cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.155652.v1
title: Gaussian Job Archive for C144H144(2+)

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.155647
title: Bedrock erosion by granular flow, Appendix 1: Erosion sample photographs and erosion maps

description: Photographs and erosion maps for the experiments in Hsu, L. (2010), Bedrock erosion by granular flow, Ph.D thesis, University of California, Berkeley. Two pdf files. Bedrock erosion experiments were performed in a 4 meter diameter, 80 cm wide vertically-rotating drum flume. Shallow flows were composed of clay, silt, sand, gravel, cobbles, and water. The flows eroded synthetic bedrock (concrete) samples. Erosion maps were made by differencing the topography before and after the flow with MATLAB. More information at the NCED Repository (https://repository.nced.umn.edu/)
DOI: 10.6084/m9.figshare.155654.v1
title: IPOL & SPOL: Reproducible Research Journals for Image and Signal Processing

description: presented at the SINTEF 13th annual Winter School in eScience on "Reproducible Science And Modern Scientific Software", 2013-01-23, Geilo, NO
DOI: 10.6084/m9.figshare.155647.v1
title: Bedrock erosion by granular flow, Appendix 1: Erosion sample photographs and erosion maps

description: Photographs and erosion maps for the experiments in Hsu, L. (2010), Bedrock erosion by granular flow, Ph.D thesis, University of California, Berkeley. Two pdf files. Bedrock erosion experiments were performed in a 4 meter diameter, 80 cm wide vertically-rotating drum flume. Shallow flows were composed of clay, silt, sand, gravel, cobbles, and water. The flows eroded synthetic bedrock (concrete) samples. Erosion maps were made by differencing the topography before and after the flow with MATLAB. More information at the NCED Repository (https://repository.nced.umn.edu/)
DOI: 10.6084/m9.figshare.155649.v1
title: Software as Science

description: presented at the FOSDEM 2013 "FOSS for Scientists" devroom, 2013-02-02, Bruxelles, BE Software is science, in the sense that when developed in the course of computational science research, it can't be classified as "infrastructure" or "support". If a telescope is infrastructure for astronomy, then its equivalent or computational mathematics is a supercomputer. On the other hand, code produced to prove a theorem, simulate an explosion or study an image denoising algorithm is the subject-matter of the science being investigated. We need this work to be recognized and time and effort invested in it must be rewarded by scholarship standards. On the other hand, when science is based on software foundations, the computational part of the research should be subject to validation by the scientific method. This implies that every program used in the elaboration of a research paper should, at least, be usable by referees, and if possible be publicly available is source form. Open Source software is part of the equation, but it is not sufficient to answer the questions raised here. During this talk, we will present the rationale for the "Software as Science" approach, in relation with other ideas, chiefly Reproducible Research and Open Science, and we will mention recent workshops and conferences, as well as groups, projects and institutions involved in these dynamics. We will list and detail numerous obstacles to the recognition of software in the scientific method and open questions on that matter: identification and citation, standard APIs and languages, verification and validation, copyright and patents, limits to reproducibility, etc. Finally, we will present our own project, IPOL, a research journal on image processing, in which every algorithm is published (Open Access license) and reviewed with the source code of its implementation (Open Source license) and a web interface to test it and browse archived experiments.
DOI: 10.6084/m9.figshare.155613
title: git repository for paper on git and reproducible science

description: This is the archived git repostiory for this paper: git can facilitate greater reproducibility and increased transparency in science Paper is currently in press in Source Code in Medicine and Biology and this zipped repo gives you access to the full history of the paper's development.
DOI: 10.6084/m9.figshare.155613.v1
title: git repository for paper on git and reproducible science

description: This is the archived git repostiory for this paper: git can facilitate greater reproducibility and increased transparency in science Paper is currently in press in Source Code in Medicine and Biology and this zipped repo gives you access to the full history of the paper's development.
DOI: 10.6084/m9.figshare.155525
title: CogSci2013: Experiment 2 Optimization

