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computers and Education: X Reality 2024年 5卷

作者： Akinwale, Olawale Babatunde Abiona, Olatunde Oluwatope, Ayodeji Oludola Otuyemi, Olayinka Donald Ijarotimi, Omotade Adebimpe Olubusola Komolafe, Abiola Aregbesola, Stephen Babatunde Kolawole, Babatope Ayodeji Adetutu, Olufemi Mayowa Agunbiade, Ojo Melvin Ayinde, Adeboye Titus Idowu, Lanre Okunola, Oluseye Ademola Adediwura, Alaba Adeyemi Department of Electronic and Electrical Engineering Faculty of Technology Obafemi Awolowo University Ile-Ife 220005 Nigeria Computer Information Systems Department College of Arts and Sciences Indiana University Northwest 3400 Broadway Gary 46408 IN United States Department of Computer Science and Engineering Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Child Dental Health Faculty of Dentistry College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Obstetrics Gynaecology and Perinatology Faculty of Clinical Sciences College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Nursing Science Faculty of Basic Medical Science College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Oral and Maxillofacial Surgery Faculty of Dentistry College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Medicine Faculty of Clinical Sciences College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Dept. of Demography and Social Statistics Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Sociology and Anthropology Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Psychology Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Educational Technology and Library Studies Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Educational Foundation and Counselling Obafemi Awolowo University Ile-Ife 220005 Nigeria

The COVID-19 pandemic clearly showed how much medical and clinical students’ education relied on physical instruction and examination. The work presented here was born by the fact that medical and clinical education had to be suspended during the social distancing phase of the pandemic. This work presents the lessons learned from creating a virtual reality system (VTRACS) for educating and assessing clinical students on a limited budget. Our work showed that clinical education could be done in a virtual space with a minimal virtual reality setup and a low-cost virtual reality headset. © 2024 The Authors

关键词： Clinical education Haptic feedback Low-cost Medical education Virtual reality

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First Demonstration of CMOS Inverter and 6T-SRAM Based on GAA CFETs Structure for 3D-IC Applications

First Demonstration of CMOS Inverter and 6T-SRAM Based on GA...

引用

International Electron Devices Meeting (IEDM)

作者： S.-W. Chang P.-J. Sung T-Y. Chu D. D. Lu C.-J. Wang N.-C. Lin C.-J. Su S.-H. Lo H.-F. Huang J.-H. Li M.-K. Huang Y.-C. Huang S.-T. Huang H.-C. Wang Y.-J. Huang J.-Y. Wang L. - W Yu Y.-F. Huang F. - K. Hsueh C.-T. Wu W. C.-Y. Ma K.-H. Kao Y. - J. Lee C.-L. Lin R. W. Chuang K.-P. Huang S. Samukawa Y. Li W. - H. Lee T.-S. Chao G. - W. Huang W.-F. Wu J. - Y. Li J.-M. Shieh W. - K. Yeh Y.-H. Wang Taiwan Semiconductor Research Institute Hsinchu Taiwan Dept. of Electrical Engineering National Cheng Kung University Tainan Taiwan Dept. of Electrophysics National Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National Sun Yat-sen University Kaohsiung Taiwan Dept. of Electronic Engineering Feng Chia University Taichung Taiwan Mechanical and Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Institute of Fluid Science Tohoku University Sendai Japan Dept. of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering and Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

For the first time, CMOS inverters and 6T-SRAM cells based on vertically stacked gate-all-around complementary FETs (CFETs) are experimentally demonstrated. Manufacturing difficulties of vertically stacked source and drain electrodes of the CFETs have been overcome by using junctionless transistors, thereby reducing the number of lithographic steps required. Furthermore, with post metallization treatments, both the voltage transfer characteristics (VTCs) of CMOS inverters and butterfly curves of SRAM show significant improvements due to the symmetry of nMOS and pMOS threshold voltages. Simulation shows that 3-dimensional CFET inverters have lower input parasitic capacitance than standard 2-dimensional CMOS, leading to reduced gate delay and lower power consumption.

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Improving contamination detectability in water distribution systems using active fault detection 1

Improving contamination detectability in water distribution ...

