Search

Your search keyword '"Andy Nelson"' showing total 32 results
Start Over Author "Andy Nelson"
32 results on '"Andy Nelson"'

1. Long-term assessment of ecosystem services at ecological restoration sites using Landsat time series.

Author

Trinidad Del Río-Mena, Louise Willemen, Anton Vrieling, Andy Snoeys, and Andy Nelson

Subjects
Medicine, Science
Abstract

Reversing ecological degradation through restoration activities is a key societal challenge of the upcoming decade. However, lack of evidence on the effectiveness of restoration interventions leads to inconsistent, delayed, or poorly informed statements of success, hindering the wise allocation of resources, representing a missed opportunity to learn from previous experiences. This study contributes to a better understanding of spatial and temporal dynamics of ecosystem services at ecological restoration sites. We developed a method using Landsat satellite images combined with a Before-After-Control-Impact (BACI) design, and applied this to an arid rural landscape, the Baviaanskloof in South Africa. Since 1990, various restoration projects have been implemented to halt and reverse degradation. We applied the BACI approach at pixel-level comparing the conditions of each intervened pixel (impact) with 20 similar control pixels. By evaluating the conditions before and after the restoration intervention, we assessed the effectiveness of long-term restoration interventions distinguishing their impact from environmental temporal changes. The BACI approach was implemented with Landsat images that cover a 30-year period at a spatial resolution of 30 meter. We evaluated the impact of three interventions (revegetation, livestock exclusion, and the combination of both) on three ecosystem services; forage provision, erosion prevention, and presence of iconic vegetation. We also evaluated whether terrain characteristics could partially explain the variation in impact of interventions. The resulting maps showed spatial patterns of positive and negative effects of interventions on ecosystem services. Intervention effectiveness differed across vegetation conditions, terrain aspect, and soil parent material. Our method allows for spatially explicit quantification of the long-term restoration impact on ecosystem service supply, and for the detailed visualization of impact across an area. This pixel-level analysis is specifically suited for heterogeneous landscapes, where restoration impact not only varies between but also within restoration sites.

Published
2021
Full Text
View/download PDF

2. Winter cover crops in Dutch maize fields: Variability in quality and its drivers assessed from multi-temporal Sentinel-2 imagery

Author

Xinyan Fan, Anton Vrieling, Bert Muller, and Andy Nelson

Subjects
Catch crop, Sentinel-2, Sowing time, NDVI time series, Phenological analysis, Temperature, Physical geography, GB3-5030, Environmental sciences, GE1-350
Abstract

Planting a cover crop between the main cropping seasons is an agricultural management measure with multiple potential benefits for sustainable food production. In the maize production system of the Netherlands, an effective establishment of a winter cover crop is important for reducing nitrogen leaching to groundwater. Cover crop establishment after maize cultivation is obliged by law for sandy soils and consequently implemented on nearly all maize fields, but the winter-time vegetative ground cover varies significantly between fields. The objectives of this study are to assess the variability in winter vegetative cover and evaluate to what extent this variability can be explained by the timing of cover crop establishment and weather conditions in two growing seasons (2017–2018). We used Sentinel-2 satellite imagery to construct NDVI time series for fields known to be cultivated with maize within the province of Overijssel. We fitted piecewise logistic functions to the time series in order to estimate cover crop sowing date and retrieve the fitted NDVI value for 1 December (NDVIDec). We used NDVIDec to represent the quality of cover crop establishment at the start of the winter season. The Sentinel-2 estimated sowing dates compared reasonably with ground reference data for eight fields (RMSE = 6.6 days). The two analysed years differed considerably, with 2018 being much drier and warmer during summer. This drought resulted in an earlier estimated cover crop sowing date (on average 19 days) and an NDVIDec value that was 0.2 higher than in 2017. Combining both years and all fields, we found that Sentinel-2 retrieved sowing dates could explain 55% of the NDVIDec variability. This corresponded to a positive relationship (R2 = 0.50) between NDVIDec and the cumulative growing degree days (GDD) between sowing date and 1 December until reaching 400 GDD. Based on cumulative GDD derived from two weather stations within Overijssel, we found that on average for the past three decades a sowing date of 19 September (± 7 days) allowed to attain these 400 GDD; this provides support for the current legislation that states that from 2019 onwards a cover crop should be sown before 1 October. To meet this deadline, while simultaneously ascertaining a harvest-ready main crop, in practice implies that undersowing of the cover crop during spring will gain importance. Our results show that Sentinel-2 NDVI time series can assess the effectiveness and timing of cover crop growth for small agricultural fields, and as such has potential to inform regulatory frameworks as well as farmers with actionable information that may help to reduce nitrogen leaching.

