ART 2-A: An Adaptive Resonance Algorithm for Rapid Category Learning and Recognition

This article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders of magnitude faster. Analysis and simulations show how the ART 2-A systems correspond to ART 2 dynamics at both the fast-learn limit and at intermediate learning rates. Intermediate learning rates permit fast commitment of category nodes but slow recoding, analogous to properties of word frequency effects, encoding specificity effects, and episodic memory. Better noise tolerance is hereby achieved without a loss of learning stability. The ART 2 and ART 2-A systems are contrasted with the leader algorithm. The speed of ART 2-A makes practical the use of ART 2 modules in large-scale neural computation.BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530); Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088

The effect of HIV and antiretroviral therapy on chromosomal radiosensitivity

Introduction: Antiretroviral Treatment (ART) has led to an improvement in survival of HIV infected individuals. Some of them will develop cancer during the course of their infection and will require radiation therapy. HIV positive cancer patients have presented with adverse side effects of radiotherapy and elevated chromosomal radiosensitivity. This study investigated if ART has an influence on chromosomal radiosensitivity of HIV positive individuals. Methods and Materials: Blood samples from 60 HIV positive individuals were in vitro exposed to doses of X-rays of 0, 2 and 4Gy and chromosomal radiosensitivity was assessed with the micronucleus assay. The micronucleus assay was also performed on lymphocytes of a group of non HIV-infected health care workers taking prophylactic post-exposure ART to measure the effect of these ART drugs on chromosomal radiosensitivity without HIV as a confounding factor. Results: All HIV patients (those on ART and without ART) had significantly higher radiation induced Micronuclei (MN) than healthy controls. The MN yields increased in the HIV patients taking ART compared to HIV patients not on treatment. The evaluation of chromosomal radiosensitivity of health care workers on ART revealed no effects of ART. Conclusions: HIV positive individuals show an increased chromosomal radiosensitivity. Antiretroviral treatment given to HIV positive individuals can lead to enhanced chromosomal radiosensitivity and therefore impose higher risks for radiotherapy side effects in these patients

Predicate Abstraction for Linked Data Structures

We present Alias Refinement Types (ART), a new approach to the verification of correctness properties of linked data structures. While there are many techniques for checking that a heap-manipulating program adheres to its specification, they often require that the programmer annotate the behavior of each procedure, for example, in the form of loop invariants and pre- and post-conditions. Predicate abstraction would be an attractive abstract domain for performing invariant inference, existing techniques are not able to reason about the heap with enough precision to verify functional properties of data structure manipulating programs. In this paper, we propose a technique that lifts predicate abstraction to the heap by factoring the analysis of data structures into two orthogonal components: (1) Alias Types, which reason about the physical shape of heap structures, and (2) Refinement Types, which use simple predicates from an SMT decidable theory to capture the logical or semantic properties of the structures. We prove ART sound by translating types into separation logic assertions, thus translating typing derivations in ART into separation logic proofs. We evaluate ART by implementing a tool that performs type inference for an imperative language, and empirically show, using a suite of data-structure benchmarks, that ART requires only 21% of the annotations needed by other state-of-the-art verification techniques