cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14191097.v1
title: Supplementary Material for: Early Adiposity Rebound Predicts Obesity and Adiposity in Youth with Congenital Adrenal Hyperplasia

description: <b><i>Introduction:</i></b> Youth with classical congenital adrenal hyperplasia (CAH) have higher prevalence of cardiometabolic risk factors such as obesity, abdominal adiposity, and hypertension. Patients with CAH also exhibit an earlier adiposity rebound (AR) compared to normative populations. However, the predictive relationship between AR and cardiometabolic risk factors needs to be better understood. <b><i>Methods:</i></b> We performed a retrospective cohort study at a US tertiary pediatric center in youth with classical CAH due to 21-hydroxylase deficiency. AR was determined by cubic polynomial modeling. A subset of participants had fasting analytes, whole-body dual-energy X-ray absorptiometry, and magnetic resonance imaging as adolescents. <b><i>Results:</i></b> In 42 youth with CAH (45.2% female, 54.8% Hispanic, and 90.5% salt-wasting form), the average age at AR was 3.4 ± 1.3 years. AR differed by BMI-z, with youth with obesity having an earlier AR (2.8 ± 1.0 years) compared to lean youth (4.1 ± 1.3 years, <i>p</i> = 0.001). However, AR did not differ by either CAH form or sex. Earlier AR predicted higher BMI-z at 7 and 12 years of age. In addition, earlier AR predicted increased central obesity (as measured by waist circumference, subcutaneous adipose tissue, and trunk fat) and total body fat in adolescence. AR was negatively correlated with bone age, and its relationships with HDL and hypertension were trending towards significance. <b><i>Conclusions:</i></b> AR in youth with classical CAH could serve as a useful clinical marker to identify those patients who are at higher risk for developing cardiometabolic risk factors during childhood and adolescence.
DOI: 10.6084/m9.figshare.16964656.v3
title: China-LDRL: China’s surface water bodies, Large Dams, Reservoirs, and Lakes dataset

description: A dataset of China’s surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) by analyzing all available Landsat imagery in 2019 (19,338 images) in Google Earth Engine and very-high spatial resolution imagery in Google Earth.
DOI: 10.6084/m9.figshare.7873238.v1
title: Supplementary Material for: Thiamine Substitution in Alcohol Use Disorder: A Narrative Review of Medical Guidelines

description: <b><i>Aims:</i></b> Patients with alcohol use disorder (AUD) frequently suffer from cognitive deficits ranging from mild symptoms to most severe forms. Wernicke encephalopathy (WE), caused by thiamine deficiency, is a potentially fatal syndrome characterized by the clinical triad of ophthalmoplegia, ataxia, and confusion. WE frequently presents in patients with AUD and, if left untreated, can progress to Wernicke-Korsakoff syndrome, which constitutes severe anterograde amnesia, confabulation, and behavioral abnormalities. Due to oftentimes indistinct clinical presentation, WE remains undiagnosed in up to 80% of cases. We conducted a review of current treatment guidelines for AUD in order to identify recommendations for the use of thiamine. <b><i>Methods:</i></b> Three different keyword combinations (“alcohol treatment guideline,” “alcohol withdrawal guideline,” and “alcohol treatment recommendation”) were entered in PubMed and Scopus, additional guidelines were searched screening the online sites of the respective agencies or societies. In total, 14 guidelines were included. <b><i>Results:</i></b> Thiamine was mentioned in all but one of the reviewed publications. Specifications on application modalities and indications varied considerably. While the majority of reviewed guidelines recommended parenteral thiamine only for patients at high risk for WE, some gave no information regarding the application form or dosage. <b><i>Conclusion:</i></b> Substitution of parenteral thiamine in individuals with suspected WE is a well-established treatment regimen. However, suggestions according to guidelines vary widely. Furthermore, hardly any evidence-based recommendations exist on a more general use of thiamine as a preventative intervention in individuals with AUD. Further research is of utmost importance to raise awareness for this potentially undervalued problem.
DOI: 10.17632/pbcb786v78
title: Supplementary Figures for: Preferential CD123 expression in granuloma annulare compared to necrobiosis lipoidica and sarcoidosis