Published
2020
Full Text
View/download PDF

3. Understanding Intra-Annual Dynamics of Ecosystem Services Using Satellite Image Time Series

Author

Trinidad del Río-Mena, Louise Willemen, Anton Vrieling, and Andy Nelson

Subjects
integrated monitoring, temporal variability, isodata clustering, seasonality, sentinel-2, remote sensing, Science
Abstract

Landscape processes fluctuate over time, influencing the intra-annual dynamics of ecosystem services. However, current ecosystem service assessments generally do not account for such changes. This study argues that information on the dynamics of ecosystem services is essential for understanding and monitoring the impact of land management. We studied two regulating ecosystem services (i. erosion prevention, ii. regulation of water flows) and two provisioning services (iii. provision of forage, iv. biomass for essential oil production) in thicket vegetation and agricultural fields in the Baviaanskloof, South Africa. Using models based on Sentinel-2 data, calibrated with field measurements, we estimated the monthly supply of ecosystem services and assessed their intra-annual variability within vegetation cover types. We illustrated how the dynamic supply of ecosystem services related to temporal variations in their demand. We also found large spatial variability of the ecosystem service supply within a single vegetation cover type. In contrast to thicket vegetation, agricultural land showed larger temporal and spatial variability in the ecosystem service supply due to the effect of more intensive management. Knowledge of intra-annual dynamics is essential to jointly assess the temporal variation of supply and demand throughout the year to evaluate if the provision of ecosystem services occurs when most needed.

Published
2020
Full Text
View/download PDF

4. A Review of Roads Data Development Methodologies

Author

Taro Ubukawa, Alex de Sherbinin, Harlan Onsrud, Andy Nelson, Karen Payne, Olivier Cottray, and Mikel Maron

Subjects
Science (General), Q1-390
Abstract

There is a clear need for a public domain data set of road networks with high special accuracy and global coverage for a range of applications. The Global Roads Open Access Data Set (gROADS), version 1, is a first step in that direction. gROADS relies on data from a wide range of sources and was developed using a range of methods. Traditionally, map development was highly centralized and controlled by government agencies due to the high cost or required expertise and technology. In the past decade, however, high resolution satellite imagery and global positioning system (GPS) technologies have come into wide use, and there has been significant innovation in web services, such that a number of new methods to develop geospatial information have emerged, including automated and semi-automated road extraction from satellite/aerial imagery and crowdsourcing. In this paper we review the data sources, methods, and pros and cons of a range of road data development methods: heads-up digitizing, automated/semi-automated extraction from remote sensing imagery, GPS technology, crowdsourcing, and compiling existing data sets. We also consider the implications for each method in the production of open data.

Published
2014
Full Text
View/download PDF

5. Crowd-Driven and Automated Mapping of Field Boundaries in Highly Fragmented Agricultural Landscapes of Ethiopia with Very High Spatial Resolution Imagery

Author

Michael Marshall, Sophie Crommelinck, Divyani Kohli, Christoph Perger, Michael Ying Yang, Aniruddha Ghosh, Steffen Fritz, Kees de Bie, and Andy Nelson

Subjects
agriculture, cropland, food security, image segmentation, object detection, crowdsourcing, remote sensing, WorldView, Science
Abstract

Mapping the extent and location of field boundaries is critical to food security analysis but remains problematic in the Global South where such information is needed the most. The difficulty is due primarily to fragmentation in the landscape, small farm sizes, and irregular farm boundaries. Very high-resolution satellite imagery affords an opportunity to delineate such fields, but the challenge remains of determining such boundaries in a systematic and accurate way. In this paper, we compare a new crowd-driven manual digitization tool (Crop Land Extent) with two semi-automated methods (contour detection and multi-resolution segmentation) to determine farm boundaries from WorldView imagery in highly fragmented agricultural landscapes of Ethiopia. More than 7000 one square-kilometer image tiles were used for the analysis. The three methods were assessed using quantitative completeness and spatial correctness. Contour detection tended to under-segment when compared to manual digitization, resulting in better performance for larger (approaching 1 ha) sized fields. Multi-resolution segmentation on the other hand, tended to over-segment, resulting in better performance for small fields. Neither semi-automated method in their current realizations however are suitable for field boundary mapping in highly fragmented landscapes. Crowd-driven manual digitization is promising, but requires more oversight, quality control, and training than the current workflow could allow.

