cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/d7sx7bf2hk
title: Experimental raw data of B7 and B10

description: The spectra of B7 (DE5) and B10 (D0) was acquired using FTIR spectrometer. By analyzing a broad infrared spectrum (6000-80 cm-1) encompassing near-infrared (NIR), mid-infrared (MIR), and far-infrared (FIR) regions, the characteristic vibrational signatures of these samples were investigated. Utilizing a Bruker Invenio-R spectrometer equipped with an attenuated total reflection (ATR) (2mm) diamond accessory, high-resolution spectra with an accumulation of 64 scans, at a spectral resolution of 4 cm-1 are acquired and processed using OPUS 8.7.41 software. This research demonstrates the significant potential of FTIR spectroscopy as a robust tool for characterizing local biodiesel fuels, providing valuable insights into their unique chemical makeup and properties.
No. Product Brand Lot number 
1 INFINITI DIESEL BHPetrol DE5_BP1_433
2 BIO EURO 5 BIO DIESEL BHPetrol D0_BP1_433
3 BIODIESEL B10 EURO 5 Petronas D0_PS1_433
4 EURO5 B7 POWERD W TECHROND/BULK Caltex DE5_CX1_433
5 EURO5 B10 DIESEL W TECHROND/BULK Caltex D0_CX1_433
6 TURBO DIESEL E5 Petron (PMRMB) DE5_PN1_433
7 DIESEL MAX B10 Petron (PMRMB) D0_PN1_433
8 DIESEL MAX B10 Petron (PFISB) D0_PN2_433
9 SHELL FUELSAVE DIESEL EURO 5 B10 MAINGRADE BULK Shell D0_SL1_433
10 SHELL FUELSAVE DIESEL EURO 5 B10 MAINGRADE BULK Shell D0_SL2_433
11 TURBO DIESEL E5 Petron (PMRMB) DE5_PN3_433
12 DIESEL MAX B10 Petron (PMRMB) D0_PN3_433
13 BIODIESEL B10 EURO 5 Petronas D0_PS2_433
14 BIODIESEL B10 EURO 5 Petronas D0_PS3_433
15 BIODIESEL B7 EURO5 PREMIUM Petronas DE5_PS3_433
16 SHELL FUELSAVE DIESEL EURO 5 B10 BULK Shell D0_SL3_433
17 SHELL FUELSAVE DIESEL EURO 5 B7 BULK Shell DE5_SL3_433
18 DIESEL MAX B10 Petron (PMRMB) D0_PN4_433
19 BIODIESEL B7 EURO5 PREMIUM Petronas DE5_PS4_433
20 BIODIESEL B10 EURO 5 Petronas D0_PS4_433
21 EURO5 B10 DIESEL W TECHROND/BULK Caltex D0_CX2_433
22 DIESEL MAX B10 Petron D0_PN5_868
23 B10 EURO 5 BIO DIESEL BHPetrol D0_BP2_868
24 TURBO DIESEL E5 Petron DE5_PN6_868
25 DIESEL MAX B10 Petron D0_PN6_868
26 BIODIESEL B10 EURO 5 Petronas D0_PS5_868
27 BIODIESEL B7 EURO5 PREMIUM Petronas DE5_PS5_868
28 EURO5 B10 DIESEL WTECHROND/BULK Caltex D0_CX3_868
29 B7 EURO 5 BIO DIESEL BHPetrol DE5_BP3_868
30 B10 EURO 5 BIO DIESEL BHPetrol D0_BP3_868
DOI: 10.17632/wrmnj7n57d
title: Tumour Infiltrating Lymphocytes in Follicular Lymphoma - additional data 2

description: Part 2/10 Description provided in the dataset linked below.
DOI: 10.6084/m9.figshare.28787594.v2
title: DATASET AI

description: This dataset contains clinical, biological, and electrocardiographic parameters collected from adult patients diagnosed with ST-elevation myocardial infarction (STEMI), with the goal of supporting early prediction of cardiogenic shock (CS) during initial phases of care. The data were retrospectively collected from a single tertiary care center and include patients evaluated between the prehospital stage and cardiology-on-call consultation.The dataset is organized into three distinct phases of early care:<b>Prehospital phase</b> – includes variables recorded by emergency medical services (EMS) prior to hospital arrival.<b>Emergency department (ED) phase</b> – contains vital signs, initial labs, and ECG features available at ED presentation.<b>Cardiology-on-call phase</b> – reflects clinical reassessment prior to urgent coronary angiography.Key variables include Killip class, heart rate, systolic blood pressure, ECG rhythm abnormalities, creatinine, potassium, and other laboratory indicators of renal or hemodynamic dysfunction. These parameters were selected for their routine availability and clinical relevance in STEMI management.The primary aim of this dataset is to enable the development and validation of machine learning models for:Early identification of STEMI patients at high risk of developing cardiogenic shock;Clinical triage optimization and prioritization for urgent angiography;Supporting time-sensitive decision-making in resource-limited or overcrowded emergency settings.The dataset includes model-ready variables suitable for classification tasks and has been used to train and evaluate algorithms such as Extra Trees, Support Vector Machines (SVM), Random Forest, and Quadratic Discriminant Analysis (QDA). Performance metrics include accuracy, precision, recall, F1-score, and Matthews Correlation Coefficient (MCC).All data have been de-identified and processed in accordance with institutional ethical standards.
DOI: 10.11583/dtu.19222434.v1
title: Complementary data for Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant

description: Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk), ORCID: https://orcid.org/0000-0001-5664-9421 <br> -------------------------------------------------------------------------------<br> <br> The paper related to this dataset is currently In Press. <br> Title: Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant Submmited: Feb 2022 Accepted: May 2022 Published: ------------------------------------------------------------------------------- The folder contains the data implemented in the study cases of the related paper.
DOI: 10.6084/m9.figshare.10278089.v2
title: data.zip

description: All the data used in the paper is included here. See the readme.txt file after unzip the file<br><br>The streamflow data is missing from the previous version, so upload that on Sep 12, 2020<br><br>
DOI: 10.6084/m9.figshare.12994289.v1
title: soil_chemical_data.csv

description: Soil chemical data. Soils were field-collected from natural habitats. Soil data in this file include: pH, EC, NH4-N, NO3-N, MBC, MBP, P(tot), P(org), P(in), P(aicd), P(Fe/Al), P(Ca) and P(occ). This soil_chemical_data.csv file was created using Microsoft Excel 2013.<br>
DOI: 10.6084/m9.figshare.26131978.v3
title: <b>Annotated </b><b>interictal epileptiform discharges in </b><b>intracranial EEG (iEEG) sleep data</b>

description: This dataset comprises multichannel intracranial EEG (iEEG) recordings from epilepsy patients during overnight sleep, collected at two medical centers. The data consists of 852 interictal epileptiform discharges from 25 patients annotated by expert neurologists, mostly from medial temporal lobe regions.Detailed description published here (if you use this data, please cite):<br>Falach R, Geva-Sagiv M, Eliashiv D, Goldstein L, Budin O, Gurevitch G, Morris G, Strauss I, Globerson A, Fahoum F, Fried I, Nir Y. Annotated interictal discharges in intracranial EEG sleep data and related machine learning detection scheme. Sci Data. 2024 Dec 18;11(1):1354. doi: 10.1038/s41597-024-04187-y.
DOI: 10.6084/m9.figshare.27024196.v1
title: Azobenzene training set for MS-ANI, json file compatible with MLAtom.

description: Training set for the MS-ANI model predicting azobenzene NAMD.
DOI: 10.6084/m9.figshare.28423709.v1
title: RawData_Gutu_et_al_Time_Matters

description: The circadian clock plays a pivotal role in regulating various aspects of cancer, influencing tumor growth and treatment responses. There are significant changes in drug efficacy and adverse effects when drugs are administered at different times of the day, underscoring the importance of considering the time of day in treatments. Despite these well-established findings, chronotherapy approaches in drug treatment have yet to fully integrate into clinical practice, largely due to the stringent clinical requirements for proving efficacy and safety, alongside the need for deeper mechanistic insights. In this study, we employ a combined mathematical and experimental approach to systematically investigate the factors influencing time-of-day drug sensitivity in human cells. Here we show how circadian and drug properties independently shape time-of-day profiles, providing valuable insights into the temporal dynamics of treatment responses. Understanding how drug efficacy fluctuates throughout the day holds immense potential for the development of personalized treatment strategies aligned with an individual's internal biological clock, revolutionizing cancer treatment by maximizing therapeutic benefits. Moreover, our framework offers a promising avenue for refining future drug screening efforts, paving the way for more effective and targeted therapies across diverse tissue types.
DOI: 10.17632/9s54cy253d
title: Focal mechanism catalog for Southern California

description: 1 year
2 month
3 day
4 hour
5 minute
6 second
7 event ID
8 latitude
9 longitude
10 depth
11 magnitude
12 strike
13 dip
14 rake
15 1st nodal plane uncertainty
16 2nd nodal plane uncertainty
17 number of polarities
18 polarity misfit
19 number of S/P amplitude ratio
20 average log10(S/P) amplitude ratio misfit
21 focal mechanism quality
22 probability of solution close to real solution
23 azimuth gap
24 take-off angle gap
25 polarity misfit
26 station distribution ratio (STDR)
DOI: 10.6084/m9.figshare.14892492.v2
title: Online materials for 'Novel rock image classification: The proposal and implementation of HKUDES_Net'

description: Online materials for 'Novel rock image classification: The proposal and implementation of HKUDES_Net'
DOI: 10.17632/7k9sg622g7
title: Dataset of "A Meta-analysis on the Success of Resin Composite Restorations Since 2010"

description: This dataset consists of data extracted from the following studies: 

