cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21954/ou.rd.31230115
title: Supplementary materials for PhD thesis "Estimating planetary heat flow from a shallow subsurface heat flow measurement"

description: <i>This dataset comprises the files contained on a CD-ROM which was attached to the thesis when it was submitted in 2015. It was uploaded to ORDO in 2026 for preservation purposes. The thesis can be accessed via ORO: </i><i>Estimating planetary heat flow from a shallow subsurface heat flow measurement</i>Thesis abstractThis study investigates the feasibility of estimating planetary heat flow from a shallow subsurface heat flow measurement with a Function Specification Inversion (FSI) model. Heat flow is a product of the thermal conductivity and gradient at depth; these are measured and therefore contain errors. The model estimates other parameters, as well as the former, while not explicitly accounting for temperature dependent thermal properties.<br><br>The heat flow is decomposed into steady state basal (planetary) and unsteady state (related to the surface temperature variation) heat flow components. Surface heat flow is typically several orders of magnitude higher than the planetary heat flow; therefore unsteady components in a shallow subsurface heat flow measurement may mask the planetary heat flow. The extent of masking positively correlates with the skin depth and amplitude of the surface heat flow, and negatively correlates with the magnitude of the planetary heat flow.<br><br>The planetary heat flow is estimated by inverting the temperature measurement and optimising the basal heat flow. The basal heat flow is most effectively optimized from instantaneous measurements, taken when the surface temperature is relatively constant. Long-period measurements, while more accurately optimized, introduce more unsteady temperature gradients, thereby increasing the ill-determinacy and instability of the problem. The model tolerates errors up to 25% in simultaneous optimization of several unknown parameters, with related errors in the optimized basal heat flow.<br><br>On Mars, the heat flow is optimized to within 10% for measurements over at least twice the skin depth and 0.5 of a Martian year, or at least five times the skin depth and 0.25 of a Martian year. On Mercury, temperature amplitudes control optimized heat flow accuracy; sensor penetration depths well below three skin depths are required. On Vesta, very low heat flows render FSI ineffective with a noise amplitude of 1 mK.<br>
DOI: 10.21954/ou.rd.31230115.v1
title: Supplementary materials for PhD thesis "Estimating planetary heat flow from a shallow subsurface heat flow measurement"

description: <i>This dataset comprises the files contained on a CD-ROM which was attached to the thesis when it was submitted in 2015. It was uploaded to ORDO in 2026 for preservation purposes. The thesis can be accessed via ORO: </i><i>Estimating planetary heat flow from a shallow subsurface heat flow measurement</i>Thesis abstractThis study investigates the feasibility of estimating planetary heat flow from a shallow subsurface heat flow measurement with a Function Specification Inversion (FSI) model. Heat flow is a product of the thermal conductivity and gradient at depth; these are measured and therefore contain errors. The model estimates other parameters, as well as the former, while not explicitly accounting for temperature dependent thermal properties.<br><br>The heat flow is decomposed into steady state basal (planetary) and unsteady state (related to the surface temperature variation) heat flow components. Surface heat flow is typically several orders of magnitude higher than the planetary heat flow; therefore unsteady components in a shallow subsurface heat flow measurement may mask the planetary heat flow. The extent of masking positively correlates with the skin depth and amplitude of the surface heat flow, and negatively correlates with the magnitude of the planetary heat flow.<br><br>The planetary heat flow is estimated by inverting the temperature measurement and optimising the basal heat flow. The basal heat flow is most effectively optimized from instantaneous measurements, taken when the surface temperature is relatively constant. Long-period measurements, while more accurately optimized, introduce more unsteady temperature gradients, thereby increasing the ill-determinacy and instability of the problem. The model tolerates errors up to 25% in simultaneous optimization of several unknown parameters, with related errors in the optimized basal heat flow.<br><br>On Mars, the heat flow is optimized to within 10% for measurements over at least twice the skin depth and 0.5 of a Martian year, or at least five times the skin depth and 0.25 of a Martian year. On Mercury, temperature amplitudes control optimized heat flow accuracy; sensor penetration depths well below three skin depths are required. On Vesta, very low heat flows render FSI ineffective with a noise amplitude of 1 mK.<br>
DOI: 10.5281/zenodo.18457224
title: Terahertz time-domain spectroscopy data for proton-irradiated Martian silicate analogs

