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This article examines the type of economic analyses of capitalism presented by leading exponents of the neoclassical, marxian, Austrian and institutionalist schools of economic thought. Although each school has something to offer, it is argued that all except the institutionalist school are largely insensitive to different types of structure within capitalism and are blind to the cultures and institutions which characterize different kinds of capitalism. This conclusion is reached by addressing three issues: the problem of universal and specific assumptions in economic analysis; the question of "necessary impurities" in an economic system; and the relationship between actor and structure. It is concluded that institutional economics is most sensitive to the immense actual and potential variety within capitalism itself, and recognizes that the development of different capitalist systems can be divergent rather than convergent.
An attempt has been made in this article to critically survey the field of low Reynolds number flows, with particular regard to the hydrodynamic resistance of particles in this regime. A remarkable burgeoning of interest in such problems has occurred wlthin the past decade. Significant advances have been recorded on both the theoretical and experimental sides, with the former gains far outdlstancing the latter m scope. Problems which would have been impossible to solve rigorously before the advent of singular perturbation techniques are now being regularly solved, though hardly in a routine fashion; insight, intuition, inspiration, and ingenuity are still the order of the day. For those interested in direct engineering applications of the material covered by this review, the perspective from which many of the more general results set forth here should be viewed is, perhaps, best illustrated by an example: The resistance of any solid particle to translational and rotational motions in Stokes flow may be completely calculated from knowledge of a set of 21 scalar coefficients (Section II,C,l). While it seems highly improbable to expect that all these coefficients could be experimentally measured in practice, except perhaps in the trivial case of highly symmetrical bodies for which many of the coefficients vanish identically, this does not detract from the conceptual advantages of knowing exactly how much one does not know. Having an ideal goal against which the extent of present knowledge can be gaged permits a rational decision as to how to optimize one's investment of time, effort, and money in the pursuit of additional data. Furthermore, with the development of high-speed digital computers it may soon be possible to calculate all these coefficients for any given body (O 1 b). The general theory provides a rigorous framework into which such knowledge may be embedded. Use of symbolic" drag coefficients" (Section II,C,2) and symbolic heat- and mass-transfer" coefficients" (Section IV,A) furnishes a unique method for describing the intrinsic, interphase transport properties of particles for a wide variety of boundary conditions. Here, the particle resistance is characterized by a partial differential operator that represents its intrinsic resistance to vector or scalar transfer, independently of the physical properties of the fluid, the state of motion of the particle, or of the unperturbed velocity or temperature fields at infinity. Though restricted as yet in applicability, the general ideas underlying the existence of these operators appear capable of extension in a variety of ways. A recurrent theme arising throughout the analysis pertains to the screwlike properties of particles and of their intrinsic right- and left-handedness (Sections II,C, 1; II,C,2; III,C and IV,B). Such properties reflect an inseparable coupling between the translational and rotational motions of the particle. Helicoidally isotropic particles furnish the simplest examples of bodies manifesting screw-like behavior. These particles are isotropic, in that their properties are the same in all directions. Yet they possess a sense, and spin as they settle in a fluid. These id eas are likely to be of interest to microbiologists, biophysicists, geneticists, and others in the life sciences for whom handedness and life are intimately intertwined. The microscopic dimensions of the objects of interest to them insures ipso Jacto that the motion takes place at very small Reynolds numbers. Readers interested in an elementary but broad survey of sense in the physical and biological sciences are referred to Gardner's delightful book "The Ambidextrous Universe" (01). First-order corrections to the Stokes force on a particle, arising from wallor inertial-effects, can be directly expressed in terms of the Stokes force on the body in the absence of such effects. Thus, with regard to wall-effects in the Stokes regime, Eq. (135) expresses the force experienced by a particle falling in, say, a circular cylinder, in terms of the comparable force experienced by the particle when falling with the same velocity and orientation in the unbounded fluid. Equation (139) expresses a similar relationship for the torque on a rotating particle in a circular cylinder, as does Eq. (166) for the first-order interaction between two particles in an unbounded fluid in terms of the properties of the individual particles. Analogously, Eq. (234) expresses the inertial correction to the Stokes drag force in terms of the Stokes force itself. A comparable relationship exists (Section IV, A) between the heat-transfer coefficient at small, nonzero Peelet numbers and the heat-transfer coefficient at zero Peelet number-that is, the coefficient for conduction heat transfer. Finally, Eqs. (78)-(79) (or their symbolic operator counterparts) permit direct calculation of the Stokes force and torque experienced by a particle in an arbitrary field of flow solely from knowledge of the elementary solutions of Stokes equations for translation and rotation of the particle in a fluid at rest at infinity. The utility of already available knowledge is thus greatly extended by the existence of such relations. It permits one whose interests lie entirely in the macroscopic manifestation of the motion, e.g., the force and torque on the body, to bypass the oftentimes difficult problem of obtaining a detailed solution of the equations of motion, and to proceed directly to the computation of the force and torque on the body from the prescribed boundary conditions alone. The calculation is thereby reduced to a quadrature. The contents of this review may be read simultaneously from two different points of view. First and foremost it may be regarded as a compendium of recent advances in low Reynolds number flows. Secondly, from a pedagogic viewpoint it may be profitably used to illustrate the direct application of invariant techniques, that is, vector-polyadic and tensor methods, to a class of physical problems. Because of the relative simplicity and rich variety of physical problems associated with low Reynolds number motions, intuitive arguments may be employed to gain insight into the nature of polyadics and tensors; the role played by the concept of direction as a primitive entity is brought out here to a degree not usually found in standard works on tensor analysis.
