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830 results for “Industrialization”
Simulations for pre-industrial climate using EC-Earth3-LR model — selected data for a study on AMOC
<p>A long-term control simulation of pre-industrial period (1850 CE) climates were performed by the EC-Earth3-LR climate model with a horizontal resolution of ~1.125°. The dataset contains selected output data from the simulations.</p> <p>In total, a 2000-year long control simulation was made, which has pre-industrial orbital boundary conditions, initialized by a pre-run steady restart file (the output of approximately 500-year pre-industrial control simulation). This dataset is used to investigate internal climate variability without external forcing changes under pre-industrial climate conditions.</p> <p>The dataset contains Earth system model results from EC-Earth3 presented in the study by Cao et al. (2022).</p> <p><strong>Model configuration</strong><br> Time periods: Pre-Industrial (2000-year time slice)<br> ESM configuration: EC-Earth3-LR<br> Horizontal resolution: ~1.125° (~125 km)</p> <p><strong>Available data</strong><br> Annual mean data for standard oceanographic and meteorological variables.</p>
Simulated industrial CT dataset for deep learning with dual-energy tomograms and ground truth material maps for copper and iron
<p>We use this dataset for training and evaluation of a deep learning model to discriminate multi-material systems with X-ray CT.</p> <p>The dataset consists of:</p> <ul> <li>inputs: dual-energy tomograms as binary files without a header (tensor <strong>shape for numpy: 2x128x128 @float32</strong>) <ul> <li>simulated spectra are 250kVp and 450kVp both prefiltered using 2mmCuSn</li> </ul> </li> <li>outputs: the material maps a.k.a. ground truths for the training (same shape as inputs) <ul> <li>sampled with a delaunay algorithm and randomly filled with iron and copper fractions</li> </ul> </li> </ul> <p>The <strong>dataset is normalized to [0, 1]</strong>, so you have to multiply by the mass densities of copper and iron to obtain effective fractions in g/cm^3.</p>
PALEODEM/Social networks mediated the rapid spread of Mesolithic trapeze industries in Iberia
<p>This repository contains data files, R codes and the agent-based model used to produce the analysis of cultural diffusion in the case study of the spread of Mesolithic trapezes industries in Iberia.</p> <p>They correspond to the following reference:</p> <p>Romano, V, Gómez-Puche, M., Cucart-Mora, C., Fernández-López de Pablo, J., Lozano, S. “Social networks mediated the rapid spread of Mesolithic trapeze industries in Iberia”</p> <p>We specify the content of each folder/file further down:</p> <ol> <li>Data files folder contains empirical data employed in the analysis. More precisely contains 3 archives with the geographic coordinates of archaeological sites from TS1, TS2 and TS3 and the Distances matrices file.</li> <li>R codes folder contains the scripts to reproduce the analyses, as well as the csv files employed.</li> <li>Social diffusion model folder contains the NetLogo model employed.</li> </ol> <p>Additionally, we provide the empirical dataset of lithic assemblages (n=70) and archaeological sites (n=53) analyzed in this work (Table S1.xlsx), and a list of archaeological references corresponding to archaeological sites analyzed.</p>
Replication Package: Model-Driven Engineering for the Interoperability of Simulation Modeling Languages: a Case Study in the Space Industry
<p>Replication package "Architectural Support for Software Performance in Continuous Software Engineering: a Systematic Mapping Study".</p>
Dataset of pre-industrial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.