Published
2019
Full Text
View/download PDF

6. Repurposing a learning activity on academic integrity: the experience of three universities

Author

Karen Fill, Samuel Leung, David DiBiase, and Andy Nelson

Subjects
online learning, reuse, learning resources repositories, benefits, repurposing resources, plagiarism, innovation, educational technology, Theory and practice of education, LB5-3640
Abstract

Abstract: There is currently great interest in reuse of digital learning resources, from single items to multi-task activities, to whole units or programmes of study. Associated with this interest is the ongoing development of tools to enable such resources to be placed in or recovered from repositories, to facilitate searching for them and their instantiation on different learning platforms. Many of these tools are highly technical, in terms of both technology and terminology, and they are the province of learning technologists and computer scientists, rather than teachers. Concentration on such tools begs the question as to whether teachers and learners will truly benefit from reuse of learning resources. This paper describes the re-purposing of a learning activity created in a university in the US for use in two UK universities. The case study approach facilitates comparison of the technical and content issues that were addressed and resolved. The authors formulate and explore a proposition about the validity of an 'object based' approach to learning resources and conclude with a plea for better tools for teachers.Interactive demonstrations: The learning activities are available at www.dialogplus.soton.ac.uk/aig/index.html.

Published
2006
Full Text
View/download PDF

8. PRISMA and Sentinel-2 spectral response to the nutrient composition of grains

Author

Mariana Belgiu, Michael Marshall, Mirco Boschetti, Monica Pepe, Alfred Stein, Andy Nelson, Department of Earth Observation Science, Digital Society Institute, UT-I-ITC-ACQUAL, Faculty of Geo-Information Science and Earth Observation, Department of Natural Resources, and UT-I-ITC-FORAGES

Subjects
ITC-HYBRID, ITC-ISI-JOURNAL-ARTICLE, Hyperspectral images, UT-Hybrid-D, Soil Science, Geology, Agriculture, Food security, Computers in Earth Sciences, Hidden hunger
Abstract

Micronutrient malnutrition is a global challenge affecting >2 billion people, in particular those with a crop-based diet and limited access to nutrient-rich food sources. Conventional methods for measuring the crop nutrients such as wet chemical analysis of grains are time-consuming and cost-prohibitive and, consequently, unsuitable for the consistent quantification of nutrients across space and time. In this study, we propose a new method that is using PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Sentinel-2 images to estimate the nutrient concentrations of crop grains before harvest. We collected grain samples for corn, rice, soybean, and wheat from a farm situated in Italy and measured their nutrient concentrations in the lab. These measurements together with the PRISMA and Sentinel-2 images acquired at the main phases of crop development (vegetative, reproductive, maturity) were used as input for two-band vegetation indices (TBVIs) and Partial Least Squares Regression (PLSR) to predict Calcium (Ca), Iron (Fe), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulphur (S) and Zinc (Zn). Models' performances were assessed using the coefficient of determination (R2) and Root Mean Square Error (RMSE). For PRISMA images, the best prediction results were obtained for P in soybean (R2 = 0.69), K in soybean (R2 = 0.66), Mg in soybean (R2 = 0.58), Fe in soybean (R2 = 0.57), K in wheat (R2 = 0.57), K in corn (R2 = 0.55), P in wheat (R2 = 0.51), S in rice (R2 = 0.58) using TBVIs. In contrast to PRISMA, PLSR outperformed TBVIs when Sentinel-2 images were used as input. For Sentinel-2, the best predictions were obtained for P in soybean (R2 = 0.73), K in wheat (R2 = 0.67), Mg in soybean (R2 = 0.62), Zn in wheat (R2 = 0.56), Fe in soybean (R2 = 0.52), P in wheat (R2 = 0.52). Our study showed that estimating the nutrient composition of crops using remote sensing images has the potential to change how we approach a cost-effective, timely, and spatially explicit representation of the crops' nutritional quality.