Human mimicry
(2009)
Human mimicry is ubiquitous, and often occurs without the awareness of the person mimicking or the person being mimicked. First, we briefly describe some of the major types of nonconscious mimicry -verbal, facial, emotional, and behavioral- and review the evidence for their automaticity. Next, we argue for the broad impact of mimicry and summarize the literature documenting its influence on the mimicry dyad and beyond. This review highlights the moderators of mimicry as well, including the social, motivational, and emotional conditions that foster or inhibit automatic mimicry. We interpret these findings in light of current theories of mimicry. First, we evaluate the evidence for and against mimicry as a communication tool. Second, we review neuropsychological research that sheds light on the question of how we mimic. What is the cognitive architecture that enables us to do what we perceive others do? We discuss a proposed system, the perception-behavior link, and the neurological evidence (Le., the mirror system) supporting it. We will then review the debate on whether mimicry is innate and inevitable. We propose that the architecture enabling mimicry is innate, but that the behavioral mimicry response may actually be (partly) a product of learning or associations. Finally. we speculate on what the behavioral data on mimicry may imply for the evolution of mimicry.
We analyzed the possibility of introducing a single stochastic scaling parameter a to describe the spatial variability of soil hydraulic properties, using the soil hydraulic properties of the Hamra field (Russo and Bresler 1981) and the Panache field (Nielsen, Biggar, and Erh 1973). In the traditional approach (Peck, Luxmoore, and Stolzy 1977; Russo and Bresler 1980; Warrick, Mullen, and Nielsen 1977), sets of scaling factors are estimated from the h(s) and K(s) functions. For "perfectly similar media," the two sets of a should be identical. Even though the sets of a in these studies were found to be correlated (table 2), they possessed different statistical properties, and were not identical. Results of structural analyses of the sets of a from the two fields suggested that the spatial structures of the two a-sets are quite distinct, reflecting the different spadal behavior of the h(θ) and the K(θ) functions. Moreover, there was poor correlation between the uncorrelated residuals of the a-sets, indicating that part of the high correlation between the a-sets found in earlier work must stem from the presence of an undetected drift and from correlation between nearby measurements. Under field conditions, the saturated hydraulic conductivity is controlled by the flow of water through large structural voids (macropores), which drain at very small negative values of water pressure. Because of this, we tried eliminating Ks by using relative hydraulic properties instead of the hydraulic properties themselves to estimate the scaling factor sets. For the Hamra field, for which we assumed that the hydraulic properties could be described by the model of Brooks and Corey (1964), we found the resultant sets of scaling factors to be highly correlated (R2 = 0.996) with the same spatial structure, but with slightly different variance. By examining the relationships between the two a-sets implied by the Brooks and Corey (1964) model we saw that (1) in general, both sets will be functions of the range of water saturation values used to estimate them, (2) the correlation between the two sets can be improved for media with broad pore-size distributions, and (3) the two sets will be identical if and only if the relative hydraulic conductivity function K,.(hr) is described by the deterministic function Kr(hr) = hy -2 ("strictly similar media"). This analysis suggests that, for media that are not well described by Kr = hr -2, a scaling factor would be required in addition to a in order to achieve agreement between scaled values of hr(θ) and Kr(θ) at all points. A general model Kr = hr -η was proposed, with η as a second stochastic scaling factor for media that do not obey the restrictive assumptions of macroscopic Miller similitude. In the Hamra field, this modified scaling procedure produced perfect agreement between the scaling hydraulic properties. In the Panache field, with values of η determined from linear regression analysis of the logarithmic transformations of Kr and h,., agreement was improved considerably between the scaled hydraulic properties as compared to the more restrictive scaling procedure. In contrast to the Hamra field, however, there remained some significant differences between the scaled properties. These differences may have been artifacts of the different methods used to estimate the hIs) and the K(s) functions for the Panache field. The results of our analysis suggest that in any transient transport problem involving both K(s) and h(s), the description of their spatial variability requires the use of at least three stochastic variates-Ks , α, and η-not a alone.