Standard Indicators for the Social Appropriation of Science Persist Eu

Total Page:16

File Type:pdf, Size:1020Kb

Standard Indicators for the Social Appropriation of Science Persist Eu STANDARD INDICATORS FOR THE SOCIAL APPROPRIATION OF SCIENCE PERSIST_EU ERASMUS+ PROJECT Lessons learned Standard indicators for the social appropriation of science. Lessons learned First published: March 2021 ScienceFlows Research Data Collection © Book: Coordinators, authors and contributors © Images: Coordinators, authors and contributors © Edition: ScienceFlows and FyG consultores The Research Institute on Social Welfare Policy (Polibienestar) Campus de Tarongers C/ Serpis, 29. 46009. Valencia [email protected] How to cite: PERSIST_EU (2021). Standard indicators for the social appropriation of science: Lessons learned. Valencia (Spain): ScienceFlows & Science Culture and Innovation Unit of University of Valencia ISBN: 978-84-09-30199-7 This project has been funded with support from the European Commission under agreements 2018-1-ES01-KA0203-050827. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein. PERSIST_EU PROJECT Project number: 2018-1-ESO1-KA0203-050827 Project coordinator: Carolina Moreno-Castro (University of Valencia) COORDINATING PARTNER ScienceFlows- Universitat de València. Spain Carolina Moreno-Castro Empar Vengut-Climent Isabel Mendoza-Poudereux Ana Serra-Perales Amaia Crespo-Costa PARTICIPATING PARTNERS Instituto de Ciências Sociais da Universidade de Lisboa (ICS) Trnavská univerzita v Trnave Portugal Slovakia Ana Delicado Martin Fero Helena Vicente Lenka Diener João Estevens Peter Guran Jussara Rowland Karlsruher Institut Fuer Technology Danmar Computers (KIT) Poland Germany Margaret Miklosz Annette Leßmöllmann Chris Ciapala André Weiß Łukasz Kłapa Observa Science in Society FyG Consultores Italy Spain Giuseppe Pellegrini Fabián Gómez Andrea Rubin Aleksandra Staszynka Nieves Verdejo INDEX About the project and the book• 6 1. Cosmovision and worldviews of the university European students• 9 2. PERSIST_EU ICT tool• 14 2.1 What is the PERSIST tool• 15 3. Science Camps as an activity to use the tool• 20 3.1 Insights into the ScienceCamps 3.2 Results from the ScienceCamps 4. Common questions posed by participants on each topic• 35 4.1 Climate change• 36 4.2 Genetically Modified Organisms (GMO)• 42 4.3 Complementary and Alternative Medicine (CAM)• 47 4.4 Vaccines• 50 Annexes• 56 Annex 1. How to create and manage a questionnaire• 57 Annex 2. How to create personalized e-mails• 66 Annex 3. Activities to use the ICT platform• 67 Annex 4. Examples of sources for the questionnaires• 74 About the project and the book This book is the result of a two-and-a-half- the pandemic situation and the particular year close collaboration between the seven circumstances of COVID-19, the final number partners of the Erasmus+ KA203 project of participants was reduced, and the Science “Knowledge, beliefs, perceptions about the camps had to be held online (Teams, Zoom, science of European students (Persist_EU)”. Blackboard Collaborate) and not in person, during the spring of 2020, as originally planned. One of the project’s main objectives was to In any case, being online, we had an advantage, develop a tool to evaluate European students’ and that is that students from other universities initial knowledge when configuring their beliefs participated, and therefore the plurality of and perceptions about different science topics. participants increased. The Science Camps with Once the tool (platform) had been designed, the students of the five European universities the next step consisted of carrying out activities allowed us to know the modifications in the (Science camps), which would allow validating response scales, before and after the training, the platform and identifying changes in in the four blocks of questions on knowledge, perception (through questionnaires with Likert belief, trust and perception. All the results of scales), which students experienced during the five activities are collected in this book and their participation in training activities, organised guides to replicate the activities in other areas. within the framework of the project. For this, five From the project consortium, we hope that Science camps were organised in five European the results obtained will serve to support the universities, two in central Europe (Germany, platform’s use to make evaluations of specific Slovakia), and three nations in southern topics or other science dissemination activities Europe (Portugal, Spain and Italy). Therefore, and incorporate the research results into public we make sure to cover differences related to health or environmental programs. In short, it socio-geopolitical issues. The topics that were helps improve science communication. chosen for the debate were climate change, genetically-modified organisms (GMOs), The project had two central objectives linked complementary and alternative