cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28144058.v2
title: Stochastic Gradient Descent-based Inference for Dynamic Network Models with Attractors

description: In Coevolving Latent Space Networks with Attractors (CLSNA) models, nodes in a latent space represent social actors, and edges indicate their dynamic interactions. Attractors are added at the latent level to capture the notion of attractive and repulsive forces between nodes, borrowing from dynamical systems theory. However, CLSNA reliance on MCMC estimation makes scaling difficult, and the requirement for nodes to be present throughout the study period limit practical applications. We address these issues by (i) introducing a Stochastic gradient descent (SGD) parameter estimation method, (ii) developing a novel approach for uncertainty quantification using SGD, and (iii) extending the model to allow nodes to join and leave over time. Simulation results show that our extensions result in little loss of accuracy compared to MCMC, but can scale to much larger networks. We apply our approach to the longitudinal social networks of members of US Congress on the social media platform X. Accounting for node dynamics overcomes selection bias in the network and uncovers uniquely and increasingly repulsive forces within the Republican Party. Supplemental materials for the article are available online.
DOI: 10.6084/m9.figshare.28143431
title: Inferences in Multinomial Dynamic Mixed Logit Models

description: In this article we propose a general multinomial dynamic mixed logits model which explains how a multinomial/categorical response at a given time can be affected by (a) an individual’s categorical fixed covariates, (b) certain category prone random effects, and (c) an individual’s past multinomial responses. This model may be considered as a generalization of the (a) existing multinomial dynamic fixed models to the mixed model setup with category prone random effects; or (b) existing standard random effects based multinomial dynamic mixed models involving past binary responses to the complete multinomial dynamic (depending on past multinomial) setup, or (c) existing multinomial mixed models to the multinomial longitudinal mixed model setup. We use a conditional fixed effects based likelihood approach for estimation of the parameters. An intensive simulation study is carried out to examine the finite sample performance of the estimators under the general dynamic mixed models, as well as under various specialized models. The proposed model and estimation methodology is also illustrated with a real life longitudinal survey data on health, aging and retirement in Europe. Asymptotic properties such as consistency of the conditional fixed effects based likelihood estimators of the main fixed effects based regression parameters are studied in details. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28143381
title: Semiparametric Regression Analysis of Interval-Censored Multi-State Data with An Absorbing State

description: In studies of chronic diseases, the health status of a subject can often be characterized by a finite number of transient disease states and an absorbing state, such as death. The times of transitions among the transient states are ascertained through periodic examinations and thus interval-censored. The time of reaching the absorbing state is known or right-censored, with the transient state at the previous instant being unobserved. In this article, we provide a general framework for analyzing such multi-state data. We formulate the effects of potentially time-dependent covariates on the multi-state disease process through semiparametric proportional intensity models with random effects. We combine nonparametric maximum likelihood estimation with sieve estimation and develop a stable expectation-maximization algorithm. We establish the asymptotic properties of the proposed estimators through novel use of modern empirical process theory, sieve estimation theory, and semiparametric efficiency theory. In addition, we dynamically predict future states and survival time using the evolving disease history. Finally, we assess the performance of the proposed methods through extensive simulation studies and provide an illustration with a cardiac allograft vasculopathy study. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.21227/nwxe-ct19
title: 15 Year Evolution of Smart NICs

description: Network Interface Cards (NICs) are one of the key enablers of the modern-day Internet. They serve as gateways for connecting computing devices to networks for the exchange of data with other devices. Recently, the pervasive nature of Internet-enabled devices coupled with the growing demands for faster network access have necessitated the enhancement of NICs to Smart NICs (SNICs), capable of processing enormous volumes of data at near real-time speed. These devices are fitted with Compute Elements that allow them to handle several tasks, thus relieve their host's CPUs of these workloads. This dataset on SNICs is curated from 370 articles published in IEEE Xplore, over the past 15 years, from 2010 to 2024. It contains data about SNIC types, models, manufacturers, research foci, and application use cases.
DOI: 10.5517/ccdc.csd.cc2f0xky
title: CSD 2235210: Experimental Crystal Structure Determination

