cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9956378.v1
title: Xerophyta humilis normalised expression

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><i><br></i>Normalised expression values for each gene cluster (i.e. at the gene level) for both seed and leaf datasets (calculated independently, but displayed together). Adjusted p-value is shown for each tissue type only if the change in expression was significant (FDR &lt; 0.01). Column values: <br>padj seed | padj leaf | early maturation seed 1 | early maturation seed 2 | early maturation seed 3 | mid maturation seed 1 | mid maturation seed 2 | mid maturation seed 3 | dry seed 1 | dry seed 2 | dry seed 3 | 100% RWC leaf 1 | 100% RWC leaf 2 | 100% RWC leaf 3 | 80% RWC leaf 1 | 80% RWC leaf 2 | 80% RWC leaf 3 | 60% RWC leaf 1 | 60% RWC leaf 2 | 60% RWC leaf 3 | 40% RWC leaf 1 | 40% RWC leaf 2 | 40% RWC leaf 3 | 5% RWC leaf 1 | 5% RWC leaf 2 | 5% RWC leaf 3
DOI: 10.6084/m9.figshare.9956387.v1
title: grid.1005.4

description: What does Australasian Research Look Like Data for institution
DOI: 10.6084/m9.figshare.9956333
title: Direct infusion electrospray ionisation mass spectrometry applied in the detection of adulteration of coconut oil with palm kernel oil

description: Coconut oil has properties that are beneficial to human health. It assists in reducing total cholesterol, triacylglycerol (TAG), phospholipids, low-density lipoprotein (LDL) cholesterol, and very low-density lipoprotein (VLDL) cholesterol in serum and tissues. So its production, and consequently consumption, have increased in recent years. However, it has been a target for intentional adulteration with lower priced oils and fats, such as soybean oil and palm kernel oil (PKO). Coconut oil (CO) and PKO have similar chemical and physical characteristics that make it difficult to verify adulteration of CO with PKO. This study demonstrates a simple, sensitive, and fast technique that uses direct infusion electrospray ionisation mass spectrometry (ESI-MS) in conjunction with principal component analysis (PCA), in order to detect CO adulterated with PKO. Among the seven commercial coconut oil samples analysed, three were adulterated with PKO. Therefore, the suggested direct infusion ESI-MS method can be used in routine analysis to guarantee the quality of coconut oil.
DOI: 10.6084/m9.figshare.9956333.v1
title: Direct infusion electrospray ionisation mass spectrometry applied in the detection of adulteration of coconut oil with palm kernel oil

description: Coconut oil has properties that are beneficial to human health. It assists in reducing total cholesterol, triacylglycerol (TAG), phospholipids, low-density lipoprotein (LDL) cholesterol, and very low-density lipoprotein (VLDL) cholesterol in serum and tissues. So its production, and consequently consumption, have increased in recent years. However, it has been a target for intentional adulteration with lower priced oils and fats, such as soybean oil and palm kernel oil (PKO). Coconut oil (CO) and PKO have similar chemical and physical characteristics that make it difficult to verify adulteration of CO with PKO. This study demonstrates a simple, sensitive, and fast technique that uses direct infusion electrospray ionisation mass spectrometry (ESI-MS) in conjunction with principal component analysis (PCA), in order to detect CO adulterated with PKO. Among the seven commercial coconut oil samples analysed, three were adulterated with PKO. Therefore, the suggested direct infusion ESI-MS method can be used in routine analysis to guarantee the quality of coconut oil.
DOI: 10.6084/m9.figshare.9956306
title: rat follicular stimulation

description: The data of the follicular counts of the rat ovaries. One side of the rat ovaries was incised and rat were undergone ovarian hyper stimulation with gonadotropins. After hyper stimulation, rat ovaries were removed and compared for follicular counts between each other.
DOI: 10.6084/m9.figshare.9956288
title: Xerophyta humilis representative sequences

