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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

Nature ecology & evolution 2025年 2025 May 22页

作者： Stephen Pringle Martin Dallimer Mark A Goddard Léni K Le Goff Emma Hart Simon J Langdale Jessica C Fisher Sara-Adela Abad Marc Ancrenaz Fabio Angeoletto Fernando Auat Cheein Gail E Austen Joseph J Bailey Katherine C R Baldock Lindsay F Banin Cristina Banks-Leite Aliyu S Barau Reshu Bashyal Adam J Bates Jake E Bicknell Jon Bielby Petra Bosilj Emma R Bush Simon J Butler Dan Carpenter Christopher F Clements Antoine Cully Kendi F Davies Nicolas J Deere Michael Dodd Rosie Drinkwater Don A Driscoll Guillaume Dutilleux Mads Dyrmann David P Edwards Mohammad S Farhadinia Aisyah Faruk Richard Field Robert J Fletcher Chris W Foster Richard Fox Richard M Francksen Aldina M A Franco Alison M Gainsbury Charlie J Gardner Ioanna Giorgi Richard A Griffiths Salua Hamaza Marc Hanheide Matt W Hayward Marcus Hedblom Thorunn Helgason Sui P Heon Kevin A Hughes Edmund R Hunt Daniel J Ingram George Jackson-Mills Kelly Jowett Timothy H Keitt Laura N Kloepper Stephanie Kramer-Schadt Jim Labisko Frédéric Labrosse Jenna Lawson Nicolas Lecomte Ricardo F de Lima Nick A Littlewood Harry H Marshall Giovanni L Masala Lindsay C Maskell Eleni Matechou Barbara Mazzolai Alistair McConnell Brett A Melbourne Aslan Miriyev Eric Djomo Nana Alessandro Ossola Sarah Papworth Catherine L Parr Ana Payo-Payo Gad Perry Nathalie Pettorelli Rajeev Pillay Simon G Potts Miranda T Prendergast-Miller Lan Qie Persie Rolley-Parnell Stephen J Rossiter Marcus Rowcliffe Heather Rumble Jon P Sadler Christopher J Sandom Asiem Sanyal Franziska Schrodt Sarab S Sethi Adi Shabrani Robert Siddall Simón C Smith Robbert P H Snep Carl D Soulsbury Margaret C Stanley Philip A Stephens P J Stephenson Matthew J Struebig Matthew Studley Martin Svátek Gilbert Tang Nicholas K Taylor Kate D L Umbers Robert J Ward Patrick J C White Mark J Whittingham Serge Wich Christopher D Williams Ibrahim B Yakubu Natalie Yoh Syed A R Zaidi Anna Zmarz Joeri A Zwerts Zoe G Davies Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury UK. s.pringle@kent.ac.uk. Centre for Environmental Policy Imperial College London London UK. Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne UK. School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK. Synthotech Ltd Milner Court Hornbeam Square Harrogate UK. Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury UK. Mechanical Engineering Department University College London London UK. HUTAN SWD Kota Kinabalu Malaysia. Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brasil. Department of Engineering Harper Adams University Newport UK. Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge UK. Centre for Ecology and Hydrology Penicuik UK. Department of Life Sciences Imperial College London Silwood Park Campus Ascot UK. Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria. Greenhood Nepal Kathmandu Nepal. Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire UK. School of Biological and Environmental Sciences Liverpool John Moores University Liverpool UK. Lincoln Centre for Autonomous Systems University of Lincoln Lincoln UK. Royal Botanic Garden Edinburgh Edinburgh UK. School of Biological Sciences University of East Anglia Norwich Research Park Norwich UK. Digital Ecology Limited Bristol UK. School of Biological Sciences University of Bristol Bristol UK. Department of Computing Imperial College London London UK. Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA. Faculty of Science Technology Engineering and Mathematics (STEM) The Open University Walton Hall Milt

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more 'difficult' taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively.

