Mapping competitiveness with European data. Bruegel Blueprint 23, 6 March 2015

Europe needs improved competitiveness to escape the current economic malaise, so it might seem surprising that there is no common European definition of competitiveness, and no consensus on how to consistently measure it. To help address this situation, this Blueprint provides an inventory and an assessment of the data related to the measurement of competitiveness in Europe. It is intended as a handbook for researchers interested in measuring competiveness, and for policymakers interested in new and better measures of competitiveness. MAPCOMPETE has been designed to provide an assessment of data opportunities and requirements for the comparative analysis of competitiveness in European countries at the macro and the micro level.

Infrared microspectroscopic mapping of the homogeneity of extruded blends: Application to starch/polyester blends

Blends of starch and a biodegradable polyester, produced by an extrusion process, which included a cross-linker/compatibilizer (maleic anhydride) and an initiator (dicumyl peroxide), were studied by infrared (IR) microspectroscopy using an attenuated total reflectance (ATR) objective. Extruded material, which had a diameter of about 3 mm, was sectioned and embedded in epoxy resin prior to IR analysis. Spectra were collected in a grid pattern across the sectioned face of the sample. Measurement of various band parameters from the spectra allowed IR maps to be constructed containing semi-quantitative information about the distribution of blend components. These maps showed the quality of the blend on a microscopic scale and showed how it varied with different concentrations of compatibilizer and initiator. (c) 2005 Elsevier Ltd. All rights reserved.

Mud, algae or seagrass: An assessment of remote sensing techniques for mapping inter-tidal seagrass cover and composition in turbid tropical environments

Large areas of tropical sub- and inter-tidal seagrass beds occur in highly turbid environments and cannot be mapped through the water column. The purpose of this project was to determine if and how airborne and satellite imaging systems could be used to map inter-tidal seagrass properties along the wet-tropics coast in north Queensland, Australia. The work aimed to: (1) identify the minimum level of seagrass foliage cover that could be detected from airborne and satellite imagery; and (2) define the minimum detectable differences in seagrass foliage cover in exposed intertidal seagrass beds. High resolution spectral-reflectance data (2040 bands, 350 – 2500nm) were collected over 40cm diameter plots from 240 sites on Magnetic Island, Pallarenda Beach and Green Island in North Queensland at spring low tides in April 2006. The seagrass species sampled were: Thalassia hemprechii, Halophila ovalis, Halodule uninerivs; Syringodium isoetifolium, Cymodocea serrulata, and Cymodoea rotundata. Digital photos were captured for each plot and used to derive estimates of seagrass species cover, epiphytic growth, micro- and macro-algal cover, and substrate colour. Sediment samples were also collected and analysed to measure the concentration of Chlorophyll-a associated with benthic micro-algae. The field reflectance spectra were analysed in combination with their corresponding seagrass species foliage cover levels to establish the minimum foliage projective cover required for each seagrass to be significantly different from bare substrate and substrate with algal cover. This analysis was repeated with reflectance spectra resampled to the bandpass functions of Quickbird, Ikonos, SPOT 5 and Landsat 7 ETM. Preliminary results indicate that conservative minimum detectable seagrass cover levels across most the species sampled were between 30%- 35% on dark substrates. Further analysis of these results will be conducted to determine their separability and satellite images and to assess the effects epiphytes and algal cover.

An X-ray micro-fluorescence study to investigate the distribution of Al, Si, P and Ca ions in the surrounding soft tissue after implantation of a calcium phosphate-mullite ceramic composite in a rabbit animal model

Synthetic calcium phosphates, despite their bioactivity, are brittle. Calcium phosphate-mullite composites have been suggested as potential dental and bone replacement materials which exhibit increased toughness. Aluminium, present in mullite, has however been linked to bone demineralisation and neurotoxicity: it is therefore important to characterise the materials fully in order to understand their in vivo behaviour. The present work reports the compositional mapping of the interfacial region of a calcium phosphate-20 wt% mullite biocomposite/soft tissue interface, obtained from the samples implanted into the long bones of healthy rabbits according to standard protocols (ISO-10993) for up to 12 weeks. X-ray micro-fluorescence was used to map simultaneously the distribution of Al, P, Si and Ca across the ceramic-soft tissue interface. A well defined and sharp interface region was present between the ceramic and the surrounding soft tissue for each time period examined. The concentration of Al in the surrounding tissue was found to fall by two orders of magnitude, to the background level, within similar to 35 mu m of the implanted ceramic.

A micro-opto-electro-mechanical system (MOEMS) for microstructure manipulation

Microstructure manipulation is a fundamental process to the study of biology and medicine, as well as to advance micro- and nano-system applications. Manipulation of microstructures has been achieved through various microgripper devices developed recently, which lead to advances in micromachine assembly, and single cell manipulation, among others. Only two kinds of integrated feedback have been demonstrated so far, force sensing and optical binary feedback. As a result, the physical, mechanical, optical, and chemical information about the microstructure under study must be extracted from macroscopic instrumentation, such as confocal fluorescence microscopy and Raman spectroscopy. In this research work, novel Micro-Opto-Electro-Mechanical-System (MOEMS) microgrippers are presented. These devices utilize flexible optical waveguides as gripping arms, which provide the physical means for grasping a microobject, while simultaneously enabling light to be delivered and collected. This unique capability allows extensive optical characterization of the structure being held such as transmission, reflection, or fluorescence. The microgrippers require external actuation which was accomplished by two methods: initially with a micrometer screw, and later with a piezoelectric actuator. Thanks to a novel actuation mechanism, the "fishbone", the gripping facets remain parallel within 1 degree. The design, simulation, fabrication, and characterization are systematically presented. The devices mechanical operation was verified by means of 3D finite element analysis simulations. Also, the optical performance and losses were simulated by the 3D-to-2D effective index (finite difference time domain FDTD) method as well as 3D Beam Propagation Method (3D-BPM). The microgrippers were designed to manipulate structures from submicron dimensions up to approximately 100 μm. The devices were implemented in SU-8 due to its suitable optical and mechanical properties. This work demonstrates two practical applications: the manipulation of single SKOV-3 human ovarian carcinoma cells, and the detection and identification of microparts tagged with a fluorescent "barcode" implemented with quantum dots. The novel devices presented open up new possibilities in the field of micromanipulation at the microscale, scalable to the nano-domain.

