cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2jw6f2
title: CCDC 2349844: Experimental Crystal Structure Determination

description: Related Article: Guowei Chen, Si-Wei Chen, Yaozu Su, Ru-Jia Wang, Luo Huang, Xiao-Long Liu, Long-Jiang Xing, Bo Liu, Jia-Ming Jin, Yanping Huo, Season Si Chen, Shaomin Ji, Man-Chung Tang, Wen-Cheng Chen|2025|Adv.Funct.Mater.|35|2501039|doi:10.1002/adfm.202501039
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: 10.7910/dvn/8wyegi
title: Soul Science by Pawan Upadhyay

description: Soul Science presents a unified spiritual-biological model proposing that the soul enters living systems at the exact moment life begins—specifically, during zygote formation in humans and seed germination in plants. The model suggests that the presence of the soul is the driving force behind the activation of cellular processes, rapid cell division, coordinated growth, and the emergence of a unified living organism. This paper explores these concepts in a structured scientific-spiritual framework.
DOI: 10.21950/3sk54x
title: Federico-Tena World Population Historical Database : List of Polities (World countries)

description: Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: List of Polities (World countries)
description: Microsoft Excel
description: Web site: <strong>https://www.uc3m.es/investigacion/federico-tena-population</strong>
DOI: 10.6084/m9.figshare.25050242
title: Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation

description: This article advocates proximal Markov chain Monte Carlo (ProxMCMC) as a flexible and general Bayesian inference framework for constrained or regularized estimation. Originally introduced in the Bayesian imaging literature, ProxMCMC employs the Moreau-Yosida envelope for a smooth approximation of the total-variation regularization term, fixes variance and regularization strength parameters as constants, and uses the Langevin algorithm for the posterior sampling. We extend ProxMCMC to be fully Bayesian by providing data-adaptive estimation of all parameters including the regularization strength parameter. More powerful sampling algorithms such as Hamiltonian Monte Carlo are employed to scale ProxMCMC to high-dimensional problems. Analogous to the proximal algorithms in optimization, ProxMCMC offers a versatile and modularized procedure for conducting statistical inference on constrained and regularized problems. The power of ProxMCMC is illustrated on various statistical estimation and machine learning tasks, the inference of which is traditionally considered difficult from both frequentist and Bayesian perspectives.
DOI: 10.6084/m9.figshare.25050242.v1
title: Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation

description: This article advocates proximal Markov chain Monte Carlo (ProxMCMC) as a flexible and general Bayesian inference framework for constrained or regularized estimation. Originally introduced in the Bayesian imaging literature, ProxMCMC employs the Moreau-Yosida envelope for a smooth approximation of the total-variation regularization term, fixes variance and regularization strength parameters as constants, and uses the Langevin algorithm for the posterior sampling. We extend ProxMCMC to be fully Bayesian by providing data-adaptive estimation of all parameters including the regularization strength parameter. More powerful sampling algorithms such as Hamiltonian Monte Carlo are employed to scale ProxMCMC to high-dimensional problems. Analogous to the proximal algorithms in optimization, ProxMCMC offers a versatile and modularized procedure for conducting statistical inference on constrained and regularized problems. The power of ProxMCMC is illustrated on various statistical estimation and machine learning tasks, the inference of which is traditionally considered difficult from both frequentist and Bayesian perspectives.
DOI: 10.6084/m9.figshare.25189094
title: Fitting Log-Gaussian Cox Processes Using Generalized Additive Model Software

description: While log-Gaussian Cox process regression models are useful tools for modeling point patterns, they can be technically difficult to fit and require users to learn/adopt bespoke software. We show that, for suitably formatted data, we can actually fit these models using generalized additive model software, via a simple line of code, demonstrated on R by the popular mgcv package. We are able to do this because a common and computationally efficient way to fit a log-Gaussian Cox process model is to use a basis function expansion to approximate the Gaussian random field, as is provided by a generic bivariate smoother over geographic space. We further show that if basis functions are parameterized appropriately then we can estimate parameters in the spatial covariance function for the latent random field using a generalized additive model. We use simulation to show that this approach leads to model fits of comparable quality to state-of-the-art software, often more quickly. But we see the main advance from this work as lowering the technology barrier to spatial statistics for applied researchers, many of whom are already familiar with generalized additive model software.
DOI: 10.6084/m9.figshare.25189094.v2
title: Fitting Log-Gaussian Cox Processes Using Generalized Additive Model Software

