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Nonlocality in photonic materials and metamaterials: roadmap

Optical materials Express 2025年第7期15卷 1544-1709页

作者： Francesco Monticone N Asger Mortensen Antonio I Fernández-domínguez Yu Luo Xuezhi Zheng Christos Tserkezis Jacob B Khurgin Tigran V Shahbazyan André J Chaves Nuno M R Peres Gino Wegner Kurt Busch Huatian Hu Fabio della Sala Pu Zhang Cristian Ciracì Javier Aizpurua Antton Babaze Andrei G Borisov Xue-Wen Chen Thomas Christensen Wei Yan Yi Yang Ulrich Hohenester Lorenz Huber Martijn Wubs Simone de Liberato P A d Gonçalves F Javier García de Abajo Ortwin Hess Illya Tarasenko Joel d Cox Line Jelver Eduardo J C dias Miguel Sánchez Sánchez dionisios Margetis Guillermo Gómez-Santos Igor M Vasilevskiy Tobias Stauber Sergei Tretyakov Constantin Simovski Samaneh Pakniyat J Sebastián Gómez-díaz Igor V Bondarev Svend-Age Biehs Alexra Boltasseva Vladimir M Shalaev Alexey V Krasavin Anatoly V Zayats Andrea Alù Jung-Hwan Song Mark L Brongersma Uriel Levy Olivia Y Long Cheng Guo Shanhui Fan Sergey I Bozhevolnyi Adam Overvig Filipa R Prudêncio Mário G Silveirinha S Ali Hassani Gangaraj Christos Argyropoulos Paloma A Huidobro Emanuele Galiffi Fan Yang John B Pendry david A B Miller School of Electrical and Computer Engineering Cornell University Ithaca New York 14853 USA POLIMA—Center for Polariton-driven Light-Matter Interactions University of Southern Denmark Campusvej 55 DK-5230 Odense M Denmark D-IAS—Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 DK-5230 Odense M Denmark Departamento de Física Teórica de la Materia Condensada Universidad Autónoma de Madrid E-28049 Madrid Spain Condensed Matter Physics Center (IFIMAC) Universidad Autónoma de Madrid E-28049 Madrid Spain School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing 211106 China WaveCoRE Division Department of Electrical Engineering KU Leuven Leuven B-3001 Belgium Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland 21218 USA Department of Physics Jackson State University Jackson Mississippi 39217 USA Department of Physics Aeronautics Institute of Technology 12228-900 So Jos dos Campos SP Brazil Centro de Física (CF-UM-UP) and Departamento de Física Universidade do Minho P-4710-057 Braga Portugal International Iberian Nanotechnology Laboratory (INL) Av Mestre José Veiga 4715-330 Braga Portugal Max-Born-Institut 12489 Berlin Germany Humboldt-Universität zu Berlin Institut für Physik AG Theoretische Optik and Photonik 12489 Berlin Germany Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Via Barsanti 14 73010 Arnesano Italy Institute for Microelectronics and Microsystems (CNR-IMM) Via Monteroni Campus Unisalento 73100 Lecce Italy School of Physics Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China Donostia International Physics Center DIPC 20018 Donostia-San Sebastián Spain Ikerbasque Basque Foundation fo

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally adopted in optical material modeling. The growing interest in plasmonic, polaritonic, and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces—can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In metasurfaces, in particular, nonlocality engineering has emerged as a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials and metamaterials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward—toward new scientific discoveries and technological *** by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License . Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and dOI.

关键词： Chemical elements Localized surface plasmon resonance material properties Near field scanning optical microscopy Optical materials Thin films

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research on Image Compression technology Based on Bp Neural Network 17

Research on Image Compression Technology Based on Bp Neural ...

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17th International Conference on Machine Learning and Cybernetics, ICMLC 2018

作者： Li, Cheng-Cheng Li, Gong-Fa Sun, Ying Jiang, Guo-Zhang Kong, Jian-Yi Xu, Shuang Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430083 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430083 China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781538652121

The traditional image compression technique uses the redundancy of the image data to compress the image without lossless coding by the corresponding coding techniques. different compression coding techniques are redundant for different image data. Under the background of many new applications, the traditional image compression technology can no longer meet the requirement of further improving the quality of compressed images. In recent years, with the continuous development of artificial neural network technology, Some good properties of neural network, such as nonlinear, fault-Tolerant, self-organizing and adaptive, has been widely applied in image processing technology, which greatly simplifies the complexity of image processing. This paper mainly introduces the basic principles of BP neural network, studies the application of neural network in image compression, carries out simulation experiments through MATLAB, and analyzes the feasibility and advantages of BP neural network applied to image compression. © 2018 IEEE.