Published
2023
Full Text
View/download PDF

13. Is the Promise of PROMs Being Realized? Implementation Experience in a Large Orthopedic Practice

Author

Jeanette Y. Ziegenfuss, Elizabeth S. Grossman, Leif I. Solberg, Ella A. Chrenka, Ann Werner, Stephen E. Asche, Christine K. Norton, Andy Nelson, Megan Reams, and Robin R. Whitebird

Subjects
Orthopedics, Research Design, Health Policy, Surveys and Questionnaires, Patient-Centered Care, Humans, Patient Reported Outcome Measures
Abstract

Patient-reported outcome measures (PROMs), increasingly used for research and quality measurement, are lauded for their potential to improve patient-centered care, both through aggregate reporting and when integrated into clinical practice. However, there are few published studies of the resultant use of PROMs in clinical practice. This case study describes the implementation and use of PROMS in a Midwestern multispecialty medical group orthopedic practice among patients undergoing total knee and hip surgery. Specifically, rates of PROMs use by care teams are tracked over time once made available in the electronic health record. During this time, the orthopedics department achieved a patient PROMS survey response rate of 68% at baseline, 58% 3 months post-surgery, and 55% 12 months post-surgery. However, these data were only accessed by the care teams for fewer than 1% of associated clinical encounters. This suggests that making PROMs available for care team review in the electronic health record, even when coupled with relatively high response rates from patients and departmental leadership support is not enough to encourage integration of PROMs into clinical care for patients. Additional effort is required to identify barriers to PROMs use in clinical care and to test methods to enhance use.

Published
2022

14. A colorimetric chemical tongue detects and distinguishes between multiple analytes

Author

Francis Buan Hong Lim, Tingjun Lei, Gabriella Fernandez, Nicole Lopez, Andre-Lorenz Chu, Allan Valiente, Abhignyan Nagesetti, Andy Nelson, Kerstin Schmidt, Ta Chen Chang, Obdulio Piloto, and Ian Cheong

Subjects
Tongue, Electrochemistry, Environmental Chemistry, Colorimetry, Hydrogels, Biochemistry, Spectroscopy, Analytical Chemistry, Polymerization
Abstract

The rate-limiting step for diagnostics development is the discovery and validation of biomarker analytes. We describe a new analyte-agnostic and label-free approach based on colorimetric reactions involving type I polymerization photoinitiators. We demonstrate that a chemically diverse array of hydrogels embedded with cleaved type I photoinitiators could act as microreactors, undergoing colorimetric reactions with bound analytes. The colorimetric signatures produced were visually distinctive and readable with a flatbed document scanner. Signatures of a broad range of sample types were accurately differentiated by unsupervised clustering without knowledge of any analytes bound to the array. The principles described have the potential to enable scalable and cost-effective analysis of complex samples.

Published
2022

15. Field-level crop yield estimation with PRISMA and Sentinel-2

Author

Michael Marshall, Mariana Belgiu, Mirco Boschetti, Monica Pepe, Alfred Stein, Andy Nelson, Department of Natural Resources, UT-I-ITC-FORAGES, Faculty of Geo-Information Science and Earth Observation, Department of Earth Observation Science, and UT-I-ITC-ACQUAL

Subjects
ITC-HYBRID, Hyperspectral, ITC-ISI-JOURNAL-ARTICLE, Machine learning, UT-Hybrid-D, Agriculture, Computers in Earth Sciences, Remote sensing, Engineering (miscellaneous), Atomic and Molecular Physics, and Optics, Imaging spectroscopy, Computer Science Applications, Random forest
Abstract

