Nonlinear Exchange Rate Predictability

We study whether the nonlinear behavior of the real exchange rate can help us account for the lack of predictability of the nominal exchange rate. We construct a smooth nonlinear error-correction model that allows us to test the hypotheses of nonlinear predictability of the nominal exchange rate and nonlinear behavior on the real exchange rate in the context of a fully specified cointegrated system. Using a panel of 19 countries and three numeraires, we find evidence of nonlinear predictability of the nominal exchange rate and of nonlinear mean reversion of the real exchange rate. Out-of-sample Theil's U-statistics show a higher forecast precision of the nonlinear model than the one obtained with a random walk specification. Although the robustness of the out-of-sample results over different forecast windows is somewhat limited, we are able to obtain significant predictability gains--from a parsimonious structural model with PPP fundamentals--even at short-run horizons.Exchange rates; Predictability; Nonlinearities; Purchasing power parity

Principles for Consciousness in Integrated Cognitive Control

In this article we will argue that given certain conditions for the evolution of bi- \ud ological controllers, these will necessarily evolve in the direction of incorporating \ud consciousness capabilities. We will also see what are the necessary mechanics for \ud the provision of these capabilities and extrapolate this vision to the world of artifi- \ud cial systems postulating seven design principles for conscious systems. This article \ud was published in the journal Neural Networks special issue on brain and conscious- \ud ness

Multifunctional Impacts of the Olive Farming Practices in Andalusia, Spain: An Analytic Network Approach

Olive agriculture represents one of the most important economic activities in the region of Andalusia, Spain. Additionally to its economic importance the multifunctional character of agriculture and its wide territorial presence entails that it has a high potential incidence in the environmental and social dimensions of the sustainable development of the region. Despite this importance, it is hypothesised and aimed to be contrasted that olive farmers are not implementing the agricultural practices optimal from an economic, environmental and social point of view. Contrasting this hypothesis entails to evaluate with a holistic and systemic approach the multiple impacts of the different technical alternatives to diverse agricultural practices. The use of the Analytic Network Process, a Multiple Criteria Decision Analysis technique, will be illustrated as a useful approach to deal with this kind of problems characterised by complexity, lack of information and risk. The study will focus on the average yield, climatic, environmental, etc., conditions of olive cultivation in Andalusia. The results seem to confirm the initial hypothesis when comparing the current situation with different scenarios of optimal technical alternatives. In particular the technical alternatives implemented nowadays they are far from being environmentally optimal. The multifunctional benefits and the technical costs of a change from the current situation to these optimal scenarios will be analysed.Olive farming practices, Multifunctionality, Analytic Network Process, Farm Management,

Library Preparation for Whole Genome Bisulfite Sequencing of Plant Genomes

Epigenetic mechanisms are a key interface between the environment and the genotype. These mechanisms regulate gene expression in response to plant development and environmental stimuli, which ultimately affects the plant’s phenotype. DNA methylation, in particular cytosine methylation, is probably the best studied epigenetic modification in eukaryotes. It has been associated to the regulation of gene expression in response to cell/tissue differentiation, organism development and adaptation to changing environments. Whole genome bisulfite sequencing (WGBS) is considered the gold standard to study DNA methylation at a genome level. Here we present a protocol for the preparation of whole genome bisulfite sequencing libraries from plant samples (grapevine leaves) which includes detailed instructions for sample collection and DNA extraction, sequencing library preparation and bisulfite treatment

Bankruptcy prediction models in Galician companies. Application of parametric methodologies and artificial intelligence

This paper provides empirical evidence on the prediction of non-financial companies’ failure. We develop several models to evaluate failure risk in companies from Galicia. We check the predictive ability of parametric models (multivariate discriminant, logit) compared with auditor’s report. Models are based on relevant financial variables and ratios, in financial logic and a in financial distress situations. We examine a random sample of companies in cross-sectional perspective, checking the predictive capacity at any given time, also verifying is models give reliable signals to anticipate future events of financial distress. Findings suggest that our models are extremely effective when applied in medium and long term, and that they offer higher predictive capabilities than external audit.peer-reviewe

The Regulation of Plant Vegetative Phase Transition and Rejuvenation: miRNAs, a Key Regulator

