Predictors of underlying coronary artery disease in cocaine associated myocardial infarction: a meta-analysis of case reports

A preliminary report presenting the results of fibular strut grafting in the severely resorbed mandibular and maxillary region is presented. Thirteen patients were treated due to severe resorption of alveolar and basilar bone of 49 segments of the mandible and the maxilla. Two patients additionally had pathological fractures of the mandible. In 10 cases the strut graft was harvested by means of a new minimally invasive technique. After modelling the fibular bone it was fixed to the recipient site by miniscrews or implants. After a mean follow-up period of 20 months (max. 31, min. 11 months) a retrospective analysis of clinical and radiological findings was carried out. It showed that a mean augmentation of 16 mm was achieved. Compared to other studies the fibular strut graft was resorbed less, and due to the primary stability it could be used for the treatment of fractures of the mandible. No more than natural resorption was observed when the patients received their prostheses fixed to dental implants.     

Low-truncation-error finite difference equations for photonicssimulation. II. Vertical-cavity surface-emitting lasers

For part I see, ibid., p. 134, 1998. The basic approach outlined in the previous article is applied to the difficult problem of computing the optical modes of a vertical-cavity surface-emitting laser. The formulation utilizes a finite difference equation based upon the lowest order term of an infinite series solution of the scalar Helmholtz equation in a local region. This difference equation becomes exact in the one-dimensional (1-D) limit, and is thus ideally suited for nearly 1-D devices such as vertical-cavity lasers. The performance of the resulting code is tested on both a simple cylindrical cavity with known solutions and an oxide-confined vertical-cavity laser structure, and the results compared against second-order-accurate code based upon Crank-Nicolson differencing     

Soft commutation in capacitive idling converters

The capacitive idling converters derived from the Cuk, SEPIC, Zeta, and flyback topologies allow soft commutation of power switches without the need for additional circuitry, making it possible to increase the switching frequency while maintaining high efficiency     

Scientific and artistic investigation of multi-dimensional fractals on the AT & T pixel machine

The pipelined architecture and parallel organization of the AT&T Pixel Machine image computer are described and demonstrated with applications for the visualization of multidimensional fractals, particularly linear fractals and quaternion/ stacked Julia sets. Techniques for pushing the Pixel Machine to its peak abilities are described and apply to more recent parallel image computers as well.     

Partial indexing for nonuniform data distributions in relationalDBMS's

It is well known that the effectiveness of relational database systems is greatly dependent on the efficiency of the data access strategies. For this reason, much work has been devoted to the development of new access techniques, supported by adequate access structures such as the B⁺trees. The effectiveness of the B ⁺tree also depends on the data distribution characteristics; in particular, poor performance results when the data show strong key value distribution unbalancing. The aim of this paper is to present the partial index: a new access structure that is useful in such cases of unbalancing, as an alternative to the B⁺tree unclustered indexes. The access structures are built in the physical design phase, and at execution (or compilation) time, the optimizer chooses the most efficient access path. Thus, integration of the partial indexing technique in the design and in the optimization process are also described     

Evaluation of a parallel branch-and-bound algorithm on a class ofmultiprocessors

We propose and evaluate a parallel “decomposite best-first” search branch-and-bound algorithm (dbs) for MIN-based multiprocessor systems. We start with a new probabilistic model to estimate the number of evaluated nodes for a serial best-first search branch-and-bound algorithm. This analysis is used in predicting the parallel algorithm speed-up. The proposed algorithm initially decomposes a problem into N subproblems, where N is the number of processors available in a multiprocessor. Afterwards, each processor executes the serial best-first search to find a local feasible solution. Local solutions are broadcasted through the network to compute the final solution. A conflict-free mapping scheme, known as the step-by-step spread, is used for subproblem distribution on the MIN. A speedup expression for the parallel algorithm is then derived using the serial best-first search node evaluation model. Our analysis considers both computation and communication overheads for providing realistic speed-up. Communication modeling is also extended for the parallel global best-first search technique. All the analytical results are validated via simulation. For large systems, when communication overhead is taken into consideration, it is observed that the parallel decomposite best-first search algorithm provides better speed-up compared to other reported schemes     

Partitioned encoding schemes for algorithm-based fault tolerance inmassively parallel systems

Considers the applicability of algorithm based fault tolerance (ABET) to massively parallel scientific computation. Existing ABET schemes can provide effective fault tolerance at a low cost For computation on matrices of moderate size; however, the methods do not scale well to floating-point operations on large systems. This short note proposes the use of a partitioned linear encoding scheme to provide scalability. Matrix algorithms employing this scheme are presented and compared to current ABET schemes. It is shown that the partitioned scheme provides scalable linear codes with improved numerical properties with only a small increase in hardware and time overhead     

Parallel architecture for fast transforms with trigonometric kernel

We present an unified parallel architecture for four of the most important fast orthogonal transforms with trigonometric kernel: Complex Valued Fourier (CFFT), Real Valued Fourier (RFFT), Hartley (FHT), and Cosine (FCT). Out of these, only the CFFT has a data flow coinciding with the one generated by the successive doubling method, which can be transformed on a constant geometry flow using perfect unshuffle or shuffle permutations. The other three require some type of hardware modification to guarantee the constant geometry of the successive doubling method. We have defined a generalized processing section (PS), based on a circular CORDIC rotator, for the four transforms. This PS section permits the evaluation of the CFFT and FCT transforms in n data recirculations and the RFFT and FHT transforms in n-1 data recirculations, with n being the number of stages of a transform of length N=rⁿ. Also, the efficiency of the partitioned parallel architecture is optimum because there is no cycle loss in the systolic computation of all the butterflies for each of the four transforms     

The classification, fusion, and parallelization of array languageprimitives

We present a classification scheme for array language primitives that quantifies the variation in parallelism and data locality that results from the fusion of any two primitives. We also present an algorithm based on this scheme that efficiently determines when it is beneficial to fuse any two primitives. Experimental results show that five LINPACK routines report 50% performance improvement from the fusion of array operators