Bioaccumulation Trends of Ten Metals in a Pelagic Food Web of Lake Champlain

Many metals have serious toxic effects when ingested by aquatic organisms, and the process of bioaccumulation intensifies this problem. A better understanding of bioaccumulation trends of anthropogenically introduced metals in freshwater food webs is necessary for the development of effective management strategies to protect aquatic organisms, as well as organisms (including humans) that consume top-predator fish in these food webs. Various fish species representing different trophic levels of a pelagic food chain were sampled from Lake Champlain (VT/NY). Atomic absorption spectrometry (AAS) was used to determine levels of chromium, copper, cobalt, cadmium, lead, zinc, nickel, rubidium, cesium and potassium in the fish samples. Metal concentrations for chromium, cobalt, nickel, cesium, cadmium (<5.0 ppm) and lead (<10.0 ppm) were found to be all below detection limits. Carbon and nitrogen isotopic ratios were analyzed to determine the trophic relationship of each fish species. Stable isotope and AAS metal data were used in tandem to produce linear regressions for each metal against trophic level to assess biomagnification. Both potassium and zinc showed no biomagnification because they are homeostatically regulated essential trace metals. Copper was under the detection limits for all fish species with the exception of the sea lamprey; but showed a significant biodiminution among the invertebrates and lamprey. Rubidium, a rarely studied metal, was shown to increase with trophic level in a marginally significant linear relationship suggesting biomagnification is possible where more trophic levels are sampled.

A Virtual Joystick as a Novel Interaction Modality for Surgeon-Computer Interaction During Computer-Assisted Surgical Procedures

Interacting with a computer system in the operating room (OR) can be a frustrating experience for a surgeon, who currently has to verbally delegate to an assistant every computer interaction task. This indirect mode of interaction is time consuming, error prone and can lead to poor usability of OR computer systems. This thesis describes the design and evaluation of a joystick-like device that allows direct surgeon control of the computer in the OR. The device was tested extensively in comparison to a mouse and delegated dictation with seven surgeons, eleven residents, and five graduate students. The device contains no electronic parts, is easy to use, is unobtrusive, has no physical connection to the computer and makes use of an existing tool in the OR. We performed a user study to determine its effectiveness in allowing a user to perform all the tasks they would be expected to perform on an OR computer system during a computer-assisted surgery. Dictation was found to be superior to the joystick in qualitative measures, but the joystick was preferred over dictation in user satisfaction responses. The mouse outperformed both joystick and dictation, but it is not a readily accepted modality in the OR.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.