cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rgdj46688d
title: Dataset_environmental_sustainability

description: Dataset to examine factors influencing intentions towards environmental sustainability of hospitality and tourism students in Thailand
DOI: 10.6084/m9.figshare.154688.v2
title: Gas hydrate deposits: a primer

description: THE .pdf ISN'T DISPLAYING ON FIGSHARE'S PREVIEW FOR REASONS UNKNOWN. TRYING TO FIX... This graphic is a draft from an educational course I'm compiling about the Earth's natural gas reserves. It attempts to summarise what gas hydrates are and where they can be found, adn accompanies further graphics that explain the chemistry of hydrates. No attempt is made to quantify the amount of methane that might be present in these deposits globally - this is the subject of much uncertainty. Those interested in the details of resource size can refer to the sources listed in the graphic and GEA (2012). <em>Global Energy Assessment - Toward a Sustainable Future</em>. Cambridge University Press. I hope some will find this useful. Any comments, corrections and queries welcome.
DOI: 10.6084/m9.figshare.24916140.v1
title: A 100-m gridded population dataset of China’s seventh census using ensemble learning and geospatial big data

description: A 100-m gridded population dataset of China’s seventh census in 2020 was generated by stacking ensemble learning and geospatial big data. The county-level and town-level data of China’s seventh census and ten related covariates at the 100-m resolution were first collected as the input datasets. Three popular machine learning algorithms (i.e., random forest, XGBoost, and LightGBM) were chosen as base models to create and train the stacking ensemble learning to generate gridded population dataset for China.The estimated gridded population dataset (R<sup>2</sup>=0.8936) is more accurate than existing WorldPop (R<sup>2</sup>=0.7427) and LandScan (R<sup>2</sup>=0.7165) products assessed by the town-level test census data. The dataset is associated with the paper of "Yuehong Chen, Congcong Xu, Yong Ge, Xiaoxiang Zhang and Ya'nan Zhou. A 100-m gridded population dataset of China’s seventh census using ensemble learning and big geospatial data, 2024" published in the journal of Earth System Science Data.
DOI: 10.17632/63rjyv54w4
title: Data for: The NONO protein regulates nonclassical DNA structure: effects on circadian genes and DNA damage

description: Data for Experiments 3 and 6:
- Table S2: Excel file containing additional data too large to fit in a PDF, related to STAR Methods Section and Figure S10, S11 (RNA sequencing and DRIP sequencing at CT6).
- Table S3: Excel file containing even more data too large to fit in a PDF, related to Figure S10, S11 (RNA sequencing and DRIP sequencing at CT18).
DOI: 10.6084/m9.figshare.28328186.v1
title: Supplementary Materials - On the Evolution of Agile Software Team Work Arrangements

description: These are the supplementary materials for the study "On the Evolution of Agile Software Team Work Arrangements". The materials provided are: the interview protocol, including the interview questions, the codebook, and a coding excerpt from the data analysis.
DOI: 10.17632/38n9386r8m
title: Data for: Erosion and fuel retentions of various reduced-activation ferritic martensitic steel grades exposed to deuterium plasma
DOI: 10.6084/m9.figshare.1314099.v5
title: Human behavior in contextual multi-armed bandit problems - Experimental data

description: This is raw data from the experiment described in the following article: Stojic, H., Analytis, P. P., & Speekenbrink, M. (2015). Human behavior in contextual multi-armed bandit problems. Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. See exp1_Readme.pdf file for more detailed instructions, descriptions of variables and licencse. The experiment itself can be tried out at the following URL: http://experimentnext.com/CMABvsMABexp1
DOI: 10.6084/m9.figshare.25224986.v1
title: Datasets to accompany: Environmental visual complexity increases the foraging success of mesopredators by promoting explorative behaviours (https://doi.org/10.1016/j.anbehav.2024.123057)

