, Leonid L., Sayganov, Sergey A., Subbotina, Irina, Kuzmina-Krutetskaya, Anastasia M., Gumerova, Victoria, Zbyshevskaya, Elizaveta V., Katamadze, Nana O., Nikolaeva, Olga B., Kozlov, Pavel S., Kozulin, Vikentiy Y., Lubinskaya, Ekaterina I., Luis Lopez-Sendon, Jose, Castro, Almudena, Lopez-Sendon, Jose, Fernández-Figares, Virginia, Castro, Almudena, Refoyo Salicio, Elena, Guzman, Gabriela, Galeote, Gabriel, Valbuena, Silvia, Peteiro, Jesús, Dolores Martínez-Ruíz, María, Pérez-Fernández, Ruth, Blanco-Calvo, Moisés, Cuenca-Castillo, José J, Alonso-Álvarez, Encarnación, Flores-Ríos, Xacobe, García-González, Paula, Prada-Delgado, Óscar, Barge-Caballero, Gonzalo, Ramon Gonzalez Juanatey, Jose, Seijas Amigo, Jose, Souto Bayarri, Miguel, Pubull Nuñez, Virginia, Ocaranza Sanchez, Raymundo, Cid Alvarez, Belen, Peña Gil, Carlos, Martinez Monzonis, Amparo, Sionis, Alessandro, Fernández Martínez, Ana, Vila Perales, Montserrat, Maria Padró, Josep, Serra Peñaranda, Antonio, García Picart, Joan, Ginel Iglesias, Antonino, Garcia-Moll Marimon, Xavier, Pons Lladó, Guillem, Carreras Costa, Francesc, Miro, Vicente, Igual, Begoña, Diez, Jose L, Calvillo, Pilar, Ortuño, F. 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

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2024
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