description: While log-Gaussian Cox process regression models are useful tools for modeling point patterns, they can be technically difficult to fit and require users to learn/adopt bespoke software. We show that, for suitably formatted data, we can actually fit these models using generalized additive model software, via a simple line of code, demonstrated on R by the popular mgcv package. We are able to do this because a common and computationally efficient way to fit a log-Gaussian Cox process model is to use a basis function expansion to approximate the Gaussian random field, as is provided by a generic bivariate smoother over geographic space. We further show that if basis functions are parameterized appropriately then we can estimate parameters in the spatial covariance function for the latent random field using a generalized additive model. We use simulation to show that this approach leads to model fits of comparable quality to state-of-the-art software, often more quickly. But we see the main advance from this work as lowering the technology barrier to spatial statistics for applied researchers, many of whom are already familiar with generalized additive model software.
DOI: 10.6084/m9.figshare.25189094.v1
title: Fitting log-Gaussian Cox processes using generalized additive model software

description: While log-Gaussian Cox process regression models are useful tools for modeling point patterns, they can be technically difficult to fit and require users to learn/adopt bespoke software. We show that, for suitably formatted data, we can actually fit these models using generalized additive model software, via a simple line of code, demonstrated on R by the popular mgcv package. We are able to do this because a common and computationally efficient way to fit a log-Gaussian Cox process model is to use a basis function expansion to approximate the Gaussian random field, as is provided by a generic bivariate smoother over geographic space. We further show that if basis functions are parameterized appropriately then we can estimate parameters in the spatial covariance function for the latent random field using a generalized additive model. We use simulation to show that this approach leads to model fits of comparable quality to state-of-the-art software, often more quickly. But we see the main advance from this work as lowering the technology barrier to spatial statistics for applied researchers, many of whom are already familiar with generalized additive model software.
DOI: 10.15159/phytop.154
title: Harku

description: Phytoplankton biomass, diversity and abundance in samples collected from Lake Harku during the period 1953-2009.
DOI: 10.6084/m9.figshare.29114100
title: Zero-Truncated Modelling in a Meta-Analysis on Suicide Data after Bariatric Surgery

description: Meta-analysis is a well-established method for integrating results from several independent studies to estimate a common quantity of interest. However, meta-analysis is prone to selection bias, notably when particular studies are systematically excluded. This can lead to bias in estimating the quantity of interest. Motivated by a meta-analysis to estimate the rate of completed-suicide after bariatric surgery, where studies which reported no suicides were excluded, a novel zero-truncated count modeling approach was developed. This approach addresses heterogeneity, both observed and unobserved, through covariate and overdispersion modeling, respectively. Additionally, through the Horvitz-Thompson estimator, an approach is developed to estimate the number of excluded studies, a quantity of potential interest for researchers. Uncertainty quantification for both estimation of suicide rates and number of excluded studies is achieved through a parametric bootstrapping approach.
DOI: 10.6084/m9.figshare.29114100.v1
title: Zero-Truncated Modelling in a Meta-Analysis on Suicide Data after Bariatric Surgery

description: Meta-analysis is a well-established method for integrating results from several independent studies to estimate a common quantity of interest. However, meta-analysis is prone to selection bias, notably when particular studies are systematically excluded. This can lead to bias in estimating the quantity of interest. Motivated by a meta-analysis to estimate the rate of completed-suicide after bariatric surgery, where studies which reported no suicides were excluded, a novel zero-truncated count modeling approach was developed. This approach addresses heterogeneity, both observed and unobserved, through covariate and overdispersion modeling, respectively. Additionally, through the Horvitz-Thompson estimator, an approach is developed to estimate the number of excluded studies, a quantity of potential interest for researchers. Uncertainty quantification for both estimation of suicide rates and number of excluded studies is achieved through a parametric bootstrapping approach.
DOI: 10.6084/m9.figshare.30053626
title: Near-Peer Mentoring in Data Science: A Plot for Mutual Growth

