Solving the N-Queens problem with a binary Hopfield-type network

The application of a discrete Hopfield-type neural network to solving the NP-Hard optimization problem — the N-Queens Problem (NQP) — is presented. The applied network is binary, and at every moment each neuron potential is equal to either 0 or 1. The network can be implemented in the asynchronous mode as well as in the synchronous one with n parallel running processors. In both cases the convergence rate is up to 100%, and the experimental estimate of the average computational complexity is polynomial. Based on the computer simulation results and the theoretical analysis, the proper network parameters are established. The behaviour of the network is explained.     

Lipid changes during development of Blastocladiella emersonii

The lipid composition of swimming spores, cysts and five hour germlings was established. Spores utilized triglycerides first, then phospholipids. Upon encystment all glycolipid components decreased, while in germlings the phospholipids, monoglycerides and sterol esters exhibited a marked increase.     

Effect of slide projections and tape-recorded suggestions on thermal biofeedback training

A previous experiment(Herzfeld & Taub, 1977) demonstrated that slide projections and explicit suggestions relating to thermal experiences can significantly augment temperature self-regulations training(.5° F,p<.05). However, the experimental design was thought to result in an underestimate of the magnitude of the effect, since each subject served as his own control and could therefore make use on nonsuggestion training days of material provided on training days. In this experiment, separate groups of subjects either were given feedback combined with the suggestion procedure on each of 8 training days or were given feedback alone. The mean temperature self-regulation of the suggestion group(2.01° F) was significantly better than the self-regulation(.73) of the nonsuggestion group(t test,p<.01).a difference of 1.28° F.