cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/94xb9rn9jv.2
title: Data for: Effect of modifying industrial plant configuration on reducing agricultural loss due to air pollution

description: Data and sources of figures and tables.
DOI: 10.6073/pasta/c531e6a0eec5137a0853a8a168d47103
title: 2003 Prescribed Burn Effect on Chihuahuan Desert Grasses and Shrubs at the Sevilleta National Wildlife Refuge, New Mexico: Grass Recovery Study (2003-2018)

description: The U.S. Fish and Wildlife's plan to apply a prescribed burn to a large portion of McKenzie Flats was deemed an opportunity to study the effects of fire on the vegetation at the boundary between shrubland and grassland. This study actually was undertaken on an area that had prescribed fire applied to 8 of 16 (300 m x 300 m) plots 10 years before in 1993. This previous study had also examined the effects of fencing to exclude the indigenous prong-horn antelope. In the 2003 study the prescribed fire was applied to the northeastern half of the 16 plots while the southwestern plots were intentionally protected. Sampling prior to the prescribed burn included quantification of fuel load (ie. the standing biomass of all grasses and forbs in the area to be burned). These measurements were made using Daubenmire quadrat frames that are 5 cm x 20 cm and delineate a 0.1 square meter area. Four samples were taken adjacent to the six 3 m x 4 m quadrats in each of the eight plots that were to be burned. Quadrat frames were laid down over the vegetation and all vegetation rooted within the frame was clipped at ground level. This material was bagged, oven-dried and weighed. Following the prescribed burn, re-measurements were made every fall of from 2004 until 2012 when vegetation had reached its annual peak biomass. Data were not collected from 2014-2017, but were collected again in 2018.
DOI: 10.17632/ck8b5s8z9f.2
title: Data for: Verification of On-the-fly Homogenization Method Based on the Analysis of HTTR

description: raw date used by figures
DOI: 10.17632/6hcddsf735.2
title: Data for: Initiation of subduction of Proto-Tethys Ocean lithosphere and back-arc extension in the northern Altun Mountains, northwestern China: evidence from high-Mg diorites and A-type rhyolites

description: We provide major and trace elements, zircon U-Pb ages and Hf isotopes for the Baijianshan high-Mg diorites and Dawanbei and Dabanxi A-type rhyolites.
DOI: 10.17632/sy4vhs86n6.2
title: Data for: Photovoltaic power forecasting based on support vector machine with improved ant colony optimization

description: Original data
DOI: 10.17632/j3c3tmw6wz.2
title: Data for: Predicting long-term resource allocation and outcome after cardiac surgery. Evidence from an Italian administrative registry.

description: Selected ICD-9CM codes to identify comorbidities and in-hospital complications related to cardiac surgery patients.
DOI: 10.5281/zenodo.4724152
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.13661315.v9
title: Acoustic diversity dataset

description: Dataset and code for "<i>A machine learning approach for classifying and quantifying acoustic diversity</i>"<br><b></b>
DOI: 10.5519/qd.xt2xuei2
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (63866 records)
DOI: 10.6084/m9.figshare.14498103
title: microRNA database for understanding tomato fruit development and ripening

description: This data was acquire, processed and processed by me, Christopher Cedillo (TW @chrisantics).<br>This data was used for further analysis during my PhD Thesis "Gen silencing during tomato fruit development by exogenic small interfering RNA" at Universidad Autonoma de Queretaro Engineering Faculty.
DOI: 10.17909/t9-e05b-1j72
title: Galactic C I absorptions toward extragalactic targets

description: STIS Medium resolution echelle spectra used for the paper "Thermal Pressures in the Interstellar Medium away from Stellar Environments" by E. B. Jenkins and T. M. Tripp
DOI: 10.5281/zenodo.4709704
title: Ground-based observation of negative sprites over a tropical thunderstorm as the embryo of Hurricane Harvey (2017)

