cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5902390
title: ICE-based Refinement Type Discovery for Higher-Order Functional Programs

description: This dataset contains the code and benchmarks needed to replicate the experimental results presented in the TACAS 2016 paper "ICE-based Refinement Type Discovery for Higher-Order Functional Programs".<br>The verification of higher-order functional programs is a challenging problem, the existing approaches to which are hampered by the need for predicates describing loops and components behave in order for verification to be possible. Here, a novel approach intended to overcome these requirements by combining the existing refinement types approach with the invariant discovery framework ICE is presented.<br>This novel implementation consists of two parts. First, a front end written in OCaml, named RType (https://github.com/hopv/r_type), that generates Horn clauses from programs written in a subset of OCaml (as described in section 2 of the accompanying paper). Second, a Horn clause solver written in Rust, named HoIce (https://github.com/hopv/hoice), that implements the modified ICE framework presented in the accompanying paper.<br>The novel implementation as well as the benchmarks and scripts needed to reproduce its evaluation are presented here. Further details on those benchmarks and instructions on running them can be found in the <b>README</b> file.
DOI: 10.6084/m9.figshare.5902387
title: bedrock outcrop models and photographs

description: The .ply files were created in vSFM for the purpose of generating a scale for photographs where a scale could not be obtained directly in the field. The scale was generated using the 3D model and known relative camera locations. The .JPG photographs were used to trace the fractures within the sampling window.
DOI: 10.6084/m9.figshare.5902387.v1
title: bedrock outcrop models and photographs

description: The .ply files were created in vSFM for the purpose of generating a scale for photographs where a scale could not be obtained directly in the field. The scale was generated using the 3D model and known relative camera locations. The .JPG photographs were used to trace the fractures within the sampling window.
DOI: 10.6084/m9.figshare.5902381
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed.
DOI: 10.6084/m9.figshare.5902381.v1
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: This archive contains a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by using the Variational Interpolation (VI) method to remove clouds which pollutes the original Snow Cover Area (SCA) products from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS)’s.
DOI: 10.6084/m9.figshare.5902381.v2
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed.
DOI: 10.6084/m9.figshare.5902381.v4
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed.
DOI: 10.6084/m9.figshare.5902381.v3
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed.
DOI: 10.6084/m9.figshare.5902369
title: Country central coordinates

description: This dataset is a .csv file containing central latitude and longitude points for all countries around the globe
DOI: 10.6084/m9.figshare.5902366
title: Rock failure and erosion of a fault damage zone as a function of rock properties: Alpine Fault at Waikukupa River

description: Erosion rates in the hanging wall of the Alpine Fault are high, keeping pace with rock uplift over time frames of 10<sup>4</sup>–10<sup>6</sup> years. On shorter time frames, prediction of temporal and spatial distribution of erosion is challenging and must account for local conditions and parameters including rock strength, topographic stresses and failure conditions. Constrained by field observations of rock strength, we use 3D mechanical models to predict where and by what mechanism slope failure and erosion are likely to take place along the Waikukupa section of the Alpine Fault. Shear failure is favoured along the base of slopes and where pore pressure is high. Tensile failure is favoured along ridges, higher on slopes and when pore pressure is moderate. A dry material with a high degree of rock strength heterogeneity promotes bedrock gully development, whereas distributed failure is more likely to occur when the material is saturated.
DOI: 10.6084/m9.figshare.5902366.v1
title: Rock failure and erosion of a fault damage zone as a function of rock properties: Alpine Fault at Waikukupa River

description: Erosion rates in the hanging wall of the Alpine Fault are high, keeping pace with rock uplift over time frames of 10<sup>4</sup>–10<sup>6</sup> years. On shorter time frames, prediction of temporal and spatial distribution of erosion is challenging and must account for local conditions and parameters including rock strength, topographic stresses and failure conditions. Constrained by field observations of rock strength, we use 3D mechanical models to predict where and by what mechanism slope failure and erosion are likely to take place along the Waikukupa section of the Alpine Fault. Shear failure is favoured along the base of slopes and where pore pressure is high. Tensile failure is favoured along ridges, higher on slopes and when pore pressure is moderate. A dry material with a high degree of rock strength heterogeneity promotes bedrock gully development, whereas distributed failure is more likely to occur when the material is saturated.
DOI: 10.6084/m9.figshare.5902360
title: longRange

description: YY1 HiChip<br><br>
DOI: 10.6084/m9.figshare.5902360.v1
title: longRange

description: YY1 HiChip<br><br>
DOI: 10.6084/m9.figshare.5902279
title: Single agent and synergistic combinatorial efficacy of first-in-class small molecule imipridone ONC201 in hematological malignancies

description: ONC201, founding member of the imipridone class of small molecules, is currently being evaluated in advancer cancer clinical trials. We explored single agent and combinatorial efficacy of ONC201 in preclinical models of hematological malignancies. ONC201 demonstrated (GI50 1–8 <i>µ</i>M) dose- and time-dependent efficacy in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), Burkitt's lymphoma, anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), Hodgkin's lymphoma (nodular sclerosis) and multiple myeloma (MM) cell lines including cells resistant to standard of care (dexamethasone in MM) and primary samples. ONC201 induced caspase-dependent apoptosis that involved activation of the integrated stress response (ATF4/CHOP) pathway, inhibition of Akt phosphorylation, Foxo3a activation, downregulation of cyclin D1, IAP and Bcl-2 family members. ONC201 synergistically reduced cell viability in combination with cytarabine and 5-azacytidine in AML cells. ONC201 combined with cytarabine in a Burkitt's lymphoma xenograft model induced tumor growth inhibition that was superior to either agent alone. ONC201 synergistically combined with bortezomib in MM, MCL and ALCL cells and with ixazomib or dexamethasone in MM cells. ONC201 combined with bortezomib in a Burkitt's lymphoma xenograft model reduced tumor cell density and improved CHOP induction compared to either agent alone. These results serve as a rationale for ONC201 single-agent trials in relapsed/refractory acute leukemia, non-Hodgkin's lymphoma, MM and combination trial with dexamethasone in MM, provide pharmacodynamic biomarkers and identify further synergistic combinatorial regimens that can be explored in the clinic.
DOI: 10.6084/m9.figshare.5902279.v1
title: Single agent and synergistic combinatorial efficacy of first-in-class small molecule imipridone ONC201 in hematological malignancies

