Analysis of optical surfaces by means of surface plasmonspectroscopy

The sensitivity to material parameters of surface plasmon oscillations is explored for the design of a prototype system operating at a wavelength of 670 nm, for the simultaneous determination of thickness, complex permittivity and surface roughness of metal films. The apparatus was employed for characterization of gold and silver films with thicknesses within the 10-100 nm range. Thickness data measured with the prototype system were well correlated with those measured on a conventional surface profilometer. The Fourier spectrum of surface irregularities extracted from scattered light, enhanced by surface plasmon oscillations, was used to determine surface roughness parameters for the distinct samples. Those parameters were shown to be representative of typical surface structures observed with the atomic force microscope     

TGF-beta-induced apoptosis of cerebellar granule neurons is prevented by depolarization

The regulation of programmed cell death in the developing nervous system involves target-derived survival factors, afferent synaptic activity, and hormone- and cytokine-dependent signaling. Cultured immature cerebellar granule neurons die by apoptosis within several days in vitro unless maintained in depolarizing (high) concentrations of potassium (25 mM K+). Here we report that transforming growth factors (TGF)-beta1, -beta2, and -beta3 accelerate apoptosis of these neurons when maintained in physiological (low) K+ medium (5mM K+) as assessed by measures of viability, quantitative DNA fragmentation, and nuclear morphology. TGF-beta-induced apoptosis of these neurons is not blocked by CNTF and LIF, cytokines that enhance neuronal survival when applied alone, or by IGF-I, which prevents apoptosis upon potassium withdrawal. In contrast, neurons that differentiate in high K+ medium for several days in vitro acquire resistance to TGF-beta-mediated cell death. Granule neurons maintained in either low or high K+ medium produce latent, but not bioactive, TGF-beta1 and -beta2. Because neutralizing TGF-beta antibodies fail to augment survival of low K+ neurons, the cerebellar neurons are apparently unable to activate latent TGF-beta. Thus, apoptosis of low K+ neurons is not attributable to endogenous production of TGF-beta. Taken together, our data suggest that TGF-beta may limit the expansion of postmitotic neuronal precursor populations by promoting their apoptosis but may support survival of those neurons that have maturated, differentiated, and established supportive synaptic connectivity.     

An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping

Journal of Scheduling - Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in...     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

A structural linearization principle for processes

In [11], an induction principle for processes was given which allows one to apply model-checking techniques to parameterized families of processes. A limitation of the induction principle is that it does not apply to the case in which one process depends directly upon a parameterized number of processes, which grows without bound. This would seem to preclude its application to families ofN processes interconnected in a star topology. Nonetheless, we show that if the dependency can be computed incrementally, then the direct dependency upon the parameterized number of processes may be re-expressed recursively in terms of a linear cascade of processes, yielding in effect a linearization of the inter-process dependencies and allowing the induction principle to apply.A previous version of this paper appears in the Proceedings of CAV 1993 (LNCS 697).     

Minimally invasive cardiac surgery

In a short period of time, tremendous progress has been made in the field of minimally invasive cardiac surgery. The goal of true "minimally invasive" cardiac surgery should be a totally thoracoscopic or transvascular procedure that allows a very short hospital stay and prompt patient recovery at acceptable costs. To accomplish this goal, efforts to miniaturize and refine instrumentation/cannulae/visualization and the development of innovative new techniques must be pursued. The concept of performing intracardiac repair of a variety of pathologies on the beating heart is under investigation and will require a new generation of technology, which will include through-blood imaging, such as blood displacement videoscopes, and task-specific instruments. Robotics may offer additional assistance in the performance of complex and fine maneuvers.     

Context‐Dependent Crowd Evaluation

Many times, even if a crowd simulation looks good in general, there could be some specific individual behaviors which do not seem correct. Spotting such problems manually can become tedious, but ignoring them may harm the simulation's credibility. In this paper we present a data‐driven approach for evaluating the behaviors of individuals within a simulated crowd. Based on video‐footage of a real crowd, a database of behavior examples is generated. Given a simulation of a crowd, an analog analysis is performed on it, defining a set of queries, which are matched by a similarity function to the database examples. The results offer a possible objective answer to the question of how similar are the simulated individual behaviors to real observed behaviors. Moreover, by changing the video input one can change the context of evaluation. We show several examples of evaluating simulated crowds produced using different techniques and comprising of dense crowds, sparse crowds and flocks.     

A new fast prototype selection method based on clustering

In supervised classification, a training set T is given to a classifier for classifying new prototypes. In practice, not all information in T is useful for classifiers, therefore, it is convenient to discard irrelevant prototypes from T. This process is known as prototype selection, which is an important task for classifiers since through this process the time for classification or training could be reduced. In this work, we propose a new fast prototype selection method for large datasets, based on clustering, which selects border prototypes and some interior prototypes. Experimental results showing the performance of our method and comparing accuracy and runtimes against other prototype selection methods are reported.     

Impact of orthorectification and spatial sampling on maximum NDVI composite data in mountain regions

Topography and accuracy of image geometric registration significantly affect the quality of satellite data, since pixels are displaced depending on surface elevation and viewing geometry. This effect should be corrected for through the process of accurate image navigation and orthorectification in order to meet the geolocation accuracy for systematic observations specified by the Global Climate Observing System (GCOS) requirements for satellite climate data records. We investigated the impact of orthorectification on the accuracy of maximum Normalized Difference Vegetation Index (NDVI) composite data for a mountain region in north-western Canada at various spatial resolutions (1 km, 4 km, 5 km, and 8 km). Data from AVHRR on board NOAA-11 (1989 and 1990) and NOAA-16 (2001, 2002, and 2003) processed using a system called CAPS (Canadian AVHRR Processing System) for the month of August were considered. Results demonstrate the significant impact of orthorectification on the quality of composite NDVI data in mountainous terrain. Differences between orthorectified and non-orthorectified NDVI composites (ΔNDVI) adopted both large positive and negative values, with the 1% and 99% percentiles of ΔNDVI at 1 km resolution spanning values between − 0.16 < ΔNDVI < 0.09. Differences were generally reduced to smaller numbers for coarser resolution data, but systematic positive biases for non-orthorectified composites were obtained at all spatial resolutions, ranging from 0.02 (1 km) to 0.004 (8 km). Analyzing the power spectra of maximum NDVI composites at 1 km resolution, large differences between orthorectified and non-orthorectified AVHRR data were identified at spatial scales between 4 km and 10 km. Validation of NOAA-16 AVHRR NDVI with MODIS NDVI composites revealed higher correlation coefficients (by up to 0.1) for orthorectified composites relative to the non-orthorectified case. Uncertainties due to the AVHRR Global Area Coverage (GAC) sampling scheme introduce an average positive bias of 0.02 ± 0.03 at maximum NDVI composite level that translates into an average relative bias of 10.6% ± 19.1 for sparsely vegetated mountain regions. This can at least partially explain the systematic average positive biases we observed relative to our results in AVHRR GAC-based composites from the Global Inventory Modeling and Mapping Studies (GIMMS) and Polar Pathfinder (PPF) datasets (0.19 and 0.05, respectively). With regard to the generation of AVHRR long-term climate data records, results suggest that orthorectification should be an integral part of AVHRR pre-processing, since neglecting the terrain displacement effect may lead to important biases and additional noise in time series at various spatial scales.