Transient shear banding in time-dependent fluids

We study the dynamics of shear-band formation and evolution using a simple rheological model. The description couples the local structure and viscosity to the applied shear stress. We consider in detail the Couette geometry, where the model is solved iteratively with the Navier-Stokes equation to obtain the time evolution of the local velocity and viscosity fields. It is found that the underlying reason for dynamic effects is the nonhomogeneous shear distribution, which is amplified due to a positive feedback between the flow field and the viscosity response of the shear thinning fluid. This offers a simple explanation for the recent observations of transient shear banding in time-dependent fluids. Extensions to more complicated rheological systems are considered.

Characterization of Mechanically Alloyed Nanocrystalline Fe(Al): Crystallite Size and Dislocation Density

A nanostructured disordered Fe(Al) solid solution was obtained from elemental powders of Fe and Al using a high-energy ball mill. The transformations occurring in the material during milling were studied with the use of X-ray diffraction. In addition lattice microstrain, average crystallite size, dislocation density, and the lattice parameter were determined. Scanning electron microscopy (SEM) was employed to examine the morphology of the samples as a function of milling times. Thermal behaviour of the milled powders was examined by differential scanning calorimetry (DSC). The results, as well as dissimilarity between calorimetric curves of the powders after 2 and 20 h of milling, indicated the formation of a nanostructured Fe(Al) solid solution

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Ultralow-density nanocage-based metal-oxide polymorphs

For two important metal oxides (MO, M=Mg, Zn) we predict, via accurate electronic structure calculations, that new low-density nanoporous crystalline phases may be accessible via the coalescence of nanocluster building blocks. Specifically, we consider the assembly of cagelike (MO)12 clusters exhibiting particularly high gas phase stability, leading to new polymorphs with energetic stabilities rivaling (and sometimes higher) than those of known MO polymorphs.

Fragmentation of massive dense cores down to <~ 1000 AU: relation between fragmentation and density structure

In order to shed light on the main physical processes controlling fragmentation of massive dense cores, we present a uniform study of the density structure of 19 massive dense cores, selected to be at similar evolutionary stages, for which their relative fragmentation level was assessed in a previous work. We inferred the density structure of the 19 cores through a simultaneous fit of the radial intensity profiles at 450 and 850 μm (or 1.2 mm in two cases) and the spectral energy distribution, assuming spherical symmetry and that the density and temperature of the cores decrease with radius following power-laws. Even though the estimated fragmentation level is strictly speaking a lower limit, its relative value is significant and several trends could be explored with our data. We find a weak (inverse) trend of fragmentation level and density power-law index, with steeper density profiles tending to show lower fragmentation, and vice versa. In addition, we find a trend of fragmentation increasing with density within a given radius, which arises from a combination of flat density profile and high central density and is consistent with Jeans fragmentation. We considered the effects of rotational-to-gravitational energy ratio, non-thermal velocity dispersion, and turbulence mode on the density structure of the cores, and found that compressive turbulence seems to yield higher central densities. Finally, a possible explanation for the origin of cores with concentrated density profiles, which are the cores showing no fragmentation, could be related with a strong magnetic field, consistent with the outcome of radiation magnetohydrodynamic simulations.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Is contextual-potentiated eating dependent on caloric density of food?

One experiment tested whether a specific context could elicit eating in rats as a result of Pavlovian conditioning and whether this effect depended on the caloric density of food. Thirty two deprived rats experienced two contexts. They had access to food in context A, but no food was available in context B. During conditioning, half of the animals received high density caloric food (HD groups) whereas the other half, low density caloric food (LD groups). Then, half of the rats in each type of food group was tested in context A and the other half in context B. The results demonstrated an effect of context conditioning only in HD groups. These findings suggest the relevance of both contextual conditioning and caloric density of food in eating behaviour. Implications for the aetiology of binge eating will be discussed.