cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14531542
title: ORNLERASE - EPA REGIONAL REMOVAL MANAGEMENT LEVELS FALL 2024 THQ=3.0

description: The Regional Removal Management Levels (RMLs) website provides essential tools for On-Scene Coordinators (OSCs) and site managers to assess the potential need for removal actions at contaminated sites. RMLs are chemical-specific concentrations applicable to contaminants in tap water, air, and soil, calculated using methodologies similar to those in the EPA's remedial program. However, RMLs focus on risk levels and exposure scenarios specific to identifying areas, contaminants, and conditions where removal authority may be appropriate.

Unlike Regional Screening Levels (RSLs), Preliminary Remediation Goals (PRGs), or cleanup standards mandated under Applicable or Relevant and Appropriate Requirements (ARARs) of CERCLA, RMLs are not intended to serve as cleanup levels. Instead, they help guide decisions on short-term removal actions based on site-specific threats. Final cleanup values must be tailored to address the unique risks at each site.

Under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), two types of response actions are authorized: remedial and removal. While remedial actions aim for long-term, significant risk reduction, removal actions focus on short-term stabilization or cleanup to address imminent and substantial threats to human health or the environment.

By integrating removal and remedial approaches, the EPA ensures efficient and effective management of environmental contamination, leveraging related triggers for initiating action and pursuing shared goals for site cleanup. The RMLs are a key component of this integrated strategy, facilitating timely responses to urgent environmental risks.
DOI: 10.5281/zenodo.14531543
title: ORNLERASE - EPA REGIONAL REMOVAL MANAGEMENT LEVELS FALL 2024 THQ=3.0

description: The Regional Removal Management Levels (RMLs) website provides essential tools for On-Scene Coordinators (OSCs) and site managers to assess the potential need for removal actions at contaminated sites. RMLs are chemical-specific concentrations applicable to contaminants in tap water, air, and soil, calculated using methodologies similar to those in the EPA's remedial program. However, RMLs focus on risk levels and exposure scenarios specific to identifying areas, contaminants, and conditions where removal authority may be appropriate.

Unlike Regional Screening Levels (RSLs), Preliminary Remediation Goals (PRGs), or cleanup standards mandated under Applicable or Relevant and Appropriate Requirements (ARARs) of CERCLA, RMLs are not intended to serve as cleanup levels. Instead, they help guide decisions on short-term removal actions based on site-specific threats. Final cleanup values must be tailored to address the unique risks at each site.

Under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), two types of response actions are authorized: remedial and removal. While remedial actions aim for long-term, significant risk reduction, removal actions focus on short-term stabilization or cleanup to address imminent and substantial threats to human health or the environment.

By integrating removal and remedial approaches, the EPA ensures efficient and effective management of environmental contamination, leveraging related triggers for initiating action and pursuing shared goals for site cleanup. The RMLs are a key component of this integrated strategy, facilitating timely responses to urgent environmental risks.
DOI: 10.5281/zenodo.14531502
title: ORNLERASE - EPA REGIONAL REMOVAL MANAGEMENT LEVELS FALL 2024 THQ=1.0

description: The Regional Removal Management Levels (RMLs) website provides essential tools for On-Scene Coordinators (OSCs) and site managers to assess the potential need for removal actions at contaminated sites. RMLs are chemical-specific concentrations applicable to contaminants in tap water, air, and soil, calculated using methodologies similar to those in the EPA's remedial program. However, RMLs focus on risk levels and exposure scenarios specific to identifying areas, contaminants, and conditions where removal authority may be appropriate.

Unlike Regional Screening Levels (RSLs), Preliminary Remediation Goals (PRGs), or cleanup standards mandated under Applicable or Relevant and Appropriate Requirements (ARARs) of CERCLA, RMLs are not intended to serve as cleanup levels. Instead, they help guide decisions on short-term removal actions based on site-specific threats. Final cleanup values must be tailored to address the unique risks at each site.

Under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), two types of response actions are authorized: remedial and removal. While remedial actions aim for long-term, significant risk reduction, removal actions focus on short-term stabilization or cleanup to address imminent and substantial threats to human health or the environment.

By integrating removal and remedial approaches, the EPA ensures efficient and effective management of environmental contamination, leveraging related triggers for initiating action and pursuing shared goals for site cleanup. The RMLs are a key component of this integrated strategy, facilitating timely responses to urgent environmental risks.
DOI: 10.5281/zenodo.14531503
title: ORNLERASE - EPA REGIONAL REMOVAL MANAGEMENT LEVELS FALL 2024 THQ=1.0

description: The Regional Removal Management Levels (RMLs) website provides essential tools for On-Scene Coordinators (OSCs) and site managers to assess the potential need for removal actions at contaminated sites. RMLs are chemical-specific concentrations applicable to contaminants in tap water, air, and soil, calculated using methodologies similar to those in the EPA's remedial program. However, RMLs focus on risk levels and exposure scenarios specific to identifying areas, contaminants, and conditions where removal authority may be appropriate.

