Margarine products quality monitoring using reflectance UV-VIS-SWNIR spectroscopy

Margarine is a term that can indicate any of a wide range of butter substitutes. Due to the great diversity of the raw material, margarine end-product quality characteristics are expected to be highly diversified. This article proposes the use of reflectance UV-VIS-SWNIR spectroscopy to monitor the margarine end-product quality properties. The main effort in this work was the development of a fast monitoring procedure to assess the quality of the manufactured margarines. 
The study was performed on two margarine products: regular margarine (less than 80% fat) and reduced-fat margarine (less than 60% fat). The nine product samples were collected during the production line normal operating conditions on different days. The samples had the surface cleaned in order to remove any sign of oxidized material. Then, spectra were collected by a reflectance probe normal to the sample surface. The samples temperature was recorded (10.0± 2.0ºC) and the probe-sample distance was kept constant for all the samples. The integration time was set to 40s for the collection of the five UV/VIS spectra per samples; the three VIS/NIR spectra per sample were collected using a 10s integration time.
The data analysis was performed on each product and for each spectral range independently. The spectra were normalized by its maximum intensity and the corrected for using a robust multiplicative scatter correction algorithm. A principal component analysis was performed to the pre-process spectra and the multivariate statistical process control limits were determined with bootstrap for each product/spectral range.
Results show that UV-VIS-SWNIR reflectance spectroscopy provides a quick and fast assessment of these products characteristics and thus it can be used as an indication of the overall product variability

Multiwavelength active optics Shack-Hartmann sensor for seeing and turbulence outer scale monitoring

Real-time seeing and outer scale estimation at the location of the focus of a telescope is fundamental for the adaptive optics systems dimensioning and performance prediction, as well as for the operational aspects of instruments. This study attempts to take advantage of multiwavelength long exposure images to instantaneously and simultaneously derive the turbulence outer scale and seeing from the full-width at half-maximum (FWHM) of seeing-limited images taken at the focus of a telescope. These atmospheric parameters are commonly measured in most observatories by different methods located away from the telescope platform, and thus differing from the effective estimates at the focus of a telescope, mainly because of differences in pointing orientation, height above the ground, or local seeing bias (dome contribution). Long exposure images can either directly be provided by any multiwavelength scientific imager or spectrograph, or alternatively from a modified active optics Shack-Hartmann sensor (AOSH). From measuring simultaneously the AOSH sensor spot point spread function FWHMs at different wavelengths, one can estimate the instantaneous outer scale in addition to seeing. Although AOSH sensors are specified to measure not spot sizes but slopes, real-time r0 and L0 measurements from spot FWHMs can be obtained at the critical location where they are needed with major advantages over scientific instrument images: insensitivity to the telescope field stabilization, and being continuously available. Assuming an alternative optical design allowing simultaneous multiwavelength images, AOSH sensor gathers all the advantages for real-time seeing and outer scale monitoring. With the substantial interest in the design of extremely large telescopes, such a system could have a considerable importance.Comment: Accepted for publication in A&A. arXiv admin note: text overlap with arXiv:1201.233

Selecting Quasars by their Intrinsic Variability

We present a new and simple technique for selecting extensive, complete and pure quasar samples, based on their intrinsic variability. We parametrize the single-band variability by a power-law model for the light-curve structure function, with amplitude A and power-law index gamma. We show that quasars can be efficiently separated from other non-variable and variable sources by the location of the individual sources in the A-gamma plane. We use ~60 epochs of imaging data, taken over ~5 years, from the SDSS stripe 82 (S82) survey, where extensive spectroscopy provides a reference sample of quasars, to demonstrate the power of variability as a quasar classifier in multi-epoch surveys. For UV-excess selected objects, variability performs just as well as the standard SDSS color selection, identifying quasars with a completeness of 90% and a purity of 95%. In the redshift range 2.5<z<3, where color selection is known to be problematic, variability can select quasars with a completeness of 90% and a purity of 96%. This is a factor of 5-10 times more pure than existing color-selection of quasars in this redshift range. Selecting objects from a broad griz color box without u-band information, variability selection in S82 can afford completeness and purity of 92%, despite a factor of 30 more contaminants than quasars in the color-selected feeder sample. This confirms that the fraction of quasars hidden in the 'stellar locus' of color-space is small. To test variability selection in the context of Pan-STARRS 1 (PS1) we created mock PS1 data by down-sampling the S82 data to just 6 epochs over 3 years. Even with this much sparser time sampling, variability is an encouragingly efficient classifier. For instance, a 92% pure and 44% complete quasar candidate sample is attainable from the above $griz$-selected catalog.Comment: 16 pages, 9 color figures and 5 tables - v3: Equations corrected and text updated (see Erratum for details of corrections). Erratum: http://adsabs.harvard.edu/abs/2010ApJ...721.1941S Original Paper: http://adsabs.harvard.edu/abs/2010ApJ...714.1194

