Estimation of soil water repellency of different particle size fractions in relation with carbon content by different methods

The water repellency of soils with different texture under different types of plant cover was determined by applying the WDPT and MED methods to both whole samples and the following size fractions: 2-1, 1-0.5, 0.5-0.25, 0.25-0.05 and <0.05 mm. Based on the results, the soils under maize crop and grassland, which were mostly wettable in the whole samples, exhibited water repellency in the finest fraction (<0.05 mm) as a result of its higher organic carbon content. On the other hand, all fractions in the forest soils, which were extremely water repellent, contributed to the overall repellency; in any case, the MED test revealed that the finest fraction was strongly repellent in the forest soils as well.     

Evaluation of a screening method for classifying virgin and recycled paper and board samples

This paper deals with the study of volatile compounds released by recycled paper and board. The aim of the study was to demonstrate the feasibility of headspace procedure coupled to gas chromatography/mass spectrometry (GC/MS) applied to complex paper‐based samples together with a chemometric procedure as a powerful method for screening potential volatile contaminants released by the recycled and virgin paper samples. Using this procedure, the identification of virgin or recycled paper could be achieved based on the identification on specific markers of the recycled pulp. Fifteen different samples within virgin and recycled paper were studied. After equilibration, the vapour phase of the samples was analysed by automatic headspace coupled online to GC/MS. The analytical approach for volatile compounds, their identification and the selection of some compounds as markers for recycled pulp are shown and discussed. A discriminate analysis applied to the set of results obtained allows classification of the samples into four different groups according to the content of recycled pulp (0, 10–30 and > 80% of recycled pulp), the surface treatment of the paper (no surface treatment, clay coating and plastic coating), the grammage (from < 100 to > 300 g/m²) and the sample thickness (from < 300 to > 600 µm). The matrix effect on the volatilization of some compounds from the paper samples and the analytical behaviour are also discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Effect of decortication and protease treatment on the kinetics of liquefaction,saccharification, and ethanol production from sorghum

BACKGROUND: This study analyzes the effect of decortication and protease treatment on the kinetics of liquefaction, saccharification and ethanol production from sorghum kernels. In general, bioethanol yields from sorghum are lower than those from maize. This has been attributed to reduced access of starch‐degrading enzymes due to the crosslinked protein net in the sorghum kernels. RESULTS: Liquefaction is described as a zero order kinetics process, with reaction rates enhanced by protease treatment. The use of protease almost doubled the liquefaction rate in both whole and decorticated sorghum, compared with untreated kernels. During saccharification of decorticated sorghum, protease treatment significantly affected the glucose/starch yield and the glucose concentration profile over time. When compared with maize, protease treatment of decorticated sorghum resulted in superior ethanol production rates. Specific ethanol yields during fermentation were statistically comparable with those for maize. CONCLUSION: Protease treatment of decorticated sorghum kernels can impart substantial economic benefits in terms of improvement of bioethanol yield (13% over whole sorghum) and in reduced fermentation time (approximately 50% with respect to maize). Copyright © 2010 Society of Chemical Industry     

Influence of phytosterol and phytostanol food supplementation on plasma liposoluble vitamins and provitamin A carotenoid levels in humans: An updated review of the evidence

Phytosterols and phytostanols (PAP) compete with cholesterol absorption in the intestine, resulting in a 5–15%-reduction in plasma total and LDL cholesterol. An important issue is the PAP potential to reduce the plasma concentrations of fat-soluble vitamins and provitamin A carotenoids. Here, an update of the scientific evidence is reviewed to evaluate plant PAP-enriched foods impact on plasma fat-soluble vitamins and carotenoid levels, and to discuss potential implications in terms of cardiovascular risk. Based on 49 human interventional and 3 bioavailability studies, results showed that regular consumption, particularly over the long term, of foods fortified with PAP as recommended in labeling does not significantly impact plasma vitamins A, D, and K concentration. A 10% significant median reduction was observed for α-tocopherol. Concerning carotenoids, while 13 studies did not demonstrate statistically significant plasma β-carotene reduction, 20 studies showed significant reductions, with median effect size of ?24%. This decline can be mitigated or offset by increased fruits and vegetables consumption. Furthermore, higher cardiovascular risk was observed for differences in plasma β-carotene concentration of the same magnitude as the estimated average decrease by PAP consumption. These results are supported by the only study of β-carotene bioavailability showing decrease in absorption by phytosterols daily intake.     