description: Related Article: Laidong Zhou, J. David Bazak, Baltej Singh, Chang Li, Abdeljalil Assoud, Nancy M. Washton, Vijayakumar Murugesan, Linda F. Nazar|2023|Angew.Chem.,Int.Ed.|62|e202300404|doi:10.1002/anie.202300404
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f0xlz
title: CSD 2235211: Experimental Crystal Structure Determination

description: Related Article: Laidong Zhou, J. David Bazak, Baltej Singh, Chang Li, Abdeljalil Assoud, Nancy M. Washton, Vijayakumar Murugesan, Linda F. Nazar|2023|Angew.Chem.,Int.Ed.|62|e202300404|doi:10.1002/anie.202300404
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.14939003
title: Tomato spotted wilt virus facilitates non-vector spider mite species (Tetranychus urticae and Tetranychus evansi) on whole tomato plants

description: Available dataset for the manuscipt titled "Tomato spotted wilt virus facilitates non-vector spider mite species (Tetranychus urticae and Tetranychus evansi) on whole tomato plants" accepted in the journal of Plant-Arthropod-Microbe Interactions.
DOI: 10.5281/zenodo.14939002
title: Tomato spotted wilt virus facilitates non-vector spider mite species (Tetranychus urticae and Tetranychus evansi) on whole tomato plants

description: Available dataset for the manuscipt titled "Tomato spotted wilt virus facilitates non-vector spider mite species (Tetranychus urticae and Tetranychus evansi) on whole tomato plants" accepted in the journal of Plant-Arthropod-Microbe Interactions.
DOI: 10.6073/pasta/5f2d04344563192ae94c580a584afbbd
title: Dissolved organic carbon (DOC) concentrations in glacial meltwater streams, McMurdo Dry Valleys, Antarctica (1990-2023, ongoing)

description: As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic aqueous geochemical sampling program has been undertaken. A series of terrestrial water samples have been collected and analyzed for dissolved organic carbon levels. This dataset shows concentrations of dissolved organic carbon found in various streams of the McMurdo Dry Valleys.
DOI: 10.5281/zenodo.14784110
title: Sequences of fungi isolated from mouse intestine

description: Culturomics ITS sequences of fungi cultured in mouse cecal contents
DOI: 10.5281/zenodo.14784111
title: Sequences of fungi isolated from mouse intestine

description: Culturomics ITS sequences of fungi cultured in mouse cecal contents
DOI: 10.5281/zenodo.13384388
title: Composition of coffee beans influenced by bioprocessing with selected bacteria

description: Dataset contains calculation files (Ex2 and Ex3_raw data.xlsx) and summary excel file (Statistics_data.xlsx), on which statistical analysis was performed using attached code in R programming language.

Ex1 - Experiment 1; Screening of bacterial strains’ growth.

Ex2 - Experiment 2; Coffee fermentation with selected bacterial strains.

Ex3 - Experiment 3; Influence of time on coffee fermentation with selected bacterium.
DOI: 10.5281/zenodo.13384389
title: Composition of coffee beans influenced by bioprocessing with selected bacteria

description: Dataset contains calculation files (Ex2 and Ex3_raw data.xlsx) and summary excel file (Statistics_data.xlsx), on which statistical analysis was performed using attached code in R programming language.

Ex1 - Experiment 1; Screening of bacterial strains’ growth.

Ex2 - Experiment 2; Coffee fermentation with selected bacterial strains.

Ex3 - Experiment 3; Influence of time on coffee fermentation with selected bacterium.
DOI: 10.5281/zenodo.14939091
title: Composition of coffee beans influenced by bioprocessing with selected bacteria

description: Dataset contains calculation files (Ex2 and Ex3_raw data.xlsx) and summary excel file (Statistics_data.xlsx), on which statistical analysis was performed using attached code in R programming language.

Ex1 - Experiment 1; Screening of bacterial strains’ growth.

