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.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.

Distribution and pattern of moraines in Far NE Russia reveal former glacial extent

Here we present a series of six maps illustrating the distribution of end moraines in Far NE Russia. The maps are the first to systematically document the distribution of moraines across this region from the Verkhoyansk Mountains at the westernmost limit of our study area to the Chukchi Peninsula in the NE and to Kamchatka in the south, covering almost 4 million km2. Moraines were identified and mapped from analysis of satellite images and digital elevation model data. A total of 2173 moraines are identified, and we highlight some 197 more speculative features (perhaps moraines) that require further investigation. The distribution of moraines indicates that much of the region, now largely ice-free, was formerly occupied by glaciers centred upon the region’s uplands and that glacier outlets were typically < 200 km in length. The maps demonstrate the usefulness of remote sensing to derive an improved understanding of the glacial history of this vast and isolated region, and we present them to stimulate further work and act as a systematic framework for targeted geochronometric dating.

How position, velocity, and temporal information combine in the prospective control of catching:data and model

The cerebral cortex contains circuitry for continuously computing properties of the environment and one's body, as well as relations among those properties. The success of complex perceptuomotor performances requires integrated, simultaneous use of such relational information. Ball catching is a good example as it involves reaching and grasping of visually pursued objects that move relative to the catcher. Although integrated neural control of catching has received sparse attention in the neuroscience literature, behavioral observations have led to the identification of control principles that may be embodied in the involved neural circuits. Here, we report a catching experiment that refines those principles via a novel manipulation. Visual field motion was used to perturb velocity information about balls traveling on various trajectories relative to a seated catcher, with various initial hand positions. The experiment produced evidence for a continuous, prospective catching strategy, in which hand movements are planned based on gaze-centered ball velocity and ball position information. Such a strategy was implemented in a new neural model, which suggests how position, velocity, and temporal information streams combine to shape catching movements. The model accurately reproduces the main and interaction effects found in the behavioral experiment and provides an interpretation of recently observed target motion-related activity in the motor cortex during interceptive reaching by monkeys. It functionally interprets a broad range of neurobiological and behavioral data, and thus contributes to a unified theory of the neural control of reaching to stationary and moving targets.

The distribution of arsenic in soils affected by the Aznalcóllar mine spill, SW Spain

In April 1998, a holding lagoon containing pyrite ore processing waste, failed and released an estimated 5-6 million m(3) of metal rich sludge and acidic waters into the Rio Guadiamar, SW Spain. Over 2700 ha of the internationally important Doñana National and Natural Parks were contaminated. The sludge component of the waste contained up to 0.6% arsenic. This paper presents an extensive set of 0-5 cm soil analyses results from samples taken 6-8 months after the spill. Data are presented on pseudo-total arsenic levels in these samples, and on arsenic removed by both single batch and sequential extraction techniques. Pseudo-total levels of arsenic in the sludge ranged from 1521 to 3510 mg kg(-1), and a mean 4.4% of this was found to be extractable using 2.5% acetic acid. Soils in the Guadiamar Valley and Entremuros areas (those worst affected by the spill) were found to contain 85.4-782 mg kg(-1) and 7.1-196 mg kg(-1) pseudo-total arsenic, respectively. The mean acetic acid extractable component in these areas was 2.5% and 4.9%, respectively. Background pseudo-total arsenic levels in the soils of the area have been found to be 4.2-13.6 mg kg(-1). Rapid input of acidic waters, and the acidic nature of the sludge itself, may have caused depletion of Mg, Na and K, and to a lesser extent Mn, Ca and PO(4) in the upper 5 cm of the worst affected soils. Sequential extraction results suggest clear As-Fe associations, and possible As-Mn associations within the more soluble phases.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.

Postglacial dispersal, rather than in situ glacial survival, best explains the disjunct distribution of the Lusitanian plant species Daboecia cantabrica (Ericaceae)

Aim:

The distribution of the Lusitanian flora and fauna, species which are found only in southern and western Ireland and in northern Spain and Portugal but which are absent from intervening countries, represents one of the classic conundrums of biogeography. The aim of the present study was to determine whether the distribution of the Lusitanian plant species Daboecia cantabrica was due to persistence in separate Irish and Iberian refugia, or has resulted from post-glacial recolonization followed by subsequent extinction of intervening populations.

Location:

Northern Spain and Co. Galway, western Ireland.