Bootstrap prediction intervals in state–space models

Abstract.  Prediction intervals in state–space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, with the true parameters substituted by consistent estimates. This approach has two limitations. First, it does not incorporate the uncertainty caused by parameter estimation. Second, the Gaussianity of future innovations assumption may be inaccurate. To overcome these drawbacks, Wall and Stoffer [ Journal of Time Series Analysis (2002) Vol. 23, pp. 733–751] propose a bootstrap procedure for evaluating conditional forecast errors that requires the backward representation of the model. Obtaining this representation increases the complexity of the procedure and limits its implementation to models for which it exists. In this article, we propose a bootstrap procedure for constructing prediction intervals directly for the observations, which does not need the backward representation of the model. Consequently, its application is much simpler, without losing the good behaviour of bootstrap prediction intervals. We study its finite-sample properties and compare them with those of the standard and the Wall and Stoffer procedures for the local level model. Finally, we illustrate the results by implementing the new procedure to obtain prediction intervals for future values of a real time series.     

Prediction of botanical composition in grassland herbage samples by near infrared reflectance spectroscopy

Near infrared reflectance spectroscopy (NIRS) was evaluated as a method to predict the botanical composition of seminatural grassland in ‘dehesa’ systems. Samples of herbaceous biomass were harvested over four consecutive years, determining in each—by manual separation—the proportion by weight of the following taxonomic groups: grasses, legumes and the rest of the families in a single block (‘others’). After reconstructing the natural samples they were analysed by NIRS. One set of samples (calibration set) was selected for the development of the equations, assaying different mathematical treatments (log l/R, first derivative and second derivative). The ranges of coefficients of multiple determination and standard errors of calibration, respectively, for the various components were: grasses, 0.86 to 0.92 and 6.66 to 9.14; legumes, 0.77 to 0.81 and 6.82 to 7.43; and ‘others’, 0.85 to 0.88 and 8.17 to 9.54. The remaining samples not included in the development of the NIRS equations (prediction set) were used for the purposes of validating the best equations. Standard errors of performance were: grasses, 6.12; legumes, 7.56 and ‘others’, 7.70.     

Risk factors for cognitive impairment in epilepsy.

The literature suggests that seizure disorders are associated with an increased likelihood of intellectual problems, prompting researchers to investigate risk factors of cognitive impairment in epileptic patients. This study examined the contribution of certain variables (age of seizure onset, duration, etiology, seizure location and laterality, sex, handedness, and cerebral speech pattern) to cognitive outcome in patients with medically refractory seizures. Seizure location (temporal or extratemporal), age of onset of seizures, and handedness proved to be the best indicators of general intellectual ability. There was a relatively diverse pattern of relationships when neuropsychological tests of language, visuospatial ability, and memory were considered individually. However, a factor analytic approach revealed a simpler pattern in which location of dysfunction, age at seizure onset, hand preference, cerebral speech dominance, and gender were relevant and independent indicators of verbal and nonverbal ability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of extractables from one euphorbia

Chemical analyses have been made of the heptane extractable material ofEuphorbia lathyris, a plant which has been proposed as an “energy farm” candidate. The heptane extract is 4–5% of the dry plant weight and has a heat value of ≈18×10³ BTU/Ib. This reduced photosynthetic material consists almost entirely of polycyclic triterpenoids.     

Grid Data Management: Open Problems and New Issues

Initially developed for the scientific community, Grid computing is now gaining much interest in important areas such as enterprise information systems. This makes data management critical since the techniques must scale up while addressing the autonomy, dynamicity and heterogeneity of the data sources. In this paper, we discuss the main open problems and new issues related to Grid data management. We first recall the main principles behind data management in distributed systems and the basic techniques. Then we make precise the requirements for Grid data management. Finally, we introduce the main techniques needed to address these requirements. This implies revisiting distributed database techniques in major ways, in particular, using P2P techniques. Work partially funded by ARA “Massive Data” of the French ministry of research (project Respire), the European Strep Grid4All project, the CAPES–COFECUB Daad project and the CNPq–INRIA Gridata project.