medicines to two intellectual outputs. The first intellectual (CAM) and vaccines, and it was expected product that we developed was an evaluation that around 100 students would participate in method, based on an open, online platform each of the universities of the PERSIST_EU so that in the future, any teaching activity consortium (Valencia, Karlsruhe Institute of and potentially at any educational level Technology, Trnava, Lisbon, and Vicenza). could evaluate whether students modify their worldview once they would acquire The original idea of the project was to have knowledge and training on a subject or, if the opinions of 500 students, 100 from each despite knowledge, the lack of confidence in of the participating universities, but due to science, or in a particular subject, continues Persist_EU 5 to persist. Therefore, launching the open- in terms of their social science. Besides, these access platform for everyone was the first scales can also measure when fundamentalist challenge. Subsequently, hard work was done positions are due to ideological or religious to incorporate a questionnaire into the platform issues. It can be identified when the responses to measure how the responses would be did not move. For this reason, we believe modified, through questionnaires with Likert’s that this type of platform can measure over scales, to be answered before and after time the profiles of students who have a more carrying out training activities. For example, inclined tendency to increase or decrease the how does the scale vary between the answer scale depending on how the debate presented to questionnaire 1, sent a week before the and how the expert defended their topic. training activity, and questionnaire 2, sent after attending the training activity, on topics such as The book, which is published in Open Access, vaccines? Probably, a student, before knowing consists of five chapters. In the first chapter, the risks that not being vaccinated can produce the state of the art is presented. In the second on public health, could have a different level of chapter, the design of the platform is explained. perception than after attending a formative talk Besides, a detailed description of the platform and a Socratic debate. That is the question that is made and how the questionnaires and we were seeking to identify with the project. questions were entered and how they must be used correctly. In the third chapter, it is The second intellectual output derived from explained how the Science Camps were PERSIST_EU is this book. This publication carried out in each university and the main includes the processes and steps that we results that were obtained. In the fourth carried out for the project’s execution and chapter, the main questions students posed, collects both the technical point of view and the the answers the experts provided, as well as a research results (through the activities). Once list of trustworthy online resources for the four the science camps have been held, we assess topics are presented, so they can be used for the weight that the activities have had in each support in different activities related to these participating country. The science camps helped topics. And, in the fifth and last chapter, the us verify the platform’s usability and validate annexes, including a detailed guide to using it as an evaluation instrument. Likewise, the the platform, and other included activities are questionnaires’ results, by checking how the detailed, as well as suggestions and proposals scales have moved, once the training activities for other activities that could be carried out to and debates were held, allowed us to analyse improve the experience. the differences between countries, gender and cultural differences among university students All the members of the PERSIST consortium have Persist_EU 6 participated in the book: Danmar Computers contributing authors, I would like to thank (Poland), FyG Consultores (Spain), Karlsruhe European students, experts, professors, and all Institute of Technology (Germany), Instituto de people who were deeply involved in managing Ciências Sociais (Portugal), Observa Science the development of the different Science in Society (Italy), Trnava University (Slovakia), Camps and the implication of this publication. and University of Valencia (Spain). The overall Also, a very special thanks to each partner’s work presented in this book was carried out leaders for providing editors with a trusting as part of the project PERSIST_EU, funded environment to prepare this publication. by the European Commission (Erasmus+ program 2018-1-ES01-KA0203-050827). Besides, this book’s publication
Recommended publications
  • Thebault Dagher Fanny 2020