关键词： Image compression

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医用增材制造——从前沿技术到产品研发

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Engineering 2020年第11期6卷 31-41页

作者：邱贵兴丁文江田伟秦岭赵宇张联盟吕坚陈代杰袁广银吴成铁卢秉恒杜如虚陈继明 Mo Elbestawi 顾忠伟李涤尘孙伟赵远锦赫捷金大地刘斌张凯李鉴墨 Kam W.Leong 赵德伟郝定均敖英芳邓旭亮杨惠林徐少克陈英奇李龙樊建平聂国辉陈芸曾晖陈玮赖毓霄 Department of Orthopedics Peking Union Medical College Hospital Chinese Academy of Medical Science & Peking Union Medical College National Engineering Research Center of Light Alloys Net Forming & State Key Laboratory of Metal Matrix Composite Shanghai Jiao Tong University National Engineering Research Center of Mg Materials and Applications and School of Materials Science & Engineering Shanghai Jiao Tong University Department of Spine Surgery Beijing Jishuitan Hospital Center for Translational Medicine Research and Development Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Engineering Laboratory of Biomaterials Additive Manufacturing State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Center for Advanced Structural Materials City University of Hong Kong Shenzhen Research Institute Hong Kong Branch of National Precious Metals Material Engineering Research Center Department of Material Science and Engineering City University of Hong Kong Department of Mechanical Engineering City University of Hong Kong School of Pharmacy Shanghai Jiao Tong University China State Institute of Pharmaceutical Industry Shanghai Institute of Pharmaceutical Industry State Key Laboratory of High-Performance Ceramics and Superfine Microstructure Shanghai Institute of Ceramics Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of the Chinese Academy of Sciences Micro- and Nano-Technology Research Center State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Shien-Ming Wu School of Intelligent Engineering Guangzhou International Campus South China University of Technology Beijing Engineering Research Center of 3D Printing for Digital Medical Health Beijing University of Technology Beijing Engineering Research Center of Laser Technology Beijing University of Technology Key Laboratory of Trans-Scale Las

1.医用增材制造原料的研发和挑战医用增材制造的原料与其他多个领域使用的原料具有广泛通用性,这是构成三维(3d)打印领域的重要基础。这些领域的增材制造在材料类型、粉体特性、成型性和黏弹性等方面面临着相同的问题和挑战。例如,航空...

1.医用增材制造原料的研发和挑战医用增材制造的原料与其他多个领域使用的原料具有广泛通用性,这是构成三维(3d)打印领域的重要基础。这些领域的增材制造在材料类型、粉体特性、成型性和黏弹性等方面面临着相同的问题和挑战。例如,航空领域采用了多种金属材料,而生物医学领域会使用金属、聚合物和无机材料。在生物医学领域,

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research On Image Compression technology Based On Bp Neural Network

Research On Image Compression Technology Based On Bp Neural ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： CHENG-CHENG LI GONG-FA LI YING SUN GUO-ZHANG JIANG JIAN-YI KONG SHUANG XU Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan China

The traditional image compression technique uses the redundancy of the image data to compress the image without lossless coding by the corresponding coding techniques. different compression coding techniques are redundant for different image data. Under the background of many new applications, the traditional image compression technology can no longer meet the requirement of further improving the quality of compressed images. In recent years, with the continuous development of artificial neural network technology, Some good properties of neural network, such as nonlinear, fault-tolerant, self-organizing and adaptive, has been widely applied in image processing technology, which greatly simplifies the complexity of image processing. This paper mainly introduces the basic principles of BP neural network, studies the application of neural network in image compression, carries out simulation experiments through MATLAB, and analyzes the feasibility and advantages of BP neural network applied to image compression.

关键词： Image coding Training Biological neural networks Neurons Image reconstruction Transforms

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research On Image Segmentation Based On Support Vector Machine

Research On Image Segmentation Based On Support Vector Machi...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chong Tan Ying Sun Gong-Fa Li Guo-Zhang Jiang Jian-Yi Kong Bo Tao Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781538652152

Image segmentation technology is one of the important topics in the field of digital image processing. However, the existing image segmentation technology does not have a uniform standard, and the traditional image segmentation technology is only suitable for some fixed situations. Therefore, the image segmentation technology on new theories and new methods deserves further research and development. The SVM algorithm for image segmentation, a variety of image features can be used to get a better segmentation results. So, this paper based on the theory of support vector machines, introduces the basic idea of SVM in detail, and the current state of image segmentation and the development trend of image segmentation are described in detail. Finally, the necessity of introducing statistical learning into image segmentation and the possibility of introducing SVM into image segmentation are studied and analyzed in depth. The results show that support vector machine can well segment the image target.

