91 resultados para Pulsed outputs
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We identified hotspots of terrestrial vertebrate species diversity in Europe and adjacent islands. Moreover, we assessed the extent to which by the end of the 21(st) century such hotspots will be exposed to average monthly temperature and precipitation patterns which can be regarded as extreme if compared to the climate experienced during 1950-2000. In particular, we considered the entire European sub-continent plus Turkey and a total of 1149 species of terrestrial vertebrates. For each species, we developed species-specific expert-based distribution models (validated against field data) which we used to calculate species richness maps for mammals, breeding birds, amphibians, and reptiles. Considering four global circulation model outputs and three emission scenarios, we generated an index of risk of exposure to extreme climates, and we used a bivariate local Moran's I to identify the areas with a significant association between hotspots of diversity and high risk of exposure to extreme climates. Our results outline that the Mediterranean basin represents both an important hotspot for biodiversity and especially for threatened species for all taxa. In particular, the Iberian and Italian peninsulas host particularly high species richness as measured over all groups, while the eastern Mediterranean basin is particularly rich in amphibians and reptiles; the islands (both Macaronesian and Mediterranean) host the highest richness of threatened species for all taxa occurs. Our results suggest that the main hotspots of biodiversity for terrestrial vertebrates may be extensively influenced by the climate change projected to occur over the coming decades, especially in the Mediterranean bioregion, posing serious concerns for biodiversity conservation.
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We describe the unusual spread of a penicillin-susceptible methicillin-resistant Staphylococcus aureus (MRSA) clone in hospitals in western Switzerland, where the incidence of MRSA is usually low. During a 2-year period, this clone had been responsible for several outbreaks and had been isolated from >156 persons in 21 institutions. Molecular typing by pulsed-field gel electrophoresis (PFGE) demonstrated that all of these isolates belonged to the same clone. In 1 of the outbreaks, involving 30 cases, the clone was responsible for at least 17 secondary cases. In contrast, during the period of the latter outbreak, 9 other patients harboring different MRSA strains, as assessed by PFGE, were hospitalized in the same wards, but no secondary cases occurred. These observations suggest that this clone, compared with other MRSA strains, had some intrinsic factor(s) that contributed to its ability to disseminate and could thus be considered epidemic.
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The present study was undertaken to examine the cross-sectional vascular compliance at the anastomotic site. METHODS AND MATERIAL: We performed end-to-end anastomosis on the carotid artery of six pigs using continuous 6/0 polypropylene. Four carotid arteries were excised and mounted in a perfusion chamber while the remaining two were left in living animals. We used pulsed ultrasound (NIUS 02) to generate detailed longitudinal profiles of diameter and compliance in the proximity and on the anastomosis. RESULTS: On the anastomosis, the vessel diameter decreases (-1 to -2.6% of diastolic diameter) when blood pressure increases with an exponential correlation (R2 = 0.75). The arterial compliance at the anastomosis was negative: the vessel cross-section reduction for a pulse pressure of 1 up to 32 mmHg was 0.9 to 2% of diastolic vessel cross-section. CONCLUSIONS: Vessel movement generated a dynamic stenosis whose magnitude seems to depend on blood pressure level. Increasing blood pressure causes the retraction of vessel ends which causes vessel lumen reduction. These results suggest that continuous suture does not provide the continuity of mechanical properties of the artery.
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INTRODUCTION: Intravoxel incoherent motion (IVIM) imaging is an MRI perfusion technique that uses a diffusion-weighted sequence with multiple b values and a bi-compartmental signal model to measure the so-called pseudo-diffusion of blood caused by its passage through the microvascular network. The goal of the current study was to assess the feasibility of IVIM perfusion fraction imaging in patients with acute stroke. METHODS: Images were collected in 17 patients with acute stroke. Exclusion criteria were onset of symptoms to imaging >5 days, hemorrhagic transformation, infratentorial lesions, small lesions <0.5 cm in minimal diameter and hemodynamic instability. IVIM imaging was performed at 3 T, using a standard spin-echo Stejskal-Tanner pulsed gradients diffusion-weighted sequence, using 16 b values from 0 to 900 s/mm(2). Image quality was assessed by two radiologists, and quantitative analysis was performed in regions of interest placed in the stroke area, defined by thresholding the apparent diffusion coefficient maps, as well as in the contralateral region. RESULTS: IVIM perfusion fraction maps showed an area of decreased perfusion fraction f in the region of decreased apparent diffusion coefficient. Quantitative analysis showed a statistically significant decrease in both IVIM perfusion fraction f (0.026 ± 0.019 vs. 0.056 ± 0.025, p = 2.2 · 10(-6)) and diffusion coefficient D compared with the contralateral side (3.9 ± 0.79 · 10(-4) vs. 7.5 ± 0.86 · 10(-4) mm(2)/s, p = 1.3 · 10(-20)). CONCLUSION: IVIM perfusion fraction imaging is feasible in acute stroke. IVIM perfusion fraction is significantly reduced in the visible infarct. Further studies should evaluate the potential for IVIM to predict clinical outcome and treatment response.