description: Universities have been expanding undergraduate data science programs. Involving graduate students in these new opportunities can foster their growth as data science educators. We describe two programs that employ a near-peer mentoring structure, in which graduate students mentor undergraduates, to (a) strengthen their teaching and mentoring skills and (b) provide research and learning experiences for undergraduates from diverse backgrounds. In the Data Science for Social Good program, undergraduate participants work in teams to tackle a data science project with social impact. Graduate mentors guide project work and provide just-in-time teaching and feedback. The Stanford Mentoring in Data Science course offers training in effective and inclusive mentorship strategies. In an experiential learning framework, enrolled graduate students are paired with undergraduate students from non-R1 schools, whom they mentor through weekly one-on-one remote meetings. In end-of-program surveys, mentors reported growth through both programs. Drawing from these experiences, we developed a self-paced mentor training guide, which engages teaching, mentoring and project management abilities. These initiatives and the shared materials can serve as prototypes of future programs that cultivate mutual growth of both undergraduate and graduate students in a high-touch, inclusive, and encouraging environment.
DOI: 10.6084/m9.figshare.30053626.v1
title: Near-Peer Mentoring in Data Science: A Plot for Mutual Growth

description: Universities have been expanding undergraduate data science programs. Involving graduate students in these new opportunities can foster their growth as data science educators. We describe two programs that employ a near-peer mentoring structure, in which graduate students mentor undergraduates, to (a) strengthen their teaching and mentoring skills and (b) provide research and learning experiences for undergraduates from diverse backgrounds. In the Data Science for Social Good program, undergraduate participants work in teams to tackle a data science project with social impact. Graduate mentors guide project work and provide just-in-time teaching and feedback. The Stanford Mentoring in Data Science course offers training in effective and inclusive mentorship strategies. In an experiential learning framework, enrolled graduate students are paired with undergraduate students from non-R1 schools, whom they mentor through weekly one-on-one remote meetings. In end-of-program surveys, mentors reported growth through both programs. Drawing from these experiences, we developed a self-paced mentor training guide, which engages teaching, mentoring and project management abilities. These initiatives and the shared materials can serve as prototypes of future programs that cultivate mutual growth of both undergraduate and graduate students in a high-touch, inclusive, and encouraging environment.
DOI: 10.5281/zenodo.18329807
title: A multi-method Antarctic atmospheric blocking dataset based on ERA5 (1979–2024)

description: Overview of the Blocking Dataset

Each folder corresponds to one blocking detection method applied to either Z500 or PV.

The dataset contains the following method folders:

PV-Abs, PV-SD, PV-Perc, Z500-Abs, Z500-Abs_detrend, Z500-Grad, Z500-Perc, Z500-Perc_detrend, Z500-SD, Z500-SD_detrend.

All methods use the same data structure described below.

1. Variables

Z500Geopotential height at 500 hPa.

PVVertically integrated potential vorticity (150–500 hPa).

2. Blocking Detection Methods (names only)

Absolute threshold method: Z500-Abs, PV-AbsStandard deviation anomaly method: Z500-SD, PV-SDPercentile-based anomaly method: Z500-Perc, PV-PercGradient method: Z500-GradDetrended variants: Z500-Abs_detrend, Z500-Perc_detrend, Z500-SD_detrend

3. Contents of Each Method Folder

Every method folder contains four subdirectories:

3.1 blocking/

Instantaneous blocking masks (6-hourly, 1979–2024).Each file contains gridcell values: 1 = blocked, 0 = not blocked.

3.2 blocking_id/

Event ID fields for tracked blocking events and each blocked gridcell has an event number.

3.3 clim/

Blocking climatologies derived from the full record.Provided at annual, seasonal, and monthly timescales.Each includes:



Blocking frequency

Blocking intensity

Blocking persistence


Example filenames:ERA5_blocking_frequency_PV-Perc_clim_annual_SH.ncERA5_blocking_intensity_PV-Perc_clim_seasonal_SH.ncERA5_blocking_persistence_PV-Perc_clim_monthly_SH.nc

3.4 time_series/

Time series of blocking metrics aggregated over the Southern Hemisphere.Provided at annual, seasonal, and monthly timescales.Each includes:



