Featured Research

Generating exact optimal designs via particle swarm optimization: Assessing efficacy and efficiency via case studyIn this study we address existing deficiencies in the literature on applications of Particle Swarm Optimization (PSO) to generate optimal designs. We present the results of a large computer study i...

I-optimal or G-optimal: Do we have to choose?When optimizing an experimental design for good prediction performance based on an assumed second order response surface model, it is common to focus on a single optimality criterion, either G-opti...

Improved G-Optimal Designs for Small Exact Response Surface Scenarios: Fast and Efficient Generation via Particle Swarm OptimizationG-optimal designs are those which minimize the worst-case prediction variance. Thus, such designs are of interest if prediction is a primary component of the post-experiment analysis and decision making. G-optimal designs have not attained widespread use in practical applications, in part, because they are difficult to compute. In this paper, we review the last two decades of algorithm development for generating exact G-optimal designs. To date, Particle Swarm Optimization (PSO) has not been applied to construct exact G-optimal designs for small response surface scenarios commonly encountered in industrial settings. We were able to produce improved G-optimal designs for the second-order model and several sample sizes under experiments with K=1,2,3,4, and 5 design factors using an adaptation of PSO. Thereby, we publish updated knowledge on the best-known exact G-optimal designs. We compare computing cost/time and algorithm efficacy to all previous published results including those generated by the current state-of-the-art (SOA) algorithm, the G(Iλ)-coordinate exchange. PSO is hereby demonstrated to produce better designs than the SOA at commensurate cost. In all, the results of this paper suggest PSO should be adopted by more practitioners as a tool for generating exact optimal designs.

Generating optimal designs with user‐specified pure replication structureQuality and Reliability Engineering International is a quality engineering journal solving real-life quality and reliability problems across engineering.

Overview of Optimal Experimental Design and a Survey of Its Expanse in Application to Agricultural StudiesOptimal Design of Experiments is currently recognized as the modern dominant approach to planning experiments in industrial engineering and manufacturing applications. This approach to design has gained traction among practitioners in the last two decades on two-fronts: 1) optimal designs are the result of a complicated optimization calculation and recent advances in both computing efficiency and algorithms have enabled this approach in real time for practitioners, and 2) such designs are now popular because they allow the researcher to ‘design for the experiment’ by working constraints, cost, number of experiments, and the model of the intended post-hoc data analysis into the design definition, thereby creating designs with more practical meaning than classical or catalogue designs. In this talk, I will review the definition of optimal design, discuss recent computational advancements in this field, and provide a survey of the expanse of this design approach in the agricultural literature.

Ketamine produces no detectable long-term positive or negative effects on cognitive flexibility or reinforcement learning of male rats - PsychopharmacologyRationale Patients with major depressive disorder (MDD) often experience abnormalities in behavioral adaptation following environmental changes (i.e., cognitive flexibility) and tend to undervalue positive outcomes but overvalue negative outcomes. The probabilistic reversal learning task (PRL) is used to study these deficits across species and to explore drugs that may have therapeutic value. Selective serotonin-reuptake inhibitors (SSRIs) have limited effectiveness in treating MDD and produce inconsistent effects in non-human versions of the PRL. As such, ketamine, a novel and potentially rapid-acting therapeutic, has begun to be examined using the PRL. Two previous studies examining the effects of ketamine in the PRL have shown conflicting results and only examined short-term effects of ketamine. Objective This experiment examined PRL performance across a 2-week period following a single exposure to a ketamine dose that varied across groups. Methods After five sessions of PRL training, groups of rats received an injection of either 0, 10, 20 or 30 mg/kg ketamine. One-hour post-injection, rats engaged in the PRL, and subsequently sessions continued daily for 2 weeks. Traditional behavioral and computational reinforcement learning-derived measures were examined. Results Results showed that ketamine had acute effects 1-h post-injection, including a significant decrease in the value of the punishment learning rate. Beyond 1 h, ketamine produced no detectable improvements nor decrements in performance across 2 weeks. Conclusion Overall, the present results suggest that the range of ketamine doses examined do not have long-term positive or negative effects on cognitive flexibility or reward processing in healthy rats as measured by the PRL.

Page updated

Google Sites

Report abuse