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119 results for “Economic analysi”
Data for: Techno-economic analysis of a novel laccase production process utilizing perennial biomass and the aqueous phase of bio-oil, Iowa, USA 2023-2025
This dataset contains the experimental design, measurements, and derived variables used to parameterize a techno‑economic model of laccase production via two‑stage solid‑state fermentation of prairie biomass with bio‑oil aqueous phase induction. It includes nutrient screening data for Pleurotus ostreatus growth on prairie biomass with alternative nitrogen sources and a corn‑steep solids dose series; factorial/response‑surface experiments varying substrate bed depth, substrate‑to‑inoculum (S:I) ratio, and pre‑induction growth time; and time‑resolved induction measurements. For each run and replicate, the data record the full set of spectrophotometric absorbances at 0–210 s, fitted slopes and r-square values, dilution and volume factors, and laccase activities normalized per mL and per gram of biomass, alongside the exact culture timings and environmental conditions used in the ABTS assay at 420 nm. Results tables provide the fitted central‑composite design model terms (coefficients, F‑statistics, and p‑values) used directly as inputs to the minimum laccase selling price (MLSP) calculations, together with the underlying per‑condition raw results.
Techno-economic sustainability analysis methodology for conversion routes of renewable feedstock resources to bio-based products – case studies
<p>The dataset provides a set of sustainability principles, criteria and indicators for the evaluation of the conversion routes stage of a bio-based product. The selected case studies on the employment of alternative feedstocks and production of the bio-based products are implemented in order to evaluate the proposed methodology. Mass and energy balances for all case studies, estimated techno-economic metrics, cost of externalities and risk assessment results are provided</p>
Geospatial Analysis of Economic Development in kenya by Province
<p>This dataset presents both vector and raster data combinations for pm2.5, elevation, nightlight data, population density, area, and population that can be used to estimate the economic development of Kenya using distribution of banks as a proxy.</p>
When Do Authoritarian Regimes Use Digital Technologies for Covert Repression? A Qualitative Comparative Analysis (QCA) of Politico-Economic Conditions
<p>This is a replication dataset together with the QCA script used for the analysis of the article "When Do Authoritarian Regimes Use Digital Technologies for Covert Repression? A Qualitative Comparative Analysis (QCA) of Politico-Economic Conditions" submitted to the Swiss Political Science Review in 2024, for the special issue "Re-Authoritarianisation with Digital Means? Recent Developments in Digital Politics in East Central Europe and Central Asia". The package contains the following elements:</p> <p>1) The original QCA dataset with references.</p> <p>2) The supplementary dataset with the calculations related to autocratic linkages.</p> <p>3) The R script used for the QCA.</p> <p> </p>
Supplemental Materials to Accompany: Abowd and Schmutte "An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices"
<p>Materials to supplement "<a href="https://www.aeaweb.org/articles?id=10.1257/aer.20170627">An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices</a>" by John Abowd and Ian Schmutte.</p>
Supplementary information for D4.6 CEMCAP comparative techno-economic analysis of CO2 capture in cement plants
<p>Supplementary information for D4.6 CEMCAP comparative techno-economic analysis of CO2 capture in cement plants</p>
Techno Economic Analysis of Biogas Purification by Methane and Acetate Manufacturing CO2 to CH4 2024 SuppInfo
<p>Techno Economic Analysis calculations for manuscript of Biogas Purification by Methane and Acetate Manufacturing to convert CO2 to CH4: Wastewater treatment plants have two persistent financial and energetic drains, the carbon dioxide content of biogas, which limits its commercial sale, and the presence of trace organics in the wastewater effluent, which damages the aquatic ecosystem. Biogas is a renewable methane resource that is underutilized due to the variable CO2 content (~40%). Biogas is energy intensive to purify and limited by the economy of scale (>8.85 GJ/hour) to large-scale purification methods, thus small-scale processes require development. Electrocatalytic microbes native to wastewater have been shown to convert CO2 to CH4 and acetate, however complete