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1,322 results for “chains”
REALISE: Enabling full-chain CCUS for refineries through cluster-based strategies
<p>Refineries play a major role in our modern lifestyles, creating an almost infinite range of everyday products. Alongside other industries, they face the challenge to decarbonise as part of Europe’s wider efforts to meet climate targets by 2030. </p> <p>This webinar introduced the REALISE CCUS project, an international partnership of industry and scientists working to support the delivery of carbon capture, utilisation and storage (CCUS) technology for the refinery sector. </p> <p>Our research, funded by the European Union's Horizon 2020 programme, focuses on the full CCUS chain – from CO<sub>2</sub> capture, transport and geological CO<sub>2</sub> storage to CO<sub>2</sub> reuse – for clusters which include refineries and other industries. </p> <p>Specifically, we aim to demonstrate CCUS technology, enable sizeable cost-reductions, undertake public engagement and assess financial, political and regulatory barriers. </p> <p>Programme:</p> <ul> <li>Welcome & intro – Inna Kim, SINTEF (5 mins) </li> <li>Optimising and validating technologies for refineries (WP1) – Solrun Vevelstad, SINTEF (10 mins) </li> <li>Demonstrating pilot-scale CO<sub>2</sub> capture with optimised solvent (WP2) – Juliana Monteiro, TNO (10 mins) </li> <li>Assessing potential for CCUS at oil refineries within clusters (WP3) – Pádraig Fleming, Ervia (10 mins) </li> <li>Social, political and commercial context for CCS deployment (WP4) – Niall Dunphy, UCC (10 mins) </li> <li>Q&A (15 mins) </li> </ul>
TERMINUS WP5: Chain Extension Kinetics for Solvent-Free Adhesive Components
<p>In two-component polyurethane (PUR) adhesives, polyols and isocyanates are reacted to produce binding media.In order to obtain a Solvent-Free prepolymer as one of PUR components, an excess of macrodiols can be reacted with diisocyanates.The addition reaction between OH and NCO functional groups is frequently called “Chain-Extension”.PUR polymerization rarely follows classical kinetic theories, therefore, experimental study was carried out to monitor the rate of polymerization.Small specimens of the reaction mixture were periodically withdrawn during the course of Chain Extension.The amount of isocyanates was measured by titration.Four different macrodiols and two diisocyanates were tested at several temperatures and concentrations.Some data on two reactions from previous Dataset 5-1 “Adhesive_Chain_Extension_WP5” is also included to broaden the range of studied temperatures. Collected data can be used for future kinetic studies of both Solvent-Based and Solvent-Free PUR adhesives.</p>
Indicator values for the many-body localization of the Heisenberg spin chain at various energies, system sizes and disorder magnitude
<p>This data set accompanies the preprint <em>Scalable approach to many-body localization via quantum data </em>(arXiv: <a href="https://arxiv.org/abs/2202.08853">2202.08853</a>) and its code, available at <a href="https://github.com/GreschAl/MBLlearning">GitHub</a>.</p> <p>It consists of the numerically obtained indicator values for the many-body localization for the Heisenberg model (see preprint for details and background) for various values of the energy density <span class="math-tex">\(\epsilon = 0.05, 0.1, \dots, 0.9, 0.95\)</span> and for chain lengths <span class="math-tex">\(L = 10, 12, 14\)</span>. For each tuple <span class="math-tex">\((\epsilon,L)\)</span>, there exist two files, representing the training and the test set, respectively. Each such file contains various values of the disorder parameter <span class="math-tex">\(h = 0.5, 1, \dots, 14.5, 15\)</span> with <span class="math-tex">\(N = 1000\ (100)\)</span> sampled realizations of the disorder vector for each <span class="math-tex">\(h\)</span> for the training (test) set, followed by the three calculated values of the three indicators.</p> <p>The data is automatically processable by the code provided in the GitHub repository.</p>
Innovative agrifood value chains