Unlike Regional Screening Levels (RSLs), Preliminary Remediation Goals (PRGs), or cleanup standards mandated under Applicable or Relevant and Appropriate Requirements (ARARs) of CERCLA, RMLs are not intended to serve as cleanup levels. Instead, they help guide decisions on short-term removal actions based on site-specific threats. Final cleanup values must be tailored to address the unique risks at each site.

Under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), two types of response actions are authorized: remedial and removal. While remedial actions aim for long-term, significant risk reduction, removal actions focus on short-term stabilization or cleanup to address imminent and substantial threats to human health or the environment.

By integrating removal and remedial approaches, the EPA ensures efficient and effective management of environmental contamination, leveraging related triggers for initiating action and pursuing shared goals for site cleanup. The RMLs are a key component of this integrated strategy, facilitating timely responses to urgent environmental risks.
DOI: 10.15468/dl.jrtsx3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aiouea effusa (Meisn.) R.Rohde & Rohwer)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015876-250127130748423/datasets/export for details.
DOI: 10.5281/zenodo.14531206
title: ORNLERASE - EPA REGIONAL SCREENING LEVELS FALL 2024 THQ=0.1

description: The Regional Screening Levels (RSL) tables are a comprehensive resource developed by the U.S. Environmental Protection Agency (EPA) in collaboration with Oak Ridge National Laboratory (ORNL). It consolidates previous screening tables from multiple EPA regions into a unified platform, now serving as the primary source for screening levels across all EPA regions.

Designed to support Remedial Project Managers (RPMs), On-Scene Coordinators (OSCs), risk assessors, and other decision-makers, the website provides standardized screening tables and a dynamic calculator. These tools assist in evaluating contamination levels at CERCLA (Superfund) hazardous waste sites to determine if further investigation is warranted. While applicable to various programs, users should carefully consider the underlying assumptions to appropriately apply the screening levels (SLs).

The RSLs represent chemical-specific concentrations in air, drinking water, and soil that, if exceeded, may signal the need for additional analysis. The calculator can generate both default and site-specific concentrations for contaminants in soil, air, water, and sediment. SLs are particularly valuable during early project phases, such as Remedial Investigation (RI) scoping and chemical screening. However, these levels are not cleanup standards and should not be misconstrued as final remediation goals.

This tool integrates risk-based screening level equations, considering both carcinogenic and systemic toxicities of chemicals. Default tables address exposure scenarios for residential soil, outdoor worker soil, indoor air (residential and worker), and tap water. The SLs are derived using default exposure parameters and incorporate Reasonable Maximum Exposure (RME) conditions, ensuring standardized and reliable results for early-stage site assessment and planning.
DOI: 10.5281/zenodo.14531207
title: ORNLERASE - EPA REGIONAL SCREENING LEVELS FALL 2024 THQ=0.1

description: The Regional Screening Levels (RSL) tables are a comprehensive resource developed by the U.S. Environmental Protection Agency (EPA) in collaboration with Oak Ridge National Laboratory (ORNL). It consolidates previous screening tables from multiple EPA regions into a unified platform, now serving as the primary source for screening levels across all EPA regions.

Designed to support Remedial Project Managers (RPMs), On-Scene Coordinators (OSCs), risk assessors, and other decision-makers, the website provides standardized screening tables and a dynamic calculator. These tools assist in evaluating contamination levels at CERCLA (Superfund) hazardous waste sites to determine if further investigation is warranted. While applicable to various programs, users should carefully consider the underlying assumptions to appropriately apply the screening levels (SLs).

The RSLs represent chemical-specific concentrations in air, drinking water, and soil that, if exceeded, may signal the need for additional analysis. The calculator can generate both default and site-specific concentrations for contaminants in soil, air, water, and sediment. SLs are particularly valuable during early project phases, such as Remedial Investigation (RI) scoping and chemical screening. However, these levels are not cleanup standards and should not be misconstrued as final remediation goals.

