The Electrolysis of Metallic Chloride Solutions With the Use of Rotating Silver Anode and Mercury Cathode.

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Tungsten Hexabromide.

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Deep learning for real-time single-pixel video

Single-pixel cameras capture images without the requirement for a multi-pixel sensor, enabling the use of state-of-the-art detector technologies and providing a potentially low-cost solution for sensing beyond the visible spectrum. One limitation of single-pixel cameras is the inherent trade-off between image resolution and frame rate, with current compressive (compressed) sensing techniques being unable to support real-time video. In this work we demonstrate the application of deep learning with convolutional auto-encoder networks to recover real-time 128 × 128 pixel video at 30 frames-per-second from a single-pixel camera sampling at a compression ratio of 2%. In addition, by training the network on a large database of images we are able to optimise the first layer of the convolutional network, equivalent to optimising the basis used for scanning the image intensities. This work develops and implements a novel approach to solving the inverse problem for single-pixel cameras efficiently and represents a significant step towards real-time operation of computational imagers. By learning from examples in a particular context, our approach opens up the possibility of high resolution for task-specific adaptation, with importance for applications in gas sensing, 3D imaging and metrology

Speciation in Western North America: Lomatium as an Example of Diversification and Convergent Evolution

Species delimitations and understanding the processes that drive speciation are essential to nearly all aspects of human endeavor. Determining species boundaries traditionally used morphology. Phylogenetic analyses based on DNA sequence data provide a means to resolve species boundaries, as well as test hypotheses regarding the evolutionary processes. Numerous species radiations have occurred in Western North America. Among these are several plant groups such as Astragalus, Artemisia, and Lomatium. Recent phylogenetic analyses of Lomatium and related genera have demonstrated that many of the morphological characters used to delimit taxa have arisen multiple times and that most taxa are para- or polyphyletic. Here we examine one of the clades recovered in the Lomatium group of taxa that includes Lomatium triternatum and L. grayi. The several subspecific taxa of L. triternatum have not been recovered as monophyletic and L. grayi has a widespread habitat distribution that may indicate cryptic speciation. Previous analyses have not fully resolved phylogenetic relationships with strong support. In the present study we sample an additional four loci (three chloroplast and one nuclear ribosomal) to improve the support for evolutionary relationships across this clade, resolve species boundaries, and test hypotheses on the evolution of morphological traits

OPTN recruitment to a Golgi-proximal compartment regulates immune signalling and cytokine secretion

Optineurin (OPTN) is a multifunctional protein involved in autophagy, secretion as well as NF-κB and IRF3 signalling and OPTN mutations are associated with several human diseases. Here we show that, in response to viral RNA, OPTN translocates to foci in the perinuclear region, where it negatively regulates NF-κB and IRF3 signalling pathways and downstream pro-inflammatory cytokine secretion. These OPTN foci consist of a tight cluster of small membrane vesicles, which are positive for ATG9A. Disease mutations linked to POAG cause aberrant foci formation in the absence of stimuli, which correlates with the ability of OPTN to inhibit signalling. Using proximity labelling proteomics, we identify the LUBAC complex, CYLD and TBK1 as part of the OPTN interactome and show that these proteins are recruited to this OPTN-positive perinuclear compartment. Our work uncovers a crucial role for OPTN in dampening NF-κB and IRF3 signalling through the sequestration of LUBAC and other positive regulators in this viral RNA-induced compartment leading to altered pro-inflammatory cytokine secretion

Exploring Eye Movements in Patients with Glaucoma When Viewing a Driving Scene

Background: Glaucoma is a progressive eye disease and a leading cause of visual disability. Automated assessment of the visual field determines the different stages in the disease process: it would be desirable to link these measurements taken in the clinic with patient's actual function, or establish if patients compensate for their restricted field of view when performing everyday tasks. Hence, this study investigated eye movements in glaucomatous patients when viewing driving scenes in a hazard perception test (HPT). Methodology/Principal Findings: The HPT is a component of the UK driving licence test consisting of a series of short film clips of various traffic scenes viewed from the driver's perspective each containing hazardous situations that require the camera car to change direction or slow down. Data from nine glaucomatous patients with binocular visual field defects and ten age-matched control subjects were considered (all experienced drivers). Each subject viewed 26 different films with eye movements simultaneously monitored by an eye tracker. Computer software was purpose written to pre-process the data, co-register it to the film clips and to quantify eye movements and point-of-regard (using a dynamic bivariate contour ellipse analysis). On average, and across all HPT films, patients exhibited different eye movement characteristics to controls making, for example, significantly more saccades (P<0.001; 95% confidence interval for mean increase: 9.2 to 22.4%). Whilst the average region of ‘point-of-regard’ of the patients did not differ significantly from the controls, there were revealing cases where patients failed to see a hazard in relation to their binocular visual field defect. Conclusions/Significance: Characteristics of eye movement patterns in patients with bilateral glaucoma can differ significantly from age-matched controls when viewing a traffic scene. Further studies of eye movements made by glaucomatous patients could provide useful information about the definition of the visual field component required for fitness to drive

Raising a Small Flock of Sheep in Ohio

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Deep learning optimized single-pixel LiDAR

Interest in autonomous transport has led to a demand for 3D imaging technologies capable of resolving fine details at long range. Light detection and ranging (LiDAR) systems have become a key technology in this area, with depth information typically gained through time-of-flight photon-counting measurements of a scanned laser spot. Single-pixel imaging methods offer an alternative approach to spot-scanning, which allows a choice of sampling basis. In this work, we present a prototype LiDAR system, which compressively samples the scene using a deep learning optimized sampling basis and reconstruction algorithms. We demonstrate that this approach improves scene reconstruction quality compared to an orthogonal sampling method, with reflectivity and depth accuracy improvements of 57% and 16%, respectively, for one frame per second acquisition rates. This method may pave the way for improved scan-free LiDAR systems for driverless cars and for fully optimized sampling to decision-making pipelines

ViCTree: an automated framework for taxonomic classification from protein sequences

Motivation: The increasing rate of submission of genetic sequences into public databases is providing a growing resource for classifying the organisms that these sequences represent. To aid viral classification, we have developed ViCTree, which automatically integrates the relevant sets of sequences in NCBI GenBank and transforms them into an interactive maximum likelihood phylogenetic tree that can be updated automatically. ViCTree incorporates ViCTreeView, which is a JavaScript-based visualisation tool that enables the tree to be explored interactively in the context of pairwise distance data. Results: To demonstrate utility, ViCTree was applied to subfamily Densovirinae of family Parvoviridae. This led to the identification of six new species of insect virus. Availability: ViCTree is open-source and can be run on any Linux- or Unix-based computer or cluster. A tutorial, the documentation and the source code are available under a GPL3 license, and can be accessed at http://bioinformatics.cvr.ac.uk/victree_web/