Metabolomics demonstrates divergent responses of two Eucalyptus species to water stress

Past studies of water stress in Eucalyptus spp. generally highlighted the role of fewer than five “important” metabolites, whereas recent metabolomic studies on other genera have shown tens of compounds are affected. There are currently no metabolite profiling data for responses of stress-tolerant species to water stress. We used GC–MS metabolite profiling to examine the response of leaf metabolites to a long (2 month) and severe (Ψpredawn < −2 MPa) water stress in two species of the perennial tree genus Eucalyptus (the mesic Eucalyptus pauciflora and the semi-arid Eucalyptus dumosa). Polar metabolites in leaves were analysed by GC–MS and inorganic ions by capillary electrophoresis. Pressure–volume curves and metabolite measurements showed that water stress led to more negative osmotic potential and increased total osmotically active solutes in leaves of both species. Water stress affected around 30–40% of measured metabolites in E. dumosa and 10–15% in E. pauciflora. There were many metabolites that were affected in E. dumosa but not E. pauciflora, and some that had opposite responses in the two species. For example, in E. dumosa there were increases in five acyclic sugar alcohols and four low-abundance carbohydrates that were unaffected by water stress in E. pauciflora. Re-watering increased osmotic potential and decreased total osmotically active solutes in E. pauciflora, whereas in E. dumosa re-watering led to further decreases in osmotic potential and increases in total osmotically active solutes. This experiment has added several extra dimensions to previous targeted analyses of water stress responses in Eucalyptus, and highlights that even species that are closely related (e.g. congeners) may respond differently to water stress and re-watering

Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space

Learning the structure of a graphical model from data is a common task in a wide range of practical applications. In this paper, we focus on Gaussian Bayesian networks, i.e., on continuous data and directed acyclic graphs with a joint probability density of all variables given by a Gaussian. We propose to work in an equivalence class search space, specifically using the k-greedy equivalence search algorithm. This, combined with regularization techniques to guide the structure search, can learn sparse networks close to the one that generated the data. We provide results on some synthetic networks and on modeling the gene network of the two biological pathways regulating the biosynthesis of isoprenoids for the Arabidopsis thaliana plant

n-Alkan-2-ones in peat-forming plants from the Roñanzas ombrotrophic bog (Asturias, northern Spain)

We determined the distribution of lipids (n-alkanes and n-alkan-2-ones) in present-day peat-formingplants in the RoñanzasBog in northernSpain. Consistent with the observation of others, most Sphagnum (moss) species alkanes maximized at C23, whereas the other plants maximized at higher molecular weight (C27 to C31). We show for the first time that plants other than seagrass and Sphagnum moss contain n-alkan-2-ones. Almost all the species analysed showed an n-alkan-2-one distribution between C21 and C31 with an odd/even predominance, maximizing at C27 or C29, except ferns, which maximized at lower molecular weight (C21–C23). We also observed that microbial degradation can be a major contributor to the n-alkan-2-one distribution in sediments as opposed to a direct input of ketones from plants

Reachability-based acyclicity analysis by Abstract Interpretation

In programming languages with dynamic use of memory, such as Java, knowing that a reference variable x points to an acyclic data structure is valuable for the analysis of termination and resource usage (e.g., execution time or memory consumption). For instance, this information guarantees that the depth of the data structure to which x points is greater than the depth of the data structure pointed to by x.f for any field f of x. This, in turn, allows bounding the number of iterations of a loop which traverses the structure by its depth, which is essential in order to prove the termination or infer the resource usage of the loop. The present paper provides an Abstract-Interpretation-based formalization of a static analysis for inferring acyclicity, which works on the reduced product of two abstract domains: reachability, which models the property that the location pointed to by a variable w can be reached by dereferencing another variable v (in this case, v is said to reach w); and cyclicity, modeling the property that v can point to a cyclic data structure. The analysis is proven to be sound and optimal with respect to the chosen abstraction.

A framework for the analysis and optimization of encoding latency for multiview video

We present a novel framework for the analysis and optimization of encoding latency for multiview video. Firstly, we characterize the elements that have an influence in the encoding latency performance: (i) the multiview prediction structure and (ii) the hardware encoder model. Then, we provide algorithms to find the encoding latency of any arbitrary multiview prediction structure. The proposed framework relies on the directed acyclic graph encoder latency (DAGEL) model, which provides an abstraction of the processing capacity of the encoder by considering an unbounded number of processors. Using graph theoretic algorithms, the DAGEL model allows us to compute the encoding latency of a given prediction structure, and determine the contribution of the prediction dependencies to it. As an example of DAGEL application, we propose an algorithm to reduce the encoding latency of a given multiview prediction structure up to a target value. In our approach, a minimum number of frame dependencies are pruned, until the latency target value is achieved, thus minimizing the degradation of the rate-distortion performance due to the removal of the prediction dependencies. Finally, we analyze the latency performance of the DAGEL derived prediction structures in multiview encoders with limited processing capacity.

Evolución paleoambiental de la Península Ibérica desde hace 1 Ma a partir de los biomarcadores del registro de la Turbera de Padul (Granada)

La Turbera de Padul, en la Provincia de Granada, ofrece unas posibilidades de estudio muy atractivas desde el punto de vista de la reconstrucción paleoambiental. Se trata de una fosa tectónica subsidente de naturaleza detrítica, a cuyo techo aparecen alternantes niveles de turba. El sondeo, de 107 metros, se realizó en un punto donde los estratos de turba aparecen a mayor profundidad, lo que permite obtener un registro geoquímico orgánico con mucho detalle con una antigüedad de hasta 1Ma. Se tomaron muestras cada 20 cm para el análisis de biomarcadores. Estos biomarcadores se obtuvieron mediante extracción Soxhlet, posterior separación de fracciones de diferente polaridad mediante Cromatografía en Columna, con Gel de Sílice y Alúmina, y posteriormente el análisis e identificación por Cromatografía de Gases - Espectrometría de masas, con confirmación de los compuestos químicos identificados por comparación con Bibliotecas de Espectros de Masas. La datación del sondeo se realizó utilizando distintos métodos como datación por 14C, U/Th, y datación por racemización de aminoácidos. Los resultados dataron el muro del sondeo con una antigüedad de 1 millón de años. El estudio de los biomarcadores ha permitido identificar episodios con distintas características en un escenario complejo, como es la Turbera de Padul, donde el aporte de agua por fusión nival complica la interpretación paleoambiental, y es la responsable de la existencia de la lámina de agua en la turbera en periodos secos con temperaturas elevadas. Se han identificado series de n-alcanos, de n-metilcetonas y series de nalcanoles, que han permitido identificar la aportación de materia orgánica de distintas fuentes al sedimento y por tanto la interpretación paleoambiental. La identificación de diterpenoides fenólicos (cis-Totatol, trans-Totarol y Ferruginol) han permitido identificar episodios de clima templado y húmedo con proliferación de cupresáceas, y precipitaciones abundantes. Por otro lado, se han identificado triterpenoides como el Friedelan-3-ona (Friedelin) y el A-norfriedel-8en-10-ona, cuya relación como precursor (Friedelin) y producto (A-norfriedel-8en-10-ona) ha permitido identificar episodios con fluctuaciones del espesor de la lámina de agua y aporte de material vegetal. ABSTRACT The Bog of Padul, in the province of Granada, offers very attractive possibilities for the study of paleoenvironmental reconstruction. It is a subsiding graben of detrital nature, whose upper part appear alternating peat levels. The core of 107 meters, obtained from a borehole drilled in a place where the layers of peat appear deeper, allowing to obtain organic geochemist information along the last 1 million years. Every 20 cm samples for biomarkers analysis were taken. These biomarkers were obtained by Soxhlet extraction, subsequent separation of fractions of different polarity by column chromatography with silica gel and alumina, and then analyzed and identified by gas chromatography - mass spectrometry, with confirmation of the chemicals identified by comparison to mass spectral libraries. The dating of the core was conducted using different methods such as 14C dating, U/Th, and amino acid racemization dating. The results dated the base of the core to be 1 million years old. The study has identified biomarkers episodes with different characteristics in a complex scenario, such as the Bog of Padul, where the contribution of snowmelt water complicates the paleoenvironmental interpretation, and is responsible for the existence of a sheet of water in dry periods with high temperatures. There have been identified series of n-alkanes, n-methyl ketones and series of n-alkanols that have shown the contribution of different organic matter sources to the sediment and therefore allowed to paleo interpretation. The identification of phenolic diterpenoids (cis-Totatol, trans-Totarol and Ferruginol) have identified episodes of mild and humid climate with proliferation of Cupressaceae, and abundant rainfall. In addition, triterpenoids have been identified, as the friedelan-3-one (friedelin) and the A-norfriedel-8en-10-one, whose relationship as precursor (friedelin) and product (A-norfriedel-8en-10-one) has identified episodes with fluctuations on the thickness of the sheet of water and supply of plant material debris.

