The career indecision profile : measurement equivalence in two international samples

This study tested for the measurement equivalence of a four-factor measure of career indecision (Career Indecision Profile-65 [CIP-65]) between a U.S. sample and two international samples; one composed of French-speaking young adults from France and Switzerland and the other of Italian ado- lescents. Previous research had supported the four-factor structure of the CIP-65 in both the United States and Iceland but also showed that items on two of the four scales may be interpreted differently by young adults growing up in these two countries. This study extends previous research by testing whether the four CIP-65 factors are measured equivalently in two additional international samples. Results largely supported the configural and metric invariance of the CIP-65 in the United States and international samples, but several scales showed a lack of scalar invariance. Some explanations are offered for these findings along with suggestions for future research and implications for practice.

The neurochemical profile quantified by in vivo 1H NMR spectroscopy.

Proton NMR spectroscopy is emerging from translational and preclinical neuroscience research as an important tool for evidence based diagnosis and therapy monitoring. It provides biomarkers that offer fingerprints of neurological disorders even in cases where a lesion is not yet observed in MR images. The collection of molecules used as cerebral biomarkers that are detectable by (1)H NMR spectroscopy define the so-called "neurochemical profile". The non-invasive quality of this technique makes it suitable not only for diagnostic purposes but also for therapy monitoring paralleling an eventual neuroprotection. The application of (1)H NMR spectroscopy in basic and translational neuroscience research is discussed here.

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

Precision and scaling in morphogen gradient read-out.

Morphogen gradients infer cell fate as a function of cellular position. Experiments in Drosophila embryos have shown that the Bicoid (Bcd) gradient is precise and exhibits some degree of scaling. We present experimental results on the precision of Bcd target genes for embryos with a single, double or quadruple dose of bicoid demonstrating that precision is highest at mid-embryo and position dependent, rather than gene dependent. This confirms that the major contribution to precision is achieved already at the Bcd gradient formation. Modeling this dynamic process, we investigate precision for inter-embryo fluctuations in different parameters affecting gradient formation. Within our modeling framework, the observed precision can only be achieved by a transient Bcd profile. Studying different extensions of our modeling framework reveals that scaling is generally position dependent and decreases toward the posterior pole. Our measurements confirm this trend, indicating almost perfect scaling except for anterior most expression domains, which overcompensate fluctuations in embryo length.