description: This dataset contains Mendeley Supplementary Figures 1 through 6 for the Brief Report manuscript titled “Preferential CD123 expression in granuloma annulare compared to necrobiosis lipoidica and sarcoidosis.” Supplementary Figures 1 and 2 show CD123 immunohistochemical staining in necrobiosis lipoidica and rheumatoid nodule, respectively. Supplementary Figures 3 through 6 show hematoxylin and eosin staining for granuloma annulare, necrobiosis lipoidica, sarcoidosis, and rheumatoid nodule.
DOI: 10.17632/3jhhtc57t5
title: TIMIR (Low Light - Dark Images)

description: Low-light image enhancement is a significant area of research and development in computer vision and image processing. The research based on low light images aims to improve the visibility and quality of images captured in poor lighting conditions. The database, TIMIR, is created in order to facilitate the researchers with different datasets. This dataset contains total 946 images of different categories like animals, birds, clouds, flowers, foods and random clicks.
DOI: 10.17632/gk693pzzwb
title: Manganese oxidation states and availability in forest weathering profiles of contrasting climate

description: The data related to: Manganese oxidation states and availability in forest weathering profiles of contrasting climate
DOI: 10.17632/3x2bk3x5fm
title: seismic-bumps

description: Seismic hazard is the hardest detectable and predictable of natural hazards and in this respect it is comparable to an earthquake. More and more advanced seismic and seismoacoustic monitoring systems allow a better understanding rock mass processes and definition of seismic hazard prediction methods. Accuracy of so far created methods is however far from perfect. Complexity of seismic processes and big disproportion between the number of low-energy seismic events and the number of high-energy phenomena (e.g. &gt; 10^4J) causes the statistical techniques to be insufficient to predict seismic hazard. Therefore, it is essential to search for new opportunities of better hazard prediction, also using machine learning methods. In seismic hazard assessment data clustering techniques can be applied (Lesniak A., Isakow Z.: Space-time clustering of seismic events and hazard assessment in the Zabrze-Bielszowice coal mine, Poland. Int. Journal of Rock Mechanics and Mining Sciences, 46(5), 2009, 918-928), and for prediction of seismic tremors artificial neural networks are used (Kabiesz, J
DOI: 10.6084/m9.figshare.19115018.v1
title: BL for CO2 storage

description: The excel file showing results of CMG simulation and the analytical solution is included.
DOI: 10.17632/7fd2vdtx48
title: Evaluation of Physicochemical Properties of Honey produced in East Azerbaijan Province, Iran

description: raw data
DOI: 10.6084/m9.figshare.14925180.v1
title: The Therapeutic Potential of Bedside Art Observation in Hematologic Cancer Inpatients: A Randomized Controlled Trial

description: The Therapeutic Potential of Bedside Art Observation in Hematologic Cancer Inpatients: A Randomized Controlled Trial
DOI: 10.17632/59xns3ckdy
title: Association of mental health outcomes and lower patient satisfaction among adults with alopecia: A cross-sectional population-based study

description: Supplemental material for the manuscript "Association of mental health outcomes and lower patient satisfaction among adults with alopecia: A cross-sectional population-based study." published in the Journal of the American Academy of Dermatology International.
DOI: 10.17632/7dbk89y3jy
title: Data for: An easy-to-handle speed of sound test object for skills-labs using additive manufacturing (RAPTUS-SOS)

description: raw data for Sigma plot (SOS-speed of sound data)
DOI: 10.17632/8nh8stpxrt
title: Data for: Abundance and composition of kaolinite on Mars: Information from NIR spectra of rocks from acid-alteration environments, Riotinto, SE Spain

description: Files containing: raw data of near-infrared samples from four areas (El Villar, Calañas, Quebrantahuesos, and Tharsis) in the Iberian Pyrite Belt raw data of thermal analysis of the above samples raw data of a survey of near-infrared spectra from Mars (Leighton Crater, Mawrth Vallis and Nili Fossae)
DOI: 10.17632/m69g9whc46
title: Machine Learning and Business Innovation: A Systematic Review of AI’s Role in Entrepreneurship

