An approach to health and safety in E.U. forestry operations – Hazards and preventive measures

Forestry in general and logging in particular continue to be among the three most hazardous sectors in European countries. The aim of this article is to characterize health and safety problems and solutions in E.U. forestry operations, and particularly in Portuguese operations. Forest types, production, employment and ownership are used to characterize the forest sector. Forestry accidents and health problems data are mentioned. Typical hazards associated to the nature of logging operations are systematized. Preventive measures, focused on a wide spectrum of measures, making safety considerations an integral feature of all operational activities from planning to organization to execution and supervision of work are emphasized in this article.

The portuguese pharmaceutial market in the near future - A time series exploration approach

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Iterative reconstruction methods in two different MDCT scanners: Physical metrics and 4-alternative forced-choice detectability experiments - A phantom approach.

This paper characterizes and evaluates the potential of three commercial CT iterative reconstruction methods (ASIR?, VEO? and iDose(4 ()?())) for dose reduction and image quality improvement. We measured CT number accuracy, standard deviation (SD), noise power spectrum (NPS) and modulation transfer function (MTF) metrics on Catphan phantom images while five human observers performed four-alternative forced-choice (4AFC) experiments to assess the detectability of low- and high-contrast objects embedded in two pediatric phantoms. Results show that 40% and 100% ASIR as well as iDose(4) levels 3 and 6 do not affect CT number and strongly decrease image noise with relative SD constant in a large range of dose. However, while ASIR produces a shift of the NPS curve apex, less change is observed with iDose(4) with respect to FBP methods. With second-generation iterative reconstruction VEO, physical metrics are even further improved: SD decreased to 70.4% at 0.5 mGy and spatial resolution improved to 37% (MTF(50%)). 4AFC experiments show that few improvements in detection task performance are obtained with ASIR and iDose(4), whereas VEO makes excellent detections possible even at an ultra-low-dose (0.3 mGy), leading to a potential dose reduction of a factor 3 to 7 (67%-86%). In spite of its longer reconstruction time and the fact that clinical studies are still required to complete these results, VEO clearly confirms the tremendous potential of iterative reconstructions for dose reduction in CT and appears to be an important tool for patient follow-up, especially for pediatric patients where cumulative lifetime dose still remains high.

A fractionally integrated approach to monetary policy and inflation dynamics

This paper relaxes the standard I(0) and I(1) assumptions typically stated in the monetary VAR literature by considering a richer framework that encompasses the previous two processes as well as other fractionally integrated possibilities. First, a timevarying multivariate spectrum is estimated for post WWII US data. Then, a structural fractionally integrated VAR (VARFIMA) is fitted to each of the resulting time dependent spectra. In this way, both the coefficients of the VAR and the innovation variances are allowed to evolve freely. The model is employed to analyze inflation persistence and to evaluate the stance of US monetary policy. Our findings indicate a strong decline in the innovation variances during the great disinflation, consistent with the view that the good performance of the economy during the 80’s and 90’s is in part a tale of good luck. However, we also find evidence of a decline in inflation persistence together with a stronger monetary response to inflation during the same period. This last result suggests that the Fed may still play a role in accounting for the observed differences in the US inflation history. Finally, we conclude that previous evidence against drifting coefficients could be an artifact of parameter restriction towards the stationary region. Keywords: monetary policy, inflation persistence, fractional integration, timevarying coefficients, VARFIMA. JEL Classification: E52, C32

Evolutionary forces affect multigenomic arbuscular mycorhizal fungi : an experimental approach using Glomus intraradices