<p>This data-set has been produced in the frame of H2020 project CO-FRESH, in Deliverable 1.2 "List of value chains and a data-set on the characteristics of the identified sustainable, innovative and competitive agrifood value chains"</p> <p>Grand societal challenges, such as climate change, environmental degradation, food security, immigration, and digital transformation, urge value chains actors from farm to fork to interact for improving the system. In this context, innovation, that has long been considered as a factor of growth and competitiveness, becomes an increasingly important factor to create value while addressing sustainability challenges (both environmental, social and economic).</p> <p><strong>The CO-FRESH project</strong> aims to enhance collaboration for sustainability-oriented innovation in the agri-food sector, by proposing interventions for re-designing fruit and vegetables (F&V) value chains across Europe. To reach these objectives, Work Package 1 takes the lead in <em>Identification, Analysis and Design of Innovative and Sustainable Agri-food Value Chains</em>. The current report is the outcome of <em>Task 1.2. Identify innovative agri-food value chains and collect empirical data. </em></p> <p><strong>Deliverable 1.2.</strong> presents a list of value chains and a data-set on the characteristics of the identified sustainable, innovative and competitive agrifood value chains. This list is the results of a participatory inventory led by WUR and involving all the CO-FRESH consortium partners.</p> <p>This report contains three core elements. <strong>First,</strong> it presents the methodology that was used for the inventory creation, drawing on the concepts and selection criteria developed in <em>D1.1.Review state of the art</em>. <strong>Second,</strong> the report provides the list of the selected 100+ value chains and their general characteristics. <strong>Third,</strong> the report shows the different types of sustainability-oriented innovations implemented in these value chains, as well as the various modes of collaboration used to design and implement the innovations.</p> <p>The inventory has been presented to the CO-FRESH consortium during a workshop held 7 October 2021 (CO-FRESH Milestone 2). The inventory will be used in the next step of the project for further data collection and analysis (Task 1.3). For the next milestone, a survey will be addressed to a representative of each of these 100+ value chains in order to gain better understanding of the drivers of collaboration and to assess the impact of the sustainability-oriented innovation implemented. Second, the inventory will be used to select and investigate a portfolio of business models in the Task 1.4. Based on this inventory and the following analysis in Task 1.3 and Task 1.4, recommendations will be developed for interventions to redesign the value chains of the CO-FRESH pilot cases.</p>
A structural database of chain-chain and domain-domain interfaces of proteins
<p>Library of protein-protein and domain-domain interfaces from the protein data bank. The data also contains the structural clusters of protein-protein and domain-domain interfaces.</p>
data set of scopus about technology and halal meat supply chain publications
<p>This is the dataset of papers related to the topics of technology and halal meat supply chain collected from Scopus. The duration of year was 2008-2022</p>
Supporting Information for "From Hofmeister to hydrotrope: Effect of anion hydrocarbon chain length on a polymer brush"
<p>This deposition contains the data and analysis (Jupyter notebooks) detailed in “From Hofmeister to hydrotrope: Effect of anion hydrocarbon chain length on a polymer brush”. All Jupyter notebooks have also been converted into PDF files for ease of viewing.</p> <p>All data and code (notebooks) required to reproduce the analysis can be found within the “supporting_data_analysis.zip” archive. This archive contains four sub-directories:</p> <ul> <li>Computional_data <ul> <li>Optimised geometry files (.xyz) for all short chain fatty acid (SCFA) anion-solvent and anion-NIPAM fragment structures.</li> <li>Summary of analysed data (“SAPT_computational_data.xlsx”) describing the different interaction energies between a SCFA anion-NIPAM fragment and anion-solvent: electrostatic, exchange, induction, dispersion and total interaction energy contributions.</li> </ul> </li> <li>Ellipsometry <ul> <li>Data directory containing all raw ellipsometry data.</li> <li>“refellips_Dry.ipynb” and “refellips_Spectroscopic_SL.ipynb” notebooks to reproduce the analysis of a dry (solid-air) and hydrated (solid-liquid) polymer brush, respectively. </li> <li>A spatial map of the polymer brush used for spectroscopic ellipsometry data analysis: “PNIPAM_brush_spatial_map.png”.