<p>Results from the simulation of pre-industrial climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly.</p> <p>Detailed description of the methods are in the original publication:</p> <p>Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022.</p>
Vision and mission statements in pharmaceutical industry: Evidence from content analysis perspectives
<p><strong>Background:</strong> Recently, the growth of pharmaceutical sector in Nigeria are challenged by competitive and dynamic environment. There is a strategic planning process that the organisation needs to use to achieve the pre-determined objectives. This study aimed to determine the vision and mission statements of the pharmaceutical industries which affects their growth and performance outcomes.</p> <p><strong>Methods:</strong> To accomplish this study, a sample of 20 Top Pharmaceutical Companies in Nigeria was analyzed using excel spreadsheet to draw out the vision and mission components. And the list was obtained from Pharmaapproach, Pharmaceutical and Medical Manufacturing Companies in Nigeria as well as InfoGuide Nigeria.</p> <p><strong>Results:</strong> The findings examined that the 20 pharmaceutical firms do have recurring vision and mission statements that are published in their various corporate websites. The industries’ vision statements shows the survival; growth and profitability concern; technology; products and services; markets; philosophy; concern of employees; customers; self-concept and; concern for public image while the mission statement fulfill the components of statement of purpose; customer; products and services; location/market; core technology; concern for growth and profit; philosophy value; self-concept; concern for public image; concern for shareholders and concern for employees.</p> <p><strong>Conclusions:</strong> The study recommends that components of vision and mission statements of pharmaceutical industries have to be consistent, strategically-crafted, well-organized and established. Vision statements have a strategic future plan for an industry and how target goals of the firm will be met. Mission statements, however, is an effectiveness of work done in the industry They determine the daily task that is being carried out, and what direction the firm is heading towards to achieve the specific vision of the industry. It was emphasized that pharmaceutical industries have comprehensive vision and mission statements that helps in achieving their various goals and objectives.</p> <p>___________________________________________________________________________</p> <p><strong>Keywords</strong></p> <p>Competitive Advantage; Mission Statement; Purposes; Strategic Planning; Vision Statement; Products; Services; Competitors</p>
Experimental investigation on hydrogen-rich fuel mixtures (H2/CH4/CO) doped with C6H6 in a 20 kW semi-industrial scale furnace
<p>The effects of benzene doping H2-rich fuel mixtures have been investigated in a semi-industrial furnace integrated with a recuperative burner of 20 kW of nominal power. The tested fuels consist of an H2/ CH4/CO blend, doped with a progressive addition of C6H6 (up to 5% v/v). This fuel blend represents a surrogate of a more complex Coke Oven Gas (COG) industrial mixture, an attractive by-product of coal carbonization. The relative ratios of H<sub>2</sub>, CH<sub>4,</sub> and CO correspond to the ones of a typical COG mixture. The emissions, along with the OH* and CH* chemiluminescence emissions and the flame temperatures were monitored under a wide range of equivalence ratios, i.e. Φ=0.71, 0.80, 0.91, 1.00, 1.05, 1.10, 1.20. The thermal input was kept constant at 20 kW for all the investigated cases, hence the flow rate of the fuel was decreased when C<sub>6</sub>H<sub>6</sub> was added to the reference mixture due to the increase of the lower calorific value. The exhaust gas composition was monitored by means of a Fourier Transform Infrared Spectroscopy (FTIR) analyzer from HORIBA® (HORIBA MEXA-ONE), equipped with a paramagnetic analyzer (MPA) for O2 measurements. On the other hand, OH* and CH* chemiluminescence imaging was carried out by means of an IRO (Intensified Relay Optics) and a CCD (Charge-Coupled Device) camera 1.4 M (La Vision 1392 x 1040 pixels) coupled with UV 78mm f/3.8 lens and two interferential filters to collect the chemiluminescence emitted by OH* (310 ± 10 nm) and CH* (438 ± 24 nm). Finally, in-situ flame temperature measurements were also performed by using an air-cooled suction pyrometer probe equipped with a B-type thermocouple.</p> <p> </p>
