Sea-surface temperature reconstruction of sediment core JT96-09PC

Changes of sea surface temperature (SST) in the subarctic NE Pacific over the last 16,000 calendar years before present (16 kyr BP) have been inferred from the study of C37 alkenone unsaturation in a sediment core from the western Canadian continental slope. Between 16.0 and 11.0 kyr, three distinct cold phases (6-7°C) interrupt two warmer periods (9-10°C). Within the 2sigma range of the radiocarbon based time control, the observed SST oscillations correspond to the Oldest Dryas, the Bolling, the Older Dryas, the Allered, and the Younger Dryas periods in the GISP2 d180 record. These results represent the first high resolution marine paleotemperature estimates off the northern West coast of North America and imply that the climate of this region may be very strongly coupled to that of the North Atlantic. Given the fast rates of SST change (1°C/40-80 yr), such coupling must be controlled by atmospheric transmission of the climate signal.

Phytoplankton production, photosynthetic (P vs E) parameters, and particulate organic carbon and nitrogen within distinct water masses of eastern Australian coastal and shelf waters between 29 °S and 36 °S during spring 2010

The present dataset is part of an interdisciplinary project carried out on board the RV Southern Surveyor off New South Wales (Australia) from the 15th to the 31st October 2010. The main objective of the research voyage was to evaluate how the East Australian Current (EAC) affects the optical, chemical, physical, and biological water properties of the continental shelf and slope off the NSW coast.

Physical oceanography and current meter measurements on the Gulf of Lion continental margin between June 1993 and July 1996

Nine hydrographic cruises were performed on the Gulf of Lion continental margin between June 1993 and July 1996. These observations are analysed to quantify the fluxes of particulate matter and organic carbon transported along the slope by the Northern Current and to characterise their seasonal variability. Concentration of particulate matter and organic carbon are derived from light-transmission data and water sample analyses. The circulation is estimated from the geostrophic current field. The uncertainty on the transport estimate, related to the error on the prediction of particle concentrations from light-transmission data and the error on velocities, is assessed. The particulate matter inflow entering the Gulf of Lion off Marseille is comparable to the Rhône River input and varies seasonally with a maximum transport between autumn and spring. These modifications result from variations of the water flux rather than variations of the particulate matter concentration. Residual transports of particulate matter and organic carbon across the entire Gulf of Lion are calculated for two cruises enclosing the domain that were performed in February 1995 and July 1996. The particulate matter budgets indicate a larger export from the shelf to deep ocean in February 1995 (110 ± 20 kg/s) than in July 1996 (25 ± 18 kg/s). Likewise, the mean particulate organic carbon export is 12.8 ± 0.5 kg/s in February 1995 and 0.8 ± 0.2 kg/s in July 1996. This winter increase is due to larger allochthonous and autochthonous inputs and also to enhanced shelf-slope exchange processes, in particular the cascading of cold water from the shelf. The export of particulate matter by the horizontal currents is moreover two orders of magnitude larger than the vertical particulate fluxes measured at the same time with sediment traps on the continental slope.

Oceanography and methane of waters from the Lena Delta

The Lena River is one of the largest Russian rivers draining into the Laptev Sea. The permafrost areas surrounding the Lena are predicted to thaw at increasing rates due to global temperature increases. With this thawing, large amounts of carbon - either organic or in the gaseous forms carbon dioxide and methane - will reach the waters of the Lena and the adjacent Buor-Khaya Bay (Laptev Sea). Methane concentrations and the isotopic signal of methane in the waters of the Lena Delta and estuary were monitored from 2008 to 2010. Creeks draining from permafrost soils produced hotspots for methane input into the river system (median concentration 1500 nM) compared with concentrations of 30-85 nM observed in the main channels of the Lena. No microbial methane oxidation could be detected; thus diffusion is the main process of methane removal. We estimated that the riverine diffusive methane flux is 3-10 times higher than the flux from surrounding terrestrial environment. To maintain the observed methane concentrations in the river, additional methane sources are necessary. The methane-rich creeks could be responsible for this input.

Understanding traders' regional arbitage : the case of rice traders in Antananarivo, Madagascar

Many studies find that agricultural markets in developing countries are poorly integrated spatially. Traders' regional arbitrage plays a key role in integrating markets across space. We investigate the performance of regional arbitrage and the associated obstacles for rice traders in Antananarivo, Madagascar. On the basis of a trader-level biweekly survey spanning 2012–2013, we find that traders are not fully exploiting the regional arbitrage opportunities: most of them fail to purchase from the cheapest district and are paying higher prices than those in the cheapest district. One apparent obstacle is obtaining price information from many different regions. To reduce search costs, we provided regional price information via SMS to randomly selected traders, but found that this had a null-effect on improving arbitrage performance. Traders tend to concentrate on trading with a few fixed districts, even if they are informed about cheaper prices in other new districts, because they worry about quality uncertainty and the trustworthiness of new partners. These findings suggest that not only transmission of price information but also issues related to produce quality and matching prevent the performance of arbitrage and market integration.

