Scientific and technological performance evaluation of the Spanish Council for Scientific Research (CSIC) in the field of Biotechnology

An evaluation of the Spanish CSIC performance in Biotechnology, as compared with those of the French CNRS and the Italian CNR, has been carried out to determine the balance between the generation of scientific knowledge and the transfer of technology. This study shows a high scientific productivity mostly in journals with moderate impact factor, a low generation of patents and an insufficient transfer of knowledge to the Spanish companies. Other indicators confirm the existence of competitive human resources in biotechnological research producing scientific knowledge of interest for the development of patents and that cooperates successfully at European level.     

Spectral domain analysis of conductor losses in a multiconductorsystem via the incremental inductance rule

Spectral domain analysis is adapted to analyse the conductor losses of a multiconductor system embedded in a multilayered medium using a quasi-TEM approach and assuming a strong skin effect. After adapting the incremental rule to a multiconductor system, the conductor losses are computed in terms of the derivative of the inductance matrix     

Electrochemical,FTIR and morphological study of polypyrrole—Polystyrenesulphonate conducting films

The electrochemical behaviour, FTIR spectrum and the morphology of polypyrrole-polystyrenesulphonate (PPy-PSS) films obtained potentiostatically at 0.6 V in a 0.05m Py + 1.7 × 10^?2m NaPSS medium have been analysed. Different electrochemical parameters have been modified in order to establish the first polaron formation, the reversibility of the redox process and the doping mechanism. The FTIR spectrum confirms the existence of C?O groups in the film structure and two possible explanations are suggested. SEM reveals a higher homogeneity in these films than in PPy films doped with smaller counterions.     

Enantiospecific synthesis fromd-fructose of (2S,5R)- and (2R,5R)-2-methyl-1,6-dioxaspiro[4.5]decane [the odor bouquet minor components ofParavespula vulgaris (L.)]

The synthesis of (2S,5R)-(1) and (2R,5R)-2-methyl-1,6-dioxaspiro [4.5]decane (2) from (2RS,5R,8R,9R,10S)-8,9,10-trihydroxy-2-methyl-1, 6-dioxaspiro[4.5]decane (8), obtained in five steps fromd-fructose using Wittig's methodology, reduction, and spiroketalation, has been accomplished by a Corey dideoxygenation at C-8,9, followed by a Barton deoxygenation at C-10, of the appropriately protected derivatives.Enantiospecific synthesis of spirocetals. Part V. For Part IV, see Izquierdo et al. (1992).     

Enantiospecific synthesis of (R)-1,7-dioxaspiro [5.5]undecane [major component of olive fruit fly (Dacus Oleae) sex pheromone] from d-Fructose

The synthesis of the title compound13 has been carried out through the preparation of its precursor, (3R,4R,5S,6R)-3,4,5-trihydroxy-1,7-dioxaspiro[5.5]undecane (6), obtained fromd-fructose using Wittig's methodology, reduction, and spiroketalation. Compound6 was transformed into13 by a Barton deoxygenation at C-5 followed by a Corey dideoxygenation at C-3,4 of the appropriately protected derivatives.Enantiospecific synthesis of spiroacetals. Part II. For Part I, see Izquierdo and Plaza (1990).     

Consequences and conjectures in preordered sets

In a preordered set, or preset, consequence operators in the sense of Tarski, defined on families of subsets, are introduced. From them, the corresponding sets of conjectures, hypotheses, speculations and refutations are considered, studying the relationships between these sets and those previously defined on ortholattices. All the concepts introduced are illustrated with three particular consequence operators, whose behavior is studied in detail. The results obtained are applied to the case of fuzzy sets endowed with the usual pointwise ordering.     

On the use of small training sets for neural network-based characterization of mixed pixels in remotely sensed hyperspectral images

In this work, neural network-based models involved in hyperspectral image spectra separation are considered. Focus is on how to select the most highly informative samples for effectively training the neural architecture. This issue is addressed here by several new algorithms for intelligent selection of training samples: (1) a border-training algorithm (BTA) which selects training samples located in the vicinity of the hyperplanes that can optimally separate the classes; (2) a mixed-signature algorithm (MSA) which selects the most spectrally mixed pixels in the hyperspectral data as training samples; and (3) a morphological-erosion algorithm (MEA) which incorporates spatial information (via mathematical morphology concepts) to select spectrally mixed training samples located in spatially homogeneous regions. These algorithms, along with other standard techniques based on orthogonal projections and a simple Maximin-distance algorithm, are used to train a multi-layer perceptron (MLP), selected in this work as a representative neural architecture for spectral mixture analysis. Experimental results are provided using both a database of nonlinear mixed spectra with absolute ground truth and a set of real hyperspectral images, collected at different altitudes by the digital airborne imaging spectrometer (DAIS 7915) and reflective optics system imaging spectrometer (ROSIS) operating simultaneously at multiple spatial resolutions.     

A model for “crisp reasoning” with fuzzy sets

In the setting of a general type of fuzzy algebras, this paper deals with a new theoretic view on the commonsense reasoning, consisting of a kind of Popper's search for conjectures and refutations. It is supposed that the reasoning is done in natural language, but only with nonambiguous precise and imprecise terms, respectively, represented by crisp and fuzzy sets. © 2012 Wiley Periodicals, Inc.     

A glass/silicon technology for low-power robust gas sensors

Semiconductor gas sensors are devices based on metallic oxides that operate at high temperatures for achieving good sensitivities to the gases of interest. Silicon micromachined structures are often used as platforms for obtaining both high temperatures and low-power consumption at the same time. In this paper, a microstructure based on the combination of micromachined silicon substrates and glass wafers is presented. The device incorporates an array of four different thin-film gas sensors that, depending on the design, can operate at the same or at different temperatures. The designs have been optimized by the finite element method (FEM) and the geometrical parameters of the structure have been selected in order to reduce the power consumption. The full process fabrication is presented. It is based on the combination of bulk micromachining, glass structuring, anodic bonding, and sensitive material deposition. Electrical, thermal, and mechanical tests have been done to demonstrate that the devices show high robustness and can reach high temperatures with low-power consumption.