关键词： Image segmentation Support vector machines Statistical learning Classification algorithms Training Kernel

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Author Correction: Battery-free, wireless soft sensors for continuous multi-site measurements of pressure and temperature from patients at risk for pressure injuries

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Nature communications 2021年第1期12卷 6827页

作者： Yong Suk Oh Jae-Hwan Kim Zhaoqian Xie Seokjoo Cho Hyeonseok Han Sung Woo Jeon Minsu Park Myeong Namkoong Raudel Avila Zhen Song Sung-Uk Lee Kabseok Ko Jungyup Lee Je-Sang Lee Weon Gi Min Byeong-Ju Lee Myungwoo Choi Ha Uk Chung Jongwon Kim Mengdi Han Jahyun Koo Yeon Sik Choi Sung Soo Kwak Sung Bong Kim Jeonghyun Kim Jungil Choi Chang-Mo Kang Jong Uk Kim Kyeongha Kwon Sang Min Won Janice Mihyun Baek Yujin Lee So Young Kim Wei Lu Abraham Vazquez-Guardado Hyoyoung Jeong Hanjun Ryu Geumbee Lee Kyuyoung Kim Seunghwan Kim Min Seong Kim Jungrak Choi dong Yun Choi Quansan Yang Hangbo Zhao Wubin Bai Hokyung Jang Yongjoon Yu Jaeman Lim Xu Guo Bong Hoon Kim Seokwoo Jeon Charles davies Anthony Banks Hyung Jin Sung Yonggang Huang Inkyu Park John A Rogers Center for Bio-Integrated Electronics Northwestern University Evanston IL USA. Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea. Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA. Department of Materials Science and Engineering University of Illinois at Urbana Champaign Urbana IL USA. Querrey Simpson Institute for Bioelectronics Northwestern University Evanston IL USA. State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering Mechanics Dalian University of Technology Dalian People's Republic of China. Ningbo Institute of Dalian University of Technology Ningbo People's Republic of China. Department of Biomedical Engineering Texas A&M University College Station TX USA. Department of Mechanical Engineering Northwestern University Evanston IL USA. Advanced 3D Printing Technology Development Division Korea Atomic Energy Research Institute Daejeon Republic of Korea. Qualcomm Institute La Jolla CA USA. Sibel Health Inc Niles IL USA. Department of Rehabilitation Medicine Gimhae Hansol Rehabilitation & Convalescent Hospital Gimhae Republic of Korea. Department of Planning and Development Gimhae Hansol Rehabilitation & Convalescent Hospital Gimhae Republic of Korea. Department of Rehabilitation Medicine Pusan national university hospital Busan Republic of Korea. Department of Materials Science and Engineering KAIST Institute for The Nanocentury (KINC) Korea Advanced Institute of Science and Technology Daejeon Republic of Korea. Department of Materials Science and Engineering Northwestern University Evanston IL USA. Department of Mechanical Engineering Kyung Hee University Yongin Republic of Korea. Department of Biomedical Engineering College of Future Technology Peking University Beijing People's Republic of China. School of Biomedical Engineering Korea University Seoul Republic of Korea. Interdisci

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Board-Level Reliability of 3d Through Glass Via Filters during Thermal Cycling

Board-Level Reliability of 3D Through Glass Via Filters Duri...

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IEEE Electronic Components and technology Conference

作者： Scott McCann Satoru Kuramochi Hobie Yun Venkatesh Sundaram M. Raj Pulugurtha Rao R. Tummala Suresh K. Sitaraman 3D System Packaging Research Center Georgia Institute of Technology Atlanta GA USA George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Dai Nippon Printing Co. Ltd. Kashiwa Chiba Japan Qualcomm Technologies Inc. San Diego CA USA

