Pattern expressions and pattern automata

We define the pattern expressions as an extension of both regular expressions and patterns. We prove several properties of the new family of languages, similar to those of extended regex languages [Câmpeanu et al., Int. J. Found. Comput. Sci. 14 (6) (2003) 1007-1018]. We also define an automata system that recognizes these languages. Differences between regex and pattern expressions are also discussed.     

Development of a virtual reality laboratory stressor

Virtual Reality - This research report describes the development of a virtual reality (VR) laboratory stressor to study the effects of exposure to stressful events. The aim of the research was to...     

Modeling on triangulations with geodesic curves

This paper discusses the problem of modeling on triangulated surfaces with geodesic curves. In the first part of the paper we define a new class of curves, called geodesic Bézier curves, that are suitable for modeling on manifold triangulations. As a natural generalization of Bézier curves, the new curves are as smooth as possible. In the second part we discuss the construction of C ⁰ and C ¹ piecewise Bézier splines. We also describe how to perform editing operations, such as trimming, using these curves. Special care is taken to achieve interactive rates for modeling tasks. The third part is devoted to the definition and study of convex sets on triangulated surfaces. We derive the convex hull property of geodesic Bézier curves.

How much nitrogen is fixed by biological symbiosis in tropical dry forests? 2. Herbs

Although biological nitrogen fixation (BNF) is considered the main input of N in mature and regenerating native tropical vegetation, it has seldom been quantified. Biomass and N accumulation and fixation were determined for spontaneously occurring herbaceous species in caatinga areas in four regeneration stages (2, 17, 39 and >50?years after abandonment from agricultural use). BNF was estimated using the ¹⁵N natural-abundance method. The 2-year regeneration area had the highest total herb (6,355?kg?ha^?1) and legume (262?kg?ha^?1) biomass production, N stocks (82?kg?ha^?1) and fixed N (5.0?kg?ha^?1). N₂-fixing legumes (nine species in the sampled area) contributed over 97?% of legume biomass in all areas. Macroptilium gracile added the largest amount of N (3.9?kg?ha^?1 in the 2-year regeneration area) because of its large biomass production (205?kg?ha^?1), although it was not the species with the highest proportion of fixed N (76?%). All of the N₂-fixing species obtained large proportions of their N from symbiosis, most of them more than 50?%.However, the amounts of fixed N per unit area were relatively low (0.22?C5.00?kg?ha^?1) because the biomass of N₂-fixing species was always less than 5?% of the total herb biomass.     

Modification of the La0.6Sr0.4CoO3 coating deposited on ferritic stainless steel by spray pyrolysis after oxidation in air at high temperature

The behaviour of La_0.6Sr_0.4CoO₃ applied to ferritic stainless steel (AISI 430) by spray pyrolysis was investigated after oxidation at 800 °C in air. The film was characterized with regard to its morphology, structure and adhesion. The film was regular over the entire surface and adhered well to the metallic substrate. Oxidation modified the film structure, forming an oxide (SrCrO₄) in the metal/coating region due to Sr diffusion from the coating and Cr diffusion from the metallic substrate. A thermodynamic computational simulation confirmed the formation and stability of this oxide.     

How much nitrogen is fixed by biological symbiosis in tropical dry forests? 1. Trees and shrubs

Despite the recognized importance of the process, estimates of the amount of nitrogen fixed by biological symbiosis in tropical dry forests are almost nonexistent. We estimated the nitrogen fixed annually by the leaves of trees and shrubs at sites regenerating for 16 and 38?years and in an old-growth dry forest using ¹⁵N abundance methodology. The total leaf biomass (1,824?C3,036?kg?ha^?1) and nitrogen contents (62?C90?kg?ha^?1) did not differ among the areas. In all of the areas, most of the leaf biomass belonged to legume plants, but the proportion of the N₂-fixing legumes decreased with increasing regeneration time. In the 16-year regenerating area, almost all of the N was in the leaves of the N-fixing Mimosa tenuiflora plants, but fixation was absent or very low as it was in the N-fixing species present in the 38-year regenerating area. In the old-growth Caatinga, all of the N-fixing species (M. tenuiflora, Piptadenia stipulacea and Anadenanthera colubrina) had large proportions (47?C62?%) of their N derived from atmospheric N₂, but the amount of fixed N (6?kg?ha^?1) was a small proportion of the total leaf N because these plant species were a small part of the vegetation. The total input of biologically fixed N to the old-growth forest was similar in magnitude to an estimate made for a humid tropical forest in Amazonia.     

Can Brazil replace 5% of the 2025 gasoline world demand with ethanol?

Increasing use of petroleum, coupled with concern for global warming, demands the development and institution of CO₂ reducing, non-fossil fuel-based alternative energy-generating strategies. Ethanol is a potential alternative, particularly when produced in a sustainable way as is envisioned for sugarcane in Brazil. We consider the expansion of sugarcane-derived ethanol to displace 5% of projected gasoline use worldwide in 2025. With existing technology, 21 million hectares of land will be required to produce the necessary ethanol. This is less than 7% of current Brazilian agricultural land and equivalent to current soybean land use. New production lands come from pasture made available through improving pasture management in the cattle industry. With the continued introduction of new cane varieties (annual yield increases of about 1.6%) and new ethanol production technologies, namely the hydrolysis of bagasse to sugars for ethanol production and sugarcane trash collection providing renewable process energy production, this could reduce these modest land requirements by 29–38%.     

Ultrasonic densitometer using a multiple reflection technique

This work presents recent improvements in a density measurement cell with a double-element transducer that can eliminate diffraction effects. A new mechanical design combined with the use of more appropriate materials has resulted in better parallelism between interfaces, more robust assembly, and chemical resistance. A novel method of signal processing, named the energy method, is introduced to obtain the reflection coefficient, reducing sensitivity to noise and improving accuracy. The measurement cell operation is verified both theoretically, using an acoustic wave propagation model, and experimentally, using homogeneous liquids with different densities. The accuracy in the density measurement is 0.2% when compared with the measurements made with a pycnometer.     

Incremental construction of minimal deterministic finite cover automata

We present a fast incremental algorithm for constructing minimal Deterministic Finite Cover Automata (DFCA) for a given language. Since it was shown that the minimal DFCA for a language L has less states than the minimal Deterministic Finite Automata (DFA) for the same language L, this technique seems to be the best choice for incrementally building the automaton for a large language, especially when the number of states in the DFCA is significantly less than the number of states in the corresponding minimal DFA. We have implemented the proposed algorithm and have tested it against the best-known DFCA minimization technique.     

Using Boolean factors for the construction of an artificial neural networks

ABSTRACT

We propose a novel approach to define Artificial Neural Network(ANN) architecture from Boolean factors. ANNs are a subfield of machine learning applicable to several areas of life. However, defining its architecture for solving a given problem is not formalized and remains an open research problem. Since it is difficult to look into the network and figure out exactly what it has learnt, the complexity of such a technique makes its interpretation more tedious. We propose in this paper to build feedforward ANNs using the optimal factors obtained from the Boolean context representing a data. Since optimal factors completely cover the data and therefore give an explanation to these data, We could give an interpretation to the neurons activation and justify the presence of a neuron in our proposed neural network. We show through experiments and comparisons on the use data sets that this approach provides relatively better results for some key performance measures.