Satellite image data deliver consistent and frequent information for crop yield estimation over large areas. Hyperspectral narrowbands are more sensitive spectrally to changes in crop growth than multispectral broadbands but few studies quantified the gains in the former over the later. The PRecursore IperSpettrale della Missione Applicativa (PRISMA) mission offers narrow (≤10 nm) band capability across the full optical range. The multispectral broadband Sentinel-2 mission carries four experimental red-edge and near infrared (NIR) hyperspectral narrow (≤20 nm) bands. We compared the performance of PRISMA and Sentinel-2 spectral bands at important phases of crop development (vegetative, reproductive, maturity) in estimating field-level biomass and yield for corn, rice, soybean, and wheat. We selected three data-driven methods: two-band vegetation indices (TBVIs), partial least squares regression (PLSR), and random forest (RF). The PRISMA and Sentinel-2 models on average explained approximately 20% more variability in biomass and yield with RF than TBVIs and PLSR. The mean RMSE of the PRISMA RF models was 0.42 and 0.17 kg m−2, which was lower than the Sentinel-2 RF models (0.48 and 0.18 kg m−2). Multidate image (seasonal) model performance was generally higher than single-date image model performance. PRISMA shortwave infrared narrowbands and Sentinel-2 red-edge and near infrared bands were among the top-performing spectral regions. The results highlight potential complementarity between the PRISMA and Sentinel-2 missions for predicting crop biomass and yield. The results also show the benefits, limitations, and pitfalls of hyperspectral imaging in agricultural monitoring, which is important for upcoming operational hyperspectral missions, such as ESA CHIME and NASA Surface Biology and Geology (formerly HysPIRI).

Published
2022

16. Clearing the Digital Minefield for Optimized Oilfield Production

Author

Andy Nelson

Subjects
Fuel Technology, Waste management, Strategy and Management, Industrial relations, Clearing, Energy Engineering and Power Technology, Environmental science, Production (economics)
Abstract

The success of any digital oilfield project is predicated on the quality of the data structure, acquisition, communication, validation, storage, retrieval, and provenance of the data. Therefore, the mission of the digital oilfield architect is clear: Deliver the right data to the right users at the right time. This task is becoming more difficult because of the sheer variety of sensors, the multitude of data formats, challenges with data communication and synchronization, and the potentially large volume of data produced. While the advent of data analytics has increased the importance of designing fast and efficient data management systems, it is a multifaceted minefield to gather and process data to ensure production is optimized and risk is minimized in both conventional and unconventional operating environments.