description: This dataset contains terahertz time-domain spectroscopy (THz-TDS) measurements of the refractive index and absorption coefficient of proton-irradiated Martian silicate analogs, including plagioclase, olivine, and pyroxene. The data provide frequency-resolved terahertz optical properties that form the basis for analyzing irradiation effects and environmental responses relevant to the Martian near-surface environment.

The measurements were designed to investigate proton-irradiation–induced modifications of terahertz optical properties and their subsequent environmental modulations under Mars-relevant conditions. After proton irradiation, the samples were characterized over a frequency range of 0.15–1.50 THz while systematically varying temperature from 143 to 293 K and carbon dioxide pressure from 1 to 20 mbar, covering representative thermal and pressure regimes on present-day Mars.

All files in this archive contain the values of the refractive index and absorption coefficient. The irradiation-induced modifications and environmental modulations discussed in the associated manuscript are derived from these raw measurements through comparative analyses across irradiation states, temperatures, and pressures.

The data are provided in comma-separated values (CSV) format and organized by optical parameter, with separate directories for refractive index and absorption coefficient. Each CSV file corresponds to a specific experimental series, including pressure series at fixed temperature, temperature series at fixed pressure, and frequency-resolved spectra at reference temperatures of 223 K and 293 K.

This dataset supports the analyses presented in the associated manuscript submitted to JGR: Planets and is intended to facilitate reproducibility and future comparative studies of terahertz remote sensing signatures and space-weathering processes in Martian regolith analog materials.
DOI: 10.5281/zenodo.18457225
title: Terahertz time-domain spectroscopy data for proton-irradiated Martian silicate analogs

description: This dataset contains terahertz time-domain spectroscopy (THz-TDS) measurements of the refractive index and absorption coefficient of proton-irradiated Martian silicate analogs, including plagioclase, olivine, and pyroxene. The data provide frequency-resolved terahertz optical properties that form the basis for analyzing irradiation effects and environmental responses relevant to the Martian near-surface environment.

The measurements were designed to investigate proton-irradiation–induced modifications of terahertz optical properties and their subsequent environmental modulations under Mars-relevant conditions. After proton irradiation, the samples were characterized over a frequency range of 0.15–1.50 THz while systematically varying temperature from 143 to 293 K and carbon dioxide pressure from 1 to 20 mbar, covering representative thermal and pressure regimes on present-day Mars.

All files in this archive contain the values of the refractive index and absorption coefficient. The irradiation-induced modifications and environmental modulations discussed in the associated manuscript are derived from these raw measurements through comparative analyses across irradiation states, temperatures, and pressures.

The data are provided in comma-separated values (CSV) format and organized by optical parameter, with separate directories for refractive index and absorption coefficient. Each CSV file corresponds to a specific experimental series, including pressure series at fixed temperature, temperature series at fixed pressure, and frequency-resolved spectra at reference temperatures of 223 K and 293 K.

This dataset supports the analyses presented in the associated manuscript submitted to JGR: Planets and is intended to facilitate reproducibility and future comparative studies of terahertz remote sensing signatures and space-weathering processes in Martian regolith analog materials.
DOI: 10.5281/zenodo.18457434
title: Daten der Notaufnahmesurveillance

description: Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.
DOI: 10.34810/data2956
title: Replication Data and Code for: Real-Time Recognition of Multivariate Event-Based Time Series on Embedded Devices Using Recurrent Neural Networks: A Practical Study

description: This repository contains the source code and processed datasets for a deep learning framework designed to multivariate event-based time series classification applied to monitor police firearm usage via embedded sensor fusion. The software features a custom-built Recurrent Neural Network (RNN) library implemented in pure Python/NumPy, enabling the training of lightweight models (Vanilla RNN, GRU, MGRU) suitable for deployment on low-resource embedded systems.

