Learning spatially correlation filters based on convolutional features via PSO algorithm and two combined color spaces for visual tracking

Last years, we have seen an emergence of wide methods in visual object tracking topic as convolutional neural network combined with correlation filter such as hierarchical features (HCF) (Ma et al. 20). However, upon the fact that some features may cause the tracking failures, the existing methods are still suffering of handling complex object appearance changes such as fast motion, significant deformation and occlusions. Further, they learn the correlation filter in frequency domain using Fourier transform, which cause unwanted boundary effects, which severely degrade the quality of the tracking model. Moreover, these methods are incapable of dealing with the illumination variation because they rely only on RGB base for color sequences. In this paper, we propose a novel method, which addresses the pre-cited problems. As first contribution, we learn adaptively three correlation filters in the spatial domain, with hierarchical convolutional features extracted from specific layers. Indeed, we apply the Particle Swarm Optimization algorithm to solve the update model equation of the correlation filters. Second, we propose that the switching between RGB and HSV color bases, give a soft manner to handle the illumination variation. For this aim, an HSV-energy condition is presented to choose the appropriate color base resorting to the energy of the second HSV component. Extensive experiments on a common benchmark dataset, justify that the proposed method outperforms the state-of-art methods.     

Computational heat transfer and two-phase flow topology in miniature tubes

Detailed computational multi-fluid dynamics simulations have been performed to study the effect of two-phase flow regime on heat transfer in small diameter pipes. Overall the heat removal rate in two-phase flow is higher than in single phase. Subtle differences in thermal removal rates are revealed when the flow-regime transitions from bubbly to slug and slug-train configurations. It is found that the wall thermal layer is affected by two separate mechanisms: an early-stage compression due to gas-jet fragmentation into slugs or bubbles, and a background inclusion-induced flow superimposed on the equivalent single-phase fully developed flow far downstream. The first mechanism resembles a confinement or blockage effect, and is shown to directly influence radial temperature gradients. The downstream mechanism is a cell-based developed flow (rather than fully developed), and is shown here to increase the wall shear in the vicinity of the cell, leading to higher heat transfer rates. The mean Nusselt number distribution shows that the bubbly, slug and slug-train patterns transport as much as three to four times more heat from the tube wall to the bulk flow than pure water flow. A mechanistic heat transfer model is proposed, based on frequency and length scale of inclusions.     

Classification of business documents for real-time application

In this paper, we present a new document classification based on physical layout features and graph b-coloring modeling. In order to reduce the computing time and to increase the performance of our automatic reading system, we propose to pre-classify the business documents by introducing an Automatic Recognition of Documents stage as a pre-analysis phase. This phase guides others involved in the recognition process of the documents contents. Once the document type is identified, the reading system will use its corresponding information source to improve the recognition of its logical layout, the selection and parameterization of the OCR, and the final decision of sorting. The graph coloring model is introduced for both layout analysis and document classification. The proposed method is reliable, robust to various constraints and guarantees a real-time answer to the sorting of business documents.     

Evidence on correlation between number of disulfide bridge and toxicity of class IIa bacteriocins

The aim of this work was to study in the same microbiological conditions and for the first time the inhibitory action of eight class IIa bacteriocins against 23 Gram-positive bacteria in which some of them are industrially used as starters and against the eight class IIa bacteriocins producing strains themselves. The sensitivity of each strain was determined after MPA using the mathematical model described by Cabo et al. (1999, J. Appl. Microbiol. 87, 907-914). Therefore, the principal component analysis realized led to a strong correlation between spectrum and extra-disulfide bridge and a minor correlation between spectrum and isoelectric point of each bacteriocin.     

Characterisation of an antiviral pediocin-like bacteriocin produced by Enterococcus faecium

The bacteriocin-producing strain Enterococcus faecium ST5Ha was isolated from smoked salmon and identified by biomolecular techniques. Ent. faecium ST5Ha produces a pediocin-like bacteriocin with activity against several lactic acid bacteria, Listeria spp. and some other human and food pathogens, and remarkably against HSV-1 virus. Bacteriocin ST5Ha was produced at high levels in MRS broth at 30 °C and 37 °C, reaching a maximum production of 1.0 × 10⁹ AU/ml, checked against Listeria ivanovii ATCC19119 as target strain and surrogate of pathogenic strain Listeria monocytogenes. The molecular weight of bacteriocin ST5Ha was estimated to be 4.5 kDa according to tricine-SDS-PAGE data. Ent. faecium ST5Ha harbors a 1.044 kb chromosomal DNA fragment fitting in size to that of pediocin PA-1/AcH. In addition, the sequencing of bacteriocin ST5Ha gene indicated 99% of DNA homology to pediocin PA-1/AcH. The combined application of low levels (below MIC) of ciprofloxacin and bacteriocin ST5Ha resulted in a synergetic effect in the inhibition of target strain L. ivanovii ATCC19119. Bacteriocin ST5Ha displayed antiviral activity against HSV-1, an important human pathogen, with a selectivity index of 173. To the best of our knowledge, this is the first report on Ent. faecium as a potential producer of pediocin-like bacteriocin with antiviral activity.     

From SIR to SEAIRD: A novel data-driven modeling approach based on the Grey-box System Theory to predict the dynamics of COVID-19

Applied Intelligence - Common compartmental modeling for COVID-19 is based on a priori knowledge and numerous assumptions. Additionally, they do not systematically incorporate asymptomatic cases....     

Inhibition of levodopa effects by internal pallidal stimulation

We report three patients with bilateral GPi stimulation for stage 4 Parkinson's disease (PD) with severe levodopa-induced dyskinesias (LID). In all three it was possible to completely inhibit LID using high-stimulation parameters. Parallel to complete inhibition of LID, an inhibition of the anti-akinetic effect of levodopa was observed, whereas, at the same time, rigidity was markedly improved. GPi stimulation is adaptable over time, and stimulation parameters have to be programmed according to off- and on-period motor symptoms. The main interest of stimulation is the possibility of finding a compromise between LID alleviation in on-phase without loss of the beneficial motor effects and improvement in parkinsonism in off-phase. In some patients, residual dyskinesias have to be accepted so as not to aggravate on-period motor symptoms by a presumed overinhibition of basal ganglia outflow.     

Transport phenomena effect on the performance of proton exchange membrane fuel cell (PEMFC)

The aim of this work is to present a two-dimensional transient model, of heat and mass transfer in a proton exchange membrane fuel cell (PEMFC). The model includes various conservation equations such as mass (hydrogen, oxygen, water concentration), Momentum and energy equations this model is combined with the electrochemical model.     

One dimensional transient numerical study of the mass heat and charge transfer in a proton exchange membrane for PEMFC

The objective of our study is to quantify the mass water transferred by various modes: diffusion, convection and migration. For the water transfer, the principal forces considered in the model are, the convection force, the osmotic force (i.e. diffusion) and the electric force (migration). The first of these forces results from a pressure gradient, the second of a concentration gradient and the third of a protons' migration from the anode to the cathode, which has an effect on the dipole of the water molecules (resistance force to the advancement). The numerical tool used to solve the equations' system is the finite element method. The results obtained numerically considering this method are concentration profiles and concentration variation with time and membrane thickness. These results illustrate the contribution of each mass transfer mode.