Scaling digital screen reading with one-shot learning and re-identification

Using only a mobile phone app, our objective is to cheaply retro-fit digital meters (e.g blood pressure, blood glucose or industrial gauges) with 'smart' data transfer capabilities. Using the mobile phone camera we build an app to securely and accurately transcribe information from digital meter screens. Only a single labelled training image of a target meter is required to build a custom screen reading module. Here we show how this can scale to potentially hundreds of different meters by learning to recognising the meter type so that the reading module can be automatically selected. This makes the system very easy for a user who would need to scan multiple different meter types. To this end, we build a CNN based system which runs in real-time on mobile device with very high read accuracy and meter recognition. Our contributions include (i) a method of one-shot training by synthesis through domain shift reduction, (ii) a deep embedding network for scale, translation and rotation invariant re-identification of digital meters, (iii) a highly accurate and efficient mobile phone app for recognising and parsing digital meter screens and (iv) release of a new digital meter re-identification dataset

The GSC-II-based survey of ancient cool white dwarfs I. The sample of spectroscopically confirmed WDs

The GSC-II white dwarf survey was designed to identify faint and high proper motion objects, which we used to define a new and independent sample of cool white dwarfs. With this survey we aim to derive new constraints on the halo white dwarf space density. Also, these data can provide information on the age of thick disk and halo through the analysis of the luminosity function. On the basis of astrometric and photometric parameters, we selected candidates with mu > 0.28 as/yr and R_F > 16 in an area of 1150 square degrees. Then, we separated white dwarfs from late type dwarfs and subdwarfs by means of the reduced proper motion diagram. Finally, spectroscopic follow-up observations were carried out to confirm the white dwarf nature of the selected candidates. We found 41 white dwarfs of which 24 are new discoveries. Here we present the full sample and for each object provide positions, absolute proper motions, photometry, and spectroscopy.Comment: 14 pages, 7 figures, submitted to A&

Samuel D. Gross, M.D. (1805-1884): an innovator, even in death.

Dr. Samuel Gross\u27 contributions to the field of surgery are well known and range from numerous clinical advances to pioneering scholarship and professional activities. Dr. Gross was ceaselessly ambitious and even remarked in his autobiography that his ‘‘conviction has always been that is far better for a man to wear out than to rust out.’’1 It is through this frame of motivation that Dr. Gross lived his life

Kinematic mental simulations in abduction and deduction

We present a theory, and its computer implementation, of how mental simulations underlie the abductions of informal algorithms and deductions from these algorithms. Three experiments tested the theory’s predictions, using an environment of a single railway track and a siding. This environment is akin to a universal Turing machine, but it is simple enough for nonprogrammers to use. Participants solved problems that required use of the siding to rearrange the order of cars in a train (experiment 1). Participants abduced and described in their own words algorithms that solved such problems for trains of any length, and, as the use of simulation predicts, they favored “while-loops” over “for-loops” in their descriptions (experiment 2). Given descriptions of loops of procedures, participants deduced the consequences for given trains of six cars, doing so without access to the railway environment (experiment 3). As the theory predicts, difficulty in rearranging trains depends on the numbers of moves and cars to be moved, whereas in formulating an algorithm and deducing its consequences, it depends on the Kolmogorov complexity of the algorithm. Overall, the results corroborated the use of a kinematic mental model in creating and testing informal algorithms and showed that individuals differ reliably in the ability to carry out these tasks

Planar Thinned Arrays: Optimization and Subarray Based Adaptive Processing

A new approach is presented for the optimized design of a planar thinned array; the proposed strategy works with single antenna elements or with small sets of different subarray types, properly located on a planar surface. The optimization approach is based on the maximization of an objective function accounting for side lobe level and considering a fixed number of active elements/subarrays. The proposed technique is suitable for different shapes of the desired output array, allowing the achievement of the desired directivity properties on the corresponding antenna pattern. The use of subarrays with a limited number of different shapes is relevant for industrial production, which would benefit from reduced design and manufacturing costs. The resulting modularity allows scalable antenna designs for different applications. Moreover, subarrays can be arranged in a set of subapertures, each connected to an independent receiving channel. Therefore, adaptive processing techniques could be applied to cope with and mitigate clutter echoes and external electromagnetic interferences. The performance of adaptive techniques with subapertures taken from the optimized thinned array is evaluated against assigned clutter and jamming scenarios and compared to the performance achievable considering a subarray based filled array with the same number of active elements

Sixteen years of bathymetry and waves at San Diego beaches.