Published
2020
Full Text
View/download PDF

28. Dark Matter Benchmark Models for Early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum

Author

Daniel Abercrombie, Nural Akchurin, Ece Akilli, Juan Alcaraz Maestre, Brandon Allen, Barbara Alvarez Gonzalez, Jeremy Andrea, Alexandre Arbey, Georges Azuelos, Patrizia Azzi, Mihailo Backović, Yang Bai, Swagato Banerjee, James Beacham, Alexander Belyaev, Antonio Boveia, Amelia Jean Brennan, Oliver Buchmueller, Matthew R. Buckley, Giorgio Busoni, Michael Buttignol, Giacomo Cacciapaglia, Regina Caputo, Linda Carpenter, Nuno Filipe Castro, Guillelmo Gomez Ceballos, Yangyang Cheng, John Paul Chou, Arely Cortes Gonzalez, Chris Cowden, Francesco D’Eramo, Annapaola De Cosa, Michele De Gruttola, Albert De Roeck, Andrea De Simone, Aldo Deandrea, Zeynep Demiragli, Anthony DiFranzo, Caterina Doglioni, Tristan du Pree, Robin Erbacher, Johannes Erdmann, Cora Fischer, Henning Flaecher, Patrick J. Fox, Benjamin Fuks, Marie-Helene Genest, Bhawna Gomber, Andreas Goudelis, Johanna Gramling, John Gunion, Kristian Hahn, Ulrich Haisch, Roni Harnik, Philip C. Harris, Kerstin Hoepfner, Siew Yan Hoh, Dylan George Hsu, Shih-Chieh Hsu, Yutaro Iiyama, Valerio Ippolito, Thomas Jacques, Xiangyang Ju, Felix Kahlhoefer, Alexis Kalogeropoulos, Laser Seymour Kaplan, Lashkar Kashif, Valentin V. Khoze, Raman Khurana, Khristian Kotov, Dmytro Kovalskyi, Suchita Kulkarni, Shuichi Kunori, Viktor Kutzner, Hyun Min Lee, Sung-Won Lee, Seng Pei Liew, Tongyan Lin, Steven Lowette, Romain Madar, Sarah Malik, Fabio Maltoni, Mario Martinez Perez, Olivier Mattelaer, Kentarou Mawatari, Christopher McCabe, Théo Megy, Enrico Morgante, Stephen Mrenna, Chang-Seong Moon, Siddharth M. Narayanan, Andy Nelson, Sérgio F. Novaes, Klaas Ole Padeken, Priscilla Pani, Michele Papucci, Manfred Paulini, Christoph Paus, Jacopo Pazzini, Björn Penning, Michael E. Peskin, Deborah Pinna, Massimiliano Procura, Shamona F. Qazi, Davide Racco, Emanuele Re, Antonio Riotto, Thomas G. Rizzo, Rainer Roehrig, David Salek, Arturo Sanchez Pineda, Subir Sarkar, Alexander Schmidt, Steven Randolph Schramm, William Shepherd, Gurpreet Singh, Livia Soffi, Norraphat Srimanobhas, Kevin Sung, Tim M.P. Tait, Timothee Theveneaux-Pelzer, Marc Thomas, Mia Tosi, Daniele Trocino, Sonaina Undleeb, Alessandro Vichi, Fuquan Wang, Lian-Tao Wang, Ren-Jie Wang, Nikola Whallon, Steven Worm, Mengqing Wu, Sau Lan Wu, Hongtao Yang, Yong Yang, Shin-Shan Yu, Bryan Zaldivar, Marco Zanetti, Zhiqing Zhang, Alberto Zucchetta, Institut Pluridisciplinaire Hubert Curien (IPHC), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche Astrophysique de Lyon (CRAL), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique Nucléaire de Lyon (IPNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Oviedo Univ, Louisville Univ, Duke Univ, CERN, Heidelberg Univ, Cornell Univ, INFN Padua, Boston Univ, Rutgers State Univ, NIKHEF, Paris LPTHE, Hyderabad Univ, UC Irvine, Munich MPI, MIT, INFN Rome, SISSA Trieste, LBL, Rhein Westfal TH Aachen, Princeton Univ, Delhi Univ, Florida Univ, Univ Maryland, Texas Tech Univ, Univ Geneva, CIEMAT, Univ Lyon, CNRS, Ecole Normale Super Lyon, Univ Montreal, TRIUMF, INFN Padova, Univ Wisconsin, Ohio State Univ, Rutherford Appleton Lab, Univ Southampton, Univ Melbourne, Imperial Coll London, SISSA, INFN, Univ Strasbourg, Univ Calif Santa Cruz, LIP Minho, Univ Porto, Univ Chicago, IFAE Barcelona, Univ Calif Berkeley, LBNL, Univ Zurich, Univ Lyon 1, Univ Calif Irvine, Dept Theoret Phys, Lund Univ, San Diego Univ, Louvain CP3, Osaka Univ, Kings Coll London, Freiburg Univ, DESY, Kyungpook Natl Univ, Vanderbilt Univ, Brandeis Univ, Perimeter, Annecy LAPTH, Mainz Univ, Univ Ghent, LPHE Lausanne, Univ Birmingham, Beijing IHEP, Shanghai Jiao Tong Univ, LAPTh, Zurich Univ, Univ Calif Davis, Tech Univ Dortmund, Univ Bristol, Fermilab Natl Accelerator Lab, Univ Grenoble Alpes, Austrian Acad Sci, Northwestern Univ, Univ Oxford, Univ Malaya, Harvard Univ, Univ Durham, Natl Cent Univ, Chung Ang Univ, Univ Tokyo, Vrije Univ Brussel IIHE, Lab Phys Corpusculaire, Catholic Univ Louvain, IPPP Durham, Vrije Univ Brussel, Int Solvay Inst, Univ Amsterdam, FNAL, Universidade Estadual Paulista (Unesp), Stockholm Univ, Carnegie Mellon Univ, Stanford Univ, Univ Wien, Quaid I Azam Univ, SLAC, Max Planck Inst Phys & Astrophys, Nikhef, GRAPPA, Univ Napoli, Niels Bohr Inst, Univ Hamburg, Santa Cruz Inst Particle Phys, Univ Copenhagen, Chulalongkorn Univ, Clermont Univ, Univ Blaise Pascal, Southampton Univ, Univ Padua, Northeastern Univ, Univ Washington, Univ Libre Bruxelles, Univ Paris Sud 11, Abercrombie D., Akchurin N., Akilli E., Maestre J.A., Allen B., Gonzalez B.A., Andrea J., Arbey A., Azuelos G., Azzi P., Backovic M., Bai Y., Banerjee S., Beacham J., Belyaev A., Boveia A., Brennan A.J., Buchmueller O., Buckley M.R., Busoni G., Buttignol M., Cacciapaglia G., Caputo R., Carpenter L., Castro N.F., Ceballos G.G., Cheng Y., Chou J.P., Gonzalez A.C., Cowden C., D'Eramo F., De Cosa A., De Gruttola M., De Roeck A., De Simone A., Deandrea A., Demiragli Z., DiFranzo A., Doglioni C., du Pree T., Erbacher R., Erdmann J., Fischer C., Flaecher H., Fox P.J., Fuks B., Genest M.-H., Gomber B., Goudelis A., Gramling J., Gunion J., Hahn K., Haisch U., Harnik R., Harris P.C., Hoepfner K., Hoh S.Y., Hsu D.G., Hsu S.-C., Iiyama Y., Ippolito V., Jacques T., Ju X., Kahlhoefer F., Kalogeropoulos A., Kaplan L.S., Kashif L., Khoze V.V., Khurana R., Kotov K., Kovalskyi D., Kulkarni S., Kunori S., Kutzner V., Lee H.M., Lee S.-W., Liew S.P., Lin T., Lowette S., Madar R., Malik S., Maltoni F., Perez M.M., Mattelaer O., Mawatari K., McCabe C., Megy T., Morgante E., Mrenna S., Moon C.-S., Narayanan S.M., Nelson A., Novaes S.F., Padeken K.O., Pani P., Papucci M., Paulini M., Paus C., Pazzini J., Penning B., Peskin M.E., Pinna D., Procura M., Qazi S.F., Racco D., Re E., Riotto A., Rizzo T.G., Roehrig R., Salek D., Pineda A.S., Sarkar S., Schmidt A., Schramm S.R., Shepherd W., Singh G., Soffi L., Srimanobhas N., Sung K., Tait T.M.P., Theveneaux-Pelzer T., Thomas M., Tosi M., Trocino D., Undleeb S., Vichi A., Wang F., Wang L.-T., Wang R.-J., Whallon N., Worm S., Wu M., Wu S.L., Yang H., Yang Y., Yu S.-S., Zaldivar B., Zanetti M., Zhang Z., Zucchetta A., Physics, Elementary Particle Physics, Universidade do Minho, GRAPPA (ITFA, IoP, FNWI), ATLAS (IHEF, IoP, FNWI), Daniel, A, Nural, A, Ece, A, Juan Alcaraz, M, Brandon, A, Barbara Alvarez, G, Jeremy, A, Alexandre, A, Georges, A, Patrizia, A, Mihailo, B, Yang, B, Swagato, B, James, B, Alexander, B, Antonio, B, Amelia Jean, B, Oliver, B, Matthew R., B, Giorgio, B, Michael, B, Giacomo, C, Regina, C, Linda, C, Nuno Filipe, C, Guillelmo Gomez, C, Yangyang, C, John Paul, C, Arely Cortes, G, Chris, C, Francesco, D, Annapaola De, C, Michele De, G, Albert De, R, Andrea De, S, Aldo, D, Zeynep, D, Anthony, D, Caterina, D, Tristan du PreeRobin, E, Johannes, E, Cora, F, Henning, F, Patrick J., F, Benjamin, F, Marie-Helene, G, Bhawna, G, Andreas, G, Johanna, G, John, G, Kristian, H, Ulrich, H, Roni, H, Philip C., H, Kerstin, H, Siew Yan, H, Dylan George, H, Shih-Chieh, H, Yutaro, I, Valerio, I, Thomas, J, Xiangyang, J, Felix, K, Alexis, K, Laser Seymour, K, Lashkar, K, Valentin V., K, Raman, K, Khristian, K, Dmytro, K, Suchita, K, Shuichi, K, Viktor, K, Hyun Min, L, Sung-Won, L, Seng Pei, L, Tongyan, L, Steven, L, Romain, M, Sarah, M, Fabio, M, Mario Martinez, P, Olivier, M, Kentarou, M, Christopher, M, Théo, M, Enrico, M, Stephen, M, Siddharth M., N, Andy, N, Sérgio F., N, Klaas Ole, P, Priscilla, P, Michele, P, Manfred, P, Christoph, P, Jacopo, P, Björn, P, Michael E., P, Deborah, P, Massimiliano, P, Shamona F., Q, Davide, R, Re, E, Antonio, R, Thomas G., R, Rainer, R, David, S, Arturo Sanchez, P, Subir, S, Alexander, S, Steven Randolph, S, William, S, Gurpreet, S, Livia, S, Norraphat, S, Kevin, S, Tim M. P., T, Timothee, T, Marc, T, Mia, T, Daniele, T, Sonaina, U, Alessandro, V, Fuquan, W, Lian-Tao, W, Ren-Jie, W, Nikola, W, Steven, W, Mengqing, W, Sau Lan, W, Hongtao, Y, Yong, Y, Shin-Shan, Y, Bryan, Z, Marco, Z, Zhiqing, Z, Alberto, Z, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), and Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11)

