Double shear layer evolution on the non-uniform computational mesh

This paper considers the canonical problem of a thin shear layer evolution at Reynolds number Re = 400000 using the novel Compact Accurately Boundary Adjusting high-Resolution Technique (CABARET). The study is focused on the effect of the specific mesh refinement in the high shear rate areas on the flow properties under the influence of the developing instability. The original sequence of computational meshes (256^2, 512^2, 1024^2, 2048^2 cells) is modified using an iterative refinement algorithm based on the hyperbolic tangent. The properties of the solutions obtained are discussed in terms of the initial momentum thickness and the initial vorticity thickness, viscous and dilatational dissipation rates and also integral enstrophy. The growth rate for the most unstable mode depending on the mesh resolution is considered. In conclusion the accuracy of calculated mesh functions is estimated via L1, L2, L∞ norms.

Potential of High-Resolution Mass Spectrometry for the Detection of Drugs and Metabolites in Hair: Methoxetamine in a Real Forensic Case

The analysis of drugs of abuse in hair and other biological matrices of forensic interest requires great selectivity and sensitivity. This is done traditionally through target analysis, with one or more analytical methods, or with different and specific preanalytical phases, and complex procedures performed by the toxicological laboratories, and there is no exception with ketamine-like compounds, such as methoxetamine, a new psychoactive substance whose use has increased in the last decades, and continues to grow quickly year by year. More validated methods of analysis are needed to detect these substances in low concentrations selectively. Reanalyzing the samples of a former case of a polydrug consumer accused of a crime against public health in Spain, five metabolites of methoxetamine (normethoxetamine, O-desmethylmethoxetamine, dehydromethoxetamine, dihydronormethoxetamine and hydroxynormethoxetamine) were tentatively detected using a high-resolution technique, i.e., liquid chromatography coupled to high-resolution mass spectrometry (LC–HR-MS-MS). The highest analytical selectivity of LC–HR-MS-MS method together a universal and simpler pretreatment stages has demonstrated to allow faster analysis and more sensitivity than the one performed traditionally at the INTCF laboratories, which was gas chromatography coupled to mass spectrometry.

Orientation analysis of pentacene molecules in organic field-effect transistor devices using polarization-dependent Raman spectroscopy

Pentacene, an organic molecule, is a promising material for high-performance field effect transistors due to its high charge carrier mobility in comparison to usual semiconductors. However, the charge carrier mobility is strongly dependent on the molecular orientation of pentacene in the active layer of the device, which is hard to investigate using standard techniques in a real device. Raman scattering, on the other hand, is a high-resolution technique that is sensitive to the molecular orientation. In this work, we investigated the orientation distribution of pentacene molecules in actual transistor devices by polarization-dependent Raman spectroscopy and correlated these results with the performance of the device. This study can be utilized to understand the distribution of molecular orientation of pentacene in various electronic devices and thus would help in further improving their performances.

A Lagrangian Particle Algorithm (SPH) for an Autocatalytic Reaction Model with Multicomponent Reactants

For the numerical simulation of convection-dominated reacting flow problems governed by convection-reaction equations, grids-based Eulerian methods may cause different degrees of either numerical dissipation or unphysical oscillations. In this paper, a Lagrangian particle algorithm based on the smoothed particle hydrodynamics (SPH) method is proposed for convection-reaction equations and is applied to an autocatalytic reaction model with multicomponent reactants. Four typical Eulerian methods are also presented for comparison, including the high-resolution technique with the Superbee flux limiter, which has been considered to be the most appropriate technique for solving convection-reaction equations. Numerical results demonstrated that when comparing with traditional first- and second-order schemes and the high-resolution technique, the present Lagrangian particle algorithm has better numerical accuracy. It can correctly track the moving steep fronts without suffering from numerical diffusion and spurious oscillations.

Autometa: Automated extraction of microbial genomes from individual shotgun metagenomes

MotivationShotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of “binning” where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. Existing methods, however, suffer from: (1) reliance on human pattern recognition, which is inherently unscalable; (2) requirement for multiple co-assembled metagenomes, which degrades assembly quality due to strain variance; and (3) assumption of prior host genome removal not feasible for non-model hosts. We therefore devised a fully-automated pipeline, termed “Autometa,” to address these issues. Results: Autometa implements a method for taxonomic partitioning of contigs based on predicted protein homology, and this was shown to vastly improve binning in host-associated and complex metagenomes. Autometa’s method of automated clustering, based on Barnes-Hut Stochastic Neighbor Embedding (BH-tSNE) and DBSCAN, was shown to be highly scalable, outperforming other binning pipelines in complex simulated datasets.Availability and implementationAutometa is freely available at https://bitbucket.org/jasonckwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3)[email protected] informationSupplementary data are available attached to this article at https://biorxiv.org

Enhanced FIB-SEM systems for large-volume 3D imaging

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 106 µm3. These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.