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1,610 results for “economic”
Novel cropping system strategies in China can increase plant protein with higher economic value but lower greenhouse gas emissions and water use
<p> This database contains the average crop residue, manure nitrogen, manure organic carbon, net greenhouse gas emissions, and cropland area for 17 cropping systems at prefecture level during the period 2014-2018. In addition, it contained the changes of net greenhouse gas emissions caused by the optimization at prefecture level and province level.</p> <p> We also shared the key code for optimizing cropping systems at prefecture level and provided the all data. Users can run it the Matlab platform.</p>
Socio-economic modeling based on GRDEM model
<p>Socio-economic modeling based on GRDEM model </p>
Socio-economic modeling based on GRDEM model
<table> <tbody> <tr> <td>Socio-economic modeling based on GRDEM model </td> </tr> </tbody> </table>
Supplementary S6.2 Economic calculation
<p>This is the supplementary file for Chapter 6 of PhD thesis, entitled</p> <p>"An integrated epidemiological and economic analysis of foot and mouth disease (FMD) in Thailand: Evaluation of FMD control"</p>
Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
<ol> <li>With increasing numbers of large grazing birds on agricultural grassland, conflict with farmers is rising. One management approach to alleviate conflict allows foraging on dedicated agricultural land (accommodation areas) and nature reserves, combined with scaring on remaining agricultural land. Here, we examine the cost-effectiveness of these measures by studying the influence on barnacle goose distribution and associated economic damage.</li> <li>We present an individual/agent-based model of barnacle geese (<em>Branta</em> <em>leucopsis</em>) foraging on grasslands in Fryslân, the Netherlands. The model is parameterized using field observations and GPS-tracks and allows simulation of management scenarios, differing in scaring probability and accommodation area size, with different potential management costs. </li> <li>Our model shows that, while yield loss decreases with higher scaring probabilities, costs of damage appraisal increase because geese graze on more fields. With small accommodation areas, achieving high scaring probabilities takes more effort and could result in goose population decline. Total management costs are lowest without scaring activity. </li> <li> <em>Synthesis and applications</em>: Considering costs of active scaring and the need to maintain the barnacle goose population in a favourable conservation status, our model suggests that the most cost-effective scenario is to prevent disturbance of geese. A high scaring probability could be beneficial if applied in small areas, for example around sensitive crops or airfields. Scaring in large areas could result in costs outweighing benefits and a declining barnacle goose population.</li> </ol>
Results of the Macro-Economic Analysis by the REMES model in the openENTRANCE project
<p>This dataset contains scenario results from the REMES:EU model as part of the macro-economic analysis in the openENTRANCE project.</p> <p>The data file follows the IAMC data format and the conventions established by the openENTRANCE project. See <a href="https://github.com/openENTRANCE/openentrance">https://github.com/openENTRANCE/openentrance</a> for details.</p> <p>Visit the openENTRANCE Scenario Explorer at <a href="https://data.ene.iiasa.ac.at/openentrance">https://data.ece.iiasa.ac.at/openentrance</a> for more information about the openENTRANCE project and other datasets.</p>
Dataset on Public Proposals for Infrastructure, Social, and Economic Sectors Based on Participatory Planning
<p>The dataset was collected using data mining techniques. We logged in to e-Musrenbang website as City Admin and retrieved the public proposal data based on sectors, specifically infrastructure, social, and economic. We also selected the proposal budget to be added to the dataset. The dataset was downloaded in Excel with xlsx format.</p>
Replication data for Temperature variability and long-run economic development
<p><strong>Description</strong></p> <p>This dataset contains the processed data used for the statistical analysis in Linsenmeier, M. (2023): Temperature variability and long-term economic development, published in the Journal of Environmental Economics and Management.</p> <p>The main data on nightlights stem from the satellites of the Visible Infrared Imaging Radiometer Suite (VIIRS). The data are downloaded as annual composites (vcm) of version V1 (Elvidge et al., 2017). For robustness tests, also annual composites of version V2 are used (Elvidge et al., 2021). Additional data on nightlights are taken from the U.S. Air Force Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) of Version 4. Data on the global distribution of crop land and pasture land (Ramankutty et al., 2008) are taken from NASA (Ramankutty et al., 2010). Data on population are from the Gridded Population of the World (GPW) dataset version 4.0 (CIESIN, 2018). Data on elevation are from the Global Land One-kilometer Base Elevation (GLOBE) dataset in version 1 provided by the National Oceanic and Atmospheric Administration (NOAA) (Hastings et al., 1999). Data on terrain ruggedness are from a global dataset with a resolution of 1 km (Shaver et al., 2018). Data on distances from the nearest coast are from NASA. Distance from inland water bodies are from the GloboLakes dataset (Carrea et al., 2015). Finally, data on weather are from ERA5 reanalysis (Hersbach et al. 2018). All datasets are spatially aggregated to the grid cells of the ERA5 reanalysis.