cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/v5cnpt2whh
title: The DeepFMKit python package: A toolbox for simulating and analyzing deep frequency modulation interferometers

description: Deep Frequency Modulation Interferometry (DFMI) is an emerging laser interferometry technique for high-precision metrology, offering picometer-level displacement measurements and the potential for absolute length determination with sub-wavelength accuracy. However, the design and optimization of DFMI systems involve a complex interplay between interferometer physics, laser technology, multiple noise sources, and the choice of data processing algorithm. To address this, we present DeepFMKit, a new open-source Python library for the end-to-end simulation and analysis of DFMI systems. The framework features a high-fidelity physics engine that rigorously models key physical effects such as time-of-flight delays in dynamic interferometers, arbitrary laser modulation waveforms, and colored noise from user-defined 1/fα spectral densities. This engine is coupled with a suite of interchangeable parameter estimation algorithms, including a highly-optimized, frequency-domain Non-linear Least Squares (NLS) for high-throughput batch processing of experimental data, and multiple time-domain Extended Kalman Filter (EKF) implementations for sample-by-sample state tracking, featuring both random walk and integrated random walk (constant velocity) process models. Furthermore, DeepFMKit includes a high-throughput experimentation framework for automating large-scale parameter sweeps and Monte Carlo analyses, enabling systematic characterization of system performance. DeepFMKit’s modular, object-oriented architecture facilitates the rapid configuration of virtual experiments, providing a powerful computational tool for researchers to prototype designs, investigate systematic errors, and accelerate the development of precision interferometry.
DOI: 10.17632/v5cnpt2whh.1
title: The DeepFMKit python package: A toolbox for simulating and analyzing deep frequency modulation interferometers

description: Deep Frequency Modulation Interferometry (DFMI) is an emerging laser interferometry technique for high-precision metrology, offering picometer-level displacement measurements and the potential for absolute length determination with sub-wavelength accuracy. However, the design and optimization of DFMI systems involve a complex interplay between interferometer physics, laser technology, multiple noise sources, and the choice of data processing algorithm. To address this, we present DeepFMKit, a new open-source Python library for the end-to-end simulation and analysis of DFMI systems. The framework features a high-fidelity physics engine that rigorously models key physical effects such as time-of-flight delays in dynamic interferometers, arbitrary laser modulation waveforms, and colored noise from user-defined 1/fα spectral densities. This engine is coupled with a suite of interchangeable parameter estimation algorithms, including a highly-optimized, frequency-domain Non-linear Least Squares (NLS) for high-throughput batch processing of experimental data, and multiple time-domain Extended Kalman Filter (EKF) implementations for sample-by-sample state tracking, featuring both random walk and integrated random walk (constant velocity) process models. Furthermore, DeepFMKit includes a high-throughput experimentation framework for automating large-scale parameter sweeps and Monte Carlo analyses, enabling systematic characterization of system performance. DeepFMKit’s modular, object-oriented architecture facilitates the rapid configuration of virtual experiments, providing a powerful computational tool for researchers to prototype designs, investigate systematic errors, and accelerate the development of precision interferometry.
DOI: 10.17632/p663cmn8vn
title: Demographic information of 10 LV patients treated with baricitinib

description: Baseline data of 10 patients with LV who were treated with baricitinib.
DOI: 10.17632/p663cmn8vn.2
title: Demographic information of 10 LV patients treated with baricitinib

description: Baseline data of 10 patients with LV who were treated with baricitinib.
DOI: 10.17632/ck5gfhvbgz
title: Systemic Hematological and Inflammatory Profiles in Triple-Negative Breast Cancer in a Senegalese cohort

description: The dataset includes demographic variables, clinical information such as tumor stage and treatment, as well as inflammatory biomarkers including:
• Neutrophil count (10⁹/L)
• Lymphocyte count (10⁹/L)
• Platelet count (10⁹/L)
• C-reactive protein (CRP) (mg/L)
• Neutrophil-to-lymphocyte ratio (NLR)
• Platelet-to-lymphocyte ratio (PLR)
All personal identifiers have been removed, and each subject is labeled with a unique anonymized code.
This dataset was used to investigate the association between inflammatory markers and breast cancer subtypes, as well as differences between patients and healthy controls. It supports the findings presented in the manuscript titled: Systemic Hematological and Inflammatory Profiles in Triple-Negative Breast Cancer in a Senegalese cohort.
DOI: 10.17632/ck5gfhvbgz.1
title: Systemic Hematological and Inflammatory Profiles in Triple-Negative Breast Cancer in a Senegalese cohort

