cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8161215
title: Preservation of corneous beta proteins in Mesozoic feathers

description: <strong>S-XANES data. </strong>Small samples (≥3 mm<sup>2</sup>) of untreated and experimentally degraded feathers in addition to fossil material and samples of host sediment were placed on low-sulfur mylar tape and analyzed at the Stanford Synchrotron Radiation Lightsource (SSRL) using synchrotron X-ray absorption near-edge spectroscopy (XANES) at beam line 6-2. S-XANES data were collected in fluorescence mode using a single element Vortex silicon drift detector set at an angle of ~90° to the incident beam to minimize the scatter signal. The incident x-ray energy was selected using a Si(111) monochromator, which was calibrated using a Na<sub>2</sub>S<sub>2</sub>O<sub>3 </sub>standard with the thiol pre-edge peak defined as 2472.02 eV. S-XANES standards for selected S-bearing compounds, representing different S species, were prepared by mixing commercially available analytical standards (Sigma Aldrich; ≥98% pure) with BN to obtain a S concentration of ca. 5 wt% in each standard. Data alignment, averaging, background subtraction and normalisation were performed using Athena v. 0.9.26. <strong>FTIR data.</strong> Fossil data were collected in the 4000–600 cm<sup>-1</sup> range using a PerkinElmer Frontier FTIR spectrometer fitted with a Spotlight 400 microscope. Each spectrum was collected as an average of 8–36 scans. Spectra for untreated and matured feathers were collected in the 4000–500 cm<sup>-1</sup> range using a universal diamond ATR accessory on the Frontier spectrometer. Each spectrum was collected as an average of 10 scans. Each spectrum was baseline-corrected using SpectraGryph v. 1.2.7 using the parameters adaptive correction, 15% coarseness and no offset. In addition, interactive baseline correction was performed on data in the region 898–450 cm<sup>-1</sup> using Spectrum IR v. 10.6.1 (PerkinElmer, USA). This ensured a consistent baseline across the entire scan range to facilitate spectral comparison. Each spectrum was standardized to remove sample thickness effects.
description: The software package Athena is required to open all X-ray absorption spectroscopy data in .prj files and is available in the Demeter software suite. Spectragryph software is required to open all Fourier transform infrared spectroscopy data in .sp and .spc files. OriginPro is required to open all deconvolution data in .opju files. This study was also supported by the Irish Research Council New Foundations award.
DOI: 10.5519/qd.2pu3dw8o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (17 records)
DOI: 10.25345/c5862bn8b
title: MassIVE MSV000092907 - Cell wall proteomics in live Mycobacterium tuberculosis uncovers exposure of ESX substrates to the periplasm
title: The cell wall of mycobacteria plays a key role in interactions with the environment and its ability to act as a selective filter is crucial to bacterial survival. Proteins in the cell wall enable this function by mediating the import and export of diverse metabolites from ions to lipids to proteins. Accurately identifying cell wall proteins is an important step in assigning function, especially as many mycobacterial proteins lack functionally characterized homologues. Current methods for protein localization have inherent limitations that reduce accuracy. Here we showed that protein tagging by the engineered peroxidase APEX2 within live Mycobacterium tuberculosis enabled the accurate identification of the cytosolic and cell wall proteomes. Our data indicate that substrates of the virulence-associated Type VII ESX secretion system are exposed to the Mtb periplasm, providing insight into the currently unknown mechanism by which these proteins cross the mycobacterial cell envelope. The mass spectrometry raw files and search results for the APEX strategy are included here.
DOI: 10.34740/kaggle/dsv/6506278
title: MoviesDatasets
DOI: 10.34740/kaggle/dsv/6506280
title: Mahanagar Yatayat Transport Dataset
DOI: 10.25934/pr00009093
title: Secondary analysis for estimating heterogeneous treatment effects for the “Drotrecogin Alfa (Activated) in Adults with Septic Shock” trial

description: Sepsis is a life-threatening condition arising when the body’s reaction to infection injures its own tissues and organs. It occurs when the immune system – which normally helps to protect us against infection – goes into overdrive. It can lead to shock, multiple organ failure and sometimes death.