Ex2 - Experiment 2; Coffee fermentation with selected bacterial strains.

Ex3 - Experiment 3; Influence of time on coffee fermentation with selected bacterium.
DOI: 10.5281/zenodo.14938982
title: Interpretative Profiles

description:  




The "Interpretative Profiles Dataset" presents original data associated with the published research article:

Canal, P., Bischetti, L., Bertini, C., Ricci, I., Lecce, S., & Bambini, V. (2022) N400 differences between physical and mental metaphors: The role of Theories of Mind. Brain and Cognition, 161, 105879.

The materials used to collect the data are available on the figurative archive at the following link: https://neplab.shinyapps.io/FigurativeArchive/

Please acknowledge and cite the dataset using the reference above.
DOI: 10.5281/zenodo.14938981
title: Interpretative Profiles

description:  




The "Interpretative Profiles Dataset" presents original data associated with the published research article:

Canal, P., Bischetti, L., Bertini, C., Ricci, I., Lecce, S., & Bambini, V. (2022) N400 differences between physical and mental metaphors: The role of Theories of Mind. Brain and Cognition, 161, 105879.

The materials used to collect the data are available on the figurative archive at the following link: https://neplab.shinyapps.io/FigurativeArchive/

Please acknowledge and cite the dataset using the reference above.
DOI: 10.5281/zenodo.14939151
title: Interpretative Profiles

description:  




The "Interpretative Profiles Dataset" presents original data associated with the published research article:

Canal, P., Bischetti, L., Bertini, C., Ricci, I., Lecce, S., & Bambini, V. (2022) N400 differences between physical and mental metaphors: The role of Theories of Mind. Brain and Cognition, 161, 105879.

The materials used to collect the data are available on the figurative archive at the following link: https://neplab.shinyapps.io/FigurativeArchive/

Please acknowledge and cite the dataset using the reference above.
DOI: 10.5281/zenodo.14939143
title: Nguyen et al - 2025
DOI: 10.5281/zenodo.14939144
title: Nguyen et al - 2025
DOI: 10.5281/zenodo.14865961
title: Open Science Artifact: Experimenting Architectural Patterns in Federated Learning Systems

description: Description

This package contains: (ii) the code and the link to the Github Repository of AP4FED and (i) the results of the performance analysis of architectural patterns examined in the article “Experimenting Architectural Patterns in Federated Learning Systems,” which was submitted for publication in the Journal of Systems and Software’s Special Issue on “Software Architecture for Trustworthy Software.”

Structure



Performance Analysis.xlsl (An excel file containing the results of the analysis)

AP4Fed-Main.zip (The code of the tool proposed)

README.md (A set of instructions/specifications for AP4FED)


To run and test AP4FED please follow the instruction on the README.md file in this repository or in the Github repository.

Repository Link: https://github.com/IvanComp/AP4Fed
DOI: 10.5281/zenodo.14938840
title: Open Science Artifact: Experimenting Architectural Patterns in Federated Learning Systems

description: Description

This package contains: (ii) the code and the link to the Github Repository of AP4FED and (i) the results of the performance analysis of architectural patterns examined in the article “Experimenting Architectural Patterns in Federated Learning Systems,” which was submitted for publication in the Journal of Systems and Software’s Special Issue on “Software Architecture for Trustworthy Software.”

Structure



Performance Analysis.xlsl (An excel file containing the results of the analysis)

AP4Fed-Main.zip (The code of the tool proposed. It contains a README.md file with instructions/specifications for running AP4FED)


To run and test AP4FED please follow the instruction on the README.md file in this repository or in the Github repository.

Repository Link: https://github.com/IvanComp/AP4Fed
DOI: 10.5281/zenodo.14938910
title: Open Science Artifact: Experimenting Architectural Patterns in Federated Learning Systems

description: Description

This package contains: (ii) the code and the link to the Github Repository of AP4FED and (i) the results of the analysis of architectural patterns in Federated Learning Systems, as examined in the article titled “Experimenting Architectural Patterns in Federated Learning Systems", which is under revision.

