cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21650981.v1
title: artificial barriers data sheet.xlsx

description: Results of the assessment of fish passability through artificial barriers using Rapid Barrier Passability and Hydropower Assessment Tool (https://amber.international/software/). <br> As per this protocol, the parameters of the barriers measured included: DH – drop head, the height difference between the upper and lower water table (used interchangeably with barrier height); H – water depth at the crest of the barrier; Hf – water depth below the barrier; Wt – width of the barrier head; Df – height difference between the lower water table and lower part of an inclined weir; slope – tilt of barrier surface. Measured parameters refer to the state of the barrier in the moment of measurement. Almost all parameters would change under different flow conditions and if the position of movable part of the barrier was altered. <br> The ICE protocol determines passability class basing on a decision-tree scheme, with six steps of various thresholds values. When a threshold for a DH is passed, the decision tree goes to the next threshold about H, etc. There are 20 ICE species groups based on different fish species abilities. Passability class was therefore scored for 47 fish species in 20 groups. The fish passability score was divided into 4 classes: 0 – no fish of the species is able to pass the barrier, 0.33 – only the strongest fish in good condition can pass the barrier with this causing delays in migration, 0.66 – over half of the species population is able to pass the barrier, although it causes delays, 1 – most fishes of a given species are able to pass the barrier, although it still can cause a delay in migration.
DOI: 10.17632/d2d5pccps9.2
title: Effects of changing illumination zenith on mineral spectra

description: This data-set contains four kinds of data: 
1. A readme file:
The READ_ME.txt file records more information regarding the description of this supplementary data-set.
2. Mineral spectra: 
Two spectral libraries in ASCII format, one contains all pure mineral spectra measured with changing illumination angles, and another one contains spectra linearly mixed from the pure mineral spectra.
3. Analysis results on variation of spectral feature position and absorption depth with decreasing illumination zenith angle and spectral purity:
14 figures show the variation of the center position of spectral feature with changing zenith angle and spectral purity; Another 14 figures show the variation of absorption depth of spectral feature with changing zenith angle and spectral purity.
4. Rule figures:
70 figures show the variation of rule numbers produced by SAM (spectral angle mapper) and EDC (Euclidean distance classifier) while classifying mineral spectra with changing zenith angle and spectral purity.
DOI: 10.17632/d2d5pccps9.3
title: Effects of changing illumination zenith on mineral spectra

description: This data-set contains three sets of data: 
1. Two ENVI spectral library files:

One library contains all pure mineral spectra measured with changing illumination angles
-Pure_mineral_spectra
-Pure_mineral_spectra.hdr
We name each spectrum in the pure mineral spectral libraries in this way: mineral name_zenith angle under which the spectrum is measured

For instance, a spectrum of gypsum measured under a zenith angle of 55° is named: gypsum_55

Another library contains spectra linearly mixed from the pure mineral spectra
-Mixed_spectra
-Mixed_spectra.hdr
We name each spectrum in the mixed mineral spectral library in this way: mixed_abbreviation of mineral name_zenith angle under which the spectrum is measured_spectral purity of the mineral spectrum
The abbreviation for mineral names are: "vivi" for vivianite, "gyp" for gypsum, "mala" for malachite, "brx" for borax, "cal" for calcite, "kao" for kaolinite, "mont" for montmorillonite
For instance, a mixed spectrum of kaolinite (spectral purity: 75%) measured under a zenith angle of 85° is named: mixed_kao_85_75

2. A pdf file named analysis results that contains all analysis results on variation of spectral feature position and absorption depth with decreasing illumination zenith angle and spectral mixing:

