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667 results for “Null”
Data for Effective Unit Test Generation for Java Null Pointer Exceptions
<p>This is to provide all contents of our work, NPETest, including all raw experimental data used in our paper which will be published at ASE`24.</p> <p> </p> <p>NPETest is an unit test generation tool for Java projects, which utilizes both static and dynamic analysis techniques for effective NPE detection. This tool is implemented on the top of EvoSuite, a publicly available unit test generation tool for Java.</p> <p>For more technical details, please read our paper which will be published at ASE`24.</p> <p> </p> <p>The descriptions for the uploaded files are as follows:</p> <p>npetest_result.zip: results of NPETest for all benchmarks, containing the generated test-cases</p> <p>evosuite_opt_result.zip: results of EvoSuite with fine-tuned options for all benchmarks, containing the generated test-cases</p> <p>evosuite_def_result.zip: results of EvoSuite with default options for all benchmarks, containing the generated test-cases</p> <p>randoop_NPEX.tar.gz: results of Randoop for NPEX benchmarks, containing only the log-files. </p> <p>randoop_other.tar.gz: results of Randoop for Bears, BugSwarm, Defects4J, Genesis benchmarks, containing only the log-files.</p> <p>subject_gits.tar.gz: information of the buggy version for each benchmark. </p> <p>NPETestArtifact-main.zip: all contents of NPETest from the public Github respository <a href="https://github.com/kupl/NPETestArtifact" target="_blank" rel="noopener">NPETestArtifact</a>.</p> <p> </p> <p> </p> <p>The detailed description for NPETest (e.g., Install, Usage) of the tool is available on the public repository: <a href="https://github.com/kupl/NPETestArtifact" target="_blank" rel="noopener">NPETestArtifact</a>.<br>You can also download VM from the following link: <a href="https://doi.org/10.5281/zenodo.13371823" target="_blank" rel="noopener">Zenodo</a></p>
Research data used in "Quantum null dimension witness for a bipartite state"
<p>Research data used in "Quantum null dimension witness for a bipartite state"</p>
Mapped ATAC-seq data for mock and HSV-1 strain 17 infection and infection with null mutants of HSV-1
<p>Sample annotation:</p> <table> <tbody> <tr> <td>Mock_1</td> <td>mock infection, replicate 1</td> </tr> <tr> <td>Mock_2</td> <td>mock infection, replicate 2</td> </tr> <tr> <td>WT_1</td> <td>HSV-1 wt, strain 17, replicate 1</td> </tr> <tr> <td>WT_2</td> <td>HSV-1 wt, strain 17, replicate 2</td> </tr> <tr> <td>WT_plus_PAA_1</td> <td>HSV-1 wt, strain 17, +PAA, replicate 1</td> </tr> <tr> <td>WT_plus_PAA_2</td> <td>HSV-1 wt, strain 17, +PAA, replicate 2</td> </tr> <tr> <td>dICP0_1</td> <td>HSV-1 lacking expression of ICP0, replicate 1</td> </tr> <tr> <td>dICP0_2</td> <td>HSV-1 lacking expression of ICP0, replicate 2</td> </tr> <tr> <td>dICP22_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 1</td> </tr> <tr> <td>dICP22_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 2</td> </tr> <tr> <td>dICP22_3</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 3</td> </tr> <tr> <td>dICP22_4</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 4</td> </tr> <tr> <td>dICP22_plus_PAA_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 1</td> </tr> <tr> <td>dICP22_plus_PAA_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 2</td> </tr> <tr> <td>dICP27_1</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 1</td> </tr> <tr> <td>dICP27_2</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 2</td> </tr> <tr> <td>dVHS_1</td> <td>HSV-1 lacking expression of UL41, replicate 1</td> </tr> <tr> <td>dVHS_2</td> <td>HSV-1 lacking expression of UL41, replicate 2</td> </tr> </tbody> </table>
Supplementary material: animated GIF of null space shuttle with shortening of the subducted Iberian crust.
