Activity Recognition based on a Magnitude-Orientation Stream Network

The temporal component of videos provides an important clue for activity recognition, as a number of activities can be reliably recognized based on the motion information. In view of that, this work proposes a novel temporal stream for two-stream convolutional networks based on images computed from the optical flow magnitude and orientation, named Magnitude-Orientation Stream (MOS), to learn the motion in a better and richer manner. Our method applies simple nonlinear transformations on the vertical and horizontal components of the optical flow to generate input images for the temporal stream. Experimental results, carried on two well-known datasets (HMDB51 and UCF101), demonstrate that using our proposed temporal stream as input to existing neural network architectures can improve their performance for activity recognition. Results demonstrate that our temporal stream provides complementary information able to improve the classical two-stream methods, indicating the suitability of our approach to be used as a temporal video representation.Comment: 8 pages, SIBGRAPI 201

Magnitude-Orientation Stream Network and Depth Information applied to Activity Recognition

International audienceThe temporal component of videos provides an important clue for activity recognition , as a number of activities can be reliably recognized based on the motion information. In view of that, this work proposes a novel temporal stream for two-stream convolutional networks based on images computed from the optical flow magnitude and orientation, named Magnitude-Orientation Stream (MOS), to learn the motion in a better and richer manner. Our method applies simple non-linear transformations on the vertical and horizontal components of the optical flow to generate input images for the temporal stream. Moreover, we also employ depth information to use as a weighting scheme on the magnitude information to compensate the distance of the subjects performing the activity to the camera. Experimental results, carried on two well-known datasets (UCF101 and NTU), demonstrate that using our proposed temporal stream as input to existing neural network architectures can improve their performance for activity recognition. Results demonstrate that our temporal stream provides complementary information able to improve the classical two-stream methods, indicating the suitability of our approach to be used as a temporal video representation. two-stream convolutional networks, spatiotemporal information, optical flow, depth information

An Introduction to Deep Morphological Networks

Over the past decade, Convolutional Networks (ConvNets) have renewed the perspectives of the research and industrial communities. Although this deep learning technique may be composed of multiple layers, its core operation is the convolution, an important linear filtering process. Easy and fast to implement, convolutions actually play a major role, not only in ConvNets, but in digital image processing and analysis as a whole, being effective for several tasks. However, aside from convolutions, researchers also proposed and developed non-linear filters, such as operators provided by mathematical morphology. Even though these are not so computationally efficient as the linear filters, in general, they are able to capture different patterns and tackle distinct problems when compared to the convolutions. In this paper, we propose a new paradigm for deep networks where convolutions are replaced by non-linear morphological filters. Aside from performing the operation, the proposed Deep Morphological Network (DeepMorphNet) is also able to learn the morphological filters (and consequently the features) based on the input data. While this process raises challenging issues regarding training and actual implementation, the proposed DeepMorphNet proves to be able to extract features and solve problems that traditional architectures with standard convolution filters cannot

Learning to semantically segment high-resolution remote sensing images

Land cover classification is a task that requires methods capable of learning high-level features while dealing with high volume of data. Overcoming these challenges, Convolutional Networks (ConvNets) can learn specific and adaptable features depending on the data while, at the same time, learn classifiers. In this work, we propose a novel technique to automatically perform pixel-wise land cover classification. To the best of our knowledge, there is no other work in the literature that perform pixel-wise semantic segmentation based on data-driven feature descriptors for high-resolution remote sensing images. The main idea is to exploit the power of ConvNet feature representations to learn how to semantically segment remote sensing images. First, our method learns each label in a pixel-wise manner by taking into account the spatial context of each pixel. In a predicting phase, the probability of a pixel belonging to a class is also estimated according to its spatial context and the learned patterns. We conducted a systematic evaluation of the proposed algorithm using two remote sensing datasets with very distinct properties. Our results show that the proposed algorithm provides improvements when compared to traditional and state-of-the-art methods that ranges from 5 to 15% in terms of accuracy

Magnitude-Orientation Stream Network and Depth Information applied to Activity Recognition

International audienceThe temporal component of videos provides an important clue for activity recognition , as a number of activities can be reliably recognized based on the motion information. In view of that, this work proposes a novel temporal stream for two-stream convolutional networks based on images computed from the optical flow magnitude and orientation, named Magnitude-Orientation Stream (MOS), to learn the motion in a better and richer manner. Our method applies simple non-linear transformations on the vertical and horizontal components of the optical flow to generate input images for the temporal stream. Moreover, we also employ depth information to use as a weighting scheme on the magnitude information to compensate the distance of the subjects performing the activity to the camera. Experimental results, carried on two well-known datasets (UCF101 and NTU), demonstrate that using our proposed temporal stream as input to existing neural network architectures can improve their performance for activity recognition. Results demonstrate that our temporal stream provides complementary information able to improve the classical two-stream methods, indicating the suitability of our approach to be used as a temporal video representation. two-stream convolutional networks, spatiotemporal information, optical flow, depth information

Angiotensin-(1–7)/Mas axis integrity is required for the expression of object recognition memory