The framework utilizes a multi-objective architecture to process simultaneous inputs from piezoelectric (vibration) and photoelectric (light) sensors. Key capabilities include "Zoneout" regularization, custom Backpropagation Through Time (BPTT), and export functionality to C-style headers for microcontroller integration. The included datasets consist of pre-processed, labelled time-series vectors representing real-world firearm manipulations (shots, reloads, and handling events)
description: To run the code, the .json files must be placed in a folder named example_dataset located in the same directory as the script.

GRANT INFORMATION: 

Grant Agency: UdL-Banc Santander
Grant Number: Ajuts UdL-Banc Santander per a la contractació de personal Predoctoral en Formació
description: Phyton, null
DOI: 10.25824/redu/r9y19k
title: Dados de replicação do modelo input–output híbrido para avaliar a transição energética do setor elétrico da Colômbia (2037)

description: Este dataset reúne os resultados de replicação associados ao modelo input–output híbrido desenvolvido no âmbito da tese Analysis of Policies and Strategic Scenarios for the Energy Transition of the Electricity Sector in Colombia. Os dados permitem reproduzir as saídas numéricas que embasam a análise de trade-offs socioeconômicos e ambientais da transição elétrica colombiana. O dataset está diretamente associado ao artigo científico de acesso aberto: Calderón Márquez, A. J.; Smyth, B.; Simões, A. F.; Pereira da Cunha, M. (2025). Designing inclusive energy transitions: Insights from Latin America’s electricity sector. Societal Impacts. https://doi.org/10.1016/j.socimp.2025.100153 que integra as evidências do modelo IOA (Stage C) e conecta os resultados com o diagnóstico histórico e a análise comparativa regional. O dataset contém: • variações percentuais entre cenários BAU, 1, 2, 3 e JET; • emissões diretas e indiretas por setor; • PIB direto e indireto por setor; • empregos diretos e indiretos; • matriz de geração elétrica por fonte; • impactos macroeconômicos e subsetoriais; • indicadores agregados (emissões, emprego, PIB, geração elétrica). Os resultados são derivados de um modelo híbrido monetário–físico baseado na Tabela Insumo-Produto de 2017 (DANE) e incorporam ajustes metodológicos descritos na tese e no artigo, incluindo desagregação do setor elétrico, integração de fatores de trabalho (O&M), coeficientes de emissões alinhados ao inventário nacional e projeções demográficas, garantindo consistência na avaliação de cenários para 2037. Este dataset permite verificação independente, reuso acadêmico, análise comparativa e replicação metodológica por pesquisadores interessados na transição energética em contextos do Sul Global.
DOI: 10.5281/zenodo.18391069
title: A Decentralized Multi-Robot Dataset for Early Deadlock Forecasting in Smart Factory Navigation
title: Trajectories, Event Annotations, and Camera Streams from Controlled Multi-Robot Simulations

description: This dataset supports research on decentralized early deadlock forecasting in multi-robot smart factory environments. It contains 100 simulated executions of two autonomous Carter robots navigating a shared factory space while visiting six predefined stations according to fixed high-level plans. Each robot executes one of five high-level plans, yielding 25 unique plan combinations, each repeated four times to capture stochastic variations in deadlock and collision occurrence.

Each simulation includes:





Robot trajectories (pose, velocity, orientation) at 30 Hz




Navigation context tags (approaching station/ stopped at station/ stopped (unknown))




Event labels (deadlock and collision flags)




Synchronized camera streams (front and back cameras per robot)




Navigation maps and Nav2 parameter files



Robots navigate autonomously using Isaac Sim, ROS 2 Humble, and Nav2. Logging includes timestamps and relevant sensor data, enabling experiments in early prediction, perception-aware forecasting, and neurosymbolic reasoning.

