Surface geochemistry of soils associated to the Tinto River (Huelva, Spain)

The Tinto River (Iberian Pyritic Belt) is a unique ecosystem characterized by extreme acidity and abnormally high concentrations of heavy metals in water, sediments and alluvium, with high microbial diversity and low plant diversity. The low pH value, a direct consequence of the high amount of Fe and S derived from the bedrock, promotes the dispersion of heavy metals. Less mobile elements (Fe, As, Pb, Ag and Ti) show the highest concentrations in the mid stretches of the river while easily mobile metals (Cu, Zn and Cd) accumulate in the estuarine sediments. Tinto River soils show a scarcity of nutrients (Ca, K, P, Mg and Na) due to the lack of lithologic sources and to loss by acid washing. Sea water and phospho-gypsum deposits near Huelva contribute to increase the Na, Mg and P concentrations in the estuarine soils. As a whole these features represent an extreme habitat to which plants must adapt.     

Assessment of olive cake as soil amendment for the controlled release of triazine herbicides

Organic matter-rich agricultural by-products are being produced in huge quantities and can be applied to soil as a disposal strategy. The application of two different rates (2 and 8% w/w) of olive cake to a Mediterranean calcareous soil resulted in an increased sorption of four triazine herbicides, which was higher for the more hydrophobic compounds (terbuthylazine and prometryn) and lower for the more polar ones (simazine and cyanazine). However, when the sorption coefficients were normalised to the total soil organic carbon (K(oc)), the results did not significantly differ between simazine and cyanazine which is an indication that the olive cake did not exert different sorption capacity for both compounds. On the contrary, K(oc) values for terbuthylazine and prometryn increased in the amended soils. Our results from experiments using mixtures of several pesticides suggest that competition for sorption sites resulted in a decrease of herbicide sorption. Desorption was hysteretical both for the amended and unamended soils, but the addition of olive cake at the highest dose diminished desorption of most of the herbicides. In conclusion, the addition of olive cake behaves as a promising method for reducing the risk of groundwater pollution by pesticides.     

High-Impact PLA in Compatibilized PLA/PCL Blends: Optimization of Blend Composition and Type and Content of Compatibilizer

In this work, the effectiveness of seven commercial compatibilizers is tested in polylactide (PLA)/poly(ε-caprolactone) (PCL) blends with different compositions to obtain a high-impact PLA. None of the compatibilizers is effective for 90/10 and 80/20 PLA/PCL compositions, as no improvement of the impact strength is observed. For the 70/30 composition, compatibilizers having glycidyl methacrylate (GMA) and acrylate groups in their structure are proved the most effective, as the morphological change towards co-continuity induced by them leads to significant impact strength improvements (of ≈345% and 90% with respect to the neat PLA and the noncompatibilized PLA/PCL 70/30 blend, respectively). The 70/30 PLA/PCL composition, as it shows the best balance of properties, and the best compatibilizer (ElvaloyPTW) are chosen to carry out the optimization of the compatibilizer content. It is found that adding 6 phr to the blend results in highly toughened and ductile blends while maintaining a high modulus and yield strength values. Larger compatibilizer contents lead to even higher impact strength values, but the low-strain mechanical properties are notably reduced. Thus, in this work, a simple and easily scalable method to produce high-impact PLA is shown, as it implies the compounding of three commercially available components without involving any toxic solvents.     

New methodology of solar radiation evaluation using free access databases in specific locations

In this paper, solar radiation obtained from different frequently used databases is compared in some different locations. In the analyzed databases, the data come from ground measurement networks, or from different models and with different resolutions. The proposed methodology assumes the hypothesis that the uncertainty of the databases is approximately the same as the meteorological uncertainty of the location. Therefore the heterogeneity of the observations is due to different observations. A weighted average is proposed taking into account different time and spatial characteristics of each database, and the estimation of standard deviation of weighted observations that derives the meteorological variability expected.     

