Methods for assimilating blood velocity measures in hemodynamics simulations: Preliminary results

AbstractNew measurement devices and techniques in biomedical images provide medical doctors with a huge amount of data on blood flow and vascular morphologies. These data are crucial for performing (and validating) individualbased simulations of hemodynamics (see e.g. [1]). Availability of velocity measures inside a region of interest poses problems that are new to the community of computational hemodynamics and however well known in other engineering fields. In particular, integration of data (measures) and numerical simulations has been an issue of utmost relevance in the prediction of fluid geophysics phenomena and, in particular, weather forecast. In computational hemodynamics a mathematically sound assimilation of data and numerical simulations is needed, on one hand for improving reliability of numerical results, on the other one for filtering noise and measurements errors. In this paper we consider and compare some possible methods for integrating numerical simulations and velocity measures in some internal points of the computational domain. Preliminary numerical results for a 2D Stokes problem are presented both for noise free and noisy data, investigating convergence rate and noise sensitivity

Herschel-ATLAS: statistical properties of Galactic cirrus in the GAMA-9 Hour Science Demonstration Phase Field

We study the spectral energy distribution (SED) and the power spectrum of Galactic cirrus emission observed in the 14 deg^2 Science Demonstration Phase field of the Herschel-ATLAS using Herschel and IRAS data from 100 to 500 μm. We compare the Spectral and Photometric Imaging Receiver (SPIRE) 250, 350 and 500 μm maps with IRAS 100-μm emission, binned in 6-arcmin pixels. We assume a modified blackbody SED with dust emissivity parameter β (F∝λ^(−β)) and a single dust temperature T_d, and find that the dust temperature and emissivity index varies over the science demonstration field as 10 < T_d < 25K and 1 < β < 4. The latter values are somewhat higher than the range of β often quoted in the literature (1 < β < 2). We estimate the mean values of these parameters to be T_d= 19.0 ± 2.4 K and β= 1.4 ± 0.4. In regions of bright cirrus emission, we find that the dust has similar temperatures with T_d = 18.0 ± 2.5 K, and similar values of β, ranging from 1.4 ± 0.5 to 1.9 ± 0.5. We show that T_d and β associated with diffuse cirrus emission are anti-correlated and can be described by the relationship: β(T_d) =NT^α_d with [N= 116 ± 38, α=−1.4 ± 0.1]. The strong correlation found in this analysis is not just limited to high-density clumps of cirrus emission as seen in previous studies, but is also seen in diffuse cirrus in low-density regions. To provide an independent measure of T_d and β, we obtain the angular power spectrum of the cirrus emission in the IRAS and SPIRE maps, which is consistent with a power spectrum of the form P(k) =P_0(k/k_0)^γ, where γ= 2.6 ± 0.2 for scales of 50–200 arcmin in the SPIRE maps. The cirrus rms fluctuation amplitude at angular scales of 100 arcmin is consistent with a modified blackbody SED with T_d 20.1 ± 0.9 K and β= 1.3 ± 0.2, in agreement with the values obtained above

Incorporating landscape heterogeneities in the spread of an epidemics in wildlife

One of the main difficulties in the modeling and numerical simulation of the spread of an infectious disease in wildlife resides in properly taking into account the heterogeneities of the landscape. Forests, plains and mountains present different levels of hospitality, while large interstates, lakes and major waterways can provide strong natural barriers to the epidemic spread. A canonical approach has been to discretize both population and geography into geopolitical units and consider the movement of individuals from unit to unit [4]. This approach, however, does not well represent the biological realities of animal movement, since animals do not move at the scale of geopolitical units. We combine a standard SEI epidemiological model with a diffusion process to account for movement as a continuous process across a continuous region [1]. This results in a system of parabolic reaction-diffusion equations with nonlinear reaction term. Landscape heterogeneities are accounted for by including in the computational domain the significant geographical features of the area. We discretize the resulting model in time by an IMEX scheme and in space by finite elements. To show the effectiveness of the method, we present numerical simulation for rabies epidemics among raccoons in New York State

Numerical simulation of a susceptible-exposed-infectious space-continuous model for the spread of rabies in raccoons across a realistic landscape