Sustained, quantitative observations of nearshore waves and sand levels are essential for testing beach evolution models, but comprehensive datasets are relatively rare. We document beach profiles and concurrent waves monitored at three southern California beaches during 2001-2016. The beaches include offshore reefs, lagoon mouths, hard substrates, and cobble and sandy (medium-grained) sediments. The data span two energetic El Niño winters and four beach nourishments. Quarterly surveys of 165 total cross-shore transects (all sites) at 100 m alongshore spacing were made from the backbeach to 8 m depth. Monthly surveys of the subaerial beach were obtained at alongshore-oriented transects. The resulting dataset consists of (1) raw sand elevation data, (2) gridded elevations, (3) interpolated elevation maps with error estimates, (4) beach widths, subaerial and total sand volumes, (5) locations of hard substrate and beach nourishments, (6) water levels from a NOAA tide gauge (7) wave conditions from a buoy-driven regional wave model, and (8) time periods and reaches with alongshore uniform bathymetry, suitable for testing 1-dimensional beach profile change models

Parallaxes of southern extremely cool objects III : 118 L and T dwarfs

We present new results from the Parallaxes of Southern Extremely Cool dwarfs program to measure parallaxes, proper motions and multiepoch photometry of L and early T dwarfs. The observations were made on 108 nights over the course of 8 yr using the Wide Field Imager on the ESO 2.2m telescope. We present 118 new parallaxes of L and T dwarfs of which 52 have no published values and 24 of the 66 published values are preliminary estimates from this program. The parallax precision varies from 1.0 to 15.5mas with a median of 3.8mas. We find evidence for two objects with long term photometric variation and 24 new moving group candidates. We cross-match our sample to published photometric catalogues and find standard magnitudes in up to 16 pass-bands from which we build spectral energy distributions and H-R diagrams. This allows us to confirm the theoretically anticipated minimum in radius between stars and brown dwarfs across the hydrogen burning minimum mass. We find the minimum occurs between L2 and L6 and verify the predicted steep dependence of radius in the hydrogen burning regime and the gentle rise into the degenerate brown dwarf regime. We find a relatively young age of ~2 Gyr from the kinematics of our sample.Peer reviewedFinal Accepted Versio

Lung Ultrasound Findings and Endothelial Perturbation in a COVID-19 Low-Intensity Care Unit

Hypercoagulability and endothelial dysfunction related to inflammation have been clearly demonstrated in COVID-19. However, their influence on thromboembolism, lung alterations and mortality in low-intensity-care patients with COVID-19 is not completely clarified. Our aims were to evaluate the prevalence of deep vein thrombosis (DVT) with compressive ultrasound (CUS); to describe lung ultrasound (LUS) features; and to study coagulation, inflammatory and endothelial perturbation biomarkers in COVID-19 patients at low-intensity care unit admission. The predictive value of these biomarkers on mortality, need for oxygen support and duration of hospitalization was also evaluated. Of the 65 patients included, 8 were non-survivors. CUS was negative for DVT in all patients. LUS Soldati and Vetrugno scores were strongly correlated (rho = 0.95) with each other, and both significantly differed in patients who needed oxygen therapy vs. those who did not (Soldati p = 0.017; Vetrugno p = 0.023), with coalescent B lines as the most prevalent pattern in patients with a worse prognosis. Mean (SD) levels of thrombomodulin and VCAM-1 were higher in non-survivors than in survivors (7283.9 pg/mL (3961.9 pg/mL) vs. 4800.7 pg/mL (1771.0 pg/mL), p = 0.004 and 2299 ng/mL (730.35 ng/mL) vs. 1451 ng/mL (456.2 ng/mL), p < 0.001, respectively). Finally, in a multivariate analysis model adjusted for age, sex and Charlson score, VCAM-1 level increase was independently associated with death [OR 1.31 (1.06, 1.81; p = 0.036)]. In conclusion, in a cohort of mild COVID-19 patients, we found no DVT events despite the highly abnormal inflammatory, endothelial and coagulation parameters. The presence of lung alterations at admission could not predict outcome. The endothelial perturbation biomarker VCAM-1 emerged as a promising prognostic tool for mortality in COVID-19