Isothermal crystallization study on a biodegradable segmented copolymer constituted by glycolide and trimethylene carbonate units

The isothermal crystallization behavior of a segmented copolymer constituted by hard blocks of polyglycolide and soft segments derived from the copolymerization of glycolide and trimethylene carbonate was investigated. This polymer has applied relevance because it is one of the most widely used for bioabsorbable surgical sutures. Calorimetric, optical microscopy, and infrared techniques were combined to understand the thermal properties and the different factors that influence the crystallization process. Basically, only the hard blocks crystallized, although certain processing conditions allowed performing an additional crystallization associated with small lamellar domains of the soft segment. Crystallization from both the melt and the glass state rendered positive spherulites with a fibrillar texture. The observed unusual sign of birefringence was a consequence of the close packing structure of polyglycolide, which was also corroborated by electron diffraction patterns. Crystallization was characterized by an athermal nucleation, which allowed accurate estimation of the secondary nucleation parameter by using the calorimetric data only. Significant differences in the Avrami exponent (from 2.32 to 1.45) were found between the cold and hot isothermal crystallizations. The stronger geometric constraints observed in the crystallization from the glass state were also corroborated by FTIR analyses. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Diosgenin quantification,characterisation and chemical composition in a tuber collection of Dioscorea spp. in the state of Jalisco,Mexico

Dioscorea spp. tubers are known commonly as camote de cerro to the state of Jalisco, México. Besides its use as food, it contains diosgenin, a raw material used widely for synthesising steroid hormones. The purpose of the present research was to determine diosgenin contents by gas chromatography‐mass spectrometry (GC‐MS), as well as physical and chemical characteristics of sixty Dioscorea spp. accessions cultivated in mesh shade coming from eleven localities in the state of Jalisco. Extraction protocol for diosgenin was maceration combined with ethanol 80%. Significant statistical differences for diosgenin content were found between accessions, finding levels between 0.02 and 0.16 mg kg^?1 in dry basis. Length, weight tuber, proportion pulp/skin, percentage of pulp and percentage of skin showed significant differences. Chemical composition based in fresh weight presented in moisture percentage a range of 71.93–83.26%, crude protein 1.42–1.74%, ashes 0.80–1.16%, lipid 0.13–0.17%, crude fibre 3.80–4.02% and total carbohydrates 13.97–25.44%. Results show that tubers from Jalisco can be an important source of nutrients for consumers.     

Fisher’s decision tree

Univariate decision trees are classifiers currently used in many data mining applications. This classifier discovers partitions in the input space via hyperplanes that are orthogonal to the axes of attributes, producing a model that can be understood by human experts. One disadvantage of univariate decision trees is that they produce complex and inaccurate models when decision boundaries are not orthogonal to axes. In this paper we introduce the Fisher’s Tree, it is a classifier that takes advantage of dimensionality reduction of Fisher’s linear discriminant and uses the decomposition strategy of decision trees, to come up with an oblique decision tree. Our proposal generates an artificial attribute that is used to split the data in a recursive way.The Fisher’s decision tree induces oblique trees whose accuracy, size, number of leaves and training time are competitive with respect to other decision trees reported in the literature. We use more than ten public available data sets to demonstrate the effectiveness of our method.     

The influence of depressive symptoms on experimental smoking and intention to smoke in a diverse youth sample.

Numerous studies have shown associations between smoking and depression, but the generalizability of the relationship across ethnic groups remains unknown. The present study assessed the association between depression and smoking intention and experimentation among adolescents from four ethnic groups in the Los Angeles area-Chinese/Chinese American, Latino/Hispanic, Persian/Iranian, and White. Over 800 7th graders in the Los Angeles area completed measures of depressive symptoms, experimentation with smoking, intention to smoke, and sociodemographic covariates. Chinese/Chinese American students had the lowest levels of depressive symptoms, whereas Latinos/Hispanics had the highest levels. Latinos/Hispanics also were the most likely to intend to smoke in the next year and were the most likely to have started experimenting with cigarette smoking. Depressive symptoms were significantly associated with intention to smoke even after controlling for language use acculturation, socioeconomic status, gender, and ethnicity. The association between depressive symptoms and intention to smoke did not vary significantly across ethnic groups. These results indicate that the association between depressive symptoms and adolescent smoking generalizes across diverse ethnic groups.