cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13669491
title: Additional file 5 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 5. Table of PATRIC PLFams specific to SGAir0260 & SGAir0263 strains. List of strain specific (SGAir0260 and SGAir0263) PLFams detected in PATRIC analysis.
DOI: 10.6084/m9.figshare.13669491.v1
title: Additional file 5 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 5. Table of PATRIC PLFams specific to SGAir0260 & SGAir0263 strains. List of strain specific (SGAir0260 and SGAir0263) PLFams detected in PATRIC analysis.
DOI: 10.6084/m9.figshare.13669479.v1
title: Additional file 1 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 1. Table of PATRIC Codon Tree Statistics. PATRIC’s codon tree analysis statistics for SGAir0260 and SGAir0263 strains.
DOI: 10.6084/m9.figshare.13669503.v1
title: Additional file 9 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 9. Table of 55 NCBI Complete Genome Assembly Stats and PATRIC Annotation. The complete list of genomes downloaded from NCBI and their accession numbers with PATRIC annotations.
DOI: 10.6084/m9.figshare.13669500.v1
title: Additional file 8 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 8. Table(s) of Non-gene pairs, specific to NCBI Reference Strain ATCC 14579 and SGAir strains, SGAir0260 and SGAir0263. The list of CDS not found in macrosyntenic analysis gene pairs for strains ATCC 14579, SGAir0260, and SGAir0263, including location along each contig. Includes annotation of genes found in strain ATCC 14579 for region involved in rearrangement.
DOI: 10.6084/m9.figshare.13669503
title: Additional file 9 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 9. Table of 55 NCBI Complete Genome Assembly Stats and PATRIC Annotation. The complete list of genomes downloaded from NCBI and their accession numbers with PATRIC annotations.
DOI: 10.6084/m9.figshare.13669500
title: Additional file 8 of The genomic characterisation and comparison of Bacillus cereus strains isolated from indoor air

description: Additional file 8. Table(s) of Non-gene pairs, specific to NCBI Reference Strain ATCC 14579 and SGAir strains, SGAir0260 and SGAir0263. The list of CDS not found in macrosyntenic analysis gene pairs for strains ATCC 14579, SGAir0260, and SGAir0263, including location along each contig. Includes annotation of genes found in strain ATCC 14579 for region involved in rearrangement.
DOI: 10.6084/m9.figshare.13669530
title: Additional file 2 of Impacts of fludioxonil resistance on global gene expression in the necrotrophic fungal plant pathogen Sclerotinia sclerotiorum

description: Additional file 2: Table S1.
DOI: 10.6084/m9.figshare.13669530.v1
title: Additional file 2 of Impacts of fludioxonil resistance on global gene expression in the necrotrophic fungal plant pathogen Sclerotinia sclerotiorum

description: Additional file 2: Table S1.
DOI: 10.6084/m9.figshare.13669569.v1
title: Additional file 1 of Are there subgroups of chronic fatigue syndrome? An exploratory cluster analysis of biological markers

description: Additional file 1. Initial correlation analyses of all variables considered for hierarchical cluster analysis.
DOI: 10.6084/m9.figshare.13669569
title: Additional file 1 of Are there subgroups of chronic fatigue syndrome? An exploratory cluster analysis of biological markers

description: Additional file 1. Initial correlation analyses of all variables considered for hierarchical cluster analysis.
DOI: 10.5281/zenodo.4480400
title: Data for taxonomic analysis

description: The data included in this repository was used for the taxonomic analysis. (1) silva-138-99-nb-classifier.qza: The classifier was used for analysis in qiime 2 (2020.8 core distribution) (2) ref_prok_rep_genomes: Metagenome data for blast+ queries (updates, 2020-06-19; accessed on July 15, 2020). (3) NCBI_taxdump.zip: Taxa dump data for lineage extractions.
DOI: 10.5281/zenodo.4480399
title: Data for taxonomic analysis

description: The data included in this repository was used for the taxonomic analysis. (1) silva-138-99-nb-classifier.qza: The classifier was used for analysis in qiime 2 (2020.8 core distribution) (2) ref_prok_rep_genomes: Metagenome data for blast+ queries (updates, 2020-06-19; accessed on July 15, 2020). (3) NCBI_taxdump.zip: Taxa dump data for lineage extractions.
DOI: 10.6084/m9.figshare.13669256
title: ESM_3

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669256.v2
title: ESM_3

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669256.v1
title: ESM_3

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669259
title: ESM_4

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669259.v2
title: ESM_4

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669259.v1
title: ESM_4

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669262
title: ESM_5

description: measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669262.v2
title: ESM_5

description: measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669262.v1
title: ESM_5

description: measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669265
title: ESM_6

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669265.v2
title: ESM_6

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669265.v1
title: ESM_6

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669268
title: ESM_7

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669268.v2
title: ESM_7

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669268.v1
title: ESM_7

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669271
title: ESM_8

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669271.v2
title: ESM_8

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.6084/m9.figshare.13669271.v1
title: ESM_8

description: An R script to calculate LD50s with 95% CLs, judge the significance between two LD50s, and measure parallelism of response –log(dose) lines using probit/logit-log(dose) model.
DOI: 10.15784/601430
title: SPICEcore 400-480 m Major Ions SDSU

description: Major ion concentrations in SPICEcore samples from the section of 400-480 m were measured with ion chromatography. The ions are chloride, nitrate, sulfate, sodium, potassium, magnesium, and calcium. This section was analyzed to replicate the measurement of the same section at Dartmouth College.
DOI: 10.5281/zenodo.4482969
title: Supplementary Appendix 1b of "Toward a geography of community health workers in Niger: a geospatial analysis"

description: Supplementary Appendix 1b contains Supplementary Appendices 2-6, Videos 1-2, and all output datasets at 100m resolution and 1000m resolution for the research article "Toward a geography of community health workers in Niger: a geospatial analysis" by Nicholas P. Oliphant, Nicolas Ray, Khaled Bensaid, Adama Ouedraogo, Asma Yaroh Gali, Oumarou Habi, Ibrahim Maazou, Rocco Panciera, Maria Muñiz, Zeynabu Sy, Debra Jackson, and Tanya Doherty. Files are available under the Creative Commons Attribution 4.0 International License. Tab "Readme" in the file "Supplementary Appendix 1b - Metadata" contains a description of all datasets contained in Supplementary Appendix 1b.
DOI: 10.25345/c5sf6d
title: MassIVE MSV000086783 - GNPS-Ganoderma Lucidum Karst-G1-G14-Mass Spectrometry data
title: The file contains Mass Spectrometry data of 13 species of the Ganoderma gene. The sample were collected from China in 2019, and identified by Prof. Yu-Cheng Dai on the basis of morphological characteristics.
DOI: 10.6084/m9.figshare.13669733
title: WibBondIndexData.zip

description: This dataset is released in conjunction with the paper “Bond Order Predictions Using Deep Neural Networks." The dataset consists of 436,938 ordinary organic molecules, their geometries, and bond orders assigned by the NBO and Gaussian software packages, both of which are licensed to Los Alamos National Laboratory. This dataset is useful for training neural networks, specifically HIPPYNN which has been released through the Feynman Center for Innovation. The trained neural network can make accurate predictions of bond orders on organic and biological molecules significantly faster than the quantum mechanical methods the neural networks are based on. These neural networks are of relevance to basic research into biological molecules, where bonding information is used to parameterize classical force fields for molecular dynamics simulations. <br>
DOI: 10.6084/m9.figshare.13669733.v1
title: WibBondIndexData.zip

description: This dataset is released in conjunction with the paper “Bond Order Predictions Using Deep Neural Networks." The dataset consists of 436,938 ordinary organic molecules, their geometries, and bond orders assigned by the NBO and Gaussian software packages, both of which are licensed to Los Alamos National Laboratory. This dataset is useful for training neural networks, specifically HIPPYNN which has been released through the Feynman Center for Innovation. The trained neural network can make accurate predictions of bond orders on organic and biological molecules significantly faster than the quantum mechanical methods the neural networks are based on. These neural networks are of relevance to basic research into biological molecules, where bonding information is used to parameterize classical force fields for molecular dynamics simulations. <br>
DOI: 10.6084/m9.figshare.13621169.v10
title: Speedtest Open Data - Four International cities - MEL, BKK, SHG, LAX

