Design, Simulation and Manufacturing a CFRP Prototype Mirror for Active/Adaptive Optics

In this work, we are aiming to reduce the mass of large precision mirrors for space missions by using space approved composite materials. We report the development of an active/adaptive optics prototype of carbon fiber reinforced polymer mirrors using a pre-impregnated (pre-preg) composite MTM44-1/IMS65. The carbon fiber mirror has 16 layers of carbon fiber and one layer of polishable resin which compensate the well-known problem of ‘’fiber print through’’. The development of a fabrication method, suited for creating a CFRP mirror is outlined. As all materials will change properties to some degree, during cool down to cryogenic temperatures, FEA model is employed to investigate the change on overall form and figure of the mirror. Characterizing this dimensional change is critical in insuring that any mirror material can be used in this environment and, if required, corrected either by utilizing a deformable mirror control systems or by correction in the optical system. Two different piezoelectric actuators are modelled and used to create an active composite reflector. Push actuators and micro fiber composite (MFC) actuators are simulated and the performance of them are compared by surface deformation and dynamic response

World cities in the Pacific Rim: a new global test of regional coherence

A new evaluation of the Pacific Rim concept is presented. The originality of this test for regional coherence is to be found in the basic units being analysed: cities instead of states. Based on a theoretical framework that identifies world city and world city network formation in terms of the office networks of advanced producer service firms, we use a principal components analysis to analyse a data set of 28 Pacific Rim cities and 46 global service firms. This identifies five main groupings of cities in terms of similar mixes of corporate service firms: a western Rim group; a group of ‘old Commonwealth’ cities; a market communist group of cities; Tokyo as a global city; and US cities as a specific separate group. These results confirm the numerous earlier studies that were sceptical of the existence of a coherent Pacific Rim region. However, the particular approach adopted here allows us to identify the Pacific Rim generically as a particularly pernicious construct. We conclude that the Pacific Rim is a geographical chaotic conception

The assembly and alignment of the 4MOST Wide Field Corrector

The 4-metre Multi-Object Spectroscopic Telescope (4MOST) is a fibre-fed multi-object spectrograph for the VISTA telescope at the ESO Paranal Observatory in Chile. The goal of the 4MOST project is to create a general-purpose and highly efficient spectroscopic survey facility for astronomers in the 4MOST consortium and the ESO community. The instrument itself will record 2436 simultaneous spectra over a ∼4.2 square degree field of view and consists of an optical Wide-Field Corrector (WFC), a fibre positioner system based on a tilting spine design, and three spectrographs giving both high and low spectral dispersion. The WFC comprises of 6 lenses grouped into 4 elements, 2 of which are cemented doublets that act as an atmospheric dispersion corrector (ADC). The first lens element is 0.9m in diameter whilst the diameter of the other elements is 0.65m. For the instrument to meet its science goals, each lens needs to be aligned to ∼50µm – a major challenge. This is achieved using contact metrology methods supplemented by pencil beam laser probes. In particular, a novel off-axis laser beam system has been implemented to test the optics’ alignment before and after shipment. This paper details the alignment and assembly methods and presents the latest results on the achieved lens positioning and projected performance of the WF

Fabrication of the DESI Corrector Lenses

The Dark Energy Spectroscopic Instrument (DESI) is under construction to measure the expansion history of the Universe using the Baryon Acoustic Oscillation technique. The spectra of 35 million galaxies and quasars over 14000 square degrees will be measured during the life of the experiment. A new prime focus corrector for the KPNO Mayall telescope will deliver light to 5000 fiber optic positioners. The fibers in turn feed ten broad-band spectrographs. We describe the DESI corrector optics, a series of six fused silica and borosilicate lenses. The lens diameters range from 0.8 to 1.1 meters, and their weights 84 to 237 kg. Most lens surfaces are spherical, and two are challenging 10th-order polynomial aspheres. The lenses have been successfully polished and treated with an antireflection coating at multiple subcontractors, and are now being integrated into the DESI corrector barrel assembly at University College London. We describe the final performance of the lenses in terms of their various parameters, including surface figure, homogeneity, and others, and compare their final performance against the demanding DESI corrector requirements. Also we describe the reoptimization of the lens spacing in their corrector barrel after their final measurements are known. Finally we assess the performance of the corrector as a whole, compared to early budgeted estimates

Intestinal Tropism of a Betacoronavirus (Merbecovirus) in Nathusius’s Pipistrelle Bat (Pipistrellus nathusii), Its Natural Host

The emergence of several bat coronavirus-related disease outbreaks in human and domestic animals has fueled surveillance of coronaviruses in bats worldwide. However, little is known about how these viruses interact with their natural hosts. We demonstrate a Betacoronavirus (subgenus Merbecovirus), PN-βCoV, in the intestine of its natural host, Nathusius’s Pipistrelle Bat (Pipistrellus nathusii), by combining molecular and microscopy techniques. Eighty-eight P. nathusii bat carcasses were tested for PN-βCoV RNA by RT-qPCR, of which 25 bats (28%) tested positive. PN-βCoV RNA was more often detected in samples of the intestinal tract than in other sample types. In addition, viral RNA loads were higher in intestinal samples compared to other sample types, both on average and in each individual bat. In one bat, we demonstrated Merbecovirus antigen and PN-βCoV RNA expression in intestinal epithelium and the underlying connective tissue using immunohistochemistry and in situ hybridization, respectively. These results indicate that PN-βCoV has a tropism for the intestinal epithelium of its natural host, Nathusius’s Pipistrelle Bat, and imply that the fecal-oral route is a possible route of transmission.</p

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a investigation for maximising their effectiveness.We carry out a comparison between several common machine learning methods for galaxy classification (Convolutional Neural Network (CNN), K-nearest neighbour, LogisticRegression, Support Vector Machine, Random Forest, and Neural Networks) by using DarkEnergy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project(GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of _2,800 galaxies with visual classification from GZ1, we reach an accuracy of _0.99 for the morphological classification of Ellipticals and Spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals an the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually Lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both Es and Spirals.We confirm that _2.5% galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result)