cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21502999
title: Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams

description: The age of Internet of Things (IoT) has witnessed the rapid development of modern data acquisition devices and communicating-actuating networks, which enables the generation of big data streams shared across platforms for remote and efficient decision making of many critical systems. The monitoring of big data streams remains a challenging task in various practical applications mainly due to their complexity in interrelationships, large volume, and high velocity, which places prohibitive demands on monitoring methodologies and resources. To tackle the challenges of monitoring unexchangeable and correlated big data streams with only partial observations available under resource constraints, we propose a method by incorporating spatial rank-based statistics with effective data augmentation techniques for the online unobservable data streams that can analytically inform the monitoring and sampling decisions based only on partially observed data streams. By exploiting historical data, the proposed method preserves strong descriptive power of general big data streams under partial observations and can explicitly use the correlation among data streams, and thus allows effective monitoring and equitable sampling over general heterogeneous and correlated big data streams, which is free of simplified assumptions (e.g., exchangeability) compared to existing methods. Theoretical investigations are carried out to evaluate the effectiveness of the augmentation statistics as well as the sampling strategy, which guarantee the superiority of the sampling performance over existing methods. Simulations under various scenarios and two real case studies are also conducted to evaluate and validate the performance of the proposed method.
DOI: 10.6084/m9.figshare.21502999.v2
title: Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams

description: The age of Internet of Things (IoT) has witnessed the rapid development of modern data acquisition devices and communicating-actuating networks, which enables the generation of big data streams shared across platforms for remote and efficient decision making of many critical systems. The monitoring of big data streams remains a challenging task in various practical applications mainly due to their complexity in interrelationships, large volume, and high velocity, which places prohibitive demands on monitoring methodologies and resources. To tackle the challenges of monitoring unexchangeable and correlated big data streams with only partial observations available under resource constraints, we propose a method by incorporating spatial rank-based statistics with effective data augmentation techniques for the online unobservable data streams that can analytically inform the monitoring and sampling decisions based only on partially observed data streams. By exploiting historical data, the proposed method preserves strong descriptive power of general big data streams under partial observations and can explicitly use the correlation among data streams, and thus allows effective monitoring and equitable sampling over general heterogeneous and correlated big data streams, which is free of simplified assumptions (e.g., exchangeability) compared to existing methods. Theoretical investigations are carried out to evaluate the effectiveness of the augmentation statistics as well as the sampling strategy, which guarantee the superiority of the sampling performance over existing methods. Simulations under various scenarios and two real case studies are also conducted to evaluate and validate the performance of the proposed method.
DOI: 10.6084/m9.figshare.20454435
title: RSmDB: a global database of rodents and shrews-associated microbial communities from metagenomes

description:   The rodent- and shrew-associated microbial communities database (RSmDB) is a metagenomic resource to investigate the microbial communities of rodents and shrews.
DOI: 10.6084/m9.figshare.20454490.v1
title: Additional file 8 of A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken

description: Additional file 8. The phenotypic data used in this study.
DOI: 10.6084/m9.figshare.20454490
title: Additional file 8 of A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken

description: Additional file 8. The phenotypic data used in this study.
DOI: 10.5281/zenodo.10619365
title: tandanus_tandanus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.10619366
title: tandanus_tandanus_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.20454541
title: Additional file 1 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 1.
DOI: 10.6084/m9.figshare.20454541.v1
title: Additional file 1 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 1.
DOI: 10.5281/zenodo.8340471
title: The corona of a fully convective star with a near-polar flare

description: Raw XMM-Newton EPIC data, data reduction scripts for XMM-SAS, and reduced images and spectra extracted with XSPEC. The observations include the X-ray emission of TIC 277539431, a rapidly rotating M7 dwarf star that produced a polar flare in 2021, observed by the Transiting Exoplanet Survey Satellite (see Ilin et al. 2021).

