Ultrastructure of the Interface Between Stages of Eimeria funduli/i> (Apicomplexa) and Hepatocytes of the Longnose Killifish, Fundulus similis

The interface between stages of Eimeria funduli and hepatocytes of the experimentally infected killifish Fundulus similis was studied ultrastructurally. Parasitophorous vacuoles (PV's) in which meronts, macrogamonts, and microgamonts developed were lined by an inner, smooth membrane and an outer, ribosome-studded membrane. The outer membrane bordered on the cytoplasm of the host cell, whereas the inner one limited the PV. The origins of these membranes have not been determined with certainty, but images were observed in which both membranes appeared to be continuous with the outer nuclear membrane of the host cell. Furthermore, the outer PV membrane was continuous with membranes of rough endoplasmic reticulum in the host cell. For stages which were rapidly growing or differentiating, the inner membrane blebbed into the PV. Blebbing ceased and ribosomes detached from the outer membrane after maturation of the meront or fertilization of the macrogamont. Blebbing appears to be a mechanism by which nutrients transfer from the host to the parasite. During sporogony, the inner PV membrane acquired a thin layer of electron dense material, but otherwise membranes lining the PV remained intact. The two PV membranes, probably together with dense material of parasitic origin lining the inner membrane, appear to serve as the oocyst wall enclosing the sporocysts until they are released in the intermediate host.

Applications of Linear Programming to Coding Theory

Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.