Unsupervised Training for 3D Morphable Model Regression

We present a method for training a regression network from image pixels to 3D morphable model coordinates using only unlabeled photographs. The training loss is based on features from a facial recognition network, computed on-the-fly by rendering the predicted faces with a differentiable renderer. To make training from features feasible and avoid network fooling effects, we introduce three objectives: a batch distribution loss that encourages the output distribution to match the distribution of the morphable model, a loopback loss that ensures the network can correctly reinterpret its own output, and a multi-view identity loss that compares the features of the predicted 3D face and the input photograph from multiple viewing angles. We train a regression network using these objectives, a set of unlabeled photographs, and the morphable model itself, and demonstrate state-of-the-art results.Comment: CVPR 2018 version with supplemental material (http://openaccess.thecvf.com/content_cvpr_2018/html/Genova_Unsupervised_Training_for_CVPR_2018_paper.html

Long-term variability of CO2 and O in the Mars upper atmosphere from MRO radio science data

We estimate the annual variability of CO2 and O partial density using approximately 6years of Mars Reconnaissance Orbiter (MRO) radio science data from August 2006 to January 2012, which cover three full Martian years (from the northern hemisphere summer of 28 to the northern hemisphere summer of 31). These two elements are the dominant species at the MRO periapsis altitude, constituting about 70-80% of the total density. We report the recovered annual cycle of CO2 and the annual and seasonal cycle of O in the upper atmosphere. Although no other observations are available at those altitudes, our results are in good agreement with the density measurements of the Mars Express Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars, which uses stellar occultations between 60 and 130km to determine the CO2 variability, and with the Mars Global Reference Atmospheric Model 2010 for the O annual and seasonal variabilities. Furthermore, the updated model provides more reasonable MRO drag coefficients (CD), which are estimated to absorb mismodeling in the atmospheric density prediction. The higher content of dust in the atmosphere due to dust storms increases the density, so the CDs should compensate for this effect. The correlation between the drag coefficient and the dust optical depth, measured by the Mars Odyssey Thermal Emission Imaging System (THEMIS) instrument, increases from 0.4 to 0.8 with the a priori and adjusted models, respectively. The trend of CDs not only confirms a substantial improvement in the prediction of the atmospheric density with the updated model but also provides useful information for local dust storms, near MRO periapsis, that cannot be measured by the opacity level since THEMIS does not always sample the southern hemisphere evenly

Nanoroughness, Surface Chemistry and Drug Delivery Control by Atmospheric Plasma Jet on Implantable Devices

Implantable devices need specific tailored surface morphologies and chemistries to interact with the living systems or to actively induce a biological response also by the release of drugs or proteins. These customised requirements foster technologies that can be implemented in additive manufacturing systems. Here we present a novel approach based on spraying processes that allows to control separately topographic features in the submicron range ( 3d 60 nm - 2 \ub5m), ammine or carboxylic chemistry and fluorophore release even on temperature sensitive biodegradable polymers such as polycaprolactone (PCL). We developed a two-steps process with a first deposition of 220 nm silica and poly(lactic-co-glycolide) (PLGA) fluorescent nanoparticles by aerosol followed by the deposition of a fixing layer by atmospheric pressure plasma jet (APPJ). The nanoparticles can be used to create the nano-roughness and to include active molecule release, while the capping layer ensures stability and the chemical functionalities. The process is enabled by a novel APPJ which allows deposition rates of 10 - 20 nm\ub7s-1 at temperatures lower than 50 \ub0C using argon as process gas. This approach was assessed on titanium alloys for dental implants and on PCL films. The surfaces were characterized by FT-IR, AFM and SEM. Titanium alloys were tested with pre-osteoblasts murine cells line, while PCL film with fibroblasts. Cell behaviour was evaluated by viability and adhesion assays, protein adsorption, cell proliferation, focal adhesion formation and SEM. The release of a fluorophore molecule was assessed in the cell growing media, simulating a drug release. Osteoblast adhesion on the plasma treated materials increased by 20% with respect to commercial titanium alloys implants. Fibroblast adhesion increased by a 100% compared to smooth PCL substrate. The release of the fluorophore by the dissolution of the PLGA nanoparticles was verified and the integrity of the encapsulated drug model confirmed

New Analysis of Mercury Laser Altimeter Crossovers to Improve Geodetic Constraints by MESSENGER

No abstract availabl

Hierarchical progressive surveys. Multi-resolution HEALPix data structures for astronomical images, catalogues, and 3-dimensional data cubes

Scientific exploitation of the ever increasing volumes of astronomical data requires efficient and practical methods for data access, visualisation, and analysis. Hierarchical sky tessellation techniques enable a multi-resolution approach to organising data on angular scales from the full sky down to the individual image pixels. Aims. We aim to show that the Hierarchical progressive survey (HiPS) scheme for describing astronomical images, source catalogues, and three-dimensional data cubes is a practical solution to managing large volumes of heterogeneous data and that it enables a new level of scientific interoperability across large collections of data of these different data types. Methods. HiPS uses the HEALPix tessellation of the sphere to define a hierarchical tile and pixel structure to describe and organise astronomical data. HiPS is designed to conserve the scientific properties of the data alongside both visualisation considerations and emphasis on the ease of implementation. We describe the development of HiPS to manage a large number of diverse image surveys, as well as the extension of hierarchical image systems to cube and catalogue data. We demonstrate the interoperability of HiPS and Multi-Order Coverage (MOC) maps and highlight the HiPS mechanism to provide links to the original data. Results. Hierarchical progressive surveys have been generated by various data centres and groups for ~200 data collections including many wide area sky surveys, and archives of pointed observations. These can be accessed and visualised in Aladin, Aladin Lite, and other applications. HiPS provides a basis for further innovations in the use of hierarchical data structures to facilitate the description and statistical analysis of large astronomical data sets.Comment: 21 pages, 6 figures. Accepted for publication in Astronomy & Astrophysic

Postharvest loss in the supply chain for vegetables - The case of tomato, yardlong bean, cucumber and chili in Lao PDR

AVRDC Publication 06-684Christian Genova II, Katinka Weinberger, Thongsavath Chanthasombath, Bouthsakone Inthalungdsee, Kham Sanatem, Kethongsa Somsa