On the Distribution of Signal Phase in Body Area Networks

In this letter, we investigate the distribution of the phase component of the complex received signal observed in practical experiments using body area networks. Two phase distributions, the recently proposed kappa-mu and eta-mu probability densities, which together encompass the most widely used fading models, namely Semi-Gaussian, Rayleigh, Hoyt, Rice, and Nakagami-m, have been compared with measurement data. The kappa-mu distribution has been found to provide the best fit over a range of on-body links, while the user was mobile. The experiments were carried out in two dissimilar indoor environments at opposite ends of the multipath spectrum. It has also been found that the uniform phase distribution has not arisen in anyone of the experiments.

The Area Distribution of Solar Magnetic Bright Points

Magnetic bright points (MBPs) are among the smallest observable objects on the solar photosphere. A combination of G-band observations and numerical simulations is used to determine their area distribution. An automatic detection algorithm, employing one-dimensional intensity profiling, is utilized to identify these structures in the observed and simulated data sets. Both distributions peak at an area of approximate to 45,000 km(2), with a sharp decrease toward smaller areas. The distributions conform with log-normal statistics, which suggests that flux fragmentation dominates over flux convergence. Radiative magneto-convection simulations indicate an independence in the MBP area distribution for differing magnetic flux densities. The most commonly occurring bright point size corresponds to the typical width of inter-granular lanes.

Distribution, extent of inter-annual variability and diet of the bloom-forming jellyfish Rhizostoma in European waters

Jellyfish (Cnidaria: Scyphozoa) are increasingly thought to play a number of important ecosystem roles, but often fundamental knowledge of their distribution, seasonality and inter-annual variability is lacking. Bloom forming species, due to their high densities, can have particularly intense trophic and socio-economic impacts. In northern Europe it is known that one particularly large (up to 30 kg wet weight) bloom forming jellyfish is Rhizostoma spp. Given the potential importance, we set out to review all known records from peer-reviewed and broader public literature of the jellyfish R. octopus (Linnaeus) and R. pulmo (Macri) (Scyphozoa: Rhizostomae) across western Europe. These data revealed distinct hotspots where regular Rhizostoma spp. aggregations appeared to form, with other sites characterized by occasional abundances and a widespread distribution of infrequent observations. Surveys of known R. octopus hotspots around the Irish Sea also revealed marked inter-annual variation with particularly high abundances forming during 2003. The location of such consistent aggregations and inter-annual variances are discussed in relation to physical, climatic and dietary variations.

The broad-scale distribution of five jellyfish species across a temperate coastal environment

Jellyfish (medusae) are sometimes the most noticeable and abundant members of coastal planktonic communities, yet ironically, this high conspicuousness is not reflected in our overall understanding of their spatial distributions across large expanses of water. Here, we set out to elucidate the spatial (and temporal) patterns for five jellyfish species (Phylum Cnidaria, Orders Rhizostomeae and Semaeostomeae) across the Irish & Celtic Seas, an extensive shelf-sea area at Europe's northwesterly margin encompassing several thousand square kilometers. Data were gathered using two independent methods: (1) surface-counts of jellyfish from ships of opportunity, and (2) regular shoreline surveys for stranding events over three consecutive years. Jellyfish species displayed distinct species-specific distributions, with an apparent segregation of some species. Furthermore, a different species composition was noticeable between the northern and southern parts of the study area. Most importantly, our data suggests that jellyfish distributions broadly reflect the major hydrographic regimes (and associated physical discontinuities) of the study area, with mixed water masses possibly acting as a trophic barrier or non-favourable environment for the successful growth and reproduction of jellyfish species.

