cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.2068272.v1
title: Measuring Influence of Users in Twitter Ecosystems Using a Counting Process Modeling Framework

description: Data extracted from social media platforms are both large in scale and complex in nature, since they contain both unstructured text, as well as structured data, such as time stamps and interactions between users. A key question for such platforms is to determine influential users, in the sense that they generate interactions between members of the platform. Common measures used both in the academic literature and by companies that provide analytics services are variants of the popular web-search PageRank algorithm applied to networks that capture connections between users. In this work, we develop a modeling framework using multivariate interacting counting processes to capture the detailed actions that users undertake on such platforms, namely posting original content, reposting and/or mentioning other users’ postings. Based on the proposed model, we also derive a novel influence measure. We discuss estimation of the model parameters through maximum likelihood and establish their asymptotic properties. The proposed model and the accompanying influence measure are illustrated on a dataset covering a five-year period of the Twitter actions of the members of the U.S. Senate, as well as mainstream news organizations and media personalities. Supplementary material is available online including computer code, data, and derivation details.
DOI: 10.6084/m9.figshare.2068269
title: Statistics GRRA allocator- x86

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068260
title: Sum-GRRA-x86

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068263
title: Summarized GRRA data - x86

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068266
title: Summarized GRRA data - Sparc

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the Sparc architecture.
DOI: 10.6084/m9.figshare.2068275.v1
title: New draft item

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068260.v1
title: Sum-GRRA-x86

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068275.v3
title: Statistics GRRA allocator- Sparc

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068257
title: Raw data others allocators - Sparc

description: This file contains the observations collected in the experiment for each of the test-suite of programs for the other allocators (basic, fast, greedy, pbqp), generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068275.v2
title: Stat-GRRA-Sparc

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068263.v2
title: Summarized GRRA data - x86

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068266.v2
title: Summarized GRRA data - Sparc

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the Sparc architecture.
DOI: 10.6084/m9.figshare.2068269.v1
title: Stat-GRRA-x86

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068257.v2
title: Raw data others allocators - Sparc

description: This file contains the observations collected in the experiment for each of the test-suite of programs for the other allocators (basic, fast, greedy, pbqp), generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068263.v1
title: Sum-GRRA-x86

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068266.v1
title: Sum-GRRA-Sparc

description: This file contains the summarized data from the 500 observations for all the programs, generating code for the Sparc architecture.
DOI: 10.6084/m9.figshare.2068257.v1
title: Raw-Others-Alloc-Sparc

description: This file contains the observations collected in the experiment for each of the test-suite of programs for the other allocators (basic, fast, greedy, pbqp), generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068269.v3
title: Statistics GRRA allocator- x86

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068245
title: Detection of Critical Genes Associated with Overall Survival (OS) and Progression-Free Survival (PFS) in Reconstructed Canine B-Cell Lymphoma Gene Regulatory Network (GRN)

description: Canine B-cell lymphoma GRN was reconstructed from gene expression data in the STRING and MiMI databases. Critical genes of networks were identified and correlations of critical genes with overall survival (OS) and progression-free survival (PFS) were evaluated. Significant changes were detected in the expressions of <i>GLUL, CD44, CD79A, ARF3, FOS, BLOC1S1, FYN, GZMB, GALNT3, IFI44, CD3G, GNG2, ESRP1</i>, and <i>CCND1</i> in the STRING network and of <i>PECAM1, GLUL, CD44, GDI1, E2F4, TLE1, CD79A, UCP2, CCND1, FYN, RHOQ, BIN1</i>, and <i>A2M</i> in the MiMI network. Final survival analysis highlighted <i>CCND1</i> and <i>FOS</i> as genes with significant correlations with OS and PFS.
DOI: 10.6084/m9.figshare.2068251
title: Raw data others allocators - x86

description: This file contains the observations of the other allocators (basic, greedy, fast and pbqp) collected in the experiment for each of the test-suite of programs, generating code for the x86 architecture
DOI: 10.6084/m9.figshare.2068245.v1
title: Detection of Critical Genes Associated with Overall Survival (OS) and Progression-Free Survival (PFS) in Reconstructed Canine B-Cell Lymphoma Gene Regulatory Network (GRN)

