Power generation efficiency analysis of offshore wind farms connected to a SLPC (single large power converter) operated with variable frequencies considering wake effects

This paper deals with the power generation efficiency analysis of a proposed offshore wind farm topology, consisting of a SLPC (single large power converter) that simultaneously controls a group of generators. This common converter can operate at a VF (variable frequency) or at a CF (constant frequency). The results are compared with the conventional onshore wind farm scheme, where individual power converters are connected to each turbine, guaranteeing maximum power generation for the entire wind farm. A methodology to analyze different wind speed and direction scenarios, and to compute the optimal electrical frequency for each one, is presented and applied to different case studies depending on the wind farm size. In order to obtain more realistic values of wind speeds, the wake effect amongst wind turbines is considered. A wake model considering single, partial and multiple wakes inside a wind farm and taking into account different wind directions, is presented. Both wind farm topologies are analyzed by means of simulations, taking into account both wind speed variability in wind farms and the number of wind turbines. The possible resulting benefits of simplifying the MPCs (multiple power converters) of each turbine, namely saving costs, reducing losses and maintenance and increasing the reliability of the system, are analyzed, focusing on the total power extraction. The SLPC-VF scheme is also compared with a CF scheme SLPC-CF, and it is shown that a significant power increase of more than 33% can be obtained with SLPC-VF.     

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.     

Implementing the Omega failure detector in the crash-recovery failure model

Unreliable failure detectors are mechanisms providing information about process failures, that allow to solve several problems in asynchronous systems, e.g., Consensus. A particular failure detector, Omega, provides an eventual leader election functionality. This paper addresses the implementation of Omega in the crash-recovery failure model. We first propose an algorithm assuming that processes are reachable from the correct process that crashes and recovers a minimum number of times. Then, we propose two algorithms which assume only that processes are reachable from some correct process. Besides this, one of the algorithms requires the membership to be known a priori, while the other two do not.     

Semi-discretization for stability analysis of in-feed cylindrical grinding with continuous workpiece speed variation

This paper presents the advances of semi-discretization approach for the dynamic stability analysis of in-feed cylindrical grinding process. The corresponding mathematical model is an autonomous delay-differential equation and the application of continuous workpiece speed variation (CWSV) in the process leads to a time-varying delay. Discretization techniques are a good way of dealing with differential equations for which the solution cannot be given in closed forms. Therefore, the semi-discretization method is proposed to analyze the equation. Stability maps are devised to study the influence of the CWSV application. Contrary to milling and turning processes, stability in grinding is very much influenced by the residual flexibility due to the deformation of the grinding wheel-workpiece system, so this term has been included in the approach. The validation has been carried out experimentally and good correlation between test and simulation results has been achieved.     

Siliceous spicules and skeleton frameworks in sponges: origin, diversity, ultrastructural patterns, and biological functions

Silica deposition is a fundamental process in sponges. Most sponges in the Classes Demospongiae and Hexactinellida secrete siliceous elements, which can subsequently fuse, interlock with each other, or form three-dimensional structures connected by spongin. The resulting skeletal frameworks allow sponges to grow upwards and facilitate water exchange with minimal metabolic cost. Several studies on sponge skeletogenesis have been published. We are beginning to understand the mechanisms of spicule secretion and the role of spicules and skeletal frameworks in the biology, ecology, and evolution of sponges. Molecular techniques and ecological experiments have demonstrated the genetic control of the process and the contribution of environmental factors to the expression of a sponge spicule, respectively. However, other classic topics such as the role of membranes in silicon transport or whether spicules are formed in situ or secreted anywhere in the sponge mesohyl and then transported to the skeletal framework require further investigation. We review the process of silica deposition in sponges at the molecular and cellular levels, as well as the biological and ecological functions of spicules and skeletons. The genetic control of spicule shapes makes them useful in the reconstruction of sponge phylogeny, although recent experiments have demonstrated the influence of environmental factors in modulating spicule size, shape, and the presence or absence of one or more spicule types. The implications of such variations in sponge taxonomy may be important. Besides supporting sponge cells, spicules can help larvae stay buoyant while in the plankton or reach the bottom at settlement, enhance reproduction success, or catch prey. Conversely, the role of spicules and skeletons in deterring predation has not been demonstrated. Knowledge of several aspects is still based on a single or a few species and extrapolations should be made only with caution. With the advent of new molecular techniques, new lines of research are presently open and active in this field.     

