cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14730690.v2
title: Capture-mark-recapture data on the strictly protected Speleomantes italicus

description: The dataset collects ecological and morphological information on <i>Speleomantes i</i><i>talicus</i> from both epigean and subterranean environments. The dataset contains information on: snout-vent length, total length, weight and stomach contents of each captured salamander. Salamanders' identity was coded to identify recapture individuals; individuals recognition was performed observing their dorsal pattern and using Visual Implant Elastomers.<br>The dataset includes: ID (the salamander’s database code), Site (“Cave” or “Forest”), Latitude and longitude (low resolution coordinates of the site), Population (the population code), Region and Province (the relevant information for each site), Month and Year (the period in which the salamander was captured), Season (Winter, Spring, Summer, Autumn), Species (the species to which the individual belongs), ID_sampling_period (the ID of sampling primary periods), Tag (the unique code identifying each individual), Sex (male (M), female (F), juvenile (J)), Eggs (indicates whether eggs where visible from the salamander’s belly (yes/no)), SVL (estimated snout-vent length (mm)), TL (estimated total length (mm)),Weight (indicates the salamander’s weight (g)), Condition (indicates if stomach was empty (1) or not (0)), Not_identifiable (Indicates whether stomach contents were identifiable (0) or not (1) at the order level), Prey typology (for each prey typology the total number of recognized items is reported). NA means not available information.<br>
DOI: 10.6084/m9.figshare.20083916.v1
title: Bee communities net collected from California watermelon crop flowers

description: Wild bee communities were sampled at watermelon (<em>Citrullus lanatus, </em>cultivars Crimson Sweet and Yellow Baby) farms in the western USA. We netted all bees visiting crop flowers within a predefined 50- to 200-m2 transect. Netting was repeated in four ten-minute periods each sampling day. Specimens were identified to species using published taxonomic keys and assistance by expert taxonomists. <br> Data collection methods are further described in Lemanski et al, 2022, Greater bee diversity is needed to maintain crop pollination over time, Nature Ecology and Evolution. <br> Both files contain the same data, but the file "ca_wat_visits_corr.csv" is formatted for the main analysis in the manuscript, while the file "3years_wbees_oncrop.csv" is formatted for use in a null model analysis.
DOI: 10.6084/m9.figshare.27229272.v1
title: GapMind 2024

description: GapMind is an automated web-based tool for annotating amino acid biosynthesis pathways in bacterial and archaeal genomes. We updated GapMind to include recently identified enzymes, including new enzymes that we identified by using high-throughput genetics and comparative genomics.GapMind_Oct2024.tar.gz -- tarball of source code and compiled rules for the GapMind for amino acid biosynthesis. The compiled rules are in tmp/path.aa/orgsDef_206_ngaps.tsv -- table of prototrophic bacteria and archaea and the number of gaps in each genome (considering only steps on the best path that lacked even a medium-confidence step in either the protein annotation or the 6-frame translation)known_auxo.tsv -- table of known auxotrophies for bacteriaorgsDef_206.tar.gz -- GapMind analysis of the 206 prototroph genomes (tmp/orgsDef) and for the 6-frame translation (tmp/orgsDef.6f)orgsAuxo_28.tar.gz -- GapMind analysis of the 28 auxotroph genomesngaps.image -- R image including the ngaps table, the gaps table (one row per genome x pathway), and the best table (one row for each step on the best path for each genome x pathway)aa3.R -- R code for generating the tables in the R image
DOI: 10.6084/m9.figshare.c.3666502_d63.v2
title: Example video of threat-like (perch aggression) interaction (1)

description: Two bats are interacting while perching in their artificial roost. In the beginning of the interaction, a pup is departing from its mother (one of the communicating bats).
DOI: 10.17632/j73pz5g35g
title: The relationship of Energy with Atoms and Time, Space

description: In each of the previous articles, electrons, protons, etc., the relationship of ‘L’ with particle and light has been shown. It also provides detailed information on why each number used in physics is being used, and what sources are used to find the source. In the present article, too, are electrons, protons, Pi, time, space, how they come together, and what is the source of ‘C’2? (in the great formula e=mC2 . I respect sir Einstein’s contribution) .This has been discussed. I look at each article from different angles and from different perspectives; I have tried to prove their authenticity by calculating the atomic and light constants, quantum etc. by mathematics. All of these articles were later published in Mendely Data. Which has taken a place in the court of the world (scientist community) today through social media. And how the properties of matter/particles are hidden in all these combinations of Atom Therefore, I urge all readers to read each of the previous articles once to understand this article better or to know the details.
DOI: 10.6084/m9.figshare.27310764.v3
title: <b>Multimodal Hate Speech Detection: A Novel Deep Learning Framework for Multilingual Text and Images</b>

