cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10359283
title: POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance
DOI: 10.5281/zenodo.10359546
title: Data of monthly climate variables and drought indices within continental Chile for 1981-2023

description: The dataset contains derived climatic data from ERA-5 at monthly frequency for continental Chile. The variables are:

Precipitation (pre)
Minimum temperature (tas_min)
Mean temperature (tas)
Maximum temperature (tas_max)
Reference evapotranspiration (pet)
Snow water eqivalent (swe)
Soil volumetric water content at 1m depth (sm)
Besides, the dataset contains the follwoing derived drough indices:

Standardized Precipitation Index (SPI) for 1, 3, 6, 12, 24, and 36 months (spi_1 to spi_36)
Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 3, 6, 12, 24, and 36 months (spei_1 to spei_36)
Evaporative Demand Drought Index (EDDI) for 1, 3, 6, 12, 24, and 36 months (eddi_1 to eddi_36)
Anomaly of cumulative soil moisture at 1m depth (zcSM) for 1, 3, 6, 12, 24, and 36 months (zcsm_1 to zcsm_36)
Anomaly of cumulative NDVI (zcNDVI) for 1, 3, and 6 months (zcndvi1 to zcndvi6)
Snow Water Equivalent Index (SWEI)
DOI: 10.5281/zenodo.10359547
title: Data of monthly climate variables and drought indices within continental Chile for 1981-2023

description: The dataset contains derived climatic data from ERA-5 at monthly frequency for continental Chile. The variables are:

Precipitation (pre)
Minimum temperature (tas_min)
Mean temperature (tas)
Maximum temperature (tas_max)
Reference evapotranspiration (pet)
Snow water eqivalent (swe)
Soil volumetric water content at 1m depth (sm)
Besides, the dataset contains the follwoing derived drough indices:

Standardized Precipitation Index (SPI) for 1, 3, 6, 12, 24, and 36 months (spi_1 to spi_36)
Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 3, 6, 12, 24, and 36 months (spei_1 to spei_36)
Evaporative Demand Drought Index (EDDI) for 1, 3, 6, 12, 24, and 36 months (eddi_1 to eddi_36)
Anomaly of cumulative soil moisture at 1m depth (zcSM) for 1, 3, 6, 12, 24, and 36 months (zcsm_1 to zcsm_36)
Anomaly of cumulative NDVI (zcNDVI) for 1, 3, and 6 months (zcndvi1 to zcndvi6)
Snow Water Equivalent Index (SWEI)
DOI: 10.5281/zenodo.10359503
title: TextMining Dataset

description: Purpose of the Datasets:
These datasets serve as invaluable resources in the domain of information credibility assessment, fact-checking, and deception detection.
liar.csv Dataset
The liar.csv dataset, sourced from Papers With Code, is tailored explicitly for detecting deceptive information. It comprises features aimed at analyzing and identifying falsified or misleading content. The dataset contains various attributes useful for training models and conducting research in deception detection.
factcheck.csv Dataset
The factcheck.csv dataset aggregates information from FactCheck.org and includes columns such as:

author: Identifies the individual or entity responsible for creating or verifying content.
text: Contains the textual information or claim undergoing fact-checking.
source: Indicates the platform or origin of the information.
date: Represents the timestamp or publication date associated with the information.
target: Reflects the result or assessment derived from the fact-checking process regarding the accuracy of the information. This dataset provides valuable insights for assessing factual accuracy and information credibility.
politifact.csv Dataset
Derived from PolitiFact, the politifact.csv dataset encompasses:

id: Unique identifier assigned to each entry within the dataset.
target: Represents the evaluation or rating indicating the truthfulness level of statements (e.g., true, false, mostly true, etc.).
text: Contains the textual statement or claim made by an individual or entity.
name: Denotes the headline or title of the article or statement under assessment.
link: Provides a reference URL or link supporting the context of the statement.
target_numeric: Represents a numerical value corresponding to the truthfulness rating, facilitating computational analysis and modeling.
These datasets collectively offer a rich repository of information crucial for training algorithms, conducting analyses, and exploring the realm of fact-checking, deception detection, and information authenticity assessment.
DOI: 10.5281/zenodo.10359504
title: TextMining Dataset

