Beth Stauffer

USC CINAPS Builds Bridges

More than 70% of our earth is covered by water, yet we have explored less than 5% of the aquatic environment. Aquatic robots, such as autonomous underwater vehicles (AUVs), and their supporting infrastructure play a major role in the collection of oceanographic data. To make new discoveries and improve our overall understanding of the ocean, scientists must make use of these platforms by implementing effective monitoring and sampling techniques to study ocean upwelling, tidal mixing, and other ocean processes. Effective observation and continual monitoring of a dynamic system as complex as the ocean cannot be done with one instrument in a fixed location. A more practical approach is to deploy a collection of static and mobile sensors, where the information gleaned from the acquired data is distributed across the network. Additionally, orchestrating a multisensor, long-term deployment with a high volume of distributed data involves a robust, rapid, and cost-effective communication network. Connecting all of these components, which form an aquatic robotic system, in synchronous operation can greatly assist the scientists in improving our overall understanding of the complex ocean environment.

Rapid and label-free cell detection by metal-cluster-decorated carbon nanotube biosensors

The article reports the use of a metal-cluster-decorated carbon nanotube biosensors for rapid and label-free algae cell detection. Sensitivities of the devices with or without the metal-cluster coating were subsequently compared using streptavidin (SA) as a model case. The sensing responses of device conductance (G) normalized by initial conductance (G0) plotted versus time for devices without and with metal clusters are shown.

Immunofluorescence Flow Cytometry Technique for Enumeration of the Brown-Tide Alga, Aureococcus anophagefferens

ABSTRACT A new immunologically based flow cytometry (IFCM) technique was developed to enumerate Aureococcus anophagefferens, a small pelagophyte alga that is the cause of “brown tides” in bays and estuaries of the mid-Atlantic states along the U.S. coast. The method utilizes a monoclonal antibody conjugated to fluorescein isothiocyanate (FITC-MAb) to label the surface of A. anophagefferens cells which are then detected and enumerated by using a flow cytometer. Optimal conditions for FITC-MAb staining, including solution composition, incubation times, and FITC-MAb concentrations, were determined. The FITC-MAb method was tested for cross-reactivity with nontarget, similarly sized, photoautotrophic protists, and the method was compared to an enzyme-linked immunosorbent assay (ELISA) using the same MAb. Comparisons of the IFCM technique to traditional microscopy enumeration of cultures and spiked environmental samples showed consistent agreement over several orders of magnitude (r2 > 0.99). Comparisons of the IFCM and ELISA techniques for enumerating cells from a predation experiment showed a substantial overestimation (up to 10 times higher) of the ELISA in the presence of consumers of A. anophagefferens, presumably due to egested cell fragments that retained antigenicity, using the ELISA method, but were not characterized as whole algal cells by the IFCM method. Application of the IFCM method to environmental “brown-tide” samples taken from the coastal bays of Maryland demonstrated its efficacy in resolving A. anophagefferens abundance levels throughout the course of a bloom and over a large range of abundance values. IFCM counts of the brown-tide alga from natural samples were consistently lower than those obtained using the ELISA method and were equivalent to those of the polyclonal immunofluorescence microscopy technique, since both methods discriminate intact cells. Overall, the IFCM approach was an accurate and relatively simple technique for the rapid enumeration of A. anophagefferens in natural samples over a wide range of abundance values (103 to 106 cells ml−1).

Human Assisted Robotic Team Campaigns for Aquatic Monitoring

Large-scale environmental sensing, e.g., understanding microbial processes in an aquatic ecosystem, requires coordination across a multidisciplinary team of experts working closely with a robotic sensing and sampling system. We describe a human-robot team that conducted an aquatic sampling campaign in Lake Fulmor, San Jacinto Mountains Reserve, California during three consecutive site visits (May 9–11, June 19–22, and August 28–31, 2006). The goal of the campaign was to study the behavior of phytoplankton in the lake and their relationship to the underlying physical, chemical, and biological parameters. Phytoplankton form the largest source of oxygen and the foundation of the food web in most aquatic ecosystems. The reported campaign consisted of three system deployments spanning four months. The robotic system consisted of two subsystems—NAMOS (networked aquatic microbial observing systems) comprised of a robotic boat and static buoys, and NIMS-RD (rapidly deployable networked infomechanical systems) comprised of an infrastructure-supported tethered robotic system capable of high-resolution sampling in a two-dimensional cross section (vertical plane) of the lake. The multidisciplinary human team consisted of 25 investigators from robotics, computer science, engineering, biology, and statistics.We describe the lake profiling campaign requirements, the robotic systems assisted by a human team to perform high fidelity sampling, and the sensing devices used during the campaign to observe several environmental parameters. We discuss measures taken to ensure system robustness and quality of the collected data. Finally, we present an analysis of the data collected by iteratively adapting our experiment design to the observations in the sampled environment. We conclude with the plans for future deployments.

Whole-Cell Sensing for a Harmful Bloom-Forming Microscopic Alga by Measuring Antibody–Antigen Forces

Aureococcus anophagefferens, a harmful bloom-forming alga responsible for brown tides in estuaries of the Middle Atlantic U.S., has been investigated by atomic force microscopy for the first time, using probes functionalized with a monoclonal antibody specific for the alga. The rupture force between a single monoclonal antibody and the surface of A. anophagefferens was experimentally found to be 246 plusmn 11 pN at the load rate of 12 nN/s. Force histograms for A. anophagefferens and other similarly-sized algae are presented and analyzed. The results illustrate the effects of load rates, and demonstrate that force-distance measurements can be used to build biosensors with high signal-to-noise ratios for A. anophagefferens. The methods described in this paper can be used, in principle, to construct sensors with single-cell resolution for arbitrary cells for which monoclonal antibodies are available

A generic multi-scale modeling framework for reactive observing systems: an overview

Observing systems facilitate scientific studies by instrumenting the real world and collecting corresponding measurements, with the aim of detecting and tracking phenomena of interest. A wide range of critical environmental monitoring objectives in resource management, environmental protection, and public health all require distributed observing systems. The goal of such systems is to help scientists verify or falsify hypotheses with useful samples taken by the stationary and mobile units, as well as to analyze data autonomously to discover interesting trends or alarming conditions. In our project, we focus on a class of observing systems which are embedded into the environment, consist of stationary and mobile sensors, and react to collected observations by reconfiguring the system and adapting which observations are collected next. In this paper, we give an overview of our project in the context of a marine biology application.

AMBROSia: An Autonomous Model-Based Reactive Observing System

Observing systems facilitate scientific studies by instrumenting the real world and collecting corresponding measurements, with the aim of detecting and tracking phenomena of interest. Our AMBROSia project focuses on a class of observing systems which are embeddedinto the environment, consist of stationary and mobilesensors, and reactto collected observations by reconfiguring the system and adapting which observations are collected next. In this paper, we report on recent research directions and corresponding results in the context of AMBROSia.

AMBROSia: An Overview and Recent Results

Observing systems facilitate scientific studies by instrumenting the real world and collecting corresponding measurements, with the aim of detecting and tracking phenomena of interest. A wide range of critical environmental monitoring objectives in resource management, environmental protection, and public health all require distributed observing systems. The goal of such systems is to help scientists verify or falsify hypotheses with useful samples taken by the stationary and mobile units, as well as to analyze data autonomously to discover interesting trends or alarming conditions. In our AMBROSia project, we focus on a class of observing systems which are embedded into the environment, consist of stationary and mobile sensors, and react to collected observations by reconfiguring the system and adapting which observations are collected next. In this paper, we give an overview of AMBROSia.