Improving the accuracy of heat balance integral methods applied to thermal problems with time dependent boundary conditions

In this paper the two main drawbacks of the heat balance integral methods are examined. Firstly we investigate the choice of approximating function. For a standard polynomial form it is shown that combining the Heat Balance and Refined Integral methods to determine the power of the highest order term will either lead to the same, or more often, greatly improved accuracy on standard methods. Secondly we examine thermal problems with a time-dependent boundary condition. In doing so we develop a logarithmic approximating function. This new function allows us to model moving peaks in the temperature profile, a feature that previous heat balance methods cannot capture. If the boundary temperature varies so that at some time t & 0 it equals the far-field temperature, then standard methods predict that the temperature is everywhere at this constant value. The new method predicts the correct behaviour. It is also shown that this function provides even more accurate results, when coupled with the new CIM, than the polynomial profile. Analysis primarily focuses on a specified constant boundary temperature and is then extended to constant flux, Newton cooling and time dependent boundary conditions.

Evaluation of detection methods for Virus, Viroids and Phytoplasmas affecting pear and apple

The RT-PCR technique for the detection of apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), apple chlorotic leaf spot virus (ACLSV), apple mosaic virus (ApMV) and pear blister canker viroid (PBCV) was evaluated for health control of fruit plants from nurseries. The technique was evaluated in purified RNA and crude extracts and also in phloem collected in autumn and from young spring shoots. The results obtained for phytoplasma detection with ribosomal and non-ribosomal primers are also presented.

ALK rearrangement in a selected population of advanced non small cell lung cancer patients. FISH and inmunohistochemistry diagnostic methods, prevalence and clinical outcomes

Anaplastic lymphoma kinase (ALK) rearrangements represents a new driver oncogenic event in non-small cell lung cancer (NSCLC). ALK positive patients account for a 1-7% of NSCLC patients. The objective of this study is to know the prevalence and clinical characteristics of ALK positive patients in a cohort of NSCLC patients and to compare inmunohistochemistry with D5F3 monoclonal antibody with gold standard method fluorescence in situ hybridation

Scoring Methods for Ordinal Multidimensional Forced-Choice Items

In most psychological tests and questionnaires, a test score is obtained bytaking the sum of the item scores. In virtually all cases where the test orquestionnaire contains multidimensional forced-choice items, this traditionalscoring method is also applied. We argue that the summation of scores obtained with multidimensional forced-choice items produces uninterpretabletest scores. Therefore, we propose three alternative scoring methods: a weakand a strict rank preserving scoring method, which both allow an ordinalinterpretation of test scores; and a ratio preserving scoring method, whichallows a proportional interpretation of test scores. Each proposed scoringmethod yields an index for each respondent indicating the degree to whichthe response pattern is inconsistent. Analysis of real data showed that withrespect to rank preservation, the weak and strict rank preserving methodresulted in lower inconsistency indices than the traditional scoring method;with respect to ratio preservation, the ratio preserving scoring method resulted in lower inconsistency indices than the traditional scoring method

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Paper de l’ Haemophilus influenzae en les exacerbacions de la Malaltia Pulmonar Obstructiva Crònica (MPOC): tipificació molecular i factors de virulència

Objetivos: 1.-Identificar los factores clínicos y microbiológicos que ayuden a predecir la aparición de exacerbaciones en la EPOC. 2.-Diagnóstico y cuantificación de las especies bacterianas aisladas en esputo (fase de exacerbación y estable) .3.- Tipificación genotípica secuencial de las cepas de H. influenzae y P. aeruginosa. 4.- Impacto del tratamiento antibiótico en la aparición de resistencias en estos patógenos. 5.- Diseño: Estudio prospectivo (3 años). Ámbito del estudio: Hospital Universitario de tercer nivel. Pacientes con EPOC grave atendidos en la Consulta Monográfica de EPOC del Servicio de Neumología. Métodos microbiológicos: Cuantificación de la carga bacteriana en muestras respiratorias en fase estable y en exacerbación. Estudio de la sensibilidad “in vitro”. Tipificación molecular (PFGE y MLST) de H. influenzae y P. aeruginosa. Estudio de los genes de virulencia de H. influenzae mediante PCR. Resultados: Desde Febrero de 2010 a Julio de 2011 se han incluido 77 pacientes. Los microorganismos más frecuentemente aislados en fase de exacerbación fueron: P. aeruginosa (29.3%), H. influenzae (15.92%), M. catarrhalis (12.74%), S. pneumoniae (10.19%) y S. aureus (5.10%). En los 88 episodios por P. aeruginosa se detectaron 38 genotipos diferentes. En los 41 episodios por H. influenzae se detectaron 39 genotipos diferentes. El 10% de los episodios fueron polimicrobianos. Los episodios de EAEPOC y de fase estable tuvieron una distribución de microorganismos similar. Sin embargo, cuando se cuantificaron las cargas bacterianas fueron mayores en EAEPOC (intervalo 4x107 -2x108) que en fase estable (intervalo 2x105 -4x107). Conclusiones: El genotipo de las cepas de P. aeruginosa y H. influenzae aisladas en EAEPOC difieren de un paciente a otro, sin embargo la mayoría de los episodios de cada paciente están causados por un genotipo único.