description: Results from 200 runs (plus 7 control runs) of Experiment 2 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". These runs were used to optimize learning parameters. Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155606
title: CogSci2013: Experiment 2 Results

description: Results from 80 runs of Experiment 2 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". There are 15 PES, 15 hPES, and 10 control runs for transmission and binding. Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155317
title: CogSci2013: Experiment 3 Results

description: Results from 2 runs of Experiment 3 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155606.v1
title: CogSci2013: Experiment 2 Results

description: Results from 80 runs of Experiment 2 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". There are 15 PES, 15 hPES, and 10 control runs for transmission and binding. Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155314
title: CogSci2013: Experiment 1 Results

description: Results from 50 runs of Experiment 1 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155317.v1
title: CogSci2013: Experiment 3 Results

description: Results from 2 runs of Experiment 3 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155525.v2
title: CogSci2013: Experiment 2 Optimization

description: Results from 200 runs (plus 7 control runs) of Experiment 2 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". These runs were used to optimize learning parameters. Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155311
title: Gaussian Job Archive for C144H144

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.155311.v1
title: Gaussian Job Archive for C144H144

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.155314.v1
title: CogSci2013: Experiment 1 Results

description: Results from 50 runs of Experiment 1 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". Code to analyze these data can be found at https://github.com/tbekolay/cogsci2013
DOI: 10.6084/m9.figshare.155525.v1
title: CogSci2013: Experiment 2 Optimation

description: Results from 200 runs (plus 7 control runs) of Experiment 2 from "Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks". These runs were used to optimize learning parameters.
DOI: 10.6084/m9.figshare.155303
title: Poster: Incorporating Domain Knowledge into Evolutionary Computing for Discovering Gene-Gene Interaction

description: Poster presented at the 2010 Parallel Problem Solving From Nature Meeting. Published in LNCS at the link below.
DOI: 10.6084/m9.figshare.155304
title: IL-8 Reporter Assay in LPS-stimulated and unstimulated cystic fibrosis airway cells treated with WLBU-2 or LL-37

description: CF IB3-1 cells (unstimulated and LPS-stimulated) were transfected with a 5' firefly luciferase gene flanking a 200bp wild type- or dNFκB IL-8 promoter and treated with 25µM WLBU-2 or LL-37 followed by measurement of IL-8 promoter activity at time points ranging from 30min-4h by Dual-Luciferase Reporter assay. PBS was used as a control in LPS-stimulated and unstimulated cells. Data represent means/standard deviations of the count readings and calculations of fold-change relative to the PBS-treated controls.
DOI: 10.6084/m9.figshare.155305
title: Proinflammatory cytokine measurements in IB3-1 cells following cationic antimicrobial peptide exposure

description: IB31 cells were exposed to 25μM LL37 or WLBU2 for various amounts of time, followed by quantitative RT-PCR measurement of IL1β & TNFα transcripts. The spreadsheet includes raw data and delta-delta Ct calculations for Real-time PCR; strikethrough values were not included in the analyses. GADPH was used as a control reagent.
DOI: 10.6084/m9.figshare.155303.v1
title: Poster: Incorporating Domain Knowledge into Evolutionary Computing for Discovering Gene-Gene Interaction

description: Poster presented at the 2010 Parallel Problem Solving From Nature Meeting. Published in LNCS at the link below.
DOI: 10.6084/m9.figshare.155304.v1
title: IL-8 Reporter Assay in LPS-stimulated and unstimulated cystic fibrosis airway cells treated with WLBU-2 or LL-37

