cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5787537.v1
title: Minimum Mean Squared Error Estimation of the Radius of Gyration in Small-Angle X-Ray Scattering Experiments

description: Small-angle X-ray scattering (SAXS) is a technique that yields low-resolution structural information of biological macromolecules by exposing a large ensemble of molecules in solution to a powerful X-ray beam. The beam interacts with the molecules and the intensity of the scattered beam is recorded on a detector plate. The radius of gyration for a molecule, which is a measure of the spread of its mass, can be estimated from the lowest scattering angles of SAXS data. This estimation method requires specification of a window of scattering angles. Under a local polynomial model with autoregressive errors, we develop methodology and supporting asymptotic theory for selection of an optimal window, minimum mean square error estimation of the radius of gyration, and estimation of its variance. Simulation studies confirm the quality of our asymptotic approximations and the superior performance of the proposed methodology relative to the accepted standard. Our semi-automated methodology makes it feasible to estimate the radius of gyration many times, from replicated SAXS data under various experimental conditions, in an objective and reproducible manner. This in turn allows for secondary analyses of the dataset of estimates, as we demonstrate with a split–split plot analysis for 357 SAXS intensity curves. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.14113799.v4
title: Wiki-Reliability: A Large Scale Dataset for Content Reliability on Wikipedia

description: Wiki-Reliability: Machine Learning datasets for measuring content reliability on Wikipedia<br>Consists of metadata features and content text datasets, with the formats:<br><i>- {template_name}_features.csv</i> <i><br></i><i>- {template_name}_difftxt.csv.gz <br></i><i><i>- {template_name}_fulltxt.csv.gz <br></i></i><br>For more details on the project, dataset schema, and links to data usage and benchmarking:<br>https://meta.wikimedia.org/wiki/Research:Wiki-Reliability:_A_Large_Scale_Dataset_for_Content_Reliability_on_Wikipedia<br>
DOI: 10.6084/m9.figshare.16620382.v1
title: comparativeData_final_figShare.csv

description: raw comparative data for analysis
DOI: 10.6084/m9.figshare.21835020.v1
title: File 6

description: Species annotation information at class level
DOI: 10.6084/m9.figshare.23389202.v1
title: Data for publication in <em>Frontiers in immunology </em>(<strong>DOI:</strong> 10.3389/fimmu.2023.1124118)

description: In our study, an altered gut microbiota composition featured by the reduction in SCFAs-producing bacteria was demonstrated in the KD mouse model. Next, probiotic <em>C. butyricum</em> and antibiotic cocktails were respectively employed to modulate gut microbiota. The use of <em>C. butyricum</em> significantly increased the abundance of SCFAs-producing bacteria and attenuated the coronary lesions with reduced inflammatory markers IL-1β and IL-6, but antibiotics depleting gut bacteria oppositely deteriorated the inflammation response. The gut leakage induced by dysbiosis to deteriorate the host’s inflammation was confirmed by the decreased intestinal barrier proteins Claudin-1, Jam-1, Occludin, and ZO-1, and increased plasma D-lactate level in KD mice. Mechanistically, SCFAs, the major beneficial metabolites of gut microbes to maintain the intestinal barrier integrity and inhibit inflammation, was also found decreased, especially butyrate, acetate and propionate, in KD mice by gas chromatography-mass spectrometry (GC-MS). Moreover, the reduced expression of SCFAs transporters, monocarboxylate transporter 1 (MCT-1) and sodium-dependent monocarboxylate transporter 1 (SMCT-1), was also shown in KD mice by western blot and RT-qPCR analyses. As expected, the decrease of fecal SCFAs production and barrier dysfunction were improved by <em>C. butyricum</em> treatment but was deteriorated by antibiotics. <em>In vitro</em>, butyrate increased the expression of phosphatase MKP-1 to dephosphorylate activated JNK, ERK1/2 and p38 MAPK against excessive inflammation in RAW264.7 macrophages.
DOI: 10.6084/m9.figshare.5980420.v1
title: Cardiac and Musculoskeletal Responses to the Effects of Passive and Active Tilt Test in Healthy Subjects

