1,312 research outputs found
The Role of Attorney Fee Shifting in Public Interest Litigation
BACKGROUND: Brain tissue segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) are important in neuroradiological applications. Quantitative Mri (qMRI) allows segmentation based on physical tissue properties, and the dependencies on MR scanner settings are removed. Brain tissue groups into clusters in the three dimensional space formed by the qMRI parameters R1, R2 and PD, and partial volume voxels are intermediate in this space. The qMRI parameters, however, depend on the main magnetic field strength. Therefore, longitudinal studies can be seriously limited by system upgrades. The aim of this work was to apply one recently described brain tissue segmentation method, based on qMRI, at both 1.5 T and 3.0 T field strengths, and to investigate similarities and differences. METHODS: In vivo qMRI measurements were performed on 10 healthy subjects using both 1.5 T and 3.0 T MR scanners. The brain tissue segmentation method was applied for both 1.5 T and 3.0 T and volumes of WM, GM, CSF and brain parenchymal fraction (BPF) were calculated on both field strengths. Repeatability was calculated for each scanner and a General Linear Model was used to examine the effect of field strength. Voxel-wise t-tests were also performed to evaluate regional differences. RESULTS: Statistically significant differences were found between 1.5 T and 3.0 T for WM, GM, CSF and BPF (p<0.001). Analyses of main effects showed that WM was underestimated, while GM and CSF were overestimated on 1.5 T compared to 3.0 T. The mean differences between 1.5 T and 3.0 T were -66 mL WM, 40 mL GM, 29 mL CSF and -1.99% BPF. Voxel-wise t-tests revealed regional differences of WM and GM in deep brain structures, cerebellum and brain stem. CONCLUSIONS: Most of the brain was identically classified at the two field strengths, although some regional differences were observed
Considering Polymorphism in Change-Based Test Suite Reduction
With the increasing popularity of continuous integration, algorithms for
selecting the minimal test-suite to cover a given set of changes are in order.
This paper reports on how polymorphism can handle false negatives in a previous
algorithm which uses method-level changes in the base-code to deduce which
tests need to be rerun. We compare the approach with and without polymorphism
on two distinct cases ---PMD and CruiseControl--- and discovered an interesting
trade-off: incorporating polymorphism results in more relevant tests to be
included in the test suite (hence improves accuracy), however comes at the cost
of a larger test suite (hence increases the time to run the minimal
test-suite).Comment: The final publication is available at link.springer.co
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Systematic evaluation of spliced alignment programs for RNA-seq data
High-throughput RNA sequencing is an increasingly accessible method for studying gene structure and activity on a genome-wide scale. A critical step in RNA-seq data analysis is the alignment of partial transcript reads to a reference genome sequence. To assess the performance of current mapping software, we invited developers of RNA-seq aligners to process four large human and mouse RNA-seq data sets. In total, we compared 26 mapping protocols based on 11 programs and pipelines and found major performance differences between methods on numerous benchmarks, including alignment yield, basewise accuracy, mismatch and gap placement, exon junction discovery and suitability of alignments for transcript reconstruction. We observed concordant results on real and simulated RNA-seq data, confirming the relevance of the metrics employed. Future developments in RNA-seq alignment methods would benefit from improved placement of multimapped reads, balanced utilization of existing gene annotation and a reduced false discovery rate for splice junctions
The ATLAS tile calorimeter digitizer
The ATLAS Tile Calorimeter digitizer system samples photomultiplier signals from the scintillating tiles of the hadronic calorimeter. For each channel a pair of 10-bit ADCs digitize high and low gain signals at 40.08 MHz to provide the necessary 16-bit dynamic range. The sampled data is temporarily stored in digital pipelines for up to 6.375 \mus, awaiting a level-1 accept. For each accept received, the corresponding sampled pulse is transferred to a derandomizer buffer for subsequent readout to the data acquisition system (DAQ). The main functionality of the digitizer is implemented in radiation tolerant ASICs, using a fault tolerant architecture to minimize the consequences of radiation induced faults
Charge-Fluctuation-Induced Non-analytic Bending Rigidity
In this Letter, we consider a neutral system of mobile positive and negative
charges confined on the surface of curved films. This may be an appropriate
model for: i) a highly charged membrane whose counterions are confined to a
sheath near its surface; ii) a membrane composed of an equimolar mixture of
anionic and cationic surfactants in aqueous solution. We find that the charge
fluctuations contribute a non-analytic term to the bending rigidity that varies
logarithmically with the radius of curvature. This may lead to spontaneous
vesicle formation, which is indeed observed in similar systems.Comment: Revtex, 9 pages, no figures, submitted to PR
Differential expression analysis for sequence count data
*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq
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