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br><br>Representative transcripts: representative sequence for each gene cluster (the transcript with the longest CDS, or longest transcript if no CDS was found). Representative proteins: coding sequences of the best ORF for each representative transcript. <br>LAFL-ABF: contigs and protein-coding sequences for the LAFL and ABI5/ABF gene sequences discussed in the manuscript.
DOI: 10.6084/m9.figshare.9956306.v1
title: rat follicular stimulation

description: The data of the follicular counts of the rat ovaries. One side of the rat ovaries was incised and rat were undergone ovarian hyper stimulation with gonadotropins. After hyper stimulation, rat ovaries were removed and compared for follicular counts between each other.
DOI: 10.6084/m9.figshare.9956273
title: Boundary Detection Using a Bayesian Hierarchical Model for Multiscale Spatial Data

description: Spatial boundary analysis has attained considerable attention in several disciplines including engineering, shape analysis, spatial statistics, and computer science. The inferential question of interest is often to identify rapid surface change of an unobserved latent process. Curvilinear wombling and crisp wombling (or fuzzy) are two major approaches that have emerged in Bayesian spatial statistics literature. These methods are limited to a single spatial scale even though data with multiple spatial scales are often accessible. Thus, we propose a multiscale representation of the directional derivative Karhunen–Loéve expansion to perform directionally based boundary detection. Taking a multiscale spatial perspective allows us, for the first time, to consider the concept of curvilinear boundary fallacy (CBF) error, which is a boundary detection analog to the ecological fallacy that is often studied in spatial change of support literature. Furthermore, we propose a directionally based multiscale curvilinear boundary error criterion to quantify CBF. We refer to this metric as the criterion for boundary aggregation error (BAGE), and use it to perform boundary detection. Several theoretical results are derived to motivate BAGE. In particular, we show that no BAGE exists when the directional derivatives of eigenfunctions of a KL expansion are constant across spatial scales. We illustrate the use of our model through a simulated example and an analysis of Mediterranean wind measurements data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9956276
title: Xerophyta humilis BLAST2GO annotation

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br><br>Results of functional annotation performed with Blast2GO using the representative transcript/protein set.
DOI: 10.6084/m9.figshare.9956276.v1
title: Xerophyta humilis BLAST2GO annotation

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br><br>Results of functional annotation performed with Blast2GO using the representative transcript/protein set.
DOI: 10.6084/m9.figshare.9956288.v2
title: Xerophyta humilis representative sequences

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br><br>Representative transcripts: representative sequence for each gene cluster (the transcript with the longest CDS, or longest transcript if no CDS was found). Representative proteins: coding sequences of the best ORF for each representative transcript. <br>LAFL-ABF: contigs and protein-coding sequences for the LAFL and ABI5/ABF gene sequences discussed in the manuscript.
DOI: 10.6084/m9.figshare.9956264
title: Xerophyta humilis raw transcriptome

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br>Raw transcripts from Trinity de novo assembly of combined seed and leaf <i>Xerophyta humilis</i> samples. Transcript IDs are the Trinity transcript ID followed by the unique gene cluster ID if one is present (example: TRINITY_DN164427_c0_g1_i1|Xh025390c1). Gene cluster IDs denote sets of transcripts that passed RapClust filtering and mapped uniquely to the same genomic locus on the draft <i>Xerophyta humilis </i>genome (and thus represent putative isoforms or fragments of the same gene).
DOI: 10.6084/m9.figshare.9956273.v2
title: Boundary Detection Using a Bayesian Hierarchical Model for Multiscale Spatial Data

description: Spatial boundary analysis has attained considerable attention in several disciplines including engineering, shape analysis, spatial statistics, and computer science. The inferential question of interest is often to identify rapid surface change of an unobserved latent process. Curvilinear wombling and crisp wombling (or fuzzy) are two major approaches that have emerged in Bayesian spatial statistics literature. These methods are limited to a single spatial scale even though data with multiple spatial scales are often accessible. Thus, we propose a multiscale representation of the directional derivative Karhunen–Loéve expansion to perform directionally based boundary detection. Taking a multiscale spatial perspective allows us, for the first time, to consider the concept of curvilinear boundary fallacy (CBF) error, which is a boundary detection analog to the ecological fallacy that is often studied in spatial change of support literature. Furthermore, we propose a directionally based multiscale curvilinear boundary error criterion to quantify CBF. We refer to this metric as the criterion for boundary aggregation error (BAGE), and use it to perform boundary detection. Several theoretical results are derived to motivate BAGE. In particular, we show that no BAGE exists when the directional derivatives of eigenfunctions of a KL expansion are constant across spatial scales. We illustrate the use of our model through a simulated example and an analysis of Mediterranean wind measurements data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9956288.v1
title: Xerophyta humilis representative sequences