-14 figures show the variation of spectral feature depth on the original spectral with changing zenith angle and spectral purity
-14 figures show the variation of center wavelength position on the original spectral with changing zenith angle and spectral purity
-14 figures show the variation of spectral feature depth on the continuum removed spectral with changing zenith angle and spectral purity
-14 figures show the variation of center wavelength position on the continuum removed spectral with changing zenith angle and spectral purity
-14 Tables that show magnitude of variation of feature parameters with decreasing zenith. The feature parameters are calculated based on the original spectra and the continuum removed spectra respectively.
-70 rule number figures:
We produced 70 rule figures to show the rule numbers from 2 classifiers when classifying the pure mineral spectra and mixed spectra.
We namde each figure after a rule: classifier_rule_abbreviaiton of mineral name_spectral purity.
DOI: 10.17632/d2d5pccps9.1
title: Effects of changing illumination zenith on mineral spectra

description: This data-set contains four kinds of data: 
1. A read-me file:
The READ_ME.txt file records more information regarding the description of this supplementary data-set.
2. Mineral spectra: 
Two spectral libraries in ASCII format, one contains all pure mineral spectra measured with changing illumination angles, and another one contains spectra linearly mixed from the pure mineral spectra.
2. Analysis results on variation of spectral feature position and absorption depth with decreasing illumination zenith angle and spectral purity:
14 figures show the variation of center position of spectral feature with changing zenith angle and spectral purity; Another 14 figures show the variation of absorption depth of spectral feature with changing zenith angle and spectral purity.
3. Rule figures:
70 figures show the variation of rule numbers produced by SAM (spectral angle mapper) and EDC (Euclidean distance classifier) while classifying mineral spectra with changing zenith angle and spectral purity.
DOI: 10.17632/d2d5pccps9.4
title: Effects of changing illumination zenith on mineral spectra

description: This data-set contains three sets of data: 
1. Two ENVI spectral library files:

One library contains all pure mineral spectra measured with changing illumination angles
-Pure_mineral_spectra
-Pure_mineral_spectra.hdr
We name each spectrum in the pure mineral spectral libraries in this way: mineral name_zenith angle under which the spectrum is measured

For instance, a spectrum of gypsum measured under a zenith angle of 55° is named: gypsum_55

Another library contains spectra linearly mixed from the pure mineral spectra
-Mixed_spectra
-Mixed_spectra.hdr
We name each spectrum in the mixed mineral spectral library in this way: mixed_abbreviation of mineral name_zenith angle under which the spectrum is measured_spectral purity of the mineral spectrum
The abbreviation for mineral names are: "vivi" for vivianite, "gyp" for gypsum, "mala" for malachite, "brx" for borax, "cal" for calcite, "kao" for kaolinite, "mont" for montmorillonite
For instance, a mixed spectrum of kaolinite (spectral purity: 75%) measured under a zenith angle of 85° is named: mixed_kao_85_75

2. A pdf file named analysis results that contains all analysis results on variation of spectral feature position and absorption depth with decreasing illumination zenith angle and spectral mixing:

-14 figures show the variation of spectral feature depth on the original spectral with changing zenith angle and spectral purity
-14 figures show the variation of center wavelength position on the original spectral with changing zenith angle and spectral purity
-14 figures show the variation of spectral feature depth on the continuum removed spectral with changing zenith angle and spectral purity
-14 figures show the variation of center wavelength position on the continuum removed spectral with changing zenith angle and spectral purity
-14 Tables that show the magnitude of variation of feature parameters with decreasing zenith. The feature parameters are calculated based on the original spectra and the continuum removed spectra respectively.
The 14 Tables also show the Spear correlation coefficient of the variation of feature parameters with the increasing zenith angle.
-70 rule number figures:
We produced 70 rule figures to show the rule numbers from 2 classifiers when classifying the pure mineral spectra and mixed spectra.
We name each figure after a rule: classifier_rule_abbreviaiton of mineral name_spectral purity.
DOI: 10.6084/m9.figshare.21650987
title: Supporting Information of Computational results for Experimental and Theoretical Elucidation of SPAAC Kinetics for Strained Alkyne-Containing Cycloparaphenylenes

description: Supporting Info for a manuscript
DOI: 10.6084/m9.figshare.21650987.v1
title: Supporting Information of Computational results for Experimental and Theoretical Elucidation of SPAAC Kinetics for Strained Alkyne-Containing Cycloparaphenylenes

description: Supporting Info for a manuscript
DOI: 10.17632/95z3nkgjd5.1
title: Research data for soil extracellular polymeric substances (EPS) based on the deconstruction of the extraction process