description: Purpose of the Datasets:
These datasets serve as invaluable resources in the domain of information credibility assessment, fact-checking, and deception detection.
liar.csv Dataset
The liar.csv dataset, sourced from Papers With Code, is tailored explicitly for detecting deceptive information. It comprises features aimed at analyzing and identifying falsified or misleading content. The dataset contains various attributes useful for training models and conducting research in deception detection.
factcheck.csv Dataset
The factcheck.csv dataset aggregates information from FactCheck.org and includes columns such as:

author: Identifies the individual or entity responsible for creating or verifying content.
text: Contains the textual information or claim undergoing fact-checking.
source: Indicates the platform or origin of the information.
date: Represents the timestamp or publication date associated with the information.
target: Reflects the result or assessment derived from the fact-checking process regarding the accuracy of the information. This dataset provides valuable insights for assessing factual accuracy and information credibility.
politifact.csv Dataset
Derived from PolitiFact, the politifact.csv dataset encompasses:

id: Unique identifier assigned to each entry within the dataset.
target: Represents the evaluation or rating indicating the truthfulness level of statements (e.g., true, false, mostly true, etc.).
text: Contains the textual statement or claim made by an individual or entity.
name: Denotes the headline or title of the article or statement under assessment.
link: Provides a reference URL or link supporting the context of the statement.
target_numeric: Represents a numerical value corresponding to the truthfulness rating, facilitating computational analysis and modeling.
These datasets collectively offer a rich repository of information crucial for training algorithms, conducting analyses, and exploring the realm of fact-checking, deception detection, and information authenticity assessment.
DOI: 10.6084/m9.figshare.24790278
title: Prueba2

description: Datos crudos de la primera serie de experimentos de avalanchas de material granular monodisperso sobre una canaleta de 180 cm de largo, con superficie lisa y rugos; tamaño de partícula: ø = –1; ancho de la canaleta de 10 cm; inclinación de la canaleta: 35°; masas totales 10, 15 y 20 kg. Datos de celdas de carga laterales y basales.
DOI: 10.6084/m9.figshare.24790278.v1
title: Prueba2

description: Datos crudos de la primera serie de experimentos de avalanchas de material granular monodisperso sobre una canaleta de 180 cm de largo, con superficie lisa y rugos; tamaño de partícula: ø = –1; ancho de la canaleta de 10 cm; inclinación de la canaleta: 35°; masas totales 10, 15 y 20 kg. Datos de celdas de carga laterales y basales.
DOI: 10.5281/zenodo.10359599
title: OverWatch Match Data

description: A dataset of 61867 matches from OverTrack.gg was loaded into memory. Most matches represent a team of 5 vs. 5, with no possibility for ties. Since tracking matches is volutary, a not insignificant percentage of matches (7.82%) are played against a team of unrated/unknown players. The average number of matchs per unique player is about 2.338, however a decent number of players were tracked for over a hundred matches.
DOI: 10.6084/m9.figshare.24324739
title: A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data

description: Federal administrative data, such as tax data, are invaluable for research, but because of privacy concerns, access to these data is typically limited to select agencies and a few individuals. An alternative to sharing microlevel data is to allow individuals to query statistics without directly accessing the confidential data. This article studies the feasibility of using differentially private (DP) methods to make certain queries while preserving privacy. We also include new methodological adaptations to existing DP regression methods for using new data types and returning standard error estimates. We define feasibility as the impact of DP methods on analyses for making public policy decisions and the queries accuracy according to several utility metrics. We evaluate the methods using Internal Revenue Service data and public-use Current Population Survey data and identify how specific data features might challenge some of these methods. Our findings show that DP methods are feasible for simple, univariate statistics but struggle to produce accurate regression estimates and confidence intervals. To the best of our knowledge, this is the first comprehensive statistical study of DP regression methodology on real, complex datasets, and the findings have significant implications for the direction of a growing research field and public policy. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24324739.v1
title: A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data

