Synergistic Coupling of ISCO with SEAR and Bioremediation

Treatment of organic contaminants at hazardous waste sites may best be achieved by coupling technologies for improved treatment effectiveness. In particular, sites with high heterogeneity and high contaminant mass may be difficult to treat with a single approach due to difficulties associated with contacting remedial agents with contaminant, the cost of remedial amendments for complete contaminant degradation/removal, and the performance limitations of individual technologies. In situ chemical oxidation (ISCO) is one technology that may be applied prior to, simultaneous with, or after application of other active or passive techniques, in the same or adjacent treatment location. For example, bulk contaminant (e.g., non-aqueous phase liquid, or NAPL) removal, such as provided by surfactant-enhanced aquifer remediation (SEAR), may be necessary prior to ISCO treatment. Passive technologies that provide for a polishing step , such as natural attenuation, may be required following source zone removal using ISCO. Laboratory studies were conducted to investigate the important synergies and challenges associated with coupling ISCO with SEAR and with bioprocesses (e.g., natural attenuation). Results demonstrate the promise of these coupling strategies and demonstrate the importance of characterizing reactants and byproducts associated with each individual process in order to exploit positive effects and avoid negative effects in system design

Computational perspectives on cognitive development

This article reviews the efforts to develop process models of infants' and children's cognition. Computational process models provide a tool for elucidating the causal mechanisms involved in learning and development. The history of computational modeling in developmental psychology broadly follows the same trends that have run throughout cognitive science—including rule‐based models, neural network (connectionist) models, ACT‐R models, ART models, decision tree models, reinforcement learning models, and hybrid models among others