1.	Rocha A, Salas MS, Masotti A, da Rosa W, Zanchi C, Lund R. A Randomized Double-blind Clinical Trial of Dentin Surface Treatments for Composite Restorations in Noncarious Cervical Lesions: A 36-month Evaluation. Operative dentistry. 2019;44(2):114-26.
2.	Dilsad OF, Ergin E, Attar N, Gurgan S. Comparison of laser-and bur-prepared class I cavities restored with two different low-shrinkage composite resins: a randomized, controlled 60-month clinical trial. Clinical oral investigations. 2020;24(1):357-68.
3.	Gurgan S, Vural UK, Kutuk ZB, Cakir FY. Does a new formula have an input in the clinical success of posterior composite restorations? A chat study. Clinical oral investigations. 2021;25(4):1715-27.
4.	Loguercio A, Rezende M, Gutierrez M, Costa T, Armas-Vega A, Reis A. Randomized 36-month follow-up of posterior bulk-filled resin composite restorations. Journal of dentistry. 2019;85:93-102.
5.	Kitasako Y, Sadr A, Burrow M, Tagami J. Thirty‐six month clinical evaluation of a highly filled flowable composite for direct posterior restorations. Australian dental journal. 2016;61(3):366-73.
6.	Celik EU, Tunac AT, Yilmaz F. Three-year clinical evaluation of high-viscosity glass ionomer restorations in non-carious cervical lesions: a randomised controlled split-mouth clinical trial. Clinical oral investigations. 2019;23(3):1473-80.
7.	Cieplik F, Scholz KJ, Tabenski I, May S, Hiller K-A, Schmalz G, et al. Flowable composites for restoration of non-carious cervical lesions: Results after five years. Dental materials. 2017;33(12):428-37.
8.	Favetti M, Schroeder T, Montagner AF, Correa MB, Pereira-Cenci T, Cenci MS. Effectiveness of pre-treatment with chlorhexidine in restoration retention: a 36-month follow-up randomized clinical trial. Journal of dentistry. 2017;60:44-9.
DOI: 10.25385/zuyd.7857200.v6
title: Interprofessioneel Opleiden en Samenwerken (IPOS)

description: Om onze toekomstige zorgprofessionals optimaal te laten functioneren in een sterk veranderende gezondheidszorg, is het noodzakelijk om hen hierop voor te bereiden. Daarom is interprofessioneel opleiden broodnodig. Zorgprofessionals moeten goed in staat zijn om adequaat met elkaar samen te werken in dienst van een optimale zorgverlening voor de cliënt. De cliënt met zijn of haar hulpvraag dient in het zorgproces centraal te staan en niet de professional. Daarom gaat de faculteit Gezondheidszorg, in samenwerking met het Lectoraat Autonomie en Participatie van chronisch zieken, de uitdaging aan om al haar studenten interprofessioneel op te leiden. Het gaat om de bachelor opleidingen ergotherapie, fysiotherapie, logopedie, creatieve therapie, verpleegkunde, verloskunde en biometrie. Ook is samenwerking gezocht met andere faculteiten zoals Social Studies. Naast hun opleidingsspecifieke competenties verwerven de Zuyd-studenten ook interprofessionele competenties. Bij interprofessioneel opleiden leren (toekomstige) professionals over, van en met elkaar. De Wereld Gezondheidsorganisatie (2010) definieert dit als volgt: ‘Interprofessional education occurs when two or more professionals learn about, from, and with each other to enable collaboration and improve health outcomes.’
DOI: 10.6084/m9.figshare.16413405.v4
title: Metadata for: DarkCideS 1.0, a global database for bats in karsts and caves