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br><br>Representative transcripts: representative sequence for each gene cluster (the transcript with the longest CDS, or longest transcript if no CDS was found). Representative proteins: coding sequences of the best ORF for each representative transcript.
DOI: 10.6084/m9.figshare.9956264.v1
title: Xerophyta humilis raw transcriptome

description: Dataset for the article <i>Vegetative desiccation tolerance in the resurrection plant Xerophyta humilis has not evolved through reactivation of the seed canonical LAFL regulatory network.</i><br>Raw transcripts from Trinity de novo assembly of combined seed and leaf <i>Xerophyta humilis</i> samples. Transcript IDs are the Trinity transcript ID followed by the unique gene cluster ID if one is present (example: TRINITY_DN164427_c0_g1_i1|Xh025390c1). Gene cluster IDs denote sets of transcripts that passed RapClust filtering and mapped uniquely to the same genomic locus on the draft <i>Xerophyta humilis </i>genome (and thus represent putative isoforms or fragments of the same gene).
DOI: 10.6084/m9.figshare.9956273.v1
title: Boundary Detection using a Bayesian Hierarchical Model for Multiscale Spatial Data

description: Spatial boundary analysis has attained considerable attention in several disciplines including engineering, shape analysis, spatial statistics, and computer science. The inferential question of interest is often to identify rapid surface change of an unobserved latent process. Curvilinear wombling and crisp wombling (or fuzzy) are two major approaches that have emerged in Bayesian spatial statistics literature. These methods are limited to a single spatial scale even though data with multiple spatial scales are often accessible. Thus, we propose a multiscale representation of the directional derivative Karhunen-Loéve (DDKL) expansion to perform directionally based boundary detection. Taking a multiscale spatial perspective allows us, for the first time, to consider the concept of curvilinear boundary fallacy (CBF) error, which is a boundary detection analog to the ecological fallacy that is often studied in spatial change of support (COS) literature. Furthermore, we propose a directionally based multiscale curvilinear boundary error criterion to quantify CBF. We refer to this metric as the criterion for boundary aggregation error (BAGE), and use it to perform boundary detection. Several theoretical results are derived to motivate BAGE. In particular, we show that no boundary aggregation error exists when the directional derivatives of eigenfunctions of a KL expansion are constant across spatial scales. We illustrate the use of our model through a simulated example and an analysis of Mediterranean wind measurements data. Supplementary materials of this article are available online.
DOI: 10.6084/m9.figshare.9956195
title: High-Dimensional Smoothing Splines and Application in Alzheimer’s Disease Prediction Using Magnetic Resonance Imaging

description: Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer’s disease (AD) prediction. While traditional MRI-based prediction uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main statistical difficulties arise in the longitudinal MRI-based analysis: (i) the inconsistent longitudinal scans among subjects (i.e., the different scanning time and the different total number of scans); (ii) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a new feature selection and estimation method which can be applied to extract AD-related features from the heterogeneous longitudinal MRI. A key ingredient of our approach is a hybrid of the smoothing splines and the <i>l</i><sub>1</sub>-penalty. Smoothing splines can integrate information from heterogeneous progressions of ROIs and adapt to inconsistent scans of MRIs. The selection property of the <i>l</i><sub>1</sub>-penalty helps to select important ROIs related to AD. We introduce an efficient algorithm to perform the proposed method. Real data experiments on the Alzheimer’s Disease Neuroimaging Initiative database are provided to corroborate some advantages of the proposed method for AD prediction in longitudinal studies.
DOI: 10.6084/m9.figshare.9956186
title: Anais da VIII Semana do Administrador - Universidade de Pernambuco, Campus Sagueiro