Methods:

Palaeodistribution modelling using Maxent was employed to identify putative refugial areas for D. cantabrica at the Last Glacial Maximum (LGM). Phylogeographical analysis of samples from 64 locations in Ireland and Spain were carried out using a chloroplast marker (atpB–rbcL), the nuclear ITS region, and an anonymous nuclear single-copy locus.

Results:

The palaeodistribution model indicated areas with a high probability of survival for D. cantabrica at the LGM off the western coast of Galicia in Spain, and in the Bay of Biscay. Spanish populations exhibited substantially higher genetic diversity than Irish populations at all three loci, as well as geographical structuring of haplotypes within Spain consistent with divergence in separate refugia. Spanish populations also exhibited far more endemic haplotypes. Divergence time between Irish and Spanish populations associated with the putative Biscay refugium was estimated as 3.333–32 ka.

Main conclusions:

Our data indicate persistence by D. cantabrica throughout the LGM in two separate southern refugia: one in western Galicia and one in the area off the coast of western France which now lies in the Bay of Biscay. Spain was recolonized from both refugia, whilst Ireland was most likely recolonized from the Biscay refugium. On the balance of evidence across the three marker types and the palaeodistribution modelling, our findings do not support the idea of in situ survival of D. cantabrica in Ireland, contrary to earlier suggestions. The fact that we cannot conclusively rule out the existence of a small, more northerly refugium, however, highlights the need for further analysis of Lusitanian plant species.

The importance of solid-phase distribution on the oral bioaccessibility of Ni and Cr in soils overlying Palaeogene basalt lavas, Northern Ireland

Potentially toxic elements (PTEs) including nickel and chromium are often present in soils overlying basalt at concentrations above regulatory guidance values due to the presence of these elements in underlying geology. Oral bioaccessibility testing allows the risk posed by PTEs to human health to be assessed; however, bioaccessibility is controlled by factors including mineralogy, particle size, solid-phase speciation and encapsulation. X-ray diffraction was used to characterise the mineralogy of 12 soil samples overlying Palaeogene basalt lavas in Northern Ireland, and non-specific sequential extraction coupled with chemometric analysis was used to determine the distribution of elements amongst soil components in 3 of these samples. The data obtained were related to total concentration and oral bioaccessible concentration to determine whether a relationship exists between the overall concentrations of PTEs, their bioaccessibility and the soils mineralogy and geochemistry. Gastric phase bioaccessible fraction (BAF %) ranged from 0.4 to 5.4 % for chromium in soils overlying basalt and bioaccessible and total chromium concentrations are positively correlated. In contrast, the range of gastric phase BAF for nickel was greater (1.4–43.8 %), while no significant correlation was observed between bioaccessible and total nickel concentrations. However, nickel BAF was inversely correlated with total concentration. Solid-phase fractionation information showed that bioaccessible nickel was associated with calcium carbonate, aluminium oxide, iron oxide and clay-related components, while bioaccessible chromium was associated with clay-related components. This suggests that weathering significantly affects nickel bioaccessibility, but does not have the same effect on the bioaccessibility of chromium.

Temporal and geographical distribution of measles virus genotypes

The nucleotide sequence encoding the C terminus of the nucleocapsid protein of measles virus (MV) is the most variable in the genome. The sequence of this region is reported for 21 new MV strains and for virus RNA obtained from cases of subacute panencephalitis (SSPE) tissue. The nucleotide sequence of a total of 65 MV strains has been analysed using the CLUSTAL program to determine the relationships between the strains. An unrooted tree shows that eight different genotypes can be discerned amongst the sequences analysed so far. The data show that the C-terminal coding sequence of the nucleocapsid gene, although highly variable between strains, is stable in a given strain and does not appear to diverge in tissue culture. It therefore provides a good 'signature' sequence for specific genotypes. The sequence of this region can be used to discriminate new imported viruses from old 'endemic' strains of MV in a geographical area. The different genotypes are not geographically restricted although some appear to be the mainly 'endemic' types in large areas of the world. In global terms there appears to be at least four co-circulating genotypes of MV. The low level of divergence in the Edmonston lineage group isolated before 1970 indicates that some isolates are probably laboratory contaminants. This applies to some SSPE isolates such as the Halle, Mantooth and Horta-Barbosa strains as well as some wild-type isolates from that period.

Large-scale spatial patterns in the distribution of Collembola (Hexapoda) species in Antarctic terrestrial ecosystems

We tested whether the distribution of three common springtail species (Gressittacantha terranova, Gomphiocephalus hodgsoni and Friesea grisea) in Victoria Land (Antarctica) could be modelled as a function of latitude, longitude, altitude and distance from the sea.

