Pedestrian wind comfort: feasibility study of criteria homogenisation

One of the aims of COST C14 action is the assessment and evaluation of pedestrian wind comfort. At present there is no general rule available that is applied across Europe. There are several criteria that have been developed and applied in different countries. These criteria are based on the definition of two independent parameters, a threshold effective wind speed and a probability of exceedence of this threshold speed. The difficulty of the criteria comparison arises from the two-dimensional character of the criteria definition. An effort is being made to compare these criteria, trying both to find commonalities and to clearly identify differences, in order to build up the basis for the next step: to try to define common criteria (perhaps with regional and seasonal variations). The first point is to define clearly the threshold effective wind speed (mean velocity definition parameters: averaging interval and reference height) and equivalence between different ways of defining the threshold effective wind speed (mean wind speed, gust equivalent mean, etc.) in comparable terms (as far as possible). It can be shown that if the wind speed at a given location is defined in terms of a probability distribution, e.g. Weibull function, a given criterion is satisfied by an infinite set of wind conditions, that is, of probability distributions. The criterion parameters and the Weibull function parameters are linked to each other, establishing a set called iso-criteria lines (the locus of the Weibull function parameters that fulfil a given criterion). The relative position of iso-criteria lines when displayed in a suitable two-dimensional plane facilitates the comparison of comfort criteria. The comparison of several wind comfort criteria, coming from several institutes is performed, showing the feasibility and limitations of the method.

Quantitative insight into proliferation and differentiation of oligodendrocyte type 2 astrocyte progenitor cells in vitro

As part of our attempts at understanding fundamental principles that underlie the generation of nondividing terminally differentiated progeny from dividing precursor cells, we have developed approaches to a quantitative analysis of proliferation and differentiation of oligodendrocyte type 2 astrocyte (O-2A) progenitor cells at the clonal level. Owing to extensive previous studies of clonal differentiation in this lineage, O-2A progenitor cells represent an excellent system for such an analysis. Previous studies have resulted in two competing hypotheses; one of them suggests that progenitor cell differentiation is symmetric, the other hypothesis introduces an asymmetric process of differentiation. We propose a general model that incorporates both such extreme hypotheses as special cases. Our analysis of experimental data has shown, however, that neither of these extreme cases completely explains the observed kinetics of O-2A progenitor cell proliferation and oligodendrocyte generation in vitro. Instead, our results indicate that O-2A progenitor cells become competent for differentiation after they complete a certain number of critical mitotic cycles that represent a period of symmetric development. This number varies from clone to clone and may be thought of as a random variable; its probability distribution was estimated from experimental data. Those O-2A cells that have undergone the critical divisions then may differentiate into an oligodendrocyte in each of the subsequent mitotic cycles with a certain probability, thereby exhibiting the asymmetric type of differentiation.

A wholly empirical explanation of perceived motion

Because the retinal activity generated by a moving object cannot specify which of an infinite number of possible physical displacements underlies the stimulus, its real-world cause is necessarily uncertain. How, then, do observers respond successfully to sequences of images whose provenance is ambiguous? Here we explore the hypothesis that the visual system solves this problem by a probabilistic strategy in which perceived motion is generated entirely according to the relative frequency of occurrence of the physical sources of the stimulus. The merits of this concept were tested by comparing the directions and speeds of moving lines reported by subjects to the values determined by the probability distribution of all the possible physical displacements underlying the stimulus. The velocities reported by observers in a variety of stimulus contexts can be accounted for in this way.

An information theory model of hydrophobic interactions.

A molecular model of poorly understood hydrophobic effects is heuristically developed using the methods of information theory. Because primitive hydrophobic effects can be tied to the probability of observing a molecular-sized cavity in the solvent, the probability distribution of the number of solvent centers in a cavity volume is modeled on the basis of the two moments available from the density and radial distribution of oxygen atoms in liquid water. The modeled distribution then yields the probability that no solvent centers are found in the cavity volume. This model is shown to account quantitatively for the central hydrophobic phenomena of cavity formation and association of inert gas solutes. The connection of information theory to statistical thermodynamics provides a basis for clarification of hydrophobic effects. The simplicity and flexibility of the approach suggest that it should permit applications to conformational equilibria of nonpolar solutes and hydrophobic residues in biopolymers.

