cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7750826
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2003

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 500m spatial resolution and monthly 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>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2003. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2002</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2003 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> 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, 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>. (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.7750825
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2003

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 500m spatial resolution and monthly 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>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2003. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2002</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2003 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> 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, 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>. (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: 10.34740/kaggle/dsv/5199445
title: AutoXGB
DOI: 10.6084/m9.figshare.21666446
title: Felsic_Rock_Geochemistry.xlsx

description: Literature data on felsic igneous rock whole-rock composition.
DOI: 10.6084/m9.figshare.21666470
title: Supplementary_Readme

description: Supplementary Readme file for manuscript submitted to Tektonika: <strong>"Hot, wide, continental back-arcs explain Earth’s enigmatic mid-Proterozoic magmatic and metamorphic record"</strong> <br> Nick M W Roberts, Kent C. Condie, Richard M. Palin, Christopher J Spencer
DOI: 10.6084/m9.figshare.21666470.v1
title: Supplementary_Readme

description: Supplementary Readme file for manuscript submitted to Tektonika: <strong>"Hot, wide, continental back-arcs explain Earth’s enigmatic mid-Proterozoic magmatic and metamorphic record"</strong> <br> Nick M W Roberts, Kent C. Condie, Richard M. Palin, Christopher J Spencer
DOI: 10.5281/zenodo.6831903
title: dataset for paper "Leaf nitrogen from the perspective of optimal plant function"

description: This dataset is for paper "Leaf nitrogen from the perspective of optimal plant function"
DOI: 10.5281/zenodo.6831902
title: dataset for paper "Leaf nitrogen from the perspective of optimal plant function"

description: This dataset is for paper "Leaf nitrogen from the perspective of optimal plant function"
DOI: 10.5281/zenodo.6556096
title: Global Datasets of carbon isotope composition (δ13C) for Ecological and Earth System Research

description: This is dataset for paper: global Datasets of carbon isotope composition (δ13C) for Ecological and Earth System Research, which include soil δ13C samples from 2500 research sites across global.
DOI: 10.5281/zenodo.6556095
title: Global Datasets of carbon isotope composition (δ13C) for Ecological and Earth System Research

description: This is dataset for paper: global Datasets of carbon isotope composition (δ13C) for Ecological and Earth System Research, which include soil δ13C samples from 2500 research sites across global.
DOI: 10.6084/m9.figshare.16626328
title: Removal of Manganese and Copper from Aqueous Solution by Yeast <i>Papiliotrema huenov</i>

description: <i>Papiliotrema huenov</i> was previously reported to be highly tolerant of a range of extremely toxic heavy metals. This study aimed to identify the potential of <i>P. huenov</i> to remove manganese and copper from aqueous solution. Physical conditions which affect removal of Mn(II) and Cu(II) were determined. Optimal temperature for adsorption of both metal ions was 30 °C, and optimal pH for maximum uptake of Mn(II) and Cu(II) were 5 and 6, respectively. Under these conditions, living cells of <i>P. huenov</i> accumulated up to 75.58% of 110 mg/L Mn(II) and 70.5% of 128 mg/L Cu(II) over 120 h, whereas, the removal efficiency of metal ions by dead cells over 1 h was 60.3% and 56.5%, respectively. These results indicate that living cells are more effective than dead biomass for bioremediation, but that greater time is required. The experimental data extends the potential use of <i>P. huenov</i> in biosorption and bioaccumulation of toxic heavy metals to copper and manganese, two of the most common industrial contaminants.
DOI: 10.6084/m9.figshare.16626328.v1
title: Removal of Manganese and Copper from Aqueous Solution by Yeast <i>Papiliotrema huenov</i>

description: <i>Papiliotrema huenov</i> was previously reported to be highly tolerant of a range of extremely toxic heavy metals. This study aimed to identify the potential of <i>P. huenov</i> to remove manganese and copper from aqueous solution. Physical conditions which affect removal of Mn(II) and Cu(II) were determined. Optimal temperature for adsorption of both metal ions was 30 °C, and optimal pH for maximum uptake of Mn(II) and Cu(II) were 5 and 6, respectively. Under these conditions, living cells of <i>P. huenov</i> accumulated up to 75.58% of 110 mg/L Mn(II) and 70.5% of 128 mg/L Cu(II) over 120 h, whereas, the removal efficiency of metal ions by dead cells over 1 h was 60.3% and 56.5%, respectively. These results indicate that living cells are more effective than dead biomass for bioremediation, but that greater time is required. The experimental data extends the potential use of <i>P. huenov</i> in biosorption and bioaccumulation of toxic heavy metals to copper and manganese, two of the most common industrial contaminants.
DOI: 10.6084/m9.figshare.22302805
title: BR-Sa1，BR-Sa3，CA-CF1