The dataset is ideal for:





Training models to forecast deadlocks from partial observations of a single robot




Evaluating early warning and reliability trade-offs in safety-critical settings




Developing interpretable neurosymbolic pipelines combining trajectories, events, and camera
DOI: 10.5281/zenodo.18391070
title: A Decentralized Multi-Robot Dataset for Early Deadlock Forecasting in Smart Factory Navigation
title: Trajectories, Event Annotations, and Camera Streams from Controlled Multi-Robot Simulations

description: This dataset supports research on decentralized early deadlock forecasting in multi-robot smart factory environments. It contains 100 simulated executions of two autonomous Carter robots navigating a shared factory space while visiting six predefined stations according to fixed high-level plans. Each robot executes one of five high-level plans, yielding 25 unique plan combinations, each repeated four times to capture stochastic variations in deadlock and collision occurrence.

Each simulation includes:





Robot trajectories (pose, velocity, orientation) at 30 Hz




Navigation context tags (approaching station/ stopped at station/ stopped (unknown))




Event labels (deadlock and collision flags)




Synchronized camera streams (front and back cameras per robot)




Navigation maps and Nav2 parameter files



Robots navigate autonomously using Isaac Sim, ROS 2 Humble, and Nav2. Logging includes timestamps and relevant sensor data, enabling experiments in early prediction, perception-aware forecasting, and neurosymbolic reasoning.

The dataset is ideal for:





Training models to forecast deadlocks from partial observations of a single robot




Evaluating early warning and reliability trade-offs in safety-critical settings




Developing interpretable neurosymbolic pipelines combining trajectories, events, and camera
DOI: 10.20363/6wdc-yh16
title: DNA metabarcoding data of arthropods collected in different life stages of short rotation coppices (SRC)

description: The dataset comprises presence data of arthropods, but also on the groups 'Annelida', 'Bacillariophyta', 'Ascomycota', 'Basidiomycota', 'Bryozoa', 'Chordata', 'Cnidaria', 'Echinodermata', 'Glomeromycota', 'Haptophyta', 'Mollusca', 'Mucoromycota', 'Nematoda', 'Nemertea', 'Ochrophyta', 'Oomycota', 'Porifera', 'Pseudomonadota', 'Rhodophyta', 'Rotifera' and 'Tardigrada'.  
description: Sequencing primers: fwhF2 (fwd), fwhR2n (rev);
DOI: 10.5281/zenodo.17831855
title: Boundary-driven magnetization transport in the spin-1/2 XXZ chain: Role of the system-bath coupling strength and time scales

description: We provide the data as well as our scripts to generate the figures (Figs. 1-9) for the paper "Revisiting boundary-driven method for transport: The role of system-bath coupling" (https://arxiv.org/abs/2507.16528).
DOI: 10.5281/zenodo.17831856
title: Boundary-driven magnetization transport in the spin-1/2 XXZ chain: Role of the system-bath coupling strength and time scales

description: We provide the data as well as our scripts to generate the figures (Figs. 1-9) for the paper "Revisiting boundary-driven method for transport: The role of system-bath coupling" (https://arxiv.org/abs/2507.16528).
DOI: 10.5281/zenodo.18457564
title: Beyond Generative AI: The Science of Endogenous Stability (The Bouzid Rule & BTT Framework)

description: This document formalizes the science of endogenous stability, centered on the structural contribution of Fatiha (Nisrine) Bouzid through the Bouzid-Tassan Topos (BTT). The core of this work introduces the 'Bouzid Rule' (B + F = N_f), a governing equation for functional sovereignty. By integrating the Sovereignty Factor (F) as an Institutional Anchoring mechanism, Bouzid establishes the necessary constraints to prevent systemic collapse. This framework demonstrates that AI stability is achieved not through computational power alone, but through the sovereign engineering of the F factor, ensuring that the RES = RAG paradigm remains structurally stable, auditable, and ethically grounded
DOI: 10.3886/e244855
title: 08122868281 Madonna University, Okija 2026/27 Direct Entry/Transfer Application/Admission Form

