cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5831976
title: Rainfall data Senegal (1997-2016)

description: Rainfall data aggregated by Department in Senegal (1997-2016).Data were originally downloaded from Seasonal Explorer (http://dataviz.vam.wfp.org/seasonal_explorer/rainfall_vegetation/visualizations).
DOI: 10.6084/m9.figshare.5831976.v1
title: Rainfall data Senegal (1997-2016)

description: Rainfall data aggregated by Department in Senegal (1997-2016).Data were originally downloaded from Seasonal Explorer (http://dataviz.vam.wfp.org/seasonal_explorer/rainfall_vegetation/visualizations).
DOI: 10.6084/m9.figshare.5831931
title: SCRstatistics.R

description: A .R open source script that allows to extract descriptive statistics from the database multisensory_emotions_R.rda
DOI: 10.6084/m9.figshare.5831898
title: multisensory_emotions_R

description: We test stimuli delivered either through a visual, auditory, or haptic modality in a within participant experimental design. We provide the results of our study in the form of a .rda list.
DOI: 10.6084/m9.figshare.5831682
title: Woods et al_recruitment data

description: Responses to playback experiments<br>
DOI: 10.6084/m9.figshare.5831682.v1
title: Woods et al_recruitment data

description: Responses to playback experiments<br>
DOI: 10.6084/m9.figshare.5831538
title: DFT studies on the base-facilitated direct coupling of carbon dioxide with 2,2-dimethyl-1,3-propanediol

description: DFT calculations to support the article 'Synthesis of 5-to 8- membered cyclic carbonates from diols and CO<sub>2</sub>: a one-step, atmospheric pressure and ambient temperature procedure'<br>DFT study comprises:-DFT optimised geometries and computed enthalpies were used to calculate the thermodynamics and kinetics of the carbonation of 2,2-dimethyl-1,3-propanediol's alcohol moiety facilitated by NEt<sub>3</sub>, TMP, pyridine and DBU into the hydroxyl via a ternary Lewis base-CO<sub>2</sub>-diol mechanism. -DFT optimised geometries and computed enthalpies were used to calculate the thermodynamics and kinetics of the cyclisation of 4,4-dimethyl-7-oxo-7-(tosyloxy)heptanoate (BCI) to form 5,5-dimethyl-1,3-dioxan-2-one.-DFT optimised geometries and computed enthalpies were used to calculate the thermodynamics and kinetics of the NEt3-facilitated direct coupling of CO<sub>2</sub> with 2,2-dimethyl-1,3-propanediol to form 5,5-dimethyl-1,3-dioxan-2-one via three competitive mechanistic pathways. <br>Protocol:rωb97xD/6-31+g(d)/cpcm=acetonitrile/298K <br>Content:-Gaussian09 rev D.01 output files-CO2_insertion_comparison.pdf, illustrating the calculations made and summarising the enthalpies computed for NEt<sub>3</sub>, TMP, pyridine and DBU into the hydroxyl group of 2,2-dimethyl-1,3-propanediol via a ternary Lewis base-CO<sub>2</sub>-diol mechanism. -BCI_cyclisation.pdf, illustrating the calculations made and summarising the enthalpies computed for the cyclisation of BCI to form 5,5-dimethyl-1,3-dioxan-2-one- NEt3_mechanism, illustrating the calculations made and summarising the enthalpies computed for the direct coupling of CO<sub>2</sub> with 2,2-dimethyl-1,3-propanediol to form 5,5-dimethyl-1,3-dioxan-2-one via three competitive mechanistic pathways.<br>
DOI: 10.6084/m9.figshare.5831463
title: Wear reconstruction of the teeth of <i>Yindirtemys deflexus</i> (Ctenodactylidae, Rodentia) and evolution of its dental pattern

description: The dental pattern of <i>Yindirtemys deflexus</i> from Mongolia has been analysed using a Micro-CT scanner. This ctenodactylid exhibits a peculiar dental pattern, characterised by a mesodont dentition with some degree of selenodonty, an intricate enamel folding and elevated connections between cusps. Furthermore, the wear sequence in the upper tooth row shows very worn M1 even before other teeth emerge. The descriptive parameters used in the analyses (Area, Perimeter and structural density) allowed us to determine the relative wear stage in the different dental elements. The study reveals for <i>Yindirtemys deflexus</i> a wear pattern typical of mesodont teeth in which the maximum perimeter of the enamel is relatively constant over a large part of the crown height, and the Structural density decreases progressively until the senescence of the tooth. This peculiar dental morphology and eruption sequence of <i>Y. deflexus</i> is interpreted as the result of the evolution towards a relatively more durable dentition caused by the adaptation to more arid environments.
DOI: 10.6084/m9.figshare.5831463.v1
title: Wear reconstruction of the teeth of <i>Yindirtemys deflexus</i> (Ctenodactylidae, Rodentia) and evolution of its dental pattern