description: ONC201, founding member of the imipridone class of small molecules, is currently being evaluated in advancer cancer clinical trials. We explored single agent and combinatorial efficacy of ONC201 in preclinical models of hematological malignancies. ONC201 demonstrated (GI50 1–8 <i>µ</i>M) dose- and time-dependent efficacy in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), Burkitt's lymphoma, anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), Hodgkin's lymphoma (nodular sclerosis) and multiple myeloma (MM) cell lines including cells resistant to standard of care (dexamethasone in MM) and primary samples. ONC201 induced caspase-dependent apoptosis that involved activation of the integrated stress response (ATF4/CHOP) pathway, inhibition of Akt phosphorylation, Foxo3a activation, downregulation of cyclin D1, IAP and Bcl-2 family members. ONC201 synergistically reduced cell viability in combination with cytarabine and 5-azacytidine in AML cells. ONC201 combined with cytarabine in a Burkitt's lymphoma xenograft model induced tumor growth inhibition that was superior to either agent alone. ONC201 synergistically combined with bortezomib in MM, MCL and ALCL cells and with ixazomib or dexamethasone in MM cells. ONC201 combined with bortezomib in a Burkitt's lymphoma xenograft model reduced tumor cell density and improved CHOP induction compared to either agent alone. These results serve as a rationale for ONC201 single-agent trials in relapsed/refractory acute leukemia, non-Hodgkin's lymphoma, MM and combination trial with dexamethasone in MM, provide pharmacodynamic biomarkers and identify further synergistic combinatorial regimens that can be explored in the clinic.
DOI: 10.6084/m9.figshare.5902240
title: A suite of DNA methylation markers that can detect most common human cancers

description: Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available—TCGA Illumina HumanMethylation450 data with over 8,500 tumors—in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC &gt;0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, <i>SEPT9</i> and <i>GSTP1</i>, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is <i>MIR129-2</i>. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.
DOI: 10.6084/m9.figshare.5902240.v2
title: A suite of DNA methylation markers that can detect most common human cancers

description: Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available—TCGA Illumina HumanMethylation450 data with over 8,500 tumors—in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC &gt;0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, <i>SEPT9</i> and <i>GSTP1</i>, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is <i>MIR129-2</i>. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.
DOI: 10.6084/m9.figshare.5902240.v1
title: A suite of DNA methylation markers that can detect most common human cancers

description: Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available—TCGA Illumina HumanMethylation450 data with over 8,500 tumors—in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC &gt;0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, <i>SEPT9</i> and <i>GSTP1</i>, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is <i>MIR129-2</i>. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.
DOI: 10.6084/m9.figshare.5902234
title: Tooth-level versus patient-level

description: Tooth-level versus patient-level
DOI: 10.6084/m9.figshare.5902234.v1
title: Tooth-level versus patient-level

description: Tooth-level versus patient-level
DOI: 10.6084/m9.figshare.5902213
title: A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

description: We presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by using the Variational Interpolation (VI) method to remove clouds which pollutes the original Snow Cover Area (SCA) products from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS)’s
DOI: 10.6084/m9.figshare.5902198
title: Climate and visitation to Utah's ‘Mighty 5’ national parks

description: The relationship between climate and visitation to managed natural areas has been analyzed at a variety of different spatial scales. We expand upon our existing knowledge on this topic by: (1) determining how a wide range of climate variables affect visitation across a regional tourism system; and (2) identifying which variables affect visitation system-wide and which variables only affect visitation at specific parks. Our analysis focuses on five national parks located in southern Utah (USA) commonly referred to as ‘the Mighty 5’. We found monthly average daily maximum temperatures were the best predictor of system-wide visitation, suggesting average daily maximum temperatures play a more direct role in tourists’ travel decisions relative to other climate variables, including other derivations of temperature. We also found declines in monthly park visitation for three parks (Arches, Canyonlands, and Capitol Reef) once average daily maximum temperatures exceed 25 C. For Bryce Canyon and Zion however, monthly visitation continued to increase well above this threshold. The geophysical characteristics of these parks appear to mediate the relationship between average daily maximum temperature and visitation. The commonly found ‘inverted U-shape’ relationship between temperature and visitation should not be seen as a universal maxim. We also found precipitation to be a poor predictor of system-wide visitation, but a significant factor shaping the travel decisions of visitors to Bryce Canyon, the only park to offer snow-based outdoor recreation opportunities. Future research should not disregard the possibility of precipitation being a significant factor shaping visitors’ travel decisions. By conducting our analyses at two distinct scales, we have found there is a difference between the individual climate variables that are regionally-significant drivers of visitation and those that are locally-significant drivers of visitation. Scale matters in analyses of the relationship between climate and visitation.