La Golondrina : The Swallow

https://digitalcommons.library.umaine.edu/mmb-ps/1545/thumbnail.jp

Robust elastic 2D/3D geometric graph matching

We present an algorithm for geometric matching of graphs embedded in 2D or 3D space. It is applicable for registering any graph-like structures appearing in biomedical images, such as blood vessels, pulmonary bronchi, nerve fibers, or dendritic arbors. Our approach does not rely on the similarity of local appearance features, so it is suitable for multimodal registration with a large difference in appearance. Unlike earlier methods, the algorithm uses edge shape, does not require an initial pose estimate, can handle partial matches, and can cope with nonlinear deformations and topological differences. The matching consists of two steps. First, we find an affine transform that roughly aligns the graphs by exploring the set of all consistent correspondences between the nodes. This can be done at an acceptably low computational expense by using parameter uncertainties for pruning, backtracking as needed. Parameter uncertainties are updated in a Kalman-like scheme with each match. In the second step we allow for a nonlinear part of the deformation, modeled as a Gaussian Process. Short sequences of edges are grouped into superedges, which are then matched between graphs. This allows for topological differences. A maximum consistent set of superedge matches is found using a dedicated branch-and-bound solver, which is over 100 times faster than a standard linear programming approach. Geometrical and topological consistency of candidate matches is determined in a fast hierarchical manner. We demonstrate the effectiveness of our technique at registering angiography and retinal fundus images, as well as neural image stacks.Peer ReviewedPostprint (author’s final draft

Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior information of feature appearances. The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods. SDF also includes two original elements, i.e., a deterministic sampling algorithm and a novel model selection algorithm. The two algorithms are tightly coupled to boost the performance of SDF in both speed and accuracy. Specifically, the proposed sampling algorithm leverages the grouping cues of superpixels to generate reliable and consistent hypotheses. The proposed model selection algorithm further makes use of desirable properties of the generated hypotheses, to improve the conventional fit-and-remove framework for more efficient and effective performance. The key characteristic of SDF is that it can efficiently and deterministically estimate the parameters of model instances in multi-structure data. Experimental results demonstrate that the proposed SDF shows superiority over several state-of-the-art fitting methods for real images with single-structure and multiple-structure data.Comment: Accepted by European Conference on Computer Vision (ECCV

Nanocatalizadores de platino soportados sobre un sistema proteína de capa-s/partículas poliméricas : obtención, caracterización y comportamiento en la reacción de reduccción de p-nitrofenol

En este trabajo se prepararon y caracterizaron bionanocatalizadores de platino soportados sobre un template formado por proteínas de capa-S y nanopartículas poliméricas. Las proteínas de capa-S utilizadas fueron aisladas de L. kefiri y las nanopartículas poliméricas fueron a base de poliuretano y acrílico, sintetizados mediante el método del prepolímero y por polimerización en emulsión, respectivamente. Una vez obtenidos los catalizadores, se lo redujo con H2 gaseoso a temperatura ambiente. Todos los sistemas fueron caracterizados por FTIR y microscopía electrónica de transmisión para evaluar la eficiencia de la síntesis de las nanopartículas poliméricas, la morfología del template proteína de capa-S/nanopartículas poliméricas y la distribución de tamaños de las partículas metálicas. Los catalizadores se emplearon en la reacción de reducción del p-nitrofenol con NaBH4, la cual fue seguida espectrofotométricamente, midiendo la absorción del reactivo a 400 nm. Se obtuvieron conversiones de entre 80 y 100% para tiempos de reacción de entre 1 y 1.5 h, obteniéndose los mejores resultados con el catalizador soportado sobre el template capa-S de L. kefiri 83111/acrílico. La excelente performance alcanzada se asigna a la capacidad del template proteínas de capa-S/nanopartículas poliméricas de actuar como guía del crecimiento y ensamblaje de las nanopartículas de platino.Fil: Huggias, Sofía . Universidad Nacional de La PlataFil: Bolla; Patricia A.. Universidad Nacional de La PlataFil: Serradell;María A.. Universidad Nacional de La PlataFil: Peruzzo, Pablo J.. Universidad Nacional de La PlataFil: Casella, Mónica L.. Universidad Nacional de La Plat

How to use mixed precision in ocean models : Exploring a potential reduction of numerical precision in NEMO 4.0 and ROMS 3.6

