Laser‐induced surface structures on gold‐coated polymers: Influence of morphology on surface‐enhanced Raman scattering enhancement

The fabrication of highly sensitive and reproducible substrates for Surface‐Enhanced Raman Scattering (SERS) remains a challenging scientific and technological issue. In this work, laser‐induced periodic surface structures are generated on poly(trimethylen terephthalate) films upon laser irradiation with the linearly polarized beams of a Nd:YAG laser (4th harmonic, 266 nm), an ArF excimer laser (193 nm), and a Titanium:sapphire laser (795 nm), resulting in periods close to the laser wavelength when irradiating at normal incidence, and larger periods for different angles of incidence. Additional irradiation with a circularly polarized beam at 266 nm produces superficial circular structures. The nanostructured polymers are coated with a nanoparticle assembled gold layer by pulsed laser deposition at 213 nm. The capabilities of these substrates for SERS are evaluated using benzenethiol as a test molecule and different degrees of Raman signal enhancement are observed depending on the nanostructure type. The highest enhancement factor is obtained by for nanostructured substrates with the highest values of period, depth, and roughness. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42770.     

Rosuvastatin Enhances the Catabolism of LDL apoB‐100 in Subjects with Combined Hyperlipidemia in a Dose Dependent Manner

Dose‐associated effects of rosuvastatin on the metabolism of apolipoprotein (apo) B‐100 in triacylglycerol rich lipoprotein (TRL, d < 1.019 g/ml) and low density lipoprotein (LDL) and of apoA‐I in high density lipoprotein (HDL) were assessed in subjects with combined hyperlipidemia. Our primary hypothesis was that maximal dose rosuvastatin would decrease the apoB‐100 production rate (PR), as well as increase apoB‐100 fractional catabolic rate (FCR). Eight subjects received placebo, rosuvastatin 5 mg/day, and rosuvastatin 40 mg/day for 8 weeks each in sequential order. The kinetics of apoB‐100 in TRL and LDL and apoA‐I in HDL were determined at the end of each phase using stable isotope methodology, gas chromatography‐mass spectrometry, and multicompartmental modeling. Rosuvastatin at 5 and 40 mg/day decreased LDL cholesterol by 44 and 54 % (both P < 0.0001), triacylglycerol by 14 % (ns) and 35 % (P < 0.01), apoB by 30 and 36 % (both P < 0.0001), respectively, and had no significant effects on HDL cholesterol or apoA‐I levels. Significant decreases in plasma markers of cholesterol synthesis and increases in cholesterol absorption markers were observed. Rosuvastatin 5 and 40 mg/day increased TRL apoB‐100 FCR by 36 and 46 % (both ns) and LDL apoB‐100 by 63 and 102 % (both P < 0.05), respectively. HDL apoA‐I PR increased with low dose rosuvastatin (12 %, P < 0.05) but not with maximal dose rosuvastatin. Neither rosuvastatin dose altered apoB‐100 PR or HDL apoA‐I FCR. Our data indicate that maximal dose rosuvastatin treatment in subjects with combined hyperlipidemia resulted in significant increases in the catabolism of LDL apoB‐100, with no significant effects on apoB‐100 production or HDL apoA‐I kinetics.     

Bayesian Model Uncertainty In Smooth Transition Autoregressions

Abstract. In this paper, we propose a fully Bayesian approach to the special class of nonlinear time‐series models called the logistic smooth transition autoregressive (LSTAR) model. Initially, a Gibbs sampler is proposed for the LSTAR where the lag length, k, is kept fixed. Then, uncertainty about k is taken into account and a novel reversible jump Markov Chain Monte Carlo (RJMCMC) algorithm is proposed. We compared our RJMCMC algorithm with well‐known information criteria, such as the Akaikes? information criteria, the Bayesian information criteria (BIC) and the deviance information criteria. Our methodology is extensively studied against simulated and real‐time series.     

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.