description: Furqan Khan Saddozai1, Sahar K Badri2, Daniyal Alghazzawi2, Asad Khattak3, and Muhammad Zubair Asghar1*Gomal Research Institute of Computing (GRIC), Faculty of Computing, Gomal University, D.I.Khan (KP), PakistanInformation Systems Department, Faculty of Computing and Information Technology, King Abdulaziz University, 21589, Jeddah, Saudi ArabiaCollege of Technological Innovation, Zayed University, Abu Dhabi Campus, 144534,Abu Dhabi, UAE<b>Dataset Description</b>The Multimodal Multilingual Hate Speech 11K (MMHS11K) Dataset consists of 11,000 labeled Urdu Tweets with English translation, each categorized as either 'Hate' and 'No-Hate'. The dataset is divided into training (MMHS11K_train.xlsx ) and test (MMHS11K_test.xlsx ) files. The training file contains 8,800 records with an equal distribution (i.e. 4400) of 'Hate' and 'No-Hate' classes. The test file contains 2,200 records with 1,100 'Hate' and 1,100 'No-Hate' sample. Each file contains six columns:Tweet_Id: Represents the unique identifier of the corresponding tweet.Text: Contains the textual content of the tweet in Urdu.Text (English): Provides the English translation of the corresponding Urdu tweet.Image_Text: Displays text extracted from images in Urdu. If no text is extracted, the value 'NIL' is used.Image_Text (English): Contains the English translation of the corresponding Image_Text value. If Image_Text is 'NIL', this column also shows 'NIL'.Label: Indicates the classification of the multimodal multilingual tweet as either 'Hate' or 'No-Hate'The dataset contains two folders:MMHS11K_RGB_train.rar: This folder holds the training images in RGB format. It contains two subfolders: Hate and No-Hate. For each tweet in the MMHS11K_train.xlsx file, the corresponding image is stored in the appropriate subfolder (Hate or No-Hate) within the MMHS11K_RGB_train folder, using the tweet's Tweet_Id as the filename. For example, the image for Tweet_Id = 1596192893743796224 is stored in the No-Hate subfolder of MMHS11K_RGB_train, as this tweet is labeled as No-Hate.MMHS11K_RGB_test.rar: This folder contains the test images in RGB format. It also includes two subfolders: Hate and No-Hate.<b>Other Information</b>Accepted for Publication in: PeerJ Computer Science<br>
DOI: 10.6084/m9.figshare.29109665.v1
title: Interview Nick.docx

description: In-depth interview transcription
DOI: 10.6084/m9.figshare.3171472.v12
title: EventWiki: A knowledge base of major events

description: <pre>EventWiki is a knowledge base of major events happening throughout mankind history. It contains 21,275 events of 95 types. The details of event entries can be found in our paper submission and documentation file. Data in the knowledge base is mainly harvested from Wikipedia.</pre><pre>As Wikipedia, this resource can be distributed and shared under CC-BY 3.0 license.</pre>
DOI: 10.6084/m9.figshare.5124526.v1
title: Supplementary Material for: German Medical Students’ Beliefs about How Best to Treat Alcohol Use Disorder

description: <b><i>Background/Aims:</i></b> A minority of German medical students believe they know how to support smokers willing to quit. This paper examined whether the same would be true for treating alcohol use disorder (AUD), and individual factors associated with incorrect beliefs about the effectiveness of methods to treat AUD. <b><i>Methods:</i></b> In this cross-sectional study, 19,526 undergraduate students from 27 German medical schools completed a survey addressing beliefs about the effectiveness of different methods of overcoming AUD. Beliefs about AUD treatment effectiveness were compared across the 5 years of undergraduate education and predictors identified by means of multiple linear regression. <b><i>Results:</i></b> Even in the fifth year, 28.1% (95% CI: 26.5–29.7) of students believed that willpower alone was more effective for overcoming AUD than a comprehensive treatment program. The only significant predictor of this belief was a similar belief for stopping smoking. <b><i>Conclusion:</i></b> Our results indicate that a considerable proportion of German medical students overestimate the effectiveness of willpower to treat smoking and AUD. The addictive nature of these disorders needs to be stressed during undergraduate medical education to ensure that future physicians will be able and motivated to support patients in their quit attempts.
DOI: 10.6084/m9.figshare.7364810.v3
title: AFM_RawData_Seeger

