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

Comparative study of design: application to Engineering Design

A recent exploratory study examines design processes across domains and compares them. This is achieved through a series of interdisciplinary, participative workshops. A systematic framework is used to collect data from expert witnesses who are practising designers across domains from engineering through architecture to product design and fashion, including film production, pharmaceutical drugs, food, packaging, graphics and multimedia and software. Similarities and differences across domains are described which indicate the types of comparative analysis we have been able to do from our data. The paper goes further and speculates on possible lessons for selected areas of engineering design which can be drawn from comparison with processes in other domains. As such this comparative design study offers the potential for improving engineering design processes. More generally it is a first step in creating a discipline of comparative design which aims to provide a new rich picture of design processes

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&

The Drosophila Citrate Lyase Is Required for Cell Division during Spermatogenesis

The Drosophila melanogaster DmATPCL gene encodes for the human ATP Citrate Lyase (ACL) ortholog, a metabolic enzyme that from citrate generates glucose-derived Acetyl-CoA, which fuels central biochemical reactions such as the synthesis of fatty acids, cholesterol and acetylcholine, and the acetylation of proteins and histones. We had previously reported that, although loss of Drosophila ATPCL reduced levels of Acetyl-CoA, unlike its human counterpart, it does not affect global histone acetylation and gene expression, suggesting that its role in histone acetylation is either partially redundant in Drosophila or compensated by alternative pathways. Here, we describe that depletion of DmATPCL affects spindle organization, cytokinesis, and fusome assembly during male meiosis, revealing an unanticipated role for DmATPCL during spermatogenesis. We also show that DmATPCL mutant meiotic phenotype is in part caused by a reduction of fatty acids, but not of triglycerides or cholesterol, indicating that DmATPCL-derived Acetyl-CoA is predominantly devoted to the biosynthesis of fatty acids during spermatogenesis. Collectively, our results unveil for the first time an involvement for DmATPCL in the regulation of meiotic cell division, which is likely conserved in human cells

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

Depression and cardiovascular disease. the deep blue sea of women's heart

Cardiovascular disease (CVD) constitutes a leading worldwide health problem, with increasing evidence of differences between women and men both in epidemiology, pathophysiology, clinical management, and outcomes. Data from the literature suggest that women experience a doubled incidence of CVD related deaths, while angina, heart failure and stroke are increasingly prevalent in females. About 20–25% of women go through depression during their life, and depressive symptoms have been considered a relevant emergent, non-traditional risk factor for CVD in this part of the general population. Underlying mechanisms explaining the link between depression and CVD may range from behavioral to biological risk factors, including sympathetic nervous system hyperactivity and impairment in hypothalamic-pituitary-adrenal function. However, the neuroendocrine-driven background could only partially explain the differences mentioned above for chronic systemic inflammation, altered hemostasis and modulation of cardiac autonomic control. In addition, some evidence also suggests the existence of gender-specific differences in biological responses to mental stress. Given these premises, we here summarize the current knowledge about depression and CVD relationship in women, highlighting the sex differences in physiopathology, clinical presentation and treatments

Predicate Transformers and Linear Logic, yet another denotational model

International audienceIn the refinement calculus, monotonic predicate transformers are used to model specifications for (imperative) programs. Together with a natural notion of simulation, they form a category enjoying many algebraic properties. We build on this structure to make predicate transformers into a de notational model of full linear logic: all the logical constructions have a natural interpretation in terms of predicate transformers (i.e. in terms of specifications). We then interpret proofs of a formula by a safety property for the corresponding specification

nonlinear model predictive control strategy for steam turbine rotor stress

Abstract The paper proposes a Nonlinear Model Predictive Control strategy for the control of steam turbines rotor thermal stresses, which exploits the approximation of the turbine rotor as an infinite cylinder subjected to external convection. The Nonlinear Model Predictive Control allows optimizing the control strategy in the long term, by significantly reducing the machine start-up time during the power up ramp. This study proposes two different control strategies: the former one is based on the control of the Heat Transfer Coefficient, correlated to the inlet valve stroke. The latter one is based on the control of Heat Transfer Coefficient and the boiler steam temperature reference. Both strategies achieve good results in shortening the start-up time. The overall approach is validated and currently under development on Programmable Logic Controller platforms to the aim of code optimization