cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24534871
title: Supplementary Table S2:<b> </b>Sequences of the mimics, inhibitors, and controls of two miRNAs.

description: Supplementary Table S2:<b> </b>Sequences of the mimics, inhibitors, and controls of two miRNAs.
DOI: 10.17909/r6n6-3m45
title: Data from Paper
DOI: 10.6084/m9.figshare.24534850
title: Raw Data for Icon Experiment

description: The raw data of icon experiment.
DOI: 10.6084/m9.figshare.24534850.v1
title: Raw Data for Icon Experiment

description: The raw data of icon experiment.
DOI: 10.6084/m9.figshare.24534916
title: Supplementary Table S3: Primers used in quantitative real-time PCR.

description: Supplementary Table S3: Primers used in quantitative real-time PCR.
DOI: 10.6084/m9.figshare.24534925
title: Supplementary Table S4:<b> </b>Candidate genetic variants identified in the <i>HSP90AA1</i> gene of Holstein cows.

description: Supplementary Table S4:<b> </b>Candidate genetic variants identified in the <i>HSP90AA1</i> gene of Holstein cows.
DOI: 10.6084/m9.figshare.24534931
title: Supplementary Table S5: Association analyses between five genetic variants and three physiological indicators of heat stress in Holstein cows.

description: Supplementary Table S5: Association analyses between five genetic variants and three physiological indicators of heat stress in Holstein cows.
DOI: 10.17882/91156
title: Hydrographic dataset from the Eurofleets+ SINES 2022 research cruise in the Iberian Upwelling System

description: This dataset contains the hydrographic data for all the stations conducted during the EUROFLEETS+ SINES cruise that took place aboard the R/V Sarmiento de Gamboa between 11-20th of September 2022. The project "Climate change impact on ocean fronts ecosystems: The case of the Iberian Upwelling System (SINES)" was planned to be a proof of concept cruise of multidisciplinary research: integrating satellite data to past sediment records within classical methods in oceanography research and automated underwater vehicles to tackle the characterization of the Iberian Margin Upwelling System. The overall objective of this study is to identify the changes and risks for marine ecosystem services deriving from the potential impact of climate change on upwelling fronts. This research cruise was funded by the Eurofleets+ SEA Programme Call “REGIONAL” in 2019/2020 and was led by the Centre of Marine Sciences of Algarve (CCMAR, Portugal). The proposed multidisciplinary expedition was carried out between 11-19th September 2022. Full depth water column CTD profiles were collected at all the stations (15 stations, 19 CTD casts, i.e, four stations with double cast -shallow and deep-). In 12 stations, a vertical multinet haul was also collected. The depth of the multinet samples (100 µm mesh) range between 700 m and surface. A deployment of a Light Autonomous Underwater Vehicle (LAUV Explore-4) was done on 17-18th of September. The AUV conducted more than 100 high-resolution immersion profiles between the surface and 10/50/100 m depth following the track of the research vessel between the coast and the position 37.35ºN 9.4ºW. This repository included also remote sensing data from satellite observations and the processed hull mounted Acoustic Doppler Current Profiler (ADCP) data. Complete list of stations, events and positions of EUROFLEETS+ SINES also available in the dataset.
DOI: 10.20351/29sg20220911
title: SINES Cruise, RV Sarmiento de Gamboa

description: Oceanographic data acquired during the SINES Cruise (29SG20220911)  on board the Research Vessel Sarmiento de Gamboa in 2022.
DOI: 10.6084/m9.figshare.24534808
title: Supplementary Table S1: Primers for amplification of the <i>HSP90AA1</i> gene.