description: Abstract Background: Maintenance of orthostatism requires the interaction of autonomic and muscle responses for an efficient postural control, to minimize body motion and facilitate venous return in a common type of syncope called neurocardiogenic syncope (NCS). Muscle activity in standing position may be registered by surface electromyography, and body sway confirmed by displacement of the center of pressure (COP) on a force platform. These peripheral variables reflect the role of muscles in the maintenance of orthostatism during the active tilt test, which, compared with muscle activity during the passive test (head-up tilt test), enables the analyses of electromyographic activity of these muscles that may anticipate the clinical effects of CNS during these tests. Objective: to evaluate and compare the effects of a standardized protocol of active and passive tests for CNS diagnosis associated with the effects of Valsalva maneuver (VM). Methods: twenty-thee clinically stable female volunteers were recruited to undergo both tests. EMG electrodes were placed on muscles involved in postural maintenance. During the active test, subjects stood on a force platform. In addition to electromyography and the platform, heart rate was recorded during all tests. Three VMs were performed during the tests. Results: progressive peripheral changes were observed along both tests, more evidently during the active test. Conclusion: the active test detected changes in muscle and cardiovascular responses, which were exacerbated by the VM.
DOI: 10.6084/m9.figshare.c.3581339_d1.v1
title: GO_MF analysis

description: List of significantly enriched GO molecular function (MF) terms among the up- and downregulated genes
DOI: 10.17632/b5knyp45b9
title: Experiment in Greece

description: This dataset comprises a diverse sample of 300 entrepreneurs, encapsulating a broad array of characteristics pertaining to their companies. It serves as a rich repository of information, providing insights into various aspects of entrepreneurial ventures. The dataset includes quantitative metrics such as company size, revenue, profit margins, years in operation, and initial capital investment. Additionally, it features qualitative attributes like industry sector, geographical location, total assets, legal status and the demographic background of the entrepreneurs, including gender.
Designed to facilitate a comprehensive analysis of the entrepreneurial landscape, this dataset allows for the exploration of patterns and correlations across multiple dimensions.
DOI: 10.17632/j6fdbxfvfc
title: Inorganic_Li_Data

description: Data for inorganic calcite and aragonite precipitation experiments. Includes data on Experimental Runs, C and O isotope data, Li isotope and Li/Ca data, experimental solution composition data, Overgrowth fractionation estimates, Precipitation Rate estimates, calcite and aragonite seed data, and Na/Ca and Mg/Ca data.
DOI: 10.6084/m9.figshare.14457852.v1
title: Fig5a H&E staining of adult epididymus

description: Raw image dataset for H&E staining of Wdr62 genetrap adult epididymus sections.<br>1) Dewax slides.2) Harris Hematoxylin 4 mins.3) Rinse and dehydrate to 90% ethanol.4) Eosin 1min.5) Continue dehydrate to 100% ethanol, xylene and mount in DePeX. 6) Images were captured on Olympus BX51 light microscope.
DOI: 10.6084/m9.figshare.22294666.v1
title: An interprovincial input–output database distinguishing firm ownership

description: An interprovincial input–output database distinguishing firm ownership in China from 1997 to 2017. Including the IPIO tables, related files and codes.
DOI: 10.6084/m9.figshare.28106717.v1
title: E-POSE: A Large Scale Event Camera Dataset for Object Pose Estimation

description: E-POSE: A Large Scale Event Camera Dataset for Object Pose Estimation
DOI: 10.17632/2mwgk9n8mv
title: Experimental data and the executable to test the performance of situation-adaptive policy for container stacking in an automated container terminal

description: Determining where to stack the containers at the storage yard of a container terminal is an important problem because that decision critically affects the efficiency of container handling in the yard and eventually the efficiency of the vessel operations that is considered the most important for the productivity of the whole terminal. One limitation of the stacking policies previously proposed is that they are static in nature. Although good locations for stacking may change as the workload of vessel operation changes, the previous policies are insensitive to such changes. Failure to recommend good locations leads to elongated operations of yard cranes and thus makes them hard to keep up with the workload of vessel operation. In this paper, we propose a method for deriving a dynamic policy that can adapt to the workload of vessel operation that changes over time. Our method derives two boundary polices: one for very high workload and the other for very low. Then, a policy appropriate for any intermediate workload can be synthesized from the two boundary policies through an interpolation. Simulation experiments showed that the proposed policy significantly reduced overall container handling time compared to the previous static policy. When measured in terms of the time the transportation vehicles wait for container handling services, the improvement was about 19%.
DOI: 10.17632/4ywc84t5gx
title: Automatic crack detection and classification by exploiting statistical event descriptors for Deep Learning - Appendix. A - Supplementary Data