Blocking frequency

Blocking intensity

Blocking persistence


Example filenames:ERA5_blocking_frequency_PV-Perc_timeseries_annual_SH.ncERA5_blocking_persistence_PV-Perc_timeseries_seasonal_SH.ncERA5_blocking_intensity_PV-Perc_timeseries_monthly_SH.nc

4. Summary

Each blocking method folder includes:

1.    blocking/ — instantaneous masks

2.    blocking_id/ — labeled events

3.    clim/ — climatologies

4.    time_series/ — time series
DOI: 10.5281/zenodo.18329806
title: A multi-method Antarctic atmospheric blocking dataset based on ERA5 (1979–2024)

description: Overview of the Blocking Dataset

Each folder corresponds to one blocking detection method applied to either Z500 or PV.

The dataset contains the following method folders:

PV-Abs, PV-SD, PV-Perc, Z500-Abs, Z500-Abs_detrend, Z500-Grad, Z500-Perc, Z500-Perc_detrend, Z500-SD, Z500-SD_detrend.

All methods use the same data structure described below.

1. Variables

Z500Geopotential height at 500 hPa.

PVVertically integrated potential vorticity (150–500 hPa).

2. Blocking Detection Methods (names only)

Absolute threshold method: Z500-Abs, PV-AbsStandard deviation anomaly method: Z500-SD, PV-SDPercentile-based anomaly method: Z500-Perc, PV-PercGradient method: Z500-GradDetrended variants: Z500-Abs_detrend, Z500-Perc_detrend, Z500-SD_detrend

3. Contents of Each Method Folder

Every method folder contains four subdirectories:

3.1 blocking/

Instantaneous blocking masks (6-hourly, 1979–2024).Each file contains gridcell values: 1 = blocked, 0 = not blocked.

3.2 blocking_id/

Event ID fields for tracked blocking events and each blocked gridcell has an event number.

3.3 clim/

Blocking climatologies derived from the full record.Provided at annual, seasonal, and monthly timescales.Each includes:



Blocking frequency

Blocking intensity

Blocking persistence


Example filenames:ERA5_blocking_frequency_PV-Perc_clim_annual_SH.ncERA5_blocking_intensity_PV-Perc_clim_seasonal_SH.ncERA5_blocking_persistence_PV-Perc_clim_monthly_SH.nc

3.4 time_series/

Time series of blocking metrics aggregated over the Southern Hemisphere.Provided at annual, seasonal, and monthly timescales.Each includes:



Blocking frequency

Blocking intensity

Blocking persistence


Example filenames:ERA5_blocking_frequency_PV-Perc_timeseries_annual_SH.ncERA5_blocking_persistence_PV-Perc_timeseries_seasonal_SH.ncERA5_blocking_intensity_PV-Perc_timeseries_monthly_SH.nc

4. Summary

Each blocking method folder includes:

1.    blocking/ — instantaneous masks

2.    blocking_id/ — labeled events

3.    clim/ — climatologies

4.    time_series/ — time series
DOI: 10.5878/002375
title: The National SOM Survey 1990
title: Den nationella SOM-undersökningen 1990
title: Riks-SOM 1990

description: The questionnaire for the fifth study in the series of annual SOM surveys was divided into seven subject fields: mass media; politics and society; energy, nuclear power and environment; Sweden´s relation to other countries; Islam; leisure; and background. The SOM surveys contains a core of questions asked annually. New questions in SOM90 dealt with good qualities in daily papers; priority of news from different areas; confidence in Swedish mass media; whether different activities should be handled by the public sector or by private enterprises, associations, or by individuals; government intervention; opinions on different suggestions in the Swedish environmental debate, and own environmental activities; attitudes toward Islam.

Purpose:
The main purpose is to establish time series that enable researchers to analyse how various changes in society affect people's attitudes and behaviour.

The SOM Institute also has an online tool for data analysis, where you can work with data from the national SOM surveys directly in your web browser. You can find it at www.som-institutet/dataanalys
description: Detta är den femte undersökningen i serien Riks-SOM, en nationell frågeundersökning med syfte att kartlägga den svenska allmänhetens vanor och attityder på temat samhälle, opinioner och medier.

1990 års undersökning består av sju sammanhållna delar: massmedier; politik och samhälle; energi, kärnkraft och miljö; Sveriges förhållande till omvärlden; islam; fritid; samt bakgrundsuppgifter.

