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Hellkamp, J, Christ, B, Bastian, H, Jungermann, K (1991) Modulation by oxygen of the glucagon-dependent activation of the phosphoenolpyruvate carboxykinase gene in rat hepatocyte cultures Eur J Biochem 198(3): 635 639 Hern, DL, and Hubbell, JA (1998) Incorporation of adhesion peptides into nonadhesive hydrogels useful for tissue resurfacing J Biomed Mater Res 39(2): 266 276 Hersel, U, Dahmen, C, Kessler, H (2003) RGD modi ed polymers: biomaterials for stimulated cell adhesion and beyond Biomaterials 24(24): 4385 4415 Higgins, GM, and Anderson, RM (1931) Experimental pathology of the liver I: restoration of the liver of the white rat following partial surgical removal Arch Pathol 12: 186 202 Holzer, C, and Maier, P (1987) Maintenance of periportal and pericentral oxygen tensions in primary rat hepatocyte cultures: in uence on cellular DNA and protein content monitored by ow cytometry J.



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Alice and Bob share ya and yb with each other over the open, nonsecure channel Alice computes k = ybxa mod n and Bob computes k = yaxb mod n The magical thing about Diffie-Hellman is k = k because k = k = g(xa)(xb) mod n Even though the attacker knows the values for n, g, ya, and yb because he or she does not know the value for either xa or xb, the attacker cannot compute the key You need to know one of those values for the equation to work Bob and Alice just exchanged a key over an open, nonsecure channel Welcome to the wonderful world of crypto Take a look at another example Alice and Bob assign values to g and n (g = 2 and n = 3) and send them over the Internet where Eve can also intercept them.





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In the following table you can see what information is needed for this algorithm to work The table shows what information Alice knows, what Bob knows, and what Eve knows at each of the four steps in this process Step 1: Alice picks a value of 2 for xa, and Bob picks a value of 3 for xb; they do not share these values with anyone..

The currentList function converts the user s selection index in the list (1 through 5) into the name of a category. Note that this is similar to, but not the same as, the lookup performed by urlForCurrentList.

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Cell Physiol 133(2): 297 304 Huang, LE, Arany, Z, Livingston, DM, Bunn, HF (1996) Activation of hypoxia-inducible transcription factor depends primarily upon redox-sensitive stabilization of its alpha subunit J Biol Chem 271(50): 32,253 32,259 Isom, HC, Secott, T, Georgoff, I, Woodworth, C, Mummaw, J (1985) Maintenance of differentiated rat hepatocytes in primary culture Proc Natl Acad Sci USA 82(10): 3252 3256 Jakab, K, Neagu, A, Mironov, V, Markwald, RR, Forgacs, G (2004) Engineering biological structures of prescribed shape using self-assembling multicellular systems Proc Natl Acad Sci USA 101(9): 2864 2869 Jirtle, RL, and Michalopoulos, G (1982) Effects of partial hepatectomy on transplanted hepatocytes Cancer Res 42(8): 3000 3004 Joseph, B, Malhi, H, Bhargava, KK, Palestro, CJ, McCuskey, RS, Gupta, S.

that guarantees that the memory depth (the length of the moving window) will not be less than the minimum Mmin. This ensures credible estimation of the inverse covariance and also that the clusters will be continually updated with new data. The clusters de ned by the similarity relationship (12.35) can be viewed as sets of points that are characterized with their sample means, covariance matrices, and radii x 2 . We can extend those clusters by assigning additional data points that belong to them n;b with degrees of fuzzy membership corresponding to their similarities to the identi ed cluster centers. We can use either the Mahalanobis distance (12.36) or the Mahalanobislike distance as in the original GK algorithm:

It exploits a multimodel architecture with a one-versus-rest classi cation approach. It performs an evolving regression modeling for each class separately with the usage of FLEXFIS exploiting rst-order TSK fuzzy models and based on indicator vectors. In this sense, the evolution of every submodel has the same characteristics (with convergence to optimality, etc.), as pointed out in section 5.2. It does not suffer from the masking problem in case of multiple classes, as opposed to linear regression by indicator matrix. It has the exibility to include upcoming new classes during online operation mode on demand by opening up a new rst-order TSK fuzzy submodel and, hence, without disturbing already-trained fuzzy models.

The conceptual model presented here is surely not complete, and many avenues exist for further discussion and indeed further conceptual development For example, this chapter included little attention to the issue of how new goals.

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