Publications based on this data set will be linked as they appear.
description: This dataset was made possible by the Deutsche Luft- und Raumfahrtgesellschaft (FKZ 50 OR 2209, project X-ray Loops). This work is based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA.
DOI: 10.5281/zenodo.8340472
title: The corona of a fully convective star with a near-polar flare

description: Raw XMM-Newton EPIC data, data reduction scripts for XMM-SAS, and reduced images and spectra extracted with XSPEC. The observations include the X-ray emission of TIC 277539431, a rapidly rotating M7 dwarf star that produced a polar flare in 2021, observed by the Transiting Exoplanet Survey Satellite (see Ilin et al. 2021).

Publications based on this data set will be linked as they appear.
description: This dataset was made possible by the Deutsche Luft- und Raumfahrtgesellschaft (FKZ 50 OR 2209, project X-ray Loops). This work is based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA.
DOI: 10.6084/m9.figshare.19102103
title: Dataset related to "Can high-rate GNSS Capture Supershear Rupture?" submitted to Geophysical Research Letters.

description: This dataset 5 folders related to "Can high-rate GNSS Capture Supershear Rupture?" submitted to GRL by Xiao et. al (2024). They are:High-rate GNSS: The high-rate GNSS waveforms we used in the inversionInSAR: The InSAR LOS offsets we used in the inversionSlip model: The folder lists the slip predicted by our preferred Maoduo earthquake model at the center of each subfault.Static GNSS: The static coseismic GNSS offsets we used in the inversionStrong motions: The strong motion waveforms we used in the inversion
DOI: 10.6084/m9.figshare.19102103.v1
title: The Source Characteristic of 2021 M 7.3 Maduo Earthquake: A Supershear Rupture on an Extra-Slow slip Fault

description: This dataset include the observations used in "The Source Characteristic of 2021 M 7.3 Maduo Earthquake: A Supershear Rupture on an Extra-Slow slip Fault" submitted to GRL by Zhuohui Xiao et. al (2022)
DOI: 10.6084/m9.figshare.19102103.v2
title: Dataset related to "Can high-rate GNSS Capture Supershear Rupture?" submitted to Geophysical Research Letters.

description: This dataset 5 folders related to "Can high-rate GNSS Capture Supershear Rupture?" submitted to GRL by Xiao et. al (2024). They are:High-rate GNSS: The high-rate GNSS waveforms we used in the inversionInSAR: The InSAR LOS offsets we used in the inversionSlip model: The folder lists the slip predicted by our preferred Maoduo earthquake model at the center of each subfault.Static GNSS: The static coseismic GNSS offsets we used in the inversionStrong motions: The strong motion waveforms we used in the inversion
DOI: 10.5281/zenodo.10580223
title: RGBD_DATASET

description: The dataset is defined by a set of detailed technical specifications intended to capture high-quality data in a grapevine setting. The Intel Realsense D435 and the ORBBEC ASTRA sensors were used in this dataset, both of which were positioned 850 mm above ground and approximately 725 mm from the vine plants. The Intel Realsense D435 takes RGB images with a resolution of 1920 x 1080 pixels and depth information at 1280 x 720 pixels. This sensor captured 300 consecutive single-shot images while mounted on a tripod on the ground. Furthermore, a continuous stream of images at 30 frames per second (fps) was obtained, yielding approximately 3000 images while the sensor was moved by a human operator. The ORBBEC ASTRA, which had a resolution of 640 x 480 pixels for RGB and depth, used a similar operational setup, producing a continuous stream of images at 30 fps while being moved by a human operator. These technical details highlight the dataset's precise design, resulting in a diverse collection of static and dynamic images suitable for a variety of applications, including grape detection and analysis in agricultural contexts. All of the data were collected at Ktima Gerovassiliou in Epanomi, Thessaloniki.

Below, there is a folder containing the stationary images and a sample folder containing the moving images of the dataset. For the full dataset please contact Stefanos Papadam (sgpapadam@iti.gr), Ioannis Mariolis (ymariolis@iti.gr), Georgia Peleka (gpeleka@iti.gr).
DOI: 10.5281/zenodo.10580224
title: RGBD_DATASET

description: The dataset is defined by a set of detailed technical specifications intended to capture high-quality data in a grapevine setting. The Intel Realsense D435 and the ORBBEC ASTRA sensors were used in this dataset, both of which were positioned 850 mm above ground and approximately 725 mm from the vine plants. The Intel Realsense D435 takes RGB images with a resolution of 1920 x 1080 pixels and depth information at 1280 x 720 pixels. This sensor captured 300 consecutive single-shot images while mounted on a tripod on the ground. Furthermore, a continuous stream of images at 30 frames per second (fps) was obtained, yielding approximately 3000 images while the sensor was moved by a human operator. The ORBBEC ASTRA, which had a resolution of 640 x 480 pixels for RGB and depth, used a similar operational setup, producing a continuous stream of images at 30 fps while being moved by a human operator. These technical details highlight the dataset's precise design, resulting in a diverse collection of static and dynamic images suitable for a variety of applications, including grape detection and analysis in agricultural contexts. All of the data were collected at Ktima Gerovassiliou in Epanomi, Thessaloniki.

Below, there is a folder containing the stationary images and a sample folder containing the moving images of the dataset. For the full dataset please contact Stefanos Papadam (sgpapadam@iti.gr), Ioannis Mariolis (ymariolis@iti.gr), Georgia Peleka (gpeleka@iti.gr).
DOI: 10.25318/3810017001-eng
title: Coastal population and dwellings by elevation and distance from coastline

description: Dwelling and population counts in elevation classes within 10Km, 5Km and 1Km of the coastline by ecozone, ecoprovince, ecoregion and ecodistrict for every fifth year starting with 2016.
DOI: 10.6084/m9.figshare.20454547
title: Additional file 3 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 3.
DOI: 10.6084/m9.figshare.20454547.v1
title: Additional file 3 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 3.
DOI: 10.6084/m9.figshare.20454550
title: Additional file 4 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 4.
DOI: 10.5281/zenodo.6319808
title: ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions

description: Datasets supporting the publication 'ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions': catalyst evaluation data (Excel), XRD (Origin), crystallite sizes, Cu surface area, CO2 uptake, H2-TPR, CO2-TPD, CO-DRIFTS profiles (CSV)
DOI: 10.6084/m9.figshare.20454550.v1
title: Additional file 4 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 4.
DOI: 10.6084/m9.figshare.20454553
title: Additional file 5 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 5.
DOI: 10.6084/m9.figshare.20454553.v1
title: Additional file 5 of High-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth

description: Additional file 5.
DOI: 10.6084/m9.figshare.9968876
title: miR-342-5p inhibits osteosarcoma cell growth, migration, invasion, and sensitivity to Doxorubicin through targeting Wnt7b

description: Osteosarcoma (OS) accounts for 9 percent of cancer-related deaths in young people. The PI3K/Akt signaling, a well-known carcinogenic signaling pathway in human cancer, cooperates with other signaling pathways such as Wnt signaling to promote cancer progression. Wnt7b, as a transforming member of the Wnt family, could activate mTORC1 through PI3K-AKT signaling and is upregulated in OS. In the present study, we found that miR-342-5p inhibits Wnt7b expression via direct binding to Wnt7b 3′-UTR. miR-342-5p overexpression remarkably suppressed the viability and invasion while enhanced the apoptosis of OS cells; meanwhile, Wnt7b, β-catenin, c-myc, and cyclin D1 proteins were reduced while E-cadherin protein showed to be increased. Consistent with its expression pattern, Wnt7b exerted oncogenic effects on OS cells. Wnt7b could significantly attenuate the impacts of miR-342-5p. In conclusion, we demonstrated a miR-342-5p/Wnt7b axis that regulates the capacity of OS cells to proliferate and to invade through Wnt/β-catenin signaling. The miR-342-5p/Wnt7b axis might be novel targets for OS targeted therapy, which needs further in vivo and clinical investigations.
DOI: 10.6084/m9.figshare.9968876.v1
title: miR-342-5p inhibits osteosarcoma cell growth, migration, invasion, and sensitivity to Doxorubicin through targeting Wnt7b