Många av frågorna har ställts i tidigare SOM-undersökning, men ett antal frågor har tillkommit. Nya frågeställningar i Riks-SOM 1990 gäller viktiga egenskaper hos en dagstidning; prioritering av nyheter från olika områden; förtroende för de svenska massmedierna; huruvida olika verksamheter bör skötas av stat och kommun eller av privata företag, föreningar eller enskilda; statens styrning av kommuner, näringsliv och enskilda; åsikter om olika förslag i den svenska miljödebatten, samt egna miljöaktiviteter; och inställning till islam.

Genom att frågor ställts på ett likartat sätt över tid finns det i SOM-serien tidsserier om bland annat medieanvändning, politik, kärnkraftsopinion och förtroende för olika samhällsinstitutioner och grupper.

Syfte:
Huvudsyftet är att etablera tidsserier som gör det möjligt att analysera hur olika samhällsförändringar påverkar människors attityder och beteenden.

SOM-institutet har även ett onlineverktyg för dataanalys, där du kan arbeta med data från de nationella SOM-undersökningarna direkt i din webbläsare. Du hittar det på https://som-institutet.se/dataanalys
DOI: 10.5878/000173
title: The National SOM Survey 1990
title: Den nationella SOM-undersökningen 1990
title: Riks-SOM 1990

description: The questionnaire for the fifth study in the series of annual SOM surveys was divided into seven subject fields: mass media; politics and society; energy, nuclear power and environment; Sweden´s relation to other countries; Islam; leisure; and background. The SOM surveys contains a core of questions asked annually. New questions in SOM90 dealt with good qualities in daily papers; priority of news from different areas; confidence in Swedish mass media; whether different activities should be handled by the public sector or by private enterprises, associations, or by individuals; government intervention; opinions on different suggestions in the Swedish environmental debate, and own environmental activities; attitudes toward Islam.

Purpose:
The main purpose is to establish time series that enable researchers to analyse how various changes in society affect people's attitudes and behaviour.

The SOM Institute also has an online tool for data analysis, where you can work with data from the national SOM surveys directly in your web browser. You can find it at www.som-institutet/dataanalys
description: Detta är den femte undersökningen i serien Riks-SOM, en nationell frågeundersökning med syfte att kartlägga den svenska allmänhetens vanor och attityder på temat samhälle, opinioner och medier.

1990 års undersökning består av sju sammanhållna delar: massmedier; politik och samhälle; energi, kärnkraft och miljö; Sveriges förhållande till omvärlden; islam; fritid; samt bakgrundsuppgifter.

Många av frågorna har ställts i tidigare SOM-undersökning, men ett antal frågor har tillkommit. Nya frågeställningar i Riks-SOM 1990 gäller viktiga egenskaper hos en dagstidning; prioritering av nyheter från olika områden; förtroende för de svenska massmedierna; huruvida olika verksamheter bör skötas av stat och kommun eller av privata företag, föreningar eller enskilda; statens styrning av kommuner, näringsliv och enskilda; åsikter om olika förslag i den svenska miljödebatten, samt egna miljöaktiviteter; och inställning till islam.

Genom att frågor ställts på ett likartat sätt över tid finns det i SOM-serien tidsserier om bland annat medieanvändning, politik, kärnkraftsopinion och förtroende för olika samhällsinstitutioner och grupper.

Syfte:
Huvudsyftet är att etablera tidsserier som gör det möjligt att analysera hur olika samhällsförändringar påverkar människors attityder och beteenden.

SOM-institutet har även ett onlineverktyg för dataanalys, där du kan arbeta med data från de nationella SOM-undersökningarna direkt i din webbläsare. Du hittar det på https://som-institutet.se/dataanalys
DOI: 10.5518/1537
title: Code, Grasshopper files and csv data for r-funicularity/CRA analyses

description: A collection of Grasshopper(R) scripts, CSV data files, SAP2000 files and Matlab scripts accompanying the paper "Integrating R-funicularity, local stability and inter-panel constraint assessment for discrete timber shell construction design", Structures, Elsevier, 2024. Files allow the recreation of R-funicularity analyses, using Matlab and Rhino/Grasshopper, as well as CRA analyses, when combined with the compas_CRA library.