On the reduction of repetitive processes into singular and non-singular Roesser models

Multidimensional Systems and Signal Processing - In this paper we present new methods for the reduction of a polynomial system matrix describing a discrete linear repetitive process, to equivalent...     

A near-optimal multiuser detector for DS-CDMA systems using semidefinite programming relaxation

A multiuser detector for direct-sequence code-division multiple-access systems based on semidefinite programming (SDP) is proposed. It is shown that maximum likelihood (ML) detection can be carried out by "relaxing" the associated integer programming problem to a dual SDP problem, which leads to a detector of polynomial complexity. Computer simulations that demonstrate that the proposed detector offers near-optimal performance with considerably reduced computational complexity compared with that of existing primal-SDP-relaxation based detectors are presented.     

Rat heart-aorta cluster transplantation: a novel model to study transplant rejection

The purpose of this study was to develop a microsurgical cluster model of heart plus entire thoracic aorta transplantation and to compare it to the isolated model of heart transplantation as a tool to study transplant rejection. Thirty-six syngeneic (DA x DA and Lew x Lew) and allogeneic (DA x PVG and DA x Lew) cluster heart-aorta transplants were compared to 43 syngeneic and allogeneic isolated heart grafts. Graft survival, recipient survival and histological data on myocardial and aortic tissues were assessed. There was no statistically significant difference in graft survival between the two models studied (P > 0.05). In the cluster transplants, the aortic component was spared the severity of acute rejection noted for the myocardial counterpart. In conclusion, the results demonstrated that the cluster model was technically feasible and highly reproducible. Additionally, it was possible to apply this model to the study of experimental allograft rejection using novel immunosuppressants. The success of the cluster model in strongly mismatched transplant strain combinations underscores its potential for application in slower rejection combinations, making it particularly suited for chronic rejection studies. The inherent capacity for sampling a broader range of vessel sizes in one animal makes the cluster model more suitable than the isolated models of aorta or heart for application to experimental protocols.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.     

Splitting Finite Default Theories: A Comparison of Two Approaches

Default logic is computationally expensive. One of the most promising ways of easing this problem and developing powerful implementations is to split a default theory into smaller parts and compute extensions in a modular, local way. This paper compares two recent approaches, Turner's splitting and Cholewinski's stratification. It shows that the approaches are closely related – in fact the former can be viewed as a special case of the latter.     

Characterization and decomposition of waveforms for Larsen 500airborne system

The authors describe a method of accurately decomposing a Larsen waveform into the surface and bottom reflections, independently of the degree of their overlap. A mathematical model that can be used to characterize the Larsen waveforms received under diverse circumstances is established. This model is used in conjunction with an optimization technique to facilitate the decomposition of each Larsen waveform into surface and bottom reflections. The optimized parameters of the mathematical model are used to give sea depth estimates. The resolution of Larsen waveforms into two separate components by means of this technique offers two important advantages. First, sea depths can be readily determined from the displacement between the two components without human intervention, that is, the processing can be automated. Second, fairly accurate sea depths can be deduced even in cases where the two reflections strongly overlap