Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

The rising popularity of intelligent mobile devices and the daunting computational cost of deep learning-based models call for efficient and accurate on-device inference schemes. We propose a quantization scheme that allows inference to be carried out using integer-only arithmetic, which can be implemented more efficiently than floating point inference on commonly available integer-only hardware. We also co-design a training procedure to preserve end-to-end model accuracy post quantization. As a result, the proposed quantization scheme improves the tradeoff between accuracy and on-device latency. The improvements are significant even on MobileNets, a model family known for run-time efficiency, and are demonstrated in ImageNet classification and COCO detection on popular CPUs.Comment: 14 pages, 12 figure

New first trimester crown-rump length's equations optimized by structured data collection from a French general population

--- Objectives --- Prior to foetal karyotyping, the likelihood of Down's syndrome is often determined combining maternal age, serum free beta-HCG, PAPP-A levels and embryonic measurements of crown-rump length and nuchal translucency for gestational ages between 11 and 13 weeks. It appeared important to get a precise knowledge of these scan parameters' normal values during the first trimester. This paper focused on crown-rump length. --- METHODS --- 402 pregnancies from in-vitro fertilization allowing a precise estimation of foetal ages (FA) were used to determine the best model that describes crown-rump length (CRL) as a function of FA. Scan measures by a single operator from 3846 spontaneous pregnancies representative of the general population from Northern France were used to build a mathematical model linking FA and CRL in a context as close as possible to normal scan screening used in Down's syndrome likelihood determination. We modeled both CRL as a function of FA and FA as a function of CRL. For this, we used a clear methodology and performed regressions with heteroskedastic corrections and robust regressions. The results were compared by cross-validation to retain the equations with the best predictive power. We also studied the errors between observed and predicted values. --- Results --- Data from 513 spontaneous pregnancies allowed to model CRL as a function of age of foetal age. The best model was a polynomial of degree 2. Datation with our equation that models spontaneous pregnancies from a general population was in quite agreement with objective datations obtained from 402 IVF pregnancies and thus support the validity of our model. The most precise measure of CRL was when the SD was minimal (1.83mm), for a CRL of 23.6 mm where our model predicted a 49.4 days of foetal age. Our study allowed to model the SD from 30 to 90 days of foetal age and offers the opportunity of using Zscores in the future to detect growth abnormalities. --- Conclusion --- With powerful statistical tools we report a good modeling of the first trimester embryonic growth in the general population allowing a better knowledge of the date of fertilization useful in the ultrasound screening of Down's syndrome. The optimal period to measure CRL and predict foetal age was 49.4 days (9 weeks of gestational age). Our results open the way to the detection of foetal growth abnormalities using CRL Zscores throughout the first trimester

Cosmology from HI galaxy surveys with the SKA

The Square Kilometer Array (SKA) has the potential to produce galaxy redshift surveys which will be competitive with other state of the art cosmological experiments in the next decade. In this chapter we summarise what capabilities the first and the second phases of the SKA will be able to achieve in its current state of design. We summarise the different cosmological experiments which are outlined in further detail in other chapters of this Science Book. The SKA will be able to produce competitive Baryonic Oscillation (BAOs) measurements in both its phases. The first phase of the SKA will provide similar measurements in optical and IR experiments with completely different systematic effects whereas the second phase being transformational in terms of its statistical power. The SKA will produce very accurate Redshift Space Distortions (RSD) measurements, being superior to other experiments at lower redshifts, due to the large number of galaxies. Cross correlations of the galaxy redshift data from the SKA with radio continuum surveys and optical surveys will provide extremely good calibration of photometric redshifts as well as extremely good bounds on modifications of gravity. Basing on a Principle Component Analysis (PCA) approach, we find that the SKA will be able to provide competitive constraint on dark energy and modified gravity models. Due to the large area covered the SKA it will be a transformational experiment in measuring physics from the largest scales such as non-Gaussian signals. Finally, the SKA might produce the first real time measurement of the redshift drift. The SKA will be a transformational machine for cosmology as it grows from an early Phase 1 to its full power

Outcome in patients perceived as receiving excessive care across different ethical climates : a prospective study in 68 intensive care units in Europe and the USA

Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Ethical climate and intention to leave among critical care clinicians : an observational study in 68 intensive care units across Europe and the United States

PurposeApart from organizational issues, quality of inter-professional collaboration during ethical decision-making may affect the intention to leave one's job. To determine whether ethical climate is associated with the intention to leave after adjustment for country, ICU and clinicians characteristics.MethodsPerceptions of the ethical climate among clinicians working in 68 adult ICUs in 12 European countries and the US were measured using a self-assessment questionnaire, together with job characteristics and intent to leave as a sub-analysis of the Dispropricus study. The validated ethical decision-making climate questionnaire included seven factors: not avoiding decision-making at end-of-life (EOL), mutual respect within the interdisciplinary team, open interdisciplinary reflection, ethical awareness, self-reflective physician leadership, active decision-making at end-of-life by physicians, and involvement of nurses in EOL. Hierarchical mixed effect models were used to assess associations between these factors, and the intent to leave in clinicians within ICUs, within the different countries.ResultsOf 3610 nurses and 1137 physicians providing ICU bedside care, 63.1% and 62.9% participated, respectively. Of 2992 participating clinicians, 782 (26.1%) had intent to leave, of which 27% nurses, 24% junior and 22.7% senior physicians. After adjustment for country, ICU and clinicians characteristics, mutual respect OR 0.77 (95% CI 0.66- 0.90), open interdisciplinary reflection (OR 0.73 [95% CI 0.62-0.86]) and not avoiding EOL decisions (OR 0.87 [95% CI 0.77-0.98]) were all associated with a lower intent to leave.ConclusionThis is the first large multicenter study showing an independent association between clinicians' intent to leave and the quality of the ethical climate in the ICU. Interventions to reduce intent to leave may be most effective when they focus on improving mutual respect, interdisciplinary reflection and active decision-making at EOL

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide (SO2). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO2. Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission