Epidemiological study of bancroftian filariasis in Recife, northeastern Brazil

Three surgeons performed 180 atherectomy procedures in 161 patients using the Transluminal Extraction Catheter in 144 and the Auth Rotablator in 36. The primary patency rate was 55% at 1 year and 46% at 2 years, and failure was caused by stenosis in 28 (15.6%) and occlusion in 61 (33.7%) limbs. Multivariate Cox regression analysis showed significantly better outcome if the indication was claudication, the lesion was short or there was associated stenting. Vascular laboratory surveillance was performed in 93 limbs in 83 patients. Cox regression analysis in this subgroup also showed a significant relationship between outcome and the maximum peak systolic velocity from a duplex scan at the last study performed. Receiver operating characteristics curves showed that a raised maximum peak systolic velocity best predicted late failure (sensitivity 84%, specificity 66% for > 200 cm/s; sensitivity 72%, specificity 84% for > 250 cm/s); the velocity ratio at the stenosis to that in the segment above or the resting ankle/brachial pressure index were less predictive. For 50 procedures studied in the vascular laboratory which remained successful to the end of the study, maximum peak systolic velocities were > 250 cm/s from the first postoperative study, suggesting residual stenosis in 6%, or increased to become > 250 cm/s by the last study, suggesting recurrent stenoses in 12%. For 43 procedures which were studied and later failed, velocities were > 250 cm/s from the first test in 26% or increased to > 250 cm/s by the last test before failure in 40%. Vascular laboratory surveillance helps to predict outcome after atherectomy. Failure may be a result of residual disease from the time of the procedure or from restenosis. The apparent high incidence of clinically manifest or developing stenoses raises doubts as to the benefit of atherectomy over balloon dilatation alone.     

Avoiding misconstruals in database systems: a default logicapproach

A cooperative interface that, using suitable user models, alters the processing of the user's queries to include additional information that will block faulty inferences is described. In a sense, the interface actively teaches the user facts about the database not explicitly asked for. User interaction with the database then becomes a learning and discovery process guided by the queries posed to the interface. A semantics for user models is introduced that captures, with the help of default logic, the nonmonotonic behavior users normally exhibit. Results showing that the cooperative interface generates enough additional information to block all faulty inferences are presented     

A rule-based part orientation system for fixtureless assembly

A simple method to determine the orientation of an object is described. The algorithm makes use of a system generated scalene triangle and defines the orientation as the angle through which the shortest side of the triangle must be rotated to make it (the side) parallel to the Y-axis of the vision coordinate system. The scalene triangle is formed from the vertices of a 2-D image of an object or from the controids of the internal features of the object.     

Studies on densification ofα-Fe2O3 ceramics

The densification of ceramics of -Fe₂O₃ depends on the processing parameters. The separate influences of milling, sieving, isostatic pressure and sintering atmosphere were investigated. The maximum density, with a value around 96%, was obtained in a sintering atmosphere of nitrogen.     

Video-based interactive storytelling using real-time video compositing techniques

Interactive storytelling systems usually adopt computer graphics to represent virtual story worlds, which facilitates the dynamic generation of visual content. However, the quality of the images and motion produced by these systems is still inferior compared to the high quality experience found in live-action films. Interactive rates in photorealistic rendering for the film industry will not be possible for decades to come. A promising alternative is the replacement of 3D virtual characters with video sequences with real actors. In this paper, we propose a new method for video-based interactive narratives that uses video compositing algorithms that run at truly interactive frame rates. The proposed method is consistent with plots that are generated by nondeterministic planning algorithms. Moreover, we propose a system of artificial intelligent agents that perform the same roles played by filmmaking professionals. A user evaluation of the proposed method is presented. We believe that future improvements of the techniques proposed in this paper represent an important contribution to the quest for new and more immersive forms of interactive cinema.

     

Time series joins,motifs, discords and shapelets: a unifying view that exploits the matrix profile

The last decade has seen a flurry of research on all-pairs-similarity-search (or similarity joins) for text, DNA and a handful of other datatypes, and these systems have been applied to many diverse data mining problems. However, there has been surprisingly little progress made on similarity joins for time series subsequences. The lack of progress probably stems from the daunting nature of the problem. For even modest sized datasets the obvious nested-loop algorithm can take months, and the typical speed-up techniques in this domain (i.e., indexing, lower-bounding, triangular-inequality pruning and early abandoning) at best produce only one or two orders of magnitude speedup. In this work we introduce a novel scalable algorithm for time series subsequence all-pairs-similarity-search. For exceptionally large datasets, the algorithm can be trivially cast as an anytime algorithm and produce high-quality approximate solutions in reasonable time and/or be accelerated by a trivial porting to a GPU framework. The exact similarity join algorithm computes the answer to the time series motif and time series discord problem as a side-effect, and our algorithm incidentally provides the fastest known algorithm for both these extensively-studied problems. We demonstrate the utility of our ideas for many time series data mining problems, including motif discovery, novelty discovery, shapelet discovery, semantic segmentation, density estimation, and contrast set mining. Moreover, we demonstrate the utility of our ideas on domains as diverse as seismology, music processing, bioinformatics, human activity monitoring, electrical power-demand monitoring and medicine.     

A State-of-the-Art Review of Compact Vapor Compression Refrigeration Systems and Their Applications

We present a critical review of the literature on the fundamentals, design, and application aspects of compact and miniature mechanical vapor compression refrigeration systems. Examples of such systems are those envisaged for electronics and personal cooling. In comparison to other refrigeration technologies (e.g., solid-state), vapor compression enables the attainment of low evaporating temperatures while maintaining a large cooling capacity per unit power input to the system. Over the past decade, there have been a significant number of studies devoted to the miniaturization of system components, with the most critical being the compressor. When compared with competing cooling technologies, such as flow boiling in microchannels, jet impingement, and spray cooling, refrigeration is the only one capable of lowering the junction temperature to values below the ambient temperature. The combination of vapor compression refrigeration with the aforementioned technologies is also possible, necessary, and beneficial, since it increases greatly the potential for reducing the system size. For each main application, this paper sheds some light on the thermodynamic and thermal aspects of the cooling cycle and on recent developments regarding its components (compressor, heat exchangers, and expansion device). Whenever appropriate, issues and challenges associated with the different cycle designs are addressed. An overview of the ongoing efforts in competing technologies is also presented.     

Modeling of Closed-Vessel Experiments and Ballistic Parameter Estimation

ABSTRACT

Closed vessels have been used for the regression of lumped ballistic parameters for decades. If material and energy balances are coupled with burning rate empirical correlations, uncorrelated parameters can be adjusted, describing accurately the thermochemical behavior of the generated gases, even if the chemical composition of the propellant is unknown (aging of the propellant). This work presents a system of differential Equations integrated to produce pressure profiles within the vessel that are highly dependent on the choice of empirical parameters. Such parameters are manipulated via maximum likelihood statistical procedures, leading to the best set of parameters to describe the propellant.