cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22331842
title: drivedata_dwt_db3_6_decomposition.npz

description: The demo decomposed dataset file for the paper: "A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition" (https://doi.org/10.1016/j.ins.2022.12.088) . <br> This dataset is generated by performing DWT on the original dataset. The original extracted dataset can be found in https://figshare.com/articles/dataset/EEG_driver_drowsiness_dataset_unbalanced_/16586957. <br> This demo dataset file is provided for testing the code https://github.com/Eric-LRL/Decomposition-ensemble-CNN. Please let us know if you have any questions or concerns.
DOI: 10.6084/m9.figshare.22331842.v1
title: drivedata_dwt_db3_6_decomposition.npz

description: The demo decomposed dataset file for the paper: "A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition" (https://doi.org/10.1016/j.ins.2022.12.088) . <br> This dataset is generated by performing DWT on the original dataset. The original extracted dataset can be found in https://figshare.com/articles/dataset/EEG_driver_drowsiness_dataset_unbalanced_/16586957. <br> This demo dataset file is provided for testing the code https://github.com/Eric-LRL/Decomposition-ensemble-CNN. Please let us know if you have any questions or concerns.
DOI: 10.5281/zenodo.7762240
title: MUSES Leaf Area Index (LAI) 8-Day Global 250m SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 250m spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2022; Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). This dataset is the MUSES LAI product in 2014. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2013</strong></em> and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.1 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product from Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7760077
title: MUSES Leaf Area Index (LAI) 8-Day Global 250m SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 250m spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2022; Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). This dataset is the MUSES LAI product in 2014. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2013</strong></em> and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.1 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product from Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7766970
title: Development of a prognostic model for early breast cancer integrating neutrophil to lymphocyte ratio and clinical-pathological characteristics

description: <strong>Abstract</strong> Breast cancer-related inflammation is critical in tumorigenesis, cancer progression, and patient prognosis. Several inflammatory markers derived from peripheral blood cells count, such as the neutrophil-lymphocyte ratio (NLR), derived neutrophil-lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) are considered as prognostic markers in several types of malignancy. Here, we investigate and validate a prognostic model in early breast cancer (eBC) patients to predict disease-free survival (DFS) based on readily available baseline clinicopathological prognostic factors and preoperative peripheral blood-derived indexes. We analyzed a training cohort of 710 BC patients and two external validation cohorts of 980 and 157 eBC patients, respectively, with different demographic origins. An elevated preoperative NLR is a better DFS predictor than PLR, MLR, and SII in patients with eBC. The prognostic model generated in this study was able to classify patients into three groups with different risks of relapse based on ECOG-PS, presence of comorbidities, T and N stage, PgR status, and NLR. Prognostic models derived from the combination of clinicopathological features and peripheral blood indices, such as NLR, represent attractive markers mainly because they are easily detectable and applicable in daily clinical practice. More comprehensive prospective studies are needed to unveil their actual effectiveness.
DOI: 10.5281/zenodo.7766969
title: Development of a prognostic model for early breast cancer integrating neutrophil to lymphocyte ratio and clinical-pathological characteristics

description: <strong>Abstract</strong> Breast cancer-related inflammation is critical in tumorigenesis, cancer progression, and patient prognosis. Several inflammatory markers derived from peripheral blood cells count, such as the neutrophil-lymphocyte ratio (NLR), derived neutrophil-lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) are considered as prognostic markers in several types of malignancy. Here, we investigate and validate a prognostic model in early breast cancer (eBC) patients to predict disease-free survival (DFS) based on readily available baseline clinicopathological prognostic factors and preoperative peripheral blood-derived indexes. We analyzed a training cohort of 710 BC patients and two external validation cohorts of 980 and 157 eBC patients, respectively, with different demographic origins. An elevated preoperative NLR is a better DFS predictor than PLR, MLR, and SII in patients with eBC. The prognostic model generated in this study was able to classify patients into three groups with different risks of relapse based on ECOG-PS, presence of comorbidities, T and N stage, PgR status, and NLR. Prognostic models derived from the combination of clinicopathological features and peripheral blood indices, such as NLR, represent attractive markers mainly because they are easily detectable and applicable in daily clinical practice. More comprehensive prospective studies are needed to unveil their actual effectiveness.
DOI: 10.34740/kaggle/dsv/5227348
title: 2021 World Population (updated daily)
DOI: 10.57745/rzzvtb
title: FLORESENTINELLE-readme-temp-soil.txt