conversion of the CO2 content to CH4 is energy intensive. Here we show a low power bioelectrochemical fuel cell design to purify biogas to pipeline quality methane (98%), manufacture methane and/or acetate, and remove trace organics, using HCO3- as the transport charge carrier from dissolved CO2 from the biogas through an anion exchange membrane. This decreased the power required to separate CO2 from methane in biogas on a molar basis, resulting in a net energy recovery similar to current industrial systems. Magnesium anode use resulted in an energy positive system. Tests evaluated the influence of cathode potential on the current density, HCO3- ion flux and the rates and efficiencies of methane production, resulting in optimization at -0.7V vs Standard Hydrogen Electrode (SHE). A techno-economic analysis modeled a positive return on investment for scaled-up production to purify small biogas streams that are otherwise financially unrecoverable. Carbon sequestration by production of methane, acetate and solid fertilizers demonstrated profitable and energy efficient waste-to-resource conversion.</p>
Can green hydrogen drive economic transformation in Saudi Arabia? - An input-output analysis of different Power-to-X configurations. Supplementary Data
<p>Supplementary material for peer review</p> <ul> <li>Modelling Data (input & results)</li> <li>Literature Review</li> </ul>
CS6 Sea urchin enhancement Norway - Socio-economic analysis
<p>The dataset builds on dataset for this case study for AquaVitae deliverable D7.3 Profitability analysis, containing cost and profitability data for harvest of sea urchins and for urchin roe enhancement. For Deliverable D7.4 it is enhanced with data on economic multipliers, kelp reforestation data, and socioeconomics, focusing on value added, employment, wages, and economic ripple effects.</p>
CS3 Land-based IMTA abalone South Africa - Socio economic analysis
<p>Data set builds on dataset and bio-economic modelling "CS3 Land-based abalone IMTA - bioeconomic model South Africa 2022" (available in the AquaVitae community in Zenodo) by considering the integrated inclusion of sea cucumbers in abalone farming. It considers three different impacts of including sea cucumbers and compares the socio-economic effects in these with a baseline scenario of abalone farming without sea cucumbers.</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>
Supplementary Data and Code: Change Point Analysis to decode Economic Crisis Information
<p>Raw data, results and Python code of the corresponding publication "Efficient Multi-Change Point Analysis to decode Economic Crisis Information from the S&P500 Mean Market Correlation" (accepted in: Entropy; Section: Complexity; Special Issue: Complexity in Finance). The change point analysis can be performed using the <a href="https://anticpy.readthedocs.io/en/latest/">documented</a> Python package <a href="https://github.com/MartinHessler/antiCPy"><em>antiCPy</em></a>. Some further helpful Python scripts are provided here under a <em>GNU General Public License v3.0.</em></p> <p>In Data_Generation you can find a list of</p> <ol> <li>S&P500 companies which are considered in the analysis,</li> <li>a jupyter notebook to create the correlation time series.</li> </ol> <p>Data_Preprocessing contains the</p> <ol> <li>S&P500 mean market correlation Financial_Time_Series_Centered_Interval__42days.csv,</li> <li>the Python code to thin it,</li> <li>the thinned data saved as .npy file,</li> <li>the time scale is saved <ul> <li>as integer numbers in thinned_time_thinning40.npy,</li> <li>as datetime in TimeScale_FinancialData.npy.</li> </ul> </li> </ol> <p>In Change_Point_Analysis you find the following files:</p> <ol> <li>cp_probs...npy contain the joint probabilities of the corresponding change point configurations (The joint probabilities are saved corresponding to the order in which Python's <em>itertools.combinations() </em>creates the configurations. This holds also for the cp_probs_5_cps.npy for which the whole combinations array is not saved for memory reasons),</li> <li>cp_pdfs...npy contain the marginal probability density functions of the ordinal change point positions averaged over all configurations,</li> <li>cp_configs...npy contain the configurations,</li> <li>segment_fit...npy contain the segment fit data,</li> <li>segment_fit_variance...npy contain corresponding variances,</li> <li>In the case of five change points only the plotted 1st, 13th and 26th most probable configuration in config_ranking_CP1_5.npy for memory reasons.</li> <li>the data and results of figure 3 for each crisis event can be found in the corresponding directory's folders: <ul> <li>blue corresponds to the pre-crisis data segments,</li> <li>green corresponds to the data segments up to the green vertical dotted line,</li> <li>red corresponds to the longest data segments incorporating near and in-crisis data.</li> </ul> </li> </ol> <p> </p> <p> </p>
