A computational study of the feedback control of von Karman vortex shedding behind a circular cylinder at low Reynolds numbers is reported. The two-dimensional Navier-Stokes equations with feedback are solved numerically. The control actuators are a pair of blowing/suction slots located at ± 110 0 from the leading stagnation point. A single feedback sensor is used and the actuators are 180 0 out of phase with each other. Complete suppression of vortex shedding is achieved for the simulation at Reynolds number Re=60. The suppression window in the feedback sensor location Xs is narrow. With the feedback sensor location fixed at the optimum location, vortex shedding becomes suppressed with increasing feedback gain a. However, further increase of the feedback gain destabilizes the flow again. At Reynolds number Re=80, and above, the feedback control stabilizes the primary vortex shedding mode, but a secondary JDode which may be lower or higher in frequency than the primary depending upon the phase of the feedback (feedback sensor location x s ) and the feedback gain a arises.

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The principal objective of this study was to record maximum dolphin swimming speeds sustainable for several seconds utilizing different motivational strategies for both captive and free-ranging dolphins. Video records were used to determine relationships between the various kinematic parameters, particularly the Strouhal number, which characterizes dolphin-swimming motion. Comparisons were made, where possible, with results from previous studies. RESULTS Nearly 2000 swimming-speed measurements were obtained from recordings of both captive and free-ranging dolphins. Captive dolphins studied were Tursiops truncatus (bottlenose dolphin), Delphinus delphis (short-beaked common dolphin), and Pseudorca crassidens (false killer whale). Free-ranging dolphins observed were Tursiops and Delphinus capensis (long-beaked common dolphin). In all cases, some form of motivation was provided for the dolphins to swim fast. The highest swimming speeds recorded were those of captive dolphins, and ranged from 8.0 to 8.2 m/s, typically lasting for a few seconds. 'e • Several kinematic variables, and combinations thereof, were determined for dolphins swimming in large pools. The average values of the tail-beat peak-to-peak amplitude (A pp) for Tursiops truncatus and Pseudorca crassidens were respectively 22% ±2% (n=51) and 23% ±2% (n=23) of their body length. These values of A^ agree with the 20% ±3% (n=56) reported by Fish (1993) and the 19% ±1% (n=30) reported by Kayan and Pyatetskiy (1977) for trained Tursiops, also swimming in large pools. Corresponding tail-beat frequency(f) throughout the velocity range of present (= 3-7.5 m/s) and past (Fish, 1993; U = 1-6 m/s) Tursiops measurements, increase almost linearly with increasing velocity (f « 0.34 U; R 2 = 0.79). Average Strouhal numbers (A^f/U) calculated from present and past (Fish, 1993) swimming recordings of Tursiops truncatus, were 0.25 ±0.04 (n = 51) and 0.27 ±0.05 (n = 56), respectively. These values compare well with the average Strouhal number of 0.25 ±0.02 (n=17) observed by Kayan and Pyatetskiy (1977), also for captive Tursiops. The average Strouhal number calculated for Pseudorca crassidens was 0.29 ±0.04. Average Strouhal values were within the 0.25 to 0.35 range predicted by theoretical models for maximum propulsive efficiency (Triantafyllou et al., 1993). RECOMMENDATIONS Although the fastest swimming speeds reported for trained dolphins agree, there is a large discrepancy between reported swimming speeds of trained and free-ranging dolphins. Maximum swimming speeds of free-ranging dolphins are as much as two times that reported for captive dolphins. Consequently, additional recorded observations are necessary to increase confidence in existing measurements of maximum dolphin swimming speeds in the wild. Because of the low probability of recording maximum speeds, large data sets using different motivational strategies are considered essential. A study of the relationship between jump height and underwater swimming speed (prior to the jump) of captive dolphins would be ...

A common member of the intestinal microbiota in humans and animals is Escherichia coli. Based on the presence of virulence factors, E. coli can be potentially pathogenic. The focus of this study was to isolate E. coli from untreated surface waters (37 sites) in Illinois and Missouri and determine phenotypic and genotypic diversity among isolates. Water samples positive for fecal coliforms based on the Colisure® test were streaked directly onto Eosin Methylene Blue (EMB) agar (37°C) or transferred to EC broth (44.5°C). EC broth cultures producing gas were then streaked onto EMB agar. Forty-five isolates were identified as E. coli using API 20E and Enterotube II identification systems, and some phenotypic variation was observed in metabolism and fermentation. Antibiotic susceptibility of each isolate was also determined using the Kirby-Bauer Method. Differential responses to 10 antimicrobial agents were seen with 7, 16, 2, and 9 of the isolates resistant to ampicillin, cephalothin, tetracycline, and triple sulfonamide, respectively. All of the isolates were susceptible or intermediate to amoxicillin, ciprofloxacin, polymyxin B, gentamicin, imipenem, and nalidixic acid. Genotypic variation was assessed through multiplex Polymerase Chain Reaction for four virulence genes (stx1 and stx2 [shiga toxin], eaeA [intimin]; and hlyA [enterohemolysin]) and one housekeeping gene (uidA [β-D-glucuronidase]). Genotypic variation was observed with two of the isolates possessing the virulence gene (eaeA) for intimin. These findings increase our understanding of the diversity of E. coli in the environment which will ultimately help in the assessment of this organism and its role in public health.

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