description: The dental pattern of <i>Yindirtemys deflexus</i> from Mongolia has been analysed using a Micro-CT scanner. This ctenodactylid exhibits a peculiar dental pattern, characterised by a mesodont dentition with some degree of selenodonty, an intricate enamel folding and elevated connections between cusps. Furthermore, the wear sequence in the upper tooth row shows very worn M1 even before other teeth emerge. The descriptive parameters used in the analyses (Area, Perimeter and structural density) allowed us to determine the relative wear stage in the different dental elements. The study reveals for <i>Yindirtemys deflexus</i> a wear pattern typical of mesodont teeth in which the maximum perimeter of the enamel is relatively constant over a large part of the crown height, and the Structural density decreases progressively until the senescence of the tooth. This peculiar dental morphology and eruption sequence of <i>Y. deflexus</i> is interpreted as the result of the evolution towards a relatively more durable dentition caused by the adaptation to more arid environments.
DOI: 10.6084/m9.figshare.5831454
title: Matlab file for Riccati RDE solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831445
title: Matlab file for Riccati generalized NLS solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831445.v1
title: Matlab file for Riccati generalized NLS solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831442
title: Matlab file for Riccati RDE solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831442.v1
title: Matlab file for Riccati RDE solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831436
title: Matlab file for Riccati KdV solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831436.v1
title: Matlab file for Riccati KdV solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.5831433
title: Matlab file for Riccati NLS solution from Partial differential systems with non-local nonlinearities: generation and solutions

description: We develop a method for generating solutions to large classes of evolutionary partial differential systems with non-local nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations. The key is a Fredholm integral equation relating the linearized flow to an auxiliary linear flow. It is analogous to the Marchenko integral equation in integrable systems. We show explicitly how this can be achieved through several examples including reaction–diffusion systems with non-local quadratic nonlinearities and the nonlinear Schrödinger equation with a non-local cubic nonlinearity. In each case, we demonstrate our approach with numerical simulations. We discuss the effectiveness of our approach and how it might be extended. This article is part of the theme issue ‘Stability of nonlinear waves and patterns and related topics’.
DOI: 10.6084/m9.figshare.13120657.v1
title: Additional file 2 of Haematological and serum biochemical reference values in Chinese water deer (Hydropotes inermis): a preliminary study

description: Additional file 2. The parameter values of other animals from literatures in the discussion.
DOI: 10.6084/m9.figshare.12072366.v1
title: Additional file 1 of A pan-cancer study of class-3 semaphorins as therapeutic targets in cancer

description: Additional file 1: This is an MS Excel file containing the compiled TCGA data used for this study.
DOI: 10.6084/m9.figshare.12072375
title: Additional file 2 of A pan-cancer study of class-3 semaphorins as therapeutic targets in cancer

description: Additional file 2: This is an MS Excel file containing the SEMA3 gene expression and drug sensitivity score derived from NCI60 cell line study.
DOI: 10.6084/m9.figshare.13120734
title: Additional file 12 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 12: Table S2–1. The differentially expressed genes (DEGs) identified in the comparison of PR403_CK22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–2. The differentially expressed genes (DEGs) identified in the comparison of PR403_CK20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–3. The differentially expressed genes (DEGs) identified in the comparison of PY6_CK22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–4. The differentially expressed genes (DEGs) identified in the comparison of PY6_CK20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–5. The development dependent DEGs identified in the comparison of PR403_CK22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–6 The development dependent DEGs identified in the comparison of PR403_CK20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–7. The development dependent DEGs identified in the comparison of PY6_CK22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–8. The development dependent DEGs identified in the comparison of PY6_CK20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–9. The differentially expressed genes (DEGs) identified in the comparison of PR403_22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–10. The differentially expressed genes (DEGs) identified in the comparison of PR403_20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–11. The differentially expressed genes (DEGs) identified in the comparison of PY6_22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–12. The differentially expressed genes (DEGs) identified in the comparison of PY6_20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05).
DOI: 10.6084/m9.figshare.13120734.v1
title: Additional file 12 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 12: Table S2–1. The differentially expressed genes (DEGs) identified in the comparison of PR403_CK22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–2. The differentially expressed genes (DEGs) identified in the comparison of PR403_CK20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–3. The differentially expressed genes (DEGs) identified in the comparison of PY6_CK22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–4. The differentially expressed genes (DEGs) identified in the comparison of PY6_CK20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–5. The development dependent DEGs identified in the comparison of PR403_CK22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–6 The development dependent DEGs identified in the comparison of PR403_CK20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–7. The development dependent DEGs identified in the comparison of PY6_CK22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–8. The development dependent DEGs identified in the comparison of PY6_CK20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–9. The differentially expressed genes (DEGs) identified in the comparison of PR403_22vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–10. The differentially expressed genes (DEGs) identified in the comparison of PR403_20vsPR403_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–11. The differentially expressed genes (DEGs) identified in the comparison of PY6_22vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05). Table S2–12. The differentially expressed genes (DEGs) identified in the comparison of PY6_20vsPY6_CK40 (log2FC ≥ 1 and padj ≤ 0.05).
DOI: 10.6084/m9.figshare.13120740
title: Additional file 14 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 14: Table S4. Differentially expressed hub genes identified in module brown.
DOI: 10.6084/m9.figshare.13120747
title: Additional file 8 of Comprehensive transcriptomic analysis provides new insights into the mechanism of ray floret morphogenesis in chrysanthemum

