Electric Signaling and Pin2 Gene Expression on Different Abiotic Stimuli Depend on a Distinct Threshold Level of Endogenous Abscisic Acid in Several Abscisic Acid-Deficient Tomato Mutants1

Experiments were performed on three abscisic acid (ABA)-deficient tomato (Lycopersicon esculentum Mill.) mutants, notabilis, flacca, and sitiens, to investigate the role of ABA and jasmonic acid (JA) in the generation of electrical signals and Pin2 (proteinase inhibitor II) gene expression. We selected these mutants because they contain different levels of endogenous ABA. ABA levels in the mutant sitiens were reduced to 8% of the wild type, in notabilis they were reduced to 47%, and in flacca they were reduced to 21%. In wild-type and notabilis tomato plants the induction of Pin2 gene expression could be elicited by heat treatment, current application, or mechanical wounding. In flacca and sitiens only heat stimulation induced Pin2 gene expression. JA levels in flacca and sitiens plants also accumulated strongly upon heat stimulation but not upon mechanical wounding or current application. Characteristic electrical signals evolved in the wild type and in the notabilis and flacca mutants consisting of a fast action potential and a slow variation potential. However, in sitiens only heat evoked electrical signals; mechanical wounding and current application did not change the membrane potential. In addition, exogenous application of ABA to wild-type tomato plants induced transient changes in membrane potentials, indicating the involvement of ABA in the generation of electrical signals. Our data strongly suggest the presence of a minimum threshold value of ABA within the plant that is essential for the early events in electrical signaling and mediation of Pin2 gene expression upon wounding. In contrast, heat-induced Pin2 gene expression and membrane potential changes were not dependent on the ABA level but, rather, on the accumulation of JA.

Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.

Image processing via level set curvature flow.

We present a controlled image smoothing and enhancement method based on a curvature flow interpretation of the geometric heat equation. Compared to existing techniques, the model has several distinct advantages. (i) It contains just one enhancement parameter. (ii) The scheme naturally inherits a stopping criterion from the image; continued application of the scheme produces no further change. (iii) The method is one of the fastest possible schemes based on a curvature-controlled approach.