Metodología para la determinación de los parámetros de planificación de los nodos e infraestructuras logísticas en un territorio, considerando en su planificación el impacto sobre los diferentes componentes territoriales

Esta tesis presenta el diseño y la aplicación de una metodología que permite la determinación de los parámetros para la planificación de nodos e infraestructuras logísticas en un territorio, considerando además el impacto de estas en los diferentes componentes territoriales, así como en el desarrollo poblacional, el desarrollo económico y el medio ambiente, presentando así un avance en la planificación integral del territorio. La Metodología propuesta está basada en Minería de Datos, que permite el descubrimiento de patrones detrás de grandes volúmenes de datos previamente procesados. Las características propias de los datos sobre el territorio y los componentes que lo conforman hacen de los estudios territoriales un campo ideal para la aplicación de algunas de las técnicas de Minería de Datos, tales como los ´arboles decisión y las redes bayesianas. Los árboles de decisión permiten representar y categorizar de forma esquemática una serie de variables de predicción que ayudan al análisis de una variable objetivo. Las redes bayesianas representan en un grafo acíclico dirigido, un modelo probabilístico de variables distribuidas en padres e hijos, y la inferencia estadística que permite determinar la probabilidad de certeza de una hipótesis planteada, es decir, permiten construir modelos de probabilidad conjunta que presentan de manera gráfica las dependencias relevantes en un conjunto de datos. Al igual que con los árboles de decisión, la división del territorio en diferentes unidades administrativas hace de las redes bayesianas una herramienta potencial para definir las características físicas de alguna tipología especifica de infraestructura logística tomando en consideración las características territoriales, poblacionales y económicas del área donde se plantea su desarrollo y las posibles sinergias que se puedan presentar sobre otros nodos e infraestructuras logísticas. El caso de estudio seleccionado para la aplicación de la metodología ha sido la República de Panamá, considerando que este país presenta algunas características singulares, entra las que destacan su alta concentración de población en la Ciudad de Panamá; que a su vez a concentrado la actividad económica del país; su alto porcentaje de zonas protegidas, lo que ha limitado la vertebración del territorio; y el Canal de Panamá y los puertos de contenedores adyacentes al mismo. La metodología se divide en tres fases principales: Fase 1: Determinación del escenario de trabajo 1. Revisión del estado del arte. 2. Determinación y obtención de las variables de estudio. Fase 2: Desarrollo del modelo de inteligencia artificial 3. Construcción de los ´arboles de decisión. 4. Construcción de las redes bayesianas. Fase 3: Conclusiones 5. Determinación de las conclusiones. Con relación al modelo de planificación aplicado al caso de estudio, una vez aplicada la metodología, se estableció un modelo compuesto por 47 variables que definen la planificación logística de Panamá, el resto de variables se definen a partir de estas, es decir, conocidas estas, el resto se definen a través de ellas. Este modelo de planificación establecido a través de la red bayesiana considera los aspectos de una planificación sostenible: económica, social y ambiental; que crean sinergia con la planificación de nodos e infraestructuras logísticas. The thesis presents the design and application of a methodology that allows the determination of parameters for the planning of nodes and logistics infrastructure in a territory, besides considering the impact of these different territorial components, as well as the population growth, economic and environmental development. The proposed methodology is based on Data Mining, which allows the discovery of patterns behind large volumes of previously processed data. The own characteristics of the territorial data makes of territorial studies an ideal field of knowledge for the implementation of some of the Data Mining techniques, such as Decision Trees and Bayesian Networks. Decision trees categorize schematically a series of predictor variables of an analyzed objective variable. Bayesian Networks represent a directed acyclic graph, a probabilistic model of variables divided in fathers and sons, and statistical inference that allow determine the probability of certainty in a hypothesis. The case of study for the application of the methodology is the Republic of Panama. This country has some unique features: a high population density in the Panama City, a concentration of economic activity, a high percentage of protected areas, and the Panama Canal. The methodology is divided into three main phases: Phase 1: definition of the work stage. 1. Review of the State of the art. 2. Determination of the variables. Phase 2: Development of artificial intelligence model 3. Construction of decision trees. 4. Construction of Bayesian Networks. Phase 3: conclusions 5. Determination of the conclusions. The application of the methodology to the case study established a model composed of 47 variables that define the logistics planning for Panama. This model of planning established through the Bayesian network considers aspects of sustainable planning and simulates the synergies between the nodes and logistical infrastructure planning.

Palaeoenvironmental reconstruction of Las Conchas Mire (Asturias, N. Spain) from the ketone and fatty acid record= reconstrucción paleoambiental de la Turbera de las Conchas (Asturias, N. España)a partir del registro de cetonas y ácidos grasos

Se han estudiado los biomarcadores, principalmente cetonas y ácidos, preservados en el registro de 3.2 m de la Turbera de Las Conchas. Las cetonas reflejan cierta actividad bacteriana desde 94 cm hasta la base del registro, Los ácidos grasos reflejan una buena preservación de la materia orgánica, salvo en los 20 cm superiores en los que hay indicios de oxidación microbiana de alcanos .The biomarkers, mainly ketones and fally aclds, preserved In 3.2 m deep Las Conchas Mire have been studied, Kelones reflect certain bacterial activity from 94 cm to the bottom of the record. Falty aclds indlcate a good preservation of the organlc matter, wlth the exception of the uppermost 20 cm In whlch mlcroblal oxldation of alkanes are likely to occur