In sepsis, increased inflammation and blood clotting are harmful and interrelated drivers of the disease process. Protein C, a substance occurring naturally in the body that promotes clot breakdown and inhibits inflammation, is depleted. In preliminary studies, administration of activated protein C led to dose-dependent reductions in markers of deranged blood clotting and inflammation. These promising results warranted conclusive studies of clinical efficacy. Several large randomized clinical trials have produced inconsistent information about efficacy of activated protein C in a form of Drotrecogin alfa (activated) in patients with severe sepsis.

In 2011, the Drotrecogin Alfa (Activated) in Adults with Septic Shock (PROWESS-SHOCK) study failed to confirm efficacy of activated protein C for reduction of mortality. In the subgroup analysis, a trend for benefit among more severely ill patients was observed. The negative results of the PROWESS-SHOCK study resulted in withdrawal of Drotrecogin Alfa (Activated) from the market.

Whilst the study results for all the total trial population suggest a drug is ineffective, the diversity of trial participants within the trial might be hiding the fact that it is relatively effective for some subgroups. Recent advances in research methodology allow for predicting treatment effect for individual patients by using all available information, such as baseline characteristics, comorbidities, severity of illness, etc. Discrepancies between predicted individual and observed overall treatment effects suggest heterogeneity of treatment effect (HTE) determined by patients’ characteristics.

In this secondary analysis of the PROWESS-SHOCK trial we will use novel analytical approaches to test for HTE in the study population. This will allow us to identify patients that might benefit from the intervention, which may inform future research aiming at reducing mortality among patients with severe sepsis
DOI: 10.5519/qd.5zs820wy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (61 records)
DOI: 10.3886/e188606v1-141689
title: Collective Teacher Efficacy and its Enabling Conditions

description: This quantitative study aims to explore the validity of Donohoo et al.’s (2020) Enabling Conditions for Collective Teacher Efficacy Scale (EC-CTES) for fostering collective efficacy in schools and evaluate its relationship to measures of collective teacher efficacy.<b> </b>The instruments used for this study include the EC-CTES, the Collective Efficacy Scale (CES-SF), and the Collective Teacher Beliefs Scale (CTBS). The data were evaluated through confirmatory factor analysis, correlation matrices, and multiple regression models.<b> </b>The findings from this study demonstrate that the EC-CTES is a valid tool. The EC-CTES subscales are positively associated with measures of collective teacher efficacy.<b> </b>We recommend adjustments for the EC-CTES subscales for greater congruence with collective efficacy theory and practical application. Due to the theoretical density of collective teacher efficacy, a modified conceptual framework is proposed to make the enabling conditions theory more accessible to practitioners.<b></b><b></b>
DOI: 10.5281/zenodo.8363932
title: acropternis_orthonyx_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8363931
title: acropternis_orthonyx_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.20760970
title: CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches

description: <b>CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches</b>Jinmeng Rao, Song Gao , Sijia ZhuGeoDS Lab, Department of Geography, University of Wisconsin-Madison, WI<b><i>International Journal of Geographical Information Science</i></b>Abstract: The prevalence of ubiquitous location-aware devices and mobile Internet enables us to collect massive individual-level trajectory dataset from users. Such trajectory big data bring new opportunities to human mobility and GeoAI research but also raise public concerns with regard to location privacy. In this work, we present the Conditional Adversarial Trajectory Synthesis (CATS), a deep-learning-based methodological framework for privacy-preserving trajectory data publication. CATS applies K-anonymity to the underlying spatiotemporal distributions of aggregated human mobility, which provides a distributional-level strong privacy guarantee. By leveraging conditional adversarial training on K-anonymized human mobility matrices, trajectory global context learning using the attention-based mechanism, and recurrent bipartite graph matching of adjacent trajectory points, CATS is able to reconstruct trajectory topology from conditionally sampled locations and generate high-quality synthetic trajectory data, which can serve as supplements or alternatives to raw data for privacy-preserving trajectory data publication. The experiment results on over 90k trajectories show that our method has a better performance in privacy preservation, characteristic preservation, and downstream utility compared with baseline methods, which brings new insights into privacy-preserving human mobility research and explores data ethics issues in GIScience.<br>Source code for the work entitled "CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches".<br>Due to the non-disclosure agreement with the data provider, we are not releasing the original individual-level GPS trajectory data but sharing the mocked individual GPS trajectory data with the same data structure and also the k-anonymized aggregated human mobility data used in the experiments.<br>Content Introduction<br>- aggregate_mobility_matrix.py: generate the aggregated mobility distribution file from individual GPS trajectories- cats.py: provides a PyTorch implementation of CATS, including a TrajGenerator (CatGen) class and a TrajDiscriminator (CatCrt) class.- train_cats.py: provides a training example code for CATS.- run_cats.py: provides a inference example code for CATS.- log_util.py: logging class.- stmm_dataset.py: provides a Dataset class used for training the CATS.<br>- stmm_data/: k-anonymized aggregated mobility matrix data.- mocked_individual_gps_data: the mocked individual GPS trajectory data samples with the same data structure with raw data
DOI: 10.5281/zenodo.8364078
title: hafferia_zeledoni_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8364077
title: hafferia_zeledoni_spades_01.fasta.gz

