cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k7pcdgr73t
title: Limited activation interdependence, and differing patterns of the in vivo effects, of IKK1 and IKK2 downstream of NIK

description: Research data for manuscript entitled 'Limited activation interdependence, and differing patterns of the in vivo effects, of IKK1 and IKK2 downstream of NIK'.
DOI: 10.17632/k7pcdgr73t.1
title: Limited activation interdependence, and differing patterns of the in vivo effects, of IKK1 and IKK2 downstream of NIK

description: Research data for manuscript entitled 'Limited activation interdependence, and differing patterns of the in vivo effects, of IKK1 and IKK2 downstream of NIK'.
DOI: 10.17632/szhcxgx2j3
title: Extracurricular Activities and Equity in Kyrgyzstan

description: Extracurricular Activities and Equity in Kyrgyzstan: A Comparative Case Study of Soviet and Post-Independence Eras
DOI: 10.17632/szhcxgx2j3.1
title: Extracurricular Activities and Equity in Kyrgyzstan

description: Extracurricular Activities and Equity in Kyrgyzstan: A Comparative Case Study of Soviet and Post-Independence Eras
DOI: 10.17632/jv7sw27gwc
title: Cloud Scheduling Datasets

description: 1. Augmented Cloud Scheduling Dataset:
This dataset was generated by introducing small random perturbations (jitter) to the original base dataset of 100 rows. Each record contains four attributes: Index, input_size, output_size, and priority. Perturbations were clipped within valid bounds (input_size ∈ [1,99]; output_size ∈ [3,100]; priority ∈ [1,5]) to maintain realism.

2. Synthetic Uniform Cloud Scheduling Dataset:
A fully synthetic dataset generated by sampling uniformly across valid ranges: input_size ∈ [1,99]; output_size ∈ [3,100]; priority ∈ [1,5]. The number of samples can be scaled (e.g., 500 rows).

3.Bootstrap-Expanded Cloud Scheduling Dataset:
This dataset was created by resampling with replacement from the base dataset to add 500 new rows. Unique Index values were assigned, and the new samples were concatenated with the original dataset.

4.Stratified-Augmented Cloud Scheduling Dataset:
A stratified augmentation technique was applied to preserve the priority distribution observed in the original dataset. Within each priority group, small controlled perturbations were added to input_size and output_size, clipped within valid ranges.
DOI: 10.17632/jv7sw27gwc.1
title: Cloud Scheduling Datasets

description: 1. Augmented Cloud Scheduling Dataset:
This dataset was generated by introducing small random perturbations (jitter) to the original base dataset of 100 rows. Each record contains four attributes: Index, input_size, output_size, and priority. Perturbations were clipped within valid bounds (input_size ∈ [1,99]; output_size ∈ [3,100]; priority ∈ [1,5]) to maintain realism.

2. Synthetic Uniform Cloud Scheduling Dataset:
A fully synthetic dataset generated by sampling uniformly across valid ranges: input_size ∈ [1,99]; output_size ∈ [3,100]; priority ∈ [1,5]. The number of samples can be scaled (e.g., 500 rows).

3.Bootstrap-Expanded Cloud Scheduling Dataset:
This dataset was created by resampling with replacement from the base dataset to add 500 new rows. Unique Index values were assigned, and the new samples were concatenated with the original dataset.

4.Stratified-Augmented Cloud Scheduling Dataset:
A stratified augmentation technique was applied to preserve the priority distribution observed in the original dataset. Within each priority group, small controlled perturbations were added to input_size and output_size, clipped within valid ranges.
DOI: 10.17632/22dz8zm4x8
title: Individualized virtual angle offset training - reaching times by target

description: The dataset includes reaching duration by target collected for healthy individuals and for patients with stroke for reaching conducted towards targets in a virtual environment. The virtual environment included an arm avatar, and circular targets. The elbow angle was presented with a hypometric offset (offset) or without an offset (actual). 
 
Twenty-one healthy participants were divided into two groups (offset, actual). Participants underwent a 30-minute training session, in which the offset group was presented with an elbow angle which was 10 deg smaller than the physical angle, and the actual group was presented with the actual elbow angle. For each participant targets were selected within the individualized reaching zone (the zone the participant could reach). The maximal time duration to reach each target was set to 2s. After training both groups were tested with the actual elbow angle. The data of the test session was recorded and is presented in table TimeHealthy (id-participant id, offset-1 offset group, max- maximal time duration set to 2s for all healthy participants, target-target ID, time-reaching duration). When a participant did not reach a target within the set duration, the next target appeared, and the time was not recorded.

