cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.2642245
title: FluTE Synthetic Ecosystems for Seattle

description: Data files

A set of 3 data files needs to be in the same directory as the<br>
executable to specify a population for FluTE. The file names consist of<br>
a prefix (e.g., "seattle") followed by a suffix.<br>
<br>
<br>
*-tracts.dat - Tract populations and locations, from<br>
http://www.census.gov/geo/www/cenpop/cntpop2k.html. The columns in<br>
this comma-delimited file are: state FIPS code, county FIPS code,<br>
tract FIPS code, tract population, tract longitude, and tract<br>
latitude.<br>
<br>
<br>
*-wf.dat - Tract-to-tract workerflow, extracted from stp64.us from<br>
Census 2000 Special Tabulation Product 64: Census tract of work by<br>
census tract of residence 2000. For the US-level data. Commutes over<br>
100 miles were eliminated from the data. The columns in this space-<br>
delimited file are: home state FIPS code, home county FIPS code, home<br>
tract FIPS code, work state FIPS code, work county FIPS code, work<br>
tract FIPS code, and number of workers.<br>
<br>
<br>
*-employment.dat - The number of employed working-age adults and the<br>
total number of working-age adults, from the Census Summary File 3<br>
(SF3, Table PCT35). The columns in this space-delimited file are:<br>
state FIPS code, county FIPS code, tract FIPS code, number of employed<br>
20-64 year olds, and the total number of working-age individuals<br>
(19-64 year olds).

This sample population is:

seattle - metropolitan Seattle, based on the 2000 US Census.
DOI: 10.5281/zenodo.2642259
title: FluTE Synthetic Ecosystems for USA

description: Data files

A set of 3 data files needs to be in the same directory as the<br>
executable to specify a population for FluTE. The file names consist of<br>
a prefix (e.g., "seattle") followed by a suffix.<br>
<br>
<br>
*-tracts.dat - Tract populations and locations, from<br>
http://www.census.gov/geo/www/cenpop/cntpop2k.html. The columns in<br>
this comma-delimited file are: state FIPS code, county FIPS code,<br>
tract FIPS code, tract population, tract longitude, and tract<br>
latitude.<br>
<br>
<br>
*-wf.dat - Tract-to-tract workerflow, extracted from stp64.us from<br>
Census 2000 Special Tabulation Product 64: Census tract of work by<br>
census tract of residence 2000. For the US-level data. Commutes over<br>
100 miles were eliminated from the data. The columns in this space-<br>
delimited file are: home state FIPS code, home county FIPS code, home<br>
tract FIPS code, work state FIPS code, work county FIPS code, work<br>
tract FIPS code, and number of workers.<br>
<br>
<br>
*-employment.dat - The number of employed working-age adults and the<br>
total number of working-age adults, from the Census Summary File 3<br>
(SF3, Table PCT35). The columns in this space-delimited file are:<br>
state FIPS code, county FIPS code, tract FIPS code, number of employed<br>
20-64 year olds, and the total number of working-age individuals<br>
(19-64 year olds).

This sample population is:

usa - The continental United States, based on the 2000 US Census. Note<br>
that the "wf" files are split into 49 separate files, one for each<br>
state and one for Washington, D.C. The wf file would be too large as a<br>
single file. When mpiflute does not find "usa-wf.dat", it looks for<br>
"usa-wf-?.dat", where "?" is the state FIPS code(s) of the population<br>
on the processor.
DOI: 10.5281/zenodo.2642260
title: FluTE Synthetic Ecosystems for USA

description: Data files

A set of 3 data files needs to be in the same directory as the<br>
executable to specify a population for FluTE. The file names consist of<br>
a prefix (e.g., "seattle") followed by a suffix.<br>
<br>
<br>
*-tracts.dat - Tract populations and locations, from<br>
http://www.census.gov/geo/www/cenpop/cntpop2k.html. The columns in<br>
this comma-delimited file are: state FIPS code, county FIPS code,<br>
tract FIPS code, tract population, tract longitude, and tract<br>
latitude.<br>
<br>
<br>
*-wf.dat - Tract-to-tract workerflow, extracted from stp64.us from<br>
Census 2000 Special Tabulation Product 64: Census tract of work by<br>
census tract of residence 2000. For the US-level data. Commutes over<br>
100 miles were eliminated from the data. The columns in this space-<br>
delimited file are: home state FIPS code, home county FIPS code, home<br>
tract FIPS code, work state FIPS code, work county FIPS code, work<br>
tract FIPS code, and number of workers.<br>
<br>
<br>
*-employment.dat - The number of employed working-age adults and the<br>
total number of working-age adults, from the Census Summary File 3<br>
(SF3, Table PCT35). The columns in this space-delimited file are:<br>
state FIPS code, county FIPS code, tract FIPS code, number of employed<br>
20-64 year olds, and the total number of working-age individuals<br>
(19-64 year olds).