</li> <li>“Ellipsometry_sigmoid_fitting.ipynb” notebook and “Water_data.csv” file for the demonstration of the extraction of a thermotransition temperature from an ellipsometry dataset. Relevant plotting tools can be found in the <a href="https://github.com/refnx/refellips">refellips repo</a>.</li> </ul> </li> <li>Neutron_reflectometry <ul> <li>Data directory containing all relevant reduced reflectivity profiles from the Platypus reflectometry at ANSTO.</li> <li>“refnx_dry.ipynb”, “refnx_D2O.ipynb” and “refnx_SCFA_electrolytes.ipynb notebooks required to reproduce the analysis pertaining to a dry, polymer brush and a brush exposed to pure D<sub>2</sub>O and various SCFA electrolytes, respectively.</li> <li>Additional code required to model the hydrated polymer brush and various plotting tools can be in the <a href="https://github.com/igresh/refnxtoolbox">refnxtoolbox repo</a>.</li> </ul> </li> <li>QCMD_data <ul> <li>Data directory containing all processed QCM-D data (.csv)</li> </ul> </li> </ul>
Appendices/Supplementary materials to Hägele, S., Grosse, E.H. and Ivanov, D. (2023) 'Supply chain resilience: a tertiary study', International Journal of Integrated Supply Management, 16 (1), 52-81. https://doi.org/10.1504/IJISM.2023.127660
<p>This document contains supplementary material to the article:</p> <p><em>Hägele, S., Grosse, E.H. and Ivanov, D. (2023) 'Supply chain resilience: a tertiary study', International Journal of Integrated Supply Management, 16 (1), 52-81. https://doi.org/10.1504/IJISM.2023.127660</em></p>
Ancillary data for the wrf_to_tell processing chain
<p>This data supports the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. More details about the processing chain and the associated scripts can be found in the IM3 components library: https://github.com/IMMM-SFA/im3components/tree/main/im3components/wrf_to_tell.</p>
Supplementary Simulation Data for "Conformational Selection of a Tryptophan Side Chain Drives the Generalized Increase in Activity of PET Hydrolases Through a Ser/Ile Double Mutation"
<p>Additional simulation data for "Conformational Selection of a Tryptophan Side Chain Drives the Generalized Increase in Activity of PET Hydrolases Through a Ser/Ile Double Mutation", which has been submitted as a preprint to ChemRxiv.</p>
Fig. 3. Guernea ezoensis Ishimaru, 1987 in On a small collection of amphipods (Crustacea, Amphipoda) from the Lesser Kuril Chain
Fig. 3. Guernea ezoensis Ishimaru, 1987, female, 2.25 mm: a — pereopod III; b — pereopod IV; c — pereopod V; d — pereopod VI; e — pereopod VII; f — urosome (dorsally); g — epimeral plates; h — pleopod II; i — uropod I; j — uropod II; k — uropod III; l — telson. Scale bars: 0.2 mm Рис. 3. Guernea ezoensis Ishimaru, 1987, самка, 2.25 мм: a — переопоà III; b — переопоà IV; c — переопоà V; d — переопоà VI; e — переопоà VII; f — уросома (виà сверху); g — эпимераΛьные пΛастинки; h — пΛеопоà II; i — уропоà I; j — уропоà II; k — уропоà III; l — теΛьсон. Λинейки 0.2 мм
Fig. 2. Guernea ezoensis Ishimaru, 1987 in On a small collection of amphipods (Crustacea, Amphipoda) from the Lesser Kuril Chain
Fig. 2. Guernea ezoensis Ishimaru, 1987, female, 2.25 mm (a-h): a — lower lip; b — upper lip; c, d — mandibles; e — maxilla I (right); f — palp of maxilla I (left); g — maxilla II; h — maxilliped; male, 2.2 mm (i-m): i — antenna I; j — antenna II; k — uropod I; l — uropod III; m — telson. Scale bars: 0.2 mm Рис. 2. Guernea ezoensis Ishimaru, 1987, самка, 2.25 мм (a-h): a — нижняя губа; b — верхняя губа; c, d — манÃибуΛы; e — максиΛΛа I (правая); f — щупик максиΛΛы I (Λевый); g — максиΛΛа II; h — ногочеΛюсть; самец, 2.2 мм (i-m): i — антенна I; j — антенна II; k — уропоà I; l — уропоà III; m — теΛьсон. Λинейки 0.2 мм
Fig. 1. Guernea ezoensis Ishimaru, 1987 in On a small collection of amphipods (Crustacea, Amphipoda) from the Lesser Kuril Chain
Fig. 1. Guernea ezoensis Ishimaru, 1987, female, 2.25 mm: a — habitus (left side view); b — head; c — urosome (left side view); d — antenna I; e — antenna II; f — gnathopod I; g — gnathopod II. Scale bars: 0.2 mm Рис. 1. Guernea ezoensis Ishimaru, 1987, самка, 2.25 мм: a — габитус (виà сбоку); b — гоΛова; c — уросома (виà сбоку); d — антенна I; e — антенна II; f — гнатопоà I; g — гнатопоà II. Λинейки 0.2 мм
Metadata of the study HMGCR activity is essential for mitochondrial β-oxidation of fatty acids to prevent lethal accumulation of long-chain acylcarnitines in the mouse liver
