Using Relevance to Reduce Network Size Automatically

This paper proposes a means of using the knowledge in a network to determine the functionality or relevance of individual units, both for the purpose of understanding the network's behavior and improving its performance. The basic idea is to iteratively train the network to a certain performance criterion, compute a measure of relevance that identifies which input or hidden units are most critical to performance, and automatically remove the least relevant units. This skeletonization technique can be used to simplify networks by eliminating units that convey redundant information; to improve learning performance by first learning with spare hidden units and then removing the unnecessary ones, thereby constraining generalization; and to understand the behavior of networks in terms of minimal ‘rules’.     

THREE MODELS OF CLINICAL JUDGMENT.

3 SIMULATION MODELS WERE APPLIED TO CLINICAL JUDGMENTS OF "PSYCHOTIC" VS. "NEUROTIC" FOR 29 JUDGES ACROSS 7 SAMPLES OF MMPI PROFILES. A CROSS-VALIDATED MULTIPLE CORRELATION WAS USED AS A GOODNESS-OF-FIT MEASURE FOR THE 3 JUDGMENT MODELS. ON THIS BASIS, EACH OF THE 29 CLINICAL JUDGES WAS CHARACTERIZED AS BEING EITHER "LINEAR" OR "CONFIGURAL" IN HIS UTILIZATION OF MMPI TEST DATA, WHERE CONFIGURALITY WAS OPERATIONALLY DEFINED BY THE FIT OF THE DATA TO A MODEL EMPLOYING CONFIGURAL, OR PATTERNED, VARIABLES. IT WAS SHOWN THAT CONFIGURALITY WAS A CONSISTENT JUDGMENTAL CHARACTERISTIC DISTINGUISHING 16 OF THE JUDGES, BUT THIS CHARACTERISTIC WAS UNRELATED TO BOTH ACCURACY AND AMOUNT OF CLINICAL TRAINING. ALSO, JUDGES, AS A GROUP, TENDED TO CHANGE THEIR MANNER OF JUDGMENT WITH CHANGES IN SAMPLES OF MMPI PROFILES. (15 REF.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

INFLUENCE OF CONTROLLED MICROBIAL CURING ON PORCINE MUSCLE

SUMMARY— A previously developed technique was adopted to study the influence of certain microbiological populations and their effects on processed meat. The technique consisted of an initial reduction of surface bacteria on conventionally handled muscle tissue via a hot water dip, followed by processing at 28° C in a sterile plastic isolator where Pediococcus cerevisiae was introduced into the curing solution. This treatment was compared to reduced initial count and conventional samples. Identification of the bacteria in the curing solution of each treatment indicated that a Lactobacillus spp. was predominant in the reduced initial count treatment. The inoculated Podiococcus cerevisiae was predominant in the reduced initial count inoculated treatment white Staphylococcus epidermidis and Flavobacterium diffusum were predominant in the conventional treatment depending upon the trial. Tenderness and bacterial load were significantly (P < .01) increased by treatment while pH was significantly (P < .01) decreased. Oxidation and muscle composition were not affected by treatment. Samples from all treatments were acceptable organoleptically.     

Effect of Partial Phytate Removal and Heat upon Iron Bioavailability from Soy Protein-Based Diets

The effect of heat and partial phytate removal upon in vivo iron bioavailability from soy protein was studied by chick hemoglobin repletion. Iron repletion diets were formulated with unheated and heated soy protein isolates and phytate-reduced soy protein isolates, with and without iron supplementation. Heating at 120°C for 20 min, 75% phytate reduction and 20 mg/kg iron supplementation improved iron bioavailability by 65-77%, 6-11% and 10-17%, respectively. These beneficial effects were interpreted in terms of promoting protein and protein-Fe-phytate complex digestion and release of endogenous and added iron.     

NUTRITIVE VALUE OF A FIBER-FREE COCONUT PROTEIN EXTRACT OBTAINED BY AN ENZYMIC-CHEMICAL METHOD

The fiber-free coconut extract obtained by an enzymic-chemical method (J. Food Sci. 38: 607) proved to have a higher protein nutritive value than that of the original coconut meal. The improvement is attributable in part to the fact that the fiber of unmodified coconut meal has an unfavorable effect on the nutritive value of coconut protein. Amino acid analysis revealed that the extracted protein had a higher total essential amino acid content including a higher lysine content and a higher lysineto-arginine ratio than the original coconut meal.     

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