Abstract Arbuscular Mycorhizal Fungi (AMF) are important plant symbionts that can improve floristic diversity and ecosystem productivity. These important fungi are obligate biotrophs and form symbioses with roots of the majority of plant species, improving plant nutrient acquisition in exchange of photosynthates. AM fungi are successful both ecologically as they occupy a very large spectrum of environments as well as host range and evolutionarily, as this symbiosis is over 400 million years old. These fungi grow and reproduce clonally by hyphae and multinucleate spores. AMF are coenocytic and recent work has shown that they harbor genetically different nuclei and that AMF populations are genetically diverse. How AMF species diversity is maintained has been addressed theoretically and experimentally at the community level. Much less attention has been drawn to understand how genetic diversity is maintained within populations although closely related individuals are more likely to compete for the same resources and occupy similar niches. How infra-individual genetic diversity is shaped and maintained has received even less attention. In Chapter 2, we show that individuals from a field population may differ in their symbiotic efficiency under reduced phosphate availability: We show there is genetic variation in an AMF field population for fitness-related growth traits in response to different phosphate availability acid host species. Furthermore, AFLP fingerprints of the same individuals growing in contrasting environments diverged suggesting that the composition in nuclei of AMF is dynamical and affected by environmental factors. Thus environmental heterogeneity is likely to play an important role for the maintenance of genetic diversity at the population level. In Chapter 3 we show that single spores do not inherit necessarily the same genetic material. We have found genetic divergences using two different types of molecular marker, as well as phenotypic divergences among single spore lines. Our results stress the importance of considering these organisms as a multilevel hierarchical system and of better knowing their life cycle. They have important consequences for the understanding of AMF genetics, ecology and the development of commercial AMF inocculum. Résumé Les champignons endomycorhiziens arbusculaires (CEA) sont d'importants symbiontes pour les plantes, car ils augmentent la diversité et la productivité des écosystèmes. Ces importants symbiontes sont des biotrophes obligatoires et forment une symbiose avec la plupart des plantes terrestres. Ils améliorent l'acquisition de substances nutritives de leurs hôtes en échange de sucres obtenus par photosynthèse. Ces champignons ont un grand succès écologique, ils colonisent une grande rangée d'environnements ainsi que d'hôtes. Ils ont aussi un succès évolutif certain de part le fait que cette symbiose existe depuis plus de 400 millions d'années. Les CEA sont asexués et croissent clonalement en formant des hyphes et des spores multinuclées. Les CEA sont des coenocytes et des travaux de recherche récents ont montré qu'ils possèdent des noyaux génétiquement différents. D'autres travaux ont aussi révélé que les populations de CEA sont génétiquement diversifiées. Comment la diversité des CEA est maintenue a seulement été adressée par des études théoriques et expérimentalement au niveau des communautés. Très peu d'attention a été portée sur le maintien de la diversité génétique infra et inter populationnelle, or ce sont les individus les plus proches génétiquement qui vont entrer en compétition pour des ressources et niches similaires. La formation et le maintien de la diversité intra-individu des CEA a reçu très peu d'attention. Dans le chapitre 2, nous montrons que des individus CEA d'un même champ différent dans leur efficacité symbiotique lorsque la concentration en phosphoré est réduite. Nous montrons qu'il existe de la variance génétique dans une population de CEA provenant d'un même champ en réponse à différentes concentrations de phosphore, ainsi qu'en réponse à différentes espèces d'hôtes, et ceci pour des traits de croissance vraisemblablement liés au succès reproducteur. De plus grâce à des AFLP nous avons pu montrer que le génome de ces individus subissent des changements lorsqu'ils croissent dans des environnements contrastés. Ceci suggère que les noyaux génétiquement différents des CEA sont des entités dynamiques. Il est fort probable que l'hétérogénéité environnementale joue un rôle dans le maintien de la diversité génétique des populations de CEA. Dans le chapitre 3, nous montrons que toutes les spores d'un même mycélium parental de CEA ne reçoivent pas exactement le même contenu génétique. Nous avons mis en évidence des divergences entre des Lignées monosporales en utilisant deux types de marqueur moléculaires, ainsi que des différences phénotypiques. Nos résutats soulignent l'importance de considézer ces organismes comme dés systëmes hiérarchiques mufti-niveaux, ainsi que de mieux connaître leur cycle de vie. Nos résultats ont d'importantes conséquences pour la compréhension du système génétique des CEA, ainsi que de leur évolution, leur écológie, mais également des conséquences pour la production d' inoccultim commercial.

