Development and evaluation of antimicrobial natamycin‐incorporated film in gorgonzola cheese conservation

Conservation of food products depends on product quality and packaging suitability. The objective of this work was to develop and evaluate the antimicrobial efficiency of natamycin‐incorporated film in the production process of Gorgonzola cheese. It aims to optimize the production process and increase shelf‐life and food safety for the consumer. Films with different concentrations of natamycin were produced and tested in Gorgonzola cheeses to evaluate its efficiency against Penicillium roqueforti on the cheese surface. Films with 2 and 4% natamycin presented satisfactory results for fungus inhibition and the amount of natamycin released to the cheese was below that allowed by the legislation. Copyright © 2006 John Wiley & Sons, Ltd.     

Efficient procedure for computing fields created by current modes

An efficient method for computing the fields of large scatterers is presented. The current is expanded in terms of modes defined as complex exponential functions. The modes are represented efficiently by means of spline functions. Analytical expressions have been obtained to compute efficiently the fields due to the current modes.     

Targeting optimum resource allocation using reverse problem formulations and property clustering techniques

Decoupling the constitutive equations from the balance and constraint equations allows for reformulating a conventional forward problem into two reverse problems. The first reverse problem is the reverse of a simulation problem, where the process model is solved in terms of the constitutive (synthesis/design) variables instead of the process variables, thus providing the synthesis/design targets. The second reverse problem (reverse property prediction) solves the constitutive equations to identify unit operations, operating conditions and/or products by matching the synthesis/design targets. Visualization of the problem is achieved by employing recently developed property clustering techniques, which allows a high-dimensional problem to be visualized in two or three dimensions. The clusters by definition satisfy intra-stream and inter-stream conservation through linear “mixing” rules, which allows for the development of consistent additive rules along with their ternary representation.     

A model material approach to the study of fracture process zone of quasi-brittle materials

A new approach to study the fracture of quasi-brittle materials is introduced: the design and testing of model materials. By model material is understood a material with enlarged microstructure and which material parameters, such as stacking and mechanical properties of particles and cohesion force, can be fully controlled. In this paper a first example to the model materials approach is presented, consisting in 5 mm steel particles bonded in a precise stacking with an epoxy-based glue. It is shown how it is possible to correlate the different fracture mechanisms and ultimate peak load of the model material to the particle pair force and to the fracture process zone size. It is also seen how a quasi-brittle behaviour is produced in the presence of mechanisms that induced the crack to shift fracture planes, that is, in presence of energy dissipative mechanisms.     

Iterative method for the design of DFT filter Bank

Multirate adaptive filters have numerous advantages such as low computational load, fast convergence, and parallelism in the adaptation. Drawbacks when using multirate processing are mainly related to aliasing and reconstruction effects. These effects can be minimized by introducing appropriate problem formulation and employing sophisticated optimization techniques. In this paper, we propose a formulation for the design of a filter bank which controls the distortion level for each frequency component directly and minimizes the inband aliasing and the residual aliasing between different subbands. The advantage of this problem formulation is that the distortion level can be weighted for each frequency depending on the particular practical application. A new iterative algorithm is proposed to optimize simultaneously over both the analysis and the synthesis filter banks. This algorithm is shown to have a unique solution for each iteration. For a fixed distortion level, the proposed algorithm yields a significant reduction in both the inband aliasing and the residual aliasing levels compared to existing methods applied to the numerical examples.     

Structure determination of CaMgGeO4

The crystal structure of CaMgGeO₄ is described. CaMgGeO₄, M_r = 200.9, orthorhombic, Pnam, A = 11.285(5) Å, B = 5.016(2) Å, C = 6.435(2) Å, V = 364.36 ų, Dx = 3.664 Mg/m³.λ(MoK_a = 0.71069 Å, F(000) = 384, room temperature, final R = 0.045 for 1752 observed reflections. The structure is isomorphous with CaMgSiO₄ (monticellite).     

Energy efficiency, carbon emissions and economic development in Venezuela

Venezuela's vast natural resource base has largely shaped the nation's economic and energy-use patterns. Major opportunities exist for improving the efficiency of energy use in Venezuela and, consequently, restraining the growth of energy-related carbon emissions. This paper presents a detailed report of one potential development path for Venezuela and estimates the ensuing levels of energy demand and CO₂ emissions associated with pursuing this path through the year 2025. The results indicate that by adopting a development strategy that incorporates structural changes in the economy, fuel-switching measures and improved end-use efficiencies, Venezuela can introduce energy efficiency and carbon restraints as part of its economic development process.     

Experiments of Fast Learning with High Order Boltzmann Machines

This work reports the results obtained with the application of High Order Boltzmann Machines without hidden units to construct classifiers for some problems that represent different learning paradigms. The Boltzmann Machine weight updating algorithm remains the same even when some of the units can take values in a discrete set or in a continuous interval. The absence of hidden units and the restriction to classification problems allows for the estimation of the connection statistics, without the computational cost involved in the application of simulated annealing. In this setting, the learning process can be sped up several orders of magnitude with no appreciable loss of quality of the results obtained.