description: The research dataset includes changes in elemental content, biopolymer content, and optical properties of soil EPS during the two-step extraction process of the CER method. This study provides comprehensive information on the extraction dynamics and spectral characteristics of soil EPS. Analysis of soil EPS is expected to disentangle the extracellular responses of soil microbes and reveal the ecological functions of extracellular products in soil, aiming to manage microbial-mediated nutrient turnover and soil quality better.
DOI: 10.17632/95z3nkgjd5.2
title: Research data for soil extracellular polymeric substances (EPS) based on the deconstruction of the extraction process

description: The research dataset includes changes in elemental content, biopolymer content, and optical properties of soil EPS during the two-step extraction process of the CER method. This study provides comprehensive information on the extraction dynamics and spectral characteristics of soil EPS. Analysis of soil EPS is expected to disentangle the extracellular responses of soil microbes and reveal the ecological functions of extracellular products in soil, aiming to manage microbial-mediated nutrient turnover and soil quality better.
DOI: 10.6084/m9.figshare.14185739.v3
title: Global GPP, ET, Ec, Es and Ei simulated by PML-V2 with AVHRR GIMMS3g LAI at a 0.05 degree resolution over 1982-2014

description: We provide global monthly and annual gross primary production(GPP), evapotranspiration (ET), canopy transpiration (Ec), soil evapiration (Es), rainfall interception loss (Ei) at a 0.05x0.05 degree resolution as simulated by PML-V2 forced with GLDAS V2.0 climate forcings, historical monthly CO2, AVHRR GIMMS3g LAI, GLASS V4 albedo and emissivity, MODIS IGBP land-use cover data etc.
DOI: 10.17632/w7p83wmy43.1
title: NJ Recycling Centers

description: The State of New Jersey Department of Environmental Protection provides a comprehensive list of where each facility is located, exactly what types of trash they pick up and contact information.
Class A recycling centers accept all the mainstream, post-consumer trash items you would expect like metal, glass, paper, cardboard, plastic containers, etc. Class B recycling materials pertain to only materials that are specifically recycled and not disposed of in landfills, “construction debris” and need to be source separated - materials include concrete, asphalt, wood, tree material, leaves, tires, roof shingles and contaminated soil.
Class C is the easiest one to follow as the C stands for compost, including plant and food matter. Class D recycling facilities has a big variety including lots of toxic chemicals like oil, antifreeze, paints, lightbulbs, batteries, substances containing mercury, and all oil collection Intermediate processing facilities are usually Class A centers that separate sources.
The state of New Jersey Department of Environmental Protection website has compiled many lists and rankings of recycling centers with specific subcategories such as carpets, vegetable oil, and scrap tire.
Data retrieved November 2022 from: https://www.nj.gov/dep/dshw/recycling/recymkts_directory.htm (last updated 2016)
DOI: 10.5281/zenodo.7377776
title: Rohu Repeats

description: Scaffold Rohu assembly, RepeatModeler2 predicted repeat families, RepeatMasker output, and ddRAD vcf. Complete assembly can be found at GCA_022985175.1.
DOI: 10.5281/zenodo.7377775
title: Rohu Repeats

description: Scaffold Rohu assembly, RepeatModeler2 predicted repeat families, RepeatMasker output, and ddRAD vcf. Complete assembly can be found at GCA_022985175.1.
DOI: 10.17632/9zv3jbp76j.2
title: The spectrum of cutaneous immune-related adverse events in patients with skin of color

description: The spectrum of cutaneous immune-related adverse events in patients with skin of color. Representative photographs of eczematous dermatitis and lichenoid dermatitis.
DOI: 10.17632/c8ftxyyh36.1
title: The Effects of Context and Prosody on the Perception of Verbal Sarcasm