<p>Metadata of the study "HMGCR activity is essential for mitochondrial β-oxidation of fatty acids to prevent lethal accumulation of long-chain acylcarnitines in the mouse liver" published in Br J Pharmacol 2024. Apr 19. doi: 10.1111/bph.16363.</p>
Kuempel et al. (2024) Quantifying global redundant fisheries trade to streamline seafood supply chains
<p>Species trade data to accompany the publication "Quantifying global redundant fisheries trade to streamline seafood supply chains" by Kuempel et al. (2024) and the associated github repository https://github.com/cdkuempel/Redundant_fisheries_trade</p> <p> </p>
Source Code—Motorized chain models of the ideal chromosome
<p>Code and data for reproducing the findings in "Motorized chain models of the ideal chromosome" by Zhiyu Cao & Peter G Wolynes</p> <p>We carried out hybrid Brownian-Gillespie simulations of the polymer dynamics for the swimming motors. The programs can run in parallel on Cuda software. We use periodic boundary conditions without considering the self-avoiding and excluded volume effect. In addition, we solve the self-consistent equation by an iterative method.</p>
Density functional theory calculations of 1D hybrid nanoobjects composed of alternating polycyclic hydrocarbon regions and double carbon chains
<p>It has been proposed recently based on molecular dynamics simulations that electron irradiation of graphene nanoribbons of alternating width can lead to creation of 1D hybrid nanoobjects composed of alternating double carbon chains and polycyclic hydrocarbon regions [1]. We have performed density functional theory calculations of such 1D hybrid nanoobjects using Quantum ESPRESSO [2]. Semi-local exchange and correlation functional of Perdew, Burke and Ernzerhof [3] and screened exchange hybrid density functional of Heyd, Scuseria and Ernzerhof [4] were used. The dependences of structure, magnetic and electronic properies on the length of chains and type of the polycyclic hydrocarbon region were studied.</p> <p>I.V.L acknowledges the IKUR HPC project "First-principles simulations of complex condensed matter in exascale computers" funded by MCIN and by the European Union NextGenerationEU/PRTR-C17.I1, as well as by the Department of Education of the Basque Government through the collaboration agreement with nanoGUNE within the framework of the IKUR Strategy, computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES grant nos. FI-2022-1-0023, FI-2022-2-0035, FI-2022-3-0048 and FI-2023-1-0037). A.M.P., and Y.E.L. acknowledge the support by the Russian Science Foundation grant No. 23-42-10010, https://rscf.ru/en/project/23-42-10010/. S.A.V. and N.A.P. acknowledge support by the Belarusian Republican Foundation for Fundamental Research (Grant No. F23RNF-049) and by the Belarusian National Research Program "Convergence-2025".</p> <p>[1] A. S. Sinitsa, I. V. Lebedeva, Y. G. Polynskaya, D. G. de Oteyza, S. V. Ratkevich, A. A. Knizhnik, A. M. Popov, N. A. Poklonski, and Y. E. Lozovik, “Transformation of a graphene nanoribbon into a hybrid 1D nanoobject with alternating double chains and polycyclic regions,” Phys. Chem. Chem. Phys. 23, 425–441 (2021).</p> <p>[2] P. Giannozzi et al., “Advanced capabilities for materials modelling with Quantum ESPRESSO,” J. Phys.: Condens. Matter 29, 465901 (2017).</p> <p>[3] J. P. Perdew, K. Burke, and M. Ernzerhof, “Generalized gradient approximation made simple,” Phys. Rev. Lett. 77, 3865–3868 (1996).</p> <p>[4] J. Heyd, G. E. Scuseria, and M. Ernzerhof, “Hybrid functionals based on a screened Coulomb potential,” J. Chem. Phys. 118, 8207–8215 (2003).</p>
Mapping the existing food systems, value chains and markets for agroecological products
<table> <tbody> <tr> <td>The food systems and markets of our focal farming systems are mapped as well as communities across the value chain, including operations from production over to food disposal after consumption, all along with the contribution of these operations to socio-economic and environmental outcomes. The datasets are the results of survey/interviews on the above topic in the CANALLS project ALLs.<span> </span></td> </tr> </tbody> </table>
Dataset: Cheetah Net Supply Chain Service Inc. (CTNT) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Chain Bridge I (CBRGU) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
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.