We introduce a numerical model for the spread of a lethal infectious disease in wildlife. The reference model is a Susceptible-Exposed-Infectious system where the spatial component of the dynamics is modelled by a diffusion process. The goal is to develop a model to be used for real geographical scenarios, so we do not rely upon simplifying assumptions on the shape of the region of interest. For this reason, space discretization is carried out with the finite element method on an unstructured triangulation. A diffusion term is designed to take into account landscape heterogeneities such as mountains and waterways. Numerical simulations are carried out for rabies epidemics among raccoons in New York state. A qualitative comparison of numerical results to available data from real-world epidemics is discussed

Consapevolezza, accettazione e comprensione di sé: associazioni con il benessere individuale e l'apertura prosociale

The positive psychology approach involves the study of characteristics that may contribute to an optimal functioning of individual and society (e.g. Gable & Haidt, 2005), by improving for instance well-being and prosocial orientation. In this scenario, mindfulness, i.e. a non-judgmental awareness that emerges through paying attention to the present moment (e.g. Kabat-Zinn, 1994), is particularly relevant. Similarly, a growing interest has been recently devoted to self-compassion, i.e. a non-judgmental attitude towards own weaknesses (Neff, 2003). Mindfulness and self-compassion showed to be related to improved well-being (e.g. Bernard & Curry, 2011; Keng, Smoski, & Robins, 2011). Their relation to prosocial tendencies (e.g. Block-Lerner, Orsillo, & Plumb, 2004, Neff & Germer, 2013) is less clear though. Aiming to better understand the relationship of mindfulness and self-compassion with indicators of well-being and prosocial orientation, two new constructs have been developed in this thesis. The first construct is "emotional awareness", a non-judgmental awareness toward own emotions, positive and negative, which are therefore fully experienced, without alterations or suppressions. The second one, "self-caring", covers (i) the awareness to be in a time of trouble and to need help; and (ii) the openness to accept the offered support. Mindfulness is hypothesized to be a precondition of self-compassion (e.g. Birnie, Speca, & Carlson, 2010), emotional awareness and self-caring. We aimed to investigate the relationship of mindfulness, self-compassion, emotional awareness and self-caring with different indicators of well-being and prosocial tendencies, considering the simultaneous effects of social desirability. More specifically, we tested a mediation model in which the relationship of mindfulness with well-being and prosocial inclinations was mediated by self-compassion, emotional awareness and self-caring. In order to test this hypothesis, we developed an Italian adaptation of the instruments used to asses mindfulness and self-compassion, i.e., the Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003; Study 1), and the Self-Compassion Scale-Short Form (SCS-SF; Raes, Pommier, Neff & Van Gucht, 2011; Study 2). Furthermore, we developed the two instruments for the assessment of emotional awareness and self-caring dispositions and we investigated their main psychometric characteristics (Study 3). Then, through a confirmatory factor analysis, we showed that the analyzed constructs were different from each other, although partially overlapping, controlling also for their susceptibility to social desirability (Study 4). The subsequent study has preliminarily investigated the relationship of mindfulness, self-compassion, emotional awareness and self-caring with indicators of well-being and prosocial orientation (Study 5). The mediation model has been therefore tested for the first time. Finally, the last two studies examined more in depth the mediation model. Specifically, we employed indicators of general, subjective and psychological well-being (Study 6), unconditional respect and prosocial personality (Study 7). In these studies we also tested a two-level mediation model, where the relationship of mindfulness with well-being and prosocial tendencies was mediated by self-compassion, emotional awareness and self-caring, at the first level, and by gratitude and inter-being, at the second level. Gratitude has already showed to be related to an increase in well-being and prosocial inclinations, while inter-being is a new construct of Eastern origin. In all these studies, the mediation model has been examined adopting a structural equation model approach. Overall, the results suggest that mindfulness is associated with improved well-being and increased prosocial orientation, especially through higher emotional awareness, gratitude and inter-being. Strengths, limitations, implications of the studies and future perspectives are discussed