description: Federal administrative data, such as tax data, are invaluable for research, but because of privacy concerns, access to these data is typically limited to select agencies and a few individuals. An alternative to sharing microlevel data is to allow individuals to query statistics without directly accessing the confidential data. This article studies the feasibility of using differentially private (DP) methods to make certain queries while preserving privacy. We also include new methodological adaptations to existing DP regression methods for using new data types and returning standard error estimates. We define feasibility as the impact of DP methods on analyses for making public policy decisions and the queries accuracy according to several utility metrics. We evaluate the methods using Internal Revenue Service data and public-use Current Population Survey data and identify how specific data features might challenge some of these methods. Our findings show that DP methods are feasible for simple, univariate statistics but struggle to produce accurate regression estimates and confidence intervals. To the best of our knowledge, this is the first comprehensive statistical study of DP regression methodology on real, complex datasets, and the findings have significant implications for the direction of a growing research field and public policy. Supplementary materials for this article are available online.
DOI: 10.6073/pasta/db292731860501bf3395f6f57a8ce6e8
title: Soil moisture and snowdepth measurements in the Black Sand experiment for East Knoll, Audubon, Lefty, Soddie and Trough, 2018 - 2023.

description: The purpose of the Black Sand experiment is to measure treatment
 effects on date of snowmelt on Niwot Ridge. Five sites with paired
 plots (treatment and control) were implemented across Niwot as part
 of the extended summer research program in order to understand the
 effects of earlier snowmelt. This dataset contains measurements of
 snowdepth throughout the melt season, manual measurements of
 volumetric water content and temperature data as an indication of
 snowmelt timing.
DOI: 10.5281/zenodo.10359600
title: OverWatch Match Data

description: A dataset of 61867 matches from OverTrack.gg was loaded into memory. Most matches represent a team of 5 vs. 5, with no possibility for ties. Since tracking matches is volutary, a not insignificant percentage of matches (7.82%) are played against a team of unrated/unknown players. The average number of matchs per unique player is about 2.338, however a decent number of players were tracked for over a hundred matches.
DOI: 10.5281/zenodo.10359644
title: TMoTibhW02-2020
DOI: 10.5281/zenodo.10359643
title: TMoTibhW02-2020
DOI: 10.21985/n2-qsxe-g070
title: Probe accuracy defined by frameshifts
DOI: 10.5066/p9xdakof
title: Total PCB concentrations in sediment, water, macroinvertebrates and spiders and the lower Ottawa River (Toledo, OH) between 2009-2015

description: Polychlorinated biphenyl (PCB) concentrations were measured in the lower Ottawa River in 2009 before dredging and after dredging in 2011, 2012, 2013, and 2015. Media collected for analysis included sediment, water, macroinvertebrates, and tetragnathid spiders at 18 stations. At each station 16 surface sediment core samples (top 15 cm) were collected and composited together with a mechanical mixer to achieve a homogeneous composite sample. Mid-depth water column samples were collected using a Van Dorn, Niskin or similar type sampler. Artificial substrate samplers (Hester Dendys) were used to collect aquatic macroinvertebrates. Riparian spiders (family Tetragnathidae) were collected from their webs by gloved hand at night within 1 meter of the shoreline at each sampling station. All extracts were analyzed for 121 PCB congeners via gas chromotography mass spectroscopy in the selected ion monitoring mode based on U.S. EPA Method 1668A and quantified using the method of internal standards.
DOI: 10.5281/zenodo.10359653
title: TMoTibhL01-LD-2021
DOI: 10.5281/zenodo.10359654
title: TMoTibhL01-LD-2021
DOI: 10.5281/zenodo.10307338
title: Spectroradiometry with sub-microsecond time resolution using multianode photomultiplier tube assemblies