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1st International Joint Conference in Water Distribution systems Analysis and Computing and Control in the Water Industry, WDSA/CCWI 2018

作者： Lifshitz, Ron Ostfeld, Avi Vrachimis, Stelios G. Eliades, Demetrios G. Polycarpou, Marios M. Faculty of Civil and Environmental Engineering Technion - Israel Institute of Technology Haifa32000 Israel Kios Research and Innovation Center of Excellence Dept. of Electrical and Computer Engineering University of Cyprus Cyprus

Contamination event detection in Water Distribution systems (WDS) is an important part of the overall procedures followed by operators to ensure the delivery of safe drinking water to consumers. In practice, detection methodologies may use a small number of sensors, which may be placed optimally throughout the network, to monitor water quality. Typically, due to their high costs, only a small number of these sensors are available within each WDS, and as a result, a part of the network is not monitored by sensors. In this paper, we propose a novel methodology for detecting contamination events by increasing the area monitored by these water quality sensors. Specifically, the proposed methodology can be used in emergency cases when information is available about a possible contamination event in the system, to actively manipulate WDS actuators, by closing and opening valves, and alter the flow directions within the network. This is based on the concept of Active Fault Detection, in which the control input of a system is modified with the aim to improve detectability of a fault. This active detection scheme, drives flows from specific parts of the network in pre-determent paths, to allow the sensors to monitor the quality of water from previously unobserved parts of the network. As a result, the monitoring coverage of the sensors is increased and some contamination events occurring within those areas can be detected. Moreover, the methodology facilitates the isolation of the contamination propagation path and its possible source. We demonstrate how such goals can be achieved on two simple example networks, discuss the benefits of the results and open the discussion for further work in this area. © 2018 1st International WDSA / CCWI 2018 Joint Conference. All rights reserved.

关键词： Fault detection

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Towards Reproducible Bioinformatics: The OpenBio-C Scientific Workflow Environment

Towards Reproducible Bioinformatics: The OpenBio-C Scientifi...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Alexandros Kanterakis Galateia Iatraki Konstantina Pityanou Lefteris Koumakis Nikos Kanakaris Nikos Karacapilidis George Potamias Foundation for Research and Technology-Hellas (FORTH) Institute of Computer Science Heraklion Greece Dept. of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Industrial Management and Information Systems Lab MEAD University of Patras Patras Greece

ISBN: (纸本)9781728146188

The highly competitive environment of post-genomics biomedical research is pushing towards the production of highly qualified results and their utilization in clinical practice. Due to this pressure, an important factor of scientific progress has been underestimated namely, the reproducibility of the results. To this end, it is critical to design and implement computational platforms that enable seamless and unhindered access to distributed bio-data, software and computational infrastructures. Furthermore, the need to support collaboration and form synergistic activities between the engaged researchers is also raised, as the mean to achieve consensus on respective scientific discoveries. The aforementioned needs and requirements underlie the motivations for the development of OpenBio-C workflow environment, and determine its fundamental objectives. The insufficiencies of current workflow editing and execution environments are explored, and the key-directions to advance over an environment that supports reproducibility are stated. The basic components and functionality of the OpenBio-C initial implementation (beta version) are detailed.

关键词： Bioinformatics Tools Collaboration Pipelines Genomics Market research Semantics

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An Adaptive Stereoscopic Video Streaming Mechanism Using MV-HEVC and 3D-HEVC Technologies

An Adaptive Stereoscopic Video Streaming Mechanism Using MV-...

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IEEE International Conference on Ubi-Media Computing

作者： Tz-Heng Hsu Po-Hui Wu Gwo-Jiun Horng Chao-Chun Chen Mao-Yuan Pai Dept. of Computer Science and Information Engineering Southern Taiwan University of Science and Technology Taiwan R.O.C. Dept. of Computer Science and Information Engineering Institute of Manufacturing Information and Systems National Cheng Kung University General Research Service Center National Pingtung University of Science and Technology Neipu Taiwan R.O.C.

ISBN: (数字)9781728128207

ISBN: (纸本)9781728128214

In this paper, we propose an adaptive stereoscopic video streaming mechanism using MV-HEVC and 3D-HEVC technologies. When the current available bandwidth is insufficient for delivering all video layers, the mechanism selects the MV-HEVC and 3D-HEVC video pictures near the current playing point with the proposed rate control algorithm. Simulation results show that the proposed adaptive streaming mechanism can provide tolerable video quality under packet loss conditions in wireless networking environment.