description: .
DOI: 10.17632/cdc5wfmhs2.2
title: Simulation Dataset on Fire in the Cavity of Naturally Ventilated Double Skin Façade with Venetian Blinds

description: This dataset contains thermocouple temperature data in °C obtained from Fire Dynamic Simulation (FDS) of a 5MW HRR polyurethane GM27 fire in a multi-storey Double Skin Façade (DSF) building with Venetian blinds. The Excel spreadsheet has temperature data obtained from thermocouples installed on the glazing surfaces in the DSF cavity for floors 2, 3 and 4 (see Physical Model and Thermocouple Map). The data is presented for the scenarios where there is no Venetian blind installed in the DSF cavity to when the Venetian blind is 0.5m away from the inner glazing, Middle and 0.5m away from the outer glazing in the DSF cavity. In these scenarios the dataset also shows the glazing surface temperatures for various Venetian blind slat angle openings of 135°, 90°, 45° and 0° in the three Venetian blind positions in the DSF cavity. The simulation was carried out at 100s per scenario. The dataset also contains the input and output data files obtained from the National Institute of Standards and Technology’s (NIST) Fire Dynamic Simulator (FDS) software used for the investigations. A PDF of the Physical Model and Thermocouple Position Map is also provided in this dataset to provide clarity for users of this dataset. The input and output source codes are provided in folders labelled Fire in DSF with Venetian Blind - Input Data and Fire in DSF with Venetian Blind - Output Data respectively.

The dataset also includes the model validation data. The model validation data includes the surface temperatures in °C obtained from two thermocouples labelled TC 59 installed at a height of 1.6m representing the thermocouple on the upper floor and TC 63 installed at a height of 4.8m representing the thermocouple on the lower floor. The input source code for the simulation for the model validation is also included and labelled ‘Validation-Input’. A thermocouple map labelled Thermocouple Map-Validation Model is also included to provide users with clarity. 

Further information and details related to this dataset can be found in: Huang Y, Yeboah S, Shao J. Numerical investigation of fire in the cavity of naturally ventilated double skin façade with venetian blinds. Building Services Engineering Research and Technology. 2022;0(0). doi:10.1177/01436244221129763. https://journals.sagepub.com/doi/10.1177/01436244221129763
DOI: 10.5517/ccdc.csd.cc1nhwmn
title: CCDC 1534612: Experimental Crystal Structure Determination

description: Related Article: Wei Liu, Yuangang Xu, Yulong Zhang, Hanyue Zheng, Xiaodong Gou, Fei Xiao|2023|RSC Advances|13|26563|doi:10.1039/D3RA03585A
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.cc1nhwnp
title: CCDC 1534613: Experimental Crystal Structure Determination

description: Related Article: Wei Liu, Yuangang Xu, Yulong Zhang, Hanyue Zheng, Xiaodong Gou, Fei Xiao|2023|RSC Advances|13|26563|doi:10.1039/D3RA03585A
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.cc1nhy36
title: CCDC 1534658: Experimental Crystal Structure Determination

description: Related Article: Wei Liu, Yuangang Xu, Yulong Zhang, Hanyue Zheng, Xiaodong Gou, Fei Xiao|2023|RSC Advances|13|26563|doi:10.1039/D3RA03585A
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.cc2bpwwt
title: CCDC 2165997: Experimental Crystal Structure Determination