description: The dataset includes demographic variables, clinical information such as tumor stage and treatment, as well as inflammatory biomarkers including:
• Neutrophil count (10⁹/L)
• Lymphocyte count (10⁹/L)
• Platelet count (10⁹/L)
• C-reactive protein (CRP) (mg/L)
• Neutrophil-to-lymphocyte ratio (NLR)
• Platelet-to-lymphocyte ratio (PLR)
All personal identifiers have been removed, and each subject is labeled with a unique anonymized code.
This dataset was used to investigate the association between inflammatory markers and breast cancer subtypes, as well as differences between patients and healthy controls. It supports the findings presented in the manuscript titled: Systemic Hematological and Inflammatory Profiles in Triple-Negative Breast Cancer in a Senegalese cohort.
DOI: 10.17632/5gtvpk48kf
title: Hierarchical pathways linking wildfire ash properties to soil DOC and MBC dynamics under varying fuel conditions

description: Dataset on fuel conditions, fire behavior, soil physical and chemical properties, and soil microbial biomass carbon (MBC) as well as dissolved organic carbon (DOC)
DOI: 10.17632/5gtvpk48kf.1
title: Hierarchical pathways linking wildfire ash properties to soil DOC and MBC dynamics under varying fuel conditions

description: Dataset on fuel conditions, fire behavior, soil physical and chemical properties, and soil microbial biomass carbon (MBC) as well as dissolved organic carbon (DOC)
DOI: 10.17632/4vww739zw7
title: MENTAL ACCOUNTING, ATTITUDES, AND ENVIRONMENTAL AWARENESS: DRIVERS OF GEN Z’S SUSTAINABLE FINANCE BEHAVIOR

description: This study aims to analyze the influence of mental accounting, financial attitude, and environmental awareness on sustainable financial behavior among Generation Z. This study employs a quantitative approach, utilizing primary data collected through a questionnaire distributed via Google Forms. The total sample consists of 302 Generation Z respondents aged 17 to 28 years who actively use financial services such as investment products, digital payment instruments, and savings facilities in Indonesia. The data obtained was analyzed using multiple linear regression techniques assisted by the SmartPLS statistical tool. This study shows that mental accounting, financial attitude, and environmental awareness have a significant positive effect on sustainable financial behavior among Generation Z. Increasing financial awareness through mental accounting, financial attitude, and environmental awareness among Generation Z must be in line with the practice of sustainable financial behavior, so that it can shape responsible financial behavior and achieve the eighth SDG goal of decent work and economic growth. Through the results of this study, it is hoped that Generation Z can apply the habits of saving and investing in their daily lives, so that they can build long-term financial needs and achieve their financial goals with confidence.
DOI: 10.17632/4vww739zw7.1
title: MENTAL ACCOUNTING, ATTITUDES, AND ENVIRONMENTAL AWARENESS: DRIVERS OF GEN Z’S SUSTAINABLE FINANCE BEHAVIOR

description: This study aims to analyze the influence of mental accounting, financial attitude, and environmental awareness on sustainable financial behavior among Generation Z. This study employs a quantitative approach, utilizing primary data collected through a questionnaire distributed via Google Forms. The total sample consists of 302 Generation Z respondents aged 17 to 28 years who actively use financial services such as investment products, digital payment instruments, and savings facilities in Indonesia. The data obtained was analyzed using multiple linear regression techniques assisted by the SmartPLS statistical tool. This study shows that mental accounting, financial attitude, and environmental awareness have a significant positive effect on sustainable financial behavior among Generation Z. Increasing financial awareness through mental accounting, financial attitude, and environmental awareness among Generation Z must be in line with the practice of sustainable financial behavior, so that it can shape responsible financial behavior and achieve the eighth SDG goal of decent work and economic growth. Through the results of this study, it is hoped that Generation Z can apply the habits of saving and investing in their daily lives, so that they can build long-term financial needs and achieve their financial goals with confidence.
DOI: 10.17632/8y44t7mdyx
title: Efficacy of Probiotic-Supplemented Infant Formula in Treating Chronic Diarrhea in Children Aged 6–43 Months: Evidence based on a Randomized Control Trial

description: Summary of Questionnaires on Infantile Diarrhea and Follow-up Record Form for Infantile Diarrhea
DOI: 10.17632/8y44t7mdyx.1
title: Efficacy of Probiotic-Supplemented Infant Formula in Treating Chronic Diarrhea in Children Aged 6–43 Months: Evidence based on a Randomized Control Trial

description: Summary of Questionnaires on Infantile Diarrhea and Follow-up Record Form for Infantile Diarrhea
DOI: 10.17632/dfpgdv7wr8
title: neqFoam: An OpenFOAM-based Solver with a Unified Approach for the Thermochemical Non-Equilibrium Simulations

