Antenna array at focal plane of reflector with coupling network for beam switching Patent

Antenna array at focal plane of reflector with coupling network for beam switchin

Tracking antenna system Patent

Tracking antenna system with array for synchronous satellite or ground based rada

Deep learning with convolutional neural networks for decoding and visualization of EEG pathology

We apply convolutional neural networks (ConvNets) to the task of distinguishing pathological from normal EEG recordings in the Temple University Hospital EEG Abnormal Corpus. We use two basic, shallow and deep ConvNet architectures recently shown to decode task-related information from EEG at least as well as established algorithms designed for this purpose. In decoding EEG pathology, both ConvNets reached substantially better accuracies (about 6% better, ~85% vs. ~79%) than the only published result for this dataset, and were still better when using only 1 minute of each recording for training and only six seconds of each recording for testing. We used automated methods to optimize architectural hyperparameters and found intriguingly different ConvNet architectures, e.g., with max pooling as the only nonlinearity. Visualizations of the ConvNet decoding behavior showed that they used spectral power changes in the delta (0-4 Hz) and theta (4-8 Hz) frequency range, possibly alongside other features, consistent with expectations derived from spectral analysis of the EEG data and from the textual medical reports. Analysis of the textual medical reports also highlighted the potential for accuracy increases by integrating contextual information, such as the age of subjects. In summary, the ConvNets and visualization techniques used in this study constitute a next step towards clinically useful automated EEG diagnosis and establish a new baseline for future work on this topic.Comment: Published at IEEE SPMB 2017 https://www.ieeespmb.org/2017

A decomposition theorem for compact groups with application to supercompactness

We show that every compact connected group is the limit of a continuous inverse sequence, in the category of compact groups, where each successor bonding map is either an epimorphism with finite kernel or the projection from a product by a simple compact Lie group. As an application, we present a proof of an unpublished result of Charles Mills from 1978: every compact group is supercompact.Comment: 12 page

Structure of a Complete ATP Synthase Dimer Reveals the Molecular Basis of Inner Mitochondrial Membrane Morphology

We determined the structure of a complete, dimeric F1Fo-ATP synthase from yeast Yarrowia lipolytica mitochondria by a combination of cryo-EM and X-ray crystallography. The final structure resolves 58 of the 60 dimer subunits. Horizontal helices of subunit a in Fo wrap around the c-ring rotor, and a total of six vertical helices assigned to subunits a, b, f, i, and 8 span the membrane. Subunit 8 (A6L in human) is an evolutionary derivative of the bacterial b subunit. On the lumenal membrane surface, subunit f establishes direct contact between the two monomers. Comparison with a cryo-EM map of the F1Fo monomer identifies subunits e and g at the lateral dimer interface. They do not form dimer contacts but enable dimer formation by inducing a strong membrane curvature of ∼100°. Our structure explains the structural basis of cristae formation in mitochondria, a landmark signature of eukaryotic cell morphology

Radio Observations of the Supernova Remnant Candidate G312.5-3.0

The radio images from the Parkes-MIT-NRAO (PMN) Southern Sky Survey at 4850 MHz have revealed a number of previously unknown radio sources. One such source, G312.5-3.0 (PMN J1421-6415), has been observed using the multi-frequency capabilities of the Australia Telescope Compact Array (ATCA) at frequencies of 1380 MHz and 2378 MHz. Further observations of the source were made using the Molonglo Observatory Synthesis Telescope (MOST) at a frequency of 843 MHz. The source has an angular size of 18 arcmin and has a distinct shell structure. We present the reduced multi-frequency observations of this source and provide a brief argument for its possible identification as a supernova remnant.Comment: 5 pages, 5 figures, Accepted for publication in MNRA