Modelos não lineares resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada

Os controladores eletrônicos de pulverização visam minimizar a variação das taxas de insumos aplicadas no campo. Eles fazem parte de um sistema de controle, e permitem a compensação da variação de velocidade de deslocamento do pulverizador durante a operação. Há vários tipos de controladores eletrônicos de pulverização disponíveis no mercado e uma das formas de selecionar qual o mais eficiente nas mesmas condições, ou seja, em um mesmo sistema de controle, é quantificar o tempo de resposta do sistema para cada controlador específico. O objetivo desse trabalho foi estimar os tempos de resposta para mudanças de velocidade de um sistema eletrônico de pulverização via modelos de regressão não lineares, estes, resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada. Os dados foram obtidos no Laboratório de Tecnologia de Aplicação, localizado no Departamento de Engenharia de Biossistemas da Escola Superior de Agricultura \"Luiz de Queiroz\", Universidade de São Paulo, no município de Piracicaba, São Paulo, Brasil. Os modelos utilizados foram o logístico e de Gompertz, que resultam de uma soma ponderada de duas regressões lineares constantes com peso dado pela função distribuição acumulada logística e Gumbell, respectivamente. Reparametrizações foram propostas para inclusão do tempo de resposta do sistema de controle nos modelos, com o objetivo de melhorar a interpretação e inferência estatística dos mesmos. Foi proposto também um modelo de regressão não linear difásico que resulta da soma ponderada de regressões lineares constantes com peso dado pela função distribuição acumulada Cauchy seno hiperbólico exponencial. Um estudo de simulação foi feito, utilizando a metodologia de Monte Carlo, para avaliar as estimativas de máxima verossimilhança dos parâmetros do modelo.

Finite-size scaling analysis of the distributions of pseudo-critical temperatures in spin glasses

Using the results of large scale numerical simulations we study the probability distribution of the pseudo critical temperature for the three dimensional Edwards Anderson Ising spin glass and for the fully connected Sherrington-Kirkpatrick model. We find that the behaviour of our data is nicely described by straightforward finitesize scaling relations.

Alteration of natural ³⁷Ar activity concentration in the subsurface by gas transport and water infiltration

High ³⁷Ar activity concentration in soil gas is proposed as a key evidence for the detection of underground nuclear explosion by the Comprehensive Nuclear Test-Ban Treaty. However, such a detection is challenged by the natural background of ³⁷Ar in the subsurface, mainly due to Ca activation by cosmic rays. A better understanding and improved capability to predict ³⁷Ar activity concentration in the subsurface and its spatial and temporal variability is thus required. A numerical model integrating ³⁷Ar production and transport in the subsurface is developed, including variable soil water content and water infiltration at the surface. A parameterized equation for ³⁷Ar production in the first 15 m below the surface is studied, taking into account the major production reactions and the moderation effect of soil water content. Using sensitivity analysis and uncertainty quantification, a realistic and comprehensive probability distribution of natural ³⁷Ar activity concentrations in soil gas is proposed, including the effects of water infiltration. Site location and soil composition are identified as the parameters allowing for a most effective reduction of the possible range of ³⁷Ar activity concentrations. The influence of soil water content on ³⁷Ar production is shown to be negligible to first order, while ³⁷Ar activity concentration in soil gas and its temporal variability appear to be strongly influenced by transient water infiltration events. These results will be used as a basis for practical CTBTO concepts of operation during an OSI.

Bulk sediment element analysis of sediment cores GeoB10065-9 and GeoB10065-7, offshore northwest Sumba Island, Indonesia

The Australian-Indonesian monsoon has a governing influence on the agricultural practices and livelihood in the highly populated islands of Indonesia. However, little is known about the factors that have influenced past monsoon activity in southern Indonesia. Here, we present a ~6000 years high-resolution record of Australian-Indonesian summer monsoon (AISM) rainfall variations based on bulk sediment element analysis in a sediment archive retrieved offshore northwest Sumba Island (Indonesia). The record suggests lower riverine detrital supply and hence weaker AISM rainfall between 6000 yr BP and ~3000 yr BP compared to the Late Holocene. We find a distinct shift in terrigenous sediment supply at around 2800 yr BP indicating a reorganization of the AISM from a drier Mid Holocene to a wetter Late Holocene in southern Indonesia. The abrupt increase in rainfall at around 2800 yr BP coincides with a grand solar minimum. An increase in southern Indonesian rainfall in response to a solar minimum is consistent with climate model simulations that provide a possible explanation of the underlying mechanism responsible for the monsoonal shift. We conclude that variations in solar activity play a significant role in monsoonal rainfall variability at multi-decadal and longer timescales. The combined effect of orbital and solar forcing explains important details in the temporal evolution of AISM rainfall during the last 6000 years. By contrast, we find neither evidence for volcanic forcing of AISM variability nor for a control by long-term variations in the El Niño-Southern Oscillation (ENSO).