This paper theoretically and experimentally assesses the board-level reliability of glass-based 3d Integrated Passive device (IPd) with TGV-based inductor capacitor (LC) filters in thermal cycling test. Important failure modes such as well-known solder joint cracking and TGV failure as well as other failure modes such as glass cratering are investigated in this work. Through finite-element modeling, initial reliability predictions are made using a Morrow-darveaux approach for solder fatigue life. To predict glass cratering, a stress-based approach is used. In the second part of this work, reliability experiments are conducted on fabricated samples, demonstrating reliable 3d IPd glass packages. Failure analysis has found that solder joint cracking and glass cratering have occurred, but no TGV failures have occurred. The experimental results are also compared to numerical predictions. Then, for future designs, the models are used to analyze the impact of key material and design parameters on the experimentally observed failure modes. It is predicted that reducing the glass core thickness will improve solder fatigue life and help prevent glass cratering. Also, TGVs are recommended to be kept away from solder joints to prevent glass cratering. Stress buffering of the dielectric also improves the reliability, though less than glass core thickness. By developing and correlating a model specifically for these devices, this work, for the first time, enables accurate study and optimization of key design parameters for 3d glass IPd radio frequency (RF) devices to achieve high mechanically reliability, high-performance long term evolution band devices, with potentially smaller footprint and thickness compared to current LTCC counterparts.

关键词： Solder joint reliability Through glass via (TGV) Glass cratering Integrated passive device

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Thin polymer dry-film dielectric material and a process for 10 um interlayer vias in high density organic and glass interposers

Thin polymer dry-film dielectric material and a process for ...

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Electronic Components and technology Conference (ECTC)

作者： Yuya Suzuki Yutaka Takagi Venky Sundaram Rao Tummala 3D Systems Packaging Research Center Georgia Institute of Technology Atlanta GA USA Zeon Corporation Research and Development Center Kawasaki-shi Kanagawa Japan Nippon Tokushu Togyo Kabushiki Kaisha Nagoya Aichi JP NGK Spark Plug Co. LTD. Komaki-shi Aichi Japan

This paper describes the first demonstration of 10 μm diameter interlayer vias in low-moisture uptake and low surface-roughness dry film polymer dielectric for multi-layered re-distribution layer (RdL) structures to achieve 50 μm bump pitch in high density organic and glass interposers. A new series of polymer dry films, ZS-100, at 10 μm thickness were deposited on thin and low CTE organic or glass cores using double-sided vacuum lamination processes. The ultra-small vias were fabricated by 248nm KrF excimer laser drilling, followed by electroless and electrolytic copper plating. Fully-filled via structures were successfully fabricated without any chemical-mechanical polishing. The processes demonstrated in this paper achieve much finer bump pitch than current organic packages, and can be scaled to large panels leading to lower cost than previous work in fine pitch Si interposers using back-end of line (BEOL) wafer processes.

关键词： Copper Polymers dielectrics Wiring Laser ablation

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development of high performance multi-layer process with H2 plasma hardening

Development of high performance multi-layer process with H2 ...

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55th Society of Polymer Science Japan Symposium on Macromolecules

作者： Ishibashi, Takeo Ono, Yoshiharu Yamaguchi, Atsumi Hanawa, Tetsuro Tadokoro, Masahiro Yoshikawa, Kazunori Yonekura, Kazumasa Okumura, Haruki Matsunobe, Tsuyoshi Fujii, Yasushi Tanaka, Takeshi Terai, Mamoru Kumada, Teruhiko Renesas Technology Corp. Process Development Dept. 664-0005 Hyogo Japan Materials Science Lab. Toray Research Center Inc. 3-3-7 Otsu Shiga 525-8567 Japan Tokyo Ohka Kogyo Co. Ltd. Advanced Material Development Division 1 Research and Development Department 1590Tabata Samukawa-machi Koza-gun Kanagawa 253-0014 Japan Advanced Tech. R/D Center Mitsubishi Electric Corp. 8-1-1 Tsukaguchi-Honmachi Amagasaki Hyogo 661-8661 Japan

In the device manufacture after 45nm node utilization of a high precision carbon hard mask (C-HM) process is an important issue. We examined additional H2 plasma hardening treatment to the bottom organic layer in a conventional multi-layer resist process. Improved results in LWR caused by etching, which is called "wiggling", were obtained. Chemical constitution was analyzed to understand the mechanism of improvement. Analyses were carried out using GSP+FTIR and Raman spectroscopy. This hardening process will provide a very versatile C-HM process that is useful not only FEOL but also BEOL, which includes dual damascene process with via hole filling by the bottom organic layer.