</p> <p><strong>Acknowledgements</strong></p> <p>The data contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p> <p>Image and data processing by Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines. DMSP data collected by US Air Force Weather Agency.</p> <p><strong>Bibliography</strong></p> <ul> <li>Carrea, L., Embury, O., andMerchant, C.(2015). GloboLakes: High-resolution global limnology data. Center for Environmental Data Analysis. http://catalogue.ceda.ac.uk/uuid/06cef537c5b14a2e871a333b9bc0b482.</li> <li>CIESIN (2018). Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11.</li> <li>Elvidge, C. D., Baugh, K., Zhizhin, M., Hsu, F. C., and Ghosh, T. (2017). VIIRS night-time lights. International Journal of Remote Sensing, 38(21):5860–5879.</li> <li>Elvidge, C.D, Zhizhin, M., Ghosh T., Hsu FC, Taneja J. Annual time series of global VIIRS nighttime lights derived from monthly averages:2012 to 2019. Remote Sensing 2021, 13(5), p.922, doi:10.3390/rs13050922.</li> <li>Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Murakami, H., Maruyama, H., Masaharu, H., Holland, P., Payne, J., Bryant, N. A., et al. (1999). The global land one-kilometer base elevation (GLOBE) digital elevation model, version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, 325.</li> <li>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2018): ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed in January 2021), 10.24381/cds.adbb2d47</li> <li>Ramankutty, N., Evan, A., Monfreda, C., and Foley, J. (2010). Global Agricultural Lands: Pastures, 2000. Global Agricultural Lands Dataset.</li> <li>Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A. (2008). Farming the Planet: 1. Geographic Distribution of Global Agricultural Lands in the Year 2000: Global Agricultural Lands in 2000. Global Biogeochemical Cycles, 22(1).</li> <li>Shaver, A., Carter, D. B., and Shawa, T. W. (2018). Terrain ruggedness and land cover: Improved data for most research designs. Terrain Ruggedness and Land Cover Dataset.</li> </ul>
Biophysical data for: Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish
<p><span>How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (<em>Perca flavescens</em>), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate 'predictive' values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (<em>e.g</em>., currents, behavior, PLD). For the main basin populations (<em>i.e</em>., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (<em>F<sub>ST</sub></em> = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (<em>F<sub>ST</sub></em> = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.</span></p>
Techno-economic evaluation and resource assessment of hydrogen production through offshore wind farms: A European perspective - Supplementary material
<p>This is the additional material provided with the journal article "Techno-economic evaluation and resource assessment of hydrogen production through offshore wind farms: A European perspective" published in Renewable and Sustainable Energy Reviews (<a href="https://doi.org/10.1016/j.rser.2023.113699">https://doi.org/10.1016/j.rser.2023.113699</a>).</p> <p>Datasets are provided as NetCDF files for European maps and CSVfor Economically Attractive Resource curves.</p> <p>European and National plots are provided as PDF files.</p>
Ethical Considerations in Utilizing Technology to Combat Economic Crime
<p>This presentation was offered by Dr. Costantino Grasso (please see bio below), during the international conference entitled <strong>“Economic Crime in the Age of Technology (ECAT)</strong>,” which was dedicated to exploring the still untapped potential of utilizing technological advancements to counter economic crime. ECAT was held both in person at Manchester Law School and online on Zoon on the 5th of July 2023. The presentation was entitled “Ethical Considerations in Utilizing Technology to Combat Economic Crime”.</p> <p><em><strong>Abstract </strong></em><br> The rapid advancements in technology have paved the way for innovative solutions in combating economic crime. Despite the evident innovative potential of technology in this area, it is nevertheless necessary to analyze the potential risks and ethical dilemmas associated with these technological advancements. This presentation will discuss this issue, focusing on the need to establish not only internal controls but also external and independent monitoring systems on how these new technologies can be integrated for the purpose of countering financial crime, particularly within the corporate environment.