description: Related Article: Yawei Liu, Yanzhong Li, Tao Pu, Yuetian Pei, Yiwei Fan, Congjian Xu, Fuyou Li|2023|New J.Chem.|47|16794|doi:10.1039/D3NJ03430E
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.cc2bpwxv
title: CCDC 2165998: Experimental Crystal Structure Determination

description: Related Article: Yawei Liu, Yanzhong Li, Tao Pu, Yuetian Pei, Yiwei Fan, Congjian Xu, Fuyou Li|2023|New J.Chem.|47|16794|doi:10.1039/D3NJ03430E
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: 10.5281/zenodo.8364132
title: myiotriccus_ornatus_spades_01.fastq.gz

description: .
DOI: 10.5281/zenodo.8364131
title: myiotriccus_ornatus_spades_01.fastq.gz

description: .
DOI: 10.5281/zenodo.8165086
title: Narrativas médicas en texto de 100 a 1000 palabras y en audio de 30, 60, 90 y 120 segundos

description: Consta de 10 narrativas médicas en texto de diferentes numero de palabras: 100, 200, 300, 400, 500, 600, 700, 800, 900 y 1000. Las cuales pueden ser utilizadas para pruebas de PLN. Ademas consta de 4 archivos de audio en formato wav a 16kHz, los cuales son narraciones médicas, dichos audios tienen una duración de 30, 60, 90 y 120 segundos #Existen dos narrativas principales: una de 100 palabras y otra de 200 palabras. Estas narrativas sirven como base para la creación de los demás archivos de texto y de audio.
DOI: 10.5281/zenodo.8364140
title: Narrativas médicas en texto de 100 a 1000 palabras y en audio de 30, 60, 90 y 120 segundos

description: Consta de 10 narrativas médicas en texto de diferentes numero de palabras: 100, 200, 300, 400, 500, 600, 700, 800, 900 y 1000. Las cuales pueden ser utilizadas para pruebas de PLN. Ademas consta de 4 archivos de audio en formato wav a 16kHz, los cuales son narraciones médicas, dichos audios tienen una duración de 15, 30, 45, 60, 75, 90, 105 y 120 segundos #Existen dos narrativas principales: una de 100 palabras y otra de 200 palabras. Estas narrativas sirven como base para la creación de los demás archivos de texto y de audio.
DOI: 10.5281/zenodo.8165085
title: Narrativas médicas en texto de 100 a 1000 palabras y en audio de 30, 60, 90 y 120 segundos

description: Consta de 10 narrativas médicas en texto de diferentes numero de palabras: 100, 200, 300, 400, 500, 600, 700, 800, 900 y 1000. Las cuales pueden ser utilizadas para pruebas de PLN. Ademas consta de 4 archivos de audio en formato wav a 16kHz, los cuales son narraciones médicas, dichos audios tienen una duración de 15, 30, 45, 60, 75, 90, 105 y 120 segundos #Existen dos narrativas principales: una de 100 palabras y otra de 200 palabras. Estas narrativas sirven como base para la creación de los demás archivos de texto y de audio.
DOI: 10.5281/zenodo.8364154
title: Narrativas médicas en texto de 100 a 1000 palabras y en audio de 30, 60, 90 y 120 segundos

description: Consta de 10 narrativas médicas en texto de diferentes numero de palabras: 100, 200, 300, 400, 500, 600, 700, 800, 900 y 1000. Las cuales pueden ser utilizadas para pruebas de PLN. Ademas consta de 4 archivos de audio en formato wav a 16kHz, los cuales son narraciones médicas, dichos audios tienen una duración de 15, 30, 45, 60, 75, 90, 105 y 120 segundos #Existen dos narrativas principales: una de 100 palabras y otra de 200 palabras. Estas narrativas sirven como base para la creación de los demás archivos de texto y de audio.
DOI: 10.21227/z189-h227
title: license plate