description: Manuscript title:Environmental visual complexity affects the foraging success of mesopredators by modifying their exploratory behaviour<br>------<br>Corresponding files:<br>Expt1_A_Choice.txtExpt2_A_PreyCaught.txtExpt2_B_PreyTime.txtExpt2_C_Activity.txt<br>------<br>Expt1_A_Choice.txt:<br>- TrialNumber: Number of trial (1-24)- TreatmentOrder: Order in which treatment comparisons were presented (1-3)- LeftTreatment: Complexity level presented on the left-hand-side of the arena (Low, Medium or High)- RightTreatment: Complexity level presented on the right-hand-side of the arena (Low, Medium or High)- TimeLeft: Time (seconds) that a fish spent in the left-hand-side of the arena- TimeRight: Time (seconds) that a fish spent in the right-hand-side of the arena<br>------<br>Expt2_A_PreyCaught.txt:<br>- TrialNumber: Number of trial (1-72)- Complexity: Level of visual complexity presented in the arena (Low, Medium or High)- NPreyCaught: Number of prey items captured in the time available (0-3)<br>------<br>Expt2_B_PreyTime.txt:<br>- TrialNumber: Number of trial (1-72)- Complexity: Level of visual complexity presented in the arena (Low, Medium or High)- PreyNumber: The respective number of each prey item (1-3)- CaptureTime: Time (seconds) for fish to capture prey item relative to the last prey item or the start of the trial (for PreyNumber 1); NA if fish did not capture the prey item<br>------<br>Expt2_C_Activity.txt:<br>- TrialNumber: Number of trial (1-72)- Complexity: Level of visual complexity presented in the arena (Low, Medium or High)- MedianSpeed: Median speed of fish across the trial (m/s)- MedianDist: Median distance from the arena's edge across the trial (m)- PpnExpl: Proportion of the arena explored- PpnStat: Proportion of the trial that a fish was deemed to be stationary (moving at a speed lower than 0.008 m/s)- BoutsPerMin: Mean number of movement bouts per minute- MeanBoutLength: Mean length of movement bouts exhibited by fish (seconds)
DOI: 10.6084/m9.figshare.28508882.v1
title: AFM data roughness; AFM data Modulus; Microindentation data; Uniaxial tension test data

description: Data acquired in the study of a considerable number of SMILE-derived lenticules from patients of different ages and with different severity of myopia, using atomic force microscopy, microindentation and tensile testing.
DOI: 10.17632/f8z3dx8mvf
title: Supplemental Section of Evaluating Patient’s Ability to Detect Changes in Hair Density Using Standardized Global Scalp Photography: A Cross-Sectional Study

description: This is the Supplemental Section of the paper "Evaluating Patient’s Ability to Detect Changes in Hair Density Using Standardized Global Scalp Photography: A Cross-Sectional Study." This study aimed to define the threshold at which patients with and without alopecia perceive changes in hair density and compare these values to those of dermatologists. 

A validated survey method from Buontempo et al. was distributed to 205 participants (100 with alopecia, 105 without) from the NYU Skin and Cancer Clinic, NYU Faculty Group Practice, and via email (99% response rate). Participants evaluated 14 sets of standardized scalp photographs, identifying images with higher, lower, or unchanged hair density. A logistic regression model estimated the “just noticeable difference” (critical threshold) at 41.69 hairs/cm², corresponding to a 22.78% relative difference. This closely aligned with the previously reported dermatologist threshold of 20.66%. Welch’s t-test with Bonferroni correction revealed no significant differences in critical thresholds between participants with and without alopecia or between patients and dermatologists.

This supplemental section specifically details how the survey was created and what parameters/questions the survey collected. It also illustrates the demographic breakdown of the survey participants, the critical thresholds for hair density detection across multiple subgroups, and the corresponding significant difference between these subgroups via tables. Lastly, the methodology for the literature search strategy and the python code used for the paper is described. 

These findings suggest that patients perceive hair density changes at a threshold comparable to dermatologists, indicating that subjective perception alone may be sufficient for detecting early hair loss. The lack of significant differences across subgroups suggests that personal experience with alopecia does not substantially alter perception. These results support the integration of trichometric data with photography for objective disease monitoring.
DOI: 10.17632/sm3g5ft3xx
title: Data for: Feruloyloacetone can be the main curcumin transformation product

description: Curcumin is a phenolic compound produced by some plants, among which Curcuma longa is the reachest in this principal curcuminoid. At elevated temperature curcumin degrades to trans-6-(4’-hydroxy-3’-methoxyphenyl)-2,4-dioxo-5-hexenal, vanillin, ferulic acid and feruloylmethane, however, the formation of feruloyloacetone ((5E)-6-(4-hydroxy-3-methoxyphenyl)hex-5-ene-2,4-dione) in the curcumin degradation process has not been reported yet. As results from experiments, even 28.8% or 20.6% of the degraded curcumin is transformed to feruloyloacetone during 2 hrs heating of alkaline or acidic curcumin solution, respectively. The structure of the identified feruloyloacetone was confirmed by MSn, HRMS and NMR data. The presented results are important for food processing as feruloyloacetone may be formed during food products preparation and its biological activity has not been fully recognized.
DOI: 10.6084/m9.figshare.10255811.v3
title: Blocklist Features - Cell Profiler