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Three-dimensional super-resolution longitudinal magnetization spot arrays

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Light(Science & Applications) 2017年第1期6卷 630-637页

作者： Zhong-Quan Nie Han Lin Xiao-Fei Liu Ai-Ping Zhai Yan-Ting Tian Wen-Jie Wang Dong-Yu Li Wei-Qiang Ding Xue-Ru Zhang Ying-Lin Song Bao-Hua Jia Key Lab of Advanced Transducers and Intelligent Control Systems Ministry of Education of Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China Centre for Micro-Photonics Faculty of ScienceEngineering and TechnologySwinburne University of TechnologyHawthornVictoria 3122Australia Department of Science Taiyuan Institute of TechnologyTaiyuan 030008China Department of Physics Lingnan Normal UniversityZhanjiang 524048China Department of Physics Harbin Institute of TechnologyHarbin 150001China

We demonstrate an all-optical strategy for realizing spherical three-dimensional(3D)super-resolution(∼λ3/22)spot arrays of pure longitudinal magnetization by exploiting a 4πoptical microscopic setup with two high numerical aperture(NA)objective lenses,which focus and interfere two modulated vectorial *** phase filters(MPFs)are designed via an analytical approach derived from the vectorial Debye diffraction theory to modulate the two circularly polarized *** system is tailored to constructively interfere the longitudinal magnetization components,while simultaneously destructively interfering the azimuthal *** a result,the magnetization field is not only purely longitudinal but also super-resolved in all three ***,the MPFs can be designed analytically to control the number and locations of the super-resolved magnetization spots to produce both uniform and nonuniform arrays in a 3D ***,an all-optical control of all the properties of light-induced magnetization spot arrays has been demonstrated for the first *** results open up broad applications in magnetic-optical devices such as confocal and multifocal magnetic resonance microscopy,3D ultrahigh-density magneto-optic memory,and light-induced magneto-lithography.

关键词： inverse Faraday effect longitudinal magnetization magnetic-optical devices magneto-optics vectorial beams vectorial Debye diffraction theory

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Development of a global road safety performance function using deep neural networks

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International Journal of Transportation Science and technology 2017年第3期6卷 159-173页

作者： Pan, Guangyuan Fu, Liping Thakali, Lalita Department of Civil & Environmental Engineering University of Waterloo Waterloo N2L 3G1 ON Canada Intelligent Transportation Systems Research Centre Wuhan University of Technology Mailbox 125 No. 1040 Heping Road Wuhan 430063 Hubei China

This paper explores the idea of applying a machine learning approach to develop a global road safety performance function (SFP) that can be used to predict the expected crash frequencies of different highways from different regions. A deep belief network (DBN) – one of the most popular deep learning models is introduced as an alternative to the traditional regression models for crash modelling. An extensive empirical study is conducted using three real world crash data sets covering six classes of highways as defined by location (urban vs. rural), number of lanes, access control, and region. The study involves a number of experiments aiming at addressing several critical questions pertaining to the relative performance of the DBN in terms of network structure, training method, data size, and generalization ability, as compared to the traditional regression models. The experimental results have shown that a DBN model could be trained with different crash datasets with prediction performance being at least comparable to that of the locally calibrated negative binomial (NB) model. © 2017

关键词： Collision model Deep learning Global model Road safety

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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

arXiv

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arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

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Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program

arXiv

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arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

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Current status and framework of China's inland passenger ship safety system

Current status and framework of China's inland passenger shi...

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International Conference on Logistics, Informatics and Service Sciences (LISS)

作者： Shiqi Fan Di Zhang Eduardo Blanco-Davis Jin Wang Ming Huang Fan Zhang Xinping Yan School of Logistics Engineering National Engineering Research Centre for Water Transport Safety Wuhan China National Engineering Research Centre for Water Transport Safety Wuhan University of Technology Wuhan China Department of Maritime and Mechanical Engineering Liverpool John Moores University Liverpool United Kingdom School of Navigation Wuhan University of Technology Wuhan China National Engineering Research Centre for Water Transport Safety Intelligent Transport Systems Research Centre Wuhan China