description: Canine B-cell lymphoma GRN was reconstructed from gene expression data in the STRING and MiMI databases. Critical genes of networks were identified and correlations of critical genes with overall survival (OS) and progression-free survival (PFS) were evaluated. Significant changes were detected in the expressions of <i>GLUL, CD44, CD79A, ARF3, FOS, BLOC1S1, FYN, GZMB, GALNT3, IFI44, CD3G, GNG2, ESRP1</i>, and <i>CCND1</i> in the STRING network and of <i>PECAM1, GLUL, CD44, GDI1, E2F4, TLE1, CD79A, UCP2, CCND1, FYN, RHOQ, BIN1</i>, and <i>A2M</i> in the MiMI network. Final survival analysis highlighted <i>CCND1</i> and <i>FOS</i> as genes with significant correlations with OS and PFS.
DOI: 10.6084/m9.figshare.2068269.v2
title: Statistics GRRA - x86

description: This files contains general statistics about the experiment, including generated spill, runtime, confidence interval of the observations for each program and the difference between the spill generated for the GRRA allocator and the others, generating code for the x86 architecture.<br>
DOI: 10.6084/m9.figshare.2068236
title: Raw data GRRA allocator - Sparc

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068233
title: Application of multiparametric procedures for assessing the heritability of circadian health

description: At present, the measurement of circadian system status under free-living conditions by the use of sensors is a relatively new technique. The data obtained using these methods are influenced by strong environmental masking factors and artifacts that can affect its recording. Therefore, the use of integrative variables such as TAP, a measure that includes temperature, activity and position that reduces these drawbacks and the number of parameters obtained is necessary. However, the relative genetic contribution to this circadian marker is unknown. The aim of our study was to ascertain the relative importance of genetic influences in TAP, and for each of its components using classical twin models. The study was performed in 53 pairs of female twins [28 monozygotic (MZ) and 25 dizygotic (DZ)] with mean age 52 ± 6 years. Circadian patterns were studied by analyzing temperature, body position and activity for 1 week every 1 min with “Circadianware®.”. Genetic influences affecting the variability of each of the measurements were estimated by comparing the observed data in twin pairs. MZ twins showed higher intrapair correlations than DZ twins for most of the parameters. Genetic factors (broad sense heritability) were responsible for about 40–72% of TAP variance in parameters such as mesor, acrophase, amplitude, Rayleigh test, percentage of rhythmicity and circadian function index. We found more homogeneous heritability estimates of the circadian system when using an integrative technique such as TAP than with individual variables alone, suggesting that this measurement can be more reliable and less subject to environmental artifacts.
DOI: 10.6084/m9.figshare.2068233.v1
title: Application of multiparametric procedures for assessing the heritability of circadian health

description: At present, the measurement of circadian system status under free-living conditions by the use of sensors is a relatively new technique. The data obtained using these methods are influenced by strong environmental masking factors and artifacts that can affect its recording. Therefore, the use of integrative variables such as TAP, a measure that includes temperature, activity and position that reduces these drawbacks and the number of parameters obtained is necessary. However, the relative genetic contribution to this circadian marker is unknown. The aim of our study was to ascertain the relative importance of genetic influences in TAP, and for each of its components using classical twin models. The study was performed in 53 pairs of female twins [28 monozygotic (MZ) and 25 dizygotic (DZ)] with mean age 52 ± 6 years. Circadian patterns were studied by analyzing temperature, body position and activity for 1 week every 1 min with “Circadianware®.”. Genetic influences affecting the variability of each of the measurements were estimated by comparing the observed data in twin pairs. MZ twins showed higher intrapair correlations than DZ twins for most of the parameters. Genetic factors (broad sense heritability) were responsible for about 40–72% of TAP variance in parameters such as mesor, acrophase, amplitude, Rayleigh test, percentage of rhythmicity and circadian function index. We found more homogeneous heritability estimates of the circadian system when using an integrative technique such as TAP than with individual variables alone, suggesting that this measurement can be more reliable and less subject to environmental artifacts.
DOI: 10.6084/m9.figshare.2068221
title: Raw data GRRA allocator - x86

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the x86 architecture.
DOI: 10.6084/m9.figshare.2068230
title: Differences in toxicity and outcome associated with circadian variations between patients undergoing daytime and evening radiotherapy for prostate adenocarcinoma