Structure



AP4Fed-Main.zip (The code of the tool proposed. It contains a README.md file with instructions/specifications for running AP4FED)

Performance Analysis.xlsl (An excel file containing the results of the analysis)


To run and test AP4FED please follow the instruction on the README.md file in this repository or in the Github repository.

Repository Link: https://github.com/IvanComp/AP4Fed
DOI: 10.5281/zenodo.14794568
title: PaCE2022 Advanced Max Planck CloudKite data

description: This dataset was produced using the Advanced Max Planck CloudKite Instrument Box (MPCK+) during the Pallas Cloud Experiment (PaCE2022) between September 19 and September 26, 2022. It includes measurements of key meteorological variables such as temperature, relative humidity, static air pressure and wind speed together with geolocation, instrument orientation, and cloud droplet size distributions measured by a Fast Cloud Droplet Probe. This dataset contains the non-imaging Level 1 data (calibration and time correction applied to raw data), provided in NetCDF format, following the Climate and Forecast (CF) conventions.

The MPCK+ was deployed by a Max Planck CloudKite platform, which is a tethered aerostat, up to 1200 m altitude above ground with flight duration between 1.5 and 3 hours. 

 

A link to a paper describing the data structure and showing data examples will be provided after acceptance.
DOI: 10.5281/zenodo.14938135
title: PaCE2022 Advanced Max Planck CloudKite data

description: This dataset was produced using the Advanced Max Planck CloudKite Instrument Box (MPCK+) during the Pallas Cloud Experiment (PaCE2022) between September 19 and September 26, 2022. It includes measurements of key meteorological variables such as temperature, relative humidity, static air pressure and wind speed together with geolocation, instrument orientation, and cloud droplet size distributions measured by a Fast Cloud Droplet Probe. This dataset contains the non-imaging Level 1 data (calibration and time correction applied to raw data), provided in NetCDF format, following the Climate and Forecast (CF) conventions.

The MPCK+ was deployed by a Max Planck CloudKite platform, which is a tethered aerostat, up to 1200 m altitude above ground with flight duration between 1.5 and 3 hours. 

There is one Python script available for each NetCDF file, which extracts the essential data, applies corrections and creates figures. 

 

A link to a paper describing the data structure and showing data examples will be provided after acceptance.
DOI: 10.21227/g9qa-4b13
title: 15 Year Evolution of Smart NIC

description: Network Interface Cards (NICs) are one of the key enablers of the modern-day Internet. They serve as gateways for connecting computing devices to networks for the exchange of data with other devices. Recently, the pervasive nature of Internet-enabled devices coupled with the growing demands for faster network access have necessitated the enhancement of NICs to Smart NICs (SNICs), capable of processing enormous volumes of data at near real-time speed. These devices are fitted with Compute Elements that allow them to handle several tasks, thus relieve their host's CPUs of these workloads. This dataset on SNICs is curated from 370 articles published in IEEE Xplore, over the past 15 years, from 2010 to 2024. It contains data about SNIC types, models, manufacturers, research foci, and application use cases.
DOI: 10.5281/zenodo.14939245
title: Machine Learning for Early Outcome Prediction in Septic Patients in the Emergency Department
DOI: 10.5281/zenodo.14939246
title: Machine Learning for Early Outcome Prediction in Septic Patients in the Emergency Department
DOI: 10.5281/zenodo.14933821
title: All data food regime experiment VU
DOI: 10.5281/zenodo.14933822
title: All data food regime experiment VU
DOI: 10.5519/qd.gwgrita4
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (244 records)
DOI: 10.5066/p9ddb01r
title: Genomic Data from Ptarmigan and Grouse, Alaska

description: This data set provides sample data and NCBI accession information for genomic sequencing of ptarmigan and grouse from Alaska.
DOI: 10.5281/zenodo.14938963
title: 48 fungal genome assembly data