Tool cutting force modeling and wear estimation of micro -end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

Tool cutting force modeling and wear estimation of micro-end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.

A Micro-Opto-Electro-Mechanical System (MOEMS) for Microstructure Manipulation

Microstructure manipulation is a fundamental process to the study of biology and medicine, as well as to advance micro- and nano-system applications. Manipulation of microstructures has been achieved through various microgripper devices developed recently, which lead to advances in micromachine assembly, and single cell manipulation, among others. Only two kinds of integrated feedback have been demonstrated so far, force sensing and optical binary feedback. As a result, the physical, mechanical, optical, and chemical information about the microstructure under study must be extracted from macroscopic instrumentation, such as confocal fluorescence microscopy and Raman spectroscopy. In this research work, novel Micro-Opto-Electro-Mechanical-System (MOEMS) microgrippers are presented. These devices utilize flexible optical waveguides as gripping arms, which provide the physical means for grasping a microobject, while simultaneously enabling light to be delivered and collected. This unique capability allows extensive optical characterization of the structure being held such as transmission, reflection, or fluorescence. The microgrippers require external actuation which was accomplished by two methods: initially with a micrometer screw, and later with a piezoelectric actuator. Thanks to a novel actuation mechanism, the “fishbone”, the gripping facets remain parallel within 1 degree. The design, simulation, fabrication, and characterization are systematically presented. The devices mechanical operation was verified by means of 3D finite element analysis simulations. Also, the optical performance and losses were simulated by the 3D-to-2D effective index (finite difference time domain FDTD) method as well as 3D Beam Propagation Method (3D-BPM). The microgrippers were designed to manipulate structures from submicron dimensions up to approximately 100 µm. The devices were implemented in SU-8 due to its suitable optical and mechanical properties. This work demonstrates two practical applications: the manipulation of single SKOV-3 human ovarian carcinoma cells, and the detection and identification of microparts tagged with a fluorescent “barcode” implemented with quantum dots. The novel devices presented open up new possibilities in the field of micromanipulation at the microscale, scalable to the nano-domain.

Idrossiapatite biologica e di sintesi: analisi attraverso spettroscopia Raman

Le tradizionali tecniche usate per l’analisi della struttura e della composizione comprendono, tra le altre, microscopia ottica, microscopia elettronica, diffrazione a raggi X e analisi chimica. In generale però, la maggior parte di questi metodi richiede una procedura di preparazione che può modificare la struttura o la composizione del campione. È necessario infatti che il campione non subisca alterazioni particolari durante la fase di preparazioni in modo tale che le condizioni fisiologiche rimangano il più possibile simili a quelle che si hanno in situ. Una tecnica che ultimamente sta diventando sempre più significativa in ambito biomedico è la spettroscopia Raman. Innanzitutto con l’analisi Raman la quantità di materiale da studiare per ottenere buoni risultati è minima, visto che possono essere studiati campioni che vanno dai micro ai nanogrammi; inoltre, possono essere analizzati campioni umidi e a pressione atmosferica, condizioni che rispecchiano verosimilmente quelle fisiologiche. Questo tipo di analisi è inoltre vantaggiosa dato che riesce a identificare diversi composti chimici, ha un’elevata risoluzione spaziale (0.6-1µm), riuscendo quindi ad analizzare campioni molto piccoli, ha tempi di misura brevi e può essere utilizzato più volte sullo stesso campione senza che quest’ultimo venga danneggiato. Nel seguente elaborato si sono riportati i risultati di diversi studi condotti sull’idrossiapatite naturale/biologica e sintetica ottenuti mediante questa tecnica spettroscopica. In particolare, ci si è soffermati sulla diversa concentrazione di OH- presente nell’apatite stechiometrica rispetto a quella biologica e di come tale concentrazione sia influenzata dalla presenza o meno dello ione carbonato. Si riportano inoltre le analisi condotte su campioni sintetici e biologici per comprendere se le molecole di acqua si trovino all’interno della struttura del minerale (acqua di bulk) o se siano solamente assorbite in superficie.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Preference Mapping Of Dulce De Leche Commercialized In Brazilian Markets.

Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

Phylogenetic And Phylogeographic Mapping Of The Avian Coronavirus Spike Protein-encoding Gene In Wild And Synanthropic Birds.

The evolution and population dynamics of avian coronaviruses (AvCoVs) remain underexplored. In the present study, in-depth phylogenetic and Bayesian phylogeographic studies were conducted to investigate the evolutionary dynamics of AvCoVs detected in wild and synanthropic birds. A total of 500 samples, including tracheal and cloacal swabs collected from 312 wild birds belonging to 42 species, were analysed using molecular assays. A total of 65 samples (13%) from 22 bird species were positive for AvCoV. Molecular evolution analyses revealed that the sequences from samples collected in Brazil did not cluster with any of the AvCoV S1 gene sequences deposited in the GenBank database. Bayesian framework analysis estimated an AvCoV strain from Sweden (1999) as the most recent common ancestor of the AvCoVs detected in this study. Furthermore, the analysis inferred an increase in the AvCoV dynamic demographic population in different wild and synanthropic bird species, suggesting that birds may be potential new hosts responsible for spreading this virus.