description: Machine Learning and Business Innovation: A Systematic Review of AI’s Role in Entrepreneurship Data
DOI: 10.6084/m9.figshare.4214202.v1
title: File name: Nicholson_et_al_Mesozoic_latitude_script_ESM.R Title: Mesozoic turtle latitude analyses R scriptDescription: R script for cleaning and partitioning Mesozoic turtle occurrence data into 15 degree palaeolatitudinal bands and various temporal bins, Shareholder Quorum Subsampling and generalised least squares regression analyses. from Latitudinal diversity gradients in Mesozoic non-marine turtles

description: The latitudinal biodiversity gradient (LBG)–the pattern of increasing taxonomic richness with decreasing latitude–is prevalent in the structure of the modern biota. However, some freshwater taxa show peak richness at mid-latitudes; for example, extant Testudines (turtles, terrapins and tortoises) exhibit their greatest diversity at 25° N, a pattern sometimes attributed to recent bursts of climatically mediated species diversification. Here, we test whether this pattern also characterizes the Mesozoic distribution of turtles, to determine whether it was established during either their initial diversification or as a more modern phenomenon. Using global occurrence data for non-marine testudinate genera, we find that subsampled richness peaks at palaeolatitudes of 15 – 30° N in the Jurassic, 30 – 45° N through the Cretaceous to the Campanian, and from 30° to 60° N in the Maastrichtian. The absence of a significant diversity peak in southern latitudes is consistent with results from climatic models and turtle niche modelling that demonstrate a dearth of suitable turtle habitat in Gondwana during the Jurassic and Late Cretaceous. Our analyses confirm that the modern testudinate LBG has a deep-time origin and further demonstrate that LBGs are not always expressed as a smooth, equator-to-pole distribution.
DOI: 10.6084/m9.figshare.26235233.v1
title: <b>Protein : Structure and Function</b>

description: The evolution of protein structure and function is driven by several key needs and factors:<b>Adaptation to Environment</b>: Proteins evolve to better suit their environment, whether it's within a cell, an organism, or a specific ecological niche. This adaptation can involve changes in structure to interact with new substrates or to perform different functions that enhance survival and fitness.<b>Functional Optimization</b>: Natural selection favors mutations that improve the function of proteins. Proteins may evolve to become more efficient catalysts (enzymes), stronger structural components (like collagen in connective tissue), or more effective transporters of molecules across membranes.<b>Diversification of Functions</b>: Proteins can evolve new functions through mutations that alter their structure, allowing them to perform novel roles in biological processes. This can lead to the development of new metabolic pathways, signaling cascades, or regulatory mechanisms.<b>Interactions and Networks</b>: Proteins often work together in complex networks and pathways. Evolution can optimize these interactions by fine-tuning the structure of proteins to ensure they fit together effectively and function cooperatively.<b>Genetic Drift and Neutral Evolution</b>: Not all changes in protein structure and function are driven by adaptive evolution. Some changes may occur due to genetic drift or neutral evolution, where mutations accumulate randomly without necessarily conferring a direct fitness advantage or disadvantage.<b>Environmental Changes</b>: Changes in the environment, such as shifts in temperature, pH, or the availability of nutrients, can drive the evolution of protein structure to maintain functionality under new conditions. Extremophiles, for example, have proteins adapted to function in extreme environments like high temperatures or acidity.<b>Evolutionary Constraints</b>: The structure of proteins is constrained by the fundamental physicochemical properties of amino acids and the need to maintain functional integrity. Evolution must navigate these constraints while optimizing for improved function or adaptation to new roles.Overall, the evolution of protein structure and function is a dynamic process driven by the interplay of environmental pressures, genetic variation, and the selective advantages conferred by changes in protein characteristics.
DOI: 10.17632/jgd3gw2pzy
title: Supplementary Information for: High pressure thermoelasticity and sound velocities of Fe-Ni-Si alloys

description: Supplementary information for High Pressure Thermoelasticity and Sound Velocities of Fe-Ni-Si Alloys, including 1) raw NRIXS spectra, 2) additional figures pertaining to the vibrational Grüneisen parameter, 3) an approximation for the vibrational Grüneisen parameter via an alternate determination method, 4) determination of Lamb-Mössbauer factors, 5) an additional figure pertaining to the vibrational entropy and thermal expansion, 6) determination of vibrational kinetic energy and specific heat capacity, 7) figures comparing our re-analysis of data published in Murphy et al. 2011a, 2013 with the original values, and 8) additional data tables including experimental conditions, equation of state parameters, molecular masses, sound velocity results corrected for natural enrichment, and additional vibrational quantities derived from the phonon density of states
DOI: 10.6084/m9.figshare.23720949.v3
title: Raw Data