description: The modified dataset contains BASE data from the Amerflux siteSE data from the Amerflux site
DOI: 10.6084/m9.figshare.22302805.v1
title: BR-Sa1，BR-Sa3，CA-CF1

description: The modified dataset contains BASE data from the Amerflux siteSE data from the Amerflux site
DOI: 10.34740/kaggle/dsv/5199455
title: LUFlow Network Intrusion Detection Data Set
DOI: 10.6084/m9.figshare.22302826
title: Supplementary Material for: Second primary malignancies in patients with a neuroendocrine neoplasm in England

description: Introduction Patients with neuroendocrine neoplasms (NENs) may often develop other malignancies. This study aimed to identify the frequency at which these second malignancies occurred in England. Methods Data was extracted from the National Cancer Registration and Analysis Service (NCRAS) on all patients diagnosed with a NEN at one of eight NEN site groups between 2012-2018: appendix, caecum, colon, lung, pancreas, rectum, small intestine and stomach. WHO International Classification of Disease edition 10 (ICD-10) codes were used to identify patients who had been diagnosed with an additional non-NEN cancer. Standardised incidence ratios (SIRs) for tumours diagnosed after the index NEN were produced for each non-NEN cancer type by sex and site. Results A total of 20,579 patients were included in the study. The most commonly occurring non-NEN cancers after NEN diagnosis were prostate (20%), lung (20%) and breast (15%). Statistically significant SIRs were observed for non-NEN cancer of the lung (SIR=1.85, 95%CI:1.55-2.22), colon (SIR=1.78, 95%CI:1.40-2.27), prostate (SIR=1.56, 95%CI:1.31-1.86), kidney (SIR=3.53, 95%CI:2.72-4.59) and thyroid (SIR=6.31, 95%CI:4.26-9.33). When stratified by sex, statistically significant SIRs remained for lung, renal, colon and thyroid tumours. Additionally, females had a statistically significant SIR for stomach cancer (2.65, 95%CI:1.26-5.57) and bladder cancer (SIR=2.61, 95%CI:1.36-5.02). Discussion/Conclusion This study found that patients with a NEN experienced a metachronous tumour of the lung, prostate, kidney, colon and thyroid at a higher rate than the general population of England. Surveillance and engagement in existing screening programmes is required to enable earlier diagnosis of second non-NEN tumours in these patients.
DOI: 10.6084/m9.figshare.22302862
title: Supplementary Material for: Second primary malignancies in patients with a neuroendocrine neoplasm in England

description: Introduction Patients with neuroendocrine neoplasms (NENs) may often develop other malignancies. This study aimed to identify the frequency at which these second malignancies occurred in England. Methods Data was extracted from the National Cancer Registration and Analysis Service (NCRAS) on all patients diagnosed with a NEN at one of eight NEN site groups between 2012-2018: appendix, caecum, colon, lung, pancreas, rectum, small intestine and stomach. WHO International Classification of Disease edition 10 (ICD-10) codes were used to identify patients who had been diagnosed with an additional non-NEN cancer. Standardised incidence ratios (SIRs) for tumours diagnosed after the index NEN were produced for each non-NEN cancer type by sex and site. Results A total of 20,579 patients were included in the study. The most commonly occurring non-NEN cancers after NEN diagnosis were prostate (20%), lung (20%) and breast (15%). Statistically significant SIRs were observed for non-NEN cancer of the lung (SIR=1.85, 95%CI:1.55-2.22), colon (SIR=1.78, 95%CI:1.40-2.27), prostate (SIR=1.56, 95%CI:1.31-1.86), kidney (SIR=3.53, 95%CI:2.72-4.59) and thyroid (SIR=6.31, 95%CI:4.26-9.33). When stratified by sex, statistically significant SIRs remained for lung, renal, colon and thyroid tumours. Additionally, females had a statistically significant SIR for stomach cancer (2.65, 95%CI:1.26-5.57) and bladder cancer (SIR=2.61, 95%CI:1.36-5.02). Discussion/Conclusion This study found that patients with a NEN experienced a metachronous tumour of the lung, prostate, kidney, colon and thyroid at a higher rate than the general population of England. Surveillance and engagement in existing screening programmes is required to enable earlier diagnosis of second non-NEN tumours in these patients.
DOI: 10.6084/m9.figshare.22302862.v1
title: Supplementary Material for: Second primary malignancies in patients with a neuroendocrine neoplasm in England