description: Anais da VIII Semana do Administrador - Universidade de Pernambuco, Campus Sagueiro.
DOI: 10.6084/m9.figshare.9956192
title: Interim Monitoring for Futility in Clinical Trials With Two Co-Primary Endpoints Using Prediction

description: We discuss using prediction as a flexible and practical approach for monitoring futility in clinical trials with two co-primary endpoints (CPE). This approach is appealing in that it provides quantitative evaluation of potential effect sizes and associated precision, and can be combined with flexible error-spending strategies. We extend prediction of effect size estimates and the construction of predicted intervals to the two CPE case, and illustrate interim futility monitoring of treatment effects using prediction with an example. We also discuss alternative approaches based on the conditional and predictive powers, compare these methods and provide some guidance on the use of prediction for better decision in clinical trials with CPE.
DOI: 10.6084/m9.figshare.9956192.v2
title: Interim Monitoring for Futility in Clinical Trials With Two Co-Primary Endpoints Using Prediction

description: We discuss using prediction as a flexible and practical approach for monitoring futility in clinical trials with two co-primary endpoints (CPE). This approach is appealing in that it provides quantitative evaluation of potential effect sizes and associated precision, and can be combined with flexible error-spending strategies. We extend prediction of effect size estimates and the construction of predicted intervals to the two CPE case, and illustrate interim futility monitoring of treatment effects using prediction with an example. We also discuss alternative approaches based on the conditional and predictive powers, compare these methods and provide some guidance on the use of prediction for better decision in clinical trials with CPE.
DOI: 10.6084/m9.figshare.9956063
title: CLO_EAlp_1.0_BUSCO.tar.gz

description: Output from BUSCO analyses of vertebrata and aves data sets.
DOI: 10.6084/m9.figshare.9956195.v1
title: Alzheimer’s Disease Prediction Using Longitudinal and Heterogeneous Magnetic Resonance Imaging

description: Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer’s disease (AD) prediction. While traditional MRI-based prediction uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main statistical difficulties arise in the longitudinal MRI-based analysis: (i) the inconsistent longitudinal scans among subjects (i.e., the different scanning time and the different total number of scans); (ii) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a new feature selection and estimation method which can be applied to extract AD-related features from the heterogeneous longitudinal MRI. A key ingredient of our approach is a hybrid of the smoothing splines and the <i>l</i><sub>1</sub>-penalty. Smoothing splines can integrate information from heterogeneous progressions of ROIs and adapt to inconsistent scans of MRIs. The selection property of the <i>l</i><sub>1</sub>-penalty helps to select important ROIs related to AD. We introduce an efficient algorithm to perform the proposed method. Real data experiments on the Alzheimer’s Disease Neuroimaging Initiative database are provided to corroborate some advantages of the proposed method for AD prediction in longitudinal studies.
DOI: 10.6084/m9.figshare.9956063.v1
title: CLO_EAlp_1.0_BUSCO.tar.gz

description: Output from BUSCO analyses of vertebrata and aves data sets.
DOI: 10.6084/m9.figshare.9956192.v1
title: Interim Monitoring for Futility in Clinical Trials with Two Co-primary Endpoints Using Prediction

description: We discuss using prediction as a flexible and practical approach for monitoring futility in clinical trials with two co-primary endpoints. This approach is appealing in that it provides quantitative evaluation of potential effect sizes and associated precision, and can be combined with flexible error-spending strategies. We extend prediction of effect size estimates and the construction of predicted intervals to the two co-primary endpoints case, and illustrate interim futility monitoring of treatment effects using prediction with an example. We also discuss alternative approaches based on the conditional and predictive powers, compare these methods and provide some guidance on the use of prediction for better decision in clinical trials with co-primary endpoints.
DOI: 10.6084/m9.figshare.9956042
title: CLO_EAlp_1.0_quast.tar.gz

