Endoscopic removal of a dental instrument from the stomach: case report

The records of 628 patients admitted to the Joint Study of Extracranial Arterial Occlusion with transient symptoms of carotid system ischemic disease were examined to determine the accuracy of predicting disease of the extracranial internal carotid artery on the basis of clinical information alone. A patient with a history of episodes of amaurosis fugax is more likely to have a lesion of the internal carotid artery on the same side than if he were having only transient cerebral ischemic attacks. In patients with transient symptoms and a carotid bruit on the appropriate side, the incidence of an angiographically normal carotid artery was 15%. In those patients with transient symptoms and no palpable pulsation in the cervical region on the appropirate side, the incidence of an angiographically normal carotid artery was zero.     

A framework for robust parametric set membership identification

This paper proposes a new framework for studying robust parametric set membership identification. The authors derive some new results on the fundamental limitations of algorithms in this framework, given a particular model structure. The new idea is to quantify uncertainty only with respect to the (finite dimensional) parametric part of the model and not the (fixed size) unmodeled dynamics. Thus, the measure of uncertainty is different from the measures used in previous robust identification work where system norms are used to quantify uncertainty. As an example, the results are used to assess the fidelity of a certain approximate robust parametric set membership identification algorithm     

Asymptotic properties of set membership identification algorithms

This paper addresses the asymptotic worst-case properties of set membership identification (SMID) algorithms. We first present a set membership identification algorithm which can be used with a model structure consisting of parametric and nonparametric uncertainty, as well as output additive disturbances. This algorithm is then studied in the context of asymptotic worst-case behavior. We derive lower bounds on the worst-case achievable identification error measured by the volume, as well as the sum-of-sidelengths of the identified ellipsoidal uncertainty sets. We then show that there exist inputs which can shrink the uncertainty sets to these lower bounds.     

Automated Design and Programming of a Microfluidic DNA Computer

Previously, we described ways to implement the functions AND and OR in a DNA computer consisting of microreactors with attached heating elements that control annealing of DNA. Based on these findings, we have devised a similar device that can solve a satisfiability problem in any form. The device occupies linear space and operates in quadratic time, while a previously described competing device is built in quadratic space and operates in quadratic time or greater. Reducing the number of reactors in a DNA computer reduces the loss of DNA through binding to the surfaces of the system.