Chemical Defenses of the Sacoglossan Mollusk Elysia rufescens and Its Host Alga Bryopsis sp.

Sacoglossans are a group of opisthobranch mollusks that have been the source of numerous secondary metabolites; however, there are few examples where a defensive ecological role for these compounds has been demonstrated experimentally. We investigated the deterrent properties of the sacoglossan Elysia rufescens and its food alga Bryopsis sp. against natural fish predators. Bryopsis sp. produces kahalalide F, a major depsipeptide that is accumulated by the sacoglossan and that shows in vitro cytotoxicity against several cancer cell lines. Our data show that both Bryopsis sp. and Elysia rufescens are chemically protected against fish predators, as indicated by the deterrent properties of their extracts at naturally occurring concentrations. Following bioassay-guided fractionation, we observed that the antipredatory compounds of Bryopsis sp. were present in the butanol and chloroform fractions, both containing the depsipeptide kahalalide F. Antipredatory compounds of Elysia rufescens were exclusively present in the dichloromethane fraction. Further bioassay-guided fractionation led to the isolation of kahalalide F as the only compound responsible for the deterrent properties of the sacoglossan. Our data show that kahalalide F protects both Bryopsis sp. and Elysia rufescens from fish predation. This is the first report of a diet-derived depsipeptide used as a chemical defense in a sacoglossan.     

EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling

Classification with imbalanced data-sets has become one of the most challenging problems in Data Mining. Being one class much more represented than the other produces undesirable effects in both the learning and classification processes, mainly regarding the minority class. Such a problem needs accurate tools to be undertaken; lately, ensembles of classifiers have emerged as a possible solution. Among ensemble proposals, the combination of Bagging and Boosting with preprocessing techniques has proved its ability to enhance the classification of the minority class.In this paper, we develop a new ensemble construction algorithm (EUSBoost) based on RUSBoost, one of the simplest and most accurate ensemble, which combines random undersampling with Boosting algorithm. Our methodology aims to improve the existing proposals enhancing the performance of the base classifiers by the usage of the evolutionary undersampling approach. Besides, we promote diversity favoring the usage of different subsets of majority class instances to train each base classifier. Centered on two-class highly imbalanced problems, we will prove, supported by the proper statistical analysis, that EUSBoost is able to outperform the state-of-the-art methods based on ensembles. We will also analyze its advantages using kappa-error diagrams, which we adapt to the imbalanced scenario.     

Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers

The One-vs-One strategy is one of the most commonly used decomposition technique to overcome multi-class classification problems; this way, multi-class problems are divided into easier-to-solve binary classification problems considering pairs of classes from the original problem, which are then learned by independent base classifiers.The way of performing the division produces the so-called non-competence. This problem occurs whenever an instance is classified, since it is submitted to all the base classifiers although the outputs of some of them are not meaningful (they were not trained using the instances from the class of the instance to be classified). This issue may lead to erroneous classifications, because in spite of their incompetence, all classifiers' decisions are usually considered in the aggregation phase.In this paper, we propose a dynamic classifier selection strategy for One-vs-One scheme that tries to avoid the non-competent classifiers when their output is probably not of interest. We consider the neighborhood of each instance to decide whether a classifier may be competent or not. In order to verify the validity of the proposed method, we will carry out a thorough experimental study considering different base classifiers and comparing our proposal with the best performer state-of-the-art aggregation within each base classifier from the five Machine Learning paradigms selected. The findings drawn from the empirical analysis are supported by the appropriate statistical analysis.     

A biokinematic approach for the computational simulation of proteins molecular mechanism

Proteins play an essential role in the biological processes that take place in the human body. For this reason, it is very important to understand the molecular mechanisms involved. Recently a new approach, based on the parallelism between proteins and spatial mechanisms, has allowed methods to be developed to obtain atomic trajectories for protein motion using concepts from the kinematics of mechanisms. This paper presents a method for simulating protein motion, based on the evaluation of the potential energy during the motion, thereby avoiding the need to perform a minimization procedure. This approach constitutes a good compromise between computational effort and accuracy of the results. In addition, in order to efficiently simulate the motion, a new algorithm for normalization of the structure of the protein is presented. Finally, we illustrate the results of applying this method to an inorganic pyrophosphatase (family II) from Streptococcus gordonii evaluating geometric accuracy, energetic evolution and biological indicators.