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182 results for “Coal”

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dryad36/100

Study on the improvement of grouting stone properties in coal mine goafs using combined denitrifying bacteria

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publicAug 2024View details →
dryad36/100

Asymmetric allelic introgression across a hybrid zone of the coal tit (Periparus ater) in the central Himalayas

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publicNov 2022View details →
dryad36/100

Methane and carbon dioxide cumulative amounts data for: Algal amendment enhances biogenic methane production from coals of different thermal maturity

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publicFeb 2023View details →
dryad36/100

Synthesis of a novel amphoteric copolymer and its application as a dispersant for coal water slurry preparation

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publicJan 2021View details →
dryad36/100

Hydrochory, a key ecological function of a tropical dry forest river threatened by a dam and open-pit coal mining in Colombia

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publicApr 2025View details →
dryad36/100

Dynamic inferential NOx emission prediction model with delay estimation for SCR de-NOx process in coal-fired power plants

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publicFeb 2020View details →
dryad36/100

Data for: Research and application of bag filter system for railway ballast bed coal suction vehicles

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publicDec 2023View details →
zenodo32/100

FIGURE 2. Heterolepidoderma sinus Kolicka, 2015 in From saline to salty? Heterolepidoderma sinus (Chaetonotida, Chaetonotidae) from subsaline coal mine settling ponds

FIGURE 2. Heterolepidoderma sinus Kolicka, 2015. Scales are in µm. A—Dorsal body view. B—View of internal morphology. C— Ventral body view. D—Detail of head with lateral lamellae. E—Detail of head, neck and anterior trunk ventral view with visible lamellae. F—Detail of trunk, furca base and furcal appendages ventral view with visible ventral lamellae.

opennotspecifiedFeb 2019View details →
zenodo32/100

Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework

<p>Dataset for &quot;Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework&quot;</p>

opencc-by-4.0Sep 2020View details →
dryad32/100

The sustainable development of coal mines by new cutting roof technology

<p>China consumes more than 3.6 billion tons of coal every year, accounting for over 60% of the energy consumption. Therefore, the sustainable development of coal mine is a problem needed to be solved by the Chinese government. During the coal resources recovery, the protective coal pillars between the adjacent working faces cause the serious loss for coal resources. In order to solve the problem, it was put forward that the new technology of roof cutting with chain arm to retain roadway in the paper. Firstly, the process of retaining roadway, roof-cutting parameters and the damage ranges of roadway surrounding rock induced by roof cutting with chain arm were analyzed. Then, it was given that the working resistance of the temporary support equipment in technology of roof cutting with chain arm to retain roadway. Next, the roof-cutting height, the type of temporary support equipment, working resistance of portal support and support parameters of the bolt and anchor cables were optimized by the numerical calculation. Finally, the industrial experiment of retaining roadway by roof cutting with chain arm was carried out in a working face. The surrounding rock damage was minimal with the use of chain arm-roof cutting technology, and the variation range of the uniaxial compressive strength was only 5%, resulting in the roof damage rate to 82 mm. From the studies, it was concluded that this technology could be of a great asset to the coal mining community.</p>

opencc-zeroMay 2020View details →
dryad32/100

Data from: Gene flow in the European coal tit, Periparus ater (Aves: Passeriformes): low among Mediterranean populations but high in a continental contact zone

Extant phylogeographic patterns of Palearctic terrestrial vertebrates are generally believed to have originated from glacial range fragmentation. Post-Pleistocene range expansions have led to the formation of secondary contact zones among genetically distinct taxa. For coal tits (Periparus ater), such a contact zone has been localized in Germany. In this study, we quantified gene flow between Fennoscandian and southern European coal tits using a set of 13 microsatellite loci. STRUCTURE analysis revealed four genetic clusters two of these on Mediterranean islands. German populations were genetically admixed but introgression of southern alleles was evident for Fennoscandian populations. In the South, we found negligible introgression of northern alleles (and haplotypes) but slight admixture of two southern genetic clusters in the Pyrenees and on the Balkan Peninsulae and near complete sorting of these two allelic lineages on the islands of Corsica and Sardinia. Genetic distinctiveness of the Mediterranean island populations reflects general patterns of endemism in the Corso-Sardinian fauna and the Cypriot fauna. Wide-range gene flow in Central Europe suggests a broad zone of intergradation between subspecies of the coal tit rather than a narrow contact zone. This is in accordance with low morphological and bioacoustic differentiation of European coal tit populations.

opencc-zeroDec 2017View details →
dryad32/100

Data from: Restoration as mitigation: analysis of stream mitigation for coal mining impacts in southern Appalachia