description: CF IB3-1 cells (unstimulated and LPS-stimulated) were transfected with a 5' firefly luciferase gene flanking a 200bp wild type- or dNFκB IL-8 promoter and treated with 25µM WLBU-2 or LL-37 followed by measurement of IL-8 promoter activity at time points ranging from 30min-4h by Dual-Luciferase Reporter assay. PBS was used as a control in LPS-stimulated and unstimulated cells. Data represent means/standard deviations of the count readings and calculations of fold-change relative to the PBS-treated controls.
DOI: 10.6084/m9.figshare.155305.v1
title: Proinflammatory cytokine measurements in IB3-1 cells following cationic antimicrobial peptide exposure

description: IB31 cells were exposed to 25μM LL37 or WLBU2 for various amounts of time, followed by quantitative RT-PCR measurement of IL1β & TNFα transcripts. The spreadsheet includes raw data and delta-delta Ct calculations for Real-time PCR; strikethrough values were not included in the analyses. GADPH was used as a control reagent.
DOI: 10.6084/m9.figshare.155305.v3
title: Proinflammatory cytokine measurements in IB3-1 cells following cationic antimicrobial peptide exposure

description: IB31 cells were exposed to 25μM LL37 or WLBU2 for various amounts of time, followed by quantitative RT-PCR measurement of IL1β & TNFα transcripts. The spreadsheet includes raw data and delta-delta Ct calculations for Real-time PCR; strikethrough values were not included in the analyses. GADPH was used as a control reagent.
DOI: 10.6084/m9.figshare.155305.v2
title: Proinflammatory cytokine measurements in IB3-1 cells following cationic antimicrobial peptide exposure

description: IB31 cells were exposed to 25μM LL37 or WLBU2 for various amounts of time, followed by quantitative RT-PCR measurement of IL1β & TNFα transcripts. The spreadsheet includes raw data and delta-delta Ct calculations for Real-time PCR; strikethrough values were not included in the analyses. GADPH was used as a control reagent.
DOI: 10.6084/m9.figshare.154971
title: Experiment

description: Raw data of all the 4 experiments presented in this report are made available in Matlab format. These files contain a matlab structure named EVO that represents the evoked activity and related information. The field Evo.d contains the data and is organized as [space, time, condition]. The total length of the space dimension equals to Evo.ys*Evo.xs; the third dimension contains different conditions and is organized as follows: 1-2: Blank Conditions, 3: Condition A1B1, 4: A1, 5: B1, 6: A2B2, 7: A2, 8: B2, 9: A1B2, 10: B2A1. In order to plot the Nth sample of the Mth condition, one would need to issue the following command in Matlab: "imagesc(reshape(evo.d(:,N,M),evo.ys,evo.xs))4
DOI: 10.6084/m9.figshare.154973
title: Raw Ct values and relative quantities for <em>Erythroxylum coca</em> reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154970
title: Data File 2: raw transcript read counts

description: RNA-Sequencing by Expectation Maximization-estimated total counts for all genes in biological replicates of days in vitro (DIV) -8, -4, 0, 1, 7, 16, 21 and 28 samples. Genes for which no reads were detected in any biological sample were excluded.
DOI: 10.6084/m9.figshare.154971.v1
title: Experiment

description: Raw data of all the 4 experiments presented in this report are made available in Matlab format. These files contain a matlab structure named EVO that represents the evoked activity and related information. The field Evo.d contains the data and is organized as [space, time, condition]. The total length of the space dimension equals to Evo.ys*Evo.xs; the third dimension contains different conditions and is organized as follows: 1-2: Blank Conditions, 3: Condition A1B1, 4: A1, 5: B1, 6: A2B2, 7: A2, 8: B2, 9: A1B2, 10: B2A1. In order to plot the Nth sample of the Mth condition, one would need to issue the following command in Matlab: "imagesc(reshape(evo.d(:,N,M),evo.ys,evo.xs))4
DOI: 10.6084/m9.figshare.154969
title: Data File 1: summary data

