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Assemblies of vertically connected neurons in the cerebral cortex form information processing units (columns) that participate in the distribution and segregation of sensory signals. Despite well-accepted models of columnar architecture, functional mechanisms of inter-laminar communication remain poorly understood. Hence, the purpose of the present investigation was to examine the effects of sensory information features on columnar response properties. Using acute recording techniques, extracellular response activity was collected from the right hemisphere of eight mature cats (felis catus). Recordings were conducted with multichannel electrodes that permitted the simultaneous acquisition of neuronal activity within primary auditory cortex columns. Neuronal responses to simple (pure tones), complex (noise burst and frequency modulated sweeps), and ecologically relevant (con-specific vocalizations) acoustic signals were measured. Collectively, the present investigation demonstrates that despite consistencies in neuronal tuning (characteristic frequency), irregularities in discharge activity between neurons of individual A1 columns increase as a function of spectral (signal complexity) and temporal (duration) acoustic variations. Multi-unit responses to acoustic signals within A1 columnsThe data set consists of eight multi-unit electrophysiology experiments located within a single .zip file. Acoustic feature (signal type and duration) are in subfolders where data rasters for each recording session conducted can be found. Columns represent time and rows trial number. Data is presented as Matlab files.DRYAD.zip

The behavior of rational selfish agents has been classically studied in the framework of strategic games in which each player has a set of possible actions, players choose actions simultaneously and the payoff for each player is determined by the matrix of the game. However, in many applications, players choose actions asynchronously, and simultaneity of this process is not guaranteed: it is possible that a player learns the action of another player before making its choice. Delays of choices are controled by the adversary and each player can only secure the worst-case payoff over the adversary's decisions. In this paper we consider such asynchronous versions of arbitrary two-person strategic games and we study how the presence of the asynchronous adversary influences the behavior of the players, assumed to be selfish but rational. We concentrate on deterministic (pure) strategies, and in particular, on the existence and characteristics of pure Nash equilibria in such games. It turns out that the rational behavior of players changes significantly if the decision process is asynchronous. We show that pure Nash equilibria often exist in the asynchronous version of the game even if there were no such equilibria in the synchronous game. We also show that a mere threat of asynchrony in the game may make social optimum a rational choice while it was not rational in the synchronous game.

Le but de ce travail de doctorat est d’évaluer la possibilité d’utiliser Haslea ostrearia et la marennine en ostréiculture. Les objectives de ce projet sont : (1) l'évaluation du comportement alimentaire de l'huître creuse Crassostrea gigas sur des cellules d’H. ostrearia de différentes tailles et les conséquences potentielles sur les populations algales; (2) la caractérisation du verdissement par la marennine et ses conséquences sur la physiologie de C. gigas; (3) les conséquences du verdissement sur les traits comportementaux, physiologiques et biochimiques de plusieurs espèces de bivalves; (4) l'utilisation conjuguée d’H. ostrearia avec d'autres microalgues d’importance en aquaculture. Nos résultats suggèrent que la taille des cellules affecte considérablement le processus de selection d’H. ostrearia par l’huître. Cette étude démontre également que la forme extracellulaire de la marenninne contribue significativement au verdissement dans les mucocytes des branchies. Mis à part le verdissement des organes palléaux des bivalves, une concentration modérée de marennine (2 mg L-1) affecte les performances comportementales, physiologiques et biochimiques des bivalves. Néanmoins, ces effets pourraient être compensés par ses activités biologiques comme agent antibactérien naturel et source d’alimentation mixte d’algues en conchyliculture. This Ph.D. thesis focuses on several assessments to achieve the optimum benefit of utilization of marennine in the field of aquaculture. The study covers: (1) the assessment in feeding behavior of the Pacific oyster Crassostrea gigas on different sizes of Haslea ostrearia and its ecological consequence; (2) the characterization of the greening by marennine and its consequences on some physiological traits of on C. gigas. (3) the consequence of greening by marennine on behavioral, physiological and biochemical traits of bivalves; (4) the utilization of H. ostrearia and marennine in a combination diet with other microalgae relevant to aquaculture.Our results suggest that cell size impacts considerably the selection process of H. ostrearia by oyster. This study also demonstrates that the extracellular form of marennine contributes significantly to the greening in the mucocytes of the gills. Apart from greening the pallial organs of bivalves, marennine (2 mg L-1) affects the behavioural, physiological and biochemical performance. Nevertheless, these effects can be compensated for its biological activities such as natural antibacterial agent and use as a mixed algal diet for bivalve aquaculture.

An optimal control problem is studied, in which the state is required to remain in a compact set S. A control feedback law is constructed which, for given ε > 0, produces ε-optimal trajectories that satisfy the state constraint universally with respect to all initial conditions in S. The construction relies upon a constraint removal technique which utilizes geometric properties of inner approximations of S and a related tra jectory tracking result. The control feedback is shown to possess a robustness property with respect to state measurement error.

We consider the classical rumor spreading problem, where a piece of information must be disseminated from a single node to all n nodes of a given network. We devise two simple push-based protocols, in which nodes choose the neighbor they send the information to in each round using pairwise independent hash functions, or a pseudo-random generator, respectively. For several well-studied topologies our algorithms use exponentially fewer random bits than previous protocols. For example, in complete graphs, expanders, and random graphs only a polylogarithmic number of random bits are needed in total to spread the rumor in O(log n) rounds with high probability. Previous explicit algorithms require Omega(n) random bits to achieve the same round complexity. For complete graphs, the amount of randomness used by our hashing-based algorithm is within an O(log n)-factor of the theoretical minimum determined by [Giakkoupis and Woelfel, 2011].

We prove the Haagerup property for an infinite discrete group constructed using surgery on a Euclidean Tits building of type A ˜ 2 .

The OSIRIS instrument onboard the Odin spacecraft routinely measures vertical profiles of spectrally dispersed, limb scattered sunlight from the upper troposphere into the lower mesosphere. These measurements are used to retrieve the ozone number density vertical profile over the altitude range from 10 to 60 km using the SaskMART Multiplicative Algebraic Reconstruction Technique, which is a one dimensional modification of an existing two-dimensional tomographic retrieval algorithm. This technique allows for the consistent merging of the absorption information from radiance measurements at wavelengths in the Chappuis and the Hartley-Huggins bands at each iteration of the inversion. The effectiveness of the retrieval is demonstrated using a set of coincident SAGE II occultation measurements that show a mean bias of less than 2% from 18 to 53 km.

Under a Canadian Foundation for Climate and Atmospheric Sciences (CFCAS) project, targeted to study the feasibility to link regional climate models with lake models, one of the tasks was to consider such a coupling in large lakes. The objective is to provide detailed information on temperature and circulation distributions of the lake to take into account the spatial variability for temperature and the heat exchange through the water's surface. The major contribution of this work is focused on realistic representation of the heat fluxes and temperature distributions to and from lakes especially during the thermally stratified ice-free periods. This paper presents the detailed 3-D ELCOM model applied in Lake Erie in order to produce, at the surface layer of the lake, the spatial distribution of temperature and heat exchanges that eventually can be coupled with a regional climate model (CRCM). Preliminary results will be presented on how this lake model may improve the regional climate models, which currently do not consider such large lake circulation effects.

Principal component analysis provides a fast and robust method to reduce the data dimensionality of an aerosol size distribution data set. Here we describe a methodology for applying principal component analysis to aerosol size distribution measurements. We illustrate the method by applying it to data obtained during five field studies. Most variations in the sub-micrometer aerosol size distribution over periods of weeks can be described using 5 components. Using 6 to 8 components preserves virtually all the information in the original data. A key aspect of our approach is the introduction of a new method to weight the data; this preserves the orthogonality of the components while taking the measurement uncertainties into account. We also describe a new method for identifying the approximate number of aerosol components needed to represent the measurement quantitatively. Applying Varimax rotation to the resultant components decomposes a distribution into independent monomodal distributions. Normalizing the components provides physical meaning to the component scores. The method is relatively simple, computationally fast, and numerically robust. The resulting data simplification provides an efficient method of representing complex data sets and should greatly assist in the analysis of size distribution data.