This tool integrates risk-based screening level equations, considering both carcinogenic and systemic toxicities of chemicals. Default tables address exposure scenarios for residential soil, outdoor worker soil, indoor air (residential and worker), and tap water. The SLs are derived using default exposure parameters and incorporate Reasonable Maximum Exposure (RME) conditions, ensuring standardized and reliable results for early-stage site assessment and planning.
DOI: 10.15468/dl.s846kr
title: Occurrence Download

description: A dataset containing 896 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sardina pilchardus (Walbaum, 1792)",
 "HasCoordinate is true",
 "Geometry POLYGON ((-10 28, 38 28, 38 51, -10 51, -10 28))",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1850",
 "Year is less than or equal to 2014",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)"
 ]
}

 The dataset includes 896 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015877-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14527681
title: ORNLERASE - EPA REGIONAL SCREENING LEVELS FALL 2024 THQ=1.0

description: The Regional Screening Levels (RSL) tables are a comprehensive resource developed by the U.S. Environmental Protection Agency (EPA) in collaboration with Oak Ridge National Laboratory (ORNL). It consolidates previous screening tables from multiple EPA regions into a unified platform, now serving as the primary source for screening levels across all EPA regions.

Designed to support Remedial Project Managers (RPMs), On-Scene Coordinators (OSCs), risk assessors, and other decision-makers, the website provides standardized screening tables and a dynamic calculator. These tools assist in evaluating contamination levels at CERCLA (Superfund) hazardous waste sites to determine if further investigation is warranted. While applicable to various programs, users should carefully consider the underlying assumptions to appropriately apply the screening levels (SLs).

The RSLs represent chemical-specific concentrations in air, drinking water, and soil that, if exceeded, may signal the need for additional analysis. The calculator can generate both default and site-specific concentrations for contaminants in soil, air, water, and sediment. SLs are particularly valuable during early project phases, such as Remedial Investigation (RI) scoping and chemical screening. However, these levels are not cleanup standards and should not be misconstrued as final remediation goals.

This tool integrates risk-based screening level equations, considering both carcinogenic and systemic toxicities of chemicals. Default tables address exposure scenarios for residential soil, outdoor worker soil, indoor air (residential and worker), and tap water. The SLs are derived using default exposure parameters and incorporate Reasonable Maximum Exposure (RME) conditions, ensuring standardized and reliable results for early-stage site assessment and planning.
DOI: 10.5281/zenodo.14527682
title: ORNLERASE - EPA REGIONAL SCREENING LEVELS FALL 2024 THQ=1.0

description: The Regional Screening Levels (RSL) tables are a comprehensive resource developed by the U.S. Environmental Protection Agency (EPA) in collaboration with Oak Ridge National Laboratory (ORNL). It consolidates previous screening tables from multiple EPA regions into a unified platform, now serving as the primary source for screening levels across all EPA regions.

Designed to support Remedial Project Managers (RPMs), On-Scene Coordinators (OSCs), risk assessors, and other decision-makers, the website provides standardized screening tables and a dynamic calculator. These tools assist in evaluating contamination levels at CERCLA (Superfund) hazardous waste sites to determine if further investigation is warranted. While applicable to various programs, users should carefully consider the underlying assumptions to appropriately apply the screening levels (SLs).

The RSLs represent chemical-specific concentrations in air, drinking water, and soil that, if exceeded, may signal the need for additional analysis. The calculator can generate both default and site-specific concentrations for contaminants in soil, air, water, and sediment. SLs are particularly valuable during early project phases, such as Remedial Investigation (RI) scoping and chemical screening. However, these levels are not cleanup standards and should not be misconstrued as final remediation goals.

This tool integrates risk-based screening level equations, considering both carcinogenic and systemic toxicities of chemicals. Default tables address exposure scenarios for residential soil, outdoor worker soil, indoor air (residential and worker), and tap water. The SLs are derived using default exposure parameters and incorporate Reasonable Maximum Exposure (RME) conditions, ensuring standardized and reliable results for early-stage site assessment and planning.
DOI: 10.15468/dl.a7yz6r
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pseudoeurycea anitae Bogert, 1967"
 ]
}

 The dataset includes 60 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015878-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.20067329
title: IJMS Di Miceli Laye et al 2022

description: Data from Di Miceli <em>et al</em>., Int J Mol Sci, <strong>2022</strong>.
DOI: 10.6084/m9.figshare.20067329.v1
title: IJMS Di Miceli Laye et al 2022

description: Data from Di Miceli <em>et al</em>., Int J Mol Sci, <strong>2022</strong>.
DOI: 10.15468/dl.r6jrdn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aiouea elegans (van der Werff) Rohwer)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015879-250127130748423/datasets/export for details.
DOI: 10.15468/dl.q3yyuz
title: Occurrence Download

description: A dataset containing 191 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ceratoporella Hickson, 1912"
 ]
}

