cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7d86fhbf2r.1
title: Datasets for the publication "Cold Drops from Mid-Latitudes and Atmospheric Rivers from the tropics triggered the Middle East's Severe Dust Storms in Spring 2022"

description: Datasets for the publication “Cold Drops from Mid-Latitudes and Atmospheric Rivers from the tropics triggered the Middle East’s Severe Dust Storms in Spring 2022”
DOI: 10.17632/xsng4r5yhk.1
title: Flood Damage Inspection and Risk Indexing Data for an Inventory of Bridges in Central Greece

description: Inventory data for 117 bridges in Central Greece.
Flood hazard indexing and assessment of potential consequences for the transport network according to the flood risk analysis methodology documented by Loli M., Kefalas G., Dafis S., Mitoulis S.A., and Schmidt F. (2022). Flood Risk Indexing and Damage Inspection Dataset for an Inventory of Bridges in Central Greece. Science of the Total Environment. 
Damage inspection data after major flood that occurred in September 2020 involving 16/117 bridges and photos of the damaged bridges.
All the photos are taken by Marianna Loli.
DOI: 10.17632/mkw86dy3w9.1
title: Comparison of the performance of various estimated glomerular filtration rate equations with 24-hour urine creatinine clearance

description: GFR data of ESPECIAL study  (clinicaltrials.gov-No: NCT01552954)
DOI: 10.17632/v3342bpzkh.1
title: Dataresearch

description: SPSS data file
DOI: 10.17632/y4p5tsdhdn.1
title: FOREIGN LANGUAGE LEARNING THROUGH LISTENING COMPREHENSION AND READING COMPREHENSION

description: People acquire special kinds of knowledge over their lifetime experience and especially during their actual time of study. It is not enough to simply put in hard work and talent to learn a language; it is also necessary to do so in a way that is strictly consistent with human nature. There are two ways of learning a foreign language – effective and efficient (both meaning "capable of producing a result"). The difference between the meanings of both words is that when something is effective, it produces a result even if it takes more unnecessary resources to do so. When something is efficient, it not only produces a result, but it does so in a quick or simple way using as little material, time, effort, or energy as possible.   The methodology of foreign language learning in the present publication aims to propose the most efficient way of learning by engaging the learners in listening comprehension of live speech and, at a later stage, by reading comprehension, aiming to develop the understanding of the meaning of unfamiliar words from the context.
DOI: 10.17632/866rmhr3yz.1
title: InsectMeal

description: Effect of fish meal replacement with insect meal in meagre, Argyrosomus regius, juveniles’ diet
DOI: 10.17632/ncpyn2mfsd.3
title: Meta-Analysis of Hydrogen Therapy on ALI Animal Models  

description: A growing body of studies has shown that hydrogen therapy is an effective intervention to alleviate Acute Lung Injury (ALI) symptoms in animal models, but no research explores whether different interventions of molecular hydrogen have a discrepancy. Therefore， we used systematic review and meta-analysis to resolve this question through search electric databases of PubMed, EMBASE, Web of Science, and CNKI. 20 studies were selected from the search of 390 studies, and the random-effect model was used to evaluate the effect of Hydrogen therapy by indicators of W/D, PaO2, MDA, SOD, and TNF-α. The quality assessment of All included studies was reviewed by R language. The language differences were verified by SPSS 26.0.  Given that hydrogen therapy has different interventions, we used the subgroup analysis to verified that whether 2%H2 and Hydrogen saline have significant differences in the therapy of the animal ALI through STATA 14.0. The results verified that 2%H2 and Hydrogen saline have significant differences in the treatment of ALI animals. Besides, we also used meta-regression to explore the sources of high heterogeneity. Considering species differences, we used species as covariates to find heterogeneity between included studies.
DOI: 10.17632/w52hnygr5w.1
title: Replication files for Does a Currency Union Need a Capital Market Union?

