Size distributions and temporal variations of biological aerosol particles in the Amazon rainforest characterized by microscopy and real-time UV-APS fluorescence techniques during AMAZE-08

As a part of the AMAZE-08 campaign during the wet season in the rainforest of central Amazonia, an ultraviolet aerodynamic particle sizer (UV-APS) was operated for continuous measurements of fluorescent biological aerosol particles (FBAP). In the coarse particle size range (> 1 mu m) the campaign median and quartiles of FBAP number and mass concentration were 7.3x10(4) m(-3) (4.0-13.2x10(4) m(-3)) and 0.72 mu g m(-3) (0.42-1.19 mu g m(-3)), respectively, accounting for 24% (11-41%) of total particle number and 47% (25-65%) of total particle mass. During the five-week campaign in February-March 2008 the concentration of coarse-mode Saharan dust particles was highly variable. In contrast, FBAP concentrations remained fairly constant over the course of weeks and had a consistent daily pattern, peaking several hours before sunrise, suggesting observed FBAP was dominated by nocturnal spore emission. This conclusion was supported by the consistent FBAP number size distribution peaking at 2.3 mu m, also attributed to fungal spores and mixed biological particles by scanning electron microscopy (SEM), light microscopy and biochemical staining. A second primary biological aerosol particle (PBAP) mode between 0.5 and 1.0 mu m was also observed by SEM, but exhibited little fluorescence and no true fungal staining. This mode may have consisted of single bacterial cells, brochosomes, various fragments of biological material, and small Chromalveolata (Chromista) spores. Particles liquid-coated with mixed organic-inorganic material constituted a large fraction of observations, and these coatings contained salts likely from primary biological origin. We provide key support for the suggestion that real-time laser-induce fluorescence (LIF) techniques using 355 nm excitation provide size-resolved concentrations of FBAP as a lower limit for the atmospheric abundance of biological particles in a pristine environment. We also show some limitations of using the instrument for ambient monitoring of weakly fluorescent particles < 2 mu m. Our measurements confirm that primary biological particles, fungal spores in particular, are an important fraction of supermicron aerosol in the Amazon and that may contribute significantly to hydrological cycling, especially when coated by mixed inorganic material.

Generalized beta-generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets. (c) 2011 Elsevier B.V. All rights reserved.

A Homonuclear Rotational Echo Double-Resonance Method for Measuring Site-Resolved Distance Distributions in I=1/2 Spin Pairs, Clusters, and Multispin Systems

Deutsche Forschungsgemeinschaft [SFB 858]

Levy stable distributions via associated integral transform

We present a method of generation of exact and explicit forms of one-sided, heavy-tailed Levy stable probability distributions g(alpha)(x), 0 <= x < infinity, 0 < alpha < 1. We demonstrate that the knowledge of one such a distribution g a ( x) suffices to obtain exactly g(alpha)p ( x), p = 2, 3, .... Similarly, from known g(alpha)(x) and g(beta)(x), 0 < alpha, beta < 1, we obtain g(alpha beta)( x). The method is based on the construction of the integral operator, called Levy transform, which implements the above operations. For a rational, alpha = l/k with l < k, we reproduce in this manner many of the recently obtained exact results for g(l/k)(x). This approach can be also recast as an application of the Efros theorem for generalized Laplace convolutions. It relies solely on efficient definite integration. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4709443]

Sets of probability distributions, independence, and convexity

This paper analyzes concepts of independence and assumptions of convexity in the theory of sets of probability distributions. The starting point is Kyburg and Pittarelli's discussion of "convex Bayesianism" (in particular their proposals concerning E-admissibility, independence, and convexity). The paper offers an organized review of the literature on independence for sets of probability distributions; new results on graphoid properties and on the justification of "strong independence" (using exchangeability) are presented. Finally, the connection between Kyburg and Pittarelli's results and recent developments on the axiomatization of non-binary preferences, and its impact on "complete" independence, are described.

Quantum deformation of the angular distributions of synchrotron radiation. Emission from particles in the first excited state

The exact expressions for the characteristics of synchrotron radiation of charged particles in the first excited state are obtained in analytical form using quantum theory methods. We performed a detailed analysis of the angular distribution structure of radiation power and its polarization for particles with spin 0 and 1/2. It is shown that the exact quantum calculations lead to results that differ substantially from the predictions of classical theory.

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e. g., fractional Brownian motion, Levy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation sigma t which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.

