On the two classes of global primary modal instability in laminar separation bubbles

The self-excited global instability mechanisms existing in flat-plate laminar separation bubbles are studied here, in order to shed light on the causes of unsteadiness and three- dimensionality of unforced, nominally two-dimensional separated flows. The presence of two known linear global mechanisms, namely an oscillator behavior driven by local regions of absolute inflectional instability and a centrifugal instability giving rise to a steady three- dimensionalization of the bubble, is studied in a series of model separation bubbles. Present results indicate that absolute instability, and consequently a global oscillator behavior, does not exist for two-dimensional bubbles with a peak reversed-flow velocity below 12% of the free-stream velocity. However, the three-dimensional instability becomes active for recirculation levels as low as urev ≈ 7%. These findings suggest a route to the three-dimensionality and unsteadiness observed in experiments and simulations substantially different from that usually found in the literature, in which two-dimensional vortex shedding is followed by three-dimensionalization.

A global assessment of manufacturing: Economic development, energy use, carbon emissions, and the potential for energy efficiency and materials recycling

We present in two parts an assessment of global manufacturing. In the first part, we review economic development, pollution, and carbon emissions from a country perspective, tracking the rise of China and other developing countries. The results show not only a rise in the economic fortunes of the newly industrializing nations, but also a significant rise in global pollution, particularly air pollution and CO2 emissions largely from coal use, which alter and even reverse previous global trends. In the second part, we change perspective and quantitatively evaluate two important technical strategies to reduce pollution and carbon emissions: energy efficiency and materials recycling. We subdivide the manufacturing sector on the basis of the five major subsectors that dominate energy use and carbon emissions: (a) iron and steel, (b) cement, (c) plastics, (d) paper, and (e) aluminum. The analysis identifies technical constraints on these strategies, but by combined and aggressive action, industry should be able to balance increases in demand with these technical improvements. The result would be high but relatively flat energy use and carbon emissions. The review closes by demonstrating the consequences of extrapolating trends in production and carbon emissions and suggesting two options for further environmental improvements, materials efficiency, and demand reduction. © 2013 by Annual Reviews. All rights reserved.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

An exploration of risk management in global industrial investment

This article explores risk management in global industrial investment by identifying linkages and gaps between theories and practices. It identifies opportunities for further development of the field. Three related bodies of literature have been reviewed: risk management, global manufacturing and investment. The review suggests that risk management in global manufacturing is overlooked in the literature; that existing theoretical risk management processes are not well developed in the global manufacturing context and that the investment literature applies mainly to financial risk assessment rather than investment risk management structures. Further, there appears to be a serious lack of systematic industrial risk management in investment decision making. This article highlights the opportunities to deploy current good practices more effectively as well as the need to develop more robust theories of industrial investment risk management. The approach adopted to investigate this multidisciplinary topic included a historical review of literature to understand the diverse background of theoretical development. A case study research approach was adopted to collect data, involving four global manufacturing companies and one risk management advisory company to observe the patterns and rationale of current practices. Supporting arguments from secondary data sources reinforced the findings. The research focuses risk management in global industrial investment. It links theories with practice to understand the existing knowledge gap and proposes key research themes for further research. © 2013 Macmillan Publishers Ltd. 1460-3799 Risk Management.

Low-rank optimization with trace norm penalty

The paper addresses the problem of low-rank trace norm minimization. We propose an algorithm that alternates between fixed-rank optimization and rank-one updates. The fixed-rank optimization is characterized by an efficient factorization that makes the trace norm differentiable in the search space and the computation of duality gap numerically tractable. The search space is nonlinear but is equipped with a Riemannian structure that leads to efficient computations. We present a second-order trust-region algorithm with a guaranteed quadratic rate of convergence. Overall, the proposed optimization scheme converges superlinearly to the global solution while maintaining complexity that is linear in the number of rows and columns of the matrix. To compute a set of solutions efficiently for a grid of regularization parameters we propose a predictor-corrector approach that outperforms the naive warm-restart approach on the fixed-rank quotient manifold. The performance of the proposed algorithm is illustrated on problems of low-rank matrix completion and multivariate linear regression. © 2013 Society for Industrial and Applied Mathematics.

Zebrafish eaf1 and eaf2/u19 Mediate Effective Convergence and Extension Movements through the Maintenance of wnt11 and wnt5 Expression

Studies have attributed several functions to the Eaf family, including tumor suppression and eye development. Given the potential association between cancer and development, we set forth to explore Eaf1 and Eaf2/U19 activity in vertebrate embryogenesis, using zebrafish. In situ hybridization revealed similar eaf1 and eaf2/u19 expression patterns. Morpholino-mediated knockdown of either eaf1 or eaf2/u19 expression produced similar morphological changes that could be reversed by ectopic expression of target or reciprocal-target mRNA. However, combination of Eaf1 and Eaf2/U19 (Eafs)-morpholinos increased the severity of defects, suggesting that Eaf1 and Eaf2/U19 only share some functional redundancy. The Eafs knockdown phenotype resembled that of embryos with defects in convergence and extension movements. Indeed, knockdown caused expression pattern changes for convergence and extension movement markers, whereas cell tracing experiments using kaeda mRNA showed a correlation between Eafs knockdown and cell migration defects. Cardiac and pancreatic differentiation markers revealed that Eafs knockdown also disrupted midline convergence of heart and pancreatic organ precursors. Noncanonical Wnt signaling plays a key role in both convergence and extension movements and midline convergence of organ precursors. We found that Eaf1 and Eaf2/U19 maintained expression levels of wnt11 and wnt5. Moreover, wnt11 or wnt5 mRNA partially rescued the convergence and extension movement defects occurring in eafs morphants. Wnt11 and Wnt5 converge on rhoA, so not surprisingly, rhoA mRNA more effectively rescued defects than either wnt11 or wnt5 mRNA alone. However, the ectopic expression of wnt11 and wnt5 did not affect eaf1 and eaf2/u19 expression. These data indicate that eaf1 and eaf2/u19 act upstream of noncanonical Wnt signaling to mediate convergence and extension movements.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.