description: Given the growing emphasis on hypersonic propulsion systems, accurate prediction of thermochemical non-equilibrium phenomena has become paramount. However, the thermodynamic models used to simulate combustion and thermal non-equilibrium flows in hypersonic regimes differ substantially. The simple partition-function model–predominantly applied in thermal non-equilibrium simulations–relies on rigid-rotor and harmonic-oscillator approximations that neglect key molecular energy interactions, whereas polynomial representations of thermodynamic properties–widely employed in combustion simulations–incorporate additional correction factors to account for detailed molecular and atomic energy modes. In this paper, we introduce a novel OpenFOAM-based solver for a unified approach to thermochemical non-equilibrium flows using a polynomial representation. This contrasts with most prior work, which applies polynomial representations to combustion but relies on the simple partition-function model for thermal non-equilibrium flows. Notably, this solver implements a damped Newton–Raphson method to enhance numerical stability and convergence during temperature evaluations. We first analyzed the differences between these thermodynamic models and their respective impacts on predicted properties. Subsequently, we performed numerical simulations for a 0-D heat bath, the LENS-XX double cone, and a shock-induced combustion case. The results demonstrate that, the polynomial representation–incorporating detailed molecular energy modes at lower computational cost–exhibits pronounced differences in thermodynamic properties relative to the simple partition-function model, demonstrating superior suitability for thermochemical non-equilibrium flow analysis.
DOI: 10.17632/dfpgdv7wr8.1
title: neqFoam: An OpenFOAM-based Solver with a Unified Approach for the Thermochemical Non-Equilibrium Simulations

description: Given the growing emphasis on hypersonic propulsion systems, accurate prediction of thermochemical non-equilibrium phenomena has become paramount. However, the thermodynamic models used to simulate combustion and thermal non-equilibrium flows in hypersonic regimes differ substantially. The simple partition-function model–predominantly applied in thermal non-equilibrium simulations–relies on rigid-rotor and harmonic-oscillator approximations that neglect key molecular energy interactions, whereas polynomial representations of thermodynamic properties–widely employed in combustion simulations–incorporate additional correction factors to account for detailed molecular and atomic energy modes. In this paper, we introduce a novel OpenFOAM-based solver for a unified approach to thermochemical non-equilibrium flows using a polynomial representation. This contrasts with most prior work, which applies polynomial representations to combustion but relies on the simple partition-function model for thermal non-equilibrium flows. Notably, this solver implements a damped Newton–Raphson method to enhance numerical stability and convergence during temperature evaluations. We first analyzed the differences between these thermodynamic models and their respective impacts on predicted properties. Subsequently, we performed numerical simulations for a 0-D heat bath, the LENS-XX double cone, and a shock-induced combustion case. The results demonstrate that, the polynomial representation–incorporating detailed molecular energy modes at lower computational cost–exhibits pronounced differences in thermodynamic properties relative to the simple partition-function model, demonstrating superior suitability for thermochemical non-equilibrium flow analysis.
DOI: 10.17632/w92rdpzgvg
title: Operationalizing Sustainability: FNB Business Strategies for Responsible Consumption and Production (Bellbox Catering)

description: The attainment of contemporary environmental objectives necessitates a profound transformation towards a Circular Economy (CE), requiring a fundamental re-evaluation of the fossil-based, linear economic model. Achieving this systemic food transition requires active involvement from consumers and all supply chain actors, with the supply side needing to integrate sustainability into innovation by diversifying ingredients, upcycling waste, and implementing packaging strategies. While literature advocates for incorporating the consumer perspective into design, practical implementation guidelines remain scarce. To address this gap, this study operationalizes the Circular Food Design (CFD) model, a consumer-oriented, structured tool for food innovation. Through a descriptive analysis of case study— optimization at Bellbox Catering—we investigate the model's efficacy in ensuring consumer involvement in product innovation. The research employed a Design Thinking 4D framework (Discover, Define, Develop, Deliver) to facilitate interactive engagement. Key findings confirm that structuring innovation around consumer insights and inter-actor engagement across phases is crucial for product advancement. The integration of insights, often sourced from secondary data and models like the DONE and CFCP frameworks , provides strategic direction and a market-oriented approach. The study highlights that innovation is an iterative process and stresses the critical need for integrating insights from various disciplines throughout development. While the cases were limited to the Discover and Define phases, the application confirmed the CFD model's value as a structured approach to consumer-oriented innovation in the Food and Beverage (FNB) sector.
DOI: 10.17632/w92rdpzgvg.1
title: Operationalizing Sustainability: FNB Business Strategies for Responsible Consumption and Production (Bellbox Catering)