<p>Supplementary material to the paper: </p><p>Geologically constrained geometry inversion with and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees. <br>Jeremie Giraud, Mary Ford, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, Roland Martin, Paul Cupillard. </p><p>Note that the profile A-B shown here is more to the west than the profile shown in the paper. The image shows the full model inclusive of padding cells.</p>
Benchmark tests imply the explicit correlation between chain-like stress transfer and interevent violation of Gutenberg-Richter law null hypothesis in fracturing process [DATA]
<p>Data and metadata for article: Benchmark tests imply the explicit correlation between chain-like stress transfer and interevent violation of Gutenberg-Richter law null hypothesis in fracturing process</p>
Efficacy of Vitamin D on Top of Pegylated Interferon and Ribavirin in Patients With Chronic Viral Hepatitis C Null-Responders
ClinicalTrials.gov study NCT01226446. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Duffy-null Associated Neutrphil Count (DANC) Pediatric Patients
ClinicalTrials.gov study NCT06547931. IPD Sharing: YES. Countries: 1. Publications: 5.
Efficacy and Safety of G-CSF in Patients With Severe Alcoholic Hepatitis With Null or Partial Response to Steroid
ClinicalTrials.gov study NCT02442180. IPD Sharing: NO. Countries: 1. Publications: 1.
Pilot Study to Assess the Efficacy of and Tolerance to a QUadruple Therapy to Treat HIV-HCV Coinfected Patients Previously Null Responders
ClinicalTrials.gov study NCT01725542. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A graphical null model for scaling biodiversity-ecosystem functioning relationships
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Data from: Null alleles are ubiquitous at microsatellite loci in the Wedge Clam (Donax trunculus)
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Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
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Data from: Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations
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Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
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Data from: Fauxcurrence: simulating multi-species occurrences for null models in species distribution modelling and biogeography
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Assessing the genetic diversity in Argopecten nucleus (Bivalvia: Pectinidae), a functional hermaphrodite species with extremely low population density and self-fertilization: effect of null alleles
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Data from: Extending null scenarios with Faddy distributions in a probabilistic randomization protocol for presence-absence data
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Data from: Natural selection for the Duffy-null allele in the recently admixed people of Madagascar
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Data from: 'True' null allele detection in microsatellite loci: a comparison of methods, assessment of difficulties, and survey of possible improvements
Null alleles are alleles that for various reasons fail to amplify in a PCR assay. The presence of null alleles in microsatellite data is known to bias the genetic parameter estimates. Thus, efficient detection of null alleles is crucial, but the methods available for indirect null allele detection return inconsistent results. Here, our aim was to compare different methods for null allele detection, to explain their respective performance and to provide improvements. We applied several approaches to identify the 'true' null alleles based on the predictions made by five different methods, used either individually or in combination. First, we introduced simulated 'true' null alleles into 240 population data sets and applied the methods to measure their success in detecting the simulated null alleles. The single best-performing method was ML-NullFreq_frequency. Furthermore, we applied different noise reduction approaches to improve the results. For instance, by combining the results of several methods, we obtained more reliable results than using a single one. Rule-based classification was applied to identify population properties linked to the false discovery rate. Rules obtained from the classifier described which population genetic estimates and loci characteristics were linked to the success of each method. We have shown that by simulating 'true' null alleles into a population data set, we may define a null allele frequency threshold, related to a desired true or false discovery rate. Moreover, using such simulated data sets, the expected null allele homozygote frequency may be estimated independently of the equilibrium state of the population.
Presence of Circulating Cluster of Differentiation 4 Positive 28 Null T Helper Lymphocytes(CD4+CD28-) in Patients With Autoimmune Hemolytic Anemia.
ClinicalTrials.gov study NCT05711264. IPD Sharing: Not stated. Countries: 0. Publications: 6.
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.