Compensatory mitigation is commonly used to replace aquatic natural resources being lost or degraded but little is known about the success of stream mitigation. This article presents a synthesis of information about 434 stream mitigation projects from 117 permits for surface mining in Appalachia. Data from annual monitoring reports indicate that the ratio of lengths of stream impacted to lengths of stream mitigation projects were &lt; 1 for many projects, and most mitigation was implemented on perennial streams while most impacts were to ephemeral and intermittent streams. Regulatory requirements for assessing project outcome were minimal; visual assessments were the most common and 97% of the projects reported suboptimal or marginal habitat even after 5 years of monitoring. Less than a third of the projects provided biotic or chemical data; most of these were impaired with biotic indices below state standards and stream conductivity exceeding federal water quality criteria. Levels of selenium known to impair aquatic life were reported in 7 of the 11 projects that provided Se data. Overall, the data show that mitigation efforts being implemented in southern Appalachia for coal mining are not meeting the objectives of the Clean Water Act to replace lost or degraded streams ecosystems and their functions.

opencc-zeroDec 2013View details →
zenodo32/100

Cockenzie Coal Crusher Sculpture

This is a sculpture made from old bearings from a coal crusher at Cockenzie Power Station, East Lothian, Scotland now demolished. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Mar 2021View details →
zenodo32/100

Multi-level emission impacts under rapid electrification and uncertain coal power phase-out in China's netzero transition

<p>This contains the data and plotting script of the second preprint "Multi-level emission impacts under rapid electrification and uncertain coal power phase-out in China&rsquo;s netzero transition"</p>

opencc-by-4.0Dec 2024View details →
zenodo32/100

Fig. 1 in Pannonibacter carbonis sp. nov., isolated from coal mine water

Fig. 1. Phylogenetic tree showing the relationship of strains Q4.6T and Q2.11 with strains of closely related species within the genus Pannonibacter as inferred from 16S rRNA gene sequences. Data with gaps and ambiguous nucleotides were removed during alignment for reconstruction of the tree. The tree was generated using the NJ method in MEGA 7.0 based on a comparison of 1497 nt. Bootstrap values are expressed as percentages of 1000 replications. The GenBank/EMBL/DDBJ accession number of each sequence is shown in parentheses.

opennotspecifiedMay 2018View details →
zenodo32/100

FIGURE. Taphonomic process corresponding to the abundance of different kinds of plant remains in the three layers of "vegetational Pompeii" tuff bed. Single, double and triple repeated icons in different layers indicate rare, moderate and frequent occurrence respectively. Note that the thickness of the tuff bed is scaled but that of the two coal beds is neglected. in Discovery of coprolites in an Early Permian fern mesophyll

FIGURE. Taphonomic process corresponding to the abundance of different kinds of plant remains in the three layers of "vegetational Pompeii" tuff bed. Single, double and triple repeated icons in different layers indicate rare, moderate and frequent occurrence respectively. Note that the thickness of the tuff bed is scaled but that of the two coal beds is neglected.

opennotspecifiedJan 2022View details →
zenodo32/100

A Modified Guggenheim-Anderson-Boer Model for Analyzing Water Sorption in Coal

<p><strong>Data for the manuscript :A Modified Guggenheim-Anderson-Boer Model for Analyzing Water Sorption in Coal</strong></p>