LANDSAT and radar mapping of intrusive rocks in SE-Brazil

The feasibility of intrusive rock mapping was investigated and criteria for regional geological mapping established at the scale of 1:500,00 in polycyclic and polymetamorphic areas using the logic method of photointerpretation of LANDSAT imagery and radar from the RADAMBRASIL project. The spectral behavior of intrusive rocks, was evaluated using the interactive multispectral image analysis system (Image-100). The region of Campos (city) in northern Rio de Janeiro State was selected as the study area and digital imagery processing and pattern recognition techniques were applied. Various maps at the 2:250,000 scale were obtained to evaluate the results of automatic data processing

Detection and characterization of a 500 μm dust emissivity excess in the Galactic plane using Herschel/Hi-GAL observations

Context. Past and recent observations have revealed unexpected variations in the far-infrared – millimeter (FIR-mm) dust emissivity in the interstellar medium. In the Herschel spectral range, those are often referred to as a 500 μm emission excess. Several dust emission models have been developed to interpret astrophysical data in the FIR-mm domain. However, these are commonly unable to fully reconcile theoretical predictions with observations. In contrast, the recently revised two level system (TLS) model, based on the disordered internal structure of amorphous dust grains, seems to provide a promising way of interpreting existing data. Aims. The newly available Herschel infrared GALactic (Hi-GAL) data, which covers most of the inner Milky Way, offers a unique opportunity to investigate possible variations in the dust emission properties both with wavelength and environment. The goal of our analysis is to constrain the internal structure of the largest dust grains on Galactic scales, in the framework of the TLS model. Methods. By combining the IRIS (Improved Reprocessing of the IRAS Survey) 100 μm with the Hi-GAL 160, 250, 350, and 500 μm data, we model the dust emission spectra in each pixel of the Hi-GAL maps, using both the TLS model and, for comparison, a single modified black-body fit. The effect of temperature mixing along the line of sight is investigated to test the robustness of our results. Results. We find a slight decrease in the dust temperature with distance from the Galactic center, confirming previous results. We also report the detection of a significant 500 μm emissivity excess in the peripheral regions of the plane (35° < |l| < 70°) of about 13–15% of the emissivity, which can reach up to 20% in some HII regions. We present the spatial distributions of the best-fit values for the two main parameters of the TLS model, i.e. the charge correlation length, lc, used to characterize the disordered charge distribution (DCD) part of the model, and the amplitude A of the TLS processes with respect to the DCD effect. These distributions illustrate the variations in the dust properties with environment, in particular the plausible existence of an overall gradient with distance to the Galactic center. A comparison with previous findings in the solar neighborhood shows that the local value of the excess is less than expected from the Galactic gradient observed here

Modeling and predicting the shape of the far-infrared to submillimeter emission in ultra-compact HII regions and cold clumps

Dust properties are very likely affected by the environment in which dust grains evolve. For instance, some analyses of cold clumps (7 K- 17 K) indicate that the aggregation process is favored in dense environments. However, studying warm (30 K-40 K) dust emission at long wavelength ($\lambda$$>$300 $\mu$m) has been limited because it is difficult to combine far infared-to-millimeter (FIR-to-mm) spectral coverage and high angular resolution for observations of warm dust grains. Using Herschel data from 70 to 500 $\mu$m, which are part of the Herschel infrared Galactic (Hi-GAL) survey combined with 1.1 mm data from the Bolocam Galactic Plane Survey (BGPS), we compared emission in two types of environments: ultra-compact HII (UCHII) regions, and cold molecular clumps (denoted as cold clumps). With this comparison we tested dust emission models in the FIR-to-mm domain that reproduce emission in the diffuse medium, in these two environments (UCHII regions and cold clumps). We also investigated their ability to predict the dust emission in our Galaxy. We determined the emission spectra in twelve UCHII regions and twelve cold clumps, and derived the dust temperature (T) using the recent two-level system (TLS) model with three sets of parameters and the so-called T-$\beta$ (temperature-dust emissvity index) phenomenological models, with $\beta$ set to 1.5, 2 and 2.5. We tested the applicability of the TLS model in warm regions for the first time. This analysis indicates distinct trends in the dust emission between cold and warm environments that are visible through changes in the dust emissivity index. However, with the use of standard parameters, the TLS model is able to reproduce the spectral behavior observed in cold and warm regions, from the change of the dust temperature alone, whereas a T-$\beta$ model requires $\beta$ to be known.Comment: Accepted for publication in A&A. 19 pages, 8 figures, 7 table