Using GIS for law enforcement.
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Accidents, Traffic↗
Biomedical subjects
Randy Smith
Publications and source records attributed to Randy Smith.
Withdrawal, tolerance, and sensitization to dopamine mediated interoceptive cues in rats trained on a three-lever drug-discrimination task.
In the present experiment rats were trained on a three-lever, drug-discrimination task to discriminate the cues associated with 0.30 mg/kg of the indirect dopamine (DA) agonist, amphetamine (AMPH), saline (SAL), and 0.03 mg/kg of the DA, D2 receptor antagonist, haloperidol (HAL). Choice behavior determined from tests on 0.30 and 0.15 mg/kg AMPH, SAL 0.03 and 0.015 mg/kg HAL provided a behavioral baseline presumed to represent changes along a continuum of DA mediated, interoceptive cues. Results from separate groups tested on 0.30 and 0.15 mg/kg AMPH, SAL, 0.03 and 0.015 mg/kg HAL, 24 h post-treatment with an acute 7.5 mg/kg dose of AMPH, showed rapid tolerance and withdrawal to the AMPH cue and sensitization to the HAL cue. The same tests 24 h following treatment with 1.0 mg/kg HAL showed rapid tolerance to the HAL cue, sensitization to the AMPH cue, but not AMPH-like withdrawal cues. Analysis of the results showed that tolerance to the AMPH and HAL cues reflected neuroadaptive baseline shifts and not weaker cue properties. These findings are consistent with predictions from opponent process theory of motivation and provide an animal model to study the motivational consequences that aversive symptoms of AMPH withdrawal such as dysphoria and anhedonia can have on drug-taking behavior.
Amphetamine↗
Intelligent automation of high-performance liquid chromatography method development by means of a real-time knowledge-based approach.
We describe the development, attributes and capabilities of a novel type of artificial intelligence system, called LabExpert, for automation of HPLC method development. Unlike other computerised method development systems, LabExpert operates in real-time, using an artificial intelligence system and design engine to provide experimental decision outcomes relevant to the optimisation of complex separations as well as the control of the instrumentation, column selection, mobile phase choice and other experimental parameters. LabExpert manages every input parameter to a HPLC data station and evaluates each output parameter of the HPLC data station in real-time as part of its decision process. Based on a combination of inherent and user-defined evaluation criteria, the artificial intelligence system programs use a reasoning process, applying chromatographic principles and acquired experimental observations to iteratively provide a regime for a priori development of an acceptable HPLC separation method. Because remote monitoring and control are also functions of LabExpert, the system allows full-time utilisation of analytical instrumentation and associated laboratory resources. Based on our experience with LabExpert with a wide range of analyte mixtures, this artificial intelligence system consistently identified in a similar or faster time-frame preferred sets of analytical conditions that are equal in resolution, efficiency and throughput to those empirically determined by highly experienced chromatographic scientists. An illustrative example, demonstrating the potential of LabExpert in the process of method development of drug substances, is provided.
Artificial Intelligence↗