ceived funding from the EU ESiWACE H2020 Framework Programme under grant agreement no. 823988, from the Severo Ochoa (SEV-2011-00067) program of the Spanish Government and from the Ministerio de Economia y Competitividad under contract TIN2017-84553-C2-1-R.Mixed-precision approaches can provide substantial speed-ups for both computing- and memory-bound codes with little effort. Most scientific codes have overengineered the numerical precision, leading to a situation in which models are using more resources than required without knowing where they are required and where they are not. Consequently, it is possible to improve computational performance by establishing a more appropriate choice of precision. The only input that is needed is a method to determine which real variables can be represented with fewer bits without affecting the accuracy of the results. This paper presents a novel method that enables modern and legacy codes to benefit from a reduction of the precision of certain variables without sacrificing accuracy. It consists of a simple idea: we reduce the precision of a group of variables and measure how it affects the outputs. Then we can evaluate the level of precision that they truly need. Modifying and recompiling the code for each case that has to be evaluated would require a prohibitive amount of effort. Instead, the method presented in this paper relies on the use of a tool called a reduced-precision emulator (RPE) that can significantly streamline the process. Using the RPE and a list of parameters containing the precisions that will be used for each real variable in the code, it is possible within a single binary to emulate the effect on the outputs of a specific choice of precision. When we are able to emulate the effects of reduced precision, we can proceed with the design of the tests that will give us knowledge of the sensitivity of the model variables regarding their numerical precision. The number of possible combinations is prohibitively large and therefore impossible to explore. The alternative of performing a screening of the variables individually can provide certain insight about the required precision of variables, but, on the other hand, other complex interactions that involve several variables may remain hidden. Instead, we use a divide-and-conquer algorithm that identifies the parts that require high precision and establishes a set of variables that can handle reduced precision. This method has been tested using two state-of-the-art ocean models, the Nucleus for European Modelling of the Ocean (NEMO) and the Regional Ocean Modeling System (ROMS), with very promising results. Obtaining this information is crucial to build an actual mixed-precision version of the code in the next phase that will bring the promised performance benefits

Caracterización y actividad catalítica de bionanocatalizadores de platino soportados sobre sistemas proteínas de capa-s/poliuretano

Las subunidades de proteínas de capa-S poseen la capacidad de autoensamblarse sobre distintas superficies formando arreglos en la escala nanométrica. Este aspecto disparó el interés por el empleo de estas proteínas en la construcción biomolecular con prometedoras aplicaciones nanobiotecnológicas

Staphylococcus aureus Induces Eosinophil Cell Death Mediated by α-hemolysin

Staphylococcus aureus, a major human pathogen, exacerbates allergic disorders, including atopic dermatitis, nasal polyps and asthma, which are characterized by tissue eosinophilia. Eosinophils, via their destructive granule contents, can cause significant tissue damage, resulting in inflammation and further recruitment of inflammatory cells. We hypothesised that the relationship between S. aureus and eosinophils may contribute to disease pathology. We found that supernatants from S. aureus (SH1000 strain) cultures cause rapid and profound eosinophil necrosis, resulting in dramatic cell loss within 2 hours. This is in marked contrast to neutrophil granulocytes where no significant cell death was observed (at equivalent dilutions). Supernatants prepared from a strain deficient in the accessory gene regulator (agr) that produces reduced levels of many important virulence factors, including the abundantly produced α-hemolysin (Hla), failed to induce eosinophil death. The role of Hla in mediating eosinophil death was investigated using both an Hla deficient SH1000-modified strain, which did not induce eosinophil death, and purified Hla, which induced concentration-dependent eosinophil death via both apoptosis and necrosis. We conclude that S. aureus Hla induces aberrant eosinophil cell death in vitro and that this may increase tissue injury in allergic disease

Genetic spectrum of hereditary neuropathies with onset in the first year of life

Early onset hereditary motor and sensory neuropathies are rare disorders encompassing congenital hypomyelinating neuropathy with disease onset in the direct post-natal period and Dejerine–Sottas neuropathy starting in infancy. The clinical spectrum, however, reaches beyond the boundaries of these two historically defined disease entities. De novo dominant mutations in PMP22, MPZ and EGR2 are known to be a typical cause of very early onset hereditary neuropathies. In addition, mutations in several other dominant and recessive genes for Charcot–Marie–Tooth disease may lead to similar phenotypes. To estimate mutation frequencies and to gain detailed insights into the genetic and phenotypic heterogeneity of early onset hereditary neuropathies, we selected a heterogeneous cohort of 77 unrelated patients who presented with symptoms of peripheral neuropathy within the first year of life. The majority of these patients were isolated in their family. We performed systematic mutation screening by means of direct sequencing of the coding regions of 11 genes: MFN2, PMP22, MPZ, EGR2, GDAP1, NEFL, FGD4, MTMR2, PRX, SBF2 and SH3TC2. In addition, screening for the Charcot–Marie–Tooth type 1A duplication on chromosome 17p11.2-12 was performed. In 35 patients (45%), mutations were identified. Mutations in MPZ, PMP22 and EGR2 were found most frequently in patients presenting with early hypotonia and breathing difficulties. The recessive genes FGD4, PRX, MTMR2, SBF2, SH3TC2 and GDAP1 were mutated in patients presenting with early foot deformities and variable delay in motor milestones after an uneventful neonatal period. Several patients displaying congenital foot deformities but an otherwise normal early development carried the Charcot–Marie–Tooth type 1A duplication. This study clearly illustrates the genetic heterogeneity underlying hereditary neuropathies with infantile onset