In contrast to animals, adult organs in plants are not formed during embryogenesis but generated from meristematic cells as plants advance through development. Plant development involves a succession of different phenotypic stages and the transition between these stages is termed phase transition. Phase transitions need to be tightly regulated and coordinated to ensure they occur under optimal seasonal, environmental conditions. Polycarpic perennials transition through vegetative stages and the mature, reproductive stage many times during their lifecycles and, in both perennial and annual species, environmental factors and culturing methods can reverse the otherwise unidirectional vector of plant development. Epigenetic factors regulating gene expression in response to internal cues and external (environmental) stimuli influencing the plant’s phenotype and development have been shown to control phase transitions. How developmental and environmental cues interact to epigenetically alter gene expression and influence these transitions is not well understood, and understanding this interaction is important considering the current climate change scenarios, since epigenetic maladaptation could have catastrophic consequences for perennial plants in natural and agricultural ecosystems. Here, we review studies focusing on the epigenetic regulators of the vegetative phase change and highlight how these mechanisms might act in exogenously induced plant rejuvenation and regrowth following stress

Shotgun Metagenomic Sequencing Data of Sunflower Rhizosphere Microbial Community in South Africa

This dataset presents shotgun metagenomic sequencing of sunflower rhizosphere microbiome in Bloemhof, South Africa. Data were collected to decipher the structure and function in the sunflower microbial community. Illumina HiSeq platform using next generation sequencing of the DNA was carried out. The metagenome comprised 8,991,566 sequences totaling 1,607,022,279 bp size and 66% GC content. The metagenome was deposited into the NCBI database and can be accessed with the SRA accession number SRR10418054. An online metagenome server (MG RAST) using the subsystem database revealed bacteria had the highest taxonomical representation with 98.47%, eukaryote at 1.23%, and archaea at 0.20%. The most abundant genera were the Conexibacter (17%), Nocardioides (8%), Streptomyces (7%), Geodermatophilus (6%), Methylobacterium (5%), and Burkholderia (4%). MG-RAST assisted analysis also revealed functional annotation based on subsystem, carbohydrates sequence had 13.74%, clustering based subsystem 12.93%, amino acids and derivatives 10.30% coupled with other useful functional traits needed for plant growth and health

Construcción de curvas de fragilidad para viviendas unifamiliares de muros de ductilidad limitada

El Perú es un país de alta sismicidad debido a su ubicación en el Cinturón de Fuego del Pacífico. El análisis de los registros históricos, así como el estudio del desempeño de los sistemas estructurales, han servido de base para el desarrollo de disposiciones normativas de diseño sísmico. El objetivo principal de estas disposiciones es reducir el riesgo sísmico. El déficit de viviendas en el Perú y el crecimiento de la población son la razón de la demanda permanente. Las viviendas de muros de concreto de ductilidad limitada (VMDL) son preferidas por los promotores inmobiliarios. Esto se debe a que esta tipología estructural resulta muy productiva en términos de tiempo de ejecución, simplificación de los procedimientos de construcción y reducción de los costos de construcción. La ausencia de sismos de gran magnitud durante 271 años en la costa centro del Perú, hacen que las viviendas y edificios de paredes delgadas no hayan sido sometidas a fuertes aceleraciones aún. Por lo tanto, no se cuenta con información de campo sobre su desempeño. Algunas pruebas de laboratorio se han llevado a cabo para evaluar el desempeño de muros individuales a escala natural. En dichas pruebas se han seguido los protocolos y provisiones de FEMA 461. El presente trabajo se centra principalmente en el desarrollo de curvas de fragilidad para viviendas de muros de concreto de ductilidad limitada (VMDL) edificadas sobre un pefil de suelo tipo S2. Estas funciones pueden obtenerse mediante opinión de expertos, pruebas de laboratorio, recopilación de información de campo y técnicas de simulación. En esta investigación, las curvas de fragilidad son generadas por una técnica de simulación de Montecarlo. Se generan curvas de fragilidad para viviendas unifamiliares típicas de 2 y 3 pisos que han sido diseñadas siguiendo los lineamientos de la normativa peruana vigente. El modelo de 2 pisos consiste en 3 viviendas que forman un solo bloque y comparten muros medianeros, en tanto que el modelo de 3 pisos es un bloque independiente. Estos dos modelos son representativos de la oferta actual de vivienda que se viene construyendo desde los años 90. La contribución más importante es el enfoque probabilístico que toma en cuenta la aleatoriedad de las propiedades mecánicas de los materiales involucrados, tales como la resistencia a la compresión del concreto y el límite de fluencia del acero de refuerzo, así como la incertidumbre de la demanda sísmica mediante la generación de señales sintéticas compatibles con el espectro normativo. Los resultados muestran un buen desempeño sismico para ambas tipologías. Para sismo severo (PGA=0.45g) la probabilidad de presentar daño leve es del 1% o menos.Tesi