The ocean sunfish Mola mola: insights into distribution, abundance and behaviour in the Irish and Celtic Seas

Here we provide baseline data on the distribution and abundance of Mola mola within the Irish and Celtic Seas, made during aerial surveys from June to October during 2003-2005. These data were considered in conjunction with concurrent observations of three potential jellyfish prey species found throughout the region: Rhizostoma octopus, Chrysaora hysoscella and Cyanea capillata. A total area of 7850 km(2) was surveyed over the three years with an observed abundance of 68 sunfish giving a density of 0.98 ind/100 km(2). Although modest, these findings highlight that the species is more common than once thought around Britain and Ireland and an order of magnitude greater than the other apex jellyfish predator found in the region, the leatherback turtle (Dermochelys coriacea). furthermore, the distribution of sunfish sightings was inconsistent with the extensive aggregations of Rhizostoma octopus found throughout the study area. The modelled distributions of predator-prey co-occurrence (using data for all three jellyfish species) was less than the observed co-occurrence with the implication that neither jellyfish nor sunfish were randomly distributed but co-occurred more in the same areas than expected by chance. Finally, observed sunfish were typically small (similar to 1 in or less) and seen to either bask or actively swim at the surface.

Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads

In small islands, a freshwater lens can develop due to the recharge induced by rain. Magnitude and spatial distribution of this recharge control the elevation of freshwater and the depth of its interface with salt water. Therefore, the study of lens morphology gives useful information on both the recharge and water uptake due to evapotranspiration by vegetation. Electrical resistivity tomography was applied on a small coral reef island, giving relevant information on the lens structure. Variable density groundwater flow models were then applied to simulate freshwater behavior. Cross validation of the geoelectrical model and the groundwater model showed that recharge exceeds water uptake in dunes with little vegetation, allowing the lens to develop. Conversely, in the low-lying and densely vegetated sectors, where water uptake exceeds recharge, the lens cannot develop and seawater intrusion occurs. This combined modeling method constitutes an original approach to evaluate effective groundwater recharge in such environments.
[Comte, J.-C., O. Banton, J.-L. Join, and G. Cabioch (2010), Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads, Water Resour. Res., 46, W06601, doi:10.1029/2009WR008058.]

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Comparison of Experimental PIV Data and CFD Simulations for Flow in a Diesel Particulate Filter Inlet Diffuser

Flow maldistribution of the exhaust gas entering a Diesel Particulate Filter (DPF) can cause uneven soot distribution during loading and excessive temperature gradients during the regeneration phase. Minimising the magnitude of this maldistribution is therefore an important consideration in the design of the inlet pipe and diffuser, particularly in situations where packaging constraints dictate bends in the inlet pipe close to the filter, or a sharp diffuser angle. This paper describes the use of Particle Image Velocimetry (PIV) to validate a Computational Fluid Dynamic (CFD) model of the flow within the inlet diffuser of a DPF so that CFD can be used with confidence as a tool to minimise this flow maldistribution. PIV is used to study the flow of gas into a DPF over a range of steady state flow conditions. The distribution of flow approaching the front face of the substrate was of particular interest to this study. Optically clear diffusing cones were designed and placed between pipe and substrate to allow PIV analysis to take place. Stereoscopic PIV was used to eliminate any error produced by the optical aberrations caused by looking through the curved wall of the inlet cone. In parallel to the experiments, numerical analysis was carried out using a CFD program with an incorporated DPF model. Boundary conditions for the CFD simulations were taken from the experimental data, allowing an experimental validation of the numerical results. The CFD model incorporated a DPF model, the cement layers seen in segmented filters and the intumescent matting that is commonly used to pack the filter into a metal casing. The mesh contained approximately 580,000 cells and used the realizable ?-e turbulence model. The CFD simulation predicted both pressure drop across the DPF and the velocity field within the cone and at the DPF face with reasonable accuracy, providing confidence in the use the CFD in future work to design new, more efficient cones.

The velocity distribution of solar photospheric magnetic bright points.

We use high spatial resolution observations and numerical simulations to study the velocity distribution of solar photospheric magnetic bright points. The observations were obtained with the Rapid Oscillations in the Solar Atmosphere instrument at the Dunn Solar Telescope, while the numerical simulations were undertaken with the MURaM code for average magnetic fields of 200 G and 400 G. We implemented an automated bright point detection and tracking algorithm on the data set and studied the subsequent velocity characteristics of over 6000 structures, finding an average velocity of approximately 1 km s(-1), with maximum values of 7 km s(-1). Furthermore, merging magnetic bright points were found to have considerably higher velocities, and significantly longer lifetimes, than isolated structures. By implementing a new and novel technique, we were able to estimate the background magnetic flux of our observational data, which is consistent with a field strength of 400 G.