description:    Two experiments were conducted with Chinese materials in the current study. 
    In the first part of Experiment 1, we invited a 24-year-old Chinese native speaker to record 42 acoustic sentences (21 with sincere prosody and 21 with sarcastic prosody). Applying voice processing software, we extracted or calculated seven acoustic parameters (mean intensity, mean pitch, intensity SD, pitch SD, intensity range, pitch range, tempo) of these 42 sentences (as what the file named Experiment 1 Part 1 shows). The result demonstrated that sarcastic prosody and sincere prosody were distinguishable by seven acoustic features. In the second part of Experiment 1, twenty-eight participants were invited to score the recorded experimental stimuli. After listening to the target sentences, participants were asked to rate on a 7-point Likert scale to what extent they thought the intention of each sound excerpt was sincere or sarcastic (1 = very sincere, 2 = sincere, 3 = a little sincere, 4 = neutral, 5 = a little sarcastic, 6 = sarcastic, 7 = very sarcastic). Forty-two target sentences in acoustic form were played in a random order. The data (as what the file named Experiment 1 Part 2 shows) indicated that the listener could distinguish a literal sincere meaning from an implied sarcastic meaning merely according to the prosody. 
    Experiment 2 further explored the interplay role of context and prosody. The materials of Experiment 2 were 42 target sentences and 42 contexts written, recorded, and validated in Experiment 1. A single trial of Experiment 2 consisted of a situational context followed by a relevant target sentence. There were 21 contextual scenarios and 21 target sentences, and each contextual scenario included two versions: a negative context (leading to a “sarcastic” perception) and a positive context (leading to a “sincere” perception). Additionally, each target sentence included two prosodies: a negative prosody and a positive prosody. Thus, there were 84 combinations of context and target sentence (21 scenarios × 2 versions × 2 target sentences with different acoustic features). All materials were divided into four item pairs according to the Latin square design, and each participant finished one item pair. Each test consisted of 21 trials with four combined pairs. The four item pairs were combined with contexts (negative and positive) and prosodies (negative and positive). Thus, four item pairs were obtained: NN, PP, NP, and PN. 
    We obtained a total of 1680 (21 trials × 80 participants) responses including choices and RTs (21 trials × 80 participants). We rejected some invalid responses, remaining 90.48% (1520) of the total responses (as what the file named Experiment 2 shows).
DOI: 10.5517/ccdc.csd.cc283kjh
title: CCDC 2088796: Experimental Crystal Structure Determination

description: Related Article: Milon M. Sadhu, Chhavi Khajuria, Vinod K. Singh|2022|Org.Biomol.Chem.|20|9098|doi:10.1039/D2OB01532C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2czt9h
title: CCDC 2204357: Experimental Crystal Structure Determination

description: Related Article: Yunpeng Sun, Yongyue Wang, Yaqi Li, Siyuan Wang, Danyang Zhang, Lingyi Kong, Jun Luo|2022|Org.Biomol.Chem.|20|9222|doi:10.1039/D2OB01830F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21648620
title: Rating versus ranking in a Delphi survey: a randomized controlled trial

description: The Delphi technique has steeply grown in popularity in health research as a structured approach to group communication process. Rating and ranking are two different procedures commonly used to quantify participants’ opinions in Delphi surveys. Little is known about the effect of assessment procedure on the outcome of the Delphi process, questionnaire completion time, and evaluation of task difficulty. This dataset pertains to a randomized controlled parallel group trial that was embedded in a three-round online Delphi survey to compare rating and ranking. After an “open” first round, primary care patients, trained patient partners, and primary care clinicians (n=36) from seven primary care practices in Quebec, Canada, were allocated 1:1 to a rating or ranking assessment group for the remainder of the study by stratified permuted block randomization, with strata based on participants’ gender and status. Items achieving an initial consensus level ≥66.6% in each study group during round 2 were reassessed during the final (third) round. The dataset related to the main Delphi study, in which the results from the rating and ranking groups were combined and differences between patient and clinician panelists were explored, is available here: https://doi.org/10.6084/m9.figshare.20110280.v1. The study was approved by the University of Montreal Hospital Research Centre’s research ethics committee (project number 17.305). Participant recruitment and data collection took place over a one-year period, from November 2019 to November 2020. <br> Please see the README_file for more information about the variables in the dataset. <br> <br>
DOI: 10.5281/zenodo.7373382
title: ScintPi 2.0 and 3.0: low-cost GNSS-based monitors of ionospheric scintillation and total electron content

description: This data set provides measurements made by PolaR5x and ScintPi3.0 receivers in Presidente Prudente, Brazil for two consecutive days.
DOI: 10.5281/zenodo.7373383
title: ScintPi 2.0 and 3.0: low-cost GNSS-based monitors of ionospheric scintillation and total electron content