description: CellProfiler features that are known to be noisy and generally unreliable. We recommend removing these features before downstream analyses.
DOI: 10.6084/m9.figshare.15833451.v1
title: manuscript_analysis_benchmarking_output

description: This is the raw data of the benchmarking analysis used to generate Figure 5 and Supplementary Figure 2 in the manuscript.<br>Note that the first column in this csv contains information on the number of vibrations (last number before the .rds extension) as well as the number of dependent variables (e.g. ldl-3_DR1TFIBE_quantvoe_output_1_100.rds contained 3 dependent variables).
DOI: 10.6084/m9.figshare.26955565.v2
title: <b>Functional traits data for testate amoebae of Northern Holarctic realm</b>

description: The functional traits of soil protists have been employed in ecological research to enhance comprehension of the underlying mechanisms of ecological processes. Among the numerous soil protists, testate amoebae emerge as a prominent and abundant group, playing a pivotal role in soil micro-food webs. Furthermore, they are regarded as valuable bioindicators for environmental monitoring and palaeoecological studies due to their sensitivity to environmental changes. We screened 372 testate amoebae species widely distributed across Northern Holarctic realm and collected trait data, representing the morphological and feeding characteristics of testate amoebae. The dataset would provide valuable basis for investigation of the functional diversity and ecological roles of testate amoebae, thus facilitating further research on soil protist communities and ecosystem dynamics.
DOI: 10.17632/2t2xf85rnd
title: Field Monitoring of Foundations on Medium-Expansive Soil

description: Data for publication in "Data in Brief" Journal
DOI: 10.17632/9k49p7t7zx
title: Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models - Chapter 6 - dataset -Deep Learning Models Evolution Applied to Biomedical Engineering

description: In this chapter we focus on studying “Deep Learning Models Evolution” that combine midlevel elements with different connections “ANN” types to form more complex network types such as “Recurrent Neural Networks,” “Memory Augmented Neural Networks,” “Modular Neural Networks,” and “Evolutive Neural Networks". Please read this chapter at Science Direct: https://www.sciencedirect.com/science/article/pii/B978012820718500012X or buy the book/eBook at Elsevier, Amazon, and Bookstore worldwide.
Section 6.2.3.1 Research 6.1 LSTM to classify videos about human body movements and detect human falls (folder MATLAB_LTSM_videos)
Section 6.2.5.1 Research 6.2 Regional-CNN model for object detection of breast tumor in mammogram (folder MATLAB_R-CNN)
Section 6.2.6.1 Research 6.3 Hopfield Network model to reconstruct noisy chest X-ray images (folder MATLAB_HN)
Section 6.2.8.1 Research 6.4 Restricted Boltzmann Machine model to reconstruct noisy chest X-ray images (folder MATLAB_RBM)
Section 6.2.10.1 Research 6.5 Create a Reservoir Computing approach for a simulation of “Liquid State Machine (LSM)” of node neurons from “Spiking Neural Networks (SNN)” based on the “Izhikevich neuronal mathematical model” to differentiate normal and pneumonia on chest X-rays (folder MATLAB_LSM)
Section 6.3.2.1 Research 6.6 simulation of a Turing Machine (TM) using a recursive function to "analyze how the respiratory transmission of a COVID-19 infected person can spread a virus through droplets/mini-droplets emissions" (folder MATLAB_NTM)
Section 6.4.1.1 Research 6.7 Create a Deep Belief Network model to analyze and differentiate normal and pneumonia chest X-rays. “DBN model” from MATLAB based on node neurons from “Spiking Neural Networks (SNN)” applying the “Siegert Neurons mathematical model” to “differentiate normal and pneumonia chest X-rays” (folder MATLAB_DBN)
Note*: Please see an “Attention Networks” example at Chapter 7, Research 7.2 “Attention network using Long/Short-Term Memory to Classify Text of COVID-19 symptoms”.
DOI: 10.17632/tt8tmb4tbf
title: Base information for a local scale Species Distribution Model of Baccharis halimifolia and Juncus maritimus in the Oyambre estuary, Spain

