Temperature and magnetic-field dependence of the elastic constants of Ni-Mn-Al magnetic Heusler alloy

We report on measurements of the adiabatic second-order elastic constants of the off-stoichiometric Ni54Mn23Al23 single-crystalline Heusler alloy. The variation in the temperature dependence of the elastic constants has been investigated across the magnetic transition and over a broad temperature range. Anomalies in the temperature behavior of the elastic constants have been found in the vicinity of the magnetic phase transition. Measurements under applied magnetic field, both isothermal and variable temperature, show that the value of the elastic constants depends on magnetic order, thus giving evidence for magnetoelastic coupling in this alloy system.

Linear relation between deuteron matter radius and the scattering length

We explain the empirical linear relations between the triplet scattering length, or the asymptotic normalization constant, and the deuteron matter radius using the effective range expansion in a manner similar to a recent paper by Bhaduri et al. We emphasize the corrections due to the finite force range and to shape dependence. The discrepancy between the experimental values and the empirical line shows the need for a larger value of the wound extension, a parameter which we introduce here. Short-distance nonlocality of the n-p interaction is a plausible explanation for the discrepancy.

Spatial and linear correlations between soil and corn

The Technologies setting at Agricultural production system have the main characteristics the vertical productivity, reduced costs, soil physical, chemical and biological improvement to promote production sustainable growth. Thus, the study aimed to determine the variability and the linear and special correlations between the plant and soil attributes in order to select and indicate good representation of soil physical quality for forage productivity. In the growing season of 2006, on the Fazenda Bonança in Pereira Barreto (SP), the productivity of autumn corn forage (FDM) in an irrigated no-tillage system and the soil physical properties were analyzed. The purpose was to study the variability and the linear and spatial correlations between the plant and soil properties, to select an indicator of soil physical quality related to corn forage yield. A geostatistical grid was installed to collect soil and plant data, with 125 sampling points in an area of 2,500 m². The results show that the studied properties did not vary randomly and that data variability was low to very high, with well-defined spatial patterns, ranging from 7.8 to 38.0 m. On the other hand, the linear correlation between the plant and the soil properties was low and highly significant. The pairs forage dry matter versus microporosity and stem diameter versus bulk density were best correlated in the 0-0.10 m layer, while the other pairs - forage dry matter versus macro - and total porosity - were inversely correlated in the same layer. However, from the spatial point of view, there was a high inverse correlation between forage dry matter with microporosity, so that microporosity in the 0-0.10 m layer can be considered a good indicator of soil physical quality, with a view to corn forage yield.

Coexisting ferro- and antiferromagnetism in Ni2MnAl Heusler alloys

The structural and magnetic properties of stoichiometric Ni2MnAl are studied to clarify the conditions for ferromagnetic and antiferromagnetic ordering claimed to occur in this compound. X-ray and magnetization measurements show that although a single phase B2 structure can be stabilized at room temperature, a single L21 phase is not readily stabilized, but rather a mixed L21+B2 state occurs. The mixed state incorporates ferromagnetic and antiferromagnetic parts for which close-lying Curie and a Néel temperatures can be identified from magnetization measurements.

Magnetoelastic behavior of the Heusler Ni2MnGa alloy

In this work the effect of the interplay between magnetic and structural degrees of freedom in the structural transitions undergone by Ni2MnGa alloy is investigated. Elastic constant and magnetic susceptibility measurements in a magnetic field are presented. A simple phenomenological model is proposed to account for the experimental observations.

Exact temporal evolution for some non-linear diffusion process

Exact solutions to FokkerPlanck equations with nonlinear drift are considered. Applications of these exact solutions for concrete models are studied. We arrive at the conclusion that for certain drifts we obtain divergent moments (and infinite relaxation time) if the diffusion process can be extended without any obstacle to the whole space. But if we introduce a potential barrier that limits the diffusion process, moments converge with a finite relaxation time.

Variational localized-site cluster expansions. X. Dimerization in linear Heisenberg chains

Ground-state instability to bond alternation in long linear chains is considered from the point of view of valence-bond (VB) theory. This instability is viewed as the consequence of a long-range order (LRO) which is expected if the ground state is reasonably described in terms of the Kekulé states (with nearest-neighbor singlet pairing). It is argued that the bond alternation and associated LRO predicted by this simple, VB picture is retained for certain linear Heisenberg models; many-body VB calculations on spin s=1 / 2 and s=1 chains are carried out in a test of this argument.

To select or to weigh: a comparative study of linear combination schemes for superparent-one-dependence estimators

We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.

Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.