Weighted Fourier–Laplace transforms in reproducing kernel Hilbert spaces on the sphere

We study the action of a weighted Fourier–Laplace transform on the functions in the reproducing kernel Hilbert space (RKHS) associated with a positive definite kernel on the sphere. After defining a notion of smoothness implied by the transform, we show that smoothness of the kernel implies the same smoothness for the generating elements (spherical harmonics) in the Mercer expansion of the kernel. We prove a reproducing property for the weighted Fourier–Laplace transform of the functions in the RKHS and embed the RKHS into spaces of smooth functions. Some relevant properties of the embedding are considered, including compactness and boundedness. The approach taken in the paper includes two important notions of differentiability characterized by weighted Fourier–Laplace transforms: fractional derivatives and Laplace–Beltrami derivatives.

An evaluation of the distributions of polychlorinated biphenyls and organic matter in coastal sediments

The objective of this thesis is to improve the understanding of what processes and mechanism affects the distribution of polychlorinated biphenyls (PCBs) and organic carbon in coastal sediments. Because of the strong association of hydrophobic organic contaminants (HOCs) such as PCBs with organic matter in the aquatic environment, these two entities are naturally linked. The coastal environment is the most complex and dynamic part of the ocean when it comes to both cycling of organic matter and HOCs. This environment is characterised by the largest fluxes and most diverse sources of both entities. A wide array of methods was used to study these processes throughout this thesis. In the field sites in the Stockholm archipelago of the Baltic proper, bottom sediments and settling particulate matter were retrieved using sediment coring devices and sediment traps from morphometrically and seismically well-characterized locations. In the laboratory, the samples have been analysed for PCBs, stable carbon isotope ratios, carbon-nitrogen atom ratios as well as standard sediment properties. From the fieldwork in the Stockholm Archipelago and the following laboratory work it was concluded that the inner Stockholm archipelago has a low (≈ 4%) trapping efficiency for freshwater-derived organic carbon. The corollary is a large potential for long-range waterborne transport of OC and OC-associated nutrients and hydrophobic organic pollutants from urban Stockholm to more pristine offshore Baltic Sea ecosystems. Theoretical work has been carried out using Geographical Information Systems (GIS) and statistical methods on a database of 4214 individual sediment samples, each with reported individual PCB congener concentrations. From this work it was concluded that the continental shelf sediments are key global inventories and ultimate sinks of PCBs. Depending on congener, 10-80% of the cumulative historical emissions to the environment are accounted for in continental shelf sediments. Further it was concluded that the many infamous and highly contaminated surface sediments of urban harbours and estuaries of contaminated rivers cannot be of importance as a secondary source to sustain the concentrations observed in remote sediments. Of the global shelf PCB inventory < 1% are in sediments near population centres while ≥ 90% is in remote areas (> 10 km from any dwellings). The remote sub-basin of the North Atlantic Ocean contains approximately half of the global shelf sediment inventory for most of the PCBs studied.

Meridional changes in water mass distributions off NW Africa during November 2007/2008

[EN] An optimum multiparameter analysis was applied to a data set for the eastern boundary of the North Atlantic subtropical gyre, gathered during November of two consecutive years and spanning from 16 to 36º N. This data set covers over 20º of latitude with good meridional and zonal resolution over the whole coastal transition zone. The contribution from six water types in the depth range between 100 and 2000 m is solved. In the 100 to 700 m depth range the central waters of southern and northern origin meet abruptly at the Cape Verde Frontal Zone. This front traditionally has been reported to stretch from Cape Blanc, at about 21.5º N, to the Cape Verde Islands, but in our case it penetrates as far as 24º N over the continental slope. South of 21º N latitude we actually find a less saline and more oxygenated variety of South Atlantic Central Water, which we ascribe to less diluted equatorial waters. In the 700 to 1500 m depth range the dominant water type is a diluted form of Antarctic Intermediate Water (AAIW), whose influence smoothly disappears north of the Canary Islands as it is replaced by Mediterranean Water (MW); at latitudes where both water masses coexist, we observe MW offshore while AAIW is found near-shore. North Atlantic Deep Water is the dominating water type below about 1300/1700 m depth south/north of the Canary Islands; this abrupt change in depth suggests the existence of different paths for the deep waters reaching both sides of the archipelago.

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

A low complexity system based on multiple weighted decision trees for indoor localization

[EN] Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.