description: Osteosarcoma (OS) accounts for 9 percent of cancer-related deaths in young people. The PI3K/Akt signaling, a well-known carcinogenic signaling pathway in human cancer, cooperates with other signaling pathways such as Wnt signaling to promote cancer progression. Wnt7b, as a transforming member of the Wnt family, could activate mTORC1 through PI3K-AKT signaling and is upregulated in OS. In the present study, we found that miR-342-5p inhibits Wnt7b expression via direct binding to Wnt7b 3′-UTR. miR-342-5p overexpression remarkably suppressed the viability and invasion while enhanced the apoptosis of OS cells; meanwhile, Wnt7b, β-catenin, c-myc, and cyclin D1 proteins were reduced while E-cadherin protein showed to be increased. Consistent with its expression pattern, Wnt7b exerted oncogenic effects on OS cells. Wnt7b could significantly attenuate the impacts of miR-342-5p. In conclusion, we demonstrated a miR-342-5p/Wnt7b axis that regulates the capacity of OS cells to proliferate and to invade through Wnt/β-catenin signaling. The miR-342-5p/Wnt7b axis might be novel targets for OS targeted therapy, which needs further in vivo and clinical investigations.
DOI: 10.5281/zenodo.10566868
title: Light curves for variable, point-like microlensing, and extended objects microlensing sources with regular cadence and OGLE-II timestamps cadence.

description: This is the dataset used in the paper Microlensing signatures of extended dark objects using machine learning, which should be read for more details, and the code repository for the simulation code.

This dataset comprises 600,000 light curves designed for the detection of microlensing events. These curves are categorised into six classes: Cataclysmic Variables (CV), RR Lyrae and Cepheid Variables (VARIABLE), Mira Long-Period variable (LPV), Point-like Microlensing (ML), Boson Stars (BS), and NFW Subhalos (NFW).

The dataset includes simulated light curves for each class, with 100,000 instances per class. ML light curves are simulated using MicroLIA, while BS and NFW light curves were simulated using the respective mass profiles first computed here. Selection criteria, including a minimum magnification of 1.34, were applied to mimic a survey selection. The light curves have magnitudes between 15 and 20, incorporate Gaussian noise, and were generated with two cadence scenarios: OGLE-II timestamps and Regular Daily Cadence. For the extended microlensing sources (BS and NFW), mass profiles depend on a parameter, τₘ, sampled logarithmically from a uniform distribution. The minimal impact parameter, u₀, is sampled differently for each microlensing source class. A total of 148 features are computed for each light curve, encompassing statistics and derivatives of the time series.

The dataset has 189 columns (see 'columns.txt' file), grouped by type identified by a prefix:



'lc' columns: light curve.

'gen' columns: generation parameters (metadata).

'sim' columns: simulation parameters (metadata).

'feat' columns: light curve time series features. See MicroLIA (and respective paper) for more details. Features computed on the derivative time series are marked with suffix 'deriv'.


The dataset files are stored in 'parquet' format, which can be read in python using 'pandas' by installing the 'parquet' optional depence (i.e. 'pip install pandas[parquet]').
DOI: 10.5281/zenodo.10566869
title: Light curves for variable, point-like microlensing, and extended objects microlensing sources with regular cadence and OGLE-II timestamps cadence.

description: This is the dataset used in the paper Microlensing signatures of extended dark objects using machine learning, which should be read for more details, and the code repository for the simulation code.

This dataset comprises 600,000 light curves designed for the detection of microlensing events. These curves are categorised into six classes: Cataclysmic Variables (CV), RR Lyrae and Cepheid Variables (VARIABLE), Mira Long-Period variable (LPV), Point-like Microlensing (ML), Boson Stars (BS), and NFW Subhalos (NFW).

The dataset includes simulated light curves for each class, with 100,000 instances per class. ML light curves are simulated using MicroLIA, while BS and NFW light curves were simulated using the respective mass profiles first computed here. Selection criteria, including a minimum magnification of 1.34, were applied to mimic a survey selection. The light curves have magnitudes between 15 and 20, incorporate Gaussian noise, and were generated with two cadence scenarios: OGLE-II timestamps and Regular Daily Cadence. For the extended microlensing sources (BS and NFW), mass profiles depend on a parameter, τₘ, sampled logarithmically from a uniform distribution. The minimal impact parameter, u₀, is sampled differently for each microlensing source class. A total of 148 features are computed for each light curve, encompassing statistics and derivatives of the time series.