    Université de Montréal Le stress chez les enfants avec convulsions fébriles : mécanismes et contribution au pronostic par Fanny Thébault-Dagher Département de psychologie Faculté des arts et des sciences Thèse présentée en vue de l’obtention du grade de Philosophae Doctor (Ph.D) en Psychologie – Recherche et Intervention option Neuropsychologie clinique Décembre 2019 © Fanny Thébault-Dagher, 2019 Université de Montréal Département de psychologie, Faculté des arts et des sciences Cette thèse intitulée Le stress chez les enfants avec convulsions fébriles : mécanismes et contribution au pronostic Présentée par Fanny Thébault-Dagher A été évaluée par un jury composé des personnes suivantes Annie Bernier Président-rapporteur Sarah Lippé Directrice de recherche Dave Saint-Amour Membre du jury Linda Booij Examinatrice externe Résumé Le stress est continuellement associé à la genèse, la fréquence et la sévérité des convulsions en épilepsie. De nombreux modèles animaux suggèrent qu’une relation entre le stress et les convulsions soit mise en place en début de vie, voire dès la période prénatale. Or, il existe peu de preuves de cette hypothèse chez l’humain. Ainsi, l’objectif général de cette thèse était d’examiner le lien entre le stress en début de vie, dès la conception, et les convulsions chez les humains. Pour ce faire, cette thèse avait comme intérêt principal les convulsions fébriles (CF). Il s’agit de convulsions pédiatriques communes et somme toute bénignes, bien qu’elles soient associées à de légères particularités neurologiques et cognitives. En ce sens, les CF représentent un syndrome de choix pour notre étude, considérant leur incidence fréquente en très bas âge et l’absence de conséquences majeures à long terme.
    [Show full text]
  • The Lasagna Plot
    PhUSE EU Connect 2018 Paper CT03 The Lasagna Plot Soujanya Konda, GlaxoSmithKline, Bangalore, India ABSTRACT Data interpretation becomes complex when the data contains thousands of digits, pages, and variables. Generally, such data is represented in a graphical format. Graphs can be tedious to interpret because of voluminous data, which may include various parameters and/or subjects. Trend analysis is most sought after, to maximize the benefits from a product and minimize the background research such as selection of subjects and so on. Additionally, dynamic representation and sorting of visual data will be used for exploratory data analysis. The Lasagna plot makes the job easier and represents the data in a pleasant way. This paper explains the basics of the Lasagna plot. INTRODUCTION In longitudinal studies, representation of trends using parameters/variables in the fields like pharma, hospitals, companies, states and countries is a little messy. Usually, the spaghetti plot is used to present such trends as individual lines. Such data is hard to analyze because these lines can get tangled like noodles. The other way to present data is HEATMAP instead of spaghetti plot. Swihart et al. (2010) proposed the name “Lasagna Plot” that helps to plot the longitudinal data in a more clear and meaningful way. This graph plots the data as horizontal layers, one on top of the other. Each layer represents a subject or parameter and each column represents a timepoint. Lasagna Plot is useful when data is recorded for every individual subject or parameter at the same set of uniformly spaced time intervals, such as daily, monthly, or yearly.
    [Show full text]
  • Fundamental Statistical Concepts in Presenting Data Principles For
    Fundamental Statistical Concepts in Presenting Data Principles for Constructing Better Graphics Rafe M. J. Donahue, Ph.D. Director of Statistics Biomimetic Therapeutics, Inc. Franklin, TN Adjunct Associate Professor Vanderbilt University Medical Center Department of Biostatistics Nashville, TN Version 2.11 July 2011 2 FUNDAMENTAL STATI S TIC S CONCEPT S IN PRE S ENTING DATA This text was developed as the course notes for the course Fundamental Statistical Concepts in Presenting Data; Principles for Constructing Better Graphics, as presented by Rafe Donahue at the Joint Statistical Meetings (JSM) in Denver, Colorado in August 2008 and for a follow-up course as part of the American Statistical Association’s LearnStat program in April 2009. It was also used as the course notes for the same course at the JSM in Vancouver, British Columbia in August 2010 and will be used for the JSM course in Miami in July 2011. This document was prepared in color in Portable Document Format (pdf) with page sizes of 8.5in by 11in, in a deliberate spread format. As such, there are “left” pages and “right” pages. Odd pages are on the right; even pages are on the left. Some elements of certain figures span opposing pages of a spread. Therefore, when printing, as printers have difficulty printing to the physical edge of the page, care must be taken to ensure that all the content makes it onto the printed page. The easiest way to do this, outside of taking this to a printing house and having them print on larger sheets and trim down to 8.5-by-11, is to print using the “Fit to Printable Area” option under Page Scaling, when printing from Adobe Acrobat.
