cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13905309
title: Atmospheric visibility measurements at Hartheim Forest Research Site (DE-Har) from 2021-01-01 to 2021-12-31 [L2]

description: Quality controlled and gap-filled continuous atmospheric visibility data (Meteorological Observable Range MOR) measured above the forest canopy on a tower at Hartheim Forest Research Site (ICOS Associate Ecosyste Site DE-Har, UFR Code: HARTHM, 7.59814ºE, 47.93391ºN, 201 m) using an a forward scatter system (CS125, Present Weather and Visibility sensor, Campbell Scientific Inc.) operated 20 m above ground level.



Quality controlled atmospheric visibility data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2021.

Average, minimum and maximum visibility are provided on hourly, daily, monthly and annual scales.

Hours and days with at least one minute of a visibility of less than 20, 10, 4, 2, 1, 0.5 and 0.2 km based on the WMO classes are provided on daily, monthly and annual scales. Can be used to determine frequency of fog conditions.

Hours and days with at least one minute of a visibility of greater than 50 km are provided on daily, monthly and annual scales.

Maximum visibility output by the CS125 is 75 km, so a value of 75 km means greater or equal 75 km. Averaged visibility accounts for values greater than 75 km with 75 km.

Detailed information on gap-filled data is provided.

Note: All times are provided in UTC, not local time.


For more details read `HARTHM_2021_Visibility_MetaData.txt`.
description: COPYRIGHT



Creative Commons Attribution 4.0 International. Copyright Albert-Ludwigs-Universität Freiburg, Professur für Umweltmeteorologie, Werthmannstrasse 10, Freiburg, Germany.


CREATOR

This work was created by the University of Freiburg, Germany.

ATTRIBUTION

The site is operated as part of the Integrated Carbon Observation System (ICOS).

Instruments and sensors in the dataset were operated by the Chair of Environmental Meteorology, University of Freiburg, Germany.

DISCLAIMER

The use of the work is at the user's own risk. The authors and/or the involved institutions, accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The author and/or the involved institutions are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected.

MATERIAL NOTICE

The notices cover data in databases, text and images contained in the work.

MATERIAL URI

Hartheim Forest Research Site

DE-Har in the ICOS Carbon Portal
DOI: 10.15468/dl.yjuxmk
title: Occurrence Download

description: A dataset containing 78385 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Haliotis rufescens"
 ]
}

 The dataset includes 78385 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010233-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18473852
title: PERSONAL HEALTH PSYCHOLOGY AS A BIOPSYCHOSOCIAL FRAMEWORK FOR STRESS PREVENTION AND HEALTH-PROMOTING DECISION-MAKING: A NARRATIVE REVIEW

description: Background: Personal health psychology examines how individuals’ beliefs, emotions, coping patterns, and social context shape health behavior, stress responses, and illness experience.        Objective: To synthesize core constructs of personal health psychology and articulate an integrated framework for stress prevention and health-promoting decision-making grounded in biopsychosocial principles, stress theory, and self-regulation strategies.        Methods: A narrative review and concept-driven synthesis were conducted. Foundational and representative literature was mapped into four domains: (1) biopsychosocial determinants, (2) psychological resources and cognitive determinants, (3) stress theories and mechanisms, and (4) scalable self-regulation strategies. Reporting follows the logic of SANRA items (aims, search description, referencing, reasoning, and relevant endpoints).[1]

Results: The synthesis supports an integrated pathway: biopsychosocial determinants shape vulnerability and resources; stress emerges through coupled physiological activation and cognitive appraisal; chronic stress contributes to mental and physical symptom burden through neuroendocrine, immune, and behavioral pathways; and prevention is operationalized through low-threshold regulation strategies (slow-paced breathing, mindfulness, cognitive reappraisal, time structuring, and reflective writing).

Conclusion: Personal health psychology provides a coherent prevention framework linking appraisal, coping resources, and self-regulation skills to decision quality and health-supportive behavior. Future work should evaluate integrated training modules using validated outcomes and longitudinal follow-up.
DOI: 10.5281/zenodo.18473853
title: PERSONAL HEALTH PSYCHOLOGY AS A BIOPSYCHOSOCIAL FRAMEWORK FOR STRESS PREVENTION AND HEALTH-PROMOTING DECISION-MAKING: A NARRATIVE REVIEW

description: Background: Personal health psychology examines how individuals’ beliefs, emotions, coping patterns, and social context shape health behavior, stress responses, and illness experience.        Objective: To synthesize core constructs of personal health psychology and articulate an integrated framework for stress prevention and health-promoting decision-making grounded in biopsychosocial principles, stress theory, and self-regulation strategies.        Methods: A narrative review and concept-driven synthesis were conducted. Foundational and representative literature was mapped into four domains: (1) biopsychosocial determinants, (2) psychological resources and cognitive determinants, (3) stress theories and mechanisms, and (4) scalable self-regulation strategies. Reporting follows the logic of SANRA items (aims, search description, referencing, reasoning, and relevant endpoints).[1]

