Fast restoration of ATM networks

Asynchronous transfer mode (ATM) is now well recognized as the fundamental switching and multiplexing technique for future broadband ISDN. As these networks will be increasingly relied upon for providing a multitude of integrated voice, data, and video services, network reliability is a key concern. There are several intrinsic features of ATM networks that could potentially be exploited to provide improved restoration techniques, beyond those established for synchronous transfer mode (STM) networks, such as digital cross-connect restoration or self-healing rings. These features include ATM cell level error detection, inherent rate adaptation and nonhierarchical multiplexing. The authors explore the use of these features in developing fast restoration strategies for ATM networks. In particular, they address: (1) ATM error detection capabilities for enhanced failure detection, (2) network rerouting strategies, (3) spare capacity allocation, and (4) network control architecture and related implementation aspects. Their findings suggest that fast network span failure detection and bandwidth-efficient rerouting capabilities can be combined to develop restoration strategies for ATM networks with significantly greater performance-cost ratios when compared to existing STM network restoration strategies     

Angiotensin II receptor type 1 mRNA is upregulated in atria of patients with end-stage heart failure

There is increasing evidence that pathological changes in the myocardium during chronic heart failure (CHF) are partly regulated through the activation of the renin-angiotensin system (RAS), an effect mediated by the angiotensin II type 1 receptor (AT1R). We examined the expression of cardiac AT1R mRNA in normal (atria, n=7; ventricle, n=3) and end-stage CHF human hearts (atria, n=8; ventricle, n=14). Tissue was snap-frozen immediately after explantation during orthotopic cardiac transplantation; control specimens were obtained from healthy donor hearts rejected for technical reasons. Northern blots of purified total mRNA from each tissue were hybridized with a random primed radiolabeled probe for the coding sequence of AT1R. Stringent conditions were used for both hybridization (5X SSC, 65 degrees C) and washing (0.5X SSC, 0.1% SDS, 65 degrees C) of the membrane. Left and right atrial tissue showed low levels of AT1R mRNA expression in the controls, with statistically significant upregulation of expression in tissue from pathological hearts; CHF atria 1.28+/-0.86 optical density (OD) units, control atria 0.56+/-0.31 OD units, P=0.05 (mean+/-s.d.). There were undetectable levels in ventricles from either control (2/2) or dilated hearts (7/7). The results were independent of the etiology of the heart failure and suggest that increased levels of atrial AT1R mRNA may occur in response to elevated atrial pressures in heart failure.     

Monte Carlo simulation of grain growth and recrystallization in polycrystalline materials

The prediction and control of metal grain structures during processing have been major objectives of materials science. However, methodologies that are accurate and can be easily generalized to a variety of processing conditions have been difficult to formulate due to the complexity of the grain interactions. A novel Monte Carlo-based approach that explicitly incorporates these interactions has been developed to simulate the microstructural evolution driven by the minimization of grain boundary energy and lattice defect density. The applicability of this procedure has been demonstrated by the good correspondence between simulation results and experimental observations. This article reviews recent advances in the application of this technique to the investigation of a variety of phenomena, including normal and abnormal grain growth as well as static and dynamic recrystallization.     

Forming the optimal union of multiple databases

Many organizations, best illustrated by libraries, have access to hundreds of databases possessing varying degrees of complimentary and overlapping records. While users may receive positive marginal benefits from data duplications, all databases and their services cannot be supported because of resource limitations. This paper attempts to conceptualize the problem of database collection in an environment of multiple databases, with differential content and performance characteristics, diverse users, and limited resources. It defines the database collection problem as a constrained zero-one integer programming problem and solves for the optimal combination or union of databases. Several extensions are shown, where special conditions are imposed on the relationships between databases and/or their availability.     

Improved Poisson intensity estimation: denoising application using Poisson data

Recently, Timmermann and Nowak developed algorithms for estimating the means of independent Poisson random variables. The algorithms are based on a multiscale model where certain random variables are assumed to obey a beta-mixture density function. Timmermann and Nowak simplify the density estimation problem by assuming the beta parameters are known and only one mixture parameter is unknown. They use the observed data and the method of moments to estimate the unknown mixture parameter. Taking a different approach, we generate training data from the observed data and compute maximum likelihood estimates of all of the beta-mixture parameters. To assess the improved performance obtained by the proposed modification, we consider a denoising application using Poisson data.     

Suppression of void coalescence in thermal aging of tin-silver-copper-X solder joints

Addressing the potential for drop impact failure of Pb-free interconnects, the shear ductility after extensive aging of Sn-Ag-Cu (SAC) solders has been improved radically by Co or Fe modifications. Several other SAC+X candidates (X=Mn, Ni, Ge, Ti, Si, Cr, and Zn) now have been tested. Solder joint microstructures and shear strength results show that new SAC+X alloys also suppress void formation and coalescence at the Cu (substrate)/Cu₃Sn interface (and embrittlement) after aging at 150°C for up to 1,000 h. Microprobe measurements of 1,000 h aged samples suggest that Cu substitution by X is usually accentuated in the intermetallic layers, consistent with X=Co and Fe results.     

Embedded micromachined fiber-optic Fabry-Perot pressure sensors in aerodynamics applications

Small size, high bandwidth pressure sensors are required for instrumentation of probes and test models in aerodynamic studies of complex unsteady flows. Optical-fiber pressure sensors promise potential advantages of small size and low cost in comparison with their electrical counterparts. We describe miniature Fabry-Perot cavity pressure sensors constructed by micromachining techniques in a turbine test application. The sensor bodies are 500 /spl mu/m squared, 300 /spl mu/m deep with a /spl sim/2 /spl mu/m-thick copper diaphragm electroplated on one face. The sensor cavity is formed between the diaphragm and the cleaved end of a single mode fiber sealed to the sensor by epoxy. Each sensor is addressed interferometrically in reflection by three wavelengths simultaneously, giving an unambiguous phase determination; a pressure sensitivity of 1.6 radbar/sup -1/ was measured, with a typical range of vacuum to 600 kPa. Five sensors were embedded in the trailing edge of a nozzle guide vane installed upstream of a rotor in a full-scale turbine stage transient test facility. Pressure signals in the trailing edge flow show marked structure at the 8 kHz blade passing frequency. To our knowledge, this is the first report of sensors located at the trailing edge of a normal-sized turbine blade.     

Linear and nonlinear methods for brain-computer interfaces

At the recent Second International Meeting on Brain-Computer Interfaces (BCIs) held in June 2002 in Rensselaerville, NY, a formal debate was held on the pros and cons of linear and nonlinear methods in BCI research. Specific examples applying EEG data sets to linear and nonlinear methods are given and an overview of the various pros and cons of each approach is summarized. Overall, it was agreed that simplicity is generally best and, therefore, the use of linear methods is recommended wherever possible. It was also agreed that nonlinear methods in some applications can provide better results, particularly with complex and/or other very large data sets.