关键词： Streaming media Stereo image processing Encoding Bandwidth Three-dimensional displays Wireless communication Decoding

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Mechanism for embedded in-plane self assembled nanowire formation

arXiv

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arXiv 2019年

作者： Wilson, Nathaniel S. Kraemer, Stephan Pennachio, Daniel J. Callahan, Patrick Pendharkar, Mihir Palmstrøm, Christopher J. Materials Dept. University of California Santa Barbara93106-5050 United States Electrical and Computer Engineering Dept. University of California Santa Barbara93106-5050 United States Center for Nanoscale Systems Harvard University BostonMA02138 United States

We report a novel growth mechanism that produces in-plane [11#0] oriented ErSb nanowires formed during codeposition of Er0.3Ga0.7Sb via molecular beam epitaxy (MBE). Nanowires are characterized by in-situ scanning tunneling microscopy (STM), as well as ex-situ transmission electron microscopy (TEM) and electron channeling contrast imaging (ECCI). We show that complexes of macrosteps with step heights on the order of 7 nm form during nanowire growth. The macrosteps are shown to be part of the in-plane nanowire growth process and are directly responsible for the observed stratified distribution of in-plane nanowires. TEM indicates that initial growth results in out-of-plane nanowires transitioning to in-plane nanowires after a critical film thickness. A surface energy model is put forward that shows the critical thickness is due to minimization of the GaSb{110} surfaces formed during out-of-plane nanowire growth. Kinetics of the transition are discussed with respect to observed features in STM, along with the material parameters needed to achieve in-plane nanowire growth. Copyright © 2019, The Authors. All rights reserved.

关键词： Nanowires

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High-Efficiency InAs-InGaAs Quantum Dash Solar Cells Developed Through Current Constraint engineering

High-Efficiency InAs-InGaAs Quantum Dash Solar Cells Develop...

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IEEE Conference on Photovoltaic Specialists

作者： Yoshitaka Okada Naoya Miyashita Yusuke Oteki Yasushi Shoji Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan Dept. of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan National Institute of Advanced Industrial Science and Technology (AIST) Ibaraki Japan

In principle, quantum-dot intermediate band solar cell (QD-IBSC) operates at a higher current density than a III-V multijunction solar cell (MJSC). Due to this inherent property, heat management becomes important when it is operated under a high concentrated illumination. In this work, we propose one way to circumvent this issue, where a wide bandgap cell is placed on top of QD-IBSC, which acts as a current constraint cell, but instead leads to a higher V OC . We demonstrate a 32.1% efficiency under 225 suns with a bonded InGaP/GaAs widegap cell // InAs-InGaAs QDSC configuration.

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-dept. literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Understanding metric-related pitfalls in image analysis validation

arXiv

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arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： computer vision

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New approaches to the treatment of Age-Related Macular Degeneration (AMD)

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Experimental Eye Research 2022年 221卷 109134页

作者： Csaky, Karl Curcio, Christine A. Mullins, Robert F. Rosenfeld, Philip J. Fujimoto, James Rohrer, Bärbel Ribero, Ramiro Malek, Goldis Waheed, Nadia Guymer, Robyn Hageman, Gregory S. Chen, Hao Csete, Marie Retina Foundation of the Southwest 9600 N. Central Expy. #200 Dallas 75231 TX United States University of Alabama School of Medicine Dept. of Ophthalmology and Visual Sciences 670 University Blvd. Room 360 Birmingham 35294-0019 AL United States University of Iowa Hospitals and Clinics Dept. of Ophthalmology and Visual Sciences 200 Hawkins Dr. Iowa City 52242 IA United States Bascom Palmer Eye Institute University of Miami Dept. of Ophthalmology 900 NW 17th St. Miami 33136 FL United States Massachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Research Laboratory of Electronics Cambridge 02139 MA United States Medical University of South Carolina Dept. of Ophthalmology 167 Ashley Ave. Charleston 29425 SC United States Apellis Pharmaceuticals 100 Fifth Ave. 3rd Floor Waltham 02451 MA United States Duke University Depts. of Ophthalmology and Pathology Albert Eye Research Institute 2351 Erwin Rd AERI Room 4006 Durham 27710 NC United States New England Eye Center Tufts Medical Center Boston MA 02116 United States University of Melbourne Centre for Eye Research Australia Dept. of Surgery Level 7 32 Gisborne St. East Melbourne VIC 3002 Australia University of Utah Department of Ophthalmology and Visual Sciences Sharon Eccles Steel Center for Translational Medicine 65 N. Mario Capecchi Dr. Salt Lake City 84132 UT United States gRED Genentech Inc. OMNI Early Clinical Development 1 DNA Way Mailstop 258A South San Francisco 94080-4990 CA United States ConeSight Therapeutics 2265 E. Foothill Blvd. Pasadena 91107 CA United States

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