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8 results for “XLSX”
GERDAT011 Literature search for publication - Geriatric assessment in the management of older patients with cancer – a systematic review (update).xlsx
<p>Search data belonging to the publication Geriatric assessment in the management of older patients with cancer – a systematic review (update)</p>
20240809 - Analysis (waste metals).xlsx
<p>This Excel datafile includes the times series data on material and monetary flows of the global trade of waste metals between 2000 and 2022, and the analysis (ecological network analysis and ascendency analysis). This dataset is supplementary material to the publication:</p> <p>"<strong>Zisopoulos F.K.</strong>, Fath B.D., Toboso-Chavero S., Huang H., Schraven D., Steuer B., Stefanakis A., Clark O.G., Scrieciu S., Singh S., Noll D., de Jong M. (Accepted). Inequities blocking the path to circular economies: A bio-inspired network-based approach for assessing the sustainability of the global trade of waste metals. <em>Resources, Conservation & Recycling</em>. 212(January 2025), 107958."</p> <p>F.K.Z. is grateful to the <em>Impact for Sustainability Fund</em>, a named fund at <em>Stichting Erasmus TrustFonds</em>, for funding (project number: 97090.2022.101.671/074/RB). The study falls within the Sino-Dutch project <em>“Towards Inclusive CE: Transnational Network for Wise-waste Cities (IWWCs)”</em> which is one of the projects of the <em>Erasmus Initiative Dynamics of Inclusive Prosperity</em>, and it is co-funded by the <em>Dutch Research Council</em> (NWO) and the <em>National Natural Science Foundation of China</em> (NSFC); NWO project number: 482.19.608; NSFC project number: 72061137071. H.H. acknowledges his support with a grant from Princeton University's School of Engineering and Applied Science (SEAS). D.N. acknowledges funding under the research contract 2022.05039.CEECIND/CP1734/CT0001 (<a href="https://doi.org/10.54499/2022.05039.CEECIND/CP1734/CT0001" target="_blank" rel="noopener">https://doi.org/10.54499/2022.05039.CEECIND/CP1734/CT0001</a>) through the Portuguese Foundation for Science and Technology (FCT) with MED (<a href="https://doi.org/10.54499/UIDB/05183/2020" target="_blank" rel="noopener">https://doi.org/10.54499/UIDB/05183/2020</a>) and CHANGE (<a href="https://doi.org/10.54499/LA/P/0121/2020" target="_blank" rel="noopener">https://doi.org/10.54499/LA/P/0121/2020</a>). The authors are grateful for the constructive comments of the editor and two anonymous reviewers.</p>
Towards a cashless society - Examining the Impact of Digital Infrastructure on mPayment Transactions (A Cross-Region Analysis).xlsx
<p>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381). </em></p>
CAP1 - Planning and control of asphalt production - Thermal balance data (.xlsx)
<p>CAP1- Planning and Optimization of Asphalt Production</p> <p>The cognitive planning solution for asphalt production consists of a planning decision tool that, from the sensors data installed in the plant and contributing to the planning reference implementation layer of the CAP, allows to decide the right moment to start the production and the necessary adjustments to get the asphalt mix to leave the production plant to the asphalt application area in the optimal conditions (temperature mainly). It takes into account the industrial data streams coming from both the local control system located at the asphalt use case and the data coming from the new different sensors that have been connected to the local datalogger also available at the asphalt production plant and as part of this project development.</p> <p>The implementation of the cognitive system of production planning and optimization gathers all the data coming from the cognitive sensors developed in the project (as the content of bitumen or filler present in the asphalt mix) and any other sensors already installed alongside, with data coming from the laboratory if needed.</p> <p>It is needed to perform two types of calculations:</p> <ul> <li>A <strong>mass balance</strong> both at the dryer and mixing process on a daily basis and for each type of asphalt mix design (a recipe containing the proportions of each ingredient, the aggregates, bitumen and recycled asphalt).</li> <li>A <strong>thermal balance</strong> also both at the dryer (heating up the cold aggregates) and mixing of the hot aggregates, the bitumen and the cold RAP (recycled asphalt). Both processes have a temperature set point. For the drying, there is a temperature safety limit to not damage the baghouse filter. For the mixing, the temperature is set by the asphalt mix design so the final mix is transported and laid out at the job site at a minimum temperature.</li> </ul> <p>The advanced calculation of the mass balance throughout all the production chain is performed including the continuous part of it (aggregates drying process) and the batch one (mix tower). This mass balance is made up of the different calculations that can be performed using all the available data and taking into consideration both, stationary and dynamic (transitory) mass balances like mass balance of aggregates in the dryer, mass balance in the baghouse filter, mass balance in the bucket elevator to the mixing tower, mass balance in the upper sieves and in the hot aggregates hoppers and eventually the mass balance in the mixer taking into account the different additives (including RAP, bitumen, etc.). Also, the different recipes production historical data is used as a basis for the calculations of this tool.</p>
Paul Price edit and charts - WEM Agriculture_2022_WEM_EPA (2024) PRP EDIT (with some WAM analysis added).xlsx
<p>This is an edited version of the 2024 EPA Ireland GHG emissions inventory Excel workbook for Agriculture under the With Existing Measures emissions scenario (uploaded in original form as doi: <span>10.5281/zenodo.13941591). This version also includes data from the corresponding EPA agriculture workbook for the With Existing Measures emissions scenario (uploaded in original form as doi: <span>10.5281/zenodo.13941662).</span></span><br><br>Additions by Paul Price are found on the tab "<strong>3.A and 3.B CH4</strong>": in rows 147–160 are Historic Total EF+MM (CH4 kt/Yr) timeseries for the different animal type and in total, giving the total for each of methane in kilotonnes from Enteric Fermentation and Manure Management combined. Then in rows 186-192 you can see the added calculation, giving the percentage of the total from each animal type. A related chart shows the historic and projected (WEM and WAM) outputs from these calculations.</p>
Spain_dataset_xlsx
<p>Xlsx subset of the Agri4cast (<a href="https://agri4cast.jrc.ec.europa.eu/DataPortal/Index.aspx">https://agri4cast.jrc.ec.europa.eu/DataPortal/Index.aspx</a>) dataset for the region of Spain</p>
Statistics "Effect of hydrolyzed red worm (Eisenia foétida) on production parameters in red tilapia (Oreochromis sp.)".XLSX
Open the record for dataset details and reuse information.
Excel files (.xlsx and .csv)
<p>Supplementery Excel files (.xlsx and .csv)</p>
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