description: :unav
DOI: 10.57745/i4s4tc
title: floresentinelle-data-temp-soil_2021.tab

description: :unav
DOI: 10.57745/hzocjt
title: floresentinelle-data-temp-soil_2023.tab

description: :unav
DOI: 10.57745/wrhhkj
title: floresentinelle-metadata-temp-soil_2021.tab

description: :unav
DOI: 10.57745/qcmiql
title: floresentinelle-metadata-temp-soil_2023.tab

description: :unav
DOI: 10.5281/zenodo.7763552
title: Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures

description: Original dataset associated with the article "Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures". Covers all 108 final decisions in EU merger procedures with a Phase II investigation (Council Regulation 139/2004) of which a public version was available in the electronic registry of DG COMP in September 2020.
DOI: 10.5281/zenodo.7763551
title: Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures

description: Original dataset associated with the article "Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures". Covers all 108 final decisions in EU merger procedures with a Phase II investigation (Council Regulation 139/2004) of which a public version was available in the electronic registry of DG COMP in September 2020.
DOI: 10.6084/m9.figshare.20078675
title: Development and assessment of a low literacy, pictographic asthma action plan with clinical automation to enhance guideline-concordant care for children with asthma

description: Asthma is characterized by reversible pulmonary symptoms, frequent hospitalizations, poor quality of life, and varied treatment. Parents with low health literacy (HL) is linked to poor asthma outcomes in children. Recent practice updates recommended inhaled corticosteroids for the management of persistent asthma, but guideline-concordant care is suboptimal. Our aim was to develop and assess an Asthma Action Plan (AAP) that could serve as an individualized plan for low HL families and facilitate guideline-concordant care for clinicians. We followed the National Institute of Health 5-step “Clear & Simple” approach to develop the Uniformed Services AAP. Our AAP included symptom pictographs (dyspnea, cough, sleep, activity) and guideline-concordant clinical automation tools. Caregivers assessed the pictograms for validity (transparency of ≥ 85%; translucency score ≥ 5; and ≥ 85% recall). Readability was assessed using 7 formulas. (&lt;6th Grade was acceptable). Comprehensibility, design quality, and usefulness was assessed by caregivers using the Consumer Information Rating Form (CIRF) (&gt;80% was acceptable). Understandability and actionability was assessed by medical librarians using the Patient Education Materials Assessment Tool-Printable (&gt;80% was acceptable). Suitability was assessed by clinicians using the modified Suitability Assessment of Materials (SAM) instrument (&gt;70% was superior). All 12 pictograms were validated (<i>N</i> = 118 respondents). Readability demonstrated a 4th grade level. Overall CIRF percentile score = 80.4%. Understandability and Actionability = 100%. Suitability score = 75%. Our AAP was formally endorsed by the Allergy & Asthma Network. The Uniformed Services AAP is a novel tool with embedded clinical automation that can address low HL and enhance guideline-concordant care.
DOI: 10.6084/m9.figshare.20078675.v1
title: Development and assessment of a low literacy, pictographic asthma action plan with clinical automation to enhance guideline-concordant care for children with asthma