Modeling collisional processes in plasmas using discontinuous numerical methods

Thesis (Ph.D.)--University of Washington, 2016-06

Pseudo memory effects, majorization and entropy in quantum random walks

A quantum random walk on the integers exhibits pseudo memory effects, in that its probability distribution after N steps is determined by reshuffling the first N distributions that arise in a classical random walk with the same initial distribution. In a classical walk, entropy increase can be regarded as a consequence of the majorization ordering of successive distributions. The Lorenz curves of successive distributions for a symmetric quantum walk reveal no majorization ordering in general. Nevertheless, entropy can increase, and computer experiments show that it does so on average. Varying the stages at which the quantum coin system is traced out leads to new quantum walks, including a symmetric walk for which majorization ordering is valid but the spreading rate exceeds that of the usual symmetric quantum walk.

Molecular dynamics characterization of n-octyl-beta-D-glucopyranoside micelle structure in aqueous solution

n-Octyl-beta-D-glueopyranoside (OG) is a non-ionic glycolipid, which is used widely in biotechnical and biochemical applications. All-atom molecular dynamics simulations from two different initial coordinates and velocities in explicit solvent have been performed to characterize the structural behaviour of an OG aggregate at equilibrium conditions. Geometric packing properties determined from the simulations and small angle neutron scattering experiment state that OG micelles are more likely to exist in a non-spherical shape, even at the concentration range near to the critical micelle concentration (0.025 M). Despite few large deviations in the principal moment of inertia ratios, the average micelle shape calculated from both simulations is a prolate ellipsoid. The deviations at these time scales are presumably the temporary shape change of a micelle. However, the size of the micelle and the accessible surface areas were constant during the simulations with the micelle surface being rough and partially elongated. Radial distribution functions computed for the hydroxyl oxygen atoms of an OG show sharper peaks at a minimum van der Waals contact distance than the acetal oxygen, ring oxygen, and anomeric carbon atoms. This result indicates that these atoms are pointed outwards at the hydrophilic/hydrophobic interface, form hydrogen bonds with the water molecules, and thus hydrate the micelle surface effectively. (c) 2005 Elsevier Inc. All rights reserved.

The role of habitat disturbance and recovery in metapopulation persistence

Classical metapopulation theory assumes a static landscape. However, empirical evidence indicates many metapopulations are driven by habitat succession and disturbance. We develop a stochastic metapopulation model, incorporating habitat disturbance and recovery, coupled with patch colonization and extinction, to investigate the effect of habitat dynamics on persistence. We discover that habitat dynamics play a fundamental role in metapopulation dynamics. The mean number of suitable habitat patches is not adequate for characterizing the dynamics of the metapopulation. For a fixed mean number of suitable patches, we discover that the details of how disturbance affects patches and how patches recover influences metapopulation dynamics in a fundamental way. Moreover, metapopulation persistence is dependent not only oil the average lifetime of a patch, but also on the variance in patch lifetime and the synchrony in patch dynamics that results from disturbance. Finally, there is an interaction between the habitat and metapopulation dynamics, for instance declining metapopulations react differently to habitat dynamics than expanding metapopulations. We close, emphasizing the importance of using performance measures appropriate to stochastic systems when evaluating their behavior, such as the probability distribution of the state of the. metapopulation, conditional on it being extant (i.e., the quasistationary distribution).

Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.

Stochastic modelling of the invasion process of nematodes in fly larvae

Stochastic models based on Markov birth processes are constructed to describe the process of invasion of a fly larva by entomopathogenic nematodes. Various forms for the birth (invasion) rates are proposed. These models are then fitted to data sets describing the observed numbers of nematodes that have invaded a fly larval after a fixed period of time. Non-linear birthrates are required to achieve good fits to these data, with their precise form leading to different patterns of invasion being identified for three populations of nematodes considered. One of these (Nemasys) showed the greatest propensity for invasion. This form of modelling may be useful more generally for analysing data that show variation which is different from that expected from a binomial distribution.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.