Twelve hospitalized individuals with sub-acute stroke were divided into two groups (offset, actual), they underwent three 30-minute training sessions over one week. In each session the participant was presented with several rounds of 30 targets, the offset group was presented with an elbow angle which was 10 deg smaller than the physical angle, and the actual group was presented with the actual elbow angle. For each participant targets were selected within an individualized reaching zone (the zone the participant could reach). The maximal time duration to reach a target was set to 2s, 4s, or 6s based on patient capabilities. The data of the all session was recorded and is presented in table TimeStroke ( id-participant id, offset-1 offset group, max- maximal time duration set to 2s for all healthy participants, session – A (first),B (second), or C (third), round – target round with the session, target-target ID, time-reaching duration). When a participant did not reach a target within the set duration, the next target appeared, and the time was not recorded.
DOI: 10.17632/22dz8zm4x8.1
title: Individualized virtual angle offset training - reaching times by target

description: The dataset includes reaching duration by target collected for healthy individuals and for patients with stroke for reaching conducted towards targets in a virtual environment. The virtual environment included an arm avatar, and circular targets. The elbow angle was presented with a hypometric offset (offset) or without an offset (actual). 
 
Twenty-one healthy participants were divided into two groups (offset, actual). Participants underwent a 30-minute training session, in which the offset group was presented with an elbow angle which was 10 deg smaller than the physical angle, and the actual group was presented with the actual elbow angle. For each participant targets were selected within the individualized reaching zone (the zone the participant could reach). The maximal time duration to reach each target was set to 2s. After training both groups were tested with the actual elbow angle. The data of the test session was recorded and is presented in table TimeHealthy (id-participant id, offset-1 offset group, max- maximal time duration set to 2s for all healthy participants, target-target ID, time-reaching duration). When a participant did not reach a target within the set duration, the next target appeared, and the time was not recorded.

Twelve hospitalized individuals with sub-acute stroke were divided into two groups (offset, actual), they underwent three 30-minute training sessions over one week. In each session the participant was presented with several rounds of 30 targets, the offset group was presented with an elbow angle which was 10 deg smaller than the physical angle, and the actual group was presented with the actual elbow angle. For each participant targets were selected within an individualized reaching zone (the zone the participant could reach). The maximal time duration to reach a target was set to 2s, 4s, or 6s based on patient capabilities. The data of the all session was recorded and is presented in table TimeStroke ( id-participant id, offset-1 offset group, max- maximal time duration set to 2s for all healthy participants, session – A (first),B (second), or C (third), round – target round with the session, target-target ID, time-reaching duration). When a participant did not reach a target within the set duration, the next target appeared, and the time was not recorded.
DOI: 10.17632/4cngm8bv5h
title: São Paulo macro-metropolis land cover trajectories from 2005 to 2020.

description: Ferreira et al. 2025 - LC-trajectories 2005-2020.gpkg
Data referring to figures 3, S4 and S5 of the paper "Urban boundaries are an underexplored frontier for ecological restoration" (https://doi.org/10.1038/s41598-025-19699-9)
Land cover (LC) data from the eighth collection of MapBiomas were analyzed from 2005 to 2020 and grouped according to seven different trajectories: 
1) Anthropic from 2005-2020 (A): Pixel classified as anthropic in all scenes (Grouped as No change between 2005-2020)
2) Old growth forest- from 2005 to 2020 (1V): Pixel classified as old growth vegetation in all scenes (Grouped as No change between 2005-2020)
3) Secondary vegetation-from 2005 to 2020 (2V): Pixel classified as secondary vegetation in all scenes (Grouped as No change between 2005-2020)
4) Deforestation without regeneration (D): Pixel classified as deforestation in any year without any occurrence of regeneration (Grouped as Deforestation without regeneration)
5) Deforestation after regeneration (R-D): Pixel classified as anthropic in 2020 with occurrence of regeneration and deforestation between 2005 and 2020 (Grouped as Deforestation without regeneration)
6) Regeneration (R): Pixel classified as regeneration in any year between 2005-2020, without any occurrence of deforestation, and classified as natural land cover in 2020 (Grouped as Regeneration)
7) Regeneration after deforestation (D-R): Pixel classified as natural land cover in 2020 with occurrence of regeneration and deforestation between 2005 and 2020 (Grouped as Regeneration)
8) No confidence (NoC): Transitions that need more information to be confirmed (Grouped as No confidence)