description: Raw data
DOI: 10.17632/h5s7rz29vg
title: Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing

description: The data can be grouped as follows: 1.1 Generation of techno-economic data under uncertainty The input parameter assumption distributions and associated Monte Carlo sampling-based trial data for the base case techno-economic process model are described in the data file, 0.1 Assumption distribution & trial data. These assumptions distribution trial data feed into the techno-economic process model (publicly available at http://mcdonald-nandi.ech.ucdavis.edu/tools/techno-economics/) to generate the forecast variable output data in the base case scenario and facility oversizing scenarios (in which the equipment of the facility is sized larger to accommodate the uncertainty of production). This is described in data file, 02. Simulation trial data. The details of the equipment oversizing scenarios of the techno-economic process model to accommodate the uncertainty of production are described in the data file, 03. Equipment oversizing specification. 1.2 Analysis of techno-economic forecast variable outputs The forecast variable output data are compared between the base case and facility oversizing scenarios using two-sample t-tests for evaluation of the means and Kolmogorv-Smirnov tests for evaluation of the distributions, which is summarized in the data file, 04. Statistical test results. Box plots and quantile-quantile plots are shown in the data file, 05. Forecast variable normality, as assessments of normality. Univariate sensitivity of the forecast variables to the input parameters is investigated using tornado plots and spider charts in the data files, 06. Forecast univariate sensitivity, data, and 07. Forecast univariate sensitivity, charts. The contribution to variance of each input parameter to each forecast variable is calculated by rank correlation coefficient using Monte Carlo-based techno-economic simulation run data for the base case in which Pearson correlation coefficients are not included, the results of which are described in the data file, 08. Contribution to variance. Techno-economic output metrics are generated in the techno-economic modelling software using input parameter values associated with Monte Carlo-based techno-economic simulation trials that yielded the minimum, mean, and maximum values of internal rate of return after tax for the base case and facility oversizing scenarios, as described in the data file, 09. Cost breakdowns. 1.3 Techno-economic optimization under uncertainty A facility retrofitting case which presumes that the cation exchange chromatography is a new addition to an existing facility is approached with the base case facility sizing assumed to be fixed and the cation exchange chromatography column diameter is set as a decision variable to minimize internal rate of return after tax, as described in the data file, 10. Simulation results summary (CEX size optimization).
DOI: 10.17632/hpbszmrns7
title: N-BaIoT processed for anomaly detection

description: The original data comes from the work of Meidan et al. [1]. It was preprocessed in this setting for comparative analysis of anomaly detection. The following steps have been taken as preprocessing: (1) five devices have been selected: Danmini doorbell, Ecobee thermostat, Philips baby monitor, Provision security camera, Samsung webcam, (2) for each botnet, the malicious traffic of all five behaviour types have been merged, (3) for each device and botnet combination, malicious requests have been sampled to comprise 5% of the final dataset.

[1] Meidan, Y., Bohadana, M., Mathov, Y., Mirsky, Y., Shabtai, A., Breitenbacher, D., & Elovici, Y. (2018). N-baiot—network-based detection of iot botnet attacks using deep autoencoders. IEEE Pervasive Computing, 17(3), 12-22.
DOI: 10.6084/m9.figshare.5554540.v1
title: Experiment CLA-SubjectF-150917-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.17632/5vnnbf8hd6
title: Cleaned and validated Irish EPC database

