Sensory acceptability of raw and extruded bovine rumen protein in processed meat products

The use of bovine rumen protein (raw and extruded) as a replacement for extruded soy protein concentrate in three meat products (pork sausage, chicken hamburger, and kibbe) was investigated. Similarity between rumen and soy protein meat products was assessed using triangle tests and sensory acceptability evaluated by consumer panelists using a nine-point hedonic scale. The addition of raw rumen protein was detected in all meat product types tested, while extruded rumen protein was only detected in kibbe. The addition of raw rumen protein decreased the acceptability of pork sausage aroma and flavor, but improved kibbe appearance, texture and overall acceptability. The addition of extruded rumen protein reduced the acceptability of chicken hamburger texture, but improved pork sausage flavor. Replacement of soy protein by bovine rumen protein is feasible based upon sensory results, but depended upon its form and the type of meat product to which it was added.     

Chance-constrained model predictive control for spacecraft rendezvous with disturbance estimation

A robust Model Predictive Controller (MPC) is used to solve the problem of spacecraft rendezvous, using the Hill-Clohessy-Wiltshire model with additive disturbances and line-of-sight constraints. Since a standard (non-robust) MPC is not able to cope with disturbances, a robust MPC is designed using a chance-constrained approach for robust satisfaction of constraints in a probabilistic sense. Disturbances are modeled as Gaussian allowing for an explicit transformation of the probabilistic constraints into simple algebraic constraints. To estimate the distribution parameters a predictor of disturbances is proposed. Both robust and non-robust MPC control laws are compared using the Monte Carlo method, which shows the superiority of the robust MPC.     

Background subtraction model based on color and depth cues

Background subtraction consists of segmenting objects in movement in a video captured by a static camera. This is typically performed using color information, but it leads to wrong estimations due to perspective and illumination issues. We show that multimodal approaches based on the integrated use of color and depth cues produce more accurate and robust results than using either data source independently. Depth is less affected by issues such as shadows or foreground objects similar to background. However, objects close to the background may not be detected when using only range information, being color information complementary in those cases. We propose an extension of a well-known background subtraction technique which fuses range and color information, as well as a post-processing mask fusion stage to get the best of each feature. We have evaluated the method proposed using a well-defined dataset and different disparity estimation algorithms, showing the benefits of our method for fusion color and depth cues.     

Lie Algebra and System Identification Techniques for 3D Rigid Motion Estimation and Monocular Tracking

This paper addresses the parameters’ estimation of 2D and 3D transformations. For the estimation we present a method based on system identification theory, we named it the “A-method”. The transformations are considered as elements of the Lie group GL(n) or one of its subgroups. We represent the transformations in terms of their Lie Algebra elements. The Lie algebra approach assures to follow the shortest path or geodesic in the involved Lie group. To prove the potencial of our method, two experiments are presented. The first one is a monocular estimation of 3D rigid motion of an object in the visual space. With this aim, the six parameters of the rigid motion are estimated based on measurements of the six parameters of the affine transformation in the image. Secondly, we present the estimation of the affine or projective transformations involved in monocular region tracking. Jaime Ortegón-Aguilar received his degree in computer sciences at the Universidad Autonoma de Yucatan in Merida, Mexico in 2000. He earned his M.Sc. degree at the Cinvestav in Guadalajara, Mexico in 2002. He received his PhD degree from Cinvestav in 2006. His research interests include image processing, computer vision, robotics and applications of geometric algebra. Eduardo Jose Bayro-Corrochano gained his Ph.D. in Cognitive Computer Science in 1993 from the University of Wales at Cardiff. From 1995 to 1999 he has been Researcher and Lecturer at the Institute for Computer Science, Christian Albrechts University, Kiel, Germany, working on applications of geometric Clifford algebra to cognitive systems. At present is a full professor at CINVESTAV Unidad Guadalajara, México, Department of Electrical Engineering and Computer Science. His current research interest focuses on geometric methods for artificial perception and action systems. It includes geometric neural networks, visually guided robotics, humanoids, color image processing, Lie bivector algebras for early vision and robot maneuvering. He developed the quaternion wavelet transform for quaternion multi-resolution analysis using the phase concept. He is associate editor of Robotics and Journal of Advanced Robotic Systems and member of the editorial board of Journal of Pattern Recognition, Journal of Mathematical Imaging and Vision, Iberoamerican Journal of Computer and Systems and Journal of Theoretical and Numerical Approximation. He is editor and author of the following books: Geometric Computing for Perception Action Systems, E. Bayro-Corrochano, Springer Verlag, 2001; Geometric Algebra with Applications in Science and Engineering, E. Bayro-Corrochano and G. Sobczyk (Eds.), Birkhauser 2001; Handbook of Geometric Computing for Pattern Recognition, Computer Vision, Neurocomputing and Robotics, E. Bayro-Corrochano, Springer Verlag, 2005. He has published over 120 refereed journal, book chapters and conference papers. He is fellow of the IAPR society.     

