Combined application of electrolysed water and ultrasound to improve the sanitation of knives in the meat industry

This study investigated the effect of the combination of basic electrolysed water (BEW) and slightly acid electrolysed water (SAEW) with ultrasound (US) for cleaning and sanitation of the knives used in slaughtering processes. The knives were sonicated in a US bath using two modes of operation (normal and sweep) in two steps: (i) 5 min with BEW and (ii) 10 min with SAEW at 35 °C. The microbiological counts and the possible changes in the physical structure of the knives were evaluated. The association BEW + SAEW + US, in the sweep mode, provided lower mesophilic, enterobacterial, Staphylococcus aureus and yeast counts when compared to the values recommended by the international legislation. In addition, these conditions removed all organic residues from the knife blades and promoted the highest migration rate of the residues to the US water bath (12.35 mg/L·min), without modifications in the knife blades. Thus, cleaning and sanitation of knives was feasible with the association of BEW + SAEW + US, which could be a useful alternative for the meat industry.     

Magnetic and structural properties of Fe65Co35 alloys obtained by melting,high-energy milling and heat treatment

The influence of milling and annealing conditions on the structural and magnetic behaviour of mechanically milled Fe₆₅Co₃₅ alloys has been studied. By differential scanning calorimetry measurements we determined the internal stress relaxation temperature, recrystallisation temperature and structural order/disorder transition temperature of bulk and mechanical milled Fe₆₅Co₃₅. The width of the X-ray diffraction peaks was found to increase with the milling time. Two types of annealing were performed: a conventional heat treatment at 500, 550 and 600 °C for 2 h and a rapid annealing for a maximum of 2 min at 700, 750 or 800 °C followed by quenching. Crystallite size increases with increasing heat treatment temperature and time, as both are parameters that influence the magnetic properties of the sample. Magnetic permeability variations result from internal stress evolution, changes in crystallite size, supposing that the crystallite size of the annealed samples is at the border between viability of the Herzer model and the classical behaviour of the permeability vs. crystallite size.     

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? 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.     

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%.     

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.     

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.