description: This dataset compares four cities broadband internet speeds:- Melbourne, AU- Bangkok, TH- Shanghai, CN- Los Angeles, US<br>ERRATA:1.Data is for Q3 2020, but some files are labelled incorrectly as 02-20 of June 20. They all should read Sept 20, or 09-20 as Q3 20, rather than Q2. Will rename and reload.Amended in v7.<br>2. LAX file named 0320, when should be Q320.Amended in v8.<br><br>*lines of data for each geojson file; a line equates to a 600m^2 location, inc total tests, devices used, and average upload and download speed- MEL 16181 lines- SHG 31745 lines- BKK 29296 lines- LAX 15899 lines<br>Geojsons of these 2* by 2* extracts for MEL, BKK, SHG now added, and LAX added v6..<br>This dataset unpacks, geospatially, data summaries provided in Speedtest Global Index (linked below). See Jupyter Notebook (*.ipynb) to interrogate geo data. See link to install Jupyter.<br>** To DoWill add Google Map versions so everyone can see without installing Jupyter.- Link to Google Map (BKK) added below. Key:Green &gt; 100Mbps(Superfast). Black &gt; 500Mbps (Ultrafast). CSV provided. Code in Speedtestv1.1.ipynb Jupyter Notebook.<br>** Pythonmelb = au_tiles.cx[144:146 , -39:-37] #Lat/Lon extract<br>shg = tiles.cx[120:122 , 30:32] #Lat/Lon extract<br>bkk = tiles.cx[100:102 , 13:15] #Lat/Lon extract<br>lax = tiles.cx[-118:-120, 33:35] #lat/Lon<br>Histograms, and data visualisations will be provided.Data Sourced from - This is an extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>**VERSIONSv10 Add Four Histograms in one pic.v9 Add Histogram for Four Cities. Add NBN-Intl.v1.1.ipynb (Jupyter Notebook).v8 Renamed LAX file to Q3, rather than 03.v7 Amended file names of BKK files to correctly label as Q3, not Q2 or 06.v6 Added LAX file.v5 Add screenshot of BKK Google Map.v4 Add BKK Google map(link below), and BKK csv mapping files. v3 replaced MEL map with big key version. Prev key was very tiny in top right corner.v2 Uploaded MEL, SHG, BKK data and Jupyter Notebookv1 Metadata record<br>** LICENCEAWS data licence on Speedtest data is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>** Other uses of Speedtest Open Data;- see link at Speedtest below.<br>
DOI: 10.6084/m9.figshare.13643483
title: Data.csv

description: Contains movie rating, volume of rating of Indian movies released in India between 2010 and 2019
DOI: 10.6084/m9.figshare.13643483.v1
title: Data.csv

description: Contains movie rating, volume of rating of Indian movies released in India between 2010 and 2019
DOI: 10.14457/cu.the.1998.130
title: ความรู้ เจตคติ และทักษะการรับรู้เชิงจริยธรรมในนิสิตแพทย์ คณะแพทยศาสตร์ จุฬาลงกรณ์มหาวิทยาลัย
DOI: 10.26255/heal.9fbs-ubaq
title: Test dataset 21
DOI: 10.20392/91f05bb6-5ddc-4121-ae02-8a2f6a3dc47a
title: Late Medieval Landscape in North-east Scotland data files

description: Data files relating to the book 'The Late Medieval Landscape in North-east Scotland; Renaissance, Reformation, Revolution'
description: Spreadsheets and SPSS output
DOI: 10.14457/cu.the.2016.164
title: Poisson approximation for call function via Stein-Chen’s method

description: A call function is a nonnegative real-valued function defined by hz(v) = (v−z)+ for z " 0 where (v − z)+ = max{v − z, 0}. There are many applications of call function in finance. For example, the standard collateralized debt obligation tranche pricing. In this work, we give bounds of Poisson approximation for hz(V ) where V is a sum of independent nonnegative integer-valued random variables. The technique used is Stein-Chen’s method with the zero bias transformation. Moreover, in case that V is a sum of independent Bernoulli random variables, we improve the bounds of Poisson approximation for hz(V ) by adding some correction terms.
DOI: 10.14457/cu.the.2016.165
title: Gradient directional second derivative PEH CT number correction and soft tissue preservation for Electronic cleansing in CTC images

description: This dissertation proposes two electronic cleansing (EC) methods in Computed Tomography Colonography. These methods can solve the problems in EC which are the artifact partial volume effect at an AT layer, pseudo-enhancement (PEH) effect, the ambiguity between AT and ATT layers, and the artifacts at T-junctions. The first proposed EC method removes fecal-tagging material (FTM) using a simple thresholding method after applying the gradient directional second derivative (GDSD) PEH correction method to solve the PEH effect and the modified local roughness to separate AT layers from ATT layers. The second proposed EC method integrates GDSD into material fraction model to preserve PEH soft- tissue voxels and remove FTM and artifacts at AT layers and T-junctions. AT layers can be distinguished from ATT layers using the AT layer identification to preserve ATT layers. The results from clinical evaluation by the radiologist show reliability and improvement of the proposed method when comparing with the existing method and commercial software.
DOI: 10.14457/cu.the.2016.166
title: Non-uniform bounds on normal approximation by Stein’s Method and bounded monotone size biased couplings

description: This dissertation contains two main parts. First, we give a non-uniform exponential bound on normal approximation by using the Stein’s method and bounded monotone size biased couplings. Second, applications of the main theorem to give the bound on normal approximation for sum of independent random variables, the number of bulbs on at the terminal time in the lightbulb process, and the number of m runs are provided.
DOI: 10.14457/cu.the.2016.167
title: Programming of one- and two-electron integrals in MOCCA program