Ferreira et al. 2025 - LC-trajectories 2005-2020_Style.qml
Color scheme for the LC-trajectories map
DOI: 10.17632/4cngm8bv5h.1
title: São Paulo macro-metropolis land cover trajectories from 2005 to 2020.

description: Ferreira et al. 2025 - LC-trajectories 2005-2020.gpkg
Data referring to figures 3, S4 and S5 of the paper "Urban boundaries are an underexplored frontier for ecological restoration" (https://doi.org/10.1038/s41598-025-19699-9)
Land cover (LC) data from the eighth collection of MapBiomas were analyzed from 2005 to 2020 and grouped according to seven different trajectories: 
1) Anthropic from 2005-2020 (A): Pixel classified as anthropic in all scenes (Grouped as No change between 2005-2020)
2) Old growth forest- from 2005 to 2020 (1V): Pixel classified as old growth vegetation in all scenes (Grouped as No change between 2005-2020)
3) Secondary vegetation-from 2005 to 2020 (2V): Pixel classified as secondary vegetation in all scenes (Grouped as No change between 2005-2020)
4) Deforestation without regeneration (D): Pixel classified as deforestation in any year without any occurrence of regeneration (Grouped as Deforestation without regeneration)
5) Deforestation after regeneration (R-D): Pixel classified as anthropic in 2020 with occurrence of regeneration and deforestation between 2005 and 2020 (Grouped as Deforestation without regeneration)
6) Regeneration (R): Pixel classified as regeneration in any year between 2005-2020, without any occurrence of deforestation, and classified as natural land cover in 2020 (Grouped as Regeneration)
7) Regeneration after deforestation (D-R): Pixel classified as natural land cover in 2020 with occurrence of regeneration and deforestation between 2005 and 2020 (Grouped as Regeneration)
8) No confidence (NoC): Transitions that need more information to be confirmed (Grouped as No confidence)

Ferreira et al. 2025 - LC-trajectories 2005-2020_Style.qml
Color scheme for the LC-trajectories map
DOI: 10.17632/jz9bxwwzdk
title: São Paulo macro-metropolis dense urban areas, urban boundaries and rural areas

description: Ferreira et al. 2025 - Limits.gpkg
São Paulo macro-metropolis dense urban areas, urban boundaries, rural areas, water bodies and hamlets/rural clusters based on the Brazilian Institute of Geography and Statistics (IBGE) definitions and limits from 2021.
DOI: 10.17632/jz9bxwwzdk.1
title: São Paulo macro-metropolis dense urban areas, urban boundaries and rural areas

description: Ferreira et al. 2025 - Limits.gpkg
São Paulo macro-metropolis dense urban areas, urban boundaries, rural areas, water bodies and hamlets/rural clusters based on the Brazilian Institute of Geography and Statistics (IBGE) definitions and limits from 2021.
DOI: 10.17632/6gk8czckvb
title: Mapping the Future: A Bibliometric Analysis of Engagement Trends in Artificial Intelligence within Higher Education - June 13, 2024

description: Scopus Bibliometric Dataset - June 13, 2024
DOI: 10.17632/6gk8czckvb.1
title: Mapping the Future: A Bibliometric Analysis of Engagement Trends in Artificial Intelligence within Higher Education - June 13, 2024

description: Scopus Bibliometric Dataset - June 13, 2024
DOI: 10.17632/bxw23pcwfh.3
title: The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida

description: Replication Materials for "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida"
This repository provides the R scripts and supporting materials to replicate the methodology presented in the paper "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida." The study employs difference-in-differences methods and staggered event models to explore the impact of Dollar General store openings on neighboring small firms in Florida.

Data and Replication
The analysis is based on the National Establishment Time-Series (NETS) Database, a proprietary product licensed from Walls & Associates. Under our data use agreement, we are prohibited from redistributing the raw dataset.

To ensure methodological transparency and demonstrate the functionality of our code, we have created and included a simulated dataset. While this simulated data will not reproduce the exact numerical findings of the paper, it is designed to mimic the structure of the original data. Its purpose is to allow users to run the provided R scripts for data processing and analysis from start to finish, confirming that the code works as intended.