The dataset has 189 columns (see 'columns.txt' file), grouped by type identified by a prefix:



'lc' columns: light curve.

'gen' columns: generation parameters (metadata).

'sim' columns: simulation parameters (metadata).

'feat' columns: light curve time series features. See MicroLIA (and respective paper) for more details. Features computed on the derivative time series are marked with suffix 'deriv'.


The dataset files are stored in 'parquet' format, which can be read in python using 'pandas' by installing the 'parquet' optional depence (i.e. 'pip install pandas[parquet]').
DOI: 10.6084/m9.figshare.9968876.v3
title: miR-342-5p inhibits osteosarcoma cell growth, migration, invasion, and sensitivity to Doxorubicin through targeting Wnt7b

description: Osteosarcoma (OS) accounts for 9 percent of cancer-related deaths in young people. The PI3K/Akt signaling, a well-known carcinogenic signaling pathway in human cancer, cooperates with other signaling pathways such as Wnt signaling to promote cancer progression. Wnt7b, as a transforming member of the Wnt family, could activate mTORC1 through PI3K-AKT signaling and is upregulated in OS. In the present study, we found that miR-342-5p inhibits Wnt7b expression via direct binding to Wnt7b 3′-UTR. miR-342-5p overexpression remarkably suppressed the viability and invasion while enhanced the apoptosis of OS cells; meanwhile, Wnt7b, β-catenin, c-myc, and cyclin D1 proteins were reduced while E-cadherin protein showed to be increased. Consistent with its expression pattern, Wnt7b exerted oncogenic effects on OS cells. Wnt7b could significantly attenuate the impacts of miR-342-5p. In conclusion, we demonstrated a miR-342-5p/Wnt7b axis that regulates the capacity of OS cells to proliferate and to invade through Wnt/β-catenin signaling. The miR-342-5p/Wnt7b axis might be novel targets for OS targeted therapy, which needs further in vivo and clinical investigations.
DOI: 10.6084/m9.figshare.9968876.v2
title: miR-342-5p inhibits osteosarcoma cell growth, migration, invasion, and sensitivity to Doxorubicin through targeting Wnt7b

description: Osteosarcoma (OS) accounts for 9 percent of cancer-related deaths in young people. The PI3K/Akt signaling, a well-known carcinogenic signaling pathway in human cancer, cooperates with other signaling pathways such as Wnt signaling to promote cancer progression. Wnt7b, as a transforming member of the Wnt family, could activate mTORC1 through PI3K-AKT signaling and is upregulated in OS. In the present study, we found that miR-342-5p inhibits Wnt7b expression via direct binding to Wnt7b 3′-UTR. miR-342-5p overexpression remarkably suppressed the viability and invasion while enhanced the apoptosis of OS cells; meanwhile, Wnt7b, β-catenin, c-myc, and cyclin D1 proteins were reduced while E-cadherin protein showed to be increased. Consistent with its expression pattern, Wnt7b exerted oncogenic effects on OS cells. Wnt7b could significantly attenuate the impacts of miR-342-5p. In conclusion, we demonstrated a miR-342-5p/Wnt7b axis that regulates the capacity of OS cells to proliferate and to invade through Wnt/β-catenin signaling. The miR-342-5p/Wnt7b axis might be novel targets for OS targeted therapy, which needs further in vivo and clinical investigations.
DOI: 10.5281/zenodo.6303502
title: ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions

description: Datasets supporting the publication 'ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions': catalyst evaluation data (Excel), performance, stability, crystallite sizes, XRD, H2-TPR, CO2-TPD, N2O titration, CO2 chemisorption, CO-DRIFTS (Origin)
DOI: 10.5281/zenodo.6303501
title: ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions

description: Datasets supporting the publication 'ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions': catalyst evaluation data (Excel), XRD (Origin), crystallite sizes, Cu surface area, CO2 uptake, H2-TPR, CO2-TPD, CO-DRIFTS profiles (CSV)
DOI: 10.6084/m9.figshare.19930368
title: Additional file 4 of Comparative analysis of the gut microbiota composition between knee osteoarthritis and Kashin-Beck disease in Northwest China

description: Additional file 4: Table S2.