Deliverable [D4.1] Techno-economic sustainability analysis methodology on resources for bio-based products, conversion routes and end-of-life alternative valorisation options
<p>Techno-economic sustainability analysis (TESA) is a methodology framework to evaluate the performance of a process under technical and economic perspective. A process can be divided into three main sections, the resources required for bio-based products, the conversion routes for the production and finally, the end-of-life alternative valorisation options. Consequently, TESA is carried out separately in the three sections and evaluates the likelihood of their different technology scales and applications and their economic feasibility.</p>
Datasets for the study "Hydro-economic analysis of infrastructure investment options within the Water-Energy-Food nexus in the Niger River basin"
<p>This is the dataset used in the study "Hydro-economic analysis of infrastructure investment options within the Water-Energy-Food nexus in the Niger River basin". This study has been conducted within the Department of Environmental Engineering at the Technical University of Denmark as a Master Thesis project. </p> <p>The dataset describes the water-energy-food nexus of the Niger River basin used as input to the open source single objective hydro-economic optimization model WHAT-IF. Note that the Energy Module is partly filled, but has not been used in the study (except the hydropower sheet).</p> <p>More information on data organization <a href="https://zenodo.org/record/2646476#.XxqORudS93g">here</a>.</p> <p>The model is documented in this <a href="https://hess.copernicus.org/articles/23/4129/2019/hess-23-4129-2019-discussion.html">publication</a>.</p> <p>The code is available on <a href="https://github.com/RaphaelPB/WHAT-IF">Github</a>.</p>
Analysis tools and data for study "Better insurance could effectively mitigate the increase in economic growth losses from US hurricanes under global warming"
<p>This scripts are used for post-analysis and for creating the main figures for our study "Better insurance could effectively mitigate the increase in economic growth losses from US hurricanes under global warming". Our raw results are calculated by InGroClIm (DOI:10.5281/zenodo.5017904).</p>
Economics Analysis of Small and Large Farm Size Honey Bee Sub-Sector in Chitwan District, Nepal
<p>This is an SPSS file that can be used for calculating various descriptive statistics and performing statistical tests such as t-tests and chi-square tests. Ranking of scale can also be carried out from these datasets.</p>
Academic Research at UNTRM: Bibliometric Analysis in Economic and Administrative Sciences
<p><span>Bibliometric analysis is crucial to assess research trends in disciplines such as economics and administrative sciences. This study aims to detail trends and developments in these areas at the Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), highlighting emerging themes and influential actors. A systematic bibliometric methodology was used to understand the scientific focus of the publications of the thesis students of the Faculty of Economics and Administrative Sciences of the UNTRM. Scopus documents were thoroughly reviewed, using specific inclusion and exclusion criteria. The research followed a qualitative descriptive approach with non-experimental and longitudinal design. A total of 379 faculty theses were analyzed through December 31, 2023, using keywords such as "bibliometric analysis," "economic sciences," "management," "digital transformation," "business sustainability," and "energy efficiency." The initial search identified 786 papers, which were refined for quality assurance. Bibliometric analysis was performed with VOSviewer and Bibliometrix R, facilitating the creation of scientific maps and exploration of citation patterns. Results showed that the most researched topics include digital transformation, sustainability, energy efficiency and business innovation. Influential authors and institutions within UNTRM were identified and major research trends were mapped, highlighting emerging areas and gaps in the current literature. These findings are significant for future research as they provide a basis for exploring new directions in economics and management sciences. This bibliometric analysis not only maps research streams and scholarly collaborations at UNTRM, but also promotes a deeper understanding of the dynamics in these key areas of study.</span></p>
