An integrated modeling approach to predict flooding on urban basin.

Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.     

Thin-film ferroelectrics of PZT of sol-gel processing

The ferroelectric effect has been demonstrated for sol-gel derived lead zirconate titanate (PZT) (53/47) thin films. The respective values of coercive field and remanent polarization were 4x10(6) V/m and 0.36 C/m(2). The thin-film fabrication process is simple and compatible with Si planar technology, and offers a wide variety of potential uses for counting, memory, and integrated optical circuit applications.     

Electrohydrodynamic‐Induced SERS Immunoassay for Extensive Multiplexed Biomarker Sensing

Cancer diagnosis and patient monitoring require sensitive and simultaneous measurement of multiple cancer biomarkers considering that single biomarker analysis present inadequate information on the underlying biological transformations. Thus, development of sensitive and selective assays for multiple biomarker detection might improve clinical diagnosis and expedite the treatment process. Herein, a microfluidic platform for the rapid, sensitive, and parallel detection of multiple cancer‐specific protein biomarkers from complex biological samples is presented. This approach utilizes alternating current electrohydrodynamic‐induced surface shear forces that provide exquisite control over fluid flow thereby enhancing target–sensor interactions and minimizing non‐specific binding. Further, the use of surface‐enhanced Raman scattering‐based spectral encoding with individual barcodes for different targets enables specific and simultaneous detection of captured protein biomarkers. Using this approach, the specific and sensitive detection of clinically relevant biomarkers including human epidermal growth factor receptor 2 (HER2); Mucin 1, cell surface associated (MUC1); epidermal growth factor receptor; and Mucin 16, cell surface associated (MUC16) at concentrations as low as 10 fg mL^?1 in patient serum is demonstrated. Successful target detection from patient samples further demonstrates the potential of this current approach for the clinical diagnosis, which envisages a clinical translation for a rapid and sensitive appraisal of clinical samples in cancer diagnostics.     

Optimizing spatiotemporal sensors placement for nutrient monitoring: a stochastic optimization framework

Nutrient monitoring is very important for the area of food–energy–water nexus. The sensor network for nutrient monitoring requires dynamic sensing where the positions of the sensors change with time. In this work, we have proposed a methodology to optimize a dynamic sensor network which can address the spatiotemporal aspect of nutrient movement in a watershed. This is a first paper in the series where an algorithmic and methodological framework for spatiotemporal sensor placement problem is proposed. Dynamic sensing is widely used in wireless sensors, and the current approaches to solving this problem are data intensive. This is the first time we are introducing a stochastic optimization approach to dynamic sensing which is efficient. This framework is based on a novel stochastic optimization algorithm called Better Optimization of Nonlinear Uncertain Systems (BONUS). A small case study of the dynamic sensor placement problem is presented to illustrate the approach. In the second paper of this series, we will present a detailed case study of nutrient monitoring in a watershed.     

Amplification‐Free Multi‐RNA‐Type Profiling for Cancer Risk Stratification via Alternating Current Electrohydrodynamic Nanomixing

Simultaneous analysis of messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA)—multi‐RNA‐type profiling—is increasingly crucial in cancer diagnostics. Yet, rapid multi‐RNA‐type profiling is challenging due to enzymatic amplification reliance and RNA‐type‐dependent characteristics. Here, a nanodevice is reported to uniquely use alterable alternating current electrohydrodynamic (ac‐EHD) forces to enhance probe–target hybridization prior to direct native RNA target detection, without target amplification or surface functionalization. To exemplify clinical applicability, noninvasive screening of next‐generation prostate cancer (PCa) RNA biomarkers (of different types) in patient urine samples is performed. A strong correlation between multi‐RNA‐type expression and aggressive PCa is found, and the nanodevice performance is statistically evaluated. It is believed that this miniaturized system exhibits great potential for cancer risk stratification via multi‐RNA‐type profiling.     

Smooth anisotropic sources with application to three-dimensional surface mesh generation

Isotropic sources are extended to take anisotropy into account in order to obtain a smooth anisotropic sizing field for anisotropic mesh generation. Different types of anisotropic sources are described to represent boundary layers on surfaces and in volume that guarantee a smooth anisotropic field. This allows to us resolve multiple boundary layer intersections properly and naturally provides a smooth transition between the anisotropic boundary layer sizing and the isotropic region. Furthermore, the interaction between a smooth anisotropic sizing field and curvature is studied, and estimates of the tangential size spacing are provided for first and second order approximation of the geometry to ensure smoothness of the sizing field. It is also shown that, in order to get a smooth size variation, volumetric and surface meshing can not be decoupled. The filtering of the sources in order to obtain a computationally efficient method is described. Numerical examples demonstrate our method.     

An explicit predictor-corrector solver with application to seismic wave modelling

Wave-equation-based forward modelling using explicit finite-difference methods is a standard technique for calculating synthetic seismograms. The stability criterion restricts the size of the time step. In this paper a predictor–corrector method for solving the wave equation is described which allows the use of a larger time step. A stability analysis of the method is also carried out. Parallel implementation of the algorithm is described for a distributed computing environment which makes use of MPI and PVM message passing calls for communication between processors.     

Using a soft core in a SoC design: experiences with picoJava

Through our experience in synthesis, validation, test, and integration of the picoJava processor core in a system-on-chip (SoC) design we point out the challenges faced and issues to address in efficient reuse of a soft core     

On Kalman filtering over fading wireless channels with controlled transmission powers

We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.     

A parallel hp‐FEM infrastructure for three‐dimensional structural acoustics

This paper describes a parallel three‐dimensional numerical infrastructure for the solution of a wide range of time‐harmonic problems in structural acoustics and vibration. High accuracy and rate of error‐convergence, in the mid‐frequency regime,is achieved by the use of hp‐finite and infinite element approximations. The infrastructure supports parallel computation in both single and multi‐frequency settings. Multi‐frequency solves utilize concurrent factoring of the frequency‐dependent linear algebraic systems and are naturally scalable. Scalability of large‐scale single‐frequency problems is realized by using FETI‐DP—an iterative domain‐decomposition scheme. Numerical examples are presented to cover applications in vibratory response of fluid‐filled elastic structures as well as radiation and scattering from elastic structures submerged in an infinite acoustic medium. We demonstrate both the numerical accuracy as well as parallel scalability of the infrastructure in terms of problem parameters that include wavenumber and number of frequencies, polynomial degree of finite/infinite element approximations as well as the number of processors. Scalability and accuracy is evaluated for both single and multiple frequency sweeps on four high‐performance parallel computing platforms: SGI Altix, SGI Origin, IBM p690 SP and Linux‐cluster. Results show good performance on shared as well as distributed‐memory architecture. Copyright © 2006 John Wiley & Sons, Ltd.