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The minimum chromosome number of Glomus intraradices was assessed through cloning and sequencing of the highly divergent telomere-associated sequences (TAS) and by pulsed field gel electrophoresis (PFGE). The telomere of G. intraradices, as in other filamentous fungi, consists of TTAGGG repeats, this was confirmed using Bal31 nuclease time course reactions. Telomere length was estimated to be roughly 0.9 kb by Southern blots on genomic DNA and a telomere probe. We have identified six classes of cloned chromosomal termini based on the TAS. An unusually high genetic variation was observed within two of the six TAS classes. To further assess the total number of chromosome termini, we used telomere fingerprinting. Surprisingly, all hybridization patterns showed smears, which demonstrate that TAS are remarkably variable in the G. intraradices genome. These analyses predict the presence of at least three chromosomes in G. intraradices while PFGE showed a pattern of four bands ranging from 1.2 to 1.5 Mb. Taken together, our results indicate that there are at least four chromosomes in G. intraradices but there are probably more. The information on TAS and telomeres in the G. intradicies will be essential for making a physical map of the G. intraradices genome and could provide molecular markers for future studies of genetic variation among nuclei in these multigenomic fungi.
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BACKGROUND: Data on the epidemiology of MRSA infection in lung transplantation is limited. METHODS: We performed a 5-year retrospective study to assess the incidence and microbiologic and clinical characteristics of methicillin-resistant Staphylococcus aureus (MRSA) infection in a cohort of 163 lung transplant recipients. RESULTS: Seventeen patients with MRSA colonization and/or infection were identified, for a calculated incidence rate of 76.1 cases per 1,000 transplanted-years. Pulsed-field gel electrophoresis identified 3 different distinct MRSA profiles, all of them consistent with hospital-associated MRSA infection. CONCLUSION: Despite negative polymerase chain reaction (PCR) for the virulence factor Panton-Valentine leukocidin, MRSA infections resulted in significant disease and morbidity.
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Patients with stage I-III melanoma were vaccinated with the modified HLA-A2-binding gp100(209-2M)-peptide after complete surgical resection of their primary lesion and sentinel node biopsy. Cytoplasmic interferon-gamma production by freshly thawed peripheral blood mononuclear cells (direct ex vivo analysis) or by peripheral blood mononuclear cells subjected to 1 cycle of in vitro sensitization with peptide, interleukin-2, and interleukin-15 was measured following restimulation with the modified and native gp100 peptides, and also A2gp100 melanoma cell lines. Peptide-reactive and tumor-reactive T cells were detected in 79% and 66% of selected patients, respectively. Patients could be classified into 3 groups according to their vaccine-elicited T-cell responses. One group of patients responded only to the modified peptide used for immunization, whereas another group of patients reacted to both the modified and native gp100 peptides, but not to naturally processed gp100 antigen on melanoma cells. In the third group of patients, circulating CD8 T cells recognized A2gp100 melanoma cell lines and also both the modified and native peptides. T cells with a low functional avidity, which were capable of lysing tumor cells only if tumor cells were first pulsed by the exogenous administration of native gp100(209-217) peptide were identified in most patients. These results indicate that vaccination with a modified gp100 peptide induced a heterogeneous group of gp100-specific T cells with a spectrum of functional avidities; however, high avidity, tumor-reactive T cells were detected in the majority of patients.
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Purpose: To evaluate the sensitivity of the perfusion parameters derived from Intravoxel Incoherent Motion (IVIM) MR imaging to hypercapnia-induced vasodilatation and hyperoxygenation-induced vasoconstriction in the human brain. Materials and Methods: This study was approved by the local ethics committee and informed consent was obtained from all participants. Images were acquired with a standard pulsed-gradient spin-echo sequence (Stejskal-Tanner) in a clinical 3-T system by using 16 b values ranging from 0 to 900 sec/mm(2). Seven healthy volunteers were examined while they inhaled four different gas mixtures known to modify brain perfusion (pure oxygen, ambient air, 5% CO(2) in ambient air, and 8% CO(2) in ambient air). Diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), and blood flow-related parameter (fD*) maps were calculated on the basis of the IVIM biexponential model, and the parametric maps were compared among the four different gas mixtures. Paired, one-tailed Student t tests were performed to assess for statistically significant differences. Results: Signal decay curves were biexponential in the brain parenchyma of all volunteers. When compared with inhaled ambient air, the IVIM perfusion parameters D*, f, and fD* increased as the concentration of inhaled CO(2) was increased (for the entire brain, P = .01 for f, D*, and fD* for CO(2) 5%; P = .02 for f, and P = .01 for D* and fD* for CO(2) 8%), and a trend toward a reduction was observed when participants inhaled pure oxygen (although P > .05). D remained globally stable. Conclusion: The IVIM perfusion parameters were reactive to hyperoxygenation-induced vasoconstriction and hypercapnia-induced vasodilatation. Accordingly, IVIM imaging was found to be a valid and promising method to quantify brain perfusion in humans. © RSNA, 2012.