description: The dataset here includes optical data of sprite, cloud top temperature, lightning location data,sounding data, and broadband magnetic sferics (LF, VLF, ULF) for cases analyzed in the paper "<strong>Ground-based observation of negative sprites over a tropical</strong><strong> thunder</strong><strong>storm </strong><strong>as</strong><strong> the embryo of Hurricane Harvey (2017)</strong>".
DOI: 10.5281/zenodo.4709703
title: Ground-based observation of negative sprites over a tropical thunderstorm as the embryo of Hurricane Harvey (2017)

description: The dataset here includes optical data of sprite, cloud top temperature, lightning location data,sounding data, and broadband magnetic sferics (LF, VLF, ULF) for cases analyzed in the paper "<strong>Ground-based observation of negative sprites over a tropical</strong><strong> thunder</strong><strong>storm </strong><strong>as</strong><strong> the embryo of Hurricane Harvey (2017)</strong>".
DOI: 10.5281/zenodo.4724146
title: An artificial intelligence nanopore platform for SARS-CoV-2 virus detection

description: Ionic current-time profiles of nanoparticles, corona viruses, and clinical specimens
DOI: 10.5281/zenodo.3745947
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅲ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For precipitation in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (in Matlab):<br> Pr(Pr==2333)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3745946
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅲ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For precipitation in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (in Matlab):<br> Pr(Pr==2333)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.6084/m9.figshare.14495775
title: RNAseq data of poly-γ-glutamic acid enhanced drought resistance of maize

description: When the maize seeds germinated, half of the seedlings were treated with γ-PGA (10 kDa, 50 mg/L) solution. All seedlings at three-leaf stage were exposed to a drought stress treatment by stopping watering and sheltering them from rain. After 5 days treatment (soil water content decreased to 9.8 %). The leaves were taken for RNA sequencing.RNA sequencing and primary bioinformatics analysis were performed by BGI Tech Solutions Co., Ltd. (She nzhen, China). Primary sequencing data (raw read) were produced by Illumina HiSeq™ 2000.
DOI: 10.6084/m9.figshare.14495775.v1
title: RNAseq data of poly-γ-glutamic acid enhanced drought resistance of maize

description: When the maize seeds germinated, half of the seedlings were treated with γ-PGA (10 kDa, 50 mg/L) solution. All seedlings at three-leaf stage were exposed to a drought stress treatment by stopping watering and sheltering them from rain. After 5 days treatment (soil water content decreased to 9.8 %). The leaves were taken for RNA sequencing.RNA sequencing and primary bioinformatics analysis were performed by BGI Tech Solutions Co., Ltd. (She nzhen, China). Primary sequencing data (raw read) were produced by Illumina HiSeq™ 2000.
DOI: 10.5281/zenodo.3747017
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅰ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Tmax in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmax(Tmax&gt;2606)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3747016
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅰ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Tmax in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmax(Tmax&gt;2606)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3748094
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅱ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Tmin in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmin(Tmin&gt;2606)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3748093
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅱ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Tmin in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmin(Tmin&gt;2606)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3748954
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅳ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Wind in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (Matlab): Wind(Wind==2333)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.3748953
title: Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅳ

description: A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region. <strong>Note: For Wind in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (Matlab): Wind(Wind==2333)=nan;</strong> More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.
DOI: 10.5281/zenodo.4724172
title: From Blackboard to the Office: A Look Into How Practitioners Perceive Software Testing Education [Data]

description: The teaching-learning process may require specific pedagogical approaches to establish a relationship with industry practices. Recently, some studies investigated the educators' perspectives and the undergraduate courses curriculum to identify potential weaknesses and solutions for the software testing teaching process. However, it is still unclear how the practitioners evaluate the acquisition of knowledge about software testing in undergraduate courses. This study carried out an expert survey with 68 newly graduated practitioners to determine what the industry expects from them and what they learned in academia. The yielded results indicated that those practitioners learned at a similar rate as others with a long industry experience. Also, they studied less than half of the 35 software testing topics collected in the survey and took industry-backed extracurricular courses to complement their learning. Additionally, our findings point out a set of implications for future research, as the respondents' learning difficulties (e.g., lack of learning sources), and the gap between academic education and industry expectations (e.g., certifications).
DOI: 10.5281/zenodo.4724171
title: From Blackboard to the Office: A Look Into How Practitioners Perceive Software Testing Education [Data]