description: Asthma is characterized by reversible pulmonary symptoms, frequent hospitalizations, poor quality of life, and varied treatment. Parents with low health literacy (HL) is linked to poor asthma outcomes in children. Recent practice updates recommended inhaled corticosteroids for the management of persistent asthma, but guideline-concordant care is suboptimal. Our aim was to develop and assess an Asthma Action Plan (AAP) that could serve as an individualized plan for low HL families and facilitate guideline-concordant care for clinicians. We followed the National Institute of Health 5-step “Clear & Simple” approach to develop the Uniformed Services AAP. Our AAP included symptom pictographs (dyspnea, cough, sleep, activity) and guideline-concordant clinical automation tools. Caregivers assessed the pictograms for validity (transparency of ≥ 85%; translucency score ≥ 5; and ≥ 85% recall). Readability was assessed using 7 formulas. (&lt;6th Grade was acceptable). Comprehensibility, design quality, and usefulness was assessed by caregivers using the Consumer Information Rating Form (CIRF) (&gt;80% was acceptable). Understandability and actionability was assessed by medical librarians using the Patient Education Materials Assessment Tool-Printable (&gt;80% was acceptable). Suitability was assessed by clinicians using the modified Suitability Assessment of Materials (SAM) instrument (&gt;70% was superior). All 12 pictograms were validated (<i>N</i> = 118 respondents). Readability demonstrated a 4th grade level. Overall CIRF percentile score = 80.4%. Understandability and Actionability = 100%. Suitability score = 75%. Our AAP was formally endorsed by the Allergy & Asthma Network. The Uniformed Services AAP is a novel tool with embedded clinical automation that can address low HL and enhance guideline-concordant care.
DOI: 10.6084/m9.figshare.20152423
title: Association of corticosteroid use and attention deficit/hyperactivity disorder in asthmatic children varies by age

description: We aim to examine the impact of corticosteroids use on ADHD among children with asthma by administration routes. A population-based, cross-sectional analysis included pediatric patients ages 5–20 years old from the 2016 and 2019 Kids Inpatient Database (unweighted <i>N</i> = 111,702). ICD-10-CM codes were used to identify corticosteroids use, asthma, and ADHD cases. Survey logistic regression models with purposeful variable selection algorithms were built to examine the association between corticosteroids use, and ADHD by asthma severity and age. An inverse probability weighting (IPW) approach was used to help further control residual confounding, Among children aged 5–11 years old, the odds of ADHD were significantly higher in children with moderate to severe asthma who used inhaled corticosteroids than nonusers (moderate asthma: adjusted odds ratios [aOR] 1.46, 95% confidence interval [CI] 1.14–2.44; severe asthma: aOR 1.61, 95% CI 1.18–2.21). Although oral corticosteroid use was not independently associated with ADHD in young children, combined use of inhaled and oral corticosteroid had almost 5 times higher odds of use among ADHD in children with severe asthma <i>vs.</i> nonusers (aOR 4.85, 95% CI 2.07 − 11.35). No associations were found between any corticosteroid use and ADHD among asthmatic children aged 12–20 years. In this retrospective analysis, we found inhaled corticosteroids were positively associated with ADHD in younger children with moderate to severe asthma, but not in older children.
DOI: 10.6084/m9.figshare.20152423.v1
title: Association of corticosteroid use and attention deficit/hyperactivity disorder in asthmatic children varies by age

description: We aim to examine the impact of corticosteroids use on ADHD among children with asthma by administration routes. A population-based, cross-sectional analysis included pediatric patients ages 5–20 years old from the 2016 and 2019 Kids Inpatient Database (unweighted <i>N</i> = 111,702). ICD-10-CM codes were used to identify corticosteroids use, asthma, and ADHD cases. Survey logistic regression models with purposeful variable selection algorithms were built to examine the association between corticosteroids use, and ADHD by asthma severity and age. An inverse probability weighting (IPW) approach was used to help further control residual confounding, Among children aged 5–11 years old, the odds of ADHD were significantly higher in children with moderate to severe asthma who used inhaled corticosteroids than nonusers (moderate asthma: adjusted odds ratios [aOR] 1.46, 95% confidence interval [CI] 1.14–2.44; severe asthma: aOR 1.61, 95% CI 1.18–2.21). Although oral corticosteroid use was not independently associated with ADHD in young children, combined use of inhaled and oral corticosteroid had almost 5 times higher odds of use among ADHD in children with severe asthma <i>vs.</i> nonusers (aOR 4.85, 95% CI 2.07 − 11.35). No associations were found between any corticosteroid use and ADHD among asthmatic children aged 12–20 years. In this retrospective analysis, we found inhaled corticosteroids were positively associated with ADHD in younger children with moderate to severe asthma, but not in older children.
DOI: 10.6084/m9.figshare.20341097
title: Impact of mepolizumab in patients with high-burden severe asthma within a managed care population