description: Raw data (e.g. MA-PMT timeseries), and processed data (e.g. temperature and emissivity fits) for the submitted manuscript. The python script shows a simple example of how to load and plot data from the "..._processed.json" files. The spreadsheet called "Descriptions of json file parameters" explains the meaning of parameters in all the json files for standard experiments. Parameters in "non-standard" json files (e.g. system response .json files; Fig18_accuracy-summary.json) are intended to be self-explanatory.
DOI: 10.5281/zenodo.10307340
title: Spectroradiometry with sub-microsecond time resolution using multianode photomultiplier tube assemblies

description: Raw data (e.g. MA-PMT timeseries), and processed data (e.g. temperature and emissivity fits) for the submitted manuscript. The python script shows a simple example of how to load and plot data from the "..._processed.json" files. The spreadsheet called "Descriptions of json file parameters" explains the meaning of parameters in all the json files for standard experiments. Parameters in "non-standard" json files (e.g. system response .json files; Fig18_accuracy-summary.json) are intended to be self-explanatory.
DOI: 10.5281/zenodo.10359661
title: TMoTibhW03-2022
DOI: 10.5281/zenodo.10359662
title: TMoTibhW03-2022
DOI: 10.48432/fmxotw
title: LiDAR survey on 1200 hectares in Feliz Natal I, Mato Grosso, Brasil in 2018.

description: The LiDAR data Feliz Natal (FNA_A01_2018_LiDAR) refers to the survey carried out in Feliz Natal municipality, Mato Grosso state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.34943/68431f8e-fd74-47d0-ab87-177a7bff4136
title: Endeavour South Acoustic Doppler Current Profiler 75 kHz Deployed 2012-06-14

description: The RDI Workhorse Long Ranger ADCP 75 kHz (3867) was deployed on 2012-06-14 at Endeavour South. This south section of the Endeavour Hydrothermal Vents includes two moorings to monitor the regional circulation. This device is a Acoustic Doppler Current Profiler 75 kHz. Acoustic Doppler Current Profilers (ADCP) are hydroacoustic instruments, similar to sonars. ADCPs measure current speed and direction at multiple predetermined depths simultaneously. ADCPs use the Doppler effect of sound waves that are scattered by particles in seawater over a depth range. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/cbe303f2-6057-4eea-b41b-289019911531
title: Endeavour South Acoustic Doppler Current Profiler 75 kHz Deployed 2012-06-14

description: The RDI Workhorse Long Ranger ADCP 75 kHz (3867) was deployed on 2012-06-14 at Endeavour South. This south section of the Endeavour Hydrothermal Vents includes two moorings to monitor the regional circulation. This device is a Acoustic Doppler Current Profiler 75 kHz. Acoustic Doppler Current Profilers (ADCP) are hydroacoustic instruments, similar to sonars. ADCPs measure current speed and direction at multiple predetermined depths simultaneously. ADCPs use the Doppler effect of sound waves that are scattered by particles in seawater over a depth range. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.10359665
title: TMoTibhW04-2023
DOI: 10.5281/zenodo.10359666
title: TMoTibhW04-2023
DOI: 10.25345/c5f18sr7p
title: MassIVE MSV000093636 - Mucus production, host-microbiome interactions, hormone sensitivity, and innate immune responses modeled in human cervix chips
title: Modulation of mucus production by the human endo- and ecto-cervical epithelium by steroid hormones and associated interactions with commensal microbiome play a central role in the physiology and pathophysiology of the female reproductive tract. However, most of our knowledge about these interactions is based on results from animal studies or in vitro models that fail to faithfully mimic the mucosal environment of the human cervix. Here we describe microfluidic organ-on-a-chip (Organ Chip) models of the human cervical mucosa that recreate the cervical epithelial-stromal interface with a functional epithelial barrier and produce abundant mucus that has compositional, biophysical, and hormone-responsive properties similar to the living cervix. Application of continuous fluid flow to chips lined primary human cervical epithelial cells from a commercial source that contained a mixture of primary human ecto- and endo-cervical epithelial cells promoted preferential expression of the ecto-cervical phenotype, whereas use of periodic flow including periods of stasis induced endo-cervical specialization. When the periodic flow Cervix Chips were co-cultured with living Lactobacillus crispatus and Gardnerella vaginalis bacterial communities to respectively mimic the effects of human host interactions with optimal (healthy) or non-optimal (dysbiotic) microbiome associated with an ascending infection in the female reproductive tract, significant differences in tissue innate immune responses, barrier function, cell viability and protein profile, and mucus composition were detected reminiscent of those observed in vivo. Thus, these Organ Chip models of human cervix provide a physiologically relevant experimental in vitro model to study cervical mucus physiology and its role in human host-microbiome interactions as well as a potential preclinical testbed for development of therapeutic interventions to enhance women's health.
DOI: 10.17909/vm7n-vn41
title: BH1 IR photometry 