description: Replication files for Does a Currency Union Need a Capital Market Union?, by Joseba Martinez, Thomas Philippon and Markus Sihvonen
DOI: 10.6073/pasta/3d6f721f29785f182a9df6280f8080ac
title: Annual heron counts on Chincoteague Island, Virginia 1992-2011

description: This dataset has the number of breeding pairs of herons nesting on Chincoteague, VA region.This data is also available from the Center for Conservation Biology at the College of William and Mary as part of the Virginia Coastal Avian Partnership (VCAP).
DOI: 10.17632/tdwg3fgbm4.1
title: LINF_310017600

description: amidohydrolase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/t9prmbmdfn.1
title: Queenless honeybee acoustic patterns

description:  The data set consists of acoustic patterns of five Carniola honeybee colonies located in Zacatecas, Mexico. The colonies were monitored from March to May 2018.  The beehives analyzed were two healthy queenright colonies with a huge population, two healthy colonies with moderate populations, and a queenless colony with a low population. Two queens were removed from two colonies to create the queenless condition. The acoustic pattern of healthy colonies is presented in Folder 1, and the experiment of queens removed in Folder 2. The hypothesis is that the queenless state of a beehive can be identified by comparing the acoustic pattern with the pattern of a healthy colony by using machine learning techniques and feature extraction methodologies. The data is presented with no previous preprocessing step, in the analysis Mel frequency cepstral coefficients were used for feature extraction, and the classification was carried out by using support vector machines, neural networks, and logistic regression, all of them with high classification rate.  The data can be analyzed by using singular value decomposition or principal component analysis to understand the cluster, and how they change when the queens were removed from the colonies.
DOI: 10.17632/3x7j6jtn42.1
title: LINF_310017400

description: GOLD domain-containing protein
Leishmania infantum (strain JPCM5)
DOI: 10.6073/pasta/2d3931cc1369c419c6b4ab6134aaf33f
title: Vegetation Survey on the Virginia Barrier Islands - Species by habitat, 1974

description: This dataset contains observations by Cheryl McCaffrey during a 1974 mapping of the vegetation on the barrier islands of the Virginia Coast Reserve (McCaffrey, CA, Dueser RD. 1990. Preliminary Vascular Flora for the Virginia Barrier Islands. Va. J. Sci.. 41:259-281. http://www.vacadsci.org/vjsArchives/V41/41-4A/p259.pdf) It also includes additional observations by Terry Cook on Hog Island in 1989. Note, because the primary purpose of this survey was mapping, species are listed if they were observed, but no extraordinary efforts were made to list all species on a particular island. Thus, an observation indicates that a species was there, but lack of an observation does not necessarily mean that the species was absent.
DOI: 10.17632/k6zdx6bc2k.1
title: LINF_310017300

description: CFAP300 family protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/z83bpjpfn5.1
title: LINF_310016800

description: biotin protein ligase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/fwz5t4482z.1
title: LINF_310016600

description: protein of unknown function - conserved
Leishmania infantum (strain JPCM5)
DOI: 10.17632/yfpb2tpj4r.1
title: Dataset on state-dependent Angular correlation GARCH model

description: This dataset contains precious metal futures including gold, platinum, and silver and energy futures including crude oil and fuel oil futures, and Shenzhen stock sector indices, including information technology, construction, manufacturing, consumer staples, transportation, wholesale & retail sectors. Data are Wednesday closing prices from 2010/4/21 to 2021/12/29 obtained from Datastream database. Gold and platinum futures are traded on the Chicago Mercantile Exchange, silver and West Texas Intermediate crude oil futures are traded on the New York Mercantile Exchange, and fuel oil futures is traded on the Shanghai International Energy Exchange.
DOI: 10.6073/pasta/1e87e2c1a0b298ca2dbd6f940a0dd8ca
title: Birdwood Mammal Trapping Data, Charlottesville, VA, 1974-1978

description: This data was collected by Ray Dueser, Bob Rose and their students (among them, Marcia Wilson, John Porter and Bill Ingoly). It is included in the VCR LTER database for comparative purposes. The data itself consists of trapping records for 10x10 trapping grids with 7.6m (25 foot) trap spacing. (note: grid 5 had an unusual geometry due to size constraints). Up to 4 captures of an individual may be recorded on each line of data. Trapping used modified Fitch live traps with a #10 tin can as the main chamber. Traps were baited with cracked corn or hen scratch and run for 3 sequential nights in each trapping session. In addition to the basic trapping data, there are additional files such as a fortran program for detecting inconsistencies in the data (KCHECK.FOR), a listing of known problems (ERRORLIS), a program for calculating Minimum Number Known Alive (MNAPROG.FOR) and a file containing minimum number alive (BIRDMNA.DAT) for each grid, week, sex and species combination.
DOI: 10.6084/m9.figshare.20363197.v2
title: Efficacy and safety of vutrisiran for patients with hereditary transthyretin-mediated amyloidosis with polyneuropathy: a randomized clinical trial