description: Included are raw data files for all AFM and optical fluorescence images. AFM images have been converted to .png files using the open access software, Gwyddion, for the following channels: Height, Peak Force Error and Stiffness (DMT Modulus).<br>All experiments were conducted using a ScanAsyst-Fluid cantilever, with a nominal spring constant of 0.7 N/m.
DOI: 10.17632/p8xm4fx5ys
title: Chemical compound identified in Green Honey (GH)

description: The LC-MS/MS-QTOF to identify non-targeted derivatives in GH samples. This comprehensive analysis encompasses compound names, mass-to-charge values, species, retention times, and various other details. The analysis revealed a total of 42 chemical compounds, including 10 unidentified ones. Among the identified compounds, there were 9 carbohydrates, 9 organic acids, 7 amino acids, 6 fatty acids, 2 sugars, and one compound each of phenol, terpene, sulfur, and phosphate. These findings substantiate that green honey contains a substantial array of significant compounds, making it a safe choice for daily consumption. This dataset provides a thorough overview of the analyzed samples, allowing for a more in-depth understanding of the detected compounds and their characteristics.
DOI: 10.6084/m9.figshare.25011632.v1
title: Delamination dataset

description: This is the full package-delamination dataset generated by simulation. It contains 29 run-to-failure samples to characterize typical delamination behaviour over the time .It contains folder related to Stress sensor measurements , file containing Delamination Index from Physics Of Failure model. The ground truth delamination index for all the samples is also provided in a separate file.<br>File structure1. Stress_Sensor_measurements folder :- This folder contains stress sensor measurements for 29 run-to-failure samples and input loading for each sample.For each sample there are four stress sensor measurement files. Sensor Names are Centre_sxx,Centre_syy,Edge_sxx,Edge_syy.Each file related to sensor measurement has naming convention as follows: SampleNumber_SensorName.txtEach file related to input loading has naming convention as follows: SampleNumber_temp.txt2. DI_Ground_Truth.csv :- This file contains ground truth Delamination Index for 29 run-to-failure samples which are used to validate the models3. DI_Physics_Of_Failure.csv :- This file contains Delamination Index of Physics of failure model for 29 run-to-failure samples.For more information refer to article "A hybrid model for prognostic and health management of electronic devices"<br>
DOI: 10.6084/m9.figshare.25962808.v1
title: The part 1 of dataset Outdoor

description: Here we publish the part 1 of the dataset Outdoor used in the paper "FM-Based Positioning via Deep Learning".
DOI: 10.6084/m9.figshare.9995732.v1
title: wilson.zip

description: Folder with dataset analyzed via TOBIAS software and prepared for WILSON webapp (https://github.molgen.mpg.de/loosolab/wilson-apps/)<br>
DOI: 10.6084/m9.figshare.14759232.v1
title: Topological Analysis of Geographical Flows

description: Beijing_road: The road network in Beijing. In the attribute table, osnode_id is ordered origin point id; oenode_id is ordered destination point id; order_id is ordered section id.Flow: OD flow data.Flow_Euclidean.py: The program of calculating the topological relations between flows in Euclidean space.Flow_road_network.py: The program of calculating the topological relations between flows in the road network space.Flow_Carpool.py: The program of determining which trips can be shared.
DOI: 10.6084/m9.figshare.25683621.v1
title: DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells.zip

description: Raw data files for the publication "<b>DNA-based ForceChrono Probes for </b><b>Deciphering Single-Molecule Force Dynamics in Living Cells</b>".1. Because the single molecule data of each cell is too large, only corresponding statistics and representative pictures are provided in the uploaded data.2. The Figure data is mostly provided in tif format, but due to the variety of experimental instruments, there are also some data in special formats directly exported by the instrument, such as AFM and WB imaging. These data can be opened with the offline software of the corresponding instrument or Fiji.3. If you have any questions, please contact us.
DOI: 10.6084/m9.figshare.26304115.v1
title: MIST: Reusability Report

description: Data for the figures used in the reusability report of MIST
DOI: 10.6084/m9.figshare.28254440.v1
title: File S1_Summary of 5238 species

