The valuation of N-phased investment projects under jump-diffusion processes

In this paper we consider N-phased investment opportunities where the time evolution of the project value follows a jump-diffusion process. An explicit valuation formula is derived under two different scenarios: in the first case we consider fixed and certain investment costs and in the second case we consider cost uncertainty and assume that investment costs follow a jump-diffusion process

Bottom-up retinotopic organization supports top-down mental imagery

Finding a path between locations is a routine task in daily life. Mental navigation is often used to plan a route to a destination that is not visible from the current location. We first used functional magnetic resonance imaging (fMRI) and surface-based averaging methods to find high-level brain regions involved in imagined navigation between locations in a building very familiar to each participant. This revealed a mental navigation network that includes the precuneus, retrosplenial cortex (RSC), parahippocampal place area (PPA), occipital place area (OPA), supplementary motor area (SMA), premotor cortex, and areas along the medial and anterior intraparietal sulcus. We then visualized retinotopic maps in the entire cortex using wide-field, natural scene stimuli in a separate set of fMRI experiments. This revealed five distinct visual streams or ‘fingers’ that extend anteriorly into middle temporal, superior parietal, medial parietal, retrosplenial and ventral occipitotemporal cortex. By using spherical morphing to overlap these two data sets, we showed that the mental navigation network primarily occupies areas that also contain retinotopic maps. Specifically, scene-selective regions RSC, PPA and OPA have a common emphasis on the far periphery of the upper visual field. These results suggest that bottom-up retinotopic organization may help to efficiently encode scene and location information in an eye-centered reference frame for top-down, internally generated mental navigation. This study pushes the border of visual cortex further anterior than was initially expected

The role of Lambda in the cosmological lens equation

The cosmological constant Lambda affects cosmological gravitational lensing. Effects due to Lambda can be studied in the framework of the Schwarzschild-de Sitter spacetime. Two novel contributions, which can not be accounted for by a proper use of angular diameter distances, are derived. First, a term 2m b Lambda/3 has to be added to the bending angle, where "m" is the lens mass and "b" the impact parameter. Second, Lambda brings about a difference in the redshifts of multiple images. Both effects are quite small for real astrophysical systems (contribution to the bending < 0.1 microarcsec and difference in redshift < 10^{-7}).Comment: 4 pages. (Univ. Zuerich); v2: presentation improved, discussion extended, references to papers posted after the v1-version added. In press on Phys. Rev. Let

On the evolution of the entropy and pressure profiles in X-ray luminous galaxy clusters at z > 0.4

Galaxy clusters are the most recent products of hierarchical accretion over cosmological scales. The gas accreted from the cosmic field is thermalized inside the cluster halo. Gas entropy and pressure are expected to have a self-similar behaviour with their radial distribution following a power law and a generalized Navarro-Frenk-White profile, respectively. This has been shown also in many different hydrodynamical simulations. We derive the spatially-resolved thermodynamical properties of 47 X-ray galaxy clusters observed with Chandra in the redshift range 0.4 < z < 1.2, the largest sample investigated so far in this redshift range with X-rays spectroscopy, with a particular care in reconstructing the gas entropy and pressure radial profiles. We search for deviation from the self-similar behaviour and look for possible evolution with redshift. The entropy and pressure profiles lie very close to the baseline prediction from gravitational structure formation. We show that these profiles deviate from the baseline prediction as function of redshift, in particular at z > 0.75, where, in the central regions, we observe higher values of the entropy (by a factor of 2.2) and systematically lower estimates (by a factor of 2.5) of the pressure. The effective polytropic index, which retains informations about the thermal distribution of the gas, shows a slight linear positive evolution with the redshift and the concentration of the dark matter distribution. A prevalence of non-cool-core, disturbed systems, as we observe at higher redshifts, can explain such behaviours.Comment: 14 pages, 18 figures, accepted for publication by A&

Mass - concentration relation and weak lensing peak counts

The statistics of peaks in weak lensing convergence maps is a promising tool to investigate both the properties of dark matter haloes and constrain the cosmological parameters. We study how the number of detectable peaks and its scaling with redshift depend upon the cluster dark matter halo profiles and use peak statistics to constrain the parameters of the mass - concentration (MC) relation. We investigate which constraints the Euclid mission can set on the MC coefficients also taking into account degeneracies with the cosmological parameters. To this end, we first estimate the number of peaks and its redshift distribution for different MC relations. We find that the steeper the mass dependence and the larger the normalisation, the higher is the number of detectable clusters, with the total number of peaks changing up to $40\%$ depending on the MC relation. We then perform a Fisher matrix forecast of the errors on the MC relation parameters as well as cosmological parameters. We find that peak number counts detected by Euclid can determine the normalization $A_v$, the mass $B_v$ and redshift $C_v$ slopes and intrinsic scatter $\sigma_v$ of the MC relation to an unprecedented accuracy being $\sigma(A_v)/A_v = 1\%$, $\sigma(B_v)/B_v = 4\%$, $\sigma(C_v)/C_v = 9\%$, $\sigma(\sigma_v)/\sigma_v = 1\%$ if all cosmological parameters are assumed to be known. Should we relax this severe assumption, constraints are degraded, but remarkably good results can be restored setting only some of the parameters or combining peak counts with Planck data. This precision can give insight on competing scenarios of structure formation and evolution and on the role of baryons in cluster assembling. Alternatively, for a fixed MC relation, future peaks counts can perform as well as current BAO and SNeIa when combined with Planck.Comment: 14 pages, 8 figures, accepted for publication on Astronomy & Astrophysic