description: The study objective was to assess the effect of vutrisiran, an RNA interference therapeutic that reduces transthyretin (TTR) production, in patients with hereditary transthyretin (ATTRv) amyloidosis with polyneuropathy. HELIOS-A was a phase 3, global, open-label study comparing the efficacy and safety of vutrisiran with an external placebo group (APOLLO study). Patients were randomized 3:1 to subcutaneous vutrisiran 25 mg every 3 months (Q3M) or intravenous patisiran 0.3 mg/kg every 3 weeks (Q3W) for 18 months. HELIOS-A enrolled 164 patients (vutrisiran, <i>n</i> = 122; patisiran reference group, <i>n</i> = 42); external placebo, <i>n</i> = 77. Vutrisiran met the primary endpoint of change from baseline in modified Neuropathy Impairment Score +7 (mNIS+7) at 9 months (<i>p</i> = 3.54 × 10<sup>−12</sup>), and all secondary efficacy endpoints; significant improvements versus external placebo were observed in Norfolk Quality of Life-Diabetic Neuropathy, 10-meter walk test (both at 9 and 18 months), mNIS+7, modified body-mass index, and Rasch-built Overall Disability Scale (all at 18 months). TTR reduction with vutrisiran Q3M was non-inferior to within-study patisiran Q3W. Most adverse events were mild or moderate in severity, and consistent with ATTRv amyloidosis natural history. There were no drug-related discontinuations or deaths. Vutrisiran significantly improved multiple disease-relevant outcomes for ATTRv amyloidosis versus external placebo, with an acceptable safety profile. NCT03759379
DOI: 10.6073/pasta/086fda03bd91ce9c2331e3a6fdd9bcd1
title: Long Term Mammal Data from Powdermill Biological Station 1979-1999

description: This is a 20-year record of small mammal trapping from the Powdermill Biological Station, Rector, PA 15677 collected by Joseph F. Merritt. It is included here as a comparative source of small mammal data.
DOI: 10.17632/g8tmby7psz.2
title: Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests. Frank et al

description: Each antibody dataset is related to a specific reference dataset. Below are samples grouped with their specific reference datasets.

Sample ID	Sample Info
211116_3	N_Library4_Reference_01
211116_4	N_Library5_Reference_01
211116_5	N_Lib4_R040
211116_6	N_Lib5_R040
	
211215_1	N_Library5_Reference_02
211215_2	N05_R040
211215_3	N05_MM05
211215_6	N05_MM08
211215_7	N05_NAb3
	
220104_06	N_Lib05_Reference_03
220104_07	N05_C518
220104_08	N05_C524
220104_09	N05_C706
220104_12	N05_2F4
220104_13	N05_3C3
	
220215_29	N05_Reference_04
220215_02	N05_RC17602
220215_04	N05_RC17604
220215_06	N05_R004
220215_14	N05_1C1
220215_16	N05_1A7
220215_22	N05_mAb1
220215_24	N05_mAb2
	
220225_03	N05_Reference_05
220225_07	Ab166
DOI: 10.17632/rr4gc6mybg.1
title: Research data for the manuscript: Pupil dynamics-derived sleep stage classification of a head-fixed mouse using a recurrent neural network

description: Sample datasets for estimating vigilance states from pupil dynamics using LSTM, a deep learning model.
DOI: 10.17632/crzf7hvvj9.1
title: Data for Sweet Corrosion Scale: Structure and Energetics of Siderite Facets

description: SEM image, EBSD data (including pole figures) and confocal microscope data used to confirm the identity of crystallographic orientation of facets of FeCO3 crystallites. These uploaded data are described/discussed in detail in a manuscript  entitled 'Sweet Corrosion Scale: Structure and Energetics of Siderite Facets', which is currently being considered for publication; the data are presented in Figure 4 of the manuscript.
DOI: 10.17632/j329rc9336.1
title: Conservation Tillage Effects on European Crop Yields: A Metadata Analysis

description: We were hypothesizing that ridge-till and strip-till can improve crop yields under European agroecosystems in contrast with the often observed reduction in yields under No Tillage and Reduced Tillage.To answer the hypothesized question, and based on our data, it can be stated that yields are indeed not optimal under no till as opposed to RT and ST where yields are higher than those of conventional tillage. 
The raw data shows every parameter and data extracted from peer reviewed articles while the analyzed shows the data obtained from running the meta-analysis by fitting random and mixed effect models.