Fever in neutropenic cancer patients : a structured approach

Infectious complications related to acquired neutropenia have become a major medical issue, often requiring intensive care management. These infections may be lethal if empirical broad-spectrum treatment is not rapidly started at the first sign of infection (i.e., fever), and this concept is now widely recognized a standard practice. However, the choice of antibiotics has generated considerable controversy for nearly 25 years. After reviewing some particularities of infection in neutropenic patients, this paper will discuss the options and present comprehensive algorithm for non-infectious diseases specialist, including recent advances about early IV-oral switch and the selection of low risk patients for outpatient management.

Imaging spectrum of the operated bladder : P41

Multiple complex procedures involving the bladder have been developed by surgeons in both children and adults, with their own advantages and drawbacks. A greater knowledge of the anatomic changes induced by each category of procedure is mandatory in the follow-up of patients and detection of early and late postoperative complications. A retrospective review of 50 pediatric and adult patients referred or treated in our institution is presented. The combined use of plain films, IVP, MCUG, US, Doppler US, CT, 3DCT and MRI is described. The imaging features are compared with surgical and anatomopathological findings. The purpose of this pictorial essay is to present a wide spectrum of diagnostic imaging findings in children and adult patients with operated bladder. The imaging features of surgical procedures with preserved, partially replaced and totally replaced bladder are described, with emphasis on a systematic multimodality approach. Learning objectives: 1) To provide an in-depth review of bladder surgical procedures with their indications, anatomopathological and imaging features. 2) To describe optimal multimodality imaging techniques for evaluating the operated bladder.

Diffusion-weighted spectroscopy: a novel approach to determine macromolecule resonances in short-echo time 1H-MRS.

Quantification of short-echo time proton magnetic resonance spectroscopy results in >18 metabolite concentrations (neurochemical profile). Their quantification accuracy depends on the assessment of the contribution of macromolecule (MM) resonances, previously experimentally achieved by exploiting the several fold difference in T(1). To minimize effects of heterogeneities in metabolites T(1), the aim of the study was to assess MM signal contributions by combining inversion recovery (IR) and diffusion-weighted proton spectroscopy at high-magnetic field (14.1 T) and short echo time (= 8 msec) in the rat brain. IR combined with diffusion weighting experiments (with δ/Δ = 1.5/200 msec and b-value = 11.8 msec/μm(2)) showed that the metabolite nulled spectrum (inversion time = 740 msec) was affected by residuals attributed to creatine, inositol, taurine, choline, N-acetylaspartate as well as glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost not affected (< 8%). The combination of metabolite-nulled IR spectra with diffusion weighting allows a specific characterization of MM resonances with minimal metabolite signal contributions and is expected to lead to a more precise quantification of the neurochemical profile.

First and second branchial arch syndromes: multimodality approach.

First and second branchial arch syndromes (BAS) manifest as combined tissue deficiencies and hypoplasias of the face, external ear, middle ear and maxillary and mandibular arches. They represent the second most common craniofacial malformation after cleft lip and palate. Extended knowledge of the embryology and anatomy of each branchial arch derivative is mandatory for the diagnosis and grading of different BAS lesions and in the follow-up of postoperative patients. In recent years, many new complex surgical approaches and procedures have been designed by maxillofacial surgeons to treat extensive maxillary, mandibular and external and internal ear deformations. The purpose of this review is to evaluate the role of different imaging modalities (orthopantomogram (OPG), lateral and posteroanterior cephalometric radiographs, CT and MRI) in the diagnosis of a wide spectrum of first and second BAS, including hemifacial microsomia, mandibulofacial dysostosis, branchio-oto-renal syndrome, Pierre Robin sequence and Nager acrofacial dysostosis. Additionally, we aim to emphasize the importance of the systematic use of a multimodality imaging approach to facilitate the precise grading of these syndromes, as well as the preoperative planning of different reconstructive surgical procedures and their follow-up during treatment.