Dataset of the Volkswagen Fond Project no. 90 216 " Early mounted nomads and their vessels Ceramic analysis project aimed at supporting the reconstruction of socio-economic conditions in mobile populations north of the Black Sea between 1100 and 600 BC"
<p>The Excel-Sheet contains information (location of the site, chronological position, type of site, archaeological culture, literature, photographies and drawings, analysis made, results of the analysis, etc.) about the samples taken in the Volkswagen Fond Project no. 90 216 "Early mounted nomads and their vessels Ceramic analysis project aimed at supporting the reconstruction of socio-economic conditions in mobile populations north of the Black Sea between 1100 and 600 BC".</p> <p>The project itself focuses on contacts and interactions between groups with different material culture remains in two vegetation zones to the north of the Black Sea.The investigation takes a complex archaeometric approach to characterise the pottery of communities that lived in the forest steppe zone and steppe zone to the north of the Black Sea between the Dniester and Dnieper rivers between 1100 and 600 BC. By using an multidisciplinary approach to study the material culture of these communities with mobile lifeways, this project will allow the comparison of the natural science and archaeological data for the first time.</p> <p>The Excel-Sheet presents the results of various analyses performed during the project and serves as the database for publications of the project members.</p>
The Economic Integration of Wind Energy: An Analysis of the ECOWAS Subregion
<p>This study evaluates the economic integration of wind energy in the <br>Economic Community of West African States (ECOWAS) between 2010 <br>and 2020. Wind energy is the energy source that can cost-effectively <br>meet the energy needs of the sub-regions due to the theoretical and <br>economic potential of the sub-regions. For this reason, the study uses data <br>from the World Bank Development Indicators using Panel Vector Auto <br>Regression to analyze the determinants underpinning the economic <br>integration of wind energy. The Panel VAR estimate shows a significant <br>direct link between fossil fuel consumption and private sector investment <br>in renewable energy. This implies that the sub-region consumes a <br>significant amount of fossil fuels, hence the need to increase clean energy <br>investments to move the sub-region towards a low-carbon future. <br>Another significant lag variable is the power consumption per capita in <br>the subregion. Per capita electricity consumption in the sub-region is <br>woefully insufficient. Therefore, wind energy can ensure access via the <br>development of small community wind farms where the national power <br>grid cannot be extended to. When assessing the economic justification of <br>wind integration, the LCOE for wind power is 2.98 cents per kilowatt for <br>the lowest cost scenario compared to nuclear power’s 2.26 per kilowatt <br>hour. The FEVD shows that 13.4% of renewable energy investments are <br>self-explanatory within the first and last periods. The FEVD for wind <br>energy illustrates the short-term variance of 16.4 percent and increases to <br>51.1 percent in the following years after system shocks. This implies that <br>the expansion of wind capacity in the sub-region is expected to increase <br>in the long-term. This serves as a blueprint for integrating wind energy <br>into the sub-region.</p>
Data Set "Efficient automatic construction of atom-economical QM regions with point-charge variation analysis"
<p>This data set accompanies the publication "Efficient automatic construction of atom-economical QM regions with point-charge variation analysis" by Felix Brandt and Christoph R. Jacob (TU Braunschweig, Germany) </p> <p>It contains the following files:</p> <p>- PDB files of the reactant and product starting structure</p> <p>- modified AMBER95 force field file</p> <p>- AMS fragment files for the ligands and ions</p> <p>- AMS input files for all geometry optimizations and single point calculations</p>
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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)
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DANDI Archive for NWB datasets
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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.