ISBN: (纸本)9781509011032

Inland passenger shipping is one of the most convenient means of waterborne travel. However, recent serious accidents with passenger ships in China, have exposed a certain weakness in the country's inland passenger ship safety system. It is thus vital to overview the current conditions of China's inland passenger ship safety system, with regard to the different ship types, employment, management systems, legislative documents, specifications and standards, navigational regulations and emergency rescue procedures. In doing so, this paper analyses similarities and discrepancies with overseas inland river passenger ship safety systems. The paper then outlines the principles and proposes suggestions underlining the improved construction and implementation of the inland ship system. In particular, the last is done considering ship design, construction, operation, regulation, emergency rescue, practitioners, and relevant documents. The purpose of this work is to provide recommendations for policy making and scientific research on inland passenger transport with life cycle perspective.

关键词： Marine vehicles Safety Rivers Accidents Navigation Standards Europe

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A multivariate empirical mode decomposition based filtering for subject independent BCI

A multivariate empirical mode decomposition based filtering ...

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Irish Signals and systems Conference (ISSC)

作者： Pramod Gaur Ram Bilas Pachori Hui Wang Girijesh Prasad Intelligent Systems Research Centre Ulster University L'Derry U.K. Discipline of Electrical Engineering Indian Institute of Technology Indore Indore India School of Computing and Mathematics Ulster University Jordanstown U.K.

ISBN: (纸本)9781509034109

Goal: A brain-computer interface (BCI) provides a way to translate the motion intentions of human using brain signals such as electroencephalogram (EEG) into control commands. EEG signals are highly subject specific and non-stationary. One of the most challenging tasks is to classify motion intentions since the recorded EEG signals have inherent non-stationarities which are due to changes in the signal properties over time within as well as across sessions. Thus it becomes difficult to achieve a stable operation of BCI. Method: We present a novel filtering method based on the multivariate empirical mode decomposition (MEMD) using subject independent BCI (MEMD-SI-BCI) for classification of motor imagery (MI) based EEG signals to achieve enhanced BCI. A subject independent BCI can be used immediately by the new user without using the user's training data. The MEMD method helps to utilize the cross channel information and enhance localization properties. It decomposes multichannel EEG signals into a set of multivariate intrinsic mode functions (MIMFs). These MIMFs can be considered narrow-band, amplitude and frequency modulated (AM-FM) signals. The statistical property, namely, mean frequency measure of these MIMFs has been used to combine these MIMFs to compute the enhanced EEG signals which have major contributions due to μ and β rhythms over the motor cortex region. The objective of the proposed method is to filter EEG signals before feature extraction and classification to enhance the features separability and ultimately the BCI task classification performance. The common spatial pattern (CSP) feature has been computed from the enhanced EEG signals and has been used as a feature set for classification of left hand and right hand MIs using a linear discriminant analysis (LDA) based classification method. Results: We have achieved an improvement of >11% in the evaluation stage using the MEMD-SI-BCI method when compared with SI-BCI. Significance: This study helps to d

关键词： Electroencephalography Feature extraction Empirical mode decomposition Training Linear discriminant analysis Electrooculography Brain-computer interfaces

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A new unidirectional coupling for global synchronization of two Hindmarsh-Rose neurons

A new unidirectional coupling for global synchronization of ...

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第27届中国控制与决策会议

作者： Ke Ding Qing-Long Han School of Information Technology Jiangxi University of Finance and Economics Jiangxi E-commerce High Level Engineering Technology Research Centre Griffith School of Engineering Griffith UniversityGold Coast Campus Centre for Intelligent and Networked Systems Central Queensland University

ISBN: (纸本)9781479970186

In this paper,a new unidirectional coupling for global synchronization of two Hindmarsh-Rose neurons is *** with existing results,external control for global synchronization is no longer required.A synchronization criterion of two Hindmarsh-Rose neurons with rigorous mathematical proof is *** example is given to illustrate the effectiveness of the obtained result.

