Automatic decomposition and efficient semi-structured meshing of complex solids

In this paper, a novel approach to automatically sub-divide a complex geometry and apply an efficient mesh is presented. Following the identification and removal of thin-sheet regions from an arbitrary solid using the thick/thin decomposition approach developed by Robinson et al. [1], the technique here employs shape metrics generated using local sizing measures to identify long-slender regions within the thick body. A series of algorithms automatically partition the thick region into a non-manifold assembly of long-slender and complex sub-regions. A structured anisotropic mesh is applied to the thin-sheet and long-slender bodies, and the remaining complex bodies are filled with unstructured isotropic tetrahedra. The resulting semi-structured mesh possesses significantly fewer degrees of freedom than the equivalent unstructured mesh, demonstrating the effectiveness of the approach. The accuracy of the efficient meshes generated for a complex geometry is verified via a study that compares the results of a modal analysis with the results of an equivalent analysis on a dense tetrahedral mesh.

Biotransformation and accumulation of arsenic in soil amended with seaweed

For many coastal regions of the world, it has been common practice to apply seaweed to the land as a soil improver and fertilizer. Seaweed is rich in arsenosugars and has a tissue concentration of arsenic up to 100 micro/g g(-1). These arsenic species are relatively nontoxic to humans; however, in the environment they may accumulate in the soil and decompose to more toxic arsenic species. The aim of this study was to determine the fate and biotransformation of these arsenosugars in soil using HPLC-ICP-MS analysis. Data from coastal soils currently manured with seaweeds were used to investigate if arsenic was accumulating in these soils. Long-term application of seaweed increased arsenic concentrations in these soils up to 10-fold (0.35 mg of As kg(-1) for nonagronomic peat, 4.3 mg of As kg(-1) for seaweed-amended peat). The biotransformation of arsenic was studied in microcosm experiments in which a sandy (machair) soil, traditionally manured with seaweed, was amended with Laminaria digitata and Fucus vesiculosus. In both seaweed species, the arsenic occurs in the form of arsenosugars (85%). The application of 50 g of seaweed to 1 kg of soil leads to an increase of arsenic in the soils, and the dominating species found in the soil pore water were dimethylarsinic acid (DMA(V)) and the inorganic species arsenate (As(V)) and arsenite (As(III)) after the initial appearance of arsenosugars. A proposed decomposition pathway of arsenosugars is discussed in which the arsenosugars are transformed to DMA(V) and further to inorganic arsenic without appreciable amounts of methylarsonic acid (MA(V)). Commercially available seaweed-based fertilizers contain arsenic concentration between 10 and 50 mg kg(-1). The arsenic species in these fertilizers depends on the manufacturing procedure. Some contain mainly arsenosugars while others contain mainly DMA(V) and inorganic arsenic. With the application rates suggested by the manufacturers, the application of these fertilizers is 2 orders of magnitude lower than the maximum permissible sewage sludge load for arsenic (varies from 0.025 kg ha(-1) yr(-1) in Styria, Austria, to 0.7 kg ha(-1) yr(-1) in the U.K.), while a direct seaweed application would exceed the maximum arsenic load by at least a factor of 2.

Climate-related changes in peatland carbon accumulation during the last millennium

Peatlands are a major terrestrial carbon store and a persistent natural carbon sink during the Holocene, but there is considerable uncertainty over the fate of peatland carbon in a changing climate. It is generally assumed that higher temperatures will increase peat decay, causing a positive feedback to climate warming and contributing to the global positive carbon cycle feedback. Here we use a new extensive database of peat profiles across northern high latitudes to examine spatial and temporal patterns of carbon accumulation over the past millennium. Opposite to expectations, our results indicate a small negative carbon cycle feedback from past changes in the long-term accumulation rates of northern peatlands. Total carbon accumulated over the last 1000 yr is linearly related to contemporary growing season length and photosynthetically active radiation, suggesting that variability in net primary productivity is more important than decomposition in determining long-term carbon accumulation. Furthermore, northern peatland carbon sequestration rate declined over the climate transition from the Medieval Climate Anomaly (MCA) to the Little Ice Age (LIA), probably because of lower LIA temperatures combined with increased cloudiness suppressing net primary productivity. Other factors including changing moisture status, peatland distribution, fire, nitrogen deposition, permafrost thaw and methane emissions will also influence future peatland carbon cycle feedbacks, but our data suggest that the carbon sequestration rate could increase over many areas of northern peatlands in a warmer future.

Carbon-14 wiggle-match dating of peat deposits: advantages and limitations

Carbon-14 wiggle-match dating (WMD) of peat deposits uses the non-linear relationship between 14C age and calendar age to match the shape of a series of closely spaced peat 14C dates with the 14C calibration curve. The method of WMD is discussed, and its advantages and limitations are compared with calibration of individual dates. A numerical approach to WMD is introduced that makes it possible to assess the precision of WMD chronologies. During several intervals of the Holocene, the 14C calibration curve shows less pronounced fluctuations. We assess whether wiggle-matching is also a feasible strategy for these parts of the 14C calibration curve. High-precision chronologies, such as obtainable with WMD, are needed for studies of rapid climate changes and their possible causes during the Holocene.

A Bayesian framework for age modeling of radiocarbon-dated peat deposits: Case studies from the Netherlands

Recently, Bayesian statistical software has been developed for age-depth modeling (wiggle-match dating) of sequences of densely spaced radiocarbon dates from peat cores. The method is described in non-statistical terms, and is compared with an alternative method of chronological ordering of 14C dates. Case studies include the dating of the start of agriculture in the northeastern part of the Netherlands, and of a possible Hekla-3 tephra layer in the same country. We discuss future enhancements in Bayesian age modeling.