description: Introduction Patients with neuroendocrine neoplasms (NENs) may often develop other malignancies. This study aimed to identify the frequency at which these second malignancies occurred in England. Methods Data was extracted from the National Cancer Registration and Analysis Service (NCRAS) on all patients diagnosed with a NEN at one of eight NEN site groups between 2012-2018: appendix, caecum, colon, lung, pancreas, rectum, small intestine and stomach. WHO International Classification of Disease edition 10 (ICD-10) codes were used to identify patients who had been diagnosed with an additional non-NEN cancer. Standardised incidence ratios (SIRs) for tumours diagnosed after the index NEN were produced for each non-NEN cancer type by sex and site. Results A total of 20,579 patients were included in the study. The most commonly occurring non-NEN cancers after NEN diagnosis were prostate (20%), lung (20%) and breast (15%). Statistically significant SIRs were observed for non-NEN cancer of the lung (SIR=1.85, 95%CI:1.55-2.22), colon (SIR=1.78, 95%CI:1.40-2.27), prostate (SIR=1.56, 95%CI:1.31-1.86), kidney (SIR=3.53, 95%CI:2.72-4.59) and thyroid (SIR=6.31, 95%CI:4.26-9.33). When stratified by sex, statistically significant SIRs remained for lung, renal, colon and thyroid tumours. Additionally, females had a statistically significant SIR for stomach cancer (2.65, 95%CI:1.26-5.57) and bladder cancer (SIR=2.61, 95%CI:1.36-5.02). Discussion/Conclusion This study found that patients with a NEN experienced a metachronous tumour of the lung, prostate, kidney, colon and thyroid at a higher rate than the general population of England. Surveillance and engagement in existing screening programmes is required to enable earlier diagnosis of second non-NEN tumours in these patients.
DOI: 10.25934/pr00006830.3
title: Available IPD datapackage for study 'MULTICENTER, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, PHASE 3 TRIAL OF FULVESTRANT (FASLODEX (REGISTERED)). WITH OR WITHOUT PD-0332991 (PALBOCICLIB) +/- GOSERELIN IN WOMEN WITH HORMONE RECEPTOR-POSITIVE, HER2-NEGATIVE METASTATIC BREAST CANCER WHOSE DISEASE PROGRESSED AFTER PRIOR ENDOCRINE THERAPY'

description: The study is a randomized, double blind, placebo controlled, Phase 3 clinical trial with the primary objective of demonstrating the superiority of palbociclib in combination with fulvestrant (Faslodex®) over fulvestrant alone in prolonging PFS in women with HR+, HER2 negative metastatic breast cancer whose disease has progressed after prior endocrine therapy. The safety between the two treatment arms will also be compared. During study treatment, pre- and perimenopausal women must be receiving therapy with the LHRH agonist goserelin (Zoladex® or generic).
DOI: 10.25934/pr00008563
title: Tumor Growth Inhibition-Overall Survival (TGI-OS) model development and validation for hormone receptor positive (HR+)/human epidermal growth factor receptor 2 negative (HER2-) breast cancer

description: Breast cancer is one of the most common cancers with more than 200 thousand new diagnoses each year in the US alone. Breast cancer has certain subtypes that influence the treatment options. One such type is called hormone receptor positive (HR+) that represents over 70% of the disease. In a woman’s body, estrogen is the hormone that regulates the menstrual cycle while progesterone is the hormone that supports pregnancy. Cell receptors are proteins either inside a cell or on its surface which receive a signal. Tumor in HR+ breast cancer express receptors against estrogen or progesterone. Another important subtype human epidermal growth factor receptor 2 negative (HER2-); HER2 helps control cell growth in normal cells. While there are multiple treatments available including recently approved drugs, significant unmet needs remain for this combination of subtypes (HR+/HER2-). The purpose of this study is to develop a tool that can enhance the development of new treatments.

One of the key challenges of the development of new cancer treatment is the size of the clinical trials (number of patients). This is because the duration of a patient’s life after treatment, or overall survival (OS), is often used as the main indicator of an effective treatment in clinical trials for cancer, and OS requires a large number of patients to demonstrate efficacy. Therefore, there is a need to develop alternative tools that can predict efficacy with smaller amounts of data.

The approach being investigated in this study is to analyze how the size of the tumor changes over time (time profile) after the treatment. Because tumor time profile has rich information on each patient’s response to treatment, it is believed that modeling tumor time profile can give us prediction of OS with smaller data. It is also believed that relationships between tumor time profile and OS are common across studies, i.e. once we learn such relationships from previous clinical trials, we can predict OS based only on the tumor time profile for a new study, thereby reducing the need for large clinical trials.