Data_ Integrating torrefaction of pulp industry sludge with anaerobic digestion to produce bioenergy and biochemicals: Techno-economic and environmental feasibility analysis
<p>In order to improve the economic competitiveness of bioenergy carriers and biochemicals, they must be produced<br> from low-cost or no-cost feedstock and at a reduced operational expenses. In that regard, this study<br> focused on understanding the techno-economic feasibility of using pulp sludge as a low-cost alternative feedstock<br> to forestry biomass in torrefaction. Economic feasibility of further integrating pulp sludge torrefaction with<br> anaerobic digestion to produce energy, biomethane and volatile fatty acids (VFA) was also studied. The operational<br> expenses were around 8.2 and 2.04 M€ and the minimum selling price of torrefied pellets was 407 and<br> 189 €/t for forestry biomass torrefaction and pulp sludge torrefaction respectively. In case of integrated approaches,<br> VFA production showed higher economic feasibility with a torrefied pellets selling price of 163 €/t<br> compared with biomethane production (213 €/t). The biomethane and VFA selling price can be reduced by 90<br> and 64% compared with current market price at torrefied pellets selling price of 260 €/t. Sensitivity analysis<br> revealed that, moisture content of the sludge is the main influencing parameter on the overall economic feasibility<br> of the pulp sludge torrefaction. The environmental analysis showed that pulp sludge torrefaction has higher<br> emissions compared with forestry biomass torrefaction.</p>
Bioprocess optimization for lactic and succinic acid production from a pulp and paper industry side stream
The data gathered in this file represent measurements and results obtained of during hydrolysis experiments done by RISE and fermentations performed by ATB. This information was necessary to optimize the lactic and succinic acid production via small scale fermentation trials. For lactic acid fermentation two Bacillus coagulans strains were used: A162 and A541. Simillarly, two succinic acid producers were used in this study: Actinobacillus succinogenes B1 and Basfia succiniciproducens B2. Moreover, the enzyme loading is described, what directly shows the hydrolysis performance.
Short Selling and Implications for The Biopharmaceutical Industry
<p>Over the past decades, the practice of short selling in the biopharmaceutical industry has grown substantially. Biopharmaceutical companies have actively expressed concern about the potential consequences of short selling for the development of new drugs and therapies. We present evidence that biopharmaceutical companies are disproportionally targeted by short sellers. We also show that companies with an emphasis on <em>Oncology</em> treatments seem to be more likely to be targeted by short sellers. Finally, we find that an increase in the number of short positions is associated with a decrease in <em>New Product </em>and C<em>linical Trial Initiations</em>.</p>
Research Scholars Workshop: Academic vs. Industry Research
<p>In this workshop, we will explore the differences between research in an academic setting versus industry, including how work is planned, executed, and disseminated. We will hear from expert researchers in both settings. </p>
A Benchmark Dataset with Knowledge Graph Generation for Industry 4.0 Production Lines