description: This database contains 4 major datasets<br><br>1. The first dataset contains taxonomic checklists for all extant cave-dwelling bats species extracted from the expert-based International Union for the Conservation Union (IUCN) Red List database version 2020.1. It also contains the General metadata for traits included in the current version of the database: habitat preference, ecological status, feeding groups, geographical range, island endemism, geopolitical endemism, distribution range, biogeographical breadth, generation length, body mass, and threatening process.2. The second dataset contains the bat cave geographical location (latitude/longitude) and recorded species.3. The third dataset included in the database contains the measured land-use and landscape features of the cave surroundings using the georeferenced data from the second dataset. Reference for individual entries in Dataset 3 are included in Dataset 2.4. The fourth dataset lists the parasitic bat flies and their Laboulbeniales fungal hyperparasites associated with cave bats.
DOI: 10.6084/m9.figshare.19769560.v1
title: SA3 area population projections by age & sex

description: This dataset contains population projections by sex and age group for SA3 areas of Australia (excluding a few areas with very small populations) for a 15 year projection horizon. The data are presented in both Excel and csv formats. <br>
DOI: 10.6084/m9.figshare.19860076.v2
title: Sakamoto_et_al_Genetic parent-offspring relationships predict sexual differences in the contributions to parental care in the Tree Sparrow

description: The dataset was intended for the reproducible data analysis for the manuscript entitled "Genetic parent-offspring relationships predict sexual differences in the contributions to parental care in the Tree Sparrow". The dataset includes original (or semi-original with modification to include results outside the R platform) tidy data and R codes. The tidy data includes four different dataset, <br> 1) genotype_data.csv 2) individual_data.csv 3) nest_data.csv 4) nest_data_withCOLONY.csv. <br> The R codes include two different codes called, <br> 1) dataanalysis.R 2) dataprep.R. <br> The two codes include "README" for the easier understanding of what the scripts do for the data. Specifically, these codes can.. <br> 1) Generate input datasets to conduct COLONY (genetic parantage analysis) 2) Summarize the COLONY results to interpret genetic parantage of offspring 3) Calculate stats descripted in the manuscript 4) Conduct modelling (GLMs) using the raw data and results provided by COLONY (that were integrated with the raw data in the dataset "nest_data_withCOLONY.csv". <br>
DOI: 10.6084/m9.figshare.5695801.v1
title: Energy management: a synthesis of scientific publications on biodigestion for waste management

description: Abstract Environmentally friendly options for waste disposal and the need for expansion and diversification of the national and international energy matrix are relevant issues today. One technique that supports these goals is anaerobic biodigestion, which generates clean energy from biomass. Accordingly, our goal was to perform a quantitative and qualitative assessment of scientific publications on biodigestion in order to understand the evolution of the technique, which is essential for environmental and economic sustainability. Ninety-nine articles indexed in the Scientific Electronic Library Online between 1980 and 2015 were evaluated. The results showed a significant increase in scientific publications since 2000 which addressed, in addition to environmentally friendly waste management, the energy issue, with the use of biogas. This increase in the number of publications coincides with increased awareness on natural resource management and concern about global energy management. Most of the articles involved a general evaluation of the process, using mainly animal waste from pigs, and emphasizing biodigestion as waste management, since pig farming produces a large volume of waste and has a high environmental impact.
DOI: 10.17632/bydzxvx9h2
title: Plankton dataset of Nuevo Gulf, northern Patagonia, Argentina

description: Here, we present a plankton dataset from northern Patagonia, Argentina, aimed at studying the ecological aspects of plankton and its relationships with environmental variables. Sampling was conducted between 2019 and 2021 during the spring and summer months at various locations in the Nuevo Gulf (42°42′S; 64°30′W), covering the heterogeneity of environmental and physical variables such as temperature, depth, chlorophyll a, and nutrients. The provided file includes three sheets: the first contains metadata for the sampling dates and station locations; the second presents the zooplankton dataset (&gt;300 µm), with abundance data (ind/m³) at the lowest possible taxonomic level; and the third details phytoplankton concentration (cells/L) for the same sampling period. This dataset represents the most recent data available for the region, including the first recorded observation of a copepod species, *Drepanopus forcipatus*, and a detailed taxonomy of the jellyfish group within the Gulf. Additionally, this dataset expands the spatial coverage compared to previous studies.
DOI: 10.17632/dygfmkkfpt
title: Data for: Damage Detection Using SAR Coherence Statistical Analysis, Application to Beirut, Lebanon.

description: Damaged regions of Beirut, Lobanon as a result from the industrial explosion on August 4th 2020
DOI: 10.6084/m9.figshare.1570181.v1
title: Data from Painting et al. 2015 Multiple exaggerated weapon morphs: a novel form of polymorphism in harvestmen

description: This is an excel spreadsheet with all the measurement data from the individual male <em>Pantopsalis cheliferoides </em>harvestmen used in the current study published in Scientific Reports, available at http://dx.doi.org/10.1038/srep16368
DOI: 10.17632/jyw3t5z93j
title: Multi-resolution T1w Brain MRI simulated data

description: This simulated data is based on the patient-specific brain phantoms that are generated by utilizing high resolution real subject 3D brain MRI data and performing automatic segmentations for all brain tissues. The brain MRI imaging dataset is obtained from the HCP healthy young adult sample. We selected two hundred unprocessed structural T1w brain MRI scans for phantom generation. The phantoms are created by applying the Philips proprietary automated complete brain segmentation tool on HR T1w structural MRI data. 