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This paper presents reflexions about statistical considerations on illicit drug profiling and more specifically about the calculation of threshold for determining of the seizure are linked or not. The specific case of heroin and cocaine profiling is presented with the necessary details on the target profiling variables (major alkaloids) selected and the analytical method used. Statistical approach to compare illicit drug seizures is also presented with the introduction of different scenarios dealing with different data pre-treatment or transformation of variables.The main aim consists to demonstrate the influence of data pre-treatment on the statistical outputs. A thorough study of the evolution of the true positive rate (TP) and the false positive rate (FP) in heroin and cocaine comparison is then proposed to investigate this specific topic and to demonstrate that there is no universal approach available and that the calculations have to be revaluate for each new specific application.
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We compared cerebral blood flow velocity during anesthesia with sevoflurane and halothane in 23 children admitted for elective surgery (age, 0.4-9.7 yr; median age, 1.9 yr; ASA physical status I-II). Inhaled induction was performed in a randomized sequence with sevoflurane or halothane. Under steady-state conditions, cerebral blood flow velocity (systolic [V(s)], mean [V(mn)], and diastolic [VD]) were measured by a blinded investigator using transcranial pulsed Doppler ultrasonography. The anesthetic was then changed. CBFV measurements were repeated after washout of the first anesthetic and after steady-state of the second (equivalent minimal alveolar concentration to first anesthetic). The resistance index was calculated. VD and V(mn) were significantly lower during sevoflurane (V(mn) 1.35 m/s) than during halothane (V(mn) 1.50 m/s; P = 0.001), whereas V(s) was unchanged. The resistance index was lower during halothane (P < 0.001). Our results indicate lower vessel resistance and higher mean velocity during halothane than during sevoflurane. IMPLICATIONS: The mean cerebral blood flow velocity is significantly decreased in children during inhaled anesthesia with sevoflurane than during halothane. This might be relevant for the choice of anesthetic in children with risk of increased intracranial pressure, neurosurgery, or craniofacial osteotomies.
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This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.
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Gastric lipase (HGL) contributes significantly to fat digestion. However, little is known about its neurohormonal regulation in humans. We studied the role of CCK and cholinergic mechanisms in the postprandial regulation of HGL and pancreatic lipase (HPL) secretion in six healthy subjects. Gastric emptying of a mixed meal and outputs of HGL, pepsin, acid, and HPL were determined with a double-indicator technique. Three experiments were performed in random order: intravenous infusion of 1) placebo, 2) low-dose atropine (5 micrograms.kg-.h-1), and 3) the CCK-A receptor antagonist loxiglumide (22 mumol.kg-.h-1). Atropine decreased postprandial outputs of HGL, pepsin, gastric acid, and HPL (P < 0.03) while slowing gastric emptying (P < 0.05). Loxiglumide markedly increased the secretion of HGL, pepsin, and acid while distinctly reducing HPL outputs and accelerating gastric emptying (P < 0.03). Plasma CCK and gastrin levels increased during loxiglumide infusion (P < 0.03). Atropine enhanced gastrin but not CCK release. Postprandial HGL, pepsin, and acid secretion are under positive cholinergic but negative CCK control, whereas HPL is stimulated by cholinergic and CCK mechanisms. We conclude that CCK and cholinergic mechanisms have an important role in the coordination of HGL and HPL secretion to optimize digestion of dietary lipids in humans.
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The Urn Sohryngkew section of Meghalaya, NE India, located 800-1000 km from the Deccan volcanic province, is one of the most complete Cretaceous-Tertiary boundary (KTB) transitions worldwide with all defining and supporting criteria present: mass extinction of planktic foraminifera, first appearance of Danian species, delta(13)C shift, Ir anomaly (12 ppb) and KTB red layer. The geochemical signature of the KTB layer indicates not only an extraterrestrial signal (Ni and all Platinum Group Elements (PGEs)) of a second impact that postdates Chicxulub, but also a significant component resulting from condensed sedimentation (P), redox fluctuations (As, Co, Fe, Pb, Zn, and to a lesser extent Ni and Cu) and volcanism. From the late Maastrichtian C29r into the early Danian, a humid climate prevailed (kaolinite: 40-60%, detrital minerals: 50-80%). During the latest Maastrichtian, periodic acid rains (carbonate dissolution; CIA index: 70-80) associated with pulsed Deccan eruptions and strong continental weathering resulted in mesotrophic waters. The resulting super-stressed environmental conditions led to the demise of nearly all planktic foraminiferal species and blooms (>95%) of the disaster opportunist Guembelitria cretacea. These data reveal that detrimental marine conditions prevailed surrounding the Deccan volcanic province during the main phase of eruptions in C29r below the KTB. Ultimately these environmental conditions led to regionally early extinctions followed by global extinctions at the KTB. (C) 2011 Elsevier B.V. All rights reserved.
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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
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In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.