A steerable UV laser system for the calibration of liquid argon time projection chambers

A number of liquid argon time projection chambers (LAr TPCs) are being built or are proposed for neutrino experiments on long- and short baseline beams. For these detectors, a distortion in the drift field due to geometrical or physics reasons can affect the reconstruction of the events. Depending on the TPC geometry and electric drift field intensity, this distortion could be of the same magnitude as the drift field itself. Recently, we presented a method to calibrate the drift field and correct for these possible distortions. While straight cosmic ray muon tracks could be used for calibration, multiple coulomb scattering and momentum uncertainties allow only a limited resolution. A UV laser instead can create straight ionization tracks in liquid argon, and allows one to map the drift field along different paths in the TPC inner volume. Here we present a UV laser feed-through design with a steerable UV mirror immersed in liquid argon that can point the laser beam at many locations through the TPC. The straight ionization paths are sensitive to drift field distortions, a fit of these distortion to the linear optical path allows to extract the drift field, by using these laser tracks along the whole TPC volume one can obtain a 3D drift field map. The UV laser feed-through assembly is a prototype of the system that will be used for the MicroBooNE experiment at the Fermi National Accelerator Laboratory (FNAL).

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.

Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity

Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform. This paper demonstrates that for ambulatory scenarios, where signal-to-noise ratios are below 10 dB, the performance in terms of repeatability of PAT measurements through characteristic points identification degrades drastically. Hence, we introduce a novel family of PAT estimators based on the parametric modeling of the anacrotic phase of a pressure pulse. In particular, we propose a parametric PAT estimator (TANH) that depicts high correlation with the Complior(R) characteristic point D1 (CC = 0.99), increases noise robustness and reduces by a five-fold factor the number of heartbeats required to obtain reliable PAT measurements.

Competitive fitness in coronaviruses is not correlated with size or number of double-membrane vesicles under reduced-temperature growth conditions.

Positive-stranded viruses synthesize their RNA in membrane-bound organelles, but it is not clear how this benefits the virus or the host. For coronaviruses, these organelles take the form of double-membrane vesicles (DMVs) interconnected by a convoluted membrane network. We used electron microscopy to identify murine coronaviruses with mutations in nsp3 and nsp14 that replicated normally while producing only half the normal amount of DMVs under low-temperature growth conditions. Viruses with mutations in nsp5 and nsp16 produced small DMVs but also replicated normally. Quantitative reverse transcriptase PCR (RT-PCR) confirmed that the most strongly affected of these, the nsp3 mutant, produced more viral RNA than wild-type virus. Competitive growth assays were carried out in both continuous and primary cells to better understand the contribution of DMVs to viral fitness. Surprisingly, several viruses that produced fewer or smaller DMVs showed a higher fitness than wild-type virus at the reduced temperature, suggesting that larger and more numerous DMVs do not necessarily confer a competitive advantage in primary or continuous cell culture. For the first time, this directly demonstrates that replication and organelle formation may be, at least in part, studied separately during infection with positive-stranded RNA virus. IMPORTANCE The viruses that cause severe acute respiratory syndrome (SARS), poliomyelitis, and hepatitis C all replicate in double-membrane vesicles (DMVs). The big question about DMVs is why they exist in the first place. In this study, we looked at thousands of infected cells and identified two coronavirus mutants that made half as many organelles as normal and two others that made typical numbers but smaller organelles. Despite differences in DMV size and number, all four mutants replicated as efficiently as wild-type virus. To better understand the relative importance of replicative organelles, we carried out competitive fitness experiments. None of these viruses was found to be significantly less fit than wild-type, and two were actually fitter in tests in two kinds of cells. This suggests that viruses have evolved to have tremendous plasticity in the ability to form membrane-associated replication complexes and that large and numerous DMVs are not exclusively associated with efficient coronavirus replication.

Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci

We undertook a meta-analysis of six Crohn's disease genome-wide association studies (GWAS) comprising 6,333 affected individuals (cases) and 15,056 controls and followed up the top association signals in 15,694 cases, 14,026 controls and 414 parent-offspring trios. We identified 30 new susceptibility loci meeting genome-wide significance (P < 5 × 10 ? ? ). A series of in silico analyses highlighted particular genes within these loci and, together with manual curation, implicated functionally interesting candidate genes including SMAD3, ERAP2, IL10, IL2RA, TYK2, FUT2, DNMT3A, DENND1B, BACH2 and TAGAP. Combined with previously confirmed loci, these results identify 71 distinct loci with genome-wide significant evidence for association with Crohn's disease.

CT screening and follow-up of lung nodules: effects of tube current-time setting and nodule size and density on detectability and of tube current-time setting on apparent size

The purpose of the study was to quantify and compare the effect of CT dose and of size and density of nodules on the detectability of lung nodules and to quantify the influence of CT dose on the size of the nodules.

Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47

Genome-wide association studies and candidate gene studies in ulcerative colitis have identified 18 susceptibility loci. We conducted a meta-analysis of six ulcerative colitis genome-wide association study datasets, comprising 6,687 cases and 19,718 controls, and followed up the top association signals in 9,628 cases and 12,917 controls. We identified 29 additional risk loci (P < 5 × 10(-8)), increasing the number of ulcerative colitis-associated loci to 47. After annotating associated regions using GRAIL, expression quantitative trait loci data and correlations with non-synonymous SNPs, we identified many candidate genes that provide potentially important insights into disease pathogenesis, including IL1R2, IL8RA-IL8RB, IL7R, IL12B, DAP, PRDM1, JAK2, IRF5, GNA12 and LSP1. The total number of confirmed inflammatory bowel disease risk loci is now 99, including a minimum of 28 shared association signals between Crohn's disease and ulcerative colitis.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

What is the optimal number of implants for fixed reconstructions: a systematic review

To assess the 5-year and 10-year survival and complication rates of implant-supported fixed reconstructions in partially and totally edentulous patients with regard to the optimal number and distribution of dental implants.

Effects of dietary supplementation with synthetic vitamin D-3 and 25-hydroxycholecalciferol on blood calcium and phosphate levels and performance in laying hens

We investigated the effects of different dietary vitamin D regimen on selected blood parameters in laying hens. Supplementation with vitamin D-3 only was compared with a combination of vitamin D-3 and its metabolite 25-hydroxy-cholecalciferol (25(OH)D-3). Blood concentrations of total calcium, phosphate and 25 (OH)D-3 were determined. Four thousand one-day-old LSL chicks were split in two treatment groups and distributed to eight pens. The control group was given a commercial animal diet containing 2800 IU synthetic vitamin D-3 in the starter feed and 2000 IU synthetic vitamin D-3 in the pullet feed. The experimental group was fed the same commercial diet in which half the synthetic vitamin D-3 content had been substituted with 25(OH)D-3 (Hy center dot D (R)). At 18 weeks of age, pullets were transferred to the layer house. At the ages of 11, 18 and 34 weeks, between 120 and 160 blood samples were collected from both the control and the experimental groups, respectively. The experimental group had higher levels of 25 (OH)D-3 than the control group at all three ages. Serum calcium levels did not differ between the treatment groups at any age. With the onset of laying, calcium levels rose significantly. Whereas blood serum concentration at 18 weeks was 3 mmol/L in both treatment groups, it increased to 8.32 mmol/L in the control group and to 8.66 mmol/L in the experimental group at week 34. At weeks 11 and 34, phosphate was significantly lower in the experimental group. In conclusion, HyD (R) significantly affected serum phosphate and 25(OH)D-3 levels. No effects of (25(OH)D-3 supplementation on performance, shell quality and fractures of keelbones were found.