Impacts of elevated CO2 on particulate and dissolved organic matter production: microcosm experiments using iron-deficient plankton communities in open subarctic waters

Response of phytoplankton to increasing CO2 in seawater in terms of physiology and ecology is key to predicting changes in marine ecosystems. However, responses of natural plankton communities especially in the open ocean to higher CO2 levels have not been fully examined. We conducted CO2 manipulation experiments in the Bering Sea and the central subarctic Pacific, known as high nutrient and low chlorophyll regions, in summer 2007 to investigate the response of organic matter production in iron-deficient plankton communities to CO2 increases. During the 14-day incubations of surface waters with natural plankton assemblages in microcosms under multiple pCO2 levels, the dynamics of particulate organic carbon (POC) and nitrogen (PN), and dissolved organic carbon (DOC) and phosphorus (DOP) were examined with the plankton community compositions. In the Bering site, net production of POC, PN, and DOP relative to net chlorophyll-a production decreased with increasing pCO2. While net produced POC:PN did not show any CO2-related variations, net produced DOC:DOP increased with increasing pCO2. On the other hand, no apparent trends for these parameters were observed in the Pacific site. The contrasting results observed were probably due to the different plankton community compositions between the two sites, with plankton biomass dominated by large-sized diatoms in the Bering Sea versus ultra-eukaryotes in the Pacific Ocean. We conclude that the quantity and quality of the production of particulate and dissolved organic matter may be altered under future elevated CO2 environments in some iron-deficient ecosystems, while the impacts may be negligible in some systems.

Seawater carbonate chemistry and copepod Centropages tenuiremis feeding, filtering and respiration rate during experiments, 2012

Climate change mediates marine chemical and physical environments and therefore influences marine organisms. While increasing atmospheric CO2 level and associated ocean acidification has been predicted to stimulate marine primary productivity and may affect community structure, the processes that impact food chain and biological CO2 pump are less documented. We hypothesized that copepods, as the secondary marine producer, may respond to future changes in seawater carbonate chemistry associated with ocean acidification due to increasing atmospheric CO2 concentration. Here, we show that the copepod, Centropages tenuiremis, was able to perceive the chemical changes in seawater induced under elevated CO2 concentration (>1700 µatm, pH < 7.60) with avoidance strategy. The copepod's respiration increased at the elevated CO2 (1000 µatm), associated acidity (pH 7.83) and its feeding rates also increased correspondingly, except for the initial acclimating period, when it fed less. Our results imply that marine secondary producers increase their respiration and feeding rate in response to ocean acidification to balance the energy cost against increased acidity and CO2 concentration.

Dynamics of halocarbons in coastal surface waters during short term mesocosm experiments

The aim of the present study was to evaluate the influence of different light quality, especially ultraviolet radiation (UVR), on the dynamics of volatile halogenated organic compounds (VHOCs) at the sea surface. Short term experiments were conducted with floating gas-tight mesocosms of different optical qualities. Six halocarbons (CH3I, CHCl3, CH2Br2, CH2ClI, CHBr3 and CH2I2), known to be produced by phytoplankton, together with a variety of biological and environmental variables were measured in the coastal southern Baltic Sea and in the Raunefjord (North Sea). These experiments showed that ambient levels of UVR have no significant influence on VHOC dynamics in the natural systems. We attribute it to the low radiation doses that phytoplankton cells receive in a normal turbulent surface mixed layer. The VHOC concentrations were influenced by their production and removal processes, but they were not correlated with biological or environmental parameters investigated. Diatoms were most likely the dominant biogenic source of VHOCs in the Baltic Sea experiment, whereas in the Raunefjord experiment macroalgae probably contributed strongly to the production of VHOCs. The variable stable carbon isotope signatures (d13C values) of bromoform (CHBr3) also indicate that different autotrophic organisms were responsible for CHBr3 production in the two coastal environments. In the Raunefjord, despite strong daily variations in CHBr3 concentration, the carbon isotopic ratio was fairly stable with a mean value of -26 per mil. During the declining spring phytoplankton bloom in the Baltic Sea, the d13C values of CHBr3 were enriched in 13C and showed noticeable diurnal changes (-12 per mil ± 4). These results show that isotope signature analysis is a useful tool to study both the origin and dynamics of VHOCs in natural systems.

Unimanual and Bimanual Weight Perception of Virtual Objects with a new Multi-finger Haptic Interface

Accurate weight perception is important particularly in tasks where the user has to apply vertical forces to ensure safe landing of a fragile object or precise penetration of a surface with a probe. Moreover, depending on physical properties of objects such as weight and size we may switch between unimanual and bimanual manipulation during a task. Research has shown that bimanual manipulation of real objects results in a misperception of their weight: they tend to feel lighter than similarly heavy objects which are handled with one hand only [8]. Effective simulation of bimanual manipulation with desktop haptic interfaces should be able to replicate this effect of bimanual manipulation on weight perception. Here, we present the MasterFinger-2, a new multi-finger haptic interface allowing bimanual manipulation of virtual objects with precision grip and we conduct weight discrimination experiments to evaluate its capacity to simulate unimanual and bimanual weight. We found that the bimanual ‘lighter’ bias is also observed with the MasterFinger-2 but the sensitivity to changes of virtual weights deteriorated.