description: %% Title: %% Automatic crack detection and classification by exploiting statistical event descriptors for Deep Learning %% Authors: %% Giulio Siracusano, Aurelio La Corte, Riccardo Tomasello, Francesco Lamonaca, %% Carmelo Scuro, Francesca Garescì, Mario Carpentieri and Giovanni Finocchio %% email: giuliosiracusano@unict.it %% Description %% Zip Archive is composed of 3 files: 1. Training_dataset_15000AE_1000_samples.mat 2. Testing_dataset_1650AE_1000_samples.mat 3. README.txt (this file) %% Legend % Training Dataset (Matlab Format) % Training_dataset_15000AE_1000_samples.mat XTrain is in the format of 15000x1000 samples there are 15000 events (5000 are tensile, 5000 shear and 5000 mixed-events) each acoustic event is composed of 1000 time samples YTrain is the categorical array in the format of 15000x1 AE events are classified according to the following type: '1' = Tensile Mode '2' = Shear Mode '3' = Mixed-Mode freq is the vector of frequencies related to the given sampling frequency. It is composed of 501 elem(s) time is the time vector (sampling frequency has been reduced to 500kHz to save space). It is composed of 1000 elem(s) % Testing Dataset (Matlab Format) % Testing_dataset_1650AE_1000_samples.mat XTest is in the format of 1650x1000 samples there are 1650 total events for testing (550 are tensile, 550 shear and 550 mixed-events) each acoustic event is composed of 1000 time samples YTest is the categorical array in the format of 1650x1 AE events are classified according to the following type: '1' = Tensile Mode '2' = Shear Mode '3' = Mixed-Mode freq is the vector of frequencies related to the given sampling frequency. It is composed of 501 elem(s) time is the time vector (sampling frequency has been reduced to 500kHz to save space). It is composed of 1000 elem(s) % Last Revision % 27-Apr-2019
DOI: 10.6084/m9.figshare.13114433.v2
title: Concentration, 13C, and 14C of dissolved and ebullition methane, dissolved inorganic carbon, dissolved organic carbon, particulate organic carbon and ebullition CO2 in rivers and thermokarst lakes in Northern Quebec, Canada

description: The dataset includes concentration, <sup>13</sup>C, and <sup>14</sup>C measurements of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), particulate organic carbon (POC), total particulate carbon (TPC), sediment carbon and organic carbon, dissolved and ebullition methane (CH<sub>4</sub>), and ebullition carbon dioxide (CO<sub>2</sub>) from five lakes and three rivers in an area of sporadic permafrost degradation in Northern Quebec. <br><br>We sampled the three thaw lakes SAS2A, SAS2B, and SAS2C, located in a peatland adjacent to the Sasapimakwananisikw River (SAS2 peatland), in August 2018, August 2019, and February 2019. The other two lakes, KWK1 and KWK12, located in the once-glaciated KWK valley adjacent to the Kwakwatanikapistikw River, were sampled in August 2019 and 2019. <br><br>
DOI: 10.15468/dl.9up5gf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Holtbyrnia innesi (Fowler, 1934)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((26.9648 10.8496,17.9648 10.8496,17.9648 1.8496,26.9648 1.8496,26.9648 10.8496))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013403-250525065834625/datasets/export for details.
DOI: 10.17632/rkhjmrdfx8
title: Digitized Marine Vessel Locations