description: The raw EPC database is filtered using ‘Python’ and ‘R’, Scripting helped in efficiently handling a large amount of data. The scripts used are combinations of data manipulation steps, applied in series, with filter, and change data based on specified user criteria. In this case, the entire EPC database accounting for 1 million entries in quarter 1 of 2022 was used as the input. This data flow captures the relative frequency of each filter and the resultant number of EPC entries cleaned from the dataset for being considered erroneous or outliers.  
Approximately 30% of EPC entries are flagged and labeled as outliers, this gives an overview of the data quality of the EPC database. As discussed earlier in section 3.7, the issue is not localized in Ireland, but it is widespread in MSs. The most striking finding was that many features which play a pivotal part in the overall performance of a dwelling and could uplift, or downgrade energy rating are plagued with poor data, i.e., Living Area Percentage, assigning the areas within a dwelling to be assumed to be heated at 21° C and 18° C . Getting it right is crucial in estimating the representative theoretical energy performance of dwellings. Also, ceiling height data is poor in quality, making it unrepresented of dwellings’ geometry, which again results in inaccurate overall energy performance.
DOI: 10.17632/b3646gm7v7
title: Preemptive Strikes or not: The Role of Emotion on Intergroup Defensive Aggression

description: This study aimed to examine intergroup preemptive behaviors and the emotional mechanism through 3 experiments. Experiment 1 designed the Group Preemptive Strike Game and found that in intergroup situations, individuals experienced intense fear and hope when they faced the potential threat from gaming counterparts, but their preemptive behaviors were not altered. Both Experiments 2 and 3, which were designed to simulate real-life groups with characteristics such as punishment (Experiment 2) and leadership (Experiment 3), found that people experienced intense fear and hope when they faced the potential threat and tended to attack preemptively. Fear and hope were mediators between the potential threat and preemptive behaviors, in which fear increased the preemptive behaviors of members, and hope decreased the preemptive behaviors. 

The dataset was collected among Chinese university students and used to study preemptive behaviors by Z-tree (Fischbacher, 2007). There are 5 sub-tables in Excel; Experiment 2 and Experiment 3 each contain 2 sub-tables.
DOI: 10.6084/m9.figshare.7316462.v2
title: Mass Spec Raw File Data

description: Here we report HDX raw files supporting the manuscript "Regulator of G-protein signaling, GPCR signaling, neurotransmitter signaling, crystal structure, Hydrogen-deuterium exchange mass-spectrometry (HDX)". The raw file sets are packaged in rar format in order to group the files into the two groups "Dimer vs Trimer" and "Monomer vs Trimer".
DOI: 10.17632/sr567vff6p
title: Monitoring Diffuse Injury in the EAE model for MS using CEST MRI

description: Comparison of MRI methods to predict and monitor disease progression in a multiple sclerosis mouse model. T1w/FLASH, T2w, T2*w, and metabolite-sensitive chemical exchange saturation transfer (CEST) MRI values (.xls) were acquired in the chronic experimental autoimmune encephalomyelitis (EAE) model (C57Bl/6, female, 6-10 weeks old, active induction against myelin antigen MOG35-55) at multiple regions of the brain and spinal cord (.ppt) over the course of the disease as paralysis progressed. CEST methods include the continuous wave (CW, at the 0-4 ppm frequencies), amide proton transfer (APT, at 3.6 ppm), and on resonance variable delay multiple pulse (onVDMP, at 0 ppm).
DOI: 10.6084/m9.figshare.11577543.v2
title: Danish AIS Data

description: This is a sample of the AIS data hosted at ftp://ftp.ais.dk/ais_data/ including:- 1st to 31st January 2017- 1st July 2017- 1st January 2018
DOI: 10.17632/4rr98d2559
title: Data for: Worldwide Implementation of Telemedicine Programs in Association with Research Performance and Health Policy

description: The data for the manuscript “Worldwide Implementation of Telemedicine Programs in Association with Research Performance and Health Policy” (HLPT_2018_160)
DOI: 10.6084/m9.figshare.6997253.v5
title: Pipeline for 16S rRNA processing using DADA2

description: Here you will find all of the code and explanations to completely reproduce our DADA2 pipeline for processing raw, pair-end 16S rRNA Illumina amplicon data. <br> The pipeline consists of two (2) parts of the workflow. <br> 1. The first part will process the data from different runs separately. Samples were sequenced across three runs, each of which was processed separately. This part consists of steps to filter and trim, learn errors, dereplicate, infer amplicon sequence variants (ASV), and merge paired end reads. We also include an optional step for identifying chimeras and assigning taxonomy for each run individually, however we actually did this on the combined data set in the next part. <br> 2. In the second part we merge the outputs from the first part, identify chimeras, and assign taxonomy. <br> Also included is the HTML file for the workflow. This can be viewed in any web browser.<br>