description: Application of quantum theory in chemical problem is acceptable by many chemists around the world. One- and two-electron integrals are the most timeconsuming part limiting quantum theory application for large scale chemical system. Operation on graphic processing units (GPUs) for quantum chemistry calculation is one choice for accelerating the calculations. In this work, the calculations of oneand two-electron integrals were implemented for MOCCA program on GPU. According to the results, the one- and two-electron integrals calculated from the MOCCA program are realiable compared with GAMESS (US) program. The accuracy of oneand two-electron integrals calculated by MOCCA program is better than the level of 1 x10¹¹ compared with GAMESS (US) program. MOCCA program can calculate faster than GAMESS (US) program about 150-7000 times.
DOI: 10.14457/cu.the.2016.168
title: Numerical methods based on discontinuous Galerkin and finite volume methods for shallow water model and applications

description: Shallow water equations (SWE) can be used to model many real flow problems such as dam break, tsunami and flood. In this dissertation, we have developed three numerical schemes for solving these equations. The first scheme is the wellbalanced discontinuous Galerkin (DG) method with weighted average flux (WAF) for one-dimensional SWE. The second scheme is developed to obtain more realistic results for the one-dimensional flow, where the one-dimensional SWE is considered for arbitrary cross-sectional areas, based on the finite volume method (FVM). And the third scheme is developed to solve real world flows by considering the two-dimensional SWE based on the well-balanced FVM with WAF.
DOI: 10.14457/cu.the.2016.169
title: Improving minimax regret approach of expected recourse Problem with vectors of uncertainty

description: Uncertainty means that more than one realizations can represent an entity of interest. This thesis concerns a special pattern of uncertainty, which is a probability interval that can be represented as a random set. Our linear optimization model min x cT x; AT x b; x ≥ 0 has a special structure of the uncertainty; i.e., the coefficients and the right hand side of each constraint form vector of uncertainty. We transform a linear program with this special uncertainty into an interval expected recourse problem, then find the minimax regret of this issue by a relaxation procedure. The relaxation procedure finally has been improved by using the idea of ordering and the fact that we can reduce the size of the probability set of all possible ordering cases and reduce the calculation time.
DOI: 10.14457/cu.the.2016.170
title: Hypothesis testing for slope heterogeneity for three dimensional panel data model

description: Tests for slope heterogeneity play important roles in panel data analysis nowadays as we can see several tests have been proposed in the last decades. However, those tests were proposed for classical panel models while multi-dimensional panel data have been becoming more available and are important in applications. Therefore, the main goal of this thesis is to derive a heterogeneity test statistic that is applicable for three-dimensional panel data model. Our test is the Lagrange multiplier test statistic based on the conditional Gaussian likelihood function of a sufficient statistic. The test is asymptotically normally distributed when the number of levels of considered direction tends to infinity and the number of time periods is fixed. Simulation results show that the proposed test has good size under considered specifications.
DOI: 10.14457/cu.the.2016.171
title: Local attractivity and periodic character of rational Difference equation

description: In this thesis, we investigate some behaviors of the rational difference equations [symbol] where k ∈ℕ, the parameters A,B0,B1,B2, . . . ,Bk, and the initial conditions x−k, x−k+1, x−k+2, . . . ,x0 are nonnegative real numbers. We classify all periodic solutions with prime period-two and prime period-three. Then, we also present the existence of periodic solutions with prime period-p, where p is a prime number. Moreover, we prove the convergence of solutions to a period-(k + 1) solution. Finally, the local attractivity of solutions about some periodic with prime periodtwo and prime period-three is established.
DOI: 10.14457/cu.the.2016.172
title: Surjections and weak forms of The axiom of choice

description: If there is an injection from a nonempty set A into a set B, then there is always a surjection from B onto A. Without the Axiom of Choice (AC), the converse of this statement is not necessarily true. There are many other consequences of AC concerning surjections. We study these consequences and introduce some new weak forms as well as equivalent forms of AC and show some relationships among them.
DOI: 10.14457/cu.the.2016.173
title: Pointwise characterization of smooth functions within the dunkl-type segal-bargmann space

description: The Dunkl-type Segal-Bargmann space is the Hilbert space of holomorphic functions on ℂ of which even parts and odd parts are square-integrable with respect to certain measures related to the modified Bessel functions of the second kind. The Dunkl-type Segal-Bargmann space is then the (internal) direct sum of the even and odd subspaces. In this work, we characterize smooth functions in the Dunkl-type Segal-Bargmann space associated with the Dunkl operator.