This sample population is:

usa - The continental United States, based on the 2000 US Census. Note<br>
that the "wf" files are split into 49 separate files, one for each<br>
state and one for Washington, D.C. The wf file would be too large as a<br>
single file. When mpiflute does not find "usa-wf.dat", it looks for<br>
"usa-wf-?.dat", where "?" is the state FIPS code(s) of the population<br>
on the processor.
DOI: 10.15482/usda.adc/1503715
title: Data from: Switchgrass cultivar, yield, and nutrient removal responses to harvest timing
DOI: 10.5258/soton/d0885
title: Dataset supporting the article entitled "Energy Harvesting Meets IoT: Fuelling Adoption of Transient Computing in Embedded Systems"

description: This dataset supports the article entitled: "Energy Harvesting Meets IoT: Fuelling Adoption of Transient Computing in Embedded Systems" accepted for publication in The IEEE 5th World Forum on Internet of Things (WF-IoT).
DOI: 10.6073/pasta/27c430750e681a7cd7d124a0b73c4713
title: Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Half-hourly soil moisture and temperature data, 2008-2018

description: The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions:  1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange?   We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range.  This data set includes half-hourly values of surface moisture content (gravimetric, 0-5cm), depth-integrated soil moisture (volumetric, 0-20 cm), and soil temperature in winter warming, summer warming, and control treatment plots at CiPEHR.
DOI: 10.6080/k0fn14ch
title: fMRI time series in orbitofrontal cortex during face-house state-space task.
title: CRCNS.org ofc-4

description: This dataset contains the preprocessed fMRI time series within orbitofrontal cortex (OFC), the design matrix and event timing information of the task performed in the work of Schuck et al., Neuron 2016: Schuck, Nicolas W., Ming Bo Cai, Robert C. Wilson, and Yael Niv. "Human orbitofrontal cortex represents a cognitive map of state space." Neuron 91, no. 6 (2016): 1402-1412.
In the task, participants watched overlapping face and house images and judged the age of one category to be young or old (meaning modern or ancient for houses). The specific rule of which category to judge required participants to keep track of which state out of 16 in total they are in. The result support the theory that orbitofrontal cortex encodes task-relevant hidden states of environments. 
The data of 24 healthy human participants used in the trial-wise analysis in the paper are included. Except for the first participant who had four successful runs of data, all participants had five runs of data. The fMRI time series were slice-timing corrected and spatially realigned to correct for head motion within and across experiment runs. An evaluation of an algorithm of Bayesian representational similarity analysis (BRSA) against other approaches of representational similarity analysis by Cai, et al. PLOS Computational Biology, 2019[3] was partly based on this dataset. The work suggested that performing RSA based on activity pattern estimated from the same runs suffer from statistical bias in the similarity matrix, and recommended either BRSA or cross-run RSA.  Paper referenced:
[3] Cai, Ming Bo, Nicolas W. Schuck, Jonathan W. Pillow, and Yael Niv. "Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias." bioRxiv (2018): 347260.
DOI: 10.17632/wm4zfwkgzr.1
title: Separate collection of lightweight packages by 21 individual Dutch households in 2017

description: This dataset is linked to an article in Waste Management in 2019, https://doi.org/10.1016/j.wasman.2019.04.021. It contains the composition of the mixed municipal solid waste (MSW) and lightweight packaging waste (LWP) (locally named PMD) of 21 households in two municipalities (Oosterhout and Waalwijk) and of the reference samples of the whole municipalities; mixed MSW and LWP taken from municipal cross-docking stations. In the second folder data of the composition of MSW and LWP from various Dutch municipalities is collected. In tables F.3 and F.4 several special acronyms are used. These relate to packaging types: PBL: Poly(ethylene terephthalate ) beverage bottles large (&gt;0.5 ltr.) and transparent. PBS: Poly(ethylene terephthalate ) beverage bottles small (≤0.5 ltr.) and transparent. PENB: Polyethylene non-beverage bottles PPNB: Polypropylene non-beverage bottles PTNB: Poly(ethylene terephthalate ) non-beverage bottles
DOI: 10.5281/zenodo.2545572
title: Handwritten Species Names Data

description: This dataset is part of a paper presented at the <em>41st European Conference on Information Retrieval</em> ,14th – 18th April 2019, in Cologne. DOI: https://doi.org/10.1007/978-3-030-15712-8_43

