Temperature affects microbial decomposition of cadavers (Rattus rattus) in contrasting soils

The ecology of soils associated with dead mammals (i.e. cadavers) is poorly understood. Although temperature and soil type are well known to influence the decomposition of other organic resource patches, the effect of these variables on the degradation of cadavers in soil has received little experimental investigation. To address this, cadavers of juvenile rats (Rattus rattus) were buried in one of three contrasting soils (Sodosol, Rudosol, and Vertosol) from tropical savanna ecosystems in Queensland, Australia and incubated at 29 °C, 22 °C, or 15 °C in a laboratory setting. Cadavers and soils were destructively sampled at intervals of 7 days over an incubation period of 28 days. Measurements of decomposition included cadaver mass loss, carbon dioxide–carbon (CO2–C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, and soil pH, which were all significantly positively affected by cadaver burial. A temperature effect was observed where peaks or differences in decomposition that at occurred at higher temperature would occur at later sample periods at lower temperature. Soil type also had an important effect on some measured parameters. These findings have important implications for a largely unexplored area of soil ecology and nutrient cycling, which are significant for forensic science, cemetery planning and livestock carcass disposal.

Microbial decomposition of skeletal muscle tissue (Ovis aries) in a sandy loam soil at different temperatures

A laboratory experiment was conducted to determine the effect of temperature (2, 12, 22 °C) on the rate of aerobic decomposition of skeletal muscle tissue (Ovis aries) in a sandy loam soil incubated for a period of 42 days. Measurements of decomposition processes included skeletal muscle tissue mass loss, carbon dioxide (CO2) evolution, microbial biomass, soil pH, skeletal muscle tissue carbon (C) and nitrogen (N) content and the calculation of metabolic quotient (qCO2). Incubation temperature and skeletal muscle tissue quality had a significant effect on all of the measured process rates with 2 °C usually much lower than 12 and 22 °C. Cumulative CO2 evolution at 2, 12 and 22 °C equaled 252, 619 and 905 mg CO2, respectively. A significant correlation (P<0.001) was detected between cumulative CO2 evolution and tissue mass loss at all temperatures. Q10s for mass loss and CO2 evolution, which ranged from 1.19 to 3.95, were higher for the lower temperature range (Q10(2– 12 °C)>Q10(12–22 °C)) in the Ovis samples and lower for the low temperature range (Q10(2–12 °C)decomposition was most efficient at 2 °C. These phenomena may be due to lower microbial catabolic requirements at lower temperature.

Mushrooms and taphonomy: the fungi that mark woodland graves

Two closely related chemoecological groups of fungi, the ammonia fungi and the postputrefaction fungi, have been associated with the decomposition by-products of cadavers. Sporocarps have been observed in disparate woodlands across the world and often mark sites of graves. These groups of fungi provide visible markers of the sites of cadaver decomposition and follow repeated patterns of successional change as apparent decomposition proceeds. We suggest these phenomena may become a useful tool for crime scene investigation, forensic archaeology and forensic taphonomy.

Objective Empirical Mode Decomposition metric

Empirical Mode Decomposition (EMD) is a data driven technique for extraction of oscillatory components from data. Although it has been introduced over 15 years ago, its mathematical foundations are still missing which also implies lack of objective metrics for decomposed set evaluation. Most common technique for assessing results of EMD is their visual inspection, which is very subjective. This article provides objective measures for assessing EMD results based on the original definition of oscillatory components.

Heterogeneous tensor decomposition for clustering via manifold optimization

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

VELOCITY FIELD OF COMPRESSIBLE MAGNETOHYDRODYNAMIC TURBULENCE: WAVELET DECOMPOSITION AND MODE SCALINGS

We study compressible magnetohydrodynamic turbulence, which holds the key to many astrophysical processes, including star formation and cosmic-ray propagation. To account for the variations of the magnetic field in the strongly turbulent fluid, we use wavelet decomposition of the turbulent velocity field into Alfven, slow, and fast modes, which presents an extension of the Cho & Lazarian decomposition approach based on Fourier transforms. The wavelets allow us to follow the variations of the local direction of the magnetic field and therefore improve the quality of the decomposition compared to the Fourier transforms, which are done in the mean field reference frame. For each resulting component, we calculate the spectra and two-point statistics such as longitudinal and transverse structure functions as well as higher order intermittency statistics. In addition, we perform a Helmholtz-Hodge decomposition of the velocity field into incompressible and compressible parts and analyze these components. We find that the turbulence intermittency is different for different components, and we show that the intermittency statistics depend on whether the phenomenon was studied in the global reference frame related to the mean magnetic field or in the frame defined by the local magnetic field. The dependencies of the measures we obtained are different for different components of the velocity; for instance, we show that while the Alfven mode intermittency changes marginally with the Mach number, the intermittency of the fast mode is substantially affected by the change.

Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient

1. Litter decomposition recycles nutrients and causes large fluxes of carbon dioxide into the atmosphere. It is typically assumed that climate, litter quality and decomposer communities determine litter decay rates, yet few comparative studies have examined their relative contributions in tropical forests. 2. We used a short-term litterbag experiment to quantify the effects of litter quality, placement and mesofaunal exclusion on decomposition in 23 tropical forests in 14 countries. Annual precipitation varied among sites (760-5797 mm). At each site, two standard substrates (Raphia farinifera and Laurus nobilis) were decomposed in fine- and coarse-mesh litterbags both above and below ground for approximately 1 year. 3. Decomposition was rapid, with >95% mass loss within a year at most sites. Litter quality, placement and mesofaunal exclusion all independently affected decomposition, but the magnitude depended upon site. Both the average decomposition rate at each site and the ratio of above- to below-ground decay increased linearly with annual precipitation, explaining 60-65% of among-site variation. Excluding mesofauna had the largest impact on decomposition, reducing decomposition rates by half on average, but the magnitude of decrease was largely independent of climate. This suggests that the decomposer community might play an important role in explaining patterns of decomposition among sites. Which litter type decomposed fastest varied by site, but was not related to climate. 4. Synthesis. A key goal of ecology is to identify general patterns across ecological communities, as well as relevant site-specific details to understand local dynamics. Our pan-tropical study shows that certain aspects of decomposition, including average decomposition rates and the ratio of above- to below-ground decomposition are highly correlated with a simple climatic index: mean annual precipitation. However, we found no relationship between precipitation and effects of mesofaunal exclusion or litter type, suggesting that site-specific details may also be required to understand how these factors affect decomposition at local scales.

Relative effect of litter quality, forest type and their interaction on leaf decomposition in south-east Brazilian forests

Decomposition was studied in a reciprocal litter transplant experiment to examine the effects of forest type, litter quality and their interaction on leaf decomposition in four tropical forests in south-east Brazil. Litterbags were used to measure decomposition of leaves of one tree species from each forest type: Calophyllum brasiliense from restinga forest; Guapira opposita from Atlantic forest; Esenbeckia leiocarpa from semi-deciduous forest; and Copaifera langsdorffii from cerradao. Decomposition rates in rain forests (Atlantic and restinga) were twice as fast as those in seasonal forests (semi-deciduous and cerradao), suggesting that intensity and distribution of precipitation are important predictors of decomposition rates at regional scales. Decomposition rates varied by species, in the following order: E. leiocarpa > C. langsdorffii > G. opposita > C. brasiliense. However, there was no correlation between decomposition rates and chemical litter quality parameters: C:N, C:P, lignin concentration and lignin:N. The interaction between forest type and litter quality was positive mainly because C. langsdorffii decomposed faster than expected in its native forest. This is a potential indication of a decomposer`s adaptation to specific substrates in a tropical forest. These findings suggest that besides climate, interactions between decomposers and plants might play an essential role in decomposition processes and it must be better understood.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

HIERARCHICAL DECOMPOSITION OF MULTICLASS PROBLEMS

Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

The role of citrate precursors on the morphology of lanthanide oxides obtained by thermal decomposition

Two series of lanthanide oxides with different morphologies were synthesized through calcinations of two types of citrate polymeric precursors. These oxides were characterized by XRD patterns, SEM electronic microscopy, and N(2) adsorption isotherms. SEM microscopy analysis showed that the calcination of crystalline fibrous precursors [Ln(2)(LH)(3)center dot 2H(2)O] (L = citrate) originated fibrous shaped particles. On the other hand, the calcination of irregular shaped particles of precursors [LnL center dot xH(2)O] originated irregular shaped particles of oxide, pointing out a morphological template effect of precursors on the formation of the respective oxides.