description: The teaching-learning process may require specific pedagogical approaches to establish a relationship with industry practices. Recently, some studies investigated the educators' perspectives and the undergraduate courses curriculum to identify potential weaknesses and solutions for the software testing teaching process. However, it is still unclear how the practitioners evaluate the acquisition of knowledge about software testing in undergraduate courses. This study carried out an expert survey with 68 newly graduated practitioners to determine what the industry expects from them and what they learned in academia. The yielded results indicated that those practitioners learned at a similar rate as others with a long industry experience. Also, they studied less than half of the 35 software testing topics collected in the survey and took industry-backed extracurricular courses to complement their learning. Additionally, our findings point out a set of implications for future research, as the respondents' learning difficulties (e.g., lack of learning sources), and the gap between academic education and industry expectations (e.g., certifications).
DOI: 10.6084/m9.figshare.14498520
title: Brood measurements 29 June 19.xlsx

description: The dung beetles<i>, Onthophagus binodis</i> was tested for its reproduction performances in the dung provided from four different time periods of a year in Australia.
DOI: 10.6084/m9.figshare.14498520.v1
title: Brood measurements 29 June 19.xlsx

description: The dung beetles<i>, Onthophagus binodis</i> was tested for its reproduction performances in the dung provided from four different time periods of a year in Australia.
DOI: 10.5281/zenodo.4724175
title: An artificial intelligence nanopore platform for SARS-CoV-2 virus detection

description: Ionic current-time profiles of nanoparticles, corona viruses, and clinical specimens
DOI: 10.21227/aahh-w207
title: Three-Phase Load Flow Analysis for Unbalanced Networks Using Newton-Raphson Method

description: A three-phase load flow problem is similar to a single-phase problem, however, in three-phase analysis it is considered that the system is unbalanced and at a bus i, there are 3 different voltages and angles, each one for phases a, b and c, respectively. In this paper it is shown how to model a three-phase load flow problem and how to calculate the variables of the system using Newton-Raphson method. It is shown a problem with 3 busbars and it is solved using a MATLAB script. The results are displayed in graphics and tables.
DOI: 10.5517/ccdc.csd.cc276h43
title: CCDC 2061814: Experimental Crystal Structure Determination

description: Related Article: Meng Juan Zhang, David James Young, Ji Long Ma, Guo Quan Shao|2021|RSC Advances|11|14899|doi:10.1039/D1RA01102B
DOI: 10.25345/c56z4j
title: MassIVE MSV000087317 - GNPS Streptomyces secondary metabolites
title: Endophytic Streptomyces sp. secondary metabolites. Full scan. Negative ion mode.
DOI: 10.6084/m9.figshare.14498589.v1
title: raw data.rar

description: raw data
DOI: 10.6084/m9.figshare.14498589
title: raw data.rar

description: raw data
DOI: 10.5281/zenodo.4724190
title: Properties of Lunar Regolith on the Moon's Farside unveiled by Chang'E-4 Lunar Penetrating Radar

description: Digital version of results in paper "Properties of Lunar Regolith on the Moon's Farside unveiled by Chang'E-4 Lunar Penetrating Radar". "day1_5_ch2B.bin" corresponds to Fig.S1, "day1_5_rbg.bin" corresponds to Fig.S2, "day1_5_comp.bin" corresponds to Fig.S3, "day1_5_bpf.bin" corresponds to Fig.4a and Fig.S5. The matrix sizes of them are 2048*4844.