description: To evaluate the real-world impact of mepolizumab on the incidence of asthma exacerbations, oral corticosteroid (OCS) use and asthma exacerbation-related costs in patients with high-burden severe asthma. This was a retrospective study of the MarketScan Commercial and Medicare Databases in patients with high-burden severe asthma (≥80th percentile of total healthcare expenditure and/or significant comorbidity burden). Patients were ≥12 years of age upon mepolizumab initiation (index date November 1, 2015–December 31, 2018) and had ≥2 mepolizumab administrations during the 6 months post-index. Asthma exacerbation frequency (primary outcome), use of OCS (secondary outcome), and asthma exacerbation-related costs (exploratory outcome) were assessed during the 12 months pre-index (baseline) and post-index (follow-up). In total, 281 patients were analyzed. Mepolizumab significantly reduced the proportion of patients with any asthma exacerbation (<i>P</i> &lt; 0.001) or exacerbations requiring hospitalization (<i>P</i> = 0.004) in the follow-up versus baseline period. The mean number of exacerbations decreased from 2.5 to 1.5 events/patient/year (relative reduction: 40.0%; <i>P</i> &lt; 0.001). The proportion of patients with ≥1 OCS claim also decreased significantly from 94.0% to 81.9% (relative reduction: 12.9%; <i>P</i> &lt; 0.001), corresponding to a decrease from 6.6 to 4.7 claims/person/year (<i>P</i> &lt; 0.001). Of the 264 patients with ≥1 OCS claim during baseline, 191 (72.3%) showed a decrease in mean daily OCS use by ≥50% in 117 patients (61.3%). Total asthma exacerbation-related costs were significantly lower after mepolizumab was initiated (<i>P</i> &lt; 0.001). Mepolizumab reduced exacerbation frequency, OCS use and asthma exacerbation-related costs in patients with high-cost severe asthma. Mepolizumab provides real-world benefits to patients, healthcare systems and payers.
DOI: 10.6084/m9.figshare.20341097.v2
title: Impact of mepolizumab in patients with high-burden severe asthma within a managed care population

description: To evaluate the real-world impact of mepolizumab on the incidence of asthma exacerbations, oral corticosteroid (OCS) use and asthma exacerbation-related costs in patients with high-burden severe asthma. This was a retrospective study of the MarketScan Commercial and Medicare Databases in patients with high-burden severe asthma (≥80th percentile of total healthcare expenditure and/or significant comorbidity burden). Patients were ≥12 years of age upon mepolizumab initiation (index date November 1, 2015–December 31, 2018) and had ≥2 mepolizumab administrations during the 6 months post-index. Asthma exacerbation frequency (primary outcome), use of OCS (secondary outcome), and asthma exacerbation-related costs (exploratory outcome) were assessed during the 12 months pre-index (baseline) and post-index (follow-up). In total, 281 patients were analyzed. Mepolizumab significantly reduced the proportion of patients with any asthma exacerbation (<i>P</i> &lt; 0.001) or exacerbations requiring hospitalization (<i>P</i> = 0.004) in the follow-up versus baseline period. The mean number of exacerbations decreased from 2.5 to 1.5 events/patient/year (relative reduction: 40.0%; <i>P</i> &lt; 0.001). The proportion of patients with ≥1 OCS claim also decreased significantly from 94.0% to 81.9% (relative reduction: 12.9%; <i>P</i> &lt; 0.001), corresponding to a decrease from 6.6 to 4.7 claims/person/year (<i>P</i> &lt; 0.001). Of the 264 patients with ≥1 OCS claim during baseline, 191 (72.3%) showed a decrease in mean daily OCS use by ≥50% in 117 patients (61.3%). Total asthma exacerbation-related costs were significantly lower after mepolizumab was initiated (<i>P</i> &lt; 0.001). Mepolizumab reduced exacerbation frequency, OCS use and asthma exacerbation-related costs in patients with high-cost severe asthma. Mepolizumab provides real-world benefits to patients, healthcare systems and payers.