Victoria Land, Ross Dependency, Antarctica.

Generalized linear models were constructed using species presence/absence data relative to geographical features (latitude, longitude, altitude, distance from sea) across the species' entire ranges. Model results were then integrated with the known phylogeography of each species and hypotheses were generated on the role of climate as a major driver of Antarctic springtail distribution.

Based on model selection using Akaike's information criterion, the species' distributions were: hump-shaped relative to longitude and monotonic with altitude for Gressittacantha terranova; hump-shaped relative to latitude and monotonic with altitude for Gomphiocephalus hodgsoni; and hump-shaped relative to longitude and monotonic with latitude, altitude and distance from the sea for Friesea grisea.

No single distributional pattern was shared by the three species. While distributions were partially a response to climatic spatial clines, the patterns observed strongly suggest that past geological events have influenced the observed distributions. Accordingly, present-day spatial patterns are likely to have arisen from the interaction of historical and environmental drivers. Future studies will need to integrate a range of spatial and temporal scales to further quantify their respective roles.

The effects of climate change on ovine parasitic gastroenteritis determined using veterinary surveillance and meteorological data for Northern Ireland over the period 1999-2009

While the influence of temperature and moisture on the free-living stages of gastrointestinal nematodes have been described in detail, and evidence for global climate change is mounting, there have been only a few attempts to relate altered incidence or seasonal patterns of disease to climate change. Studies of this type have been completed for England Scotland and Wales, but not for Northern Ireland (NI). Here we present an analysis of veterinary diagnostic data that relates three categories of gastrointestinal nematode infection in sheep to historical meteorological data for NI. The infections are: trichostrongylosis/teladorsagiosis (Teladorsagia/Trichostrongylus), strongyloidosis and nematodirosis. This study aims to provide a baseline for future climate change analyses and to provide basic information for the development of nematode control programmes. After identifying and evaluating possible sources of bias, climate change was found to be the most likely explanation for the observed patterns of change in parasite epidemiology, although other hypotheses could not be refuted. Seasonal rates of diagnosis showed a uniform year-round distribution for Teladorsagia and Trichostrongylus infections, suggesting consistent levels of larval survival throughout the year and extension of the traditionally expected seasonal transmission windows. Nematodirosis showed a higher level of autumn than Spring infection, suggesting that suitable conditions for egg and larval development occurred after the Spring infection period. Differences between regions within the Province were shown for strongyloidosis, with peaks of infection falling in the period September-November. For all three-infection categories (trichostrongylosis/teladorsagiosis, strongyloidosis and nematodirosis), significant differences in the rates of diagnosis, and in the seasonality of disease, were identified between regions. (C) 2012 Elsevier B.V. All rights reserved.

Application of factor analysis and geostatistics to identify processes controlling the distribution and bioaccessibility of trace elements in Northern Ireland soils

Geologic and environmental factors acting over varying spatial scales can control
trace element distribution and mobility in soils. In turn, the mobility of an element in soil will affect its oral bioaccessibility. Geostatistics, kriging and principal component analysis (PCA) were used to explore factors and spatial ranges of influence over a suite of 8 element oxides, soil organic carbon (SOC), pH, and the trace elements nickel (Ni), vanadium (V) and zinc (Zn). Bioaccessibility testing was carried out previously using the Unified BARGE Method on a sub-set of 91 soil samples from the Northern Ireland Tellus1 soil archive. Initial spatial mapping of total Ni, V and Zn concentrations shows their distributions are correlated spatially with local geologic formations, and prior correlation analyses showed that statistically significant controls were exerted over trace element bioaccessibility by the 8 oxides, SOC and pH. PCA applied to the geochemistry parameters of the bioaccessibility sample set yielded three principal components accounting for 77% of cumulative variance in the data
set. Geostatistical analysis of oxide, trace element, SOC and pH distributions using 6862 sample locations also identified distinct spatial ranges of influence for these variables, concluded to arise from geologic forming processes, weathering processes, and localised soil chemistry factors. Kriging was used to conduct a spatial PCA of Ni, V and Zn distributions which identified two factors comprising the majority of distribution variance. This was spatially accounted for firstly by basalt rock types, with the second component associated with sandstone and limestone in the region. The results suggest trace element bioaccessibility and distribution is controlled by chemical and geologic processes which occur over variable spatial ranges of influence.