Subjects
dark matter: interaction, Simplified model, Physics::Instrumentation and Detectors, mass [dark matter], Parameter space, 01 natural sciences, High Energy Physics - Experiment, dark matter: coupling, High Energy Physics - Experiment (hep-ex), High Energy Physics - Phenomenology (hep-ph), benchmark, effective field theory, search for [dark matter], scattering [p p], Effective field theory, [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], Dark Matter, Simplified models, 010303 astronomy & astrophysics, Physics, Large Hadron Collider, Atlas (topology), CMS, hep-ph, ATLAS, Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici, High Energy Physics - Phenomenology, CERN LHC Coll, interpretation of experiments, LHC, colliding beams [p p], interaction [dark matter], EFT, Particle Physics - Experiment, Particle physics, p p: scattering, Ciências Naturais::Ciências Físicas, WIMP, dark matter: search for, Ciências Físicas [Ciências Naturais], Dark matter, FOS: Physical sciences, dark matter: production, coupling [dark matter], 0103 physical sciences, ddc:530, mediation, ComputingMethodologies_COMPUTERGRAPHICS, Particle Physics - Phenomenology, Science & Technology, 010308 nuclear & particles physics, hep-ex, dark matter: mass, Astronomy and Astrophysics, production [dark matter], Formalism (philosophy of mathematics), Space and Planetary Science, [PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph], direct detection, p p: colliding beams
Abstract

