Flavour compound production by Yarrowia lipolytica, Saccharomyces cerevisiae and Debaryomyces hansenii in a cheese-surface model

A simple cheese model mimicking a cheese surface was developed for the detection of cheese flavour formation of yeasts. A total of 56 flavour compounds were detected by dynamic headspace sampling followed by gas chromatography–mass spectrometry analysis. Yarrowia lipolytica CBS 2075 primarily produced sulphides, furans and short-chain ketones; Saccharomyces cerevisiae D7 primarily produced esters and Debaryomyces hansenii D18335 primarily produced branched-chain aldehydes and alcohols. For several of the detected flavour compounds, an increase in production was observed upon exposure to dairy-relevant environmental stress conditions including high NaCl concentration and low temperature. The predominant yeasts on the cheese surface may be important for development of flavour, and thus the use of yeasts as ripening cultures has the potential to affect the flavour of cheese.     

A template-based approach to automatic face enhancement

This paper presents Visual ENhancement of USers (VENUS), a system able to automatically enhance male and female frontal facial images exploiting a database of celebrities as reference patterns for attractiveness. Each face is represented by a set of landmark points that can be manually selected or automatically localized using active shape models. The faces can be compared remapping the landmarks by means of Catmull–Rom splines, a class of interpolating splines particularly useful to extract shape-based representations. Given the input image, its landmarks are compared against the known beauty templates and moved towards the K-nearest ones by 2D image warping. The VENUS performances have been evaluated by 20 volunteers on a set of images collected during the Festival of Creativity, held in Florence, Italy, on October 2007. The experiments show that the 73.9% of the beautified faces are more attractive than the original pictures.     

Theoretical Performances of RC Elements Built at Turn of the Century

In the 19th century, the invention of reinforced concrete (RC) technology paved the way for innovation in building methods, though its actual mechanical behavior was not fully understood for some time afterwards. The early period of the inventors and builders, such as Jean Bordenave, Paul Cottancin, A. Bonna, Fran?ois Hennebique, Edmond Coignet, and N. de Tedesco, was followed by a time of intensive activity for the theorists, who developed several accurate analysis methods. A considerable contribution to this success came from the builders themselves, who adopted methods capable of achieving an effective distribution of the reinforcement, and from the technical literature, which facilitated the growth of this new technique. Initially, the theories were somewhat confused because different, sometimes contrasting approaches were used by different authors. By way of example, suffice it to mention the hypotheses developed by Mattias Koenen, P. Neumann, Edmond Coignet, N. de Tedesco, Max Ritter von Thullie, Josef Melan, J. B. Johnson, Léon Stellet, L. Lefort, F. Chaudy, Josef Anton Spitzer, Wilhelm Ritter, and Armand Considère. However, RC became a highly successful material for the 20th century, capable of satisfying the most challenging demands of designers and customers. In this paper special attention is paid to the contribution of the theories suggested at the time, in order to verify their validity in relation to our present understanding.     

Learning in multilayered networks used as autoassociators

Gradient descent learning algorithms may get stuck in local minima, thus making the learning suboptimal. In this paper, we focus attention on multilayered networks used as autoassociators and show some relationships with classical linear autoassociators. In addition, by using the theoretical framework of our previous research, we derive a condition which is met at the end of the learning process and show that this condition has a very intriguing geometrical meaning in the pattern space.     

Mexican tropical hardwoods — Dimensional stability

q_T , q _R ), (2) swelling coefficients (h _T , h _R ), (3) sorption coefficient (s) and (4) the time to equilibrate between EMC at 80% RH and 65% RH.

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q_T , q _R ), (2) der Quellungskoeffizient (h _T , h _R ), (3) der Sorptionskoeffizient (s) und (4) die Angleichszeit zwischen den Gleichgewichtsfeuchten bei φ = 80% und φ = 65%.

     

Hidden tree Markov models for document image classification

Classification is an important problem in image document processing and is often a preliminary step toward recognition, understanding, and information extraction. In this paper, the problem is formulated in the framework of concept learning and each category corresponds to the set of image documents with similar physical structure. We propose a solution based on two algorithmic ideas. First, we obtain a structured representation of images based on labeled XY-trees (this representation informs the learner about important relationships between image subconstituents). Second, we propose a probabilistic architecture that extends hidden Markov models for learning probability distributions defined on spaces of labeled trees. Finally, a successful application of this method to the categorization of commercial invoices is presented.     

A New Hysteretic Behavior in the Electrical Resistivity of Flexinol Shape Memory Alloys Versus Temperature

The electrical resistivity (ER) of Flexinol nickel-titanium shape memory alloys (SMA) has been measured in the range from −15 to 105°C. The investigated Flexinol wires have two diameters, 150 and 375 μm. The experimental results show new temperatures of phase transformation (TTR) evidencing the unexpected presence of the R-phase. The transformations from austenite to martensite, from austenite to R-phase, and vice versa are simultaneous. In the range [20 to 110°C] the hysteresis is almost negligible, whereas in the range [−15 to 105°C] the accommodation process of the hysteresis is observed.     

Numerical Simulation of Heat Conduction to Liquids from a Thin Vertical Cylinder

The paper presents numerical simulations of heat conduction around a circular vertical cylinder immersed in liquids. A finite volume formulation is used, and the numerical analysis is performed in unsteady state with an explicit scheme. The numerical predictions are compared with experiments performed on liquids to find the temperature inside the cylinder, where a thermocouple is located, and at the wall of the insulated coaxial container, where the liquid is poured. The cylinder is immersed vertically. The numerical results are in good agreement with the temperature at the wall of the container. The experimental temperature measurement of the thermocouple located inside the probe is intermediate between the numerical temperatures on the axis and on the surface of the probe. The natural convection phenomenon is evidenced in the experiments, after a certain time from the beginning of heating, in some of the liquids used, except glycerol. Natural convection is not considered in the present numerical simulations, which solve only the heat conduction equation.     

The Application of a Nuclease Enzyme to Clean Stubborn Soils and Odors in Laundry

The inclusion of a nuclease, a new-to-laundry enzyme class in detergent formulations, reduces the concentration of recalcitrant soils on dirty clothing. Nucleases target extracellular DNA that, albeit present in minor quantities in soiled laundry items, disproportionately contributes to the accumulation of sebaceous soils and other compounds that affect the appearance of clothes. These lingering soils accumulate over multiple wear cycles and provoke a dingy appearance in clothing, characterized by dull colors, yellow staining, and an unpleasant malodor. The single and continued use of a nuclease in detergent formulations offers increased removal of these recalcitrant soils to produce less malodorous and visually preferred textiles. Furthermore, the nuclease is effective across different detergent forms, as well as in cotton short washing cycles, enabling improved cleaning in more sustainable laundry washing conditions.