description: RNA-sequencing by Expectation Maximization summary of quality metrics for paired-end Illumina runs. The last column indicates the filenames of the corresponding FASTQ files available at Sequence Read Archive, appended with an “F” for the forward sequence read or an “R” for the reverse sequence read.
DOI: 10.6084/m9.figshare.154973.v1
title: Raw Ct values and relative quantities for Erythroxylum. coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154863
title: Plant-Pollinator Network Data

description: Datasets describe the frequency of visits observed for each pollinator-plant interaction. More info in Bartomeus et al 2008 Oecologia 155 : 761-770. The study involved pollinator surveys in 3 sites per study species. Pairs of invaded and uninvaded plots were samples in all sites. Sites were sampled every 2 weeks during the entire flowering period of both C. affine acinaciformis and O. stricta. Each plant species was sampled during 6 minutes. Each species was sampled for a total of 36 minutes per site. In total, each site was surveyed by pollinators for more than 6 hours. Plant traits are described in Bartomeus 2013 PLoSOne (see link below)
DOI: 10.6084/m9.figshare.154862
title: One word wonders: Are shorter journal titles really higher impact?

description: I looked at data for 20,698 journals from the big four publishing countries: USA, UK, Germany, and the Netherlands to see whether journal title length was related to journal impact. Impact metrics are from http://www.journalmetrics.com/values.php
DOI: 10.6084/m9.figshare.154966.v1
title: Open Educational Resources and Open Access in Higher Education in Macedonia

description: Open Educational Resources and Open Access in Higher Education in Macedonia is a report that I did back in 2010. It is not peer reviewed or published - it simply give a broather picture to the public about the situation concerning OER nad OA in Macedonia. Recomendations concerning the promotion of OA/OER can be found at the end of the report. Hope you'll find it usefull enought for citations.
DOI: 10.6084/m9.figshare.154973.v2
title: Raw Ct values and relative quantities for Erythroxylum. coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154862.v1
title: One word wonders: Are shorter journal titles really higher impact?

description: I looked at data for 20,698 journals from the big four publishing countries: USA, UK, Germany, and the Netherlands to see whether journal title length was related to journal impact. Impact metrics are from http://www.journalmetrics.com/values.php
DOI: 10.6084/m9.figshare.154973.v3
title: Raw Ct values and relative quantities for Erythroxylum. coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154839
title: Cost implications of treatment non-completion in a forensic personality disorder service: a Markov model

description: This model is described in an article currently in press in the journal Criminal Behaviour and Mental Health
DOI: 10.6084/m9.figshare.154839.v1
title: Cost implications of treatment non-completion in a forensic personality disorder service: a Markov model

description: This model is described in an article currently in press in the journal Criminal Behaviour and Mental Health
DOI: 10.6084/m9.figshare.154973.v4
title: Raw Ct values and relative quantities for Erythroxylum. coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154796
title: Experiment 1 raw data

description: Accuracy and motor reaction times (MRT) data for all participants on novel-AV (“AV”), shape-VV (“VV”), and verbal-AV (“Vver”) learning tasks. The values in each column denote: Stimulus type: 1-4 = target; 5-16 = non-target Response/Expected response: 1 = press; 0 = no press Accuracy: 0 = correct; 1 = incorrect
DOI: 10.6084/m9.figshare.154797
title: Experiment 2 raw data

description: Accuracy and motor reaction times (MRT) data for all participants on Novel-A (“NovelSounds”), Verbal-A (“VerbalSounds”), Shape-V (“RedShapes”), and three black shapes (BS) (LineSet1, 2, and 3) discrimination tasks. The values in each column denote: Stimulus type: 1 = target; 2, 3, 4 = non-target User Response: 1 = respond target; 2 = respond non-target; 999 = invalid response (both buttons pressed in response to the stimuli) Accuracy: 1 = correct; 0 = incorrect
DOI: 10.6084/m9.figshare.154797.v1
title: Experiment 2 raw data

