936 resultados para Behavior patterns


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Research on structure and magnetic properties of polynuclear metal complexes to understand the structural and chemical factors governing the electronic exchange coupling mediated by multi-atom bridging ligands is of growing interest. Hydrothermal treatment of Ni(NO3)(2)center dot 6H(2)O with N-(4-carboxyphenyl)iminodiacetic acid N-4(H(3)CPIDA)] at 150 degrees C yielded a 3D coordination polymer of general formula Ni-3{N-4( CPIDA)}(2)(H2O)(3)]center dot 6H(2)O (1). An analogous network of general formula Co-3{N-3(CPIDA)}(2)(H2O)(3)]center dot 3H(2)O (2) was synthesized using N-(3-carboxyphenyl) iminodiacetic acid N-3(H(3)CPIDA)] in combination with Co(NO3)(2)center dot 6H(2)O under identical reaction condition. Both the complexes contain trinuclear secondary building unit, and crystallized in monoclinic system with space groups C2/c (1) and P2(1)/c (2), respectively. Variable temperature magnetic characterization of these complexes in the temperature range of 2-300 K indicated the presence of overall ferromagnetic and antiferromagnetic behavior for 1 and 2, respectively. Density functional theory calculations (B3LYP functional) were performed for further insight on the trinuclear units to provide a qualitative theoretical interpretation on the overall magnetic behavior of the complexes 1 and 2. (C) 2010 Elsevier B.V. All rights reserved.

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Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.

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A minor addition of B to the Ti-6Al-4V alloy, by similar to 0.1 wt pct, reduces its as-cast prior beta grain size by an order of magnitude, whereas higher B content leads to the presence of in situ formed TiB needles in significant amounts. An experimental investigation into the role played by these microstructural modifications on the high-temperature deformation behavior of Ti-6Al-4V-xB alloys, with x varying between 0 wt pct and 0.55 wt pct, was conducted. Uniaxial compression tests were performed in the temperature range of 1023 K to 1273 K (750 degrees C to 1000 degrees C) and in the strain rate range of 10(-3) to 10(+1) s(-1). True stress-true strain responses of all alloys exhibit flow softening at lower strain rates and oscillations at higher strain rates. The flow softening is aided by the occurrence of dynamic recrystallization through lath globularization in high temperature (1173 K to 1273 K 900 degrees C to 1000 degrees C]) and a lower strain rate (10(-2) to 10(-3) s(-1)) regime. The grain size refinement with the B addition to Ti64, despite being marked, had no significant effect on this. Oscillations in the flow curve at a higher strain rate (10(0) to 10(+1) s(-1)), however, are associated with microstructural instabilities such as bending of laths, breaking of lath boundaries, generation of cavities, and breakage of TiB needles. The presence of TiB needles affected the instability regime. Microstructural evidence suggests that the matrix cavitation is aided by the easy fracture of TiB needles.

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Electrochemical quartz crystal microbalance (EQCM) has been used to study the electrochemical precipitation of Mn(OH)(2) on a Au crystal and its capacitance properties. From the EQCM data, it is inferred that NO3- ions get adsorbed on the Au crystal and then undergo reduction, resulting in an increase in pH near the electrode surface. Precipitation of Mn2+ occurs as Mn(OH)(2), with an increase in mass of the Au crystal. Mn(OH)(2) undergoes oxidation to MnO2, which exhibits electrochemical supercapacitor behavior on subjecting to electrochemical cycling in a Na2SO4 electrolyte. EQCM data indicate mass variations corresponding to surface insertion/extraction of Na+ ions during discharge/charge cycling. (C) 2010 The Electrochemical Society. DOI: 10.1149/1.3479665] All rights reserved.

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The hot deformation behaviors of β brass in the temperature range of 550°C to 800°C and α-β brass in the temperature range of 450°C to 800°C have been characterized in the strain rate range of 0.001 to 100 s−1 using processing maps developed on the basis of the Dynamic Materials Model. The map for β brass revealed a domain of superplasticity in the entire temperature range and at strain rates lower than 1 s−1, with a maximum efficiency of power dissipation of about 68 pct. The temperature variation of the efficiency of power dissipation in the domain is similar to that of the diffusion coefficient for zinc in β brass, confirming that the diffusion-accommodated flow controls the superplasticity. The material undergoes microstructural instability in the form of adiabatic shear bands and strain markings at temperatures lower than 700°C and at strain rates higher than 10 s−1. The map for α-β brass revealed a wide domain for processing in the temperature range of 550°C to 800°C and at strain rates lower than 1 s−1, with a maximum efficiency of 54 pct occurring at about 750°C and 0.001 s−1. In the domain, the α phase undergoes dynamic recrystallization and controls the hot deformation of the alloy, while the β phase deforms superplastically. At strain rates greater than 1 s−1, α-β brass exhibits microstructural instabilities manifested as flow rotations at lower temperatures and localized shear bands at higher temperatures.

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Sound recordings and behavioural data were collected from four primate species of two genera (Macaca, Presbytis). Comparative analyses of structural and behavioural aspects of vocal communication revealed a high degree of intrageneric similarity but striking intergeneric differences. In the two macaque species (Macaca silenus, Macaca radiata), males and females shared the major part of the repertoire. In contrast, in the two langurs (Presbytis johnii, Presbytis entellus), many calls were exclusive to adult males. Striking differences between both species groups occurred with respect to age-specific patterns of vocal behaviour. The diversity of vocal behaviour was assessed from the number of different calls used and the proportion of each call in relation to total vocal output for a given age/sex class. In Macaca, diversity decreases with the age of the vocalizer, whereas in Presbytis the age of the vocalizer and the diversity of vocal behaviour are positively correlated. A comparison of the data of the two genera does not suggest any causal relationship between group composition (e.g. multi-male vs. one-male group) and communication system. Within each genus, interspecific differences in vocal behaviour can be explained by differences in social behaviour (e.g. group cohesion, intergroup relation, mating behaviour) and functional disparities. Possible factors responsible for the pronounced intergeneric differences in vocal behaviour between Macaca and Presbytis are discussed.