Characteristics of Eye-Position Gain Field Populations Determine Geometry of Visual Space

We have previously demonstrated differences in eye-position spatial maps for anterior inferotemporal cortex (AIT) in the ventral stream and lateral intraparietal cortex (LIP) in the dorsal stream, based on population decoding of gaze angle modulations of neural visual responses (i.e., eye-position gain fields). Here we explore the basis of such spatial encoding differences through modeling of gain field characteristics. We created a population of model neurons, each having a different eye-position gain field. This population was used to reconstruct eye-position visual space using multidimensional scaling. As gain field shapes have never been well established experimentally, we examined different functions, including planar, sigmoidal, elliptical, hyperbolic, and mixtures of those functions. All functions successfully recovered positions, indicating weak constraints on allowable gain field shapes. We then used a genetic algorithm to modify the characteristics of model gain field populations until the recovered spatial maps closely matched those derived from monkey neurophysiological data in AIT and LIP. The primary differences found between model AIT and LIP gain fields were that AIT gain fields were more foveally dominated. That is, gain fields in AIT operated on smaller spatial scales and smaller dispersions than in LIP. Thus we show that the geometry of eye-position visual space depends on the population characteristics of gain fields, and that differences in gain field characteristics for different cortical areas may underlie differences in the representation of space

Utilização racional de touros em monta natural.

bitstream/CPAP/56379/1/ADM042.pdfFormato eletrônico

Origin of symbol-using systems: speech, but not sign, without the semantic urge

Natural language—spoken and signed—is a multichannel phenomenon, involving facial and body expression, and voice and visual intonation that is often used in the service of a social urge to communicate meaning. Given that iconicity seems easier and less abstract than making arbitrary connections between sound and meaning, iconicity and gesture have often been invoked in the origin of language alongside the urge to convey meaning. To get a fresh perspective, we critically distinguish the origin of a system capable of evolution from the subsequent evolution that system becomes capable of. Human language arose on a substrate of a system already capable of Darwinian evolution; the genetically supported uniquely human ability to learn a language reflects a key contact point between Darwinian evolution and language. Though implemented in brains generated by DNA symbols coding for protein meaning, the second higher-level symbol-using system of language now operates in a world mostly decoupled from Darwinian evolutionary constraints. Examination of Darwinian evolution of vocal learning in other animals suggests that the initial fixation of a key prerequisite to language into the human genome may actually have required initially side-stepping not only iconicity, but the urge to mean itself. If sign languages came later, they would not have faced this constraint

Dissemination of three coliphages in chicken’s organism

Fundação para a Ciência e a Tecnologia (FCT

Population Coding of Visual Space: Comparison of Spatial Representations in Dorsal and Ventral Pathways

Although the representation of space is as fundamental to visual processing as the representation of shape, it has received relatively little attention from neurophysiological investigations. In this study we characterize representations of space within visual cortex, and examine how they differ in a first direct comparison between dorsal and ventral subdivisions of the visual pathways. Neural activities were recorded in anterior inferotemporal cortex (AIT) and lateral intraparietal cortex (LIP) of awake behaving monkeys, structures associated with the ventral and dorsal visual pathways respectively, as a stimulus was presented at different locations within the visual field. In spatially selective cells, we find greater modulation of cell responses in LIP with changes in stimulus position. Further, using a novel population-based statistical approach (namely, multidimensional scaling), we recover the spatial map implicit within activities of neural populations, allowing us to quantitatively compare the geometry of neural space with physical space. We show that a population of spatially selective LIP neurons, despite having large receptive fields, is able to almost perfectly reconstruct stimulus locations within a low-dimensional representation. In contrast, a population of AIT neurons, despite each cell being spatially selective, provide less accurate low-dimensional reconstructions of stimulus locations. They produce instead only a topologically (categorically) correct rendition of space, which nevertheless might be critical for object and scene recognition. Furthermore, we found that the spatial representation recovered from population activity shows greater translation invariance in LIP than in AIT. We suggest that LIP spatial representations may be dimensionally isomorphic with 3D physical space, while in AIT spatial representations may reflect a more categorical representation of space (e.g., “next to” or “above”)