description: This data set provides measurements made by PolaR5x and ScintPi3.0 receivers in Presidente Prudente, Brazil for two consecutive days.
DOI: 10.5281/zenodo.7384019
title: ScintPi 2.0 and 3.0: low-cost GNSS-based monitors of ionospheric scintillation and total electron content

description: This data set provides measurements made by PolaR5x and ScintPi3.0 receivers in Presidente Prudente, Brazil for two consecutive days.
DOI: 10.5281/zenodo.7383894
title: Satellite-based shoreline detection: macrotidal high-energy coasts dataset

description: This dataset accompanies the article by Konstantinou <em>et al.</em> (2022) titled ‘Satellite-based shoreline detection: macrotidal high-energy coasts’. This study assesses the ability of existing satellite image analysis technology to capture shoreline position change at relevant magnitudes and timescales for two different coastal environments in the United Kingdom. It addresses the influence of tidal elevation and wave-induced water-level fluctuations at two sites representing end members of beach morphological type in a region of low satellite useability (high cloud cover combined with low image availability). The study uses 14 years of monthly topographic surveys at two macrotidal sites in the UK, combined with modelled wave data and harmonic tidal predictions to investigate the influence of tidal elevation and wave action on SDS accuracy. <strong>Description</strong> The dataset consists of two matlab files each containing the information listed below for the two test sites (Slapton Sands (SLSdata); Perranporth (PPTdata)): dnum: date of satellite image capture in matlab datenum format sat: name of satellite (L5=Landsat 5; L7=Landsat 7; L8=Landsat 8; S2=Sentinel-2) transects: a structure containing the following variables: profName – the name of the survey profile startEast; startNorth; endEast; endNorth: OSGB coordinates of the start (landward) and end (seaward) of the transect line startUTMlat; startUTMlon; endUTMlat; endUTMlon: WGS84-UTM30 coordinates of the start (landward) and end (seaward) of the transect line orientation: profile orientation shoreOrient: shoreline orientation transAngle: profile angle to shore-normal. transTimeSeries: time series of the intersection of the SDW at each transect in three columns that include chainage (m), longitude, latitude. profData: a nested structure containing the survey data at organised by profile including survey date, OSGB and WGS84-UTM30 coordinates of surveyed points.
DOI: 10.5281/zenodo.7383895
title: Satellite-based shoreline detection: macrotidal high-energy coasts dataset

description: This dataset accompanies the article by Konstantinou <em>et al.</em> (2022) titled ‘Satellite-based shoreline detection: macrotidal high-energy coasts’. This study assesses the ability of existing satellite image analysis technology to capture shoreline position change at relevant magnitudes and timescales for two different coastal environments in the United Kingdom. It addresses the influence of tidal elevation and wave-induced water-level fluctuations at two sites representing end members of beach morphological type in a region of low satellite useability (high cloud cover combined with low image availability). The study uses 14 years of monthly topographic surveys at two macrotidal sites in the UK, combined with modelled wave data and harmonic tidal predictions to investigate the influence of tidal elevation and wave action on SDS accuracy. <strong>Description</strong> The dataset consists of two matlab files each containing the information listed below for the two test sites (Slapton Sands (SLSdata); Perranporth (PPTdata)): dnum: date of satellite image capture in matlab datenum format sat: name of satellite (L5=Landsat 5; L7=Landsat 7; L8=Landsat 8; S2=Sentinel-2) transects: a structure containing the following variables: profName – the name of the survey profile startEast; startNorth; endEast; endNorth: OSGB coordinates of the start (landward) and end (seaward) of the transect line startUTMlat; startUTMlon; endUTMlat; endUTMlon: WGS84-UTM30 coordinates of the start (landward) and end (seaward) of the transect line orientation: profile orientation shoreOrient: shoreline orientation transAngle: profile angle to shore-normal. transTimeSeries: time series of the intersection of the SDW at each transect in three columns that include chainage (m), longitude, latitude. profData: a nested structure containing the survey data at organised by profile including survey date, OSGB and WGS84-UTM30 coordinates of surveyed points.