description: Accuracy and motor reaction times (MRT) data for all participants on Novel-A (“NovelSounds”), Verbal-A (“VerbalSounds”), Shape-V (“RedShapes”), and three black shapes (BS) (LineSet1, 2, and 3) discrimination tasks. The values in each column denote: Stimulus type: 1 = target; 2, 3, 4 = non-target User Response: 1 = respond target; 2 = respond non-target; 999 = invalid response (both buttons pressed in response to the stimuli) Accuracy: 1 = correct; 0 = incorrect
DOI: 10.6084/m9.figshare.154973.v5
title: Raw Ct values and relative quantities for Erythroxylum. coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154795
title: Sound files used in the experiments

description: Sounds of pseudowords (chel, doot, jat and shoap) as well as carrier and modulation frequencies used in the experiments. Carrier frequencies: Novel sound 1 (NS-1) = 400-480 Hz. Novel sound 2 (NS-2) = 1000-1350 Hz, Novel sound 3 (NS-3) = 3000-3200 Hz. Novel sound 4 (NS-4) = 250-4500 Hz. Modulation frequencies were either kept at 3 Hz (NS-1), 10 Hz (NS-2), 0.5 Hz (NS-3) or 6 Hz (NS-4)
DOI: 10.6084/m9.figshare.154798.v1
title: VoSeq

description: VoSeq
DOI: 10.6084/m9.figshare.154795.v1
title: Sound files used in the experiments

description: Sounds of pseudowords (chel, doot, jat and shoap) as well as carrier and modulation frequencies used in the experiments. Carrier frequencies: Novel sound 1 (NS-1) = 400-480 Hz. Novel sound 2 (NS-2) = 1000-1350 Hz, Novel sound 3 (NS-3) = 3000-3200 Hz. Novel sound 4 (NS-4) = 250-4500 Hz. Modulation frequencies were either kept at 3 Hz (NS-1), 10 Hz (NS-2), 0.5 Hz (NS-3) or 6 Hz (NS-4)
DOI: 10.6084/m9.figshare.154973.v6
title: Raw Ct values and relative quantities for <em>Erythroxylum</em> coca reference genes

description: Raw data based on Ct values obtained for each gene used in this study is provided. In addition, the calculated relative quantities for each gene tested in the different plant tissues is supplied as a separate file. NTC = Non template control (H20 control); STD = Standard for standard curve analysis; UNKN = Unknown (i.e. sample to quantify)
DOI: 10.6084/m9.figshare.154686
title: Figure 8 raw data: Effect of intermittent and continuous exposure to PTHrP (1-36) on BSP and OPN mRNA and BSP protein.

description: The BSP (A) and OPN (B) mRNA in RC cells exposed to 100 nM PTHrP (1-36) for 1 hr, 6 hrs, or 48 hrs for seven 48 hr treatment cycles (15 days) was measured by quantitative real-time RT-PCR.
DOI: 10.6084/m9.figshare.154686.v1
title: Figure 8 raw data: Effect of intermittent and continuous exposure to PTHrP (1-36) on BSP and OPN mRNA and BSP protein.

description: The BSP (A) and OPN (B) mRNA in RC cells exposed to 100 nM PTHrP (1-36) for 1 hr, 6 hrs, or 48 hrs for seven 48 hr treatment cycles (15 days) was measured by quantitative real-time RT-PCR.
DOI: 10.6084/m9.figshare.154684
title: Figure 6 raw data: Effect of intermittent and continuous exposure to PTHrP (1-36) on cell proliferation and apoptosis in RC cell cultures

description: Fig6A. The number of BrdU positive RC cells to the normal number of cells following 100 nM of PTHrP (1-36) treatment for 1 hr, 6 hrs, or 48 hrs for two 48 hr treatment cycles.<br>Fig6B. The number of apoptotic cells to the normal number of cells following 100 nM of PTHrP (1-36) treatment for 1 hr, 6 hrs, or 48 hrs for two 48 hr treatment cycles.