Does repeated burial of skeletal muscle tissue (Ovis aries) in soil affect subsequent decomposition?

The repeated introduction of an organic resource to soil can result in its enhanced degradation. This phenomenon is of primary importance in agroecosystems, where the dynamics of repeated nutrient, pesticide, and herbicide amendment must be understood to achieve optimal yield. Although not yet investigated, the repeated introduction of cadaveric material is an important area of research in forensic science and cemetery planning. It is not currently understood what effects the repeated burial of cadaveric material has on cadaver decomposition or soil processes such as carbon mineralization. To address this gap in knowledge, we conducted a laboratory experiment using ovine (Ovis aries) skeletal muscle tissue (striated muscle used for locomotion) and three contrasting soils (brown earth, rendzina, podsol) from Great Britain. This experiment comprised two stages. In Stage I skeletal muscle tissue (150 g as 1.5 g cubes) was buried in sieved (4.6 mm) soil (10 kg dry weight) calibrated to 60% water holding capacity and allowed to decompose in the dark for 70 days at 22 °C. Control samples comprised soil without skeletal muscle tissue. In Stage II, soils were weighed (100 g dry weight at 60% WHC) into 1285 ml incubation microcosms. Half of the soils were designated for a second tissue amendment, which comprised the burial (2.5 cm) of 1.5 g cube of skeletal muscle tissue. The remaining half of the samples did not receive tissue. Thus, four treatments were used in each soil, reflecting all possible combinations of tissue burial (+) and control (−). Subsequent measures of tissue mass loss, carbon dioxide-carbon evolution, soil microbial biomass carbon, metabolic quotient and soil pH show that repeated burial of skeletal muscle tissue was associated with a significantly greater rate of decomposition in all soils. However, soil microbial biomass following repeated burial was either not significantly different (brown earth, podsol) or significantly less (rendzina) than new gravesoil. Based on these results, we conclude that enhanced decomposition of skeletal muscle tissue was most likely due to the proliferation of zymogenous soil microbes able to better use cadaveric material re-introduced to the soil.

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.

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.

The iso-Score Curve Graph. A new tool for competitive bidding

The present work describes a new tool that helps bidders improve their competitive bidding strategies. This new tool consists of an easy-to-use graphical tool that allows the use of more complex decision analysis tools in the field of Competitive Bidding. The graphic tool described here tries to move away from previous bidding models which attempt to describe the result of an auction or a tender process by means of studying each possible bidder with probability density functions. As an illustration, the tool is applied to three practical cases. Theoretical and practical conclusions on the great potential breadth of application of the tool are also presented.

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.