Optimization of heat transfer characteristics, flow distribution, and reaction processing for a microstructured reactor/heat-exchanger for optimal performance in platinum catalyzed ammonia oxidation

The present work is focused on the demonstration of the advantages of miniaturized reactor systems which are essential for processes where potential for considerable heat transfer intensification exists as well as for kinetic studies of highly exothermic reactions at near-isothermal conditions. The heat transfer characteristics of four different cross-flow designs of a microstructured reactor/heat-exchanger (MRHE) were studied by CFD simulation using ammonia oxidation on a platinum catalyst as a model reaction. An appropriate distribution of the nitrogen flow used as a coolant can decrease drastically the axial temperature gradient in the reaction channels. In case of a microreactor made of a highly conductive material, the temperature non-uniformity in the reactor is strongly dependent on the distance between the reaction and cooling channels. Appropriate design of a single periodic reactor/heat-exchanger unit, combined with a non-uniform inlet coolant distribution, reduces the temperature gradients in the complete reactor to less than 4degreesC, even at conditions corresponding to an adiabatic temperature rise of about 1400degreesC, which are generally not accessible in conventional reactors because of the danger of runaway reactions. To obtain the required coolant flow distribution, an optimization study was performed to acquire the particular geometry of the inlet and outlet chambers in the microreactor/heat-exchanger. The predicted temperature profiles are in good agreement with experimental data from temperature sensors located along the reactant and coolant flows. The results demonstrate the clear potential of microstructured devices as reliable instruments for kinetic research as well as for proper heat management in the case of highly exothermic reactions. (C) 2002 Elsevier Science B.V. All rights reserved.

Distribution and status of the Red Squirrel (Sciurus vulgaris) and Grey Squirrel (Sciurus carolinensis) in Ireland

The distributions of the Red and Grey Squirrel were surveyed in Northern Ireland and the Republic of Ireland between 1994 and 1996. Survey methods differed between the two studies. In the former, all suitable habitat, of at least 15 ha, was inspected for species presence or absence. In the Republic, data were gathered through questionnaires to governmental and independent wildlife bodies. The combined results indicate that the Red Squirrel remains widespread and locally abundant, and is present in all but two counties. The Grey Squirrel is now more widespread than ever before, and can be found in 22 of the 32 counties. Its range expansion has varied from 0 km/yr to an estimated 13.4 km/yr, as various geographical features, principally rivers, have hindered its progress in certain directions.

Polar distribution of ablated atomic material during the pulsed laser deposition of Cu in vacuum: Dependence on focused laser spot size and power density

Experiments have been carried out to investigate the polar distribution of atomic material ablated during the pulsed laser deposition of Cu in vacuum. Data were obtained as functions of focused laser spot size and power density. Thin films were deposited onto flat glass substrates and thickness profiles were transformed into polar atomic flux distributions of the form f(theta)=cos(n) theta. At constant focused laser power density on target, I=4.7+/-0.3X10(8) W/cm(2), polar distributions were found to broaden with a reduction in the focused laser spot size. The polar distribution exponent n varied from 15+/-2 to 7+/-1 for focused laser spot diameter variation from 2.5 to 1.4 mm, respectively, with the laser beam exhibiting a circular aspect on target. With the focused laser spot size held constant at phi=1.8 mm, polar distributions were observed to broaden with a reduction in the focused laser power density on target, with the associated polar distribution exponent n varying from 13+/-1.5 to 8+/-1 for focused laser power density variation from 8.3+/-0.3X10(8) to 2.2+/-0.1X10(8) W/cm(2) respectively. Data were compared with an analytical model available within the literature, which correctly predicts broadening of the polar distribution with a reduction in focused laser spot size and with a reduction in focused laser power density, although the experimentally observed magnitude was greater than that predicted in both cases. (C) 1996 American Institute of Physics.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.