description: File S1
DOI: 10.6084/m9.figshare.28382339.v1
title: Raw Experimental Data

description: Raw experimental data.
DOI: 10.6084/m9.figshare.28490297.v1
title: Foam Prediction in Milk Filling Process

description: This dataset are process parameter that is gathered to predict foam formation during milk filling process.
DOI: 10.6084/m9.figshare.29125535.v1
title: Gastric_integrated_data

description: This scRNA-seq data is derived from human gastric tissues with 13 phenotypes. After integration of 11 datasets, 574,532 QC-passed cells were obtained with 70 cell types.
DOI: 10.17632/4ck6jf5vxf
title: micrOMEGAs 6.0: N-component dark matter

description: micrOMEGAs is a numerical code to compute dark matter (DM) observables in generic extensions of the Standard Model (SM) of particle physics. We present a new version of micrOMEGAs that includes a generalization of the Boltzmann equations governing the DM cosmic abundance evolution which can be solved to compute the relic density of N-component DM. The direct and indirect detection rates in such scenarios take into account the relative contribution of each component such that constraints on the combined signal of all DM components can be imposed. The co-scattering mechanism for DM production is also included, whereas the routines used to compute the relic density of feebly interacting particles have been improved in order to take into account the effect of thermal masses of t-channel particles. Finally, the tables for the DM self-annihilation - induced photon spectra have been extended down to DM masses of 110 MeV, and they now include annihilation channels into light mesons.
DOI: 10.17632/6wypw396y9
title: DESARROLLO DE UNA ESTRATEGIA DE COMUNICACIÓN PARA LA TIENDA VIRTUAL @SANDIA.COL

description: DESARROLLO DE UNA ESTRATEGIA DE COMUNICACIÓN PARA LA TIENDA VIRTUAL @SANDIA.COL
DOI: 10.17632/vw4kkfrz3k
title: Real-world experience of bimekizumab for plaque psoriasis in adult patients with prior exposure to interleukin-17 inhibitors: A 16-week multicenter retrospective review

description: Bimekizumab is the most recent interleukin-17 inhibitor (IL-17i) to receive approval for adult plaque psoriasis; unlike other IL-17i agents, it exclusively targets IL-17A/IL-17F. While biologic switching is common in routine clinical practice, limited information exists on switching from another IL-17i agent to bimekizumab. We conducted a real-world, multicenter, retrospective study of bimekizumab use in the setting of prior IL-17i exposure.
DOI: 10.17632/x5w9hw7789
title: Environmental sustainability disclosures in annual reports of companies on the ASX Metals & Mining industry

description: Dataset with raw data used in the analysis
DOI: 10.6084/m9.figshare.1595938.v4
title: Mining Company's Global Supply Chain - Logistics Data for a Medium Size Excavator
DOI: 10.6084/m9.figshare.20301795.v1
title: mouse156_Thy1.1negative_CD4Tcell_SalivaryGland_mCMVinfection_TCRrepertoire_AlphaChain

description: For details please refer to the metadata file in the same folder
DOI: 10.6084/m9.figshare.22591870.v1
title: MD-Ligand-Receptor: a HPC tool for characterizing ligand receptor binding interactions in molecular dynamics trajectories

description: We present MD-Ligand-Receptor, an efficient high-performance structural bioinformatics pipeline for the analysis of ligand-receptor binding interactions as a function of time, obtained from the analysis of molecular dynamics trajectories. The pipeline has been developed to work on a multicore linux server as well as on a multi-node HPC cluster. In the latter case, MD-Ligand-Receptor allows the user to analyze large trajectories in a very short time. In addition, an easy-to-use Plotly dashboard is provided to view the results of the interaction in several graphical ways. <br> The three folders contain: <br> <strong>test_data:</strong> a molecular dynamics trajectory of 100K picoseconds and the corresponding system topology. This input data can be used to test the software. <br> <strong>result_data:</strong> the results obtained by running the software on the test data. The result files are ready to be visualized in a Plotly dashboard, as described in the GitHub repository. <br> <strong>MD_ligand_receptor_software:</strong> the whole software as reported in the GitHub repository. <br> Authors: [Francesco Madeddu, Michele Pieroni, Jessica Di Martino, Manuel Arcieri, Valerio Parisi, Paolo Bottoni and Tiziana Castrignanò]
DOI: 10.6084/m9.figshare.24298774.v2
title: Results from Nanodisco

description: The .RDS files from the Nanodisco for eight bacterial samples.
DOI: 10.6084/m9.figshare.3512807.v1
title: Appendix A. User-defined code for single-season models that are not in predefined list.