description: The provided point shapefile comprehensively represents marine vessel locations within the pristine coastal waters of Bahia de Banderas, Mexico. The dataset encompasses spatial records ranging from 2017 to 2023, capturing the positions of diverse vessels navigating the waters of this bay. This dataset's temporal range, spanning from 2017 to 2023, enables the analysis of vessel activities, unveiling trends and patterns over several years.
Each point in the shapefile represents a precise geospatial location where a marine vessel was recorded within the specified time frame. Attributes associated with these points include: FID==unique feature identifier, Shape=verbal description of feature class, Month=month of observation (11=November, 12=December, 1=January, 2=February, 3=March, 4=April) Year=year of observation, Season=the winter season grouped for analysis (note that months 11&12 will be grouped with the following year's months 1,2,3 & 4 representing one winter season), DIST_TO_DEP=vessel's distance to the nearest departure point in meters, DIST_COAST=vessel's distance to the nearest coastline, and DIST_URBN= vessel's distance to the nearest urban area.
This dataset was created using high-resolution satellite imagery obtained from the RapidEye and Planet Scope satellite constellations 5m/px and 3mpx resolution each. Vessel locations were manually digitized through visual photo interpretation of high-resolution satellite imagery obtained through the Planet Application Program (Planet Labs PBC, Planet Application Program Interface: In Space for Life on Earth, 2018-2023, https://api.planet.com). Visual interpretation and digitization were overseen by Fernando
DOI: 10.17632/wjfxyxwrvt
title: Data for: Hemoglobin trigger and approach to red blood cell transfusions during veno-venous extracorporeal membrane oxygenation: the international TRAIN-ECMO survey

description: Raw data for the article: Hemoglobin trigger and approach to red blood cell transfusions during veno-venous extracorporeal membrane oxygenation: the international TRAIN-ECMO survey.
DOI: 10.6084/m9.figshare.13038257.v2
title: Electrochemical Metrics for Corrosion Resistant Alloys

description: A dataset with multiple sections using different measured corrosion resistance metrics. The six sections include data on various metal alloys with measurements of 1) pitting potential, 2) repassivation potential, 3) crevice corrosion potential, 4) pitting temperature, 5) crevice corrosion temperature, and 6) corrosion potential, corrosion current density, passivation current density, and corrosion rate. The experimental data were collected from 81 publications and include Al- and Fe-based alloys, high entropy alloys (HEAs), and NiCrMo alloys.
DOI: 10.6084/m9.figshare.22557493.v1
title: FT-ICR-MS based untargeted metabolomics of Melilotus officinalis plants grown in different soil treatments

description: This study reports the application of the leguminosae <em>Melilotus officinalis</em> in soil recovery and as a source of bioactive compounds. Plants were cultivated in semiarid soil under four different fertilizer treatments: urban waste compost at 10 t/ha (C-Low) and 20 t/ha (C-High), inorganic fertilizer (Inorg) and a Control (without any fertilizer). Metabolite composition of plants' leaves was analyzed through Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Metabolite extraction was performed from frozen lyophilized leaf samples (eight biological replicates per treatment) with 1 mL of 50% methanol/water (LC–MS grade, Merck). Then, the methanolic sample extract was diluted 1000-fold in methanol and analysed by direct infusion on a 7-Tesla SolariX XR Fourier Transform Ion Cyclotron Resonance Mass Spectrometer, equipped with a ParaCell (FT-ICR-MS, Brüker Daltonics). Leucine enkephalin (YGGFL, Sigma Aldrich) was added as internal standard ([M+H]+ =556.276575 <em>m/z</em>), at a concentration of 0.1 µg/mL, and formic acid (Sigma Aldrich, MS grade) was added at a final concentration of 0.1% (v/v) to all samples. Spectra were acquired in positive electrospray ionization (ESI+), in magnitude mode, with an acquisition size of 4M, and recorded between 100 and 1500 <em>m/z</em>. The accumulation time was 0.1 seconds, and 100 transients were accumulated for each spectrum, zero-filled and apodised (half-sine). Online calibration was performed using the monoisotopic <em>m/z</em> value of leucine enkephalin. The software Bruker Compass data Analysis 5.0 (Brüker Daltonics, Bremen, Germany) was used to process and retrieve the mass lists, considering peaks with a minimum signal-to-noise ratio of 4. The alignment of the raw data from the different replicas for each spectrum dataset was performed with Metaboscape 5.0 (Brüker Daltonics, Bremen, Germany) using T-ReX 2D (MRMS single spectrum) algorithm, with the intensities normalized to the sum of all intensities in each sample. M/z values that appeared only in one analysed sample were removed from the table.
DOI: 10.6084/m9.figshare.28774712.v2
title: U-Net Pretrained Model