Multipath Reflectivity Estimation in Urban Environments for Synthetic Aperture Radar Images

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range. SAR synthesizes a large aperture radar in order to achieve a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, today¿s new scenes force SAR systems to work in urban environments. Consequently, multiple-bounce returns are added to directscatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor resolution. By analyzing the quadratic phase error (QPE), this paper demonstrates that Earth¿s curvature influences the defocusing degree of multipath returns. In addition to the QPE, other parameters such as integrated sidelobe ratio (ISLR), peak sidelobe ratio (PSLR), contrast (C) and entropy (E) provide us with the tools to identify direct-scatter echoes in images containing undesired returns coming from multipath.

New Technique for Static Target Detection in Dense-Multipath Urban Environments

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range with a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, new uses of Unmanned Aerial Vehicles (UAVs) for civilian-security applications force SAR systems to work in much more complex scenes such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. They are known as ghost images, since they obscure true target image and lead to poor resolution. All this may involve a significant problem in applications related to surveillance and security. In this work, an innovative multipath mitigation technique is presented in which Time Reversal (TR) concept is applied to SAR images when the target is concealed in clutter, leading to TR-SAR technique. This way, the effect of multipath is considerably reduced ?or even removed?, recovering the lost resolution due to multipath propagation. Furthermore, some focusing indicators such as entropy (E), contrast (C) and Rényi entropy (RE) provide us with a good focusing criterion when using TR-SAR.

Experiments in abstract interpretation-based code certification for pervasive systems

Proof carrying code (PCC) is a general is originally a roof in ñrst-order logic of certain vermethodology for certifying that the execution of an un- ification onditions and the checking process involves trusted mobile code is safe. The baste idea is that the ensuring that the certifícate is indeed a valid ñrst-order code supplier attaches a certifícate to the mobile code proof. which the consumer checks in order to ensure that the The main practical difñculty of PCC techniques is in code is indeed safe. The potential benefit is that the generating safety certiñeates which at the same time: i) consumer's task is reduced from the level of proving to allow expressing interesting safety properties, ii) can be the level of checking. Recently, the abstract interpre- generated automatically and, iii) are easy and efficient tation techniques developed, in logic programming have to check. In [1], the abstract interpretation techniques been proposed as a basis for PCC. This extended ab- [5] developed in logic programming1 are proposed as stract reports on experiments which illustrate several is- a basis for PCC. They offer a number of advantages sues involved in abstract interpretation-based certifica- for dealing with the aforementioned issues. In particution. First, we describe the implementation of our sys- lar, the xpressiveness of existing abstract domains will tem in the context of CiaoPP: the preprocessor of the be implicitly available in abstract interpretation-based Ciao multi-paradigm programming system. Then, by code certification to deñne a wide range of safety propermeans of some experiments, we show how code certifi- ties. Furthermore, the approach inherits the automation catión is aided in the implementation of the framework. and inference power of the abstract interpretation en- Finally, we discuss the application of our method within gines used in (Constraint) Logic Programming, (C)LP. the área, of pervasive systems

Abstract interpretation-based code certification for pervasive systems: Preliminary experiments

Proof carrying code is a general methodology for certifying that the execution of an untrusted mobile code is safe, according to a predefined safety policy. The basic idea is that the code supplier attaches a certifícate (or proof) to the mobile code which, then, the consumer checks in order to ensure that the code is indeed safe. The potential benefit is that the consumer's task is reduced from the level of proving to the level of checking, a much simpler task. Recently, the abstract interpretation techniques developed in logic programming have been proposed as a basis for proof carrying code [1]. To this end, the certifícate is generated from an abstract interpretation-based proof of safety. Intuitively, the verification condition is extracted from a set of assertions guaranteeing safety and the answer table generated during the analysis. Given this information, it is relatively simple and fast to verify that the code does meet this proof and so its execution is safe. This extended abstract reports on experiments which illustrate several issues involved in abstract interpretation-based code certification. First, we describe the implementation of our system in the context of CiaoPP: the preprocessor of the Ciao multi-paradigm (constraint) logic programming system. Then, by means of some experiments, we show how code certification is aided in the implementation of the framework. Finally, we discuss the application of our method within the área of pervasive systems which may lack the necessary computing resources to verify safety on their own. We herein illustrate the relevance of the information inferred by existing cost analysis to control resource usage in this context. Moreover, since the (rather complex) analysis phase is replaced by a simpler, efficient checking process at the code consumer side, we believe that our abstract interpretation-based approach to proof-carrying code becomes practically applicable to this kind of systems.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.