description: Primers for amplification of the <i>HSP90AA1</i> gene.
DOI: 10.14473/csda/hvf1pp
title: Naše společnost SPECIÁL 2021 - únor

description: Výzkum provedl výzkumný tým CVVM Sociologického ústavu AV ČR, v.v.i., v rámci výzkumu „Naše společnost 2021". V důsledku epidemiologické situace nebyl výzkum proveden tradičním způsobem. Data za měsíc únor byla sesbírána agenturou Medián, výlučně metodou CAWI a CATI, tedy kombinací telefonického dotazování a sběru prostřednictvím online panelu. Respondenti byli vybráni do výzkumu na základě kvótních požadavků. Výsledná velikost výběrového souboru po kontrolách klientem je 1035. Podrobnosti k výzkumu naleznete v přiložených technických informacích.
DOI: 10.6084/m9.figshare.24139608.v2
title: Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution

description: Children’s health studies support an association between maternal environmental exposures and children’s birth outcomes. A common goal is to identify critical windows of susceptibility—periods during gestation with increased association between maternal exposures and a future outcome. The timing of the critical windows and magnitude of the associations are likely heterogeneous across different levels of individual, family, and neighborhood characteristics. Using an administrative Colorado birth cohort we estimate the individualized relationship between weekly exposures to fine particulate matter (PM<sub>2.5</sub>) during gestation and birth weight. To achieve this goal, we propose a statistical learning method combining distributed lag models and Bayesian additive regression trees to estimate critical windows at the individual level and identify characteristics that induce heterogeneity from a high-dimensional set of potential modifying factors. We find evidence of heterogeneity in the PM<sub>2.5</sub>—birth weight relationship, with some mother—child dyads showing a three times larger decrease in birth weight for an IQR increase in exposure (5.9–8.5 μg/m3 PM<sub>2.5</sub>) compared to the population average. Specifically, we find increased vulnerability for non-Hispanic mothers who are either younger, have higher body mass index or lower educational attainment. Our case study is the first precision health study of critical windows. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24139608
title: Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution

description: Children’s health studies support an association between maternal environmental exposures and children’s birth outcomes. A common goal is to identify critical windows of susceptibility—periods during gestation with increased association between maternal exposures and a future outcome. The timing of the critical windows and magnitude of the associations are likely heterogeneous across different levels of individual, family, and neighborhood characteristics. Using an administrative Colorado birth cohort we estimate the individualized relationship between weekly exposures to fine particulate matter (PM<sub>2.5</sub>) during gestation and birth weight. To achieve this goal, we propose a statistical learning method combining distributed lag models and Bayesian additive regression trees to estimate critical windows at the individual level and identify characteristics that induce heterogeneity from a high-dimensional set of potential modifying factors. We find evidence of heterogeneity in the PM<sub>2.5</sub>—birth weight relationship, with some mother—child dyads showing a three times larger decrease in birth weight for an IQR increase in exposure (5.9–8.5 μg/m3 PM<sub>2.5</sub>) compared to the population average. Specifically, we find increased vulnerability for non-Hispanic mothers who are either younger, have higher body mass index or lower educational attainment. Our case study is the first precision health study of critical windows. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24139608.v1
title: Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution

description: Children’s health studies support an association between maternal environmental exposures and children’s birth outcomes. A common goal is to identify critical windows of susceptibility–periods during gestation with increased association between maternal exposures and a future outcome. The timing of the critical windows and magnitude of the associations are likely heterogeneous across different levels of individual, family, and neighborhood characteristics. Using an administrative Colorado birth cohort we estimate the individualized relationship between weekly exposures to fine particulate matter (PM 2.5) during gestation and birth weight. To achieve this goal, we propose a statistical learning method combining distributed lag models and Bayesian additive regression trees to estimate critical windows at the individual level and identify characteristics that induce heterogeneity from a high-dimensional set of potential modifying factors. We find evidence of heterogeneity in the PM 2.5–birth weight relationship, with some mother-child dyads showing a 3 times larger decrease in birth weight for an IQR increase in exposure (5.9 to 8.5 μg/m3 PM 2.5) compared to the population average. Specifically, we find increased vulnerability for non-Hispanic mothers who are either younger, have higher body mass index or lower educational attainment. Our case study is the first precision health study of critical windows.
DOI: 10.6084/m9.figshare.24171450.v2
title: Bayesian Inference on High-Dimensional Multivariate Binary Responses

