Rectus abdominis muscle flap (RAMF) technique for the management of bladder exstrophies: late clinical outcome and urodynamic findings

OBJECTIVE: To investigate the efficacy of the rectus abdominis muscle flap (RAMF) technique for the closure and augmentation of small, non-compliant bladder exstrophies. PATIENTS AND METHODS: The RAMF technique was used in two girls and two boys (mean age at operation, 31.7 months, range 3-72) with bladder exstrophy. The clinical outcome and urodynamics were assessed during a follow-up of 29 months to 6 years (mean 49.2 months) and included imaging, cystoscopy, biochemical and microbiological studies. RESULTS: There were no urinary tract infections, metabolic problems or electrolyte disturbances and kidney function remained normal in all patients. Radiography confirmed intact function and anatomy of the urinary tract and cystoscopy showed complete coverage of the inner peritoneal layer of RAMF with uroepithelium. No stone formation or mucus production were detected. Currently, three patients void using clean intermittent catheterization through the native urethra and the fourth through an appendiceal Mitrofanoff valve. However, the bladder volume was insufficient at the late follow-up and three patients required bladder augmentation. CONCLUSIONS: The RAMF technique is a good alternative for closing bladder exstrophies and achieves an increase in bladder capacity; however, although there is a mild improvement in bladder capacity and compliance. RAMF should not be used as a bladder augmentation procedure. The technique is indicated in the closure of large bladder defects, bladder exstrophies with small, inelastic, non-compliant bladder remnants and failed primary closures.     

Frequency offset retrodirective antenna array

A new architecture for the Van Atta self-steering array is presented. Active antenna techniques are used to realise a compact self-steering array with enhanced retrodirective properties. The experimental performance of the array is demonstrated and a technique is described which compensates for the beam pointing error induced by antenna array element directivity     

Fast adders using enhanced multiple-output domino logic

Using an enhanced multiple output domino logic (EMODL) implementation of a carry lookahead adder (CLA), sums of several consecutive bits can be built in one nFET tree with a single carry-in. Based on this result, a new sparse carry chain architecture is proposed for the CLA adder. We demonstrate the design approach using a 32-b adder, and show that only four carries are sufficient for generating all sums, with a consequent reduction in the number of stage delays. Using a 1.2-μm CMOS technology, we verify our simulation procedures by fabrication and measurement of a 2.7 ns critical path     

Bufferless broadcasting: a low power distributed circuit techniquefor broadcasting 10-Gb/s chip input signals

Bufferless distributed circuit (BDC) broadcasting is proposed as a technique for broadcasting high-speed chip input signals to a series of on-chip destination cells as needed in crosspoint switch, parallel multiplier, distributed amplifier, etc., chip designs. In contrast with conventional techniques that use an on-chip buffer to assist broadcasting, BDC broadcasting offers the advantage of lower signal delay and power dissipation. In an experimental GaAs heterojunction bipolar transistor (HBT) 8×4 crosspoint switch assembly, BDC broadcasting was found to achieve a 40% power savings with little or no penalty in jitter or bit error rate performance at a 10-Gb/s data rate     

Optical imaging of anatomical maps derived from magnetic resonanceimages using time-independent optical sources

Presents a model suitable for computing images of absorption cross sections of thick tissue structures illuminated at near infrared (NIR) wavelengths from tomographic projection data. Image reconstruction is accomplished by solving a system of linear equations derived from transport theory. Reconstruction results using different algebraic solvers are shown for anatomical maps of the breast, derived from magnetic resonance imaging data, containing two simulated pathologies, in which case qualitatively good reconstructions were obtained. Evaluation of magnetic resonance (MR) data to optimize NIR optical tomographic imaging methods and to assess the feasibility of a combined MR-optical measurement scheme is discussed     

Optimum path planning using convex hull and local search heuristic algorithms

Whether in improving quality or productivity the impact of mechatronic systems such as robots in industry is unquestionable. One aspect of interest in robotics is planning the optimum path for a mobile robot or the optimum trajectory for link movements of a stationary robot in order to increase their efficiency. However, for a given set of points complete enumeration of all the possible paths to establish an optimal one is not feasible as the search space increases exponentially (explodes combinatorially) as the number of points increases. This problem, traditionally known as the “Traveling Salesman Problem” (TSP) has attracted a great deal of attention for a long time. Proven enumerative techniques such as “nearest neighbour algorithm”, “branch and bound”, “cutting planes”, and “dynamic programming” as well as approximation methods such as “tabu search”, “greedy algorithm”, “simulated annealing” and “genetic algorithm”, have had only a limited success in solving this problem. Recently “convex hull”, a minimum area and perimeter shape, has been used as an initial sub-tour along with enumerative techniques such as minimising insertion costs to solve the TSP problem. We present a system which uses heuristic rules to augment the convex hull initial sub-tour created by the Graham scan algorithm. The system is able to provide a solution in a polynomial time.     

Mobile robot path planning based on hierarchical hexagonal decomposition and artificial potential fields

In this article, a new algorithm based on an artificial potential field and hierarchical cell decomposition technique is developed to solve the find-path problem for a mobile robot. The complete map of the workspace including obstacle locations is assumed to be known a priori. The basic cell structure used for decomposition is a hexagon. The artificial potential field is based on an attractive force from the goal position and repelling forces from the obstacles. Computer simulations of the algorithm for various obstacle scenarios are also presented. © 1994 John Wiley & Sons, Inc.     

Invariant image classification using triple-correlation-basedneural networks

Triple-correlation-based neural networks are introduced and used in this paper for invariant classification of 2D gray scale images. Third-order correlations of an image are appropriately clustered, in spatial or spectral domain, to generate an equivalent image representation that is invariant with respect to translation, rotation, and dilation. An efficient implementation scheme is also proposed, which is robust to distortions, insensitive to additive noise, and classifies the original image using adequate neural network architectures applied directly to 2D image representations. Third-order neural networks are shown to be a specific category of triple-correlation-based networks, applied either to binary or gray-scale images. A simulation study is given, which illustrates the theoretical developments, using synthetic and real image data.