<strong>Data summary:</strong> Word images from 240 field notes from a natural history collection have been segmented and semantically annotated. This has been carried out in the context of the project ''Making Sense of Illustrated Handwritten Archives'', http://www.makingsenseproject.org/. From a field book on mammals, field notes from four different writers have been selected, to account for different handwriting styles and structures. The segmented word images were obtained from a nichesourcing effort, with the help of a group of domain expert labellers and a handwriting recognition system MONK, developed by Lambert Schomaker. The word images were subsequently manually annotated using four classes: Genus (0), Species(1), Author(2) and Other (3). 

<strong>Dataframe fields:</strong>  rel_xc (relative centroid x coordinate), rel_yc (relative centroid y coordinate), page (identifier of field book page), rel_x1 (relative left x coordinate bounding box), rel_x2 (relative right x coordinate bounding box), rel_y1 (relative upper y coordinate bounding box), rel_y2 (relative lower y coordinate bounding box), type (class label, 0-3), image (pixels of word image), height (height word image), size (height * width word image), width (width word image).
DOI: 10.5281/zenodo.2545573
title: Handwritten Species Names Data

description: This dataset is part of a paper presented at the <em>41st European Conference on Information Retrieval</em> ,14th – 18th April 2019, in Cologne. DOI: https://doi.org/10.1007/978-3-030-15712-8_43

<strong>Data summary:</strong> Word images from 240 field notes from a natural history collection have been segmented and semantically annotated. This has been carried out in the context of the project ''Making Sense of Illustrated Handwritten Archives'', http://www.makingsenseproject.org/. From a field book on mammals, field notes from four different writers have been selected, to account for different handwriting styles and structures. The segmented word images were obtained from a nichesourcing effort, with the help of a group of domain expert labellers and a handwriting recognition system MONK, developed by Lambert Schomaker. The word images were subsequently manually annotated using four classes: Genus (0), Species(1), Author(2) and Other (3). 

<strong>Dataframe fields:</strong>  rel_xc (relative centroid x coordinate), rel_yc (relative centroid y coordinate), page (identifier of field book page), rel_x1 (relative left x coordinate bounding box), rel_x2 (relative right x coordinate bounding box), rel_y1 (relative upper y coordinate bounding box), rel_y2 (relative lower y coordinate bounding box), type (class label, 0-3), image (pixels of word image), height (height word image), size (height * width word image), width (width word image).
DOI: 10.17632/86bfbk5ttb.6
title: Database on fecal glucocorticoids (fGC) in six groups of brown howlers (Alouatta guariba clamitans) in southern Brazil

description: Description of this data Datasets used to run the linear mixed models (LMM) assessing the influence of the proportion of fruit in the diet (RFc), fruit exploration intensity (Bi), fruit availability index (RFa), and proportion of time devoted to moving (%mov) on fecal glucocorticoids (fGC) in six groups of brown howlers (Alouatta guariba clamitans) in southern Brazil (see full details on each predictor variable in Methods). The results of these analyses will be published in the following paper: Chaves, Ó.M., Fernandes, F.A., Oliveira, G.T.,Bicca-Marques, J.C. (2019). Assessing the influence of ecological, climatic, and social factors on the physiological stress of a large primate in Atlantic Forest fragments
DOI: 10.17632/bwts2c3phs.1
title: Conservation Enforcement Capacity index (CECi) - Applied to Marine Turtles

description: To develop the Conservation and Enforcement Capacity index – CECi, we combined risks and threats indices of the marine turtle Regional Management Unit (RMU) framework (Wallace et al. 2011) with two social indices: HDI and a global economic index (socio-economic index) (extracted from United Nations and World Economic Situation and Prospects-WESP databases).
DOI: 10.17632/jfb3msz44d.2
title: Mouse ANKRD31 Regulates Spatiotemporal Patterning of Meiotic Recombination Initiation and Ensures Recombination between X and Y Sex Chromosomes

description: This data set contains the raw images (immunofluorescence and western blots) and unprocessed data from current study.
DOI: 10.17632/nn7ff7kkw8.1
title: Denaturing polyacrylamide gels of RNA cleavage reaction in presence or absence of bacterial GreB