Results: The synthesis supports an integrated pathway: biopsychosocial determinants shape vulnerability and resources; stress emerges through coupled physiological activation and cognitive appraisal; chronic stress contributes to mental and physical symptom burden through neuroendocrine, immune, and behavioral pathways; and prevention is operationalized through low-threshold regulation strategies (slow-paced breathing, mindfulness, cognitive reappraisal, time structuring, and reflective writing).

Conclusion: Personal health psychology provides a coherent prevention framework linking appraisal, coping resources, and self-regulation skills to decision quality and health-supportive behavior. Future work should evaluate integrated training modules using validated outcomes and longitudinal follow-up.
DOI: 10.15468/dl.aj7mum
title: Occurrence Download

description: A dataset containing 3057 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Grapsus grapsus"
 ]
}

 The dataset includes 3057 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010291-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dx7mfv
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ancylandrena koebelei"
 ]
}

 The dataset includes 74 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010290-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dk8x92
title: Occurrence Download

description: A dataset containing 80 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Brachinus variegatus, Brachinus vagus, Brachinus tetraspilotus, Brachinus tetragrammus, Brachinus tetracolon, Brachinus tenuis, Brachinus suturalis, Brachinus sulcipennis, Brachinus suberbianus, Brachinus stappersi, Brachinus simulans, Brachinus sexnotatus, Brachinus sexmaculatus, Brachinus servillei, Brachinus sericeus, Brachinus reyi, Brachinus promontorii, Brachinus obliterus, Brachinus natalicus, Brachinus midoli, Brachinus lewisii, Brachinus latus, Brachinus langenhani, Brachinus laevicostis, Brachinus hexagrammus, Brachinus gentilis, Brachinus fasciatocollis, Brachinus eucosmus, Brachinus elegantulus, Brachinus diffusus, Brachinus connectus, Brachinus connectoides, Brachinus congicus, Brachinus canaliculatus, Brachinus barclayi, Brachinus armiger, Brachinus algoensis, Brachinus abyssinicus, Brachinus abbreviatus)"
 ]
}

 The dataset includes 80 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010289-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dbv7bp
title: Occurrence Download

description: A dataset containing 90480 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Bryum argenteum"
 ]
}

 The dataset includes 90480 records from 758 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010208-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13905126
title: Atmospheric visibility measurements at Hartheim Forest Research Site (DE-Har) from 2023-01-01 to 2023-12-31 [L2]

description: Quality controlled and gap-filled continuous atmospheric visibility data (Meteorological Observable Range MOR) measured above the forest canopy on a tower at Hartheim Forest Research Site (ICOS Associate Ecosystem Site DE-Har, UFR Code: HARTHM, 7.59814ºE, 47.93391ºN, 201 m) using an a forward scatter system (CS125, Present Weather and Visibility sensor, Campbell Scientific Inc.) operated 20 m above ground level.



Quality controlled atmospheric visibility data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2023.

Average, minimum and maximum visibility are provided on hourly, daily, monthly and annual scales.

Hours and days with at least one minute of a visibility of less than 20, 10, 4, 2, 1, 0.5 and 0.2 km based on the WMO classes are provided on daily, monthly and annual scales. Can be used to determine frequency of fog conditions.

Hours and days with at least one minute of a visibility of greater than 50 km are provided on daily, monthly and annual scales.

Maximum visibility output by the CS125 is 75 km, so a value of 75 km means greater or equal 75 km. Averaged visibility accounts for values greater than 75 km with 75 km.

Detailed information on gap-filled data is provided.

Note: All times are provided in UTC, not local time.


For more details read `HARTHM_2023_Visibility_MetaData.txt`.
description: COPYRIGHT



Creative Commons Attribution 4.0 International. Copyright Albert-Ludwigs-Universität Freiburg, Professur für Umweltmeteorologie, Werthmannstrasse 10, Freiburg, Germany.


CREATOR

This work was created by the University of Freiburg, Germany.

ATTRIBUTION

The site is operated as part of the Integrated Carbon Observation System (ICOS).