On fluidization of discrete event models: observation and control of continuous Petri nets

As a preliminary overview, this work provides first a broad tutorial on the fluidization of discrete event dynamic models, an efficient technique for dealing with the classical state explosion problem. Even if named as continuous or fluid, the relaxed models obtained are frequently hybrid in a technical sense. Thus, there is plenty of room for using discrete, hybrid and continuous model techniques for logical verification, performance evaluation and control studies. Moreover, the possibilities for transferring concepts and techniques from one modeling paradigm to others are very significant, so there is much space for synergy. As a central modeling paradigm for parallel and synchronized discrete event systems, Petri nets (PNs) are then considered in much more detail. In this sense, this paper is somewhat complementary to David and Alla (2010). Our presentation of fluid views or approximations of PNs has sometimes a flavor of a survey, but also introduces some new ideas or techniques. Among the aspects that distinguish the adopted approach are: the focus on the relationships between discrete and continuous PN models, both for untimed, i.e., fully non-deterministic abstractions, and timed versions; the use of structure theory of (discrete) PNs, algebraic and graph based concepts and results; and the bridge to Automatic Control Theory. After discussing observability and controllability issues, the most technical part in this work, the paper concludes with some remarks and possible directions for future research.     

Melt processing of ethylene–vinyl acetate/banana starch/Cloisite 20A organoclay nanocomposite films: structural,thermal and composting behavior

This work shows the preparation of ethylene vinyl acetate copolymer/banana starch/Cloisite 20A organoclay (EVA/starch/C20A) nanocomposites by melt processing. Wide angle X-ray diffraction (WAXD), field emission scanning electron microscopy (FE-SEM), differential scanning calorimetry and thermogravimetric analysis were used to characterize the obtained nanocomposites. Mechanical properties were also determined. In addition, the performance of the nanocomposite films under composting was preliminarily studied; it was conducted using the soil burial test method. Despite knowing that the starch is difficult to process by extrusion, nanocomposite films with high homogeneity were obtained. In this case, C20A organoclay acts as an effective surfactant to make the starch natural polymer compatible with the EVA synthetic polymer. The good compatibility between EVA, starch and C20A clay was also deduced by the formation of intercalated and intercalated-exfoliated structures determined by WAXD and FE-SEM. Physical evidence of the damage in EVA/starch/C20A nanocomposite films after the composting test was observed. It is worth noting that despite the absence of starch, the EVA/C20A nanocomposite film, used as a control, also showed surface damage. This behavior is related to the organic modifier linked to clay C20A, which contains molecules derived from fatty acids that can be used as a food source for microorganisms.

     

Antimicrobial effects of silver nanoparticles against bacterial cells adhered to stainless steel surfaces

Given the increasing number of antibiotic-resistant bacteria and the need to synthesize new antimicrobials, silver has attracted interest in the scientific community because of its recognized antimicrobial activity. This study aimed to evaluate the antimicrobial effects of silver nanoparticles (NP) obtained by a new method and tested at concentrations of 6 μg/ml and 60 μg/ml against the species Staphylococcus aureus, Listeria innocua, Salmonella Choleraesuis, Pseudomonas aeruginosa, Escherichia coli, and Bacillus cereus. The ability of these nanoparticles to remove or kill vegetative cells adhered to stainless steel surfaces was also evaluated. We observed that the NP obtained with the new method, concentrated silver nanoparticles (CNP), and silver nanoparticles with added sodium chloride (NPNaCl) had high antimicrobial activities (P < 0.05). We also verified that the most effective condition for the removal of P. aeruginosa cells on stainless steel coupons (10 by 10 mm) was immersion of the surfaces in CNP. The CNP treatment produced a 5-log reduction of the microbial population after 30 to 60 min of immersion. The CNP treatment also performed better than water and sodium carbonate, a compound commonly applied in clean-in-place procedures in the food industry, in removing adherent B. cereus cells from stainless steel cylinders. Therefore, these results suggest that NP synthesized by a new procedure may be used as antimicrobials in the food industry, for example, for the sanitization of utensils that come into contact with foods.     

On Burst Length Distribution and Preemption Probabilities in OBS Networks with Burst Segmentation

Recently, preemption techniques have attracted considerable attention as a means to provide differentiated quality of service in optical burst switching (OBS) networks. This paper is focused on the analysis of preemption probabilities for bursts within the same priority class. As proposed by Vokkarane and Jue ((2003)* IEEE J Select Areas Commun 21(7): 1198–1209) an incoming burst will preempt the burst in service, within the same priority class, if the residual length of the burst in service is smaller than the incoming burst length. For a general case with wavelength conversion, the preemption probability of contending bursts with a generic service distribution, not necessarily exponential, is analyzed. First, we show that the size distribution for the preempting bursts is shifted to larger values, in comparison to the original burst size distribution. Second, we obtain an upper and lower bound for the preemption probability. Finally, the asymptotic behavior of the OBS switch is analyzed showing that preemption will always occur for a very large number of wavelengths.     

In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.     

Option pricing under a jump-telegraph diffusion model with jumps of random size

ABSTRACT

We present a finite difference method to solve a system of two Partial-Integro Differential Equations which arise from pricing an option under a Jump-Telegraph Diffusion Model for the underlying asset, considering the risk-neutral valuation formula under an equivalent martingale measure. This system is fully discretized using an Implicit–Explicit two-time level scheme and quadrature formulas. The resulting two tridiagonal algebraic linear systems are solved recursively using the Thomas Algorithm. Some numerical results are presented and the numerical order of convergence for the method is estimated. Finally, the robustness of the method is validated against an exact solution obtained for a perturbed problem.