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Decomposition of Arachis pintoi and Hyparrhenia rufa litters in monoculture and intercropped systems under lowland soil

Tropical grasslands under lowland soils are generally underutilized and the litter of forage legumes may be used to recover these degraded pastures. The objective of this work was to study the dynamics of litter decomposition of Arachis pintoi (pinto peanut), Hyparrhenia rufa (thatching grass) and a mixture of both species in a lowland soil. These treatments were analyzed in three areas: grass monoculture, legume monoculture and legume intercropped with the grass during the dry and wet seasons. Litter bags containing the legume, grass or a mixture of both species were incubated to estimate the decomposition rate and microorganism colonization. Decomposition constants (K) and litter half-lives (T1/2) were estimated by an exponential model whereas number of microorganisms in specific media were determined by plate dilution. The decomposition rate, release of nutrients and microorganisms number, especially bacteria, increased when pinto peanut was added to thatching grass, influenced by favorable lignin/N and C/N ratios in legume litter. When pinto peanut litter was incubated in the grass plots, 50% N and P was released within about 135 days in the dry season and in the wet season, the equivalent release occurred within 20 days. These results indicate that A. pintoi has a great potential for nutrient recycling via litter and can be used to recover degraded areas.

Limitations and information needs for engineered nanomaterial-specific exposure estimation and scenarios: recommendations for improved reporting practices

The aim of this paper is to describe the process and challenges in building exposure scenarios for engineered nanomaterials (ENM), using an exposure scenario format similar to that used for the European Chemicals regulation (REACH). Over 60 exposure scenarios were developed based on information from publicly available sources (literature, books, and reports), publicly available exposure estimation models, occupational sampling campaign data from partnering institutions, and industrial partners regarding their own facilities. The primary focus was on carbon-based nanomaterials, nano-silver (nano-Ag) and nano-titanium dioxide (nano-TiO2), and included occupational and consumer uses of these materials with consideration of the associated environmental release. The process of building exposure scenarios illustrated the availability and limitations of existing information and exposure assessment tools for characterizing exposure to ENM, particularly as it relates to risk assessment. This article describes the gaps in the information reviewed, recommends future areas of ENM exposure research, and proposes types of information that should, at a minimum, be included when reporting the results of such research, so that the information is useful in a wider context.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.