description: Additional file 8 Table S3. The DEGs encoding transcription factors with a ten-fold or more difference in FPKM.
DOI: 10.6084/m9.figshare.25145827
title: Supplementary Data 8 from Tip dating and Bayes factors provide insight into the divergences of crown bird clades across the End-Cretaceous mass extinction

description: Analysis File with J&P age priors and Asteriornis constrained to stem Galloanserae
DOI: 10.6084/m9.figshare.25145830
title: Supplementary Data 4 from Tip dating and Bayes factors provide insight into the divergences of crown bird clades across the End-Cretaceous mass extinction

description: Analysis File with Jarvis age priors and Asteriornis constrained to stem Galloanserae
DOI: 10.6084/m9.figshare.13120737.v1
title: Additional file 13 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 13: Table S3–1. Hub genes list of module black. Table S3–2. Hub genes list of module blue. Table S3–3. Hub genes list of module grey60. Table S3–4. Hub genes list of module green. Table S3–5. Hub genes list of module red. Table S3–6. Hub genes list of module brown. Table S3–7. Hub genes list of module royalblue.
DOI: 10.6084/m9.figshare.25145833.v1
title: Supplementary Data 2 from Tip dating and Bayes factors provide insight into the divergences of crown bird clades across the End-Cretaceous mass extinction

description: Analysis File with Brown age priors and Asteriornis constrained to stem Galloanserae
DOI: 10.6084/m9.figshare.13120737
title: Additional file 13 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 13: Table S3–1. Hub genes list of module black. Table S3–2. Hub genes list of module blue. Table S3–3. Hub genes list of module grey60. Table S3–4. Hub genes list of module green. Table S3–5. Hub genes list of module red. Table S3–6. Hub genes list of module brown. Table S3–7. Hub genes list of module royalblue.
DOI: 10.6084/m9.figshare.13120740.v1
title: Additional file 14 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 14: Table S4. Differentially expressed hub genes identified in module brown.
DOI: 10.6084/m9.figshare.23606864.v1
title: Additional file 4 of Calcium/calmodulin dependent protein kinase IV in trophoblast cells under insulin resistance: functional and metabolomic analyses

description: Additional file 4. The primary DEMs analysis in negative ion mode.
DOI: 10.6084/m9.figshare.13120741.v1
title: Additional file 6 of Comprehensive transcriptomic analysis provides new insights into the mechanism of ray floret morphogenesis in chrysanthemum

description: Additional file 6: Table S2. Differential expression information and annotation of DEGs in the Venn analysis.
DOI: 10.6084/m9.figshare.13120720
title: Additional file 11 of Comprehensive transcriptomic analysis provides new insights into the mechanism of ray floret morphogenesis in chrysanthemum

description: Additional file 11: Table S5. Primer sequences used in RT-PCR experiments.
DOI: 10.6084/m9.figshare.23606728
title: Additional file 2 of Microbiome and tryptophan metabolomics analysis in adolescent depression: roles of the gut microbiota in the regulation of tryptophan-derived neurotransmitters and behaviors in human and mice

description: Additional file 2.
DOI: 10.6084/m9.figshare.13120743
title: Additional file 15 of Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

description: Additional file 15: Table S5–1. GO enrichment result of module black. Table S5–2. GO enrichment result of module blue. Table S5–3. GO enrichment result of module grey60. Table S5–4. GO enrichment result of module green. Table S5–5. GO enrichment result of module red. Table S5–6. GO enrichment result of module brown. Table S5–7. GO enrichment result of module royalblue. Table S5–8 GO enrichment result of PR403 22 vs PR403 CK40. Table S5–9. GO enrichment result of PR403 20 vs PR403 CK40. Table S5–10. GO enrichment result of PY6 22 vs PY6 CK40. Table S5–11. GO enrichment result of PY6 20 vs PY6 CK40.
DOI: 10.6084/m9.figshare.13120828.v1
title: Additional file 1 of SNP barcodes provide higher resolution than microsatellite markers to measure Plasmodium vivax population genetics

description: Additional file 1: Table S1. Details of 40 P. vivax isolates from PNG sequenced and used for SNP candidate selection.
DOI: 10.6084/m9.figshare.12072330
title: Additional file 2 of Pseudogene-gene functional networks are prognostic of patient survival in breast cancer

description: Additional file 2. This file contains the p-values for univariate cox proportional hazard models on each of the genes from our model in the Swedish cohort. The test was performed on multiple subsets of patients including age and breast cancer subtype using median expression as the cutoff.