This study aims to develop a mathematical model that links tumor time profile with OS using clinical trial data for a recently approved drug (palbociclib). If successful, this can be a useful tool for future drug development in the HR+ breast cancer indication.
DOI: 10.6084/m9.figshare.22302871
title: Supplementary Material for: Second primary malignancies in patients with a neuroendocrine neoplasm in England

description: Introduction Patients with neuroendocrine neoplasms (NENs) may often develop other malignancies. This study aimed to identify the frequency at which these second malignancies occurred in England. Methods Data was extracted from the National Cancer Registration and Analysis Service (NCRAS) on all patients diagnosed with a NEN at one of eight NEN site groups between 2012-2018: appendix, caecum, colon, lung, pancreas, rectum, small intestine and stomach. WHO International Classification of Disease edition 10 (ICD-10) codes were used to identify patients who had been diagnosed with an additional non-NEN cancer. Standardised incidence ratios (SIRs) for tumours diagnosed after the index NEN were produced for each non-NEN cancer type by sex and site. Results A total of 20,579 patients were included in the study. The most commonly occurring non-NEN cancers after NEN diagnosis were prostate (20%), lung (20%) and breast (15%). Statistically significant SIRs were observed for non-NEN cancer of the lung (SIR=1.85, 95%CI:1.55-2.22), colon (SIR=1.78, 95%CI:1.40-2.27), prostate (SIR=1.56, 95%CI:1.31-1.86), kidney (SIR=3.53, 95%CI:2.72-4.59) and thyroid (SIR=6.31, 95%CI:4.26-9.33). When stratified by sex, statistically significant SIRs remained for lung, renal, colon and thyroid tumours. Additionally, females had a statistically significant SIR for stomach cancer (2.65, 95%CI:1.26-5.57) and bladder cancer (SIR=2.61, 95%CI:1.36-5.02). Discussion/Conclusion This study found that patients with a NEN experienced a metachronous tumour of the lung, prostate, kidney, colon and thyroid at a higher rate than the general population of England. Surveillance and engagement in existing screening programmes is required to enable earlier diagnosis of second non-NEN tumours in these patients.
DOI: 10.6084/m9.figshare.22302871.v1
title: Supplementary Material for: Second primary malignancies in patients with a neuroendocrine neoplasm in England

description: Introduction Patients with neuroendocrine neoplasms (NENs) may often develop other malignancies. This study aimed to identify the frequency at which these second malignancies occurred in England. Methods Data was extracted from the National Cancer Registration and Analysis Service (NCRAS) on all patients diagnosed with a NEN at one of eight NEN site groups between 2012-2018: appendix, caecum, colon, lung, pancreas, rectum, small intestine and stomach. WHO International Classification of Disease edition 10 (ICD-10) codes were used to identify patients who had been diagnosed with an additional non-NEN cancer. Standardised incidence ratios (SIRs) for tumours diagnosed after the index NEN were produced for each non-NEN cancer type by sex and site. Results A total of 20,579 patients were included in the study. The most commonly occurring non-NEN cancers after NEN diagnosis were prostate (20%), lung (20%) and breast (15%). Statistically significant SIRs were observed for non-NEN cancer of the lung (SIR=1.85, 95%CI:1.55-2.22), colon (SIR=1.78, 95%CI:1.40-2.27), prostate (SIR=1.56, 95%CI:1.31-1.86), kidney (SIR=3.53, 95%CI:2.72-4.59) and thyroid (SIR=6.31, 95%CI:4.26-9.33). When stratified by sex, statistically significant SIRs remained for lung, renal, colon and thyroid tumours. Additionally, females had a statistically significant SIR for stomach cancer (2.65, 95%CI:1.26-5.57) and bladder cancer (SIR=2.61, 95%CI:1.36-5.02). Discussion/Conclusion This study found that patients with a NEN experienced a metachronous tumour of the lung, prostate, kidney, colon and thyroid at a higher rate than the general population of England. Surveillance and engagement in existing screening programmes is required to enable earlier diagnosis of second non-NEN tumours in these patients.
DOI: 10.5281/zenodo.7751731
title: Viscosity contrasts in the Venus mantle from tidal deformations

description: The file "Comparison-Benchmark-Dumoulin" contains the values comparing our results with a previous study. The file "Monte-Carlo-sampling" contains the results of the Monte-Carlo sampling. The file "Different-alpha" contains the results to study the effect of the alpha value (related to Andrade's law).
DOI: 10.5281/zenodo.7751730
title: Viscosity contrasts in the Venus mantle from tidal deformations

description: The file "Comparison-Benchmark-Dumoulin" contains the values comparing our results with a previous study. The file "Monte-Carlo-sampling" contains the results of the Monte-Carlo sampling. The file "Different-alpha" contains the results to study the effect of the alpha value (related to Andrade's law).