description: Output from QUAST genome contiguity assessment.
DOI: 10.6084/m9.figshare.9955838
title: Tables-Supplemental.xlsx

description: Supplemental Tables for "Neonatal Macrosomia is an Interfering Factor for Analytes on the Colorado State Newborn Screen"
DOI: 10.6084/m9.figshare.9956042.v1
title: CLO_EAlp_1.0_quast.tar.gz

description: Output from QUAST genome contiguity assessment.
DOI: 10.6084/m9.figshare.9955535
title: Data Availability - Numerical Frequency Transfer Function Analysis of a Leaky Integrate-and-Fire Neuron

description: <pre>The data sets generated during and or analyzed in the article: Numerical Frequency Transfer Function Analysis of a Leaky Integrate-and-Fire Neuron</pre>
DOI: 10.6084/m9.figshare.9955838.v1
title: Tables-Supplemental.xlsx

description: Supplemental Tables for "Neonatal Macrosomia is an Interfering Factor for Analytes on the Colorado State Newborn Screen"
DOI: 10.6084/m9.figshare.9955268
title: raw data for "Clinical impact of intraoperative hyperlactatemia during craniotomy"

description: raw data for tables 1-4 and figure 1 in PONE-D-19-23758 PLOS ONE article "Clinical impact of intraoperative hyperlactatemia during craniotomy"
DOI: 10.6084/m9.figshare.9955211
title: Consensus sequences for S.suis project

description: Using nanopore sequencing, we generated S.suis whole genome (files: minion*.fasta) and performed AMR and MLST analysis.We also generated assemblies (files: illumina*.fasta) using Illumina sequencing reads. And hybrid assemblies (files: hybrid*.fasta) were performed using nanopore reads and Illumina reads.
DOI: 10.6084/m9.figshare.9955211.v1
title: Consensus sequences for S.suis project

description: Using nanopore sequencing, we generated S.suis whole genome (files: minion*.fasta) and performed AMR and MLST analysis.We also generated assemblies (files: illumina*.fasta) using Illumina sequencing reads. And hybrid assemblies (files: hybrid*.fasta) were performed using nanopore reads and Illumina reads.
DOI: 10.6084/m9.figshare.9955187
title: PhenoRipper Models and Profiles

description: There are 5 zip files: one each for the PhenoRipper models for 4 marker sets and one the profiles for all marker sets. After unzipping the contents of these zip files, please copy all .mat files into a folder called PR_Results at the root of your dataset folder.<br>
DOI: 10.5281/zenodo.4001602
title: Python Annotated Code Search (PACS) Datasets & Pretrained Models

description: This upload contains datasets and pre-trained models used for the paper <em>Neural Code Search Revisited: Enhancing Code Snippet Retrieval through Natural Language Intent. </em>The code for easily loading these datasets and models will be made available here: http://github.com/nokia/codesearch <strong>Datasets</strong><br> There are three types of datasets: snippet collections (code snippets + natural language descriptions): so-ds-feb20, staqc-py-cleaned, conala-curated code search evaluation data (queries linked to relevant snippets of one of the snippet collections): so-ds-feb20-{valid|test}, staqc-py-raw-{valid|test}, conala-curated-0.5-test training data (datasets used to train code retrieval models): so-duplicates-pacs-train, so-python-question-titles-feb20 The staqc-py-cleaned snippet collection, and the conala-curated datasets were derived from existing corpora: staqc-py-cleaned was derived from the Python StaQC snippet collection. See https://github.com/LittleYUYU/StackOverflow-Question-Code-Dataset, LICENSE. conala-curated was derived from the conala corpus. See https://conala-corpus.github.io/ , LICENSE The other datasets were mined directly from a recent Stack Overflow dump (https://archive.org/details/stackexchange, LICENSE). <br> <br> <strong>Pre-trained models</strong><br> Each model can embed queries and (annotated) code snippets in the same space. The models are released under a BSD 3-Clause License. ncs-embedder-so-ds-feb20 ncs-embedder-staqc-py tnbow-embedder-so-ds-feb20 use-embedder-pacs ensemble-embedder-pacs