Raw data
Here, the data consists of all parameters and variables extracted from the peer-reviewed articles that met the inclusion criteria. Also, there is a metadata sheet with all abbreviations and their meaning. 


Analyze data
Here, the estimate, lower (ci.lb) and upper (ci.ub) confidence intervals are in log transform format. Thus, taking the exponent gives the response ratio. Se =standard error, zval= z correlation, pval =p value, RT (ridge-till) and RH (number) = ridge height. C =Cotton, Cr = Carrot, RD = Dandellion, T=Tulips, GM= grain maize, WC= winter cereal, SB =sugar beet, SC=spring cereal, P =potato. Also, there is a metadata sheet with all abbreviations and their meaning. 

Graph
Fig. 1. Forest plot showing data plot of estimated average response ratios (RR) for No (NT), Ridge (RT) and Strip (ST) tillage based on random effects model. n is sample size/number of studies for the specific tillage type. The error bars represent the 95% confidence intervals CI. The square shapes represent the estimated RR and their size correspond to their weight (based on its sample size). The vertical broken line represents the line of no effect
DOI: 10.17632/ykrt7cpdxj.1
title: CISA

description: Model output used for the paper "Climate Implications of the Sun transition to higher activity mode"

We used SOCOL3-MPIOM model with an interactive ocean (Stenke et al., 2013; Muthers et al., 2014), which allows the evaluation of possible implications of the Sun activity switch for the terrestrial climate and ozone layer. It is based on the general circulation model ECHAM5.4 (Roeckner et al., 2003) interacting with the chemistry module MEZON (Egorova et al., 2003; Rozanov et al., 1999) and the MPIOM (Jungclaus et al., 2006; Marsland et al., 2003) for the treatment of the ocean dynamics. We executed our two 90-year-long experiments using T31 truncation providing 3.75x3.75 horizontal resolution and 39 levels in vertical direction covering the atmosphere from the ground to the mesopause at 0.01 hPa (~ 80 km altitude). Both experiments were initialized from a very long time slice spin-up run performed using preindustrial set-ups for all forcings. In the reference run, we prescribed monthly SSI for the year 2000 (solar activity maximum). In the second (experiment) run, we applied monthly SSI for the Sun in transition to a very active state.

Reference run: files are marked by p100m100
Experiment run: files are marked by p100m101
DOI: 10.6084/m9.figshare.17304137.v1
title: Facial_expression_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains the data of all the facial expression per participant. The sub-folders are named after the participant ID and include 4 sub-sub folders which are central RGB (CRGB) facial expression data, left RGB (LRGB) facial expression data, right RGB (RRGB) facial expression data, and central infrared (CIR) facial expression data. Each folder contains multiple MP4 ﬁles, and each MP4 ﬁle corresponds to valid emotional driving.
DOI: 10.6084/m9.figshare.17304137
title: Facial_expression_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains the data of all the facial expression per participant. The sub-folders are named after the participant ID and include 4 sub-sub folders which are central RGB (CRGB) facial expression data, left RGB (LRGB) facial expression data, right RGB (RRGB) facial expression data, and central infrared (CIR) facial expression data. Each folder contains multiple MP4 ﬁles, and each MP4 ﬁle corresponds to valid emotional driving.
DOI: 10.6084/m9.figshare.17304227
title: Road_scenario_data

description: This directory is divided into 40 sub-folders, each of which contains the data of driving road scenario per participant. These sub-folders were named after the participant ID and include multiple MP4 ﬁles. Each MP4 ﬁles ﬁle corresponds to valid emotional driving.
DOI: 10.6084/m9.figshare.17304227.v1
title: Road_scenario_data