    [Show full text]
  • Master Thesis
    Pelvis Runner Vergleichende Visualisierung Anatomischer Änderungen DIPLOMARBEIT zur Erlangung des akademischen Grades Diplom-Ingenieur im Rahmen des Studiums Visual Computing eingereicht von Nicolas Grossmann, BSc Matrikelnummer 01325103 an der Fakultät für Informatik der Technischen Universität Wien Betreuung: Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Eduard Gröller Mitwirkung: Univ.Ass. Renata Raidou, MSc PhD Wien, 5. August 2019 Nicolas Grossmann Eduard Gröller Technische Universität Wien A-1040 Wien Karlsplatz 13 Tel. +43-1-58801-0 www.tuwien.ac.at Pelvis Runner Comparative Visualization of Anatomical Changes DIPLOMA THESIS submitted in partial fulfillment of the requirements for the degree of Diplom-Ingenieur in Visual Computing by Nicolas Grossmann, BSc Registration Number 01325103 to the Faculty of Informatics at the TU Wien Advisor: Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Eduard Gröller Assistance: Univ.Ass. Renata Raidou, MSc PhD Vienna, 5th August, 2019 Nicolas Grossmann Eduard Gröller Technische Universität Wien A-1040 Wien Karlsplatz 13 Tel. +43-1-58801-0 www.tuwien.ac.at Erklärung zur Verfassung der Arbeit Nicolas Grossmann, BSc Hiermit erkläre ich, dass ich diese Arbeit selbständig verfasst habe, dass ich die verwen- deten Quellen und Hilfsmittel vollständig angegeben habe und dass ich die Stellen der Arbeit – einschließlich Tabellen, Karten und Abbildungen –, die anderen Werken oder dem Internet im Wortlaut oder dem Sinn nach entnommen sind, auf jeden Fall unter Angabe der Quelle als Entlehnung kenntlich gemacht habe. Wien, 5. August 2019 Nicolas Grossmann v Acknowledgements More than anyone else, I want to thank my supervisor Renata Raidou for her constructive feedback and her seemingly endless stream of ideas. It was because of her continuous encouragement that I was able to take my first steps towards a scientific career.
    [Show full text]
  • Eappendix 1: Lasagna Plots: a Saucy Alternative to Spaghetti Plots
    eAppendix 1: Lasagna plots: A saucy alternative to spaghetti plots Bruce J. Swihart, Brian Caffo, Bryan D. James, Matthew Strand, Brian S. Schwartz, Naresh M. Punjabi Abstract Longitudinal repeated-measures data have often been visualized with spaghetti plots for continuous outcomes. For large datasets, the use of spaghetti plots often leads to the over-plotting and consequential obscuring of trends in the data. This obscuring of trends is primarily due to overlapping of trajectories. Here, we suggest a framework called lasagna plotting that constrains the subject-specific trajectories to prevent overlapping, and utilizes gradients of color to depict the outcome. Dynamic sorting and visualization is demonstrated as an exploratory data analysis tool. The following document serves as an online supplement to “Lasagna plots: A saucy alternative to spaghetti plots.” The ordering is as follows: Additional Examples, Code Snippets, and eFigures. Additional Examples We have used lasagna plots to aid the visualization of a number of unique disparate datasets, each presenting their own challenges to data exploration. Three examples from two epidemiologic studies are featured: the Sleep Heart Health Study (SHHS) and the Former Lead Workers Study (FLWS). The SHHS is a multicenter study on sleep-disordered breathing (SDB) and cardiovascular outcomes.1 Subjects for the SHHS were recruited from ongoing cohort studies on respiratory and cardiovascular disease. Several biosignals for each of 6,414 subjects were collected in-home during sleep. Two biosignals are displayed here-in: the δ-power in the electroencephalogram (EEG) during sleep and the hypnogram. Both the δ-power and the hypnogram are stochastic processes. The former is a discrete- time contiuous-outcome process representing the homeostatic drive for sleep and the latter a discrete-time discrete-outcome process depicting a subject’s trajectory through the rapid eye movement (REM), non-REM, and wake stages of sleep.
