PubMed · 10103688
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C Leslie. 1990-02-15. Capturing accuracy.. https://pubmed.ncbi.nlm.nih.gov/10103688/
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OBJECTIVE: To study the relation between changes in sperm motion characteristics and sperm binding capacity to the zona pellucida (ZP) after different sperm preparation techniques. DESIGN: Prospective study. SETTING: Andrology laboratory at the Lis Maternity Hospital. PATIENT(S): Sixty-three infertile men. INTERVENTION(S): In vitro preparation of 57 sperm samples by pentoxifylline (PTX), 38 samples by SpermPrep I (SP1), and 27 samples by mini-Percoll (mPER). Sperm preparation was evaluated in comparison with the control washing technique. MAIN OUTCOME MEASURE(S): Motility variables and binding capacity. RESULT(S): Binding capacity after PTX, SP1, and mPER preparation methods was significantly higher compared with the control medium preparation. Computer-assisted sperm analysis (CASA) of sperm motility revealed a significant increase in a number of variables after the different treatments. A statistically significant but low correlation was observed between sperm binding capacity after control swim-up preparation and VAP (r = 0.27) as well as with VSL (r = 0.30). No significant correlations were found between the changes in the CASA and the improved sperm binding to the ZP. CONCLUSION(S): The two biologic effects of binding capacity enhancement and motility features improvement are not related. Furthermore, because the binding assay is highly correlated with fertilization capacity, these alterations in motility, as evidenced by CASA, probably have a minor effect on fertilization in vitro.
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This paper studies the question of lower bounds on the number of neurons and examples necessary to program a given task into feed forward neural networks. We introduce the notion of information complexity of a network to complement that of neural complexity. Neural complexity deals with lower bounds for neural resources (numbers of neurons) needed by a network to perform a given task within a given tolerance. Information complexity measures lower bounds for the information (i.e. number of examples) needed about the desired input-output function. We study the interaction of the two complexities, and so lower bounds for the complexity of building and then programming feed-forward nets for given tasks. We show something unexpected a priori--the interaction of the two can be simply bounded, so that they can be studied essentially independently. We construct radial basis function (RBF) algorithms of order n3 that are information-optimal, and give example applications.