description: Denaturing polyacrylamide gels of cleavage products show that GreB accelerates RNA cleavage (left). The resulting complex is active and resumes transcription (+NTPs). Using an RNA with phosphorothioate modifications slows down the cleavage without affecting the position (right). To help the reader, cleavage_reaction_a.tif represents the raw data, while cleavage_reaction_b.tif, matches the figure in the publication (Figure S1D).
DOI: 10.17632/nt8nw28h7c.1
title: AGLJ.J 5 days of 1-minute mid-price bar test data

description: 1 week of 1-minute mid-price bar data for Anglo American PLC prepared from TRTH transaction data over the period beginning at 9:10 on 1 November 2013 and ending at 16:50 on 5 November 2013. There are 2300 data points, equivalent to 5 days * (480 1-minutes bars - 20 1-minutes bars). The data has been used in several ABM calibration projects as a standard test set. The data is provided as a CSV file and full precision MAT file (as a MATLAB workspace).
DOI: 10.5281/zenodo.2641213
title: Dynamical charge density fluctuations pervading the phase diagram  of a Cu-based high-Tc superconductor

description: [This repository contains the raw data for the manuscript "<strong>Dynamical charge density fluctuations pervading the phase diagram of a Cu-based high-Tc superconductor</strong>" (arXiv:1809.04949)]

Charge density modulations are a common occurrence in all families of high critical temperature superconducting cuprates. Although consistently observed in the underdoped region of the phase diagram and at relatively low temperatures, it is still unclear to what extent they influence the unusual properties of these systems. Using resonant x-ray scattering we carefully determined the temperature dependence of charge density modulations in YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-δ</sub> and Nd<sub>1+x</sub>Ba<sub>2-x</sub>Cu<sub>3</sub>O<sub>7-δ</sub> for several doping levels. We discovered short-range dynamical charge density fluctuations besides the previously known quasi-critical charge density waves. They persist up to well above the pseudogap temperature <em>T*</em>, are characterized by energies of few meV and pervade a large area of the phase diagram, so that they can play a key role in shaping the peculiar normal-state properties of cuprates.
DOI: 10.5281/zenodo.2641214
title: Dynamical charge density fluctuations pervading the phase diagram  of a Cu-based high-Tc superconductor

description: [This repository contains the raw data for the manuscript "<strong>Dynamical charge density fluctuations pervading the phase diagram of a Cu-based high-Tc superconductor</strong>" (arXiv:1809.04949)]

Charge density modulations are a common occurrence in all families of high critical temperature superconducting cuprates. Although consistently observed in the underdoped region of the phase diagram and at relatively low temperatures, it is still unclear to what extent they influence the unusual properties of these systems. Using resonant x-ray scattering we carefully determined the temperature dependence of charge density modulations in YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-δ</sub> and Nd<sub>1+x</sub>Ba<sub>2-x</sub>Cu<sub>3</sub>O<sub>7-δ</sub> for several doping levels. We discovered short-range dynamical charge density fluctuations besides the previously known quasi-critical charge density waves. They persist up to well above the pseudogap temperature <em>T*</em>, are characterized by energies of few meV and pervade a large area of the phase diagram, so that they can play a key role in shaping the peculiar normal-state properties of cuprates.
DOI: 10.17632/56s4dysdz4.1
title: confidence ability and herding ability

description: We use the trading data of Wanke corporation to compute the trader’s confidence ability and herding ability, which is described in detail in our paper “The dynamics of heterogeneous investors’ trading pattern——the perspective from the level of confidence and herding”. The typical trader Bayesian updates the memory coefficients of his confidence ability and herding ability based on a monthly frequency, respectively. We show the patterns of confidence ability based on the trader’s past performance and herding ability based on the recent market ups and downs.
DOI: 10.17632/5pkywrcyz9.1
title: Table S2 the list of differentially expressed genes identified among three strains in S0, S35 and S50 groups, respectively

description: This dataset is the DEGs identified in the study of "Genetic improvement of SMD utilization of largemouth bass I: Evaluation of genetic variation and gene expression patterns of different strains related to SMD utilization".
DOI: 10.17632/bwts2c3phs.2
title: Conservation Enforcement Capacity index (CECi) - Applied to Marine Turtles

description: To develop the Conservation and Enforcement Capacity index – CECi, we combined risks and threats indices of the marine turtle Regional Management Unit (RMU) framework (Wallace et al. 2011) with two social indices: HDI and a global economic index (socio-economic index) (extracted from United Nations and World Economic Situation and Prospects-WESP databases).
DOI: 10.17632/wn95327xgc.1
title: Table S1 the list of differentially expressed genes identified among three diet groups in Marlow strain