description: N6946-BH1 is the first plausible candidate for a failed supernova (SN), a peculiar event in which a massive star disappears without the expected bright SN, accompanied by collapse into a black hole (BH). Following a luminous outburst in 2009, the source experienced a significant decline in optical brightness, while maintaining a persistent infrared (IR) presence. While it was proposed to be a potential failed SN, such behavior has been observed in SN impostor events in nearby galaxies. Here, we present late-time observations of BH1, taken 14 years after disappearance, using JWST's NIRCam and MIRI instruments to probe a never-before-observed region of the object's spectral energy distribution. We show for the first time that all previous observations of BH1 (pre- and post-disappearance) are actually a blend of at least 3 sources. In the near-IR, BH1 is notably fainter than the progenitor but retains similar brightness to its state in 2017. In the mid-IR, the flux appears to have brightened compared to the inferred fluxes from the best-fitting progenitor model. The total luminosity of the source is between 13 - 25% that of the progenitor. We also show that the IR SED appears consistent with PAH features that arise when dust is illuminated by near-ultraviolet radiation. At present, the interpretation of N6946-BH1 remains uncertain. The observations match expectations for a stellar merger, but theoretical ambiguity in the failed SN hypothesis makes it hard to dismiss.
DOI: 10.26208/fsy8-h855
title: Eddy Covariance High-Frequency Data for Agricultural Sites near Indianapolis, Indiana (US-INd, US-INe, US-INi, US-INj, US-INn, US-INp)

description: As part of the Indianapolis Flux (INFLUX) project six flux towers were deployed to measure agricultural fields surrounding Indianapolis. Each tower is of short stature, standing roughly three meters above the ground. These towers were deployed to understand better the vegetation surrounding Indianapolis. 

The time span for these data sets are US-INd: August 2018 to November 2018, US-INe: September 2017 to October 2020, US-INi: April 2019 to May 2022, US-INj: May 2020 to March 2023, US-INn: April 2019 to October 2021, US-INp: May 2020 to April 2021. The data files will be updated approximately yearly for those sites still in operation. 

US-INd was planted with a mixture of corn and soy for 2018.  US-INe was planted with corn in the growing season of 2018, soy for 2019 and corn for 2020.  US-INi was planted with soy in the growing season of 2019, corn in 2021.   US-INj was planted with corn in the growing season of 2020 and corn in 2022.  US-INn was planted with corn in the growing season of 2019 and corn in 2021.  US-INp was planted with corn in the growing season of 2020. 

These data are .ghg files containing thirty-minute periods of the 10Hz measurements from the sonic anemometer and infrared gas analyzer.  For more information, see https://sites.psu.edu/influx/site-information/.
DOI: 10.5066/p9mehm63
title: Continuous Water Quality, Suspended Solids, and Enterococci Data from the Harlem River, Bronx, New York, Jan 2021- Sept 2021

description: This data set contains continuous water-surface elevation and water-quality (temperature, specific conductance, salinity, and turbidity) data recorded at 6- and 15-minute intervals, respectively, from two sites in the Bronx on the Harlem River -- Roberto Clemente State Park and Mill Pond Park. Water elevation was monitored every second to detect changes indicative of boat wakes expected to resuspend bed sediment from nearby alcoves. Boat wake detection triggered the collection of 1-second interval water elevation and 1-minute interval turbidity data. In addition to continuous data, grab samples for fecal indicator bacteria (Enterococci) and total suspended solids were collected weekly from - March to September, 2021.