description: It has become increasingly common to collect high-dimensional binary response data; for example, with the emergence of new sampling techniques in ecology. In smaller dimensions, multivariate probit (MVP) models are routinely used for inferences. However, algorithms for fitting such models face issues in scaling up to high dimensions due to the intractability of the likelihood, involving an integral over a multivariate normal distribution having no analytic form. Although a variety of algorithms have been proposed to approximate this intractable integral, these approaches are difficult to implement and/or inaccurate in high dimensions. Our main focus is in accommodating high-dimensional binary response data with a small-to-moderate number of covariates. We propose a two-stage approach for inference on model parameters while taking care of uncertainty propagation between the stages. We use the special structure of latent Gaussian models to reduce the highly expensive computation involved in joint parameter estimation to focus inference on marginal distributions of model parameters. This essentially makes the method embarrassingly parallel for both stages. We illustrate performance in simulations and applications to joint species distribution modeling in ecology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24171450
title: Bayesian Inference on High-Dimensional Multivariate Binary Responses

description: It has become increasingly common to collect high-dimensional binary response data; for example, with the emergence of new sampling techniques in ecology. In smaller dimensions, multivariate probit (MVP) models are routinely used for inferences. However, algorithms for fitting such models face issues in scaling up to high dimensions due to the intractability of the likelihood, involving an integral over a multivariate normal distribution having no analytic form. Although a variety of algorithms have been proposed to approximate this intractable integral, these approaches are difficult to implement and/or inaccurate in high dimensions. Our main focus is in accommodating high-dimensional binary response data with a small-to-moderate number of covariates. We propose a two-stage approach for inference on model parameters while taking care of uncertainty propagation between the stages. We use the special structure of latent Gaussian models to reduce the highly expensive computation involved in joint parameter estimation to focus inference on marginal distributions of model parameters. This essentially makes the method embarrassingly parallel for both stages. We illustrate performance in simulations and applications to joint species distribution modeling in ecology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24171450.v1
title: Bayesian inference on high-dimensional multivariate binary responses

description: It has become increasingly common to collect high-dimensional binary response data; for example, with the emergence of new sampling techniques in ecology. In smaller dimensions, multivariate probit (MVP) models are routinely used for inferences. However, algorithms for fitting such models face issues in scaling up to high dimensions due to the intractability of the likelihood, involving an integral over a multivariate normal distribution having no analytic form. Although a variety of algorithms have been proposed to approximate this intractable integral, these approaches are difficult to implement and/or inaccurate in high dimensions. Our main focus is in accommodating high-dimensional binary response data with a small-to-moderate number of covariates. We propose a two-stage approach for inference on model parameters while taking care of uncertainty propagation between the stages. We use the special structure of latent Gaussian models to reduce the highly expensive computation involved in joint parameter estimation to focus inference on marginal distributions of model parameters. This essentially makes the method embarrassingly parallel for both stages. We illustrate performance in simulations and applications to joint species distribution modeling in ecology.
DOI: 10.17030/uclan.data.00000422
title: Rettie et al., 2023 - Taboo Data
DOI: 10.5281/zenodo.4071359
title: Table 1
DOI: 10.5281/zenodo.4071360
title: Table 1
DOI: 10.5281/zenodo.10091702
title: Impact of Social Media Marketing Activities and ESG Green Brand

description: Research data for "Impact of Social Media Marketing Activities and ESG Green Brand Involvement on Green Product Repurchase Intentions"
DOI: 10.5281/zenodo.10091701
title: Impact of Social Media Marketing Activities and ESG Green Brand