Researchers who wish to fully replicate the paper's results must license the NETS database directly from the provider and apply our provided scripts.
DOI: 10.7266/gkddm622
title: Survey data for PUBLIC PERCEPTIONS OF RED TIDE: EXPLORING THE INFLUENCE OF SOCIAL MEDIA ENGAGEMENT AND DEMOGRAPHICS ON ENVIRONMENTAL POLICY SUPPORT
DOI: 10.17632/9d5bx9d5c9
title: Supplemental Table 1:

description: Demographic information, clinical characteristics, microbiologic findings, treatment regimens, and follow-up outcomes of five Hispanic female patients presenting with idiopathic granulomatous mastitis (IGM).
DOI: 10.17632/9d5bx9d5c9.1
title: Supplemental Table 1:

description: Demographic information, clinical characteristics, microbiologic findings, treatment regimens, and follow-up outcomes of five Hispanic female patients presenting with idiopathic granulomatous mastitis (IGM).
DOI: 10.17632/zk4cjx8cpk
title: The role of hydrogen sulfide and trisulfur radical ion in molybdenum transport by hydrothermal fluids: implications for porphyry-epithermal Cu-Au-Mo deposits

description: Knowledge of the chemical speciation of molybdenum in fluids under hydrothermal conditions is key to understanding the formation of porphyry Cu-Au-Mo deposits, which are the primary economic source of copper, molybdenum and rhenium. However, the chemical identity and thermodynamic stability of aqueous complexes of molybdenum and the role of different ligands on metal transport yet remain inconsistent and incomplete, in particular for sulfur-bearing fluids typical of such environments. We have experimentally studied the role of hydrogen sulfide (H2S and HS‒) and the trisulfur radical ion (S3•‒) in the transport of molybdenum by hydrothermal fluids at 300 °C and 500 bar as a function of pH, redox conditions as well as sulfur speciation and concentration. We combined solubility measurements of molybdenite in hydrothermal reactors using fluid quenching or sampling, with in situ synchrotron X-ray absorption spectroscopy experiments and thermodynamic and molecular modeling. Our solubility and spectroscopic dataset is consistent with the formation of the tetrathiomolybdate complex, MoS42‒, in reduced, H2S/HS‒-dominated fluids of neutral-to-alkaline pH. In contrast, a mixed-ligand complex with three sulfide ions and one trisulfur radical ion, MoS3(S3)‒, prevails in more oxidized and more acidic fluids at the sulfide-sulfate transition where S3•‒ is far more abundant. In both complexes, Mo is nominally hexavalent and in a first-shell tetrahedral coordination with sulfur atoms. The derived equilibrium constants of the formal solubility reactions (log10K):
MoS2(s) + 2 H2S0(aq) + 0.5 O2(g) = MoS42‒ + 2 H+ + H2O(liq) and
MoS2(s) + H2S0(aq) + S3•‒ + 0.5 O2(g) = MoS3(S3)‒ + H2O(liq) , 
at 300 °C and 500 bar are 0.5±0.4 and 14.6±0.4, respectively. The solubility of MoS2(s) predicted using these constants aligns well with Mo concentrations measured in natural fluid inclusions in quartz that record S-rich fluids from porphyry-epithermal systems. In contrast, other types of Mo complexes invoked so far (molybdates, alkali ion pairs, oxy-chlorides or oxysulfides) are negligible at such conditions. Thus, trisulfur radical ion complexes may be important carriers of Mo in hydrothermal fluids and would require further systematic investigation across a wide range of temperature and pressure.

Digital database contains: 
1) Appendix_A including supplementary text, supplementary figures, supplementary tables, data for figure 1 of the main text (Tables S6-S9) and description of digital database;
2) digital data for figures 2-7 of the main text; 
3) digital data for figures presented in Appendix_A
4) original figures from the manuscript in high resolution
DOI: 10.17632/zk4cjx8cpk.7
title: The role of hydrogen sulfide and trisulfur radical ion in molybdenum transport by hydrothermal fluids: implications for porphyry-epithermal Cu-Au-Mo deposits