<p>A benchmark dataset for knowledge graph generation in Industry 4.0 production lines and to show the benefits of using ontologies and semantic annotations of data to showcase how I4.0 industry can benefit from KGs and semantic datasets. This work is a result of collaborations with the production line managers, supervisors, and engineers of a football industry to acquire realistic production line data. Knowledge Graphs (KGs) or a Knowledge Graph (KG) emerged as a significant technology to store the semantics of the domain entities. The data is mapped and populated with RGOM classes and relations using an automated solution based on JenaAPI, producing an I4.0 KG. <br> <br> Usage:<br> <br> Recently, we use this dataset to analyze the performance of the five state-of-the-art KG embedding models, namely ComplEx, DistMult,TransE, ConvKB, and ConvE. We evaluated the models using two key metrics: Mean Reciprocal Rank (MRR), and Hits@N (Hits@10, Hits@3, and Hits@1). We observed that the TransE model outperforms other models, followed by ComplEx and DistMult, with ConvE demonstrating the lowest performance. Similarly, the dataset can be used alternatively in other potential scenarios.</p>
Dataset for A MILP approach for detailed operational scheduling of a supply chain in the phosphate industry
<p>10 instances to evaluate a MILP approach for detailed operational scheduling of a supply chain in the phosphate industry.</p>
Webinar: Reducing Industrial Carbon Emissions. Carbon capture, utilisation, and storage technologies
<p>The EU recently set unprecedented goals in terms of reducing emissions (-55% by 2030, climate neutrality by 2050). Solutions such as carbon capture, utilisation and storage, or “CCUS”, involve capturing CO2 from industrial plants or installations, transporting it to designated sites, and injecting it into geological formations, making it extremely relevant to face this ambitious, but necessary challenge.</p> <p>This webinar shared some the latest advances in CCUS. The research project cluster on <strong>Better Carbon Capture for Industrial Emissions</strong> is formed by three EU-funded projects: <strong><a href="http://www.cleanker.eu/">CLEANKER</a></strong>, <strong><a href="http://www.realiseccus.eu/">REALISE CCUS</a></strong>, and <strong><a href="http://www.c4u-project.eu/">C4U</a></strong>, and are advancing the state of the art and reducing emissions from industrial plants directly focussing on three different sectors: cement, refineries and steel.</p> <p>Experts from these EU-backed projects showcased the technological approaches, their financial feasibility, and how their approaches in implementing CCUS have shown up to 90% reduction in CO2 emissions in certain plants. Policy aspects that have an effect on the implementation of CCUS were discussed.</p>
Laccases from Pleurotus ostreatus Applied to the Oxidation of Furfuryl Alcohol for the Synthesis of Key Compounds for Polymer Industry
<p>Laccases are oxidative enzymes with high synthetic potential. In this work, their value in biocatalysis is shown through the green and selective oxidation of furfuryl alcohol into furfural with the aid of mediators. The influence of different parameters, such as pH, enzyme/mediator composition, buffer type, cosolvent tolerance, and reaction times, is investigated. Under the optimal conditions, 20 mol % of TEMPO as mediator and 5.8 U mL<sup>−1</sup> of laccases POXC and POXA1b from <em>Pleurotus ostreatus</em>, quantitative production of furfural is attained after 16 h. POXC laccase stands out for its ability to catalyze the reaction at pH 6.5, whereas POXA1b is notable for its high stability. Furfural conversions reach excellent values (95 %) after 72 h using only 5 mol % of TEMPO at 100 mM. Furthermore, furfuryl alcohol bioamination is achieved by employing the amine transaminase from <em>Chromobacterium violaceum</em>, providing furfuryl amine, a key compound for the polymer industry, through a one-pot sequential approach.</p>
Data for ms. Dairy cattle welfare – the relative effect of legislation, industry standards and labelled niche production in five European countries
<p>Repository R 1: Scores on dimension values and weight on dimension from 38 international experts. </p> <p>Repository R2: Country Benchmark scores from 38 international experts.</p>
Animated video presenting the advancements from AI4DI Supply Chain for Food and Beverage industries
<p>This animated video presents the dvancements from AI4DI Supply Chain for Food and Beverage industries.</p>
China Cement Industry Dataset (CCID)