Instruments and sensors in the dataset were operated by the Chair of Environmental Meteorology, University of Freiburg, Germany.

DISCLAIMER

The use of the work is at the user's own risk. The authors and/or the involved institutions, accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The author and/or the involved institutions are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected.

MATERIAL NOTICE

The notices cover data in databases, text and images contained in the work.

MATERIAL URI

Hartheim Forest Research Site

DE-Har in the ICOS Carbon Portal
DOI: 10.60507/fk2/6kz1wd/9dxdjt
title: Lekythos_997_model.zip
DOI: 10.60507/fk2/6kz1wd/onl6vg
title: Lekythos_997_images.zip
DOI: 10.60507/fk2/6kz1wd/aq0rya
title: LANG_Lekythos_997_readme.txt
DOI: 10.60507/fk2/6kz1wd/pmubrb
title: LANG_Lekythos_997_readme.txt
DOI: 10.60507/fk2/6kz1wd/z53q0v
title: Lekythos_997_model.zip
DOI: 10.60507/fk2/6kz1wd/8bfpyc
title: LANG_Lekythos_997_readme.txt
DOI: 10.60507/fk2/6kz1wd/bm5xar
title: Lekythos_997_model.zip
DOI: 10.60507/fk2/6kz1wd/v8t8ej
title: Lekythos_997_model.zip
DOI: 10.60507/fk2/6kz1wd
title: Attic Protogeometric Lekythos in the Academic Art Museum Bonn (Inv. 997)

description: Attic Protogeometric Lekythos in the Academic Art Museum Bonn (University of Bonn, Inv. 997) showing geometric patterns. Date: -950 to -900 BC
description: Agisoft Metashape, 2.2.0
description: Blender, 4.0
description: Substance Painter, 11.1.0
description: Substance Designer, 15.0.3
DOI: 10.5281/zenodo.18473977
title: STRATEGIC DIRECTIONS FOR ORGANIZATIONAL–INSTITUTIONAL AND FINANCIAL–ECONOMIC TRANSFORMATION OF THE NATIONAL INNOVATION SYSTEM: EVIDENCE FROM UZBEKISTAN

description: In the context of the modern global economy, the effectiveness of a national innovation system (NIS) has become a decisive factor in ensuring long-term competitiveness and sustainable economic growth. This article examines the priority strategic directions for the organizational–institutional and financial–economic transformation of Uzbekistan’s national innovation system. The study integrates institutional analysis with empirical data covering the period 2015–2023 and applies forecasting tools, including linear trend models and a multifactor regression model, to assess innovation performance for 2024–2027. The results reveal a structural imbalance between the rapid quantitative expansion of innovation infrastructure and the weakening qualitative indicators related to human capital, R&D institutions, and investment intensity. While time-series trend analysis suggests potential stagnation of innovation activity, the multifactor regression model demonstrates that stabilizing key drivers—scientific institutions, human capital quality, and investment share—can generate sustained growth in innovation output. The findings highlight the critical role of coordinated institutional reforms, public–private partnerships, venture financing mechanisms, and human capital development in strengthening the national innovation ecosystem. The paper provides policy-relevant recommendations aimed at enhancing innovation efficiency and ensuring the transition from extensive to intensive innovation-driven growth in Uzbekistan.
DOI: 10.5281/zenodo.18473976
title: STRATEGIC DIRECTIONS FOR ORGANIZATIONAL–INSTITUTIONAL AND FINANCIAL–ECONOMIC TRANSFORMATION OF THE NATIONAL INNOVATION SYSTEM: EVIDENCE FROM UZBEKISTAN

description: In the context of the modern global economy, the effectiveness of a national innovation system (NIS) has become a decisive factor in ensuring long-term competitiveness and sustainable economic growth. This article examines the priority strategic directions for the organizational–institutional and financial–economic transformation of Uzbekistan’s national innovation system. The study integrates institutional analysis with empirical data covering the period 2015–2023 and applies forecasting tools, including linear trend models and a multifactor regression model, to assess innovation performance for 2024–2027. The results reveal a structural imbalance between the rapid quantitative expansion of innovation infrastructure and the weakening qualitative indicators related to human capital, R&D institutions, and investment intensity. While time-series trend analysis suggests potential stagnation of innovation activity, the multifactor regression model demonstrates that stabilizing key drivers—scientific institutions, human capital quality, and investment share—can generate sustained growth in innovation output. The findings highlight the critical role of coordinated institutional reforms, public–private partnerships, venture financing mechanisms, and human capital development in strengthening the national innovation ecosystem. The paper provides policy-relevant recommendations aimed at enhancing innovation efficiency and ensuring the transition from extensive to intensive innovation-driven growth in Uzbekistan.
DOI: 10.15468/dl.tfr8xw
title: Occurrence Download