opencc-by-4.0May 2022View details →
zenodo32/100

The installation-level China coal model IL-CCM

<p><strong>The installation-level China coal model IL-CCM</strong><br> The full version of a China coal transport model with a very high spatial resolution.</p> <p><strong>What it does</strong><br> The code works in a few steps:<br> 1. Take easily understandable and readable xlsx input files on networks, plants, demand etc, and create project build files form this (done in R).<br> 2. Take the build files and create an LP problem file from it (in python, either locally or on AWS Sagemaker).<br> 3. Solve the problem from the LP problem file, and write solution to a txt file (either in Cplex interactive or in python).<br> 4. Process the solution txt file and write to easily understandable and readable xlsx (in R).<br> The packages required to run these scripts are included in the environment.yml (for python) and the renv.lock file (for R; this first requires installation of renv package: https://rstudio.github.io/renv/articles/renv.html; after installation run renv:restore()).</p> <p><strong>The model</strong><br> The model optimizes for a minimum cost of production + transport + transmission. &nbsp;<br> Production meaning coal mining costs, transport meaning rail/truck/riverborne/ocean-going transport and handling costs, and transmission meaning inter-provincial transport of electricity via UHV cables.</p> <p><strong>Constraints in the optimization</strong><br> The constraints in the mini testbench are the same as in the full model. These are:<br> - Mines (or any other node) cannot supply types of coal they do not produce.<br> - The flow of coal of each type out of a node cannot exceed flows of coal of each type into a node plus supply by the node (with supply being non-zero only for mines).<br> - The energy content of the supply and the flows of coal of each type into a node have to be at least equal to the demand for electricity, plus other thermal coal demand, plus the energy content of flows of coal of each type out of a node. Note that only mines can supply coal, all demand for electrical power occurs in provincial demand nodes, and demand for other thermal coal is placed at city-level nodes.<br> - The amount of hard coking coal (HCC) flowing into a node has to at least be equal to the steel demand multiplied by 0.581. Note that all steel demand is placed in provincial level steel demand nodes, which are connected with uni-directional links from steel plants to steel demand nodes. This means no coal can flow out of a steel demand node and we do not need further formulae for mass balances. Also note that we presume a mix of coking coal need to produce a ton of steel of 581 kg Hard coking coal (HCC), 176 kg of soft coking coal (SCC), and 179 kg of pulverized coal for injection (PCI).<br> - The amount of soft coking coal (SCC) flowing into a node has to at least be equal to the amount of HCC flowing into that node, multiplied with 0.581/0.176.<br> - The amount of pulverized coal for injection (PCI) flowing into a node has to at least be equal to the amount of HCC flowing into that node, multiplied with 0.581/0.179.<br> - The total volume of all coal types transported along a link cannot exceed the transport capacity of that link. Note that this constraint is applied only to those links with a non-infinite transport capacity. In practice this means rail links are assumed to have a transport capacity, ocean routes, rivers, and road links are assumed to have infinite capacity.<br> - The total amount of energy transported along a link cannot exceed the transmission capacity of that link. That is, the amount of each coal type multiplied with the energy content of each coal type cannot exceed the electrical transmission capacity of links. This constraint is applied only links between power plant units and provincial electricity demand nodes, as well as UHV transmission links between provincial electricity demand nodes. These are the only links along which electrical energy is transported. All other links transport physical quantities of coal. This line simultaneously deals with the production capacity (MW) and conversion efficiency of power plants: the energy transported over a link cannot exceed the volume of each coal type, multiplied with the energy content of each coal type, multiplied with the energy conversion factor of the link. For links between coal fired power plant units and provincial electricity demand nodes, this is equal to the conversion effincy of the power plant unit. For UHV transmission links between two provincial level electricity demand nodes, this is equal to (1- transmission losses) over that UHV line, with transmission losses calculated based on transmission distance and a benchmark loss for UHV-DC or UHV-AC lines.<br> - The handling capacity of ports cannot be exceeded. Specifically, the total amount of coal flowing out of a port cannot exceed its handling capacity.<br> - The production capacity of steel plants cannot be exceeded. Specifically, the total amount of hard coking coal, soft coking coal, and pulverized coal for injection flowing out of a steel plant node (and towards a provincial steel demand node) cannot exceed the steel plant&#39;s production capacity multiplied by 0.581+0.176+0.179, the mix of different coking coals needed to produce steel.</p> <p><strong>Technical notes</strong><br> - All transport costs are pre-calculated for each link, and include a fixed handling costs and a distance based transport cost, based on the type handling (origin and destination) and type of transport (separate for rail, truck, riverborne, ocean-going. A small number of coal rail lines has specific handling and transport costs).<br> - Some of the capacities are already reported in the input sheet for the edges. The physical transport capacity from this sheet is used. For capacities of ports, steel plants, and electrical transmission capacities, the data from the separate port/steel plant/electrical capacities sheets is used.<br> - An example lp file is included to make this repository as self-contained as possible. This lp file is zipped to stay within github file size limits.</p> <p><strong>Contributions</strong><br> This model was developed by Jorrit Gosens and Alex Turnbull. Frank Jotzo was part of the team that wrote the publication introducing this model.</p> <p><strong>License</strong><br> MIT License as separately included. &nbsp;<br> In short, do what you want with this script, but refer to the original authors when you use or develop this code.</p>

opencc-by-4.0Feb 2022View details →
zenodo32/100

A near infrared spectroscopy dataset of coal and coal-measure rock under diverse conditions

<p>we selected 24 representative coal and coal-measure rock samples, created sub-samples with 11 different granularity for each sample, and collected spectral data from the sub-samples under 5 different detection azimuths, 18 different detection zeniths, and 8 different light source zeniths. Our near infrared spectroscopy dataset of coal and coal-measure rock will provide valuable data support for coal and coal-measure rock identification based on near-field spectroscopy.</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Codes for "Co-firing biomass and coal with retrofitted carbon capture and storage ease China to achieve carbon neutrality and net negative carbon in power sector"

<p>Codes for &ldquo;Co-firing biomass and coal with retrofitted carbon capture and storage ease China to achieve carbon neutrality and net negative carbon in power sector&rdquo;</p>

opencc-by-4.0Dec 2022View details →

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allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record