Schwarz methods for a preconditioned WOPSIP method for elliptic problems

We construct and analyze non-overlapping Schwarz methods for a preconditioned weakly over-penalized symmetric interior penalty (WOPSIP) method for elliptic problems.

Two methods for voltage sag source location

This paper presents and compares two approaches to estimate the origin (upstream or downstream) of voltage sag registered in distribution substations. The first approach is based on the application of a single rule dealing with features extracted from the impedances during the fault whereas the second method exploit the variability of waveforms from an statistical point of view. Both approaches have been tested with voltage sags registered in distribution substations and advantages, drawbacks and comparative results are presented

Decision Support Methods for Global Optomization

Immobile location-allocation (LA) problems is a type of LA problem that consists in determining the service each facility should offer in order to optimize some criterion (like the global demand), given the positions of the facilities and the customers. Due to the complexity of the problem, i.e. it is a combinatorial problem (where is the number of possible services and the number of facilities) with a non-convex search space with several sub-optimums, traditional methods cannot be applied directly to optimize this problem. Thus we proposed the use of clustering analysis to convert the initial problem into several smaller sub-problems. By this way, we presented and analyzed the suitability of some clustering methods to partition the commented LA problem. Then we explored the use of some metaheuristic techniques such as genetic algorithms, simulated annealing or cuckoo search in order to solve the sub-problems after the clustering analysis

The Molecular Basis for Antimicrobial Activity of Pore-Forming Cyclic Peptides

The mechanism of action of antimicrobial peptides is, to our knowledge, still poorly understood. To probe the biophysical characteristics that confer activity, we present here a molecular-dynamics and biophysical study of a cyclic antimicrobial peptide and its inactive linear analog. In the simulations, the cyclic peptide caused large perturbations in the bilayer and cooperatively opened a disordered toroidal pore, 1–2 nm in diameter. Electrophysiology measurements confirm discrete poration events of comparable size. We also show that lysine residues aligning parallel to each other in the cyclic but not linear peptide are crucial for function. By employing dual-color fluorescence burst analysis, we show that both peptides are able to fuse/aggregate liposomes but only the cyclic peptide is able to porate them. The results provide detailed insight on the molecular basis of activity of cyclic antimicrobial peptides

Portafolio selection with skewness: a comparison of methods and a generalized two fund separation result

This contribution compares existing and newly developed techniques for geometrically representing mean-variances-kewness portfolio frontiers based on the rather widely adapted methodology of polynomial goal programming (PGP) on the one hand and the more recent approach based on the shortage function on the other hand. Moreover, we explain the working of these different methodologies in detail and provide graphical illustrations. Inspired by these illustrations, we prove a generalization of the well-known two fund separation theorem from traditionalmean-variance portfolio theory.

Antimicrobial peptide genes in Bacillus strains from plant environments

The presence of the antimicrobial peptide (AMP) biosynthetic genes srfAA (surfactin), bacA (bacylisin), fenD (fengycin), bmyB (bacyllomicin), spaS (subtilin), and ituC (iturin) was examined in 184 isolates of Bacillus spp. obtained from plant environments (aerial, rhizosphere, soil) in the Mediterranean land area of Spain. Most strains had between two and four AMP genes whereas strains with five genes were seldom detected and none of the strains had six genes. The most frequent AMP gene markers were srfAA, bacA, bmyB, and fenD, and the most frequent genotypes srfAA-bacA-bmyB and srfAAbacA-bmyB-fenD. The dominance of these particular genes in Bacillus strains associated with plants reinforces the competitive role of surfactin, bacyllomicin, fengycin, and bacilysin in the fitness of strains in natural environments. The use of these AMP gene markers may assist in the selection of putative biological control agents of plant pathogens