A novel framework based on a data-driven approach for modelling the behaviour of organisms in chemical plume tracing

We propose a data-driven approach for modelling an organism's behaviour instead of conventional model-based strategies in chemical plume tracing (CPT). CPT models based on this approach show promise in faithfully reproducing organisms’ CPT behaviour. To construct the data-driven CPT model, a training dataset of the odour stimuli input toward the organism is needed, along with an output of the organism’s CPT behaviour. To this end, we constructed a measurement system comprising an array of alcohol sensors for the measurement of the input and a camera for tracking the output in a real scenario. Then, we determined a transfer function describing the input–output relationship as a stochastic process by applying Gaussian process regression, and established the data-driven CPT model based on measurements of the organism’s CPT behaviour. Through CPT experiments in simulations and a real environment, we evaluated the performance of the data-driven CPT model and compared its success rate with those obtained from conventional model-based strategies. As a result, the proposed data-driven CPT model demonstrated a better success rate than those obtained from conventional model-based strategies. Moreover, we considered that the data-driven CPT model could reflect the aspect of an organism’s adaptability that modulated its behaviour with respect to the surrounding environment. However, these useful results came from the CPT experiments conducted in simple settings of simulations and a real environment. If making the condition of the CPT experiments more complex, we confirmed that the data-driven CPT model would be less effective for locating an odour source. In this way, this paper not only poses major contributions toward the development of a novel framework based on a data-driven approach for modelling an organism’s CPT behaviour, but also displays a research limitation of a data-driven approach at this stage.

Methyl-Cyclohexane Methanol (MCHM) Isomer-Dependent Binding on Amorphous Carbon Surfaces

In January 2014, over 10,000 gallons of methyl-cyclohexane methanol (MCHM) leaked into the Elk River in West Virginia, in a chemical spill incident that contaminated a large portion of the state’s water supply and left over 300,000 residents without clean water for many days and weeks. Initial efforts to remove MCHM at the treatment plant centered on the use of granulated activated carbon (GAC), which removed some of the chemical from the water, but MCHM levels were not lowered to a “non-detect” status until well after the chemical plume had moved downstream of the intake. Months later, MCHM was again detected at the outflow (but not the inflow) at the water treatment facility, necessitating the full and costly replacement of all GAC in the facility. The purpose of this study is to investigate the hypothesis that preferential absorbance of one of the two MCHM isomers, coupled with seasonal variations in water temperature, explain this contrary observation. Calculated intermolecular potentials between ovalene (a large planar polycyclic aromatic hydrocarbon) and the MCHM isomers were compared to physisorption potentials of MCHM onto an amorphous carbon model. While a molecular mechanics (MM) force field predicts no difference in the average interaction potentials between the cis- and trans-MCHM with the planar ovalene structure, MM predicts that the trans isomer binds stronger than the cis isomer to the amorphous carbon surface. Semi-empirical and density functional theory also predict stronger binding of trans-MCHM on both the planar and amorphous surfaces. The differences in the isomer binding strengths on amorphous carbon imply preferential absorbance of the trans isomer onto activated charcoal filter media. Considering seasonal water temperatures, simple Arrhenius kinetics arguments based on these predicted binding energies help explain the environmental observations of MCHM leeching from the GAC filters months after the spill. Overall, this work shows the important implications that can arise from detailed interfacial chemistry investigations.