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Bundling function

A rather general class of such functions will be called bundling functions. There are subclasses with additional properties, too. For precise definitions and constructions, see Chapter 8. [Pg.143]

Similar to the situation with fail-stop signature schemes, this construction is not compulsory, important building blocks are bundling functions, and all existing schemes are based on constructions for signing only one message block. For more details, see [ChHP92]. [Pg.146]

Definition 8.29. A collision-intractable family of bundling functions... [Pg.246]

The bundling homomorphisms, which are defined next, are basically bundling functions that are homomorphisms. [Pg.247]

Definition S.30. A coliision-intractabie family of bundling homomorphisms is a collision-intractable family of bundling functions with the following additional properties and components ... [Pg.247]

The definition is quite similar to that of bundling functions, except that one must decide what can be hidden by the hiding function. The following definition is very general in this respect There is an arbitrary family of domains Sg, i.e., what can be hidden may depend on the key. [Pg.247]

Construction 8.56. Let a weak claw-intractable family of permutation pairs be given (see Definition 8.27). The corresponding family of iterated permutations as bundling functions is defined by the following components, which are written with an asterisk to distinguish them from the components of the family of permutation pairs ... [Pg.275]

Theorem 8.57 (Iterated permutations as bundling functions). If a strong claw-intractable family of permutation pairs is given. Construction 8.56 defines a collision-intractable family of bundling functions. If the underlying family is weak, all properties except for the bundling property are still guaranteed. ... [Pg.276]

These positional relations of the insertion sites produce the differences of each bundle function and provide a rationale for performing multi-bundle ACL reconstruction. [Pg.18]

Add Bundle function node from the functions palette by selecting Programming Cluster, Class Variant Bimdle. Connect the input terminals of the Bundle function node to the input of the DAQ Assistant2 and output of the DAQ Assistant as shown in the figure. Wire the output of the cluster to the XY graph. [Pg.272]

For the case of intramolecular energy transfer from excited vibrational states, a mixed quantum-classical treatment was given by Gerber et al. already in 1982 [101]. These authors used a time-dependent self-consistent field (TDSCF) approximation. In the classical limit of TDSCF averages over wave functions are replaced by averages over bundles of trajectories, each obtained by SCF methods. [Pg.16]

Some of these software packages also have semiempirical or molecular mechanics functionality. However, the primary strength of each is ah initio calculation. There are also ah initio programs bundled with the Unichem, Spartan, and Hyperchem products discussed previously in this appendix. [Pg.332]

The Cardiac Cycle. The heart (Eig. lb) performs its function as a pump as a result of a rhythmical spread of a wave of excitation (depolarization) that excites the atrial and ventricular muscle masses to contract sequentially. Maximum pump efficiency occurs when the atrial or ventricular muscle masses contract synchronously (see Eig. 1). The wave of excitation begins with the generation of electrical impulses within the SA node and spreads through the atria. The SA node is referred to as the pacemaker of the heart and exhibits automaticity, ie, it depolarizes and repolarizes spontaneously. The wave then excites sequentially the AV node the bundle of His, ie, the penetrating portion of the AV node the bundle branches, ie, the branching portions of the AV node the terminal Purkinje fibers and finally the ventricular myocardium. After the wave of excitation depolarizes these various stmetures of the heart, repolarization occurs so that each of the stmetures is ready for the next wave of excitation. Until repolarization occurs the stmetures are said to be refractory to excitation. During repolarization of the atria and ventricles, the muscles relax, allowing the chambers of the heart to fill with blood that is to be expelled with the next wave of excitation and resultant contraction. This process repeats itself 60—100 times or beats per minute... [Pg.111]

A microscopic description characterizes the structure of the pores. The objective of a pore-structure analysis is to provide a description that relates to the macroscopic or bulk flow properties. The major bulk properties that need to be correlated with pore description or characterization are the four basic parameters porosity, permeability, tortuosity and connectivity. In studying different samples of the same medium, it becomes apparent that the number of pore sizes, shapes, orientations and interconnections are enormous. Due to this complexity, pore-structure description is most often a statistical distribution of apparent pore sizes. This distribution is apparent because to convert measurements to pore sizes one must resort to models that provide average or model pore sizes. A common approach to defining a characteristic pore size distribution is to model the porous medium as a bundle of straight cylindrical or rectangular capillaries (refer to Figure 2). The diameters of the model capillaries are defined on the basis of a convenient distribution function. [Pg.65]

Fig. 2. Electrical resistance as a function of the temperature at the indicated magnetic fields for a bundle of CNTs. The dashed lines separate three temperature ranges, while the continuous curve is a fit using the two-band model for graphite (see inset) with an overlap of 3.7 meV and a Fermi levei right in the middie of the overlap [9]. Fig. 2. Electrical resistance as a function of the temperature at the indicated magnetic fields for a bundle of CNTs. The dashed lines separate three temperature ranges, while the continuous curve is a fit using the two-band model for graphite (see inset) with an overlap of 3.7 meV and a Fermi levei right in the middie of the overlap [9].
Sequence conservation is, in general, much weaker than structural conservation. There are proteins, which are clearly not related in sequence but are closely related in 3D-stmcture and fold, like heamoglobin and myoglobin, which have similar functions. In many proteins, fold elements like 4-helical bundles are repeated. Classifications of known structural folds of proteins are organized in the SCOP or CATH database see e.g., http //scop.mrc-lmb.cam.ac.uk/scop/. [Pg.778]


See other pages where Bundling function is mentioned: [Pg.142]    [Pg.219]    [Pg.241]    [Pg.241]    [Pg.245]    [Pg.252]    [Pg.275]    [Pg.135]    [Pg.55]    [Pg.105]    [Pg.272]    [Pg.235]    [Pg.142]    [Pg.219]    [Pg.241]    [Pg.241]    [Pg.245]    [Pg.252]    [Pg.275]    [Pg.135]    [Pg.55]    [Pg.105]    [Pg.272]    [Pg.235]    [Pg.2315]    [Pg.2649]    [Pg.205]    [Pg.145]    [Pg.151]    [Pg.196]    [Pg.513]    [Pg.84]    [Pg.307]    [Pg.110]    [Pg.474]    [Pg.1043]    [Pg.388]    [Pg.237]    [Pg.363]    [Pg.15]    [Pg.121]    [Pg.120]    [Pg.232]    [Pg.114]    [Pg.766]   
See also in sourсe #XX -- [ Pg.143 , Pg.241 , Pg.246 ]




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