Analysis of frame-compatible subsampling structures for efficient 3DTV broadcast

The evolution of the television market is led by 3DTV technology, and this tendency can accelerate during the next years according to expert forecasts. However, 3DTV delivery by broadcast networks is not currently developed enough, and acts as a bottleneck for the complete deployment of the technology. Thus, increasing interest is dedicated to ste-reo 3DTV formats compatible with current HDTV video equipment and infrastructure, as they may greatly encourage 3D acceptance. In this paper, different subsampling schemes for HDTV compatible transmission of both progressive and interlaced stereo 3DTV are studied and compared. The frequency characteristics and preserved frequency content of each scheme are analyzed, and a simple interpolation filter is specially designed. Finally, the advantages and disadvantages of the different schemes and filters are evaluated through quality testing on several progressive and interlaced video sequences.

Fungal microbiota from rain water and pathogenicity of Fusarium species isolated from atmospheric dust and rainfall dust

In order to determine the presence of Fusarium spp. in atmospheric dust and rainfall dust, samples were collected during September 2007, and July, August, and October 2008. The results reveal the prevalence of airborne Fusarium species coming from the atmosphere of the South East coast of Spain. Five different Fusarium species were isolated from the settling dust: Fusarium oxysporum, F. solani, F. equiseti, F. dimerum, and F. proliferatum. Moreover, rainwater samples were obtained during significant rainfall events in January and February 2009. Using the dilution-plate method, 12 fungal genera were identified from these rainwater samples. Specific analyses of the rainwater revealed the presence of three species of Fusarium: F. oxysporum, F. proliferatum and F. equiseti. A total of 57 isolates of Fusarium spp. obtained from both rainwater and atmospheric rainfall dust sampling were inoculated onto melon (Cucumis melo L.) cv. Piñonet and tomato (Lycopersicon esculentum Mill.) cv. San Pedro. These species were chosen because they are the main herbaceous crops in Almeria province. The results presented in this work indicate strongly that spores or propagules of Fusarium are able to cross the continental barrier carried by winds from the Sahara (Africa) to crop or coastal lands in Europe. Results show differences in the pathogenicity of the isolates tested. Both hosts showed root rot when inoculated with different species of Fusarium, although fresh weight measurements did not bring any information about the pathogenicity. The findings presented above are strong indications that long-distance transmission of Fusarium propagules may occur. Diseases caused by species of Fusarium are common in these areas. They were in the past, and are still today, a problem for greenhouses crops in Almería, and many species have been listed as pathogens on agricultural crops in this region. Saharan air masses dominate the Mediterranean regions. The evidence of long distance dispersal of Fusarium spp. by atmospheric dust and rainwater together with their proved pathogenicity must be taken into account in epidemiological studies.

Information as a Key Tool for Rural Development. 25 Years of Experience in Spain

The lack of useful information has become a major obstacle that hinders the participation of the members of the community in the development process because they can not accurately perceive how their individual and/or collective action can influence their environment, and because of the lack of elements that support the decision-making processes. This article addresses these issues from the work carried out by the Association Instituto de Desarrollo Comunitario de Cuenca (IDC Cuenca) in the rural areas of this province of Spain for 25 years. The results show how the application of methodologies for the transmission of information tailored to each group of recipients in some aspects, enhances the participation of individuals.

Direct and indirect economic impacts of drought in the agri-food sector in the Ebro River basin (Spain).

The economic evaluation of drought impacts is essential in order to define efficient and sustainable management and mitigation strategies. The aim of this study is to evaluate the economic impacts of a drought event on the agricultural sector and measure how they are transmitted from primary production to industrial output and related employment. We fit econometric models to determine the magnitude of the economic loss attributable to water storage. The direct impacts of drought on agricultural productivity are measured through a direct attribution model. Indirect impacts on agricultural employment and the agri-food industry are evaluated through a nested indirect attribution model. The transmission of water scarcity effects from agricultural production to macroeconomic variables is measured through chained elasticities. The models allow for differentiating the impacts deriving from water scarcity from other sources of economic losses. Results show that the importance of drought impacts are less relevant at the macroeconomic level, but are more significant for those activities directly dependent on water abstractions and precipitation. From a management perspective, implications of these findings are important to develop effective mitigation strategies to reduce drought risk exposure.

Contributions to the Resilience Management in the Internet of Things

El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.