description: The model was trained on over 3,000 image-mask pairs using Sentinel-2 imagery and CAL FIRE’s Wildland Fire Threat layer, specifically from the 2017 Lilac Fire in San Diego County, California. The training data was curated from the Pala Mesa region, an area significantly impacted by wildfire activity and containing critical road and rail networks.The model outputs multi-class segmentation masks that classify areas into low-moderate, high, very high, and extreme wildfire threat categories which may support emergency preparedness and response and infrastructure risk analysis. This pretrained version allows users to test the model and generate inferences without requiring a long runtime for training, making it ideal for rapid evaluation, demonstration, or integration into spatial AI workflows.NoteThis model was trained on a region-specific dataset (Lilac Fire, 2017), and generalization to other fires or regions may require fine-tuning.Masks are aligned with CAL FIRE’s threat classification and were processed using 1,000-foot buffers around infrastructure features.Data provided by:California Department of Forestry and Fire Protection (CAL FIRE)European Space Agency (Sentinel-2 via Copernicus Program)U.S. Census Bureau (TIGER/Line Roads)Federal Railroad Administration / Bureau of Transportation Statistics
DOI: 10.6084/m9.figshare.5706244.v11
title: SourceForge

description: Here is my open source collections. <br>
DOI: 10.17632/j36zgxnc5p
title: Instances of "Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty"

description: This data set concerns the experimental instances of the paper "Humanitarian relief distribution with trucks and drones under travel time uncertainty".

We adapt the R101, C101, and RC101 instances of Solomon (1987), which are used to benchmark vehicle routing problems with time windows, with locations randomly scattered over the area (R), clustered in groups of locations (C), and locations both clustered in groups as well as randomly distributed over the area (RC). Besides the Solomon inspired cases, we evaluate two historical disaster cases, namely the 2015 earthquake in Nepal and 2018 tsunami in Indonesia.  The level of uncertainty within an area can differ, e.g., parts close to the path of a hurricane or near the epicenters of earthquake aftershocks are likely to exhibit larger variance in travel time. We created risk matrices for all node pairs.

The real-world cases we consider the disaster areas after the 2015 earthquake in Nepal and the 2018 tsunami in Indonesia. In 2015, a 7.8M earthquake caused major disruption in Nepal. Eleven districts near the capital city Kathmandu were affected the most, where the mountainous surroundings posed challenges to the road transport. We focus on two districts that were significantly disrupted: Nuwakot and Dhading. Based on data collected from a field trip in August 2021 (carried out as part of our research) along multiple municipalities in the affected districts, we composed a set of 84 demand nodes and a depot located in Dhading Besi, the district headquarter of the Dhading district. We marked risk levels for all node pairs, with high risks close to the epicenter, and medium risk nodes up in the mountains. In 2018, an 7.5M undersea earthquake and a tsunami that followed resulted in a massive disruption of the city Palu and surrounding areas around the Palu Bay on the Indonesian island Sulawesi. Data from a displacement tracking matrix (International Organization for Migration 2019) with locally collected data from 2018 allows us to extract a set of 343 demand nodes and a depot at the Palu Airport. We marked the risk levels along the coast line and medium risk levels in areas that experienced soil liquefaction.

For our experiments, we consider two fleet configurations. One fleet with only trucks, and one fleet where 50% of the trucks are replaced by drones. For the instances with 26 nodes, we deploy two vehicles, with the 101 node instances eight vehicles, with the Nepal case six vehicles, and with the Indonesia case 16 vehicles considering the large number of nodes. We assume that a truck has a capacity of 10 units. Considering demands between one and five, a truck can visit at least two and at most 10 nodes. The specifications of the drone are inspired by the MiniFreighter from Wings For Aid. For the experiments, we assume that drones carry one unit of demand, and travel with a constant speed of 120 km/h following Euclidean distances, as their flights are not disrupted by damaged infrastructure.
DOI: 10.6084/m9.figshare.14687631.v1
title: data for figures

description: raw data of multiple phyiscal properties measured to plot the pattern