<br> <br> <em><strong>Speaker’s Bio</strong></em><br> Costantino is an Associate Professor in Business and Law at Manchester Law School, Founder and Editor in Chief of the Corporate Crime Observatory and the Corporate Social Responsibility and Business Ethics Blog. He specializes in corporate and economic crime, corporate governance, corporate social responsibility, and whistleblowing. He serves as an international expert on corruption and good governance for the Council of Europe and has acted as a Principal Investigator for both EU-funded and NATO-funded international research projects.<br> <br> The international conference entitled “Economic Crime in the Age of Technology (ECAT)” was organized by Dr. Costantino Grasso - Associate Professor in Law at Manchester Law School, Dr. Donato Vozza - Senior Lecturer in Law at Roehampton University, and Dr. Alessio Faccia - Assistant Professor in Finance at the University of Birmingham Dubai. For more information about the event please see the Corporate Crime Observatory at https://www.corporatecrime.co.uk/economic-crime-and-technology</p>
Reversing the great degradation of nature through economic development
<p>We analyze past and anticipated future trends in crop yields, per capita consumption, and population to estimate agricultural land requirements globally by 2050 and 2100. Assuming "business as usual," higher-income countries are expected to show little or no net growth in cropland by the end of the century, even in the face of moderate climate change. In contrast, in lower-income countries, we project that land requirements will grow dramatically, and climate change will likely double this expansion. Although economic growth is often considered to work in opposition to conservation, accelerating economic development in lower-income countries, which would help alleviate poverty and increase standards of living, would also greatly reduce potential cropland expansion in lower-income countries, even with climate change, owing to slower population growth and improved crop yields that more than offset increased per capita consumption. Combining economic development in low-income countries with reduced consumption in high-income countries could dramatically shrink global cropland requirements by the year 2100 even with moderate climate change. Such a remarkable reduction in cropland area would have enormous benefits for both biodiversity and global climate change. </p>
Economic Analysis_RawData
<p>This .zip file contains the .xlsx raw data that where used for the completion of the deliverable 5.3</p>
HIGGS_M_WP5_423_OST_Techno-economic-model_190620171000_230922
<p>Metadata for graphs of HIGGS' deliverable D5.3 "Intermediate report: key findings on potential and enablers"</p>
HIGGS_M_WP5_423_OST_Techno-economic-model_Techno-economic-model_111120171800_230922
<p>Metadata of graphs of HIGGS' deliverable D5.3 "Intermediate report: key findings on potential and enablers"</p>
Indicators of Economic Sustainability obtained from Sustainability in Aquaculture Research Network
<p>Indicators of economic sustainability obtained for the 8 systems of LTS studied. Monoc. = monoculture; sub-trop. = subtropical; IMTA = integrated multi trophic aquaculture; “-“ = no data.</p>
Positioning absorptive root respiration in the root economics space across woody and herbaceous species
<p>Root respiration is essential for nutrient acquisition. The respiration rate of absorptive roots theoretically relates to the economics of carbon-nutrient exchange, but its empirical role remains largely unexplored in the trait space defining nutrient uptake strategies. Here, we measured the respiration rates of the distal, non-woody, absorptive roots of 252 woody and herbaceous species from subtropical and temperate climate zones, including both arbuscular mycorrhizal and ectomycorrhizal fungal hosts. We found a consistent and positive correlation between root respiration rate and specific root length (root length per dry weight), irrespective of growth form, mycorrhizal type, and climate zone. Root respiration rate was also positively, but less strongly and less frequently correlated with root nitrogen concentration. Root morphology strongly explained the fast-slow gradient of root respiration in the root economics space. By quantifying the ratio of arbuscular mycorrhizal fungal DNA copy number and root tissue DNA copy number using qPCR, we found that the morphology-driven gradient did not explain the full variation in fungal collaboration; thick roots were consistently well colonized, but medium and thin roots displayed a wide range of colonization intensity. Synthesis: These results advance our understanding of the fundamental trait relationships that underpin the root economics space. Our study also provides a physiological linkage to the frequently-measured root morphological traits and relates the root economics space to root-derived carbon-nutrient cycling processes.</p>
The EMERGE Project: Feasibility of Assessing Economic and Sexual Risk Behaviors Using Text Messages in Young Adults
ClinicalTrials.gov study NCT03237871. IPD Sharing: YES. Countries: 1. Publications: 1.
Feasibility Study on the Impact of Economic Incentives to Improve the Management of Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT02891382. IPD Sharing: YES. Countries: 1. Publications: 2.
Observational Study to Evaluate PAD Treatment Clinical and Economic Outcomes
ClinicalTrials.gov study NCT01855412. IPD Sharing: Not stated. Countries: 1. Publications: 13.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.