description: The data includes the presences and pseudoabsences used for building a Species Distribution Model for the species Baccharis halimifolia and Juncus maritimus, at local scale in the Oyambre estuary, in the northern coast of Spain. It also includes the environmental rasters used for the models, both a dataset with the training conditions in 2005 and the evaluation conditions in 2014. The rasters include statistic values of hydrodynamic variables, salinity and other information used to build the models at a resolution of approaximately 10x10 m. The presences are spatial points indicating the location of known occurrences of the species in the years 2005 and 2014 in the estuary. The pseudo-absences are points generated randomly with a 20 m buffer around the presences. Readme file inside the folder with more information.
DOI: 10.6084/m9.figshare.4508741.v1
title: A methodology based on Deep Learning for advert value calculation in CPM, CPC and CPA networks

description: In this research, we propose a methodology for advert value calculation in CPM, CPC and CPA networks. Accurately estimating this value increases the three previous networks’ incomes by selecting the most profitable advert. By increasing income, publishers are better paid and improved services are afforded to advertisers. To develop this methodology, we propose a system based on traditional Machine Learning methods and Deep Learning methods. The system has two inputs and one output. The inputs are the user visit and the data about the advertiser. The output is the advert value expressed in dollars. Deep Learning predicts model behavior more precisely for many supervised problems. The three experiments carried out allow us to conclude that DL is a supervised method that is very efficient in the classification of spam adverts and in the estimation of the CTR. In the prediction of online sales, DLNN have shown, on average, worse performance than cubist and random forest methods, although better performance than model tree, model rules and linear regression methods.
DOI: 10.17632/2vg97bnv2z
title: data statement (Drivers of capital flows to European Transition Economies)

description: CE: Gross-Portfolio Equity Inflows: total, % of GDP, Source: IFS (IMF)
CD: Gross-Portfolio Debt Inflows: total, % of GDP, Source: IFS (IMF)
GE: Government Effectiveness Rate, Estimate of governance (ranges from approximately -2.5 (weak) to 2.5 (strong) governance performance), Source : Kaufman, Kraay and Mastruzzi (2010), WGI database
FD: Financial Development Index , Source: IMF data
RGDP: Real GDP Growth Rate in Local currency, Source: IFS (IMF)
RERVOL: Real Effective Exchange Rate Volatility: Based on past 12 monthly observation for all countries (calculated by authors), Source: FRED database
PD: Country Public Dept : total, % of GDP, Source:Abbas, Belhocine, ElGanainy adn Horton (2010) IMF database
FO: Financial Opennes Index, Source: Chin and Ito (2023)
VIX: The Volatility Index (VIX) computed by the Chicago Board Options, Source: FRED database
BBB: Credit spread of BBB rated US Corporate Index Option-Adjusted Spread, % Source: FRED database
INT: Short Term Interest Rates of Countries, Source: OECD database
INTS: three-month T-bill rate, Source: FRED database
G7: Growth rate of G7 countries: Annual percentage growth rate of GDP at market prices based on constant local currency, Source: WDI database
EPU: US economic policy uncertainty: Neswpaper based index, Source:www.policyuncertainty.com
DOI: 10.17632/b7dkpws7pw
title: A Two-Stage Game Model of Probabilistic Price Manipulation in Decentralized Exchanges

description: This repository contains all the data and code required to replicate the figures and tables from the paper “A Two-Stage Game Model of Probabilistic Price Manipulation in Decentralized Exchanges.” It includes the underlying datasets that capture both raw and pre-processed information used in the analysis, as well as Python scripts and notebooks that reproduce each empirical result, figure, and table presented in the paper. A comprehensive README file guides users step by step through the procedures required to run the scripts and generate all outputs. By following these instructions, anyone can replicate the paper’s core findings, including the two-stage game modeling framework, the parameters used for each simulation, and the resulting numerical and graphical outputs. If you have any questions or encounter any issues running the code, please feel free to contact the authors.
DOI: 10.17632/mybpmk9gzh
title: Data for: Pollen reconstruction of the middle Holocene maximum summer monsoon in northern China and climate dynamics