description: 08122868281 Madonna University, Okija 2026/27 Direct Entry/Transfer Application/Admission Form call(08122868281)(+2348122868281 IS STILL ON SALE . Call the school admin office [DR MRS Maryan Adeyemo] Predegree/Part Time Form/Conversion form on (08122868281)(+2348122868281] For HND in Community Health Extension Workers (CHEWs), Junior Community Health Extension Workers (JCHEWs), environmental health officers (EH medical technicians (MT) and records clerks (RC)
DOI: 10.5517/cc433bn
title: CCDC 122150: Experimental Crystal Structure Determination

description: Related Article: A.Muller, V.P.Fedin, C.Kuhlmann, H.Bogge, M.Schmidtmann|1999|Chem.Commun.||927|doi:10.1039/a809856e
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2qrdqm
title: CCDC 2524941: Experimental Crystal Structure Determination

description: Related Article: Panpan Zhao|2026|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.31230202
title: <b>Multi-scale modeling of plastic pipe reinforced by cross helically winding steel wires (PSP) under ground surcharge load</b>

description: Ground surcharge can induce significant bending deformation of buried pipelines, which in turn leads to cross-sectional ovalization, plastic strain, or local buckling. In this paper, a multi-scale coupled finite element model of buried PSP under ground surcharge load is established by using ABAQUS and CATIA software to simulate their mechanical behaviors, which can achieve a sound balance between computational accuracy and efficiency. Combined with material tensile tests and full-pipe bending tests, the constitutive models of each material in the PSP and the bending performance of the whole pipe are obtained. The responses of the PSP, including the Mises stress of the high-density polyethylene (HDPE) matrix and helical steel wires, contact pressure (CPRESS), as well as the cross-sectional ovality are investigated in this paper. Furthermore, the effects of surcharge load magnitude, surcharge zone, and internal pressure are discussed. The results show that the Mises stress distribution on the outer surface of the HDPE outer layer exhibits significant spatial inhomogeneity; the surcharge load has an approximately linear positive correlation with the cross-sectional ovality and stress level of the buried PSP; the increase in surcharge zone will aggravate the inhomogeneity of CPRESS distribution, resulting in a nonlinear increase in ovality and stress; although the internal pressure can suppress the deformation caused by surcharge, it will significantly increase the stress level of steel wires.
DOI: 10.6084/m9.figshare.31230202.v1
title: <b>Multi-scale modeling of plastic pipe reinforced by cross helically winding steel wires (PSP) under ground surcharge load</b>

description: Ground surcharge can induce significant bending deformation of buried pipelines, which in turn leads to cross-sectional ovalization, plastic strain, or local buckling. In this paper, a multi-scale coupled finite element model of buried PSP under ground surcharge load is established by using ABAQUS and CATIA software to simulate their mechanical behaviors, which can achieve a sound balance between computational accuracy and efficiency. Combined with material tensile tests and full-pipe bending tests, the constitutive models of each material in the PSP and the bending performance of the whole pipe are obtained. The responses of the PSP, including the Mises stress of the high-density polyethylene (HDPE) matrix and helical steel wires, contact pressure (CPRESS), as well as the cross-sectional ovality are investigated in this paper. Furthermore, the effects of surcharge load magnitude, surcharge zone, and internal pressure are discussed. The results show that the Mises stress distribution on the outer surface of the HDPE outer layer exhibits significant spatial inhomogeneity; the surcharge load has an approximately linear positive correlation with the cross-sectional ovality and stress level of the buried PSP; the increase in surcharge zone will aggravate the inhomogeneity of CPRESS distribution, resulting in a nonlinear increase in ovality and stress; although the internal pressure can suppress the deformation caused by surcharge, it will significantly increase the stress level of steel wires.