Behavior of propagating and evanescent components in azimuthally polarized non-paraxial fields

The contribution of the propagating and the evanescent waves associated with freely propagating non-paraxial light fields whose transverse component is azimuthally polarized at some plane is investigated. Analytic expressions are derived for describing both the spatial shape and the relative weight of the propagating and the evanescent components integrated over the transverse plane. The analysis is carried out within the framework of the plane-wave angular spectrum approach. These results are used to illustrate the behavior of a kind of donut-like beams with transverse azimuthal polarization at some plane

A quality management based on the Quality Model life cycle

Managing quality is a hard and expensive task that involves the execution and control of processes and techniques. For a good quality management, it is important to know the current state and the objective to be achieved. It is essential to take into account with a Quality Model that specifies the purposes of managing quality. QuEF (Quality Evaluation Framework) is a framework to manage quality in MDWE (Model-driven Web Engineering). This paper suggests managing quality but pointing out the Quality Model life cycle. The purpose is to converge toward a quality continuous improvement by means of reducing effort and time.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578

A methodological proposal and tool support for the HL7 standards compliance in the development of health information systems

Health information systems are increasingly complex, and their development is presented as a challenge for software development companies offering quality, maintainable and interoperable products. HL7 (Health level 7) International, an international non-profit organization, defines and maintains standards related to health information systems. However, the modelling languages proposed by HL7 are far removed from standard languages and widely known by software engineers. In these lines, NDT is a software development methodology that has a support tool called NDT-Suite and is based, on the one hand, on the paradigm of model-driven engineering and, on the other hand, in UML that is a widely recognized standard language. This paper proposes an extension of the NDT methodology called MoDHE (Model Driven Health Engineering) to offer software engineers a methodology capable of modelling health information systems conforming to HL7 using UML domain models

Usando la Web 2.0 en la distribución de puestos de prácticas en Enfermería: proyecto piloto

Las prácticas clínicas de Enfermería, son un elemento fundamental para el proceso de enseñanza – aprendizaje de los estudiantes de Grado en Enfermería. En estos entornos, los estudiantes toman contacto con su futura profesión aplicando los conocimientos teóricos y desarrollando habilidades para la prestación de cuidados a los pacientes. En este trabajo de investigación acción, se describen y aportan resultados de las dos etapas determinadas en este estudio piloto. En primer lugar, se estudia y analiza la opinión de una muestra accidental de estudiantes del grado en Enfermería sobre la organización y distribución de puestos de prácticas en este momento, empleando como instrumento un cuestionario de 15 ítems. Posteriormente y tras el análisis de los datos obtenidos en la fase previa, se decide diseñar y aplicar un instrumento basado en la Web 2.0 y se formula un protocolo en el que la elección de las unidades de prácticas las realiza la estudiante o el estudiante, siguiendo los pasos establecidos

Designing selection indices for the florida dairy goat breeding program

The aim of this study was to compare selection indices for important traits in intensive Spanish goat breeds in four economic scenarios, using the Florida as most representative breed of this production system in Spain. For this analysis, we considered the following traits: milk yield (MY), fat plus protein yields (FPY), casein yield (CY), somatic cell score (SCS), reproductive efficiency (RE), litter size (LS), mammary system (MS), final score (FS), body capacity index (BCI), and length of productive life (LPL). We estimated the genetic parameters and EBVs of most of these traits with REML methodology, while LPL was modeled through survival analysis. Four scenarios were proposed, depending on the overall objective for improvement: (1) milk production, (2) milk production and cheese extract, (3) cheese extract, and (4) milk production, cheese extract and sale of animals. Then, within each scenario, three different types of indices were designed using the different primary and secondary objectives/criteria considered suitable to improve the overall objective. The results indicated that selecting only for primary traits yielded the highest genetic response for all the scenarios. Including secondary traits led to positive correlated responses in those traits, but a decrease in the responses in the primary criteria

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

Source apportionment studies use prior exploratory methods that are not purpose-oriented and receptor modelling is based on chemical speciation, requiring costly, time-consuming analyses. Hidden Markov Models (HMMs) are proposed as a routine, exploratory tool to estimate PM10 source contributions. These models were used on annual time series (TS) data from 33 background sites in Spain and Portugal. HMMs enable the creation of groups of PM10 TS observations with similar concentration values, defining the pollutant's regimes of concentration. The results include estimations of source contributions from these regimes, the probability of change among them and their contribution to annual average PM10 concentrations. The annual average Saharan PM10 contribution in the Canary Islands was estimated and compared to other studies. A new procedure for quantifying the wind-blown desert contributions to daily average PM10 concentrations from monitoring sites is proposed. This new procedure seems to correct the net load estimation from deserts achieved with the most frequently used method

Modelling background air pollution exposure in urban environments: Implications for epidemiological research

Background pollution represents the lowest levels of ambient air pollution to which the population is chronically exposed, but few studies have focused on thoroughly characterizing this regime. This study uses clustering statistical techniques as a modelling approach to characterize this pollution regime while deriving reliable information to be used as estimates of exposure in epidemiological studies. The background levels of four key pollutants in five urban areas of Andalusia (Spain) were characterized over an 11-year period (2005e2015) using four widely-known clustering methods. For each pollutant data set, the first (lowest) cluster representative of the background regime was studied using finite mixture models, agglomerative hierarchical clustering, hidden Markov models (hmm) and k-means. Clustering method hmm outperforms the rest of the techniques used, providing important estimates of exposures related to background pollution as its mean, acuteness and time incidence values in the ambient air for all the air pollutants and sites studied