Two phase transitions in (s+id)-wave Bardeen-Cooper-Schrieffer superconductivity

We establish universal behavior in temperature dependencies of some observables in $(s+id)$-wave BCS superconductivity in the presence of a weak $s$ wave. There also could appear a second second-order phase transition. As temperature is lowered past the usual critical temperature $T_c$, a less ordered superconducting phase is created in $d$ wave, which changes to a more ordered phase in $(s+id)$ wave at $T_{c1}$ ($< T_c$). The presence of two phase transitions manifest in two jumps in specific heat at $T_c$ and $T_{c1}$. The temperature dependencies of susceptibility, penetration depth, and thermal conductivity also confirm the new phase transition.Comment: 6 pages, 5 post-script figures

Far-flung Filaments of Ejecta in the Young Supernova Remnant G292.0+1.8

New optical images of the young SNR G292.0+1.8, obtained from the 0.9-m telescope at CTIO, show a more extensive network of filaments than had been known previously. Filaments emitting in [O III] are distributed throughout much of the 8 arcmin diameter shell seen in X-ray and radio images, including a few at the very outermost shell limits. We have also detected four small complexes of filaments that show [S II] emission along with [OIII]. In a single long-slit spectrum we find variations of almost an order of magnitude in the relative strengths of oxygen and sulfur lines, which must result from abundance variations. None of the filaments, with or without [S II], shows any evidence for hydrogen, so all appear to be fragments of pure SN ejecta. The [S II] filaments provide the first evidence for undiluted products of oxygen burning in the ejecta from the supernova that gave rise to G292.0+1.8. Some oxygen burning must have occurred, but the paucity of [S II]-emitting filaments suggests that either the oxygen burning was not extensive or that most of its products have yet to be excited. Most of the outer filaments exhibit radial, pencil-like morphologies that suggest an origin as Rayleigh-Taylor fingers of ejecta, perhaps formed during the explosion. Simulations of core-collapse supernovae predict such fingers, but these have never before been so clearly observed in a young SNR. The total flux from the SNR in [OIII] 5007 is 5.4 * 10**-12 ergs/cm**2/s. Using a distance of 6 kpc and an extinction correction corresponding to E(B-V) = 0.6 (lower than previous values but more consistent both with our data and radio and X-ray estimates of NH), this leads to a luminosity of 1.6 * 10**35 ergs/s in the 5007 Ang. line.Comment: 32 pages including 10 figures, and 3 tables, accepted for publication in AJ. Vol 132, July 2006. Higher resolution versions of the figures and a pdf of the manuscript can be found at http://www-int.stsci.edu/~long/papers/g292_optical

Can virtual nature improve patient experiences and memories of dental treatment? A study protocol for a randomized controlled trial

Background Dental anxiety and anxiety-related avoidance of dental care create significant problems for patients and the dental profession. Distraction interventions are used in daily medical practice to help patients cope with unpleasant procedures. There is evidence that exposure to natural scenery is beneficial for patients and that the use of virtual reality (VR) distraction is more effective than other distraction interventions, such as watching television. The main aim of this randomized controlled trial is to determine whether the use of VR during dental treatment can improve the overall dental experience and recollections of treatment for patients, breaking the negative cycle of memories of anxiety leading to further anxiety, and avoidance of future dental appointments. Additionally, the aim is to test whether VR benefits dental patients with all levels of dental anxiety or whether it could be especially beneficial for patients suffering from higher levels of dental anxiety. The third aim is to test whether the content of the VR distraction can make a difference for its effectiveness by comparing two types of virtual environments, a natural environment and an urban environment. Methods/design The effectiveness of VR distraction will be examined in patients 18 years or older who are scheduled to undergo dental treatment for fillings and/or extractions, with a maximum length of 30 minutes. Patients will be randomly allocated into one of three groups. The first group will be exposed to a VR of a natural environment. The second group will be exposed to a VR of an urban environment. A third group consists of patients who receive standard care (control group). Primary outcomes relate to patients’ memories of the dental treatment one week after treatment: (a) remembered pain, (b) intrusive thoughts and (c) vividness of memories. Other measures of interest are the dental experience, the treatment experience and the VR experience. Trial registration Current Controlled Trials ISRCTN4144280

CARBOTRAF: A decision Support system for reducing pollutant emissions by adaptive traffic management

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC