Conference on the Matter of Pollution of the Navigable Waters of Puget Sound, the Strait of Juan de Fuca and Their Tributaries and Estuaries. 2d, Seattle, Sept. 6-7, and Oct. 6, 1967: Proceedings.

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Conference on the Matter of Pollution of the Navigable Waters of Puget Sound, the Strait of Juan de Fuca and Their Tributaries and Estuaries. 2d, Seattle, Sept. 6-7, and Oct. 6, 1967: Proceedings.

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Some remarks on the class of continuous (Semi-) strictcly quasiconvex functions

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Arquitectura wormhole per a una NoC 2D-Mesh

Aquest projecte presenta la implementació d'un disseny, i la seva posterior síntesi en una FPGA, d'una arquitectura de tipus wormhole packet switching per a una infraestructura de NetWork-On-Chip amb una topologia 2D-Mesh. Agafant un router circuit switching com a punt de partida, s'han especificat els mòduls en Verilog per tal d'obtenir l'arquitectura wormhole desitjada. Dissenyar la màquina de control per governar els flits que conformen els paquets dins la NoC,i afegir les cues a la sortida del router (outuput queuing) són els punts principals d'aquest treball. A més, com a punt final s'han comparat ambdues arquitectures de router en termes de costos en àrea i en memòria i se n’han obtingut diverses conclusions i resultats experimentals.

Avaluació dels algorismes d'encaminament per a una NoC amb topologia Mesh 2D

Aquest projecte presenta una avaluació de les diferents alternatives d'encaminament per a una NoC amb una topologia mesh 2D. Per tal d'exposar aquestes alternatives s'ha estudiat la composició d'un router implementat amb l'algorisme determinista XY i s'ha adaptat per tal que aquest suportés els algorismes parcialment adaptatius West First, North Last i Negative First. Un cop tenim els routers implementats es disposa un estudi dels diferents algorismes i com cadascun d'aquests actuen en front uns mateixos estímuls per tal de crear una comparativa entre ells que ens faciliti una elecció a priori.

Mass migration of juvenile Biomphalaria glabrata snails bred under semi-natural conditions

For the development of studies on snail interspecific competition special in-door laboratory channels were built. In the all five channels seeded with adult specimens of Biomphalaria glabrata mass migration of juvenile snails outside the water was observed. Most of the migrant snails presented apertural lamellae. Data collected during the period of two years, showed the regression of the migration phenomenon and the disappearance of the lamellate snails.

A mixed finite element method for nonlinear diffusion equations

We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.

Generic optimality conditions for semi-algebraic convex programs

We consider linear optimization over a nonempty convex semi-algebraic feasible region F. Semidefinite programming is an example. If F is compact, then for almost every linear objective there is a unique optimal solution, lying on a unique \active" manifold, around which F is \partly smooth", and the second-order sufficient conditions hold. Perturbing the objective results in smooth variation of the optimal solution. The active manifold consists, locally, of these perturbed optimal solutions; it is independent of the representation of F, and is eventually identified by a variety of iterative algorithms such as proximal and projected gradient schemes. These results extend to unbounded sets F.

H-2D ligand expression by Ly49A+ natural killer (NK) cells precludes ligand uptake from environmental cells: implications for NK cell function.

To study the adaptation of natural killer (NK) cells to their major histocompatibility complex (MHC) class I environment we have established a novel mouse model with mosaic expression of H-2D(d) using a Cre/loxP system. In these mice, we noticed that NK cells expressing the inhibitory receptor for D(d), Ly49A, were specifically underrepresented among cells with low D(d) levels. That was due to the acquisition of D(d) molecules by the Ly49A+ NK cells that have lost their D(d) transgene. The uptake of H-2D molecules via the Ly49A receptor was restricted to strong ligands of Ly49A. Surprisingly, when Ly49A+ NK cells were D(d+), uptake of the alternative ligand D(k) was not detectable. Similarly, one anti-Ly49A mAb (A1) bound inefficiently when Ly49A was expressed on D(d+) NK cells. Concomitantly, functional assays demonstrated a reduced capacity of Ly49A to inhibit H-2(b)D(d) as compared with H-2(b) NK cells, rendering Ly49A+ NK cells in D(d+) mice particularly reactive. Minor reductions of D(d) levels and/or increases of activating ligands on environmental cells may thus suffice to abrogate Ly49A-mediated NK cell inhibition. The mechanistic explanation for all these phenomena is likely the partial masking of Ly49A by D(d) on the same cell via a lateral binding site in the H-2D(d) molecule.

An algorithm for semi-infinite polynomial optimization

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Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.