description: TANG FENG: IMAGE PROCESSING AND COMPUTER VISION.In the natural road traffic environment, license plate detection and localization is one of the key technologies for realizing intelligent transport systems. To solve the problem that traditional manual methods are affected by night fatigue, poor real-time, and other factors that lead to a high loss of license plate numbers, a license plate detection method using a target detection algorithm (YOU ONLY LOOK ONCE v4, YOLOv4) is proposed, and training and testing are carried out using a real collected dataset. The results show that the average recognition accuracy of the license plate recognition model is up to the level of human eye detection.
DOI: 10.26036/cnp0004715
title: Resequencing data of a RIL population of wax gourd

description: The sequencing data were used to construct high-density genetic map of wax gourd and QTL analysis of related traits. The 105 Inbred lines were subjected to 20X resequencing using the BGISEQ platform. The average Q30 was 90.64, and the GC content ranged from 35.32 to 37.19 %. The average alignment efficiency between the sample and the reference genome (GX-19) was 98.92 %, the average coverage depth was 26.65X, and the genome coverage was 98.73 % (at least one base coverage).
DOI: 10.5281/zenodo.8364130
title: Nature Communications 2020 Kopp et al JunD ChIP-seq SeqDatas

description: This record represents SeqData objects saved as Zarr files (https://github.com/ML4GLand/SeqData) derived from ENCODE consortium ChIP-seq experiments with the JunD transcription. This data was used in one of the use cases in the EUGENe publication (https://github.com/ML4GLand/EUGENe_paper), and includes objects used in various tutorials available in the ML4GLand GitHub organization. These files are primarily accessed via the SeqDatasets package (https://github.com/ML4GLand/SeqDatasets).
DOI: 10.5281/zenodo.8364129
title: Nature Communications 2020 Kopp et al JunD ChIP-seq SeqDatas

description: This record represents SeqData objects saved as Zarr files (https://github.com/ML4GLand/SeqData) derived from ENCODE consortium ChIP-seq experiments with the JunD transcription. This data was used in one of the use cases in the EUGENe publication (https://github.com/ML4GLand/EUGENe_paper), and includes objects used in various tutorials available in the ML4GLand GitHub organization. These files are primarily accessed via the SeqDatasets package (https://github.com/ML4GLand/SeqDatasets).
DOI: 10.5281/zenodo.8302398
title: MPRA_Model

description: MPRA_Model
DOI: 10.5281/zenodo.8302399
title: MPRA_Model

description: MPRA_Model
DOI: 10.5281/zenodo.8364195
title: MPRA_Model

description: MPRA_Model
DOI: 10.5281/zenodo.8364208
title: adipose_subcutaneous

description: small RNASeq dataset from GTEX adipose subcutaneous data.
DOI: 10.5281/zenodo.8364207
title: adipose_subcutaneous

description: small RNASeq dataset from GTEX adipose subcutaneous data.
DOI: 10.5281/zenodo.7533831
title: oemof-B3 Raw Data

description: <strong>Raw data for oemof-B3 v0.0.3</strong> In the new data set, changes occur in four files: capacities.csv green field assumptions are added for excess and shortage. costs_efficiencies.csv var_value formatting is fixed. Before: "{""variable_costs"": 1E-7}". After: {"variable_costs": 1E-7}. el_gas_constraint.csv The type specification for large and small boiler has been fixed var_value convention has been adapted with newer oemof.solph version. Before: "{""gas-heat_central-B"": 1}". After: {"custom_attributes": {"gas-heat_central-B": 1}}. emission_constraint.csv var_value convention has been adapted with newer oemof.solph version. Before:"{""emission_factor"": 119.71}". After: {"custom_attributes": {"emission_factor": 119.71}}. <strong>Raw data for oemof-B3 v0.0.2</strong> Raw data for the sector-integrated energy system model of Brandenburg and Berlin oemof-B3. This dataset has been compiled by the Reiner Lemoine Institute within the project "UMAS: Untertägige Methanisierung im Aquiferspeicher". Related publications and links: Documentation on methods and input data: "Biologische Methanisierung im Untergrundspeicher im Energiesystem mit hohem Anteil Erneuerbarer Energien" (German), link will follow Final report of UMAS: "Verbundthema: Untertägige Methanisierung im Aquiferspeicher" (German), link will follow Further information and contact: https://reiner-lemoine-institut.de/umas/ Documentation of the model on ReadTheDocs and github <strong>Licenses</strong> Different licenses apply to the components of the dataset. For details see the table in Metadata.csv.