Comparison of Drying Kinetics for Small Fruits with and without Particle Shrinkage Considerations

Experimental values of volume and area changes for sweet (Prunus avium) and sour (Prunus cerasus) cherry and rose hips (Rosa rubiginosa) measured in previous works were analyzed to propose generalized correlations for the three fruits which predicted with low errors. The correlation developed is lineal and the highest errors were observed for fruit water contents corresponding to storage stability values. The shape factors were measured for the fruits, which were close to spherical values as the fruits dried. This would enable the assumption of spherical shape to calculate characteristic dimensions used in modeling. Moreover, the predictions of kinetic models were compared with experimental data for three radii: the initial, assumed constant; variable, estimating the radius with the correlations published for each fruit; and variable, calculating the radius with the generalized correlation developed in this work. The RMSE between the experimental data and the predictions by the kinetic model were between 0.321 and 0.562; 0.021 and 0.111; and 0.020 and 0.093, respectively.     

Large Time Step Finite Volume Evolution Galerkin Methods

We present two new large time step methods within the framework of the well-balanced finite volume evolution Galerkin (FVEG) schemes. The methodology will be illustrated for low Froude number shallow water flows with source terms modeling the bottom topography and Coriolis forces, but results can be generalized to more complex systems of balance laws. The FVEG methods couple a finite volume formulation with approximate evolution operators. The latter are constructed using the bicharacteristics of multidimensional hyperbolic systems, such that all of the infinitely many directions of wave propagation are taken into account explicitly. We present two variants of large time step FVEG method: a semi-implicit time approximation and an explicit time approximation using several evolution steps along bicharacteristic cones.     

Pick-by-vision: there is something to pick at the end of the augmented tunnel

We report on the long process of exploring, evaluating and refining augmented reality-based methods to support the order picking process of logistics applications. Order picking means that workers have to pick items out of numbered boxes in a warehouse, according to a work order. To support those workers, we have evaluated different HMD-based visualizations in six user studies, starting in a laboratory setup and continuing later in an industrial environment. This was a challenging task, as we had to conquer different kinds of navigation problems from very coarse to very fine granularity and accuracy. The resulting setup consists of a combined and adaptive visualization to precisely and efficiently guide the user even if the actual picking target is not always in the field of view of the HMD.     

A genetic programming method for protein motif discovery and protein classification

Proteins can be grouped into families according to some features such as hydrophobicity, composition or structure, aiming to establish common biological functions. This paper presents MAHATMA—memetic algorithm-based highly adapted tool for motif ascertainment—a system that was conceived to discover features (particular sequences of amino acids, or motifs) that occur very often in proteins of a given family but rarely occur in proteins of other families. These features can be used for the classification of unknown proteins, that is, to predict their function by analyzing their primary structure. Experiments were done with a set of enzymes extracted from the Protein Data Bank. The heuristic method used was based on genetic programming using operators specially tailored for the target problem. The final performance was measured using sensitivity, specificity and hit rate. The best results obtained for the enzyme dataset suggest that the proposed evolutionary computation method is effective in finding predictive features (motifs) for protein classification.     

Microstructure Study at Different Thicknesses of Disc-Shaped YBa2Cu3O7?x Prepared by FQMG Method

The flame-quench-melt-growth (FQMG) method was used for the preparation of bulk YBa₂Cu₃O_7?x (Y123). Both the superconducting and nonsuperconducting regions changing with thickness of superconducting sample were determined by X-ray diffraction (XRD) patterns and also observed at micrographs taken by the polarized optical microscope. It was observed that superconducting forming ratio which was examined for different thicknesses of the sample ranging from 6.54 to 1.58 mm strongly enhanced. This means that a region near the top surface of the sample contains more superconducting phase than the other regions. These observations would be helpful in designing and manufacturing the practical applications of YBCO systems.     

Hydrogen Production by Methanol Steam Reforming Over Pd/ZrO2�CTiO2 Catalysts

Pd/ZrO₂?CTiO₂ catalysts were synthesized by sol?Cgel method and studied on the steam reforming of methanol reaction for hydrogen production. X-ray diffraction patterns of the Pd supported on single oxides showed crystalline structures associated with the zirconia or titania respectively. However, the XRD pattern of the mixed ZrO₂?CTiO₂ oxide showed broad diffraction pattern consistent with an amorphous material. The reducibility of the PdO supported on single and mixed oxides showed a negative peak associated with the desorption of H₂ due to the decomposition of Pd-hydride (PdH); as well as, positive peaks related with the hydrogen consumption on the reduction of the PdO supported. Catalytic activity on the palladium supported on the mixed ZrO₂?CTiO₂ oxide showed higher catalytic activity than the Pd supported on the single TiO₂ or ZrO₂ oxides. This finding was associated at the higher Pd species present in the Pd/ZrO₂?CTiO₂ than on the Pd/ZrO₂ or Pd/TiO₂ catalysts how was observed by TPR.