description: This retrospective study tested the hypothesis that disease control and treatment-related toxicity in patients undergoing high-dose radiotherapy (HDRT) for prostate cancer varies in a circadian manner. Patients with localized prostate adenocarcinoma receiving HDRT (median 78 Gy) to the prostate and involved seminal vesicle(s) without elective pelvic irradiation were divided into a daytime treatment (before 5 PM) group (<i>n</i> = 267) and evening treatment (after 5 PM) group (<i>n</i> = 142). Biochemical failure (Phoenix definition), acute and late gastrointestinal (GI) and genitourinary toxicities (Common Terminology Criteria for Adverse Events version 4), biochemical failure-free survival (BFFS) and freedom from late toxicity were assessed. Analyses were performed by binary logistic regression and Cox proportional hazard regression. The median follow-up was 68 months, and 75% of patients were ≥70 years old. Evening HDRT was significantly associated with worse freedom from ≥grade 2 late GI complications (hazard ratio = 2.96; <i>p</i> &lt; 0.001). The detrimental effect of evening HDRT was significant in patients older than 70 years old (<i>p</i> &lt; 0.001) but not in younger patients (<i>p</i> = 0.63). In a subgroup of propensity score-matched cohort with T2b–T3 disease (<i>n</i> = 154), the 5-year BFFS was worse in the evening group than the daytime group (72% vs. 85%, hazard ratio = 1.95, <i>p</i> = 0.05). Our study indicates that evening HDRT may lead to more GI complications, especially in older patients, and worse BFFS in patients with T2b–T3 disease.
DOI: 10.6084/m9.figshare.2068236.v1
title: Raw-GRRA-Spark

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068230.v1
title: Differences in toxicity and outcome associated with circadian variations between patients undergoing daytime and evening radiotherapy for prostate adenocarcinoma

description: This retrospective study tested the hypothesis that disease control and treatment-related toxicity in patients undergoing high-dose radiotherapy (HDRT) for prostate cancer varies in a circadian manner. Patients with localized prostate adenocarcinoma receiving HDRT (median 78 Gy) to the prostate and involved seminal vesicle(s) without elective pelvic irradiation were divided into a daytime treatment (before 5 PM) group (<i>n</i> = 267) and evening treatment (after 5 PM) group (<i>n</i> = 142). Biochemical failure (Phoenix definition), acute and late gastrointestinal (GI) and genitourinary toxicities (Common Terminology Criteria for Adverse Events version 4), biochemical failure-free survival (BFFS) and freedom from late toxicity were assessed. Analyses were performed by binary logistic regression and Cox proportional hazard regression. The median follow-up was 68 months, and 75% of patients were ≥70 years old. Evening HDRT was significantly associated with worse freedom from ≥grade 2 late GI complications (hazard ratio = 2.96; <i>p</i> &lt; 0.001). The detrimental effect of evening HDRT was significant in patients older than 70 years old (<i>p</i> &lt; 0.001) but not in younger patients (<i>p</i> = 0.63). In a subgroup of propensity score-matched cohort with T2b–T3 disease (<i>n</i> = 154), the 5-year BFFS was worse in the evening group than the daytime group (72% vs. 85%, hazard ratio = 1.95, <i>p</i> = 0.05). Our study indicates that evening HDRT may lead to more GI complications, especially in older patients, and worse BFFS in patients with T2b–T3 disease.
DOI: 10.6084/m9.figshare.2068236.v3
title: Raw data GRRA allocator - Sparc

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068251.v1
title: Raw-Others-Alloc-x86

description: This file contains the observations of the other allocators (basic, greedy, fast and pbqp) collected in the experiment for each of the test-suite of programs, generating code for the x86 architecture
DOI: 10.6084/m9.figshare.2068203
title: Monitoring of Heart and Breathing Rates using Dual Cameras on a Smartphone

description: This data correspond to a manuscript of Plos One (ID: PONE-D-15-39290).Data were collected from N=11 healthy non-smokers (2 females and 9 males) between 20 and 40 years old, who were dressed in striped, spotted, or plain clothes. All subjects were instructed to breathe at a metronome rate according to a timed beeping sound programmed at a chosen frequency. The metronome breathing rate was done to test wide dynamics range of breathing rates. Each subject was asked to inhale with each beep sound followed by exhalation before the next beep sound occurred. The data were collected for breathing frequencies ranging from 0.1 to 0.5 Hz at increments of 0.1 Hz, 1 Hz, and spontaneous breathing. Prior to data collection, all subjects were acclimated to different metronome breathing rates. Two minutes of ECG, chest and abdominal movements from the front camera, and finger pulse signals from the rear camera data, were collected for each breathing maneuver, for each subject.
DOI: 10.6084/m9.figshare.2068236.v2
title: Raw-GRRA-Sparc

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the Sparc architecture
DOI: 10.6084/m9.figshare.2068251.v3
title: Raw data others allocators - x86

description: This file contains the observations of the other allocators (basic, greedy, fast and pbqp) collected in the experiment for each of the test-suite of programs, generating code for the x86 architecture
DOI: 10.6084/m9.figshare.2068221.v2
title: Raw data GRRA allocator - x86

