Comparison of various methods to delineate blood vessels in retinal images

The blood vessels in the human retina are easily visualisable via digital fundus photography and provide an excellent window to the health of a patient affected by diseases of blood circulation such as diabetes. Diabetic retinopathy is identifiable through lesions of the vessels such as narrowing of the arteriole walls, beading of venules into sausage like structures and new vessel growth as an attempt to reperfuse ischaemic regions. Automated quantification of these lesions would be beneficial to diabetes research and to clinical practice, particularly for eye-screening programmes for the detection of eye-disease amongst diabetic persons

Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy

Automated image processing has the potential to assist in the early detection of diabetes, by detecting changes in blood vessel diameter and patterns in the retina. This paper describes the development of segmentation methodology in the processing of retinal blood vessel images obtained using non-mydriatic colour photography. The methods used include wavelet analysis, supervised classifier probabilities and adaptive threshold procedures, as well as morphology-based techniques. We show highly accurate identification of blood vessels for the purpose of studying changes in the vessel network that can be utilized for detecting blood vessel diameter changes associated with the pathophysiology of diabetes. In conjunction with suitable feature extraction and automated classification methods, our segmentation method could form the basis of a quick and accurate test for diabetic retinopathy, which would have huge benefits in terms of improved access to screening people for risk or presence of diabetes

Fabrication and mechanical testing of a new sandwich structure with carbon fiber network core

The aim is the fabrication and mechanical testing of sandwich structures including a new core material known as fiber network sandwich materials. As fabrication norms for such a material do not exist as such, so the primary goal is to reproduce successfully fiber network sandwich specimens. Enhanced vibration testing diagnoses the quality of the fabrication process. These sandwich materials possess low structural strength as proved by the static tests (compression, bending), but the vibration test results give high damping values, making the material suitable for vibro-acoustic applications where structural strength is of secondary importance e.g., internal panelling of a helicopter

Bioactive compounds, antioxidant activity, and minerals in flours prepared with tropical fruit peels

This study is aimed at performing the determination of bioactive compounds, antioxidant activity, and the identification of the minerals in the flours produced with the tropical fruit peels of mango, papaya, melon, and pineapple. The results showed that the papaya peel flour has the highest amount of ascorbic acid and lycopene when compared with the other studied flours. The mango peel flour has a high content of total extractable polyphenols and a high antioxidant activity. Regarding the mineral content, the by-product of melon stood out with 523.24±26.12 mg/100 g of potassium, 104.15±3.52 mg/100 g of calcium and 6.62±0.30 mg/100 g of iron. The flours prepared with mango, papaya, melon, and pineapple peels are potential sources of bioactive compounds and minerals, also presenting good antioxidant activity, being, therefore, recommended to be used in food products to improve the nutritional quality of the product

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Palynological evidence for environmental and climatic change in the lower Guadiana valley, Portugal, during the last 13 000 years

Pollen analysis of a 48 m AMS radiocarbon-dated sediment sequence from the Guadiana estuary provides the first record of Lateglacial and Holocene vegetation history in the Algarve province of Portugal. This paper focuses on the record of terrestrial pollen taxa, which document a series of forest expansions and declines during the period 13 000 cal. BP to 1600 cal. BP and provide insights into climate evolution in southwestern Iberia. The main vegetation phases identified in the Guadiana valley are (1) Lateglacial interstadial (Allerød) forest with Quercus and Pinus under a temperate, moist, continental climate; (2) a Younger Dryas forest decline (Quercus) and expansion of pinewoods, xeric scrub and open ground habitats (with Juniperus, Artemisia, Ephedra distachya type, Centaurea scabiosa type) under arid and cold conditions; (3) an early Holocene forest/scrub/open-ground vegetation mosaic developing under a warm, dry and continental climate; (4) a maximum of Quercus forest and thermomediterranean evergreen taxa (Olea, Phillyrea, Pistacia) reflecting a warm, moist oceanic climate between c. 9000 cal. BP and c. 5000 cal. BP; and (5) the expansion of shrublands with Cistaceae and Ericaceae under a drier climatic regime and increasing anthropogenic activity since c. 5000 cal. BP. Holocene episodes of maximum climatic aridity are identified in the record of xerophytic taxa (Juniperus, Artemisia, Ephedra distachya type) centred around 10 200 cal. BP, 7800 cal. BP, 4800 cal. BP, 3100 cal. BP and 1700 cal. BP. Regional comparisons suggest a correlation of arid phases across southern Iberia and northwest Africa, which can be related to abrupt North Atlantic coolings (Bond events).Research Council studentship for WJF (NERC/S/A/2001/06109), with the support of Trinity College and the Department of Geography, University of Cambridg

Search for a W' boson decaying to a bottom quark and a top quark in pp collisions at sqrt(s) = 7 TeV

Results are presented from a search for a W' boson using a dataset corresponding to 5.0 inverse femtobarns of integrated luminosity collected during 2011 by the CMS experiment at the LHC in pp collisions at sqrt(s)=7 TeV. The W' boson is modeled as a heavy W boson, but different scenarios for the couplings to fermions are considered, involving both left-handed and right-handed chiral projections of the fermions, as well as an arbitrary mixture of the two. The search is performed in the decay channel W' to t b, leading to a final state signature with a single lepton (e, mu), missing transverse energy, and jets, at least one of which is tagged as a b-jet. A W' boson that couples to fermions with the same coupling constant as the W, but to the right-handed rather than left-handed chiral projections, is excluded for masses below 1.85 TeV at the 95% confidence level. For the first time using LHC data, constraints on the W' gauge coupling for a set of left- and right-handed coupling combinations have been placed. These results represent a significant improvement over previously published limits.Comment: Submitted to Physics Letters B. Replaced with version publishe

Search for the standard model Higgs boson decaying into two photons in pp collisions at sqrt(s)=7 TeV

A search for a Higgs boson decaying into two photons is described. The analysis is performed using a dataset recorded by the CMS experiment at the LHC from pp collisions at a centre-of-mass energy of 7 TeV, which corresponds to an integrated luminosity of 4.8 inverse femtobarns. Limits are set on the cross section of the standard model Higgs boson decaying to two photons. The expected exclusion limit at 95% confidence level is between 1.4 and 2.4 times the standard model cross section in the mass range between 110 and 150 GeV. The analysis of the data excludes, at 95% confidence level, the standard model Higgs boson decaying into two photons in the mass range 128 to 132 GeV. The largest excess of events above the expected standard model background is observed for a Higgs boson mass hypothesis of 124 GeV with a local significance of 3.1 sigma. The global significance of observing an excess with a local significance greater than 3.1 sigma anywhere in the search range 110-150 GeV is estimated to be 1.8 sigma. More data are required to ascertain the origin of this excess.Comment: Submitted to Physics Letters