Graph Spectral Image Processing

Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2D grid, if one can design an appropriate underlying graph connecting pixels with weights that reflect the image structure, then one can interpret the image (or image patch) as a signal on a graph, and apply GSP tools for processing and analysis of the signal in graph spectral domain. In this article, we overview recent graph spectral techniques in GSP specifically for image / video processing. The topics covered include image compression, image restoration, image filtering and image segmentation

Investment and Growth in Rich and Poor Countries

This paper revisits the association between investment and growth. The empirical findings highlight substantial heterogeneity for the effect of investment on growth and suggest a possible negative association. Results based on a battery of cross-sectional and time-series regressions show that the link between investment and growth has weakened over time and that investment in high-income countries is more likely to have a negative effect on growth. The adverse effect for high-income countries appears to have increased over time. An implication is that uphill capital flows could be associated with negative or zero returns. The result is robust to the presence of control variables that are commonly included in growth studies.

Vocal learning promotes patterned inhibitory connectivity.

Skill learning is instantiated by changes to functional connectivity within premotor circuits, but whether the specificity of learning depends on structured changes to inhibitory circuitry remains unclear. We used slice electrophysiology to measure connectivity changes associated with song learning in the avian analog of primary motor cortex (robust nucleus of the arcopallium, RA) in Bengalese Finches. Before song learning, fast-spiking interneurons (FSIs) densely innervated glutamatergic projection neurons (PNs) with apparently random connectivity. After learning, there was a profound reduction in the overall strength and number of inhibitory connections, but this was accompanied by a more than two-fold enrichment in reciprocal FSI-PN connections. Moreover, in singing birds, we found that pharmacological manipulations of RA's inhibitory circuitry drove large shifts in learned vocal features, such as pitch and amplitude, without grossly disrupting the song. Our results indicate that skill learning establishes nonrandom inhibitory connectivity, and implicates this patterning in encoding specific features of learned movements

Dissecting the PPP Puzzle: The Unconventional Roles of Nominal Exchange Rate and Price Adjustment

The conventional view, as expounded by sticky-price models, is that price adjustment determines the PPP reversion rate. This study examines the mechanism by which PPP deviations are corrected. Nominal exchange rate adjustment, not price adjustment, is shown to be the key engine governing the speed of PPP convergence. Moreover, nominal exchange rates are found to converge much more slowly than prices. With the reversion being driven primarily by nominal exchange rates, real exchange rates also revert at a slower rate than prices, as identified by the PPP puzzle (Rogoff, 1996).

WSC-07: Evolving the Web Services Challenge

Service-oriented architecture (SOA) is an evolving architectural paradigm where businesses can expose their capabilities as modular, network-accessible software services. By decomposing capabilities into modular services, organizations can share their offerings at multiple levels of granularity while also creating unique access points for their peer organizations. The true impact of SOA will be realized when 3rd party organizations can obtain a variety of services, on-demand, and create higher-order composite business processes. The Web Services Challenge (WSC) is a forum where academic and industry researchers can share experiences of developing tools that automate the integration of web services. In the third year (i.e. WSC-07) of the Web Services Challenge, software platforms will address several new composition challenges. Requests and results will be transmitted within SOAP messages. In addition, semantic representations will be both represented in the eXtensible Markup Language (XML) and in the Web Ontology Language (OWL). Finally, composite processes will have both sequential and concurrent branches

W-band waveguide-packaged InP HEMT reflection grid amplifier

This letter presents a 79-GHz broadband reflection-type grid amplifier using spatial power combining to combine the power of 64 unit cells. Each unit cell uses a two-stage cascade configuration with InP HEMTs arranged as a differential pair. A broadband orthogonal mode transducer (OMT) separates two orthogonally polarized input and output signals over a 75 to 85GHz range. In conjunction with the OMT, a mode converter with quadruple-ridged apertures was designed to enhance the field uniformity over the active grid. Measurements show 5-dB small signal gain at 79GHz and an 800-MHz 3-dB bandwidth. The amplifier generates an output power of 264mW with little evidence of saturation

Using molecular mechanics to predict bulk material properties of fibronectin fibers

The structural proteins of the extracellular matrix (ECM) form fibers with finely tuned mechanical properties matched to the time scales of cell traction forces. Several proteins such as fibronectin (Fn) and fibrin undergo molecular conformational changes that extend the proteins and are believed to be a major contributor to the extensibility of bulk fibers. The dynamics of these conformational changes have been thoroughly explored since the advent of single molecule force spectroscopy and molecular dynamics simulations but remarkably, these data have not been rigorously applied to the understanding of the time dependent mechanics of bulk ECM fibers. Using measurements of protein density within fibers, we have examined the influence of dynamic molecular conformational changes and the intermolecular arrangement of Fn within fibers on the bulk mechanical properties of Fn fibers. Fibers were simulated as molecular strands with architectures that promote either equal or disparate molecular loading under conditions of constant extension rate. Measurements of protein concentration within micron scale fibers using deep ultraviolet transmission microscopy allowed the simulations to be scaled appropriately for comparison to in vitro measurements of fiber mechanics as well as providing estimates of fiber porosity and water content, suggesting Fn fibers are approximately 75% solute. Comparing the properties predicted by single molecule measurements to in vitro measurements of Fn fibers showed that domain unfolding is sufficient to predict the high extensibility and nonlinear stiffness of Fn fibers with surprising accuracy, with disparately loaded fibers providing the best fit to experiment. This work shows the promise of this microstructural modeling approach for understanding Fn fiber properties, which is generally applicable to other ECM fibers, and could be further expanded to tissue scale by incorporating these simulated fibers into three dimensional network models

Brief inactivation of c-Myc is not sufficient for sustained regression of c-Myc-induced tumours of pancreatic islets and skin epidermis

Background Tumour regression observed in many conditional mouse models following oncogene inactivation provides the impetus to develop, and a platform to preclinically evaluate, novel therapeutics to inactivate specific oncogenes. Inactivating single oncogenes, such as c-Myc, can reverse even advanced tumours. Intriguingly, transient c-Myc inactivation proved sufficient for sustained osteosarcoma regression; the resulting osteocyte differentiation potentially explaining loss of c-Myc's oncogenic properties. But would this apply to other tumours? Results We show that brief inactivation of c-Myc does not sustain tumour regression in two distinct tissue types; tumour cells in pancreatic islets and skin epidermis continue to avoid apoptosis after c-Myc reactivation, by virtue of Bcl-xL over-expression or a favourable microenvironment, respectively. Moreover, tumours progress despite reacquiring a differentiated phenotype and partial loss of vasculature during c-Myc inactivation. Interestingly, reactivating c-Myc in β-cell tumours appears to result not only in further growth of the tumour, but also re-expansion of the accompanying angiogenesis and more pronounced β-cell invasion (adenocarcinoma). Conclusions Given that transient c-Myc inactivation could under some circumstances produce sustained tumour regression, the possible application of this potentially less toxic strategy in treating other tumours has been suggested. We show that brief inactivation of c-Myc fails to sustain tumour regression in two distinct models of tumourigenesis: pancreatic islets and skin epidermis. These findings challenge the potential for cancer therapies aimed at transient oncogene inactivation, at least under those circumstances where tumour cell differentiation and alteration of epigenetic context fail to reinstate apoptosis. Together, these results suggest that treatment schedules will need to be informed by knowledge of the molecular basis and environmental context of any given cancer