Tissue parameters including longitudinal relaxation time (T1), transverse relaxation time (T2) and proton density (PD) are assigned to each tissue in each phantom. These parameters are collected from literature and random samples are taken from the bounded Gaussian bell distribution of given mean and standard deviation for each
tissue relaxation times.

MRI data is simulated for T1w brain MRI using our Matlab-based simulation framework. Using the phantoms as input, MRI data is simulated at two different resolutions for voxel aligned paired data, i.e. HR and LR of 0.7𝑚𝑚 and 1𝑚𝑚 respectively in both phase encoding directions. A fixed slice thickness of 1𝑚𝑚 (axial) is used for both HR and LR data. To have HR-LR paired data aligned on voxel level, zero padding in k-space is performed for LR data, i.e. the size of the LR k-space is made equal to the size of the HR k-space and then Fourier reconstructions are performed. The resulting size of simulated data is 320x320x179 for both HR and LR MRI. Ernst angle solution for a gradient echo (GRE) sequence with fixed sequence parameters of TR 18𝑚𝑠, TE 10𝑚𝑠 and FA of 30◦ is used to simulate all pairs of data. The T1w intensities are computed for each voxel. A complex Gaussian noise (standard deviation 0.4) is generated, which is derived from the simulated WM (intensity range 0−4095) in the MRI volume. The generated complex Gaussian noise is added to the real and imaginary part of the k-space data before FFT reconstructions.

It is essential to emphasize that our simulation process intentionally did not introduce any MR imaging artifacts.

The folder structure of the paired HR-LR database is as follow:
1. HR (contains 200 T1w brain MRI simulated images in Nifti format at in-plane resolution of 0.7x0.7𝑚𝑚 with slice thickness of 1𝑚𝑚)
2. LR (contains 200 T1w brain MRI simulated images in Nifti format at in-plane resolution of 1x1𝑚𝑚 with slice thickness of 1𝑚𝑚)
3. Figures (the resulting figures of brain MRI SR in png format for the associated article "Effective deep-learning brain MRI super resolution using simulated training data")
DOI: 10.6084/m9.figshare.1342592.v3
title: Perceptual decision making EEG - subject 1

description: Participants decided on the direction of randomly moving dots. The events.mat file contains information about the behavior, while the other datafiles are the EEG time series, separately for each channel. See also the dataset containing the matlab scripts. Due to the size of the data, every subject becomes a new dataset. Belongs to http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090943#pone-0090943-g005
DOI: 10.6084/m9.figshare.19130645.v1
title: EV charging model

description: Software and dataset used to synthesise residential EV charging schedules.
DOI: 10.6084/m9.figshare.21640568.v1
title: Machine learning datasets

description: Machine learning datasets
DOI: 10.6084/m9.figshare.27965547.v1
title: <b>RSCWPBMMA_data</b>

description: Magnetic Model and magnetic anomaly generated and assembled in this study.
DOI: 10.17632/2t8y5f54pz
title: 3D scanning data for pyramid sample 

description: Point cloud data for EBM process printing surfaces. It has surface roughness and melt pool size change depending on the printing area due to heat accumulation. This data set is scanned by a customized ultra-high spatial resolution structured light scanner (5um).
DOI: 10.17632/6k7x7twz48
title: Vitamin D deficiency serves as a precursor to stunted growth and central adiposity_Knuth et. al.
DOI: 10.17632/ggk9yhc5vc
title: Microplastics on Mt. Everest (Napper et al., 2020)

description: 1) Microplastic sample information. Table includes MP collection date, sample location information, and number of MPs per sample. 2) Details of microplastics found. Table includes the characteristics of all collected MP, including their color, type, length, width, and polymer.
DOI: 10.6084/m9.figshare.12598622.v1
title: Fiber photometry of dopamine neurons during mouse auditory fear conditioning and extinction

description: This data is published in the paper: <br>Distinct signals in medial and lateral VTA dopamine neurons modulate fear extinction at different timesCai et al., eLife 2020<br>https://elifesciences.org/articles/54936<br><br>For the code that analyzes this data, and to reproduce figures seen in the paper, go to GitHub: https://github.com/neurocaience/DopamineAndFear<br><br>