关键词： Synchronization,Unidirectional coupling,Hindmarsh-Rose neuron

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Mean-risk analysis of radio frequency identification technology in supply chain with inventory misplacement: Risk-sharing and coordination

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Omega 2014年 46卷 86-103页

作者： Shuang Chen Hongwei Wang Yong Xie Chao Qi Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science & Technology Wuhan 430074 PR China Economic Research Centre Technical Economy and Consultation Department Guangdong Electric Power Design Institute Guangzhou 510663 PR China

This paper investigates the application of radio frequency identification (RFID) technology to eliminate the misplacement problems in the supply chain, which consists of a risk-neutral manufacturer and a risk-averse retailer. By considering both fixed cost and tag cost of RFID implementation, we study the agents' incentives to adopt RFID in both uncoordinated and coordinated cases. We focus on analyzing the impact of risk attitudes on the agents’ incentives and on the supply chain coordination. The central semi-deviation is adopted to measure the retailer's risk attitude. In the uncoordinated case, we find that, in order to induce the retailer to adopt RFID, the manufacturer must assume more fixed cost if the retailer is more risk-averse. In the coordinated case, we first show that the standard revenue sharing contract does not always coordinate the channel. If the channel is coordinated, we observe that the agents’ incentives will be perfectly aligned and independent of the risk attitudes, if the revenue sharing ratio equals the fixed cost sharing ratio. Then we propose a risk-sharing contract that offers the risk protection to the retailer, to achieve the channel coordination. An interesting finding is that the manufacturer's incentive will not decrease with the tag cost, if she takes much risk from the retailer. The corresponding impacts of RFID adoption on the two contracts are also analyzed in this paper. Finally, a case study in a tobacco industry is presented to show the real RFID cost in practice.

关键词： RFID radio frequency identification MV mean–variance CSD central semi-deviation SSD second-order stochastic dominance PDF probability density function CDF cumulative density function Radio frequency identification Inventory misplacement Central semi-deviation Risk-averse Risk sharing Coordination

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World Congress Integrative Medicine & Health 2017: part two Berlin, Germany. 3-5 May 2017 Abstracts

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BMC COMPLEMENTARY AND ALTERNATIVE MEDICINE 2017年第SUPPL 1期17卷 317-317页

作者： [Anonymous] National Institute of Complementary Medicine Western Sydney University Sydney Australia Department of General Practice University of Melbourne Melbourne Australia School of Rehabilitation Therapy Queens University Ontario Canada School of Health and Biomedical Sciences RMIT University Melbourne Australia School of Public Health and Preventive Medicine Monash University Melbourne Australia NAFKAM UiT The Arctic University of Norway Tromsø 9019 Norway Department of Psychology University of Sheffield Sheffield S1 1HD UK Department of Community Medicine UiT The Arctic University of Norway Tromsø 9019 Norway Institue of General Practice Goethe University Frankfurt Frankfurt 60590 Germany Department of General Practice University of Tübingen Tübingen Germany Med.-pharm. Information/Klinische Forschung WALA Heilmittel GmbH Bad Boll/ Eckwälden 73087 Germany Ressortleitung Wissenschaft WALA Heilmittel GmbH Bad Boll/Eckwälden 73087 Germany University of Minnnesota Minneapolis 55455 MN USA Minneapolis College of Art and Design Minneapolis MN USA Duke University Durham NC USA Caring Bridge Minneapolis MN USA University of Minnesota Minneapolis 55455 MN USA Phytomedicines Supply and Development Center Innovation & Development Bayer Consumer Health Steigerwald Arzneimittelwerk GmbH Darmstadt 68526 Germany University Medicine of Rostock Rostock 18055 Germany Primary Care and Population Sciences University of Southampton Southampton UK Psychology University of Southampton Southampton UK Faculty of Health University of Technology Sydney Sydney 2007 Australia st Department of Pathology and Experimental Cancer Research Semmelweis University Budapest 1085 Hungary University of Alberta Edmonton Canada Parker University Dallas TX USA Canadian Memorial Chiropractic College Toronto Canada Anglo-European College of Chiropractic Bournemouth UK University of Calgary Calgary Canada University of Toronto Toronto Canada University of Hawaii at Manoa Honolulu Hawai’

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