    [Show full text]
  • Yonette F. Thomas · Leshawndra N. Price Editors Drug Use Trajectories Among Minority Youth Drug Use Trajectories Among Minority Youth
    Yonette F. Thomas · LeShawndra N. Price Editors Drug Use Trajectories Among Minority Youth Drug Use Trajectories Among Minority Youth Yonette F. Thomas • LeShawndra N. Price Editors Drug Use Trajectories Among Minority Youth Editors Yonette F. Thomas LeShawndra N. Price The New York Academy of Medicine and Health Inequities and Global Health Branch the American Association of Geographers National Heart Lung and Blood Institute, Glenn Dale , MD , USA National Institutes of Health Bethesda , MD , USA ISBN 978-94-017-7489-5 ISBN 978-94-017-7491-8 (eBook) DOI 10.1007/978-94-017-7491-8 Library of Congress Control Number: 2016946341 © Springer Science+Business Media Dordrecht 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.
    [Show full text]
  • Displaying Your Data
    Basics and Beyond: Displaying Your Data Mario Davidson, PhD Vanderbilt University School of Medicine Department of Biostatistics Instructor Objectives 1.Understand the types of data and levels of measurement 2.Understand how a Table 1 typically looks 3.Be able to interpret all of the basic graphs. 4.Know the type of displays that may be used dependent upon the type of data and level of measurement 5.Be introduced to less familiar displays of the data Types of Data (Obj1) ●Qualitative Data ● Consist of attributes, labels, or non-numerical entries. ● If you can’t perform mathematical operations or order data, it’s qualitative. ● Ex: Colors in a box of crayons; names; county ●Quantitative Data ● Consist of numerical measurements or counts. ● Ordering is a dead give away ● Ex: BMI; age; numerical grade Levels of Measurement (Obj1) ●Nominal ● Qualitative ● Categorized using names, qualities, or labels ● Ex: Top 5 movies, jersey numbers, type of drug ●Ordinal ● Quantitative or Qualitative ● Can order ● Differences between data are not meaningful. ● Ex: Letter grade, Likert scale such as very dissatisfied to very satisfied Levels of Measurement (Obj1) ●Interval Level of Measurement ● Quantitative ● Can order ● Can calculate meaningful differences ● No Value that means “nothing/none.” A zero entry merely represents a position on a scale (i.e. no inherent zero). ● Ex: Time of day, temperature ●Ratio Level of Measurement ● Quantitative ● Can order ● Can calculate meaningful differences ● There’s a value that means “nothing/none.” ● Ex: Age, weight, test score Popular Displays Description of Table 1 (Obj2) Typically summarizes baseline characteristics of the data. Compares statistics between groups May provide means, medians, confidence intervals, percentiles, percentages, p-values, standard deviations, etc.