description: This dataset is the DEGs identified in the study of "Genetic improvement of SMD utilization of largemouth bass I: Evaluation of genetic variation and gene expression patterns of different strains related to SMD utilization".
DOI: 10.5519/qd.6u7mwodq
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1115 records)
DOI: 10.17632/8ks7pm2jw6.1
title: Decoding the Inversion Symmetry Underlying Transcription Factor DNA-Binding Specificity and Functionality in the Genome

description: [Column E and Column F] We overlapped the location coordinates of the 81,922 0-nt to 5-nt variant 13-nt ERE or HRE DNA elements in the genome and the location coordinates of the ChIPSeq or ChIPExo peaks in an experiment (157 ER experiments at 0-nt to 5-nt variant ERE DNA elements) (194 KR experiments at 0-nt to 5-nt variant HRE DNA elements) to determine the absolute number of times each 0-nt to 5-nt variant 13-nt ERE or HRE DNA element occurred within an experiment (the entire 13-nt DNA element was required to be within the peak boundaries). [Column V] Multiple peak selection criteria were used (L4, L8, L10, L15, L20), where Lx represents an x-fold greater tag density at peaks than in the surrounding 10-kb region. This performs a low-to-high stringency analysis of the data. By studying the data with respect to a multiple spectrum of peak selection criteria, we adjust for both the risk of excess background noise and the risk of filtering out any low-amplitude information. All peaks are observed at L4, [Column V] identifies whether that specific peak is also observed at L8, L10, L15 or L20. The ChIPSeq or ChIPExo peaks were annotated to regions in the genome (annotatePeaks.pl) using Homer. [Column A] Peak ID [Column B] Chromosome [Column C] Peak start position [Column D] Peak end position [Column G] Strand [Column H] Peak Score [Column I] FDR/Peak Focus Ratio/Region Size [Column J] Annotation (i.e. Exon, Intron, ...) [Column K] Detailed Annotation (Exon, Intron etc. + CpG Islands, repeats, etc.) [Column L] Distance to nearest RefSeq TSS [Column M] Nearest TSS: Native ID of annotation file [Column N] Nearest TSS: Entrez Gene ID [Column O] Nearest TSS: Unigene ID [Column P] Nearest TSS: RefSeq ID [Column Q] Nearest TSS: Ensembl ID [Column R] Nearest TSS: Gene Symbol [Column S] Nearest TSS: Gene Aliases [Column T] Nearest TSS: Gene description [Column U] Nearest TSS: Gene type
DOI: 10.17632/cbg6xbvd3z.1
title: Figures and tables for REE ore publication

description: Supplementary data to the paper entitled "STUDY OF THE PROPERTIES OF THE ELSTEI DEPOSIT ORE (DORNOGOVI MONGOLIA) AS A POTENTIAL RAW MATERIAL FOR OBTAINING OF RARE EARTH ELEMENTS" including Fig. S1 - S8 and Tab. S1-S3
DOI: 10.17632/cwsbd5cwbf.1
title: Triple Frame Buffer FPGA Implementation

description: Code base for the frame buffer presented in our paper.
DOI: 10.17632/h7m6vjpzmd.1
title: Parathyroid autofluorescence

description: Utilization of near infrared autofluorescence for intraoperative identification of parathyroid glands in surgery of thyroid and parathyroid glands
DOI: 10.17632/hw5p35hc9g.1
title: Brown et al. (2019) Visual Experience Regulates the Intrinsic Excitability of Visual Cortical Neurons to Maintain Sensory Function.

description: Electrophysiology data and MATLAB code to replicate figures in Brown et al. (2019) Cell Reports.
DOI: 10.17632/kc4zk8hdzy.1
title: Carbon Fiber Reinforced Structural Lithium-Ion Battery Composite: Multifunctional Power Integration for CubeSats

description: Carbon Fiber Reinforced Structural Lithium-Ion Battery Composite: Multifunctional Power Integration for CubeSats
DOI: 10.17632/m8zwv4jdwr.1
title: Categorised Ambient Displays published between 1996 and 2016 and identified in a systematic review.
DOI: 10.17632/3cj956nkzn.1
title: Simulator of Eu3+ spectrum from Judd-Ofelt intensity parameters

description: Simulator of emission spectrum can be downloaded here. Two versions are available, a Mathematica notebook, and CDF file. CDF file can be opened with free Wolfram CDF player, but it cannot import spectrum. Mathematica notebook opens spectrum from spectrum.txt (placed at root, in MS Windows in C:\), for comparison with the simulated spectrum. Example image is of Y2O3:Eu3+ doped with 3%.