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the x86 architecture.
DOI: 10.6084/m9.figshare.2068251.v2
title: Raw data others allocator - x86

description: This file contains the observations of the other allocators (basic, greedy, fast and pbqp) collected in the experiment for each of the test-suite of programs, generating code for the x86 architecture
DOI: 10.6084/m9.figshare.2068221.v1
title: Raw-GRRA-x86

description: This file contains all of the 500 observations collected in the experiment for each of the test-suite of programs for the GRRA allocator, generating code for the x86 architecture.
DOI: 10.6084/m9.figshare.2068167
title: Dataset-Analysis of Bipolar Radiofrequency Ablation in Treatment of Atrial Fibrillation Associated with Rheumatic Heart Disease.xls

description: Primary Data of an article entitled with Analysis of Bipolar Radiofrequency Ablation in Treatment of Atrial Fibrillation Associated with Rheumatic Heart Disease
DOI: 10.6084/m9.figshare.2068167.v1
title: Dataset-Analysis of Bipolar Radiofrequency Ablation in Treatment of Atrial Fibrillation Associated with Rheumatic Heart Disease.xls

description: Primary Data of an article entitled with Analysis of Bipolar Radiofrequency Ablation in Treatment of Atrial Fibrillation Associated with Rheumatic Heart Disease
DOI: 10.6084/m9.figshare.2068122
title: 2015 ASHS Computing Workshop Materials

description: Workshop materials presented at ASHS 2015. <br><br>Abstract: Using computers to store and analyze data has firmly landed as the norm in science. Many advanced software tools are available to the every-day computer user that can help in achieving his or her scientific goals. Section 1 of the workshop introduces a suite of advanced computing skills that provide the foundation for becoming proficient at using generalized, broadly applicable, and freely available computing software. Generalized programming languages, like Python, SQLite, and R: can be used by any scientist to customize and streamline their data management and analyses. This workshop introduces valuable concepts, techniques, and resources to incorporate advanced computing into your work. To improve the repeatability and efficiency of your data management and analysis we present a short list of simple steps: 1) improve the documentation of your data through logs and metadata, 2) maintain an unprocessed or original form of the data, 3) use standard data file formats such as .txt and .csv, 4) use good null values, and 5) simplify your data into standard tabular structure within relational databases.
DOI: 10.6084/m9.figshare.2068125
title: RLA-CL

description: Test data sets for RLA-CL.1. Used in_1000k_15_10.tar.gz and in_1000k.tar.gz for comparison among TPA(FCED), RLA, and RLA-CL.<br>2. in_3200k.tar.gz file contains 3,200,000 records, from which all other data sets are generated.3. in_1600k.tar.gz and in_1000k.tar.gz contain data sets mixed with errors deliberately.<br>
DOI: 10.6084/m9.figshare.2068122.v1
title: 2015 ASHS Computing Workshop Materials

description: Workshop materials presented at ASHS 2015. <br><br>Abstract: Using computers to store and analyze data has firmly landed as the norm in science. Many advanced software tools are available to the every-day computer user that can help in achieving his or her scientific goals. Section 1 of the workshop introduces a suite of advanced computing skills that provide the foundation for becoming proficient at using generalized, broadly applicable, and freely available computing software. Generalized programming languages, like Python, SQLite, and R: can be used by any scientist to customize and streamline their data management and analyses. This workshop introduces valuable concepts, techniques, and resources to incorporate advanced computing into your work. To improve the repeatability and efficiency of your data management and analysis we present a short list of simple steps: 1) improve the documentation of your data through logs and metadata, 2) maintain an unprocessed or original form of the data, 3) use standard data file formats such as .txt and .csv, 4) use good null values, and 5) simplify your data into standard tabular structure within relational databases.
DOI: 10.6084/m9.figshare.2068143.v1
title: Reproducibility from a Selfish Point of View

description: Slides from a presentation 2015-01-26 at EcoHealth Alliance, NYC.
DOI: 10.6084/m9.figshare.2068125.v1
title: RLA-CL

description: Test data sets for RLA-CL.1. in_3200k.tar.gz file contains 3,200,000 records, from which all other data sets are generated.2. in_1600k.tar.gz and in_1000k.tar.gz contain data sets mixed with errors deliberately.
DOI: 10.6084/m9.figshare.2068125.v3
title: RLA-CL

description: Test data sets for RLA-CL.1. Used in_1000k_15_10.tar.gz and in_1000k.tar.gz for comparison among TPA(FCED), RLA, and RLA-CL.<br>2. in_3200k.tar.gz file contains 3,200,000 records, from which all other data sets are generated.3. in_1600k.tar.gz and in_1000k.tar.gz contain data sets mixed with errors deliberately.<br>
DOI: 10.6084/m9.figshare.2068143.v2
title: Reproducibility from a Mostly Selfish Point of View

description: Slides from a presentation 2015-01-26 at EcoHealth Alliance, NYC.