SHREC'16: partial matching of deformable shapes

Matching deformable 3D shapes under partiality transformations is a challenging problem that has received limited focus in the computer vision and graphics communities. With this benchmark, we explore and thoroughly investigate the robustness of existing matching methods in this challenging task. Participants are asked to provide a point-to-point correspondence (either sparse or dense) between deformable shapes undergoing different kinds of partiality transformations, resulting in a total of 400 matching problems to be solved for each method - making this benchmark the biggest and most challenging of its kind. Five matching algorithms were evaluated in the contest; this paper presents the details of the dataset, the adopted evaluation measures, and shows thorough comparisons among all competing methods

Tethers in Space Handbook

A new edition of the Tethers in Space Handbook was needed after the last edition published in 1989. Tether-related activities have been quite busy in the 90's. We have had the flights of TSSI and TSSI-R, SEDS-1 and -2, PMG, TIPS and OEDIPUS. In less than three years there have been one international Conference on Tethers in Space, held in Washington DC, and three workshops, held at ESA/Estec in the Netherlands, at ISAS in Japan and at the University of Michigan, Ann Harbor. The community has grown and we finally have real flight data to compare our models with. The life of spaceborne tethers has not been always easy and we got our dose of setbacks, but we feel pretty optimistic for the future. We are just stepping out of the pioneering stage to start to use tethers for space science and technological applications. As we are writing this handbook TiPs, a NRL tether project is flying above our heads. There is no emphasis in affirming that as of today spacebome tethers are a reality and their potential is far from being fully appreciated. Consequently, a large amount of new information had to be incorporated into this new edition. The general structure of the handbook has been left mostly unchanged. The past editors have set a style which we have not felt needed change. The section on the flights has been enriched with information on the scientific results. The categories of the applications have not been modified, and in some cases we have mentioned the existence of related flight data. We felt that the section contributed by Joe Carroll, called Tether Data, should be maintained as it was, being a "classic" and still very accurate and not at all obsolete. We have introduced a new chapter entitled Space Science and Tethers since flight experience has shown that tethers can complement other space-based investigations. The bibliography has been updated. Due to the great production in the last few years %e had to restrict our search to works published in refereed journal. The production, however, is much more extensive. In addition, we have included the summary of the papers presented at the last International Conference which was a forum for first-hand information on all the flights

Differentiable Graph Module (DGM) for Graph Convolutional Networks

Graph deep learning has recently emerged as a powerful ML concept allowing to generalize successful deep neural architectures to non-Euclidean structured data. One of the limitations of the majority of current graph neural network architectures is that they are often restricted to the transductive setting and rely on the assumption that the underlying graph is known and fixed. Often, this assumption is not true since the graph may be noisy, or partially and even completely unknown. In such cases, it would be helpful to infer the graph directly from the data, especially in inductive settings where some nodes were not present in the graph at training time. Furthermore, learning a graph may become an end in itself, as the inferred structure may provide complementary insights next to the downstream task. In this paper, we introduce Differentiable Graph Module (DGM), a learnable function that predicts edge probabilities in the graph which are optimal for the downstream task. DGM can be combined with convolutional graph neural network layers and trained in an end-to-end fashion. We provide an extensive evaluation on applications in healthcare, brain imaging, computer graphics, and computer vision showing a significant improvement over baselines both in transductive and inductive settings

Quantum reading under a local energy constraint

Nonclassical states of light play a central role in many quantum information protocols. Their quantum features have been exploited to improve the readout of information from digital memories, modelled as arrays of microscopic beam splitters [S. Pirandola, Phys. Rev. Lett. 106, 090504 (2011)]. In this model of quantum reading, a nonclassical source of light with Einstein-Podolski-Rosen correlations has been proven to retrieve more information than any classical source. In particular, the quantum-classical comparison has been performed under a global energy constraint, i.e., by fixing the mean total number of photons irradiated over each memory cell. In this paper we provide an alternative analysis which is based on a local energy constraint, meaning that we fix the mean number of photons per signal mode irradiated over the memory cell. Under this assumption, we investigate the critical number of signal modes after which a nonclassical source of light is able to beat any classical source irradiating the same number of signals.Comment: REVTeX. Published versio

Quantum state transfer in a q-deformed chain

We investigate the quantum state transfer in a chain of particles satisfying q-deformed oscillators algebra. This general algebraic setting includes the spin chain and the bosonic chain as limiting cases. We study conditions for perfect state transfer depending on the number of sites and excitations on the chain. They are formulated by means of irreducible representations of a quantum algebra realized through Jordan-Schwinger maps. Playing with deformation parameters, we can study the effects of nonlinear perturbations or interpolate between the spin and bosonic chain.Comment: 13 pages, 4 figure

Arachidonic Acid/ppara Enhancement of Ca2+-Regulated Exocytosis in Antral Mucous Cells of Guinea Pig

N is known to be the most limiting element for vegetation growth in temperate and boreal forests. The expected increases in global temperature are predicted to accelerate N mineralization, therefore incrementing N availability in the soil and affecting the soil C cycle as well. While there is an abundance of C data collected to fulfill the requirements for national GHG accounting, more limited information is available for soil N accumulation and storage in relation to forest categories and altitudinal gradients. The data collected by the second Italian National Forest Inventory, spanning a wide range of temperature and precipitation values (10° latitudinal range), represented a unique opportunity to calculate N content and C/N ratio of the different soil layers to a depth of 30 cm. Boosted Regression Tree (BRT) models were applied to investigate the main determinants of soil N distribution and C/N ratio. Forest category was shown to be the main explanatory factor of soil N variability in seven out of eight models, both for forest floor and mineral soil layers. Moreover latitude explained a larger share of variability than single climate variables. BRT models explained, on average, the 49% of the data variability, with the remaining fraction likely due to soil-related variables that were unaccounted for. Accurate estimations of N pools and their determinants in a climate change perspective are consequently required to predict the potential impact of their degradation on forest soil N pools

Giant Sigmoid Diverticulum: A Rare Presentation of a Common Pathology

Although colonic diverticulum is a common disease, affecting about 35% of patients above the age of 60, giant sigmoid diverticulum is an uncommon variant of which only relatively few cases have been described in the literature. We report on our experience with a patient affected by giant sigmoid diverticulum who was treated with diverticulectomy. Resection of the diverticulum is a safe surgical procedure, provided that the colon section close to the lesion presents no sign of flogosis or diverticula; in addition, recurrences are not reported after 6-year follow-up

Testing the Equivalence Principle in an Einstein Elevator: Detector Dynamics and Gravity Perturbations

We discuss specific, recent advances in the analysis of an experiment to test the Equivalence Principle (EP) in free fall. A differential accelerometer detector with two proof masses of different materials free falls inside an evacuated capsule previously released from a stratospheric balloon. The detector spins slowly about its horizontal axis during the fall. An EP violation signal (if present) will manifest itself at the rotational frequency of the detector. The detector operates in a quiet environment as it slowly moves with respect to the co-moving capsule. There are, however, gravitational and dynamical noise contributions that need to be evaluated in order to define key requirements for this experiment. Specifically, higher-order mass moments of the capsule contribute errors to the differential acceleration output with components at the spin frequency which need to be minimized. The dynamics of the free falling detector (in its present design) has been simulated in order to estimate the tolerable errors at release which, in turn, define the release mechanism requirements. Moreover, the study of the higher-order mass moments for a worst-case position of the detector package relative to the cryostat has led to the definition of requirements on the shape and size of the proof masses