Effects of Spring Temperatures on the Strength of Selection on Timing of Reproduction in a Long-Distance Migratory Bird

Climate change has differentially affected the timing of seasonal events for interacting trophic levels, and this has often led to increased selection on seasonal timing. Yet, the environmental variables driving this selection have rarely been identified, limiting our ability to predict future ecological impacts of climate change. Using a dataset spanning 31 years from a natural population of pied flycatchers (Ficedula hypoleuca), we show that directional selection on timing of reproduction intensified in the first two decades (1980-2000) but weakened during the last decade (2001-2010). Against expectation, this pattern could not be explained by the temporal variation in the phenological mismatch with food abundance. We therefore explored an alternative hypothesis that selection on timing was affected by conditions individuals experience when arriving in spring at the breeding grounds: arriving early in cold conditions may reduce survival. First, we show that in female recruits, spring arrival date in the first breeding year correlates positively with hatch date; hence, early-hatched individuals experience colder conditions at arrival than late-hatched individuals. Second, we show that when temperatures at arrival in the recruitment year were high, early-hatched young had a higher recruitment probability than when temperatures were low. We interpret this as a potential cost of arriving early in colder years, and climate warming may have reduced this cost. We thus show that higher temperatures in the arrival year of recruits were associated with stronger selection for early reproduction in the years these birds were born. As arrival temperatures in the beginning of the study increased, but recently declined again, directional selection on timing of reproduction showed a nonlinear change. We demonstrate that environmental conditions with a lag of up to two years can alter selection on phenological traits in natural populations, something that has important implications for our understanding of how climate can alter patterns of selection in natural populations.

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Assessment of phytostabilization of Pb/Zn mine soils with organic amendments and a native metallicolous ecotype of Festuca Rubra l.: implications for amendment selection and recovery of soil health

La contaminación del suelo es una de las principales amenazas para los ecosistemas y la salud humana. Actualmente, desde un punto de vista tanto económico como ambiental, la fitoestabilización es la mejor tecnología para remediar suelos contaminados con elevadas concentraciones de metales como son los suelos mineros. La fitoestabilización asistida consiste en el empleo de plantas y enmiendas orgánicas y/o inorgánicas con el fin de reducir la movilidad y la biodisponibilidad de los contaminantes y recuperar la salud de suelo. En este trabajo se han realizado ensayos en microcosmos y en campo centrándonos en la salud del suelo minero contaminado con Pb y Zn durante un proceso de fitoestabilización empleando enmiendas orgánicas (purines vacunos, gallinaza, estiércol de oveja y lodos de papelera mezclados con gallinaza) y/o la especie metalífera Festuca rubra con el objetivo de (i) estudiar las interacciones suelo-enmienda responsables de los cambios inducidos por el proceso de quimioestabilización en las propiedades físicoquímicas y biológicas del suelo, (ii) evaluar la efectividad del proceso de fitoestabilización sobre suelos vegetados y de la revegetación sobre suelos desnudos (iii) valorar la idoneidad de distintos indicadores químicos y biológicos (parámetros microbianos y de la vegetación) para monitorizar la efectividad de la fitoestabilización asistida en términos de reducción de la biodisponibilidad de metales en el suelo, mejora de la vegetación y de la recuperación de la salud del suelo. La aplicación de enmiendas al suelo minero supone una entrada de materia orgánica y nutrientes que conduce a una disminución de la biodisponibilidad de metales, facilitando la colonización de las plantas y el crecimiento de la vegetación nativa, además de estimular la actividad microbiana del suelo. El pH del suelo es un factor crítico que condiciona la movilidad de los metales y la toxicidad del suelo. Las poblaciones microbianas de las enmiendas no modificaron la diversidad funcional de las comunidades microbianas nativas de la mina. Los purines vacunos y los lodos de papelera mezclados con gallinaza son los tratamientos más efectivos en el proceso de fitoestabilización asistida bajo condiciones de campo. La gallinaza fue el tratamiento que más estimuló el crecimiento de la vegetación nativa y la colonización en los suelos desnudos. El bioensayo de elongación radical de lechuga es un test sensible, sencillo y barato para evaluar la biodisponibilidad de metal y la ecotoxicidad del suelo. Los tocoferoles son biomarcadores de exposición a metales con potencial para su implementación en bioensayos de toxicidad. Este trabajo permite concluir que la población metalífera de F. rubra, combinada con enmiendas orgánicas, es una excelente candidata para los proyectos de fitoestabilización asistida. Además, la monitorización simultánea de los parámetros fisicoquímicos y microbiológicos del suelo y de su ecotoxicidad permite una evaluación adecuada de la salud del suelo, así como la selección de enmiendas apropiadas para el desarrollo de un proceso fitoestabilizador.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Temperature-and pH-Sensitive Nanohydrogels of Poly(N-Isopropylacrylamide) for Food Packaging Applications: Modelling the Swelling-Collapse Behaviour

Temperature-sensitive poly(N-isopropylacrylamide) (PNIPA) nanohydrogels were synthesized by nanoemulsion polymerization in water-in-oil systems. Several cross-linking degrees and the incorporation of acrylic acid as comonomer at different concentrations were tested to produce nanohydrogels with a wide range of properties. The physicochemical properties of PNIPA nanohydrogels, and their relationship with the swelling-collapse behaviour, were studied to evaluate the suitability of PNIPA nanoparticles as smart delivery systems (for active packaging). The swelling-collapse transition was analyzed by the change in the optical properties of PNIPA nanohydrogels using ultraviolet-visible spectroscopy. The thermodynamic parameters associated with the nanohydrogels collapse were calculated using a mathematical approach based on the van't Hoff analysis, assuming a two-state equilibrium (swollen to collapsed). A mathematical model is proposed to predict both the thermally induced collapse, and the collapse induced by the simultaneous action of two factors (temperature and pH, or temperature and organic solvent concentration). Finally, van't Hoff analysis was compared with differential scanning calorimetry. The results obtained allow us to solve the problem of determining the molecular weight of the structural repeating unit in cross-linked NIPA polymers, which, as we show, can be estimated from the ratio of the molar heat capacity (obtained from the van't Hoff analysis) to the specific heat capacity (obtained from calorimetric measurements).