Whaling error

You published recently (Nature 374, 587; 1995) a report headed "Error re-opens 'scientific' whaling debate". The error in question, however, relates to commercial whaling, not to scientific whaling. Although Norway cites science as a basis for the way in which it sets its own quota. scientific whaling means something quite different. namely killing whales for research purposes. Any member of the International Whaling Commission (IWC) has the right to conduct a research catch under the International Convention for the Regulation of Whaling. 1946. The IWC has reviewed new research or scientific whaling programs for Japan and Norway since the IWC moratorium on commercial whaling began in 1986. In every case, the IWC advised Japan and Norway to reconsider the lethal aspects of their research programs. Last year, however, Norway started a commercial hunt in combination with its scientific catch, despite the IWC moratorium.

Cetacean Notes. I. Sei and Rorqual Whales on the Mississippi Coast, a Correction. II. A Dwarf Sperm Whale in Mississippi Sound and Its Helminth Parasites

I. Gunter and Christmas (1973) described the events leading to the stranding of a baleen whale on Ship Island, Mississippi, in 1968, giving the species as Balaenopteru physalus, the Rorqual. Unfortunately the identification was in error, but fortunately good photographs were shown. The underside of the tail was a splotched white, but there was no black margin. The specimen also had fewer throat and belly grooves than the Rorqual, as a comparison with True’s (1904) photograph shows. Dr. James Mead (in litt.) pointed out that the animal was a Sei Whale, Balaenoptera borealis. This remains a new Mississippi record and according to Lowery’s (1974) count, it is the fifth specimen reported from the Gulf of Mexico. The stranding of a sixth Sei Whale on Anclote Keys in the Gulf, west of Tarpon Springs, Florida on 30 May 1974, was reported in the newspapers and by the Smithsonian Institution (1974). II. Gunter, Hubbs and Beal (1955) gave measurements on a Pygmy Sperm Whale, Kogia breviceps, which stranded on Mustang Island on the Texas coast and commented upon the recorded variations of proportional measurements in this species. Then according to Raun, Hoese and Moseley (1970) these questions were resolved by Handley (1966), who showed that a second species, Kogia simus, the Dwarf Sperm Whale, is also present in the western North Atlantic. Handley’s argument is based on skull comparisons and it seems to be rather indubitable. According to Raun et al. (op. cit.), the stranding of a species of Kogia on Galveston Island recorded by Caldwell, Ingles and Siebenaler (1960) was K. simus. They also say that Caldwell (in litt.) had previously come to the same conclusion. Caldwell et al. also recorded another specimen from Destin, Florida, which is now considered to have been a specimen of simus. The known status of these two little sperm whales in the Gulf is summarized by Lowery (op. cit.).

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.