<p>1. "China cement plants.xlsx" displays the company, clinker production lines, province, address, kiln size, clinker production capacity, and year of operation of cement plants in China. </p> <p>2. "Energy statistics for China cement plants.xlsx" displays the energy statistics of thermal and electricity consumption of part of cement plants, reported by official departments. </p> <p> </p>
Replication Package: An Expert Survey on the Use of Informal Models in the Automotive Industry
<p>This repository contains the replication package for the paper <em>An Expert Survey on the Use of Informal Models in the Automotive Industry</em> by <a href="https://orcid.org/0000-0001-6410-6769">Dominik Fuchß</a>, <a href="https://orcid.org/0000-0001-7312-2891">Thomas Kühn</a>, <a href="https://orcid.org/0000-0002-8953-1064">Jérôme Pfeiffer</a>, <a href="https://orcid.org/0000-0003-3534-253X">Andreas Wortmann</a>, and <a href="https://orcid.org/0000-0002-1593-3394">Anne Koziolek</a>. The paper has been accepted at the <a href="https://www.iese.fraunhofer.de/en/twinarch.html">TwinArch 2023: The 2nd International Workshop on Digital Twin Architecture</a> co-located with <a href="https://conf.researchr.org/home/ecsa-2023">ECSA 2023</a>.</p>
Data and code for Global change drives modern plankton communities away from pre-industrial state
<p>Data and R code for "Global change drives modern plankton communities away from pre-industrial state" by Lukas Jonkers, Helmut Hillebrandt and Michal Kucera (https://doi.org/10.1038/s41586-019-1230-3).</p> <p>Compare planktonic foraminifera species assemblages from sediments and sediment traps.</p> <p>Scripts written by Lukas Jonkers</p> <p>DATA SOURCES<br> * HadISST: Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research: Atmospheres 108, doi:10.1029/2002JD002670 (2003).<br> * ERSST v5: Huang, B. et al. NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5. Monthly mean. NOAA National Centers for Environmental Information. doi:10.7289/V5T72FNM. Access date: 14 Sep 2018. (2017).<br> * sediment assemblages: Siccha, M. & Kucera, M. ForCenS, a curated database of planktonic foraminifera census counts in marine surface sediment samples. Scientific Data 4, 170109, doi:10.1038/sdata.2017.109 (2017).<br> * sediment traps: citations provided in data files</p> <p>DATA<br> 1. Planktonic foraminifera shell flux time series<br> 1.1. all data: dat_sel.RDS<br> 1.2. time series with >125 and >150 micron data: dat_small.RDS<br> 1.3. shell flux data in csv format: shell_flux_data.csv</p> <p>2. ForCenS core top sediment assemblages<br> 2.1. all data (excluding duplicates and samples with incomplete taxonomy): forcens_trimmed_compare.RDS<br> 2.2. all data, split by region: species_domains_compare.RDS<br> 2.3. indices of samples: domain_indeces_compare.RDS</p> <p>3. SST<br> 3.1. average SST for each sample in ForCenS for 1870-1899 period based on HadISST: forcens_HadSST_1870-1899.RDS<br> 3.2. average SST for each sample in ForCenS for 1854-1883 period based on ERSST v5: forcens_ERSST_1854-1883.RDS<br> 3.3. average SST for each sediment trap site for 1870-1899 period based on HadISST: traps_HadSST_1870-1899.RDS<br> 3.4. average SST for each sediment trap site for 1854-1883 period based on ERSST v5: traps_ERSST_1854-1883.RDS<br> 3.5. average SST for each sediment trap site for deployment period based on HadISST: traps_HadSST_period.RDS<br> 3.6. average SST for each sediment trap site for deployment period based on ERSST v5: traps_ERSST_period.RDS<br> 3.7. linear SST trend between 1870 and 2015 based on HadISST: hadisst_trend_1870-2015.RDS<br> 3.8. average SST for period of sediment trap observations: hadisst_mean_1978-2013.RDS</p> <p>CODE<br> 1. get_ForCenS.R: selection of ForCenS data. Used to generate data 2.1-2.3<br> 2. make_polygons.R: make circles with 100 km radius around trap and core tope sites used in 4 and 5<br> 3. make_polygon_function.R: used by 2<br> 4. extract_HadSST.R: extraction of data 3.1, 3.3, 3.5, 3.7, 3.8<br> 5. extract_ERRSTv5.R: extraction of data 3.2, 3.4, 3.6<br> 6. make_annual_assemblages.R: process shell flux time series (data 1.1 and 1.2)<br> 7. make_annual_fluxes_function.R: used by 6<br> 8. compare_trap_sed_publish.R: code to compare sediment trap and core top assemblages<br> 9. compare_figs.R: code to create figures<br> 10. maps_robinson.R: code to create maps</p>
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.