    [Show full text]
  • Spaghetti Is Good for More Than Just Eating September/October 2009
    Datum Vol. 15, No. 4 September/October 2009 1 Department of Population Health, Medical College of Wisconsin Datum Newsletter of the Biostatistics & Epidemiology Key Function of the CTSI It Figures Aniko Szabo, Ph.D. Division of Biostatistics Volume 15, Number 4 Spaghetti is good for more than just eating September/October 2009 The previous “It Figures” article (Datum, Volume 15, Number 3) discussed how showing the underlying data values using dot plots can enhance a plot. Spaghetti plots, also called profile plots, are an extension of the same idea for longitudinal data. Longitudinal data is commonly plotted by showing the mean and standard error at each time-point. Such plots have several problems: 1) The average of the response trajectories is often not the “average” or typical trajectory. In fact, it might not resemble any of the actual trajectories. 2) The error bars don’t show the nature of the variability around the mean. Is an increase in the mean typical among all subjects, or is it just driven by a few outliers? Perhaps some subjects have consistently high/low values, but the time-trend is very In this issue: similar for everybody, or, conversely, the values keep varying around the average for everybody? 3) If the timing of measurement varies between subjects, rounding or approximation It Figures might be needed to collect enough values at each time-point for averaging. Spaghetti Plots . 1 In a spaghetti plot the trajectory of the measurements for all the individuals On the Map News from the world of are shown. The result often looks GIS .
    [Show full text]
  • A Sassy Substitute to Represent the Longitudinal Data – the Lasagna Plot Soujanya Konda, IQVIA, Germany
    PharmaSUG 2021 – Paper DV-200 A Sassy substitute to represent the longitudinal data – The Lasagna Plot Soujanya Konda, IQVIA, Germany ABSTRACT Data interpretation becomes complex when the data contains thousands of digits, pages, and variables. Generally, such data is represented in a graphical format. Graphs can be tedious to interpret because of voluminous data, which may include various parameters and/or subjects. Trend analysis is most sought after, to maximize the benefits from a product and minimize the background research such as selection of subjects and so on. Additionally, dynamic representation and sorting of visual data will be used for exploratory data analysis. The Lasagna plot makes the job easier and represents the data in a pleasant way. This paper explains the tips and tricks of the Lasagna plot. INTRODUCTION In longitudinal studies, representation of trends using parameters/variables in the fields like pharma, hospitals, companies, states and countries is a little messy. Usually, the spaghetti plot is used to present such trends as individual lines. Such data is hard to analyze because these lines can get tangled like noodles. The other way to present data is HEATMAP instead of spaghetti plot. Swihart et al. (2010) proposed the name “Lasagna Plot” that helps to plot the longitudinal data in a more clear and meaningful way. This graph plots the data as horizontal layers, one on top of the other. Each layer represents a subject or parameter and each column represents a timepoint. Lasagna Plot is useful when data is recorded for every individual subject or parameter at the same set of uniformly spaced time intervals, such as daily, monthly, or yearly.
    [Show full text]
  • Cellular Correlates of Cortical Thinning Throughout the Lifespan Didac Vidal‑Pineiro1, Nadine Parker2,3, Jean Shin4, Leon French5, Håkon Grydeland1, Andrea P
    www.nature.com/scientificreports OPEN Cellular correlates of cortical thinning throughout the lifespan Didac Vidal‑Pineiro1, Nadine Parker2,3, Jean Shin4, Leon French5, Håkon Grydeland1, Andrea P. Jackowski6,7, Athanasia M. Mowinckel1, Yash Patel2,3, Zdenka Pausova4, Giovanni Salum7,8, Øystein Sørensen1, Kristine B. Walhovd1,9, Tomas Paus2,3,10*, Anders M. Fjell1,9* & the Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle fagship study of ageing Cortical thinning occurs throughout the entire life and extends to late‑life neurodegeneration, yet the neurobiological substrates are poorly understood. Here, we used a virtual‑histology technique and gene expression data from the Allen Human Brain Atlas to compare the regional profles of longitudinal cortical thinning through life (4004 magnetic resonance images [MRIs]) with those of gene expression for several neuronal and non‑neuronal cell types. The results were replicated in three independent datasets. We found that inter‑regional profles of cortical thinning related to expression profles for marker genes of CA1 pyramidal cells, astrocytes and, microglia during development and in aging. During the two stages of life, the relationships went in opposite directions: greater gene expression related to less thinning in development and vice versa in aging. The association between cortical thinning and cell‑specifc gene expression was also present in mild cognitive impairment and Alzheimer’s Disease. These fndings suggest a role of astrocytes and microglia in promoting and supporting neuronal growth and dendritic structures through life that afects cortical thickness during development, aging, and neurodegeneration. Overall, the fndings contribute to our understanding of the neurobiology underlying variations in MRI‑derived estimates of cortical thinning through life and late‑life disease.