description: This project contains 48 fungal genome assembly data from NCBI PRJNA1066080
DOI: 10.48420/26950159.v3
title: Deccan Volcanic Province volatile data compilation

description: This is a supplementary file to the Journal of Volcanology and Geothermal Research review article on <i>Volatile Emissions from Deccan Volcanic Eruptions and their Effects on Climate across the K-Pg Boundary</i>. This document hosts the compilation of literature data on the melt inclusion analysis of the Deccan Traps (Capriolo et al., 2024; Choudhary et al., 2019; Hernandez Nava et al., 2021; Sano, 2001; Self et al., 2008). The melt inclusion analysis has been carried out using several techniques including NanoSIMS, Raman Spectroscopy, EPMA and FTIR. The majority of the inclusions analysed were glassy, with some being crystalline that were subsequently rehomogenised. Most research was conducted on mostly glassy melt inclusions preserved in plagioclase, olivine and clinopyroxene phenocrysts and glomerocrysts form different lava flows which erupted across the Cretaceous-Paleogene boundary 66 million years ago. This spreadsheet further contains the formation-specific melt S anf F content data based on calculated clinopyroxene-equilibrium melt partitioning.This dataset intends to highlight the gap in quantifying volatile content in Deccan lava flows using this methodology.
DOI: 10.5281/zenodo.14938962
title: 48 fungal genome assembly data

description: This project contains 48 fungal genome assembly data from NCBI PRJNA1066080
DOI: 10.5281/zenodo.14939226
title: 48 fungal genome assembly data

description: This project contains 48 fungal genome assembly data from NCBI PRJNA1066080
DOI: 10.5281/zenodo.12626877
title: Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

description: Dataset of multi-well plate reader files related to the analysis of the growth of C. difficile isolates on differnet carbon substrates. 

Data Collection. This dataset accompanies an mSystems article which is available at https://doi.org/10.1128/msystems.01075-24. The "Materials and Methods" section in this article fully describes the biological nature of these samples and how the samples were processed and analyzed.  

Repository Content. The amiga folders contains both the raw data (see data and mapping sub-folders), intermediate outpus (see dervied sub-folders), and final outputs (see figures and summary sub-folders). Each amiga folder corresponds to a single working directory analyzed by the AMiGA software. For the amiga-biolog directory, the notes sub-folder also includes text files related to flagging plates and wells for quality issues.

Data Organization. Growth plate data are organized by the following experiments. 



biolog

validation

ribotype-255

clade-5

yeast-extract-biolog

yeast-extract-validation


Data Analysis. Code used for manipulating and analyzing these samples is also publicly available on GitHub (https://github.com/firasmidani/cdiff-biolog-growth) under the GNU GPL-3.0 license. The scripts in "analyze-code" can be used to analyze all data and the scripts in the "generate-figures" folder can be used to reproduce all figures included in the manuscript. See the GitHub repository for instructions on how to do so.
DOI: 10.5281/zenodo.12626878
title: Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

description: Dataset of multi-well plate reader files related to the analysis of the growth of C. difficile isolates on differnet carbon substrates. 

Data Collection. This dataset accompanies an article which is available as a preprint and will be undergoing peer review when this repository is published. The "Methods and Materials" section in this article fully describes the biological nature of these samples and how the samples were processed and analyzed.  

Repository Content. The amiga folders contains both the raw data (see data and mapping sub-folders), intermediate outpus (see dervied sub-folders), and final outputs (see figures and summary sub-folders). Each amiga folder corresponds to a single working directory analyzed by the AMiGA software. 

Data Organization. Growth plate data are organized by the following experiments. 



biolog

validation

ribotype-255

clade-5

yeast-extract-biolog

yeast-extract-validation


Data Analysis. Code used for manipulating and analyzing these samples is also publicly available on GitHub (https://github.com/firasmidani/cdiff-biolog-growth) under the GNU GPL-3.0 license. The scripts in "analyze-code" can be used to analyze all data and the scripts in the "generate-figures" folder can be used to reproduce all figures included in the manuscript. See the GitHub repository for instructions on how to do so.