Dynamic Illumination for Augmented Reality with Real-Time Interaction

Current augmented and mixed reality systems suffer a lack of correct illumination modeling where the virtual objects render the same lighting condition as the real environment. While we are experiencing astonishing results from the entertainment industry in multiple media forms, the procedure is mostly accomplished offline. The illumination information extracted from the physical scene is used to interactively render the virtual objects which results in a more realistic output in real-time. In this paper, we present a method that detects the physical illumination with dynamic scene, then uses the extracted illumination to render the virtual objects added to the scene. The method has three steps that are assumed to be working concurrently in real-time. The first is the estimation of the direct illumination (incident light) from the physical scene using computer vision techniques through a 360° live-feed camera connected to AR device. The second is the simulation of indirect illumination (reflected light) from the real-world surfaces to virtual objects rendering using region capture of 2D texture from the AR camera view. The third is defining the virtual objects with proper lighting and shadowing characteristics using shader language through multiple passes. Finally, we tested our work with multiple lighting conditions to evaluate the accuracy of results based on the shadow falling from the virtual objects which should be consistent with the shadow falling from the real objects with a reduced performance cost

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project

An HST/ACS investigation of the spatial and chemical structure and sub-structure of NGC 891, a Milky Way analogue

We present a structural analysis of NGC891, an edge-on galaxy that has long been considered to be an analogue of the Milky Way. Using starcounts derived from deep HST/ACS images, we detect the presence of a thick disk component in this galaxy with vertical scale height 1.44+/-0.03 kpc and radial scale length 4.8+/-0.1 kpc, only slightly longer than that of the thin disk. A stellar spheroid with a de Vaucouleurs-like profile is detected from a radial distance of 0.5 kpc to the edge of the survey at 25 kpc; the structure appears to become more flattened with distance, reaching q = 0.50 in the outermost halo region probed. The halo inside of 15 kpc is moderately metal-rich (median [Fe/H] ~ -1.1) and approximately uniform in median metallicity. Beyond that distance a modest chemical gradient is detected, with the median reaching [Fe/H] ~ -1.3 at 20 kpc. We find evidence for subtle, but very significant, small-scale variations in the median colour and density over the halo survey area. We argue that the colour variations are unlikely to be due to internal extinction or foreground extinction, and reflect instead variations in the stellar metallicity. Their presence suggests a startling conclusion: that the halo of this galaxy is composed of a large number of incompletely-mixed sub-populations, testifying to its origin in a deluge of small accretions.Comment: 21 pages, 16 figures, accepted for publication in MNRA

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

Procedure to Approximately Estimate the Uncertainty of Material Ratio Parameters due to Inhomogeneity of Surface Roughness

Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of reproducibility (homogeneity) of the specimen. This makes it difficult to discriminate between different values of single roughness parameters. Therefore uncertainty assessment methods are required that take all relevant aspects into account. In the literature this is scarcely performed and examples specific for parameters used in friction and wear are not yet given. We propose a procedure to derive the uncertainty from a single profile employing a statistical method that is based on the statistical moments of the amplitude distribution and the autocorrelation length of the profile. To show the possibilities and the limitations of this method we compare the uncertainty derived from a single profile with that derived from a high statistics experiment.Comment: submitted to Meas. Sci. Technol., 12 figure

The DEEP2 Galaxy Redshift Survey: The Voronoi-Delaunay Method Catalog of Galaxy Groups

We present a public catalog of galaxy groups constructed from the spectroscopic sample of galaxies in the fourth data release from the Deep Extragalactic Evolutionary Probe 2 (DEEP2) Galaxy Redshift Survey, including the Extended Groth Strip (EGS). The catalog contains 1165 groups with two or more members in the EGS over the redshift range 0 0.6 in the rest of DEEP2. Twenty-five percent of EGS galaxies and fourteen percent of high-z DEEP2 galaxies are assigned to galaxy groups. The groups were detected using the Voronoi-Delaunay method (VDM) after it has been optimized on mock DEEP2 catalogs following similar methods to those employed in Gerke et al. In the optimization effort, we have taken particular care to ensure that the mock catalogs resemble the data as closely as possible, and we have fine-tuned our methods separately on mocks constructed for the EGS and the rest of DEEP2. We have also probed the effect of the assumed cosmology on our inferred group-finding efficiency by performing our optimization on three different mock catalogs with different background cosmologies, finding large differences in the group-finding success we can achieve for these different mocks. Using the mock catalog whose background cosmology is most consistent with current data, we estimate that the DEEP2 group catalog is 72% complete and 61% pure (74% and 67% for the EGS) and that the group finder correctly classifies 70% of galaxies that truly belong to groups, with an additional 46% of interloper galaxies contaminating the catalog (66% and 43% for the EGS). We also confirm that the VDM catalog reconstructs the abundance of galaxy groups with velocity dispersions above ~300 km s^(–1) to an accuracy better than the sample variance, and this successful reconstruction is not strongly dependent on cosmology. This makes the DEEP2 group catalog a promising probe of the growth of cosmic structure that can potentially be used for cosmological tests