Widening siamese architectures for stereo matching

Computational stereo is one of the classical problems in computer vision. Numerous algorithms and solutions have been reported in recent years focusing on developing methods for computing similarity, aggregating it to obtain spatial support and finally optimizing an energy function to find the final disparity. In this paper, we focus on the feature extraction component of stereo matching architecture and we show standard CNNs operation can be used to improve the quality of the features used to find point correspondences. Furthermore, we use a simple space aggregation that hugely simplifies the correlation learning problem, allowing us to better evaluate the quality of the features extracted. Our results on benchmark data are compelling and show promising potential even without refining the solution

Evidence for entanglement at high temperatures in an engineered molecular magnet

The molecular compound [Fe$_{2}$($\mu_{2}$-oxo)(C$_{3}$H$_{4}$N$_{2}$)$_{6}$(C$_{2}$O$_{4}$)$_{2}$] was designed and synthesized for the first time and its structure was determined using single-crystal X-ray diffraction. The magnetic susceptibility of this compound was measured from 2 to 300 K. The analysis of the susceptibility data using protocols developed for other spin singlet ground-state systems indicates that the quantum entanglement would remain at temperatures up to 732 K, significantly above the highest entanglement temperature reported to date. The large gap between the ground state and the first-excited state (282 K) suggests that the spin system may be somewhat immune to decohering mechanisms. Our measurements strongly suggest that molecular magnets are promising candidate platforms for quantum information processing

Equilibrium and Disorder-induced behavior in Quantum Light-Matter Systems

We analyze equilibrium properties of coupled-doped cavities described by the Jaynes-Cummings- Hubbard Hamiltonian. In particular, we characterize the entanglement of the system in relation to the insulating-superfluid phase transition. We point out the existence of a crossover inside the superfluid phase of the system when the excitations change from polaritonic to purely photonic. Using an ensemble statistical approach for small systems and stochastic-mean-field theory for large systems we analyze static disorder of the characteristic parameters of the system and explore the ground state induced statistics. We report on a variety of glassy phases deriving from the hybrid statistics of the system. On-site strong disorder induces insulating behavior through two different mechanisms. For disorder in the light-matter detuning, low energy cavities dominate the statistics allowing the excitations to localize and bunch in such cavities. In the case of disorder in the light- matter coupling, sites with strong coupling between light and matter become very significant, which enhances the Mott-like insulating behavior. Inter-site (hopping) disorder induces fluidity and the dominant sites are strongly coupled to each other.Comment: about 10 pages, 12 figure

HAPNet: hierarchically aggregated pyramid network for real-time stereo matching

©Recovering the 3D shape of the surgical site is crucial for multiple computer-assisted interventions. Stereo endoscopes can be used to compute 3D depth but computational stereo is a challenging, non-convex and inherently discontinuous optimisation problem. In this paper, we propose a deep learning architecture which avoids the explicit construction of a cost volume of similarity which is one of the most computationally costly blocks of stereo algorithms. This makes training our network significantly more efficient and avoids the needs for large memory allocation. Our method performs well, especially around regions comprising multiple discontinuities around surgical instrumentation or around complex small structures and instruments. The method compares well to the state-of-the-art techniques while taking a different methodological angle to computational stereo problem in surgical video

Ductus venosus agenesis and fetal malformations: what can we expect? - a systematic review of the literature

Background: The ductus venosus agenesis (DVA) is a rare condition with a variable prognosis that relies partly on the presence of associated conditions. The purpose of our study was to analyze the literature regarding the postnatal outcome of fetuses with DVA associated with fetal malformations, in order to discuss the best management options for couples. Methods: We performed a systematic review of the literature of MEDLINE and SCOPUS electronic databases in a 25-year period from 1992 to September 2017. Results: We found 340 cases of DVA associated with fetal abnormalities. The most common chromosomal abnormalities were: monosomy X (12/48, 25%), trisomy 21 (11/48, 22.9%) and trisomy 18 (6/48, 12.5%). From the 340 cases with DVA, in 31 cases the umbilical venous shunt type was not reported. Of the fetuses, 60.8% (188/309) had an extrahepatic umbilical venous drainage while 39.2% (121/309) presented an intrahepatic connection. The DVA was associated in 71 cases (23.0%) with cardiac abnormalities, in 82 cases (26.5%) with extracardiac abnormalities and in 85 cases (27.5%) with both cardiac and extracardiac abnormalities. Conclusion: DVA associated with both cardiac and extracardiac malformations may confer a poorer fetal outcome, a clinically relevant fact that should clarify what can be expected from this entity and help prenatal counseling

Experimental evaluation of an interleaved boost topology optimized for peak power tracking control

This paper provides an experimental evaluation of a four phase Floating Interleaved Boost Converter for a photovoltaic power system application. This converter offers improved efficiency and voltage gain, while having lower input current ripple than other DC-DC boost converters. A dual loop, discrete, linear feedback was developed to regulate inductor currents and output capacitor voltages. Maximum Power Point Tracking capability was included. Results of all control functions were used to validate the control development, and point to areas for further improvement

Taxi-Branco: espécie florestal para energia na Amazônia.

bitstream/item/145012/1/AgroenergiaEmRevista-ed09-24-27-2015.pd

Singular value decomposition and matrix reorderings in quantum information theory

We review Schmidt and Kraus decompositions in the form of singular value decomposition using operations of reshaping, vectorization and reshuffling. We use the introduced notation to analyse the correspondence between quantum states and operations with the help of Jamiolkowski isomorphism. The presented matrix reorderings allow us to obtain simple formulae for the composition of quantum channels and partial operations used in quantum information theory. To provide examples of the discussed operations we utilize a package for the Mathematica computing system implementing basic functions used in the calculations related to quantum information theory.Comment: 11 pages, no figures, see http://zksi.iitis.pl/wiki/projects:mathematica-qi for related softwar