description: Pollen counts record of HTL profile in Huitengxile Plateau of marginal monsoon area of northern China. In this paper, vegetation changes between 14,420 and 4850 cal. yr BP were reconstructed on the basis of 19 AMS 14C dates, and regional Holocene mountain foest dynamics and climate changes were discussed.
DOI: 10.17632/tvjyw4pzsk
title: Experimental Material - From User Stories to Domain Models: Recommending Relationships between Entities

description: The experiment material of the paper "From User Stories to Domain Models: Recommending Relationships between Entities", the results, the datasets, and the implementation of the method can be found here
DOI: 10.17632/8rcsspgxnt
title: Consumer Decision Making Data

description: This data was collected through more than 3000 students across Indian universities. I have utilized this data set for my study based on Emotional Intelligence and Consumer Decision Making. It also covers Cognition and Emotions facial expression Data. This data set can be used for the purpose of studying human behaviour related to ecommerce or online shopping. The context of the study was online shopping s. The data was collected online and by face to face interaction. It took 1.5 year to collect the data. I am making this data openly available.
DOI: 10.6084/m9.figshare.21624297.v1
title: Supplementary Data (annotation files from 32 species pairs)

description: Supplementary data consisting of annotation files from 32 species comparisons (TE, structural variants - identified with SyRI, including inversion, syntenic region, translocation, duplication)
DOI: 10.17632/ftmpbb5gx2
title: Single Nucleotide Polymorphisms (SNPs) of Beauveria species

description: Fungi are rich in complexes of sibling species that need combinations of approaches to be delimited, including with genomic information. Beauveria (Cordycipitaceae, Hypocreales) is a well-known genus of entomopathogenic fungi, used as a biocontrol agent. We present in this study a polyphasic taxonomy regarding two widely distributed complexes of Beauveria: B. asiatica and B. bassiana sensu lato. Some of the genetic groups as previously detected within both taxa were either confirmed or fused using population genomics. High levels of divergence were found between two clades in B. asiatica and between three clades in B. bassiana, supporting their subdivision as distinct species. 

Fungal culture and DNA extraction.
Seventy-eight strains of presumably 12 Beauveria species from BIOTEC culture collection (BCC) and ARS collection of entomopathogenic fungal cultures (ARSEF), including the type strains of known species and strains previously identified as B. bassiana or B. asiatica as well as some unidentified strains. The strains were cultured in 50 ml of potato dextrose broth and incubated at 25 °C for a week. Fungal mycelia were harvested by filtering with a sterilized nylon mesh and washed with ethylene diamine tetraacetic acid (EDTA) and distilled water. DNA extraction was done using a cetrimonium bromide (CTAB)-based method;  the DNAs were purified using the high pure PCR template preparation kit (Roche).

 

DNA library construction and sequencing
For whole genome shotgun sequencing of 78 strains, approximately 300 ng of each DNA sample was used for a library construction following the protocol in the MGIEazy FS library prep kit (MGI Tech, Shenzhen, China). The samples were pooled and sequenced in a single lane. Paired-end (150 bp) sequencing was performed on the MGISEQ-2000RS (MGI Tech, Shenzhen, China) according to the manufacturer’s instructions.

 

Data processing and detection of single nucleotide polymorphisms (SNPs)
            Using the MegaBOLT V1.5.6.11 software package, raw reads were de-multiplexed according to their barcodes and the adapter/barcode sequences were removed. After removing the low-quality regions, clean reads were mapped to the B. bassiana reference genome ARSEF8028 (Valero-Jiménez et al. 2016) using the MegaBOLT V1.5.6.11 alignment software (Minimap2 version 2.11-r797-v03) and the variants were called using GATK HaplotypeCaller version 3.8. SNP markers with poor quality data were filtered out using the following criteria: (a) a minor allele frequency <0.1; (b) depth coverage less than 10x; (c) more than 20% missing data. The ploidy was set as haploid as all the strains were collected from asexual mycelia, i.e. putatively haploid for this ascomycete fungus.
DOI: 10.17632/j3tf3y2ss6
title: Data for: Endoscopic management of post-surgical GI wall defects with the overstitch endosuturing system

description: Raw data for the article: Endoscopic management of post-surgical GI wall defects with the overstitch endosuturing system.
DOI: 10.17632/m38r3jp92z
title: Ecosystem stability in Tajikistan from 2000 to 2020

description: This dataset consists of raster data on ecosystem stability in Tajikistan at 5-year intervals for the period 2000-2020.