Angiosarcoma, porphyria cutanea tarda, and probable chloracne in a worker exposed to waste oil contaminated with 2,3,7,8-tetrachlorodibenzo-p-dioxin

A worker developed angiosarcoma, porphyria cutanea tarda, and skin lesions characteristic of mild chloracne. About 10 years earlier he had been employed at a truck terminal in Saint Louis, Missouri, at a time when it was sprayed with waste oil contaminated with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). The occurrence of these three rare conditions in a single exposed worker supports the aetiological relation between environmental exposure to TCDD and the subsequent development of soft tissue sarcoma and porphyria cutanea tarda.

Working Memory Networks for Learning Temporal Order, with Application to 3-D Visual Object Recognition

Working memory neural networks are characterized which encode the invariant temporal order of sequential events. Inputs to the networks, called Sustained Temporal Order REcurrent (STORE) models, may be presented at widely differing speeds, durations, and interstimulus intervals. The STORE temporal order code is designed to enable all emergent groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed in neural architectures which self-organize learned codes for variable-rate speech perception, sensory-motor planning, or 3-D visual object recognition. Using such a working memory, a self-organizing architecture for invariant 3-D visual object recognition is described. The new model is based on the model of Seibert and Waxman (1990a), which builds a 3-D representation of an object from a temporally ordered sequence of its 2-D aspect graphs. The new model, called an ARTSTORE model, consists of the following cascade of processing modules: Invariant Preprocessor --> ART 2 --> STORE Model --> ART 2 --> Outstar Network.