An engineering approach for the estimation of slewing bearing stiffness in wind turbine generators

The stiffness of yaw and pitch slewing bearings has a critical influence on the structural behaviour of wind turbine generators. Thus, it is commonly required by designers for their simulations to estimate deformations and select the most suitable bearing for their working conditions in preliminary design stages. In this work, a design of experiments was carried out via finite element analysis to obtain the stiffness curves of all of the standard four‐point contact slewing bearings from the catalogues of manufacturers under radial, axial, and tilting loads. From these results, a set of simple formulas to calculate the ring deformations were adjusted. Combining them with contact deformation results obtained in previous work by the authors, a complete and efficient tool for slewing bearing stiffness estimation has been developed.     

A new marker design for a robust marker tracking system against occlusions

Marker systems are a widely used optical tracking method that does not support occlusions. Thus, this paper proposes a new marker design to overcome the problem of marker occlusions. It is highly adaptable, because it can be used by any marker tracking system that uses its central area to codify the digital identification. Our proposal takes advantage of an untapped frame to place some textures that will be tracked during marker occlusion. In addition, these textures are customizable, which lets users make their own designs. Two tracking methods are combined to offer a robust tracking, updating the six degrees of freedom of the camera in real time. The first one is a fast technique based on temporal coherence, whereas the second one is a robust technique based on appearance, which is used as a recovery mode. Copyright © 2012 John Wiley & Sons, Ltd.     

Isolation of a gene encoding a G protein alpha subunit involved in the regulation of cAMP levels in the yeast Kluyveromyces lactis

Using chromosomal DNA from Kluyveromyces lactis as template and oligodeoxynucleotides designed from conserved regions of various G protein alpha subunits we were able to amplify by the polymerase chain reaction two products of approximately 0.5 kb (P-1) and 0.8 kb (P-2). Sequencing showed that these two fragments share high homology with genes coding for the G alpha subunits from different sources. Using the P-1 fragment as a probe we screened a genomic library from K. lactis and we cloned a gene (KlGPA2) whose deduced amino acid sequence showed, depending on the exact alignment, 62% similarity and 38% identity with Gpa1p and 76% similarity and 63% identity with Gpa2p, the G protein alpha subunits from Saccharomyces cerevisiae. KlGPA2 is a single-copy gene and its disruption rendered viable cells with significantly reduced cAMP level, indicating that this G alpha subunit may be involved in regulating the adenylyl cyclase activity, rather than participating in the mating pheromone response pathway. KlGpa2p shares some structural similarities with members of the mammalian G alpha s family (stimulatory of adenylyl cyclase) including the absence in its N-terminus of a myristoyl-modification sequence.     

Evolution of Gaussian Process kernels for machine translation post-editing effort estimation

In many Natural Language Processing problems the combination of machine learning and optimization techniques is essential. One of these problems is the estimation of the human effort needed to improve a text that has been translated using a machine translation method. Recent advances in this area have shown that Gaussian Processes can be effective in post-editing effort prediction. However, Gaussian Processes require a kernel function to be defined, the choice of which highly influences the quality of the prediction. On the other hand, the extraction of features from the text can be very labor-intensive, although recent advances in sentence embedding have shown that this process can be automated. In this paper, we use a Genetic Programming algorithm to evolve kernels for Gaussian Processes to predict post-editing effort based on sentence embeddings. We show that the combination of evolutionary optimization and Gaussian Processes removes the need for a-priori specification of the kernel choice, and, by using a multi-objective variant of the Genetic Programming approach, kernels that are suitable for predicting several metrics can be learned. We also investigate the effect that the choice of the sentence embedding method has on the kernel learning process.

     

Towards a standard methodology to evaluate internal cluster validity indices

The evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.     

Molecular dynamics study of the influence of functionalization on the elastic properties of single and multiwall carbon nanotubes

The effect of carboxylation on axial Young’s modulus of carbon nanotubes is investigated using a molecular dynamics (MD) approach. COMPASS force field is used to model the interatomic interactions in single wall (SWCNT) and multiwall carbon (MWCNT) with different amounts of –COOH groups attached to their surfaces. The results of the MD simulations show how an increase of the number of carboxylic groups on the CNT surface leads to a decrease on the Young moduli of the CNTs. The decrease of MWCNT Young’s modulus is found to be lower than in the case of SWCNT.     

An autonomous unmanned underwater control test vehicle: platform description and experiments

This paper presents an autonomous unmanned underwater vehicle (AUUV) that can be used as a support tool for research tasks in underwater exploration, and as a platform to test different control, communication, or vision algorithms. The vehicle operates without an external power cable and with an original modular program where a web page is enabled as a graphical user interface for wireless communication with the vehicle when it is not submerged. The modular design of the program, based on open-source libraries, allows updating or modifying the configuration of each of its main modules: control, inertial unit, and vision. Experimental results are shown to validate the performance of the proposed vehicle, implementing a non-linear control that includes a PID for the trajectory tracking of its pose (position and orientation).

     

Health-promoting substances and antioxidant properties of Opuntia sp. fruits. Changes in bioactive-compound contents during ripening process

Several Opuntia cactus fruits of different pulp colours from Argentina were studied at their physiological mature states. Analyses of these fruits showed very variable total soluble solid values and ascorbic acid contents ranging from 0.26 to 0.48 mg/g. Total phenolic compounds contents were between 0.54 and 1.2 mg of gallic acid/g, respectively. Purple Opuntia spp., dark purple Opuntia ficus-indica and orange Opuntia megacantha presented the highest levels amongst the samples studied. The antioxidant activity of Opuntia fruits was very variable and presented vitamin C equivalent values (VCEAC) between 0.25 and 0.57 mg/g. Purple Opuntia ficus-indica showed the highest antiradical ability. Besides, the antioxidant activity, ascorbic acid and phenolic compound contents in yellow and orange Opuntia megacantha fruits were monitored in different stages during their ripening process. Concentration changes of betalains and chlorophylls comparing skin and pulp and other physicochemical parameters were also measured in these fruits.