description: User-defined code for single-season models that are not in predefined list.
DOI: 10.17632/536jtpn768
title: Data for: Pristine vs. human-altered Ebro Delta habitats display contrasting resilience to RSLR

description: Input data of accretion and subsidence, and all output files of sensitivity and model simulations for each RCP scenario and year.
DOI: 10.4121/13392314.v2
title: COAST-RP: A global COastal dAtaset of Storm Tide Return Periods

description: Storm surges that occur along low-lying, densely populated coastlines can leave devastating societal, economical, and ecological impacts. To protect coastal communities from flooding, return periods of storm tides, defined as the combination of the surge and tide, must be accurately evaluated. Here we present storm tide return periods using a novel integration of two modelling techniques. For surges induced by extratropical cyclones, we use a 38-year time series based on the ERA5 climate reanalysis. For surges induced by tropical cyclones, we use synthetic tropical cyclones from the STORM dataset representing 10,000 years under current climate conditions. Tropical and extratropical cyclone surge levels are probabilistically combined with tidal levels, and return periods are computed empirically. The COAST-RP dataset contains storm tide levels representing the 1, 2, 5, 10, 25, 50, 100, 250, 500, and 1000-year return period.
DOI: 10.6084/m9.figshare.11925444.v3
title: pmoC-phages

description: The fasta format files of genomes for 22 pmoC-phages and 5 non-pmoC-phages, and the genome of predicted host of BML pmoC-phages.
DOI: 10.6084/m9.figshare.24264109.v1
title: Coral reef states data and R-code

description: These are the datasets and code needed to reproduce the analyses for the coral reef states paper.
DOI: 10.6084/m9.figshare.3559017.v1
title: Appendix A. The six functional traits and 19 character states used to characterize coral taxa recorded in our surveys of high-latitude coral communities of eastern Australia.

description: The six functional traits and 19 character states used to characterize coral taxa recorded in our surveys of high-latitude coral communities of eastern Australia.
DOI: 10.17632/gzvzb6mws4
title: Data for: Data mean and ratio of absorbance to concentration methods: a novel optimization strategy for near infrared modeling

description: The public NIR testing data were from the appendix of the published articles [1,2]. [1] R. Zhang, Y.Y. Chen, Z.B. Wang, K.W. Li, A novel ensemble L1 regularization based variable selection framework with an application in near infrared spectroscopy, Chemometr Intell Lab 163 (2017) 7-15. [2] J.H. Kalivas, Two data sets of near infrared spectra, Chemometr Intell Lab 37(2) (1997) 255-259. ① This data set consists of 80 samples of corn measured on 3 different NIR spectrometers, we anlysis one NIR spectrometer: m5spec. The wavelength range is 1100-2498nm at 2 nm intervals (700 channels). The moisture, oil, protein and starch values for each of the samples is also included. A number of NBS glass standards were also measured on each instrument. The data was originally taken at Cargill. Many thanks for Mike Blackburn for letting us distribute it. ② NIR spectra and octane numbers of 60 gasoline samples NIR: NIR spectra, measured in 2 nm intervals from 900 nm to 1700 nm octane: octane numbers spectra: a dataset array containing variables for NIR and octane
DOI: 10.6084/m9.figshare.23500326.v1
title: <strong>Analysis of a spatial point pattern in relation to a reference point</strong> Program main.cpp (c++) Data sample.csv

description: This paper develops a new method for analyzing the relationship between a set of points and another single point, the latter of which we call a reference point.
DOI: 10.6084/m9.figshare.5894584.v1
title: PNAS_paper.zip

description: The zip folder PNAS_paper contains the original ibw files for Figs 2, 3 and S1 for the recently accepted paper: Al-Rekabi Z & Contera S. 2018. PNAS. (accepted).
DOI: 10.6084/m9.figshare.14891412.v1
title: FISHMORPH_Database

description: Ten morphological traits measured on 8 342 freshwater fish species, covering 48.69% of the world freshwater fish fauna<br>
DOI: 10.6084/m9.figshare.16893394.v1
title: SNPSNAP_MATCHED_SNPS.csv

description: SNPSNAP simulated SNPS<br>