description: Research data for "Impact of Social Media Marketing Activities and ESG Green Brand Involvement on Green Product Repurchase Intentions"
DOI: 10.5281/zenodo.10091493
title: Semi-leptonic TTbar Production Dataset for Unfolding Studies
DOI: 10.5281/zenodo.10091494
title: Semi-leptonic TTbar Production Dataset for Unfolding Studies
DOI: 10.5281/zenodo.10091757
title: An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism

description: An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism
DOI: 10.5281/zenodo.10091756
title: An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism

description: An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism
DOI: 10.5281/zenodo.10083499
title: Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
DOI: 10.5281/zenodo.10082712
title: Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
DOI: 10.5281/zenodo.10082713
title: Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
DOI: 10.5281/zenodo.10083509
title: Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
DOI: 10.5281/zenodo.10091776
title: Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
DOI: 10.5281/zenodo.10086336
title: Dataset: A synthesis of the diversity of freshwater fish migrations in the Amazon basin

description: Migratory events of fishes in the Amazon basin
DOI: 10.5281/zenodo.10333095
title: GROBNICE U ULICI SV. DOMINIKA

description: Groblje ispred Crkve sv. Sebastiana u staroj jezgri Dubrovnika.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333098
title: Bootleg Transformer

description: Bootleg Transformer from Chinatown

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333099
title: Bootleg Transformer

description: Bootleg Transformer from Chinatown

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333100
title: Sta Maria in Calvenzano, Vizzolo Predabissi (MI)

description: ![](https://upload.wikimedia.org/wikipedia/commons/7/77/Vizzolo_Predabissi_chiesa_Calvenzano_facciata.JPG) Founded by the Cluniacs, the Church of Santa Maria is located in the hamlet of Calvenzano. A document from 1093 is proof that, in that year, the "de Meregnano" had authorisation to transfer its Church in Calvenzano to a Cluniac community: two years later it was transformed into an abbey. However, in 1558, the monastery was reduced to a commendam and later passed to the Milanese Chapter. The terra cotta used for the building is typically Lombard. On the late-15th-century façade, the portal has 12th-century reliefs. The apse has a fresco from the mid-14th century. According to tradition, Severino Boezio was executed here in 524.

Quick model on the fly, 129 shots under the rain with a Huawei p90

[Clunypedia](http://clunypedia.com/)/[map](http://clunypedia.com/map)

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333101
title: Sta Maria in Calvenzano, Vizzolo Predabissi (MI)

description: ![](https://upload.wikimedia.org/wikipedia/commons/7/77/Vizzolo_Predabissi_chiesa_Calvenzano_facciata.JPG) Founded by the Cluniacs, the Church of Santa Maria is located in the hamlet of Calvenzano. A document from 1093 is proof that, in that year, the "de Meregnano" had authorisation to transfer its Church in Calvenzano to a Cluniac community: two years later it was transformed into an abbey. However, in 1558, the monastery was reduced to a commendam and later passed to the Milanese Chapter. The terra cotta used for the building is typically Lombard. On the late-15th-century façade, the portal has 12th-century reliefs. The apse has a fresco from the mid-14th century. According to tradition, Severino Boezio was executed here in 524.

Quick model on the fly, 129 shots under the rain with a Huawei p90

[Clunypedia](http://clunypedia.com/)/[map](http://clunypedia.com/map)

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333102
title: Al-Thuqaibah - Basin 15/37

description: Al-Thuqaibah is an Iron Age II settlement spanning 1000 to 600 BCE. It is located south of Dhaid at the southern end of Al Madam oasis in central part of the Sharjah Emirate, United Arab Emirates. Over the last 30 years it has been investigated by archaeological teams from Sharjah, France, and Spain, uncovering mud-brick houses, gardens, and evidence of mud-brick manufacture. In the mud at the bottom of small basins are hundreds of preserved foot prints. GDH completed high-resolution scanning and photogrammetry to document the basins and the preserved features within them. These are basins 15 and 37 processed in Reality Capture from 402 images.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333103
title: Al-Thuqaibah - Basin 15/37

