In situ analysis of phytoplankton community structure was determined at five stations along the Texas Gulf coast using two instruments, the Fluoroprobe and FlowCAM. Results were compared with traditional methods to determine community structure (pigment analysis and microscopy). Diatoms and small nanoplankton (most likely haptophytes) dominated the phytoplankton community at all stations. Estimated chl concentrations for diatoms+dinoflagellates obtained via the Fluoroprobe were not significantly different for three of the five stations sampled when compared with HPLC‐chemical taxonomy analysis, whereas the concentrations of green algal and cryptophyte chl were overestimated. The FlowCAM estimates of overall nanoplankton and microplankton cell abundance were not significantly different when compared with epifluorescence microscopy, and recorded images of phytoplankton cells provided a representative population of the phytoplankton community at each station. The Fluoroprobe and FlowCAM, when used in tandem, are potentially capable of determining the general characteristics of phytoplankton community structure in situ and could be an important addition to biological observing systems in the coastal ocean.

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Purpose: Performance measurement systems for nursing homes assume that facility performance contributes heavily to individual outcomes. This research illustrates how that assumption can be assessed using the change in residents' activities of daily living (ADLs). Design and Methods: The data used in these analyses were all from residents with both an admission and a quarterly assessment in a sample of all admissions to a randomly chosen 10% of Medicare-or Medicaid-certified nursing homes operating during 2002. Results: Models including both facility and individual variables explained up to 20% of the variation in ADL change after admission. Facility identity in isolation explained between 8% and 14% of the variation in ADL change. Implications: The results suggest that quality indicators based on change in ADLs may be problematic when used in nursing home performance measurement systems. More generally, the results recommend that the level of variation in performance measures attributable to facility identity or performance become a much more central consideration when researchers evaluate quality indicators for use in nursing home performance measurement systems.

Aiming at the interferometric inverse synthetic aperture radar (InISAR) imaging in the presence of squint, we investigate the influence of squint on the InISAR imaging. First, coupling of the squint additive phase and the target azimuth/altitude coordinates to be solved may make the solution more difficult. Second, the squint angle may lead to estimation error of the vertical coordinates and distortion of the ultimate image. Traditional InISAR imaging algorithms can not solve the above two problems effectively, so we propose a new method which combines the nonlinear least square (NLS) and coordinates transform (CT) to estimate the target coordinates, and a three-dimensional (3-D) image consistent with the real target is obtained accordingly. Simulations show that the proposed method is effective for the squint-mode InISAR imaging. interferometric inverse synthetic aperture radar (InISAR), three dimensional (3-D) imaging, squint mode, nonlinear least square (NLS), coordinates transform (CT)Citation:Liu C L, He F, Gao X Z, et al. Squint-mode InISAR imaging based on nonlinear least square and coordinates transform.