Epitaxial Magnetic Oxide Nanocrystals Via Phase Decomposition of Bismuth Perovskite Precursors

The phase instability of bismuth perovskite (BiMO₃), where M is a ferromagnetic cation, is exploited to create self-assembled magnetic oxide nanocrystal arrays on oxide supports. Conditions during pulsed laser deposition are tuned so as to induce complete breakdown of the perovskite precursor into bismuth oxide (Bi₂ O₃ ) and metal oxide (M-O_x ) pockets. Subsequent cooling in vacuum volatizes the Bi₂ O₃ leaving behind an array of monodisperse nanocrystals. In situ reflective high energy electron diffraction beam is exploited to monitor the synthesis in real-time. Analysis of the patterns confi rms the phase separation and volatization process. Successful synthesis of M-O_x, where M = Mn, Fe, Co, and Cr, is shown using this template-free facile approach. Detailed magnetic characterization of nanocrystals is carried out to reveal the functionalities such as magnetic anisotropy as well as larger than bulk moments, as expected in these oxide nanostructures.

High-resolution reconstruction of atmospheric deposition of trace metals and metalloids since AD 1400 recorded by ombrotrophic peat cores in Hautes-Fagnes, Belgium

The objective of our study was to determine the trace metal accumulation rates in the Misten bog, Hautes-Fagnes, Belgium, and assess these in relation to established histories of atmospheric emissions from anthropogenic sources. To address these aims we analyzed trace metals and metalloids (Pb, Cu, Ni, As, Sb, Cr, Co, V, Cd and Zn), as well as Pb isotopes, using XRF, Q-ICP-MS and MC-ICP-MS, respectively in two 40-cm peat sections, spanning the last 600 yr. The temporal increase of metal fluxes from the inception of the Industrial Revolution to the present varies by a factor of 5–50, with peak values found between AD 1930 and 1990. A cluster analysis combined with Pb isotopic composition allows the identification of the main sources of Pb and by inference of the other metals, which indicates that coal consumption and metallurgical activities were the predominant sources of pollution during the last 600 years.

DRIFTS/MS/Isotopic Labeling Study on the NO-Moderated Decomposition of a Silica-Supported Nickel Nitrate Catalyst Precursor

In the preparation of silica-supported nickel oxide from nickel nitrate impregnation and drying, the replacement of the traditional air calcination step by a thermal treatment in 1% NO/Ar prevents agglomeration, resulting in highly dispersed NiO. The mechanism by which NO prevents agglomeration was investigated by using combined in situ diffuse reflectance infrared fourier transform (DRIFT) spectroscopy and mass spectrometry (MS). After impregnation and drying, a supported nickel hydroxynitrate phase with composition Ni(3)(NO(3))(2)(OH)(4) had been formed. Comparison of the evolution of the decomposition gases during the thermal decomposition of Ni(3)(NO(3))(2)(OH)(4) in labeled and unlabeled NO and O(2) revealed that NO scavenges oxygen radicals, forming NO(2). The DRIFT spectra revealed that the surface speciation evolved differently in the presence of NO as compared with in O(2) or Ar. It is proposed that oxygen scavenging by NO depletes the Ni(3)(NO(3))(2)(OH)(4) phase of nitrate groups, creating nucleation sites for the formation of NiO, which leads to very small (similar to 4 nm) NiO particles and prevents agglomeration.

Chemisorption and decomposition of pyrrole on Pd{111}

XPS, TPD and HREEL results indicate that molecular pyrrole is a fragile adsorbate on clean Pd{111}. At 200 K and for low coverages, the molecule remains intact and adopts an almost flat-lying geometry. With increasing coverage, pyrrole molecules tilt away from the surface and undergo N-H bond cleavage to form strongly tilted pyrrolyl (C4H4N) species. In addition, a weakly bound, strongly tilted form of molecular pyrrole is observed at coverages approaching saturation. Heating pyrrole monolayers results in desorption of similar to 15% of the overlayer as molecular pyrrole and N-a+ C4H4Na recombination with formation of hat-lying pyrrole molecules. This strongly bound species undergoes decomposition to adsorbed CN, CHx and H, leading ultimately to desorption of HCN and H-2. The implications of these results for the production of pyrrole by a heterogeneously catalysed route are discussed.

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

Water Content Determinations for Peat and Other Organic Soils Using the Oven-Drying Method

There has been much debate in the literature over the past 60 years regarding an appropriate oven-drying temperature for water content determinations in peat and other organic soils. For inorganic soils, the water content is usually based on the equilibrium dry mass corresponding to drying temperatures in the range 100-110°C. However, for peat and other organic soils, several researchers have recommended lower drying temperatures in the range 60-90°C in an attempt to prevent possible charring, oxidation, and/or vaporization of substances other than pore water. However, all of the relevant water is not fully evaporated at too low a temperature, and because specimen dry mass is a function of drying temperature, the resulting water content values are lower than those determined for the temperature range 100-110°C. Experimental data reported in this article show that oven drying of peat and other organic soils at 100-110°C using either gravity-convection or forced-draft ovens is acceptable for routine water content determinations. Because a standardized oven temperature is desirable when correlating water content with other material properties, it is recommended that oven drying of peat and other organic soils be performed over temperature ranges of either 105-110°C or 105 ± 5°C, in line with standardized ranges for inorganic soils. © 2014 Copyright Taylor & Francis Group, LLC.

NFA decomposition and multiprocessing architecture for parallel regular expression processing

This work presents a novel algorithm for decomposing NFA automata into one-state-active modules for parallel execution on Multiprocessor Systems on Chip (MP-SoC). Furthermore, performance related studies based on a 16-PE system for Snort, Bro and Linux-L7 regular expressions are presented. ©2009 IEEE.