Langevin approach to generate synthetic turbulent flows

We present an analytical scheme, easily implemented numerically, to generate synthetic Gaussian turbulent flows by using a linear Langevin equation, where the noise term acts as a stochastic stirring force. The characteristic parameters of the velocity field are well introduced, in particular the kinematic viscosity and the spectrum of energy. As an application, the diffusion of a passive scalar is studied for two different energy spectra. Numerical results are compared favorably with analytical calculations.

Microscopic calculations of the excitation spectrum of one 3He impurity in liquid 4He

We calculate the chemical potential ¿0 and the effective mass m*/m3 of one 3He impurity in liquid 4He. First a variational wave function including two- and three-particle dynamical correlations is adopted. Triplet correlations bring the computed values of ¿0 very close to the experimental results. The variational estimate of m*/m3 includes also backflow correlations between the 3He atom and the particles in the medium. Different approximations for the three-particle distribution function give almost the same values for m*/m3. The variational approach underestimates m*/m3 by ~10% at all of the considered densities. Correlated-basis perturbation theory is then used to improve the wave function to include backflow around the particles of the medium. The perturbative series built up with one-phonon states only is summed up to infinite order and gives results very close to the variational ones. All the perturbative diagrams with two independent phonons have then been summed to compute m*/m3. Their contribution depends to some extent on the form used for the three-particle distribution function. When the scaling approximation is adopted, a reasonable agreement with the experimental results is achieved.

Rapid cohort generation and analysis of disease spectrum of large animal model of cone dystrophy.

Large animal models are an important resource for the understanding of human disease and for evaluating the applicability of new therapies to human patients. For many diseases, such as cone dystrophy, research effort is hampered by the lack of such models. Lentiviral transgenesis is a methodology broadly applicable to animals from many different species. When conjugated to the expression of a dominant mutant protein, this technology offers an attractive approach to generate new large animal models in a heterogeneous background. We adopted this strategy to mimic the phenotype diversity encounter in humans and generate a cohort of pigs for cone dystrophy by expressing a dominant mutant allele of the guanylate cyclase 2D (GUCY2D) gene. Sixty percent of the piglets were transgenic, with mutant GUCY2D mRNA detected in the retina of all animals tested. Functional impairment of vision was observed among the transgenic pigs at 3 months of age, with a follow-up at 1 year indicating a subsequent slower progression of phenotype. Abnormal retina morphology, notably among the cone photoreceptor cell population, was observed exclusively amongst the transgenic animals. Of particular note, these transgenic animals were characterized by a range in the severity of the phenotype, reflecting the human clinical situation. We demonstrate that a transgenic approach using lentiviral vectors offers a powerful tool for large animal model development. Not only is the efficiency of transgenesis higher than conventional transgenic methodology but this technique also produces a heterogeneous cohort of transgenic animals that mimics the genetic variation encountered in human patients.

Langevin approach to generate synthetic turbulent flows

We present an analytical scheme, easily implemented numerically, to generate synthetic Gaussian turbulent flows by using a linear Langevin equation, where the noise term acts as a stochastic stirring force. The characteristic parameters of the velocity field are well introduced, in particular the kinematic viscosity and the spectrum of energy. As an application, the diffusion of a passive scalar is studied for two different energy spectra. Numerical results are compared favorably with analytical calculations.

Expositions médicamenteuses pendant la grossesse: une approche différenciée [Drug exposure during pregnancy: a differentiated approach].

Numerous drug exposures do occur unintentionally at the beginning of pregnancy. On the other hand, pursuing drug treatment may be necessary in women who wish to be pregnant. In these situations risk evaluation has to be done in a precise and differentiated manner, taking into account at the same time the risk for the fetus and maternal health. Teratovigilance services are able to give a thorough information enabling to avoid unwarranted drug arrests or pregnancy terminations. In return, physician's catamnesis about the outcome of the pregnancy exposed to one or several therapeutic agents will increase the bulk of knowledge health professionals and pregnant women have at their disposal.