AbstractIt has been shown that the brain has its own intrinsic renin–angiotensin system (RAS) and angiotensin-(1–7) (Ang-(1–7)) is particularly interesting, because it appears to counterbalance most of the Ang II effects. Ang-(1–7) exerts its biological function through activation of the G-protein-coupled receptor Mas. Interestingly, hippocampus is one of the regions with higher expression of Mas. However, the role of Ang-(1–7)/Mas axis in hippocampus-dependent memories is still poorly understood. Here we demonstrated that Mas ablation, as well as the blockade of Mas in the CA1-hippocampus, impaired object recognition memory (ORM). We also demonstrated that the blockade of Ang II receptors AT1, but not AT2, recovers ORM impairment of Mas-deficient mice. Considering that high concentrations of Ang-(1–7) may activate AT1 receptors, nonspecifically, we evaluate the levels of Ang-(1–7) and its main precursors Ang I and Ang II in the hippocampus of Mas-deficient mice. The Ang I and Ang II levels are unaltered in the whole hipocampus of MasKo. However, Ang-(1–7) concentration is increased in the whole hippocampus of MasKo mice, as well as in the CA1 area. Taken together, our findings suggest that the functionality of the Ang-(1–7)/Mas axis is essential for normal ORM processing

Orange Pectin Mediated Growth and Stability of Aqueous Gold and Silver Nanocolloids

International audienceThe role of orange based pectin in the nucleation and growth of silver and gold nanoparticles is addressed. Pectin is a complex polysaccharide found in fruits such as oranges, lemons, passion fruits or apples. It displays smooth and hairy chain regions contg. hydroxyl-​, ester-​, carboxylate- and eventually amine groups that can act as surface ligands interacting under various pH conditions more or less efficiently with growing nanometals. Here, a high methoxy pectin (>50​% esterified) was used as a stabilizer​/reducing agent in the prepn. of gold, silver and silver-​gold nanoparticles. Com. pectin (CP) and pectin extd. from orange bagasse (OP) were used. Optionally, trisodium citrate or oxalic acid we used to reduce AgNO3 and HAuCl4 in aq. environment. Characterization methods included UV-​vis absorption spectroscopy, transmission electron microscopy, electron diffraction and energy-​dispersive X-​ray spectroscopy. The results show that under different pH conditions, pectin and reducing agents allow producing various nanostructures shapes (triangles, spheres, rods, octahedrons and decahedrons) often with high polydispersity and sizes ranging between 5 nm and 30 nm. In addn., depending on Ag​/Au-​ratio and pH, the surface plasmon bands can be continuously shifted between 410 nm and 600 nm. Finally, pectin seems to be a highly efficient stabilizer of the colloidal systems that show a remarkable stability and unchanged optical spectral response even after five years

Reversible inhibition of Chlamydia trachomatis infection in epithelial cells due to stimulation of P2X4 receptors

Bacterial infections of the mucosal epithelium are a major cause of human disease. The prolonged presence of microbial pathogens stimulates inflammation of the local tissues, which leads to changes in the molecular composition of the extracellular milieu. A well-characterized molecule that is released to the extracellular milieu by stressed or infected cells is extracellular ATP and its ecto-enzymatic degradation products, which function as signaling molecules through ligation of purinergic receptors. There has been little information, however, on the effects of the extracellular metabolites on bacterial growth in inflamed tissues. Millimolar concentrations of ATP have been previously shown to inhibit irreversibly bacterial infection through ligation of P2X7 receptors. We show here that the proinflammatory mediator, ATP, is released from Chlamydia trachomatis-infected epithelial cells. Moreover, further stimulation of the infected cells with micromolar extracellular ADP or ATP significantly impairs the growth of the bacteria, with a profile characteristic of the involvement of P2X4 receptors. A specific role for P2X4 was confirmed using cells overexpressing P2X4. The chlamydiae remain viable and return to normal growth kinetics after removal of the extracellular stimulus, similar to responses previously described for persistence of chlamydial infection

Oral Ang-(1-7) treatment improves white adipose tissue remodeling and hypertension in rats with metabolic syndrome.

Objective: Angiotensin (Ang)-(1-7) has preventive effects on metabolic syndrome (MetS). The aim of this study was to evaluate the therapeutic effect of oral Ang-(1-7) on mean arterial pressure (MAP), insulin resistance (IR), inflammatory process, and remodeling of white adipose tissue (WAT) in rats with establishedMetS. Methods: Rats were subjected to control (CT; AIN-93M) or high-fat (HF) diets for 13 wk to induce MetS and treated with Ang-(1-7) or vehicle (V) for the last 6 wk. At the end of 13 wk, MAP, biochemical and histological parameters, and uncoupling protein (UCP) and inflammatory gene expression were determined by quantitative reverse transcription polymerase chain reaction. Results: HF-V rats showed increased visceral fat deposition, inflammatory cytokine expression, hyperplasia, and hypertrophy in retroperitoneal (WAT) and brown adipose tissue (BAT). Additionally, the gastrocnemius muscle reduced UCP-3 and increased the UCP-1 expression in BAT. HF-V also elevated levels of plasma insulin, glucose, homeostatic model assessment (HOMA) of IR and HOMA-b, and increased body mass, adiposity, and MAP. Ang-(1-7) treatment in rats with MetS [HF-Ang-(1-7)] reduced WAT area, number of adipocytes, and expression of proinflammatory adipokines in WAT and BAT and increased UCP-3 in gastrocnemius muscle and UCP-1 expression in BAT compared with the HF-V group. These events prevented body mass gain, reduced adiposity, and normalized fasting plasma glucose, insulin levels, HOMA-IR, HOMA-b, and MAP. Conclusion: Data from the present study demonstrated that oral Ang-(1-7) treatment is effective in restoring biochemical parameters and hypertension in established MetS by improving hypertrophy and hyperplasia in WAT and inflammation in adipose tissue, and regulating metabolic processes in the gastrocnemius muscle and BAT