description: Knowledge of the chemical speciation of molybdenum in fluids under hydrothermal conditions is key to understanding the formation of porphyry Cu-Au-Mo deposits, which are the primary economic source of copper, molybdenum and rhenium. However, the chemical identity and thermodynamic stability of aqueous complexes of molybdenum and the role of different ligands on metal transport yet remain inconsistent and incomplete, in particular for sulfur-bearing fluids typical of such environments. We have experimentally studied the role of hydrogen sulfide (H2S and HS‒) and the trisulfur radical ion (S3•‒) in the transport of molybdenum by hydrothermal fluids at 300 °C and 500 bar as a function of pH, redox conditions as well as sulfur speciation and concentration. We combined solubility measurements of molybdenite in hydrothermal reactors using fluid quenching or sampling, with in situ synchrotron X-ray absorption spectroscopy experiments and thermodynamic and molecular modeling. Our solubility and spectroscopic dataset is consistent with the formation of the tetrathiomolybdate complex, MoS42‒, in reduced, H2S/HS‒-dominated fluids of neutral-to-alkaline pH. In contrast, a mixed-ligand complex with three sulfide ions and one trisulfur radical ion, MoS3(S3)‒, prevails in more oxidized and more acidic fluids at the sulfide-sulfate transition where S3•‒ is far more abundant. In both complexes, Mo is nominally hexavalent and in a first-shell tetrahedral coordination with sulfur atoms. The derived equilibrium constants of the formal solubility reactions (log10K):
MoS2(s) + 2 H2S0(aq) + 0.5 O2(g) = MoS42‒ + 2 H+ + H2O(liq) and
MoS2(s) + H2S0(aq) + S3•‒ + 0.5 O2(g) = MoS3(S3)‒ + H2O(liq) , 
at 300 °C and 500 bar are 0.5±0.4 and 14.6±0.4, respectively. The solubility of MoS2(s) predicted using these constants aligns well with Mo concentrations measured in natural fluid inclusions in quartz that record S-rich fluids from porphyry-epithermal systems. In contrast, other types of Mo complexes invoked so far (molybdates, alkali ion pairs, oxy-chlorides or oxysulfides) are negligible at such conditions. Thus, trisulfur radical ion complexes may be important carriers of Mo in hydrothermal fluids and would require further systematic investigation across a wide range of temperature and pressure.

Digital database contains: 
1) Appendix_A including supplementary text, supplementary figures, supplementary tables, data for figure 1 of the main text (Tables S6-S9) and description of digital database;
2) digital data for figures 2-7 of the main text; 
3) digital data for figures presented in Appendix_A
4) original figures from the manuscript in high resolution
DOI: 10.17632/k9vbj3wwyh.1
title: Database on the Impact of Next Generation EU Funds

description: The Next Generation EU (NGEU) program, through the Recovery and Resilience Facility, was designed to foster a coordinated fiscal response in the EU to the COVID-19 crisis. It provides grants and loans to Member States to finance reforms and investments. In Spain, one of the main beneficiaries, we assess its regional economic impact using counterfactual techniques. The results show an increase in GDP per capita in 2022, projected also for 2023–2025 compared to a no-funds scenario, confirming the relevance of these exceptional measures.
As part of Elsevier’s transition to full open access, specifically for the journal Papers in Regional Science, starting in 2025, we are making publicly available the original database used in the paper entitled “On the impact of Next Generation EU funds: A regional synthetic control method approach.”
This file called Database on the Impact of Next Generation EU Funds.csv, provides the main variables used to analyze the impact of the Next Generation funds through the construction of a synthetic indicator that compares the hypothetical situation of Spanish regions without funds with the real situation with funds, over the period 2017–2025.
DOI: 10.17632/72j776c9jc
title: Inhaled S-nitrosoglutathione in asthma: AirwayAKR1A1 expression and determinants of the human bronchodilator response.

description: Asthma is characterized by airway inflammation and bronchoconstriction. Recent therapies have addressed inflammation, but few innovations have targeted bronchoconstriction. S-Nitrosoglutathione (GSNO), an endogenous bronchial smooth muscle relaxant, is deficient in asthmatic populations and impacts β2-adrenergic responsivity. However, inhaled GSNO (iGSNO) has not been studied in human asthma. Here we found that iGSNO increased forced expiratory volume at one second (FEV1) in asthmatic subjects and the magnitude of increase was linearly related, and additive, to inhaled β2-agonists. Spatial transcriptomic analysis of endobronchial biopsies revealed that AKR1A1, encoding a GSNO degrading enzyme, was upregulated in airway epithelium, and higher AKR1A1 expression was associated with reduced iGSNO bronchodilation. Conversely, sustained elevation in FeNO (fraction of exhaled NO) after iGSNO, indicative of reduced GSNO catabolism, served as a biomarker for iGSNO effectiveness. Thus, iGSNO could represent a novel, personalized asthma therapy, potentially combined with AKR1A1 inhibition.