Yellow Perch population assessment in Southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine Yellow Perch year-class strength April 1, 2004 - March 31, 2005

ID: 8528; Annual Report to Division of Fisheries, Illinois Department of Natural Resources; F-123-R-11

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of factors that Determine Yellow Perch Year-Class Strength April 1, 2005 - March 31, 2006

Annual Report, Federal Aid Project F-123-R-12, April 1, 2005 - March 31, 2006

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the Identification Factors that Determine Yellow Perch Year-Class Strength April 1,1997 - March 31, 1998

ID: 8827; issued June 1, 1998

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques April 1, 1995 - March 31, 1996

issued June 1996

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the identification Factors that Determine Yellow Perch Year-Class Strength April 1, 1998 - March 31, 1999

ID: 8863; issued June 1, 1999

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques April 1, 1994 - March 31, 1995

issued June 1995

Yellow Perch Population Assessment in Southwestern Lake Michigan

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: Federal Aid Project F-123 R-16

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2007 – March 31, 2008

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-14

Yellow perch population assessment in southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine yellow perch year-class strength April 1, 2006 – March 31, 2007

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-13

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2008 – June 30, 2009

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: Federal Aid Project F-123 R-15

Yellow Nail Syndrome: Report of Two Cases and a Brief Review of the Current Literature

Yellow Nail Syndrome (YNS) is a rare, and probably misdiagnosed, condition. It must be considered in middle-aged patients with unexplained chronic respiratory manifestations, lymphedema and nail abnormalities. We present two cases of undiagnosed YNS until the current admissions, despite several years of investigation. The authors wish to draw attention to this syndrome, of which diagnosis is clinical and of exclusion.

Map of the business portion of New York City below Madison Square : 1870.

General street map showing wards, piers, pier numbers, and streetcar lines.

Map of the business portion of New York City below Madison Square : 1870.

General street map showing wards, piers, pier numbers, and streetcar lines.

Inverted decoupling internal model control for square stable multivariable time delay systems

This paper presents a new tuning methodology of the main controller of an internal model control structure for n×n stable multivariable processes with multiple time delays based on the centralized inverted decoupling structure. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the specification of the closed-loop requirements is explained. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response. The effectiveness of the method is illustrated through different simulation examples in comparison with other works.