description: A dataset containing 5201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Perforatus perforatus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5201 records from 115 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010294-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14565191
title: Atmospheric visibility measurements at Hartheim Forest Research Site (DE-Har) from 2024-01-01 to 2024-12-31 [L2]

description: Quality controlled and gap-filled continuous atmospheric visibility data (Meteorological Observable Range MOR) measured above the forest canopy on a tower at Hartheim Forest Research Site (ICOS Associate Ecosystem Site DE-Har, UFR Code: HARTHM, 7.59814ºE, 47.93391ºN, 201 m) using an a forward scatter system (CS125, Present Weather and Visibility sensor, Campbell Scientific Inc.) operated 20 m above ground level.



Quality controlled atmospheric visibility data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2024.

Average, minimum and maximum visibility are provided on hourly, daily, monthly and annual scales.

Hours and days with at least one minute of a visibility of less than 20, 10, 4, 2, 1, 0.5 and 0.2 km based on the WMO classes are provided on daily, monthly and annual scales. Can be used to determine frequency of fog conditions.

Hours and days with at least one minute of a visibility of greater than 50 km are provided on daily, monthly and annual scales.

Maximum visibility output by the CS125 is 75 km, so a value of 75 km means greater or equal 75 km. Averaged visibility accounts for values greater than 75 km with 75 km.

Detailed information on gap-filled data is provided.

Note: All times are provided in UTC, not local time.


For more details read `HARTHM_2024_Visibility_MetaData.txt`.
description: COPYRIGHT



Creative Commons Attribution 4.0 International. Copyright Albert-Ludwigs-Universität Freiburg, Professur für Umweltmeteorologie, Werthmannstrasse 10, Freiburg, Germany.


CREATOR

This work was created by the University of Freiburg, Germany.

ATTRIBUTION

The site is operated as part of the Integrated Carbon Observation System (ICOS).

Instruments and sensors in the dataset were operated by the Chair of Environmental Meteorology, University of Freiburg, Germany.

DISCLAIMER

The use of the work is at the user's own risk. The authors and/or the involved institutions, accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The author and/or the involved institutions are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected.

MATERIAL NOTICE

The notices cover data in databases, text and images contained in the work.

MATERIAL URI

Hartheim Forest Research Site

DE-Har in the ICOS Carbon Portal
DOI: 10.15468/dl.4zq4x6
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xylosalsola paletzkiana",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 24 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010295-260129131611470/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.14450445
title: Bed load flux time series for Benavides <i>et al. </i>(2022). "The impact of intermittency on bed load sediment transport." <i>Geophysical Research Letters</i>, 49, e2021GL096088. https://doi.org/10.1029/2021GL096088

description: This zip file contains three files:1) Loading_Data_Example.py, which is a python script which shows one how to load and handle the data.2) time_series_gb.json and time_series_ng.json, json files which contain the time-series data used in the paper Benavides et al. (https://doi.org/10.1029/2021GL096088, preprint found at: https://doi.org/10.31223/X5PW3Q).3) exp_data_11_2020.txt, the experimental meta data file which contains information on the experimental conditions for each run.
DOI: 10.6084/m9.figshare.14450445.v4
title: Bed load flux time series for Benavides <i>et al. </i>(2022). "The impact of intermittency on bed load sediment transport." <i>Geophysical Research Letters</i>, 49, e2021GL096088. https://doi.org/10.1029/2021GL096088

description: This zip file contains three files:1) Loading_Data_Example.py, which is a python script which shows one how to load and handle the data.2) time_series_gb.json and time_series_ng.json, json files which contain the time-series data used in the paper Benavides et al. (https://doi.org/10.1029/2021GL096088, preprint found at: https://doi.org/10.31223/X5PW3Q).3) exp_data_11_2020.txt, the experimental meta data file which contains information on the experimental conditions for each run.
DOI: 10.6084/m9.figshare.14450445.v3
title: Bed load flux time series for Benavides, Deal, ... Perron. 2021

description: This zip file contains three files:1) Loading_Data_Example.py, which is a python script which shows one how to load and handle the data.2) time_series_gb.json and time_series_ng.json, json files which contain the time-series data used in the paper Benavides et al. (preprint found at: https://doi.org/10.31223/X5PW3Q).3) exp_data_11_2020.txt, the experimental meta data file which contains information on the experimental conditions for each run.