关键词： Multilayers

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Royal Academy of Medicine in Ireland Section of Biomedical Sciences

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Irish Journal of Medical Science 1997年第3期166卷 157-194页

作者： W. Ruddock d. M. Burns J. C. W. Brown J. M. Allen d. G. Hirst G. P. Love A. K. Keenan C. Lally A. Bird M. P. Ryan N. O’Connor K. M. O’Boyle J. G. McGeown J. G. McCarron R. M. drummond F. S. Fay T. J. Connor J. P. Kelly B. E. Leonard L. Gilmartin G. O’Cuinn C. Macdonncha A. W. S. Watson S. McGrath K. J. Brady H-C. McKillen C. W. Taylor S. K. Smith S. Thornton A. d. Martin J. R. Bailie S. R. McKeown C. A. Higgins W. J. Hatton G. McKerr d. Harvey J. Carson B. M. Hannigan d. M. P. Morrow H. McGlynn C. M. G. Thompson C. Higgins E. S. Galligan M. M. Murray J. L. Leckey G. B. Nevin d. S. Soppitt M. H. Esfandiary W. S. Gilmore T. Robson T. dineen A. Greer J. A. Houghton K. d. O’Halloran A. Bradford M. McGuire M. Macdermott A. Coogan J. J. O’Connor C. S. Regan A. M. Redmond A. Harkin A. S. Lowe G. d. Baxter G. d. Kennovin M. Leek O. P. Friery M. V. Hejmadi L. H. Patterson J. Robinson I. Hill J. Kilbride K. d. Cotton M. A. Hollywood N. G. McHale K. d. Thornbury C. P. Halligan d. P. O’Connell B. J. Harvey P. Fanning A. O’Farrell d. Cantillon J. F. Cryan d. O’Leary d. T. O’Malley A. Nolan A. P. Moran K. A. Fitzgerald L. A. J. O’Neill A. McElligott A. H. Baker K. M. Joyce T. Ruane W. J. Hall F. Markos M. F. Carey C. Galvin E. R. Perl A. K. Curran C. Connolly K. Abdullah J. R. docherty K. T. Gavin M. Browne C-A. Frazer d. M. Walsh S. Atkinson d. Brown J. M. O’Connor G. R. Wasson M. P. Bonham V. J. McKelvey-Martin J. J. Strain C. S. downes T. M. dineen R. Powell B. Van Hemelrijk T. Mubarak Abujaffom B. Caulfield M. Garrett L. Brennan M. J. Griffin A. J. McShane P. N. Convery K. R. Milligan P. Quinn K. Scott J. P. H. Fee M. Cashman A. dunne E. Healy J. Walsh A. J. Watson G. Noble d. P. Campion B. F. Leek J. P. Ryan T. Quinn M. dumbleton K. M. Smith J. C. McGrath J. B. Macmillan L. doherty F. Lynch M. Sweeney R. G. O’Regan P. McLoughlin R. A. Padua S. dudeney J. O’Byrne R. Moran K. U. O’Kelly B. A. O. McCormack C. G. Lyons C. L. Brady C. Simms S. Maher B. Schreiber d. Taylor A. J. Carr B. Higgins G. J. dempsey S. Z. Imam M. Harbi Radiation Science Group School of Biomedical Sciences University of Ulster at Jordanstown Newtownabbey Co. Antrim N. Ireland Biotherapeutics Group School of Biomedical Sciences University of Ulster at Jordanstown Newtownabbey Co. Antrim N. Ireland Rehabilitation Sciences Research Group Schools of Health Sciences University of Ulster Jordanstown Northern Ireland Rehabilitation Sciences Research Group Schools of Health Sciences and Biomedical Sciences University of Ulster Jordanstown Northern Ireland Cancer and Aging Research Group School of Biomedical Sciences University of Ulster Coleraine Northern Ireland Radiation Science Research Group School of Biomedical Sciences University of Ulster at Jordanstown Newtownabbey Co. Antrim N. Ireland Radiation Sciences and Rehabilitation Sciences Research Groups. Schools of Health Sciences University of Ulster at Jordanstown Northern Ireland Radiation Sciences and Rehabilitation Sciences Research Groups. Schools of Health Biomedical Sciences University of Ulster at Jordanstown Northern Ireland Department of Pharmacology University College Dublin Belfield Dublin 4 Pharmacology Department University College Dublin Belfield Dublin 4 School of Biomedical Sciences University of Ulster at Coleraine Northern Ireland School of Applied Biological & Chemical Sciences University of Ulster at Coleraine Northern Ireland Department of Pharmacology University College Dublin Belfield Dublin 4 School of Biomedical Science Queen’s University of Belfast UK Institute of Biology and Life Sciences University of Glasgow UK UMass Medical Center Biomedical Imaging Group Massachusetts USA Department of Pharmacology University College Galway Ireland Department of Pharmacology University College Galway Department of Biochemistry University College Galway Department Life Sciences Regional Technical College Galway Growth and Development Research Centre University of Limerick Ireland Sports Injuries Research Centre University of Limerick Irel

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