description: The attainment of contemporary environmental objectives necessitates a profound transformation towards a Circular Economy (CE), requiring a fundamental re-evaluation of the fossil-based, linear economic model. Achieving this systemic food transition requires active involvement from consumers and all supply chain actors, with the supply side needing to integrate sustainability into innovation by diversifying ingredients, upcycling waste, and implementing packaging strategies. While literature advocates for incorporating the consumer perspective into design, practical implementation guidelines remain scarce. To address this gap, this study operationalizes the Circular Food Design (CFD) model, a consumer-oriented, structured tool for food innovation. Through a descriptive analysis of case study— optimization at Bellbox Catering—we investigate the model's efficacy in ensuring consumer involvement in product innovation. The research employed a Design Thinking 4D framework (Discover, Define, Develop, Deliver) to facilitate interactive engagement. Key findings confirm that structuring innovation around consumer insights and inter-actor engagement across phases is crucial for product advancement. The integration of insights, often sourced from secondary data and models like the DONE and CFCP frameworks , provides strategic direction and a market-oriented approach. The study highlights that innovation is an iterative process and stresses the critical need for integrating insights from various disciplines throughout development. While the cases were limited to the Discover and Define phases, the application confirmed the CFD model's value as a structured approach to consumer-oriented innovation in the Food and Beverage (FNB) sector.
DOI: 10.15468/dl.x4wr9s
title: Occurrence Download

description: A dataset containing 225161 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.24_1",
 "Year 2015-2025"
 ]
}

 The dataset includes 225161 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000293-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/w9gp687zk5
title: Replication data for: "JUE Insight: Moving Cost Magnitudes in Moving Cost Models"

description: This dataset includes replication data for "JUE Insight: Moving Cost Magnitudes in Moving Cost Models," by Greg Howard in the Journal of Urban Economics. Below is the abstract of the paper:

The internal migration literature has estimated a wide range of moving costs, including some that are several times larger than annual income. How should economists interpret this estimate? I show that in standard models, average moving costs can be decomposed into an ``information'' term and a ``returns to migration'' term. The information term is proportional to the Shannon entropy of next period's location minus the Shannon information of staying in the same location. In simple models, the information term is much larger than the returns to migration term; in some cases, the returns to migration term is zero. Therefore, average moving costs are a helpful statistic about the model's predictive power regarding future moves but are not invariant to seemingly innocuous choices of the modeler.
DOI: 10.17632/w9gp687zk5.1
title: Replication data for: "JUE Insight: Moving Cost Magnitudes in Moving Cost Models"

description: This dataset includes replication data for "JUE Insight: Moving Cost Magnitudes in Moving Cost Models," by Greg Howard in the Journal of Urban Economics. Below is the abstract of the paper:

The internal migration literature has estimated a wide range of moving costs, including some that are several times larger than annual income. How should economists interpret this estimate? I show that in standard models, average moving costs can be decomposed into an ``information'' term and a ``returns to migration'' term. The information term is proportional to the Shannon entropy of next period's location minus the Shannon information of staying in the same location. In simple models, the information term is much larger than the returns to migration term; in some cases, the returns to migration term is zero. Therefore, average moving costs are a helpful statistic about the model's predictive power regarding future moves but are not invariant to seemingly innocuous choices of the modeler.
DOI: 10.15468/dl.ztg2ag
title: Occurrence Download

description: A dataset containing 1216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Drechslera",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1216 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000349-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9z43x4c6yr
title: Intermediation Frictions In Equity Markets (Replication Materials)

description: Replication Package for "Intermediation Frictions in Equity Markets" by Bryan Seegmiller
DOI: 10.15468/dl.nqvf8d
title: Occurrence Download

description: A dataset containing 664 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Otocolobus manul"
 ]
}

 The dataset includes 664 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000348-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9z43x4c6yr.2
title: Intermediation Frictions In Equity Markets (Replication Materials)

description: Replication Package for "Intermediation Frictions in Equity Markets" by Bryan Seegmiller
DOI: 10.17632/4xvj32x325
title: Dataset for "Aroma profile of oxidatively aged White and Tawny Port wines with different indication of age. Contribution of the non-rectified wine spirit"

description: This dataset contains chromatograms acquired from White and Tawny Port wine samples used in the study “Aroma profile of oxidatively aged White and Tawny Port wines with different indication of age: Contribution of the non-rectified wine spirit.” The dataset includes analytical outputs generated through MHS-SPME-GC–MS for the purpose of characterizing volatile aroma compounds associated with oxidative aging.
Each chromatogram represents the volatile composition of an individual Port wine sample. Samples cover several categories of Port wines with different indications of age (e.g., 10-year, 20-year, 30-year, and 40-year designations), including both White and Tawny styles.
DOI: 10.15468/dl.tt958c
title: Occurrence Download

description: A dataset containing 2350 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 7.2186525075025",
 "DecimalLongitude is less than 7.2217120606869",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 2350 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000350-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.