 The dataset includes 191 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015880-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28351992
title: Qualitative and quantitative detection of isothiocyanates; quantification of erucin and phenethyl isothiocyanate in Kohlrabi by a reverse phase HPLC–DAD method

description: Several breakdown products, including isothiocyanates (ITCs) are formed by hydrolysis of naturally occurring secondary metabolites in Brassica plants. These compounds are known to exert positive effects on health. The present study aimed to detect the presence of these volatile compounds in the raw and fermented Kohlrabi and optimise and validate a HPLC–DAD method for quantification of erucin and phenethyl isothiocyanate in Kohlrabi. Correlation coefficients of 0.979 and 0.978 were attained over the range 1–20 μg/ml and 0.5–10 mg/ml for erucin and phenethyl isothiocyanate, respectively, The LOD and LOQ values for erucin and phenethyl isothiocyanate were 3.36, 10.18 μg/ml and 1.73, 5.26 mg/ml, respectively. The accuracy for the analysis was confirmed by the recovery values of 97–98%. The validated method was used to analyse these two compounds in raw and fermented Kohlrabi. Furthermore, the total glucosinolate and total isothiocyanate content of raw and fermented extracts of Kohlrabi were also evaluated.
DOI: 10.6084/m9.figshare.28351992.v1
title: Qualitative and quantitative detection of isothiocyanates; quantification of erucin and phenethyl isothiocyanate in Kohlrabi by a reverse phase HPLC–DAD method

description: Several breakdown products, including isothiocyanates (ITCs) are formed by hydrolysis of naturally occurring secondary metabolites in Brassica plants. These compounds are known to exert positive effects on health. The present study aimed to detect the presence of these volatile compounds in the raw and fermented Kohlrabi and optimise and validate a HPLC–DAD method for quantification of erucin and phenethyl isothiocyanate in Kohlrabi. Correlation coefficients of 0.979 and 0.978 were attained over the range 1–20 μg/ml and 0.5–10 mg/ml for erucin and phenethyl isothiocyanate, respectively, The LOD and LOQ values for erucin and phenethyl isothiocyanate were 3.36, 10.18 μg/ml and 1.73, 5.26 mg/ml, respectively. The accuracy for the analysis was confirmed by the recovery values of 97–98%. The validated method was used to analyse these two compounds in raw and fermented Kohlrabi. Furthermore, the total glucosinolate and total isothiocyanate content of raw and fermented extracts of Kohlrabi were also evaluated.
DOI: 10.2908/nama_10_nfa_fl
title: Cross-classification of gross fixed capital formation by industry and by asset (flows)
title: Tableau croisé de la formation brute de capital fixe (FBCF) par branche d'activité et par actif (opérations)
title: Investorenkreuztabelle der Bruttoanlageinvestitionen (BAI) nach Wirtschaftsbereichen und Art der Aktiva (Transaktionen)
DOI: 10.6084/m9.figshare.27993996
title: Deconvolution Density Estimation with Penalized MLE

description: Deconvolution is the important problem of estimating the distribution of a quantity of interest from a sample with additive measurement error. Nearly all infinite-dimensional deconvolution methods in the literature use Fourier transformations. These methods are mathematically neat, but unstable, and produce bad estimates when signal-noise ratio or sample size are low. A popular alternative is to maximize penalized likelihood for a finite-dimensional basis expansion of the unknown density. We develop a new method to optimize penalized likelihood over the infinite-dimensional space of all functions. This gives the stability of regularized likelihood methods without restricting the space of solutions. Our method compares favorably with state-of-the-art methods on simulated and real data, particularly for small sample size or low signal-noise ratio. We also provide the first results on the consistency and rate of convergence of penalized maximum likelihood estimates for density deconvolution. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27993996.v1
title: Deconvolution density estimation with penalized MLE

description: Deconvolution is the important problem of estimating the distribution of a quantity of interest from a sample with additive measurement error. Nearly all infinite-dimensional deconvolution methods in the literature use Fourier transformations. These methods are mathematically neat, but unstable, and produce bad estimates when signal-noise ratio or sample size are low. A popular alternative is to maximize penalized likelihood for a finite-dimensional basis expansion of the unknown density. We develop a new method to optimize penalized likelihood over the infinite-dimensional space of all functions. This gives the stability of regularized likelihood methods without restricting the space of solutions. Our method compares favorably with state-of-the-art methods on simulated and real data, particularly for small sample size or low signal-noise ratio. We also provide the first results on the consistency and rate of convergence of penalized maximum likelihood estimates for density deconvolution.