This document is the final report of the ATLAS-CMS Dark Matter Forum, a forum organized by the ATLAS and CMS collaborations with the participation of experts on theories of Dark Matter, to select a minimal basis set of dark matter simplified models that should support the design of the early LHC Run-2 searches. A prioritized, compact set of benchmark models is proposed, accompanied by studies of the parameter space of these models and a repository of generator implementations. This report also addresses how to apply the Effective Field Theory formalism for collider searches and present the results of such interpretations., The authors would like to thank Daniel Whiteson for helping in the review of this document. This research was supported by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence "Origin and Structure of the Universe''. The authors would like to express a special thanks to the Mainz Institute for Theoretical Physics (MITP) for its hospitality and support. P. Pani wishes to thank the support of the Computing Infrastructure of Nikhef. In addition we thank CERN and acknowledge the support of: DOE and NSF (USA), including grant DE-SC0011726 for the preparation of this manuscript; SER, SNSF and Cantons of Bern and Geneva, Switzerland; MINECO, Spain; European Union, where the preparation of this manuscript is part of a project that has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement 679305); IN2P3-CNRS, CEA-DSM/IRFU, France; NSERC, NRC, and CFI, Canada; INFN, Italy; FNRS and FWO, Belgium; STFC, United Kingdom; ARC, Australia; GRICES and FCT, Portugal; SRC, Sweden; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; Austrian Academy of Sciences, Austria; MOE and UM, Malaysia; National Research Foundation and Ministry of Education, Science and Technology, Korea; MEXT and JSPS, Japan; FOM and NWO, Netherlands; CNPq and FAPESP, Brazil; Atomic Energy Commission, Pakistan; DNRF, DNSRC and Lundbeck Foundation, Denmark; Thailand Center of Excellence in Physics, Institute for the Promotion of Teaching Science and Technology, Special Task Force for Activating Research and National Science and Technology Development Agency, Thailand; MOST, Taiwan., info:eu-repo/semantics/publishedVersion

Published
2015
Full Text
View/download PDF

29. It’s About Skills

Author

Brian Runciman, Roger Camrass, and Andy Nelson

Subjects
Hardware and Architecture, Software, Computer Science Applications, Theoretical Computer Science
Published
2016
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results