description: Al-Thuqaibah is an Iron Age II settlement spanning 1000 to 600 BCE. It is located south of Dhaid at the southern end of Al Madam oasis in central part of the Sharjah Emirate, United Arab Emirates. Over the last 30 years it has been investigated by archaeological teams from Sharjah, France, and Spain, uncovering mud-brick houses, gardens, and evidence of mud-brick manufacture. In the mud at the bottom of small basins are hundreds of preserved foot prints. GDH completed high-resolution scanning and photogrammetry to document the basins and the preserved features within them. These are basins 15 and 37 processed in Reality Capture from 402 images.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333104
title: Arbour Rotunda ( Low Poly )

description: * Made in Blender.
* **Arbour Rotunda in two color sets**
* Tris: 3 618
* Faces: 1 899
* Edges: 3 713
* Verts: 1 848
*

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333105
title: Arbour Rotunda ( Low Poly )

description: * Made in Blender.
* **Arbour Rotunda in two color sets**
* Tris: 3 618
* Faces: 1 899
* Edges: 3 713
* Verts: 1 848
*

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333107
title: Kugelbunker

description: Two ball bunkers from the 2nd World War on the site of the Bunker Museum in Bruckneudorf. The combat and observation bunkers, made in a simple concrete casting process, were used in large numbers in the Reichsschutzstellung (Ostwall) on the German-Hungarian border, which was built from September 1944. The military use of these improvised bunkers was very limited.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333108
title: Kugelbunker

description: Two ball bunkers from the 2nd World War on the site of the Bunker Museum in Bruckneudorf. The combat and observation bunkers, made in a simple concrete casting process, were used in large numbers in the Reichsschutzstellung (Ostwall) on the German-Hungarian border, which was built from September 1944. The military use of these improvised bunkers was very limited.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333109
title: Longforgan memorial

description: This headstone is situated in the Longforgan burial ground.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333110
title: Longforgan memorial

description: This headstone is situated in the Longforgan burial ground.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333111
title: Bimaristan Nur Al Din, Pointcloud section

description: Lidar data, from open heritage. Cliping box and uniform  point cloud.

Over eight centuries old, the Bimaristan Nur al-Din, is the earliest surviving site for the development of Islamic medicine. Throughout the building's lifetime, the site has functioned as a medical school as well as a place of healing in the heart of the old city of Damascus. Built in 1154, the building is characterized by its red brick muqarnas, elaborate entrance block, and finely carved wooden doors. The hospital was in use until the 20th century when it was converted into a Museum of Arabic Medicine and Science. The preservation of the building is a reminder of the major contributions of Islamic medicine to the world today.

CyArk 2019: Bimaristan Nur al-Din - LiDAR - Terrestrial , Photogrammetry - Terrestrial . Collected by Directorate General of Antiquities and Museums . Distrubuted by Open Heritage 3D. https://doi.org/10.26301/nkv2-bn91

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10333112
title: Bimaristan Nur Al Din, Pointcloud section

description: Lidar data, from open heritage. Cliping box and uniform  point cloud.

Over eight centuries old, the Bimaristan Nur al-Din, is the earliest surviving site for the development of Islamic medicine. Throughout the building's lifetime, the site has functioned as a medical school as well as a place of healing in the heart of the old city of Damascus. Built in 1154, the building is characterized by its red brick muqarnas, elaborate entrance block, and finely carved wooden doors. The hospital was in use until the 20th century when it was converted into a Museum of Arabic Medicine and Science. The preservation of the building is a reminder of the major contributions of Islamic medicine to the world today.

CyArk 2019: Bimaristan Nur al-Din - LiDAR - Terrestrial , Photogrammetry - Terrestrial . Collected by Directorate General of Antiquities and Museums . Distrubuted by Open Heritage 3D. https://doi.org/10.26301/nkv2-bn91

Source: Objaverse 1.0 / Sketchfab