    [Show full text]
  • Arxiv:1604.05895V1 [Physics.Data-An] 20 Apr 2016 Horace .A Ewings, A
    Horace: software for the analysis of data from single crystal spectroscopy experiments at time-of-flight neutron instruments. R. A. Ewings,1 A. Buts,1 M. D. Le,1 J. van Duijn,2 I. Bustinduy,3 and T. G. Perring1,4, ∗ 1ISIS Facility, STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot OX11 0QX, United Kingdom 2Departamento de Mec´anica, Universidad de C´ordoba, C´ordoba, 14071, Spain 3ESS Bilbao, Poligono Ugaldeguren III, Pol. A, 7B. 48170 Zamudio, Bizkaia - Pa´ıs Vasco, Spain 4London Centre for Nanotechnology, 17-19 Gordon Street, London WC1H 0AH, United Kingdom (Dated: April 21, 2016) The Horace suite of programs has been developed to work with large multiple-measurement data sets collected from time-of-flight neutron spectrometers equipped with arrays of position-sensitive detectors. The software allows exploratory studies of the four dimensions of reciprocal space and ex- citation energy to be undertaken, enabling multi-dimensional subsets to be visualized, algebraically manipulated, and models for the scattering to simulated or fitted to the data. The software is de- signed to be an extensible framework, thus allowing user-customized operations to be performed on the data. Examples of the use of its features are given for measurements exploring the spin waves of the simple antiferromagnet RbMnF3 and ferromagnetic iron, and the phonons in URu2Si2. arXiv:1604.05895v1 [physics.data-an] 20 Apr 2016 2 I. INTRODUCTION Neutron spectrometers at central facilities around the world are routinely used to measure the wave-vector, Q, and energy, ~ω, dependency of the spectrum of lattice dynamics and magnetic excitations, S(Q,ω).
    [Show full text]
  • Structural Growth Trajectories and Rates of Change in the First 3 Months of Infant Brain Development
    Supplementary Online Content Holland D, Chang L, Ernst TM, Curran M, Buchthal SD, Alicata D, Skranes J, Johansen H, Hernandez A, Yamakawa R, Kuperman JM, Dale AM. Structural growth trajectories and rates of change in the first 3 months of infant brain development. JAMA Neurol. Published online August 11, 2014. doi:10.1001/jamaneurol.2014.1638. eIntroduction. eMethods. eResults. eTable 1. Comparison of automatic and manual segmentation. eTable 2. Whole-brain growth trajectories: model results eTable 3. Whole-brain growth trajectories: model results eFigure 1. Comparison of manual and automatic segmentation eFigure 2. Whole-brain growth trajectories, including controlling for head circumference at birth eFigure 3. Volume-for-age percentile plots, and residualized volume-for-age percentile plots eFigure 4. Growth trajectories and rates of change for caudate, cerebellum, putamen, and lateral ventricles. eFigure 5. Growth trajectories and rates of change for amygdala, hippocampus, thalamus, and brain stem. eFigure 6. Volume-by age percentile plots for caudate, cerebellum, putamen, and lateral ventricles. eFigure 7. Spaghetti plot of volume difference between left and right lateral ventricles eFigure 8. Spaghetti plots of volume difference between left and right ROIs, for amygdala, hippocampus, caudate, thalamus, putamen, and cerebellum. eReferences. This supplementary material has been provided by the authors to give readers additional information about their work. © 2014 American Medical Association. All rights reserved. 1 Downloaded From:
    [Show full text]