description: This directory is divided into 40 sub-folders, each of which contains the data of driving road scenario per participant. These sub-folders were named after the participant ID and include multiple MP4 ﬁles. Each MP4 ﬁles ﬁle corresponds to valid emotional driving.
DOI: 10.6084/m9.figshare.19728946
title: Driving_behavioural_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains all the driving behavioural data (DBD) of one participant. These sub-folders were named after the participant ID and include multiple CSV files. Each CSV file corresponds to valid emotional driving. Each row contains the driving behavioural data at an instantaneous measurement and is organized according to rec-time, UTC, acceleration, lateral-acceleration, gas-pedal-position, brake-pedal-force, gear, steering-wheel position, velocity, lateral-velocity, x-position, y-position, z-position. The organization of content in each row is shown in the Table 9.
DOI: 10.6084/m9.figshare.19728946.v1
title: Driving_behavioural_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains all the driving behavioural data (DBD) of one participant. These sub-folders were named after the participant ID and include multiple CSV files. Each CSV file corresponds to valid emotional driving. Each row contains the driving behavioural data at an instantaneous measurement and is organized according to rec-time, UTC, acceleration, lateral-acceleration, gas-pedal-position, brake-pedal-force, gear, steering-wheel position, velocity, lateral-velocity, x-position, y-position, z-position. The organization of content in each row is shown in the Table 9.
DOI: 10.6084/m9.figshare.19728919
title: Body_gesture_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains the data of body gesture per participant. These sub-folders were named after the participant ID and include multiple MP4 files. Each MP4 files file corresponds to valid emotional driving. The body gesture data of a participant’s emotional driving record is shown in the Fig.5.
DOI: 10.6084/m9.figshare.19728949
title: Physiological_data

description: 40 sub-folders are further divided in this directory, each sub-folder contains the data of all the EEG signal per participant. These sub-folders were named after the participant ID and include multiple CSV files. Each CSV file corresponds to valid emotional driving. Each row contains the EEG data at an instantaneous measurement and is organized according to rec-time, UTC, 32 channels EEG data, α, β, γ, δ, θ frequency bands data for each channel. The organization of content in each row is shown in the Table 8. Besides, the EEG montage description file is contained in the directory. The TXT file described the channels’ information created to display activity over the entire head and to provide lateralizing and localizing information, which will help the understanding and analysis of EEG data.
DOI: 10.6084/m9.figshare.19728958
title: Scripts

description: The preprocessing and main analysis codes (Python scripts) are summarized in this directory. All results in the technical verification section can be copied using these scripts. For more details, please read the instructions in the README.md file.
DOI: 10.6084/m9.figshare.19728952
title: Psychological_data

description: This directory contains the data of participant biographic, self-reported emotion labels and personality traits as three .xlsx files. BIO.XLSX. Each row contains the biographical data of a participant, organized by participant ID, gender (1=male, 2=female), age and driving age. Emotion label.XLSX. Each row contains the self-reported data of a participant’s experienced emotions, organized according to participant ID, valence, arousal, dominance, category, and intensity. The SAM scale was used to measure valence, arousal, and dominance, the DES scale was used to measure category and intensity. The organization of content in each row is shown in the Table 10. EPQ.XLSX. Each row contains the Eysenck personality questionnaire data of a participant, organized according to participant ID, P-score, E-score, N-score, L-score, Where P reflects psychoticism/socialisation, E is extraversion/introversion, N means neuroticism/stability, and L is lie/social desirability.
DOI: 10.6084/m9.figshare.19728958.v1
title: Scripts

description: The preprocessing and main analysis codes (Python scripts) are summarized in this directory. All results in the technical verification section can be copied using these scripts. For more details, please read the instructions in the README.md file.
DOI: 10.6084/m9.figshare.19728961.v1
title: Selected_stimulus_clips

description: This directory contains one sub-folder of selected video-audio clips and one clip raw links .xlsx file. Selected video-audio clips. This sub-folder contains seven selected video-audio clips for driver emotion induction. The target emotions corresponding to the seven clips are anger, sadness, disgust, fear, happiness, neutral and surprise. Selected video-audio clips raw links.XLSX. Each row contains the selected video-audio clips raw link of a target emotion, organized by target emotion and raw link.
DOI: 10.6084/m9.figshare.19728961
title: Selected_stimulus_clips

description: This directory contains one sub-folder of selected video-audio clips and one clip raw links .xlsx file. Selected video-audio clips. This sub-folder contains seven selected video-audio clips for driver emotion induction. The target emotions corresponding to the seven clips are anger, sadness, disgust, fear, happiness, neutral and surprise. Selected video-audio clips raw links.XLSX. Each row contains the selected video-audio clips raw link of a target emotion, organized by target emotion and raw link.
DOI: 10.6084/m9.figshare.20440359
title: Supplementary_data.zip

description: Supplementary_data
DOI: 10.6084/m9.figshare.20427786
title: Dataset "Do microplastics and climate change negatively affect shredder invertebrates from an Amazon stream? An ecosystem functioning perspective"

description: Database refers to leaf decomposition and survival of Amazon stream shredders. Able to be updated later.