The Twentieth Century Record of Inequality and Poverty in the United States

When the twentieth century is viewed as a whole, no clear trend in income inequality emerges. Inequality was high and rising during the first three decades and peaked during the Depression. It fell sharply during World War II and remained at the lower level in the 1950s and 1960s. From the 1970s through the mid-1990s inequality steadily increased to levels not seen since World War II, though well below those during the first three decades. The rate of poverty exhibited a long-run downward trend from about 60–70 percent in the earlier years of the century to the 12–14 percent range in recent years, with considerable fluctuation around this secular trend. Changes in inequality were produced largely by demographic and technological changes, the growth and decline of various industries, changes in patterns of international trade, cyclical unemployment, and World War II. The primary drivers of the rate of poverty were economic growth and factors that produced changes in income inequality, particularly demographic change and unemployment. Public policy has reduced the market-generated level of inequality, but since 1950 has had little effect on the trend in inequality. Prior to 1950, the growth of government, and particularly the introduction of a broadly based income tax during World War II, coincided with and partly produced the sharp downward shift in inequality of that era. Government had little effect on poverty rates until 1950. Public income transfer programs have reduced poverty rates appreciably in recent decades. Since World War II, when they have been on a large enough scale to matter, changes in tax and transfer policy have tended to reinforce market-generated trends in inequality and poverty rather than offset them.

Geometric Algebra Model of Distributed Representations

Formalism based on GA is an alternative to distributed representation models developed so far --- Smolensky's tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates recognition test results using both inner product and a clipped version of matrix representation. The influence of accidental blade equality on recognition is also studied. Finally, the efficiency of the GA model is compared to that of previously developed models.Comment: 30 pages, 19 figure

Theoretical prediction of multiferroicity in double perovskite Y2_2NiMnO6_6

We put forward double perovskites of the R$_2$NiMnO$_6$ family (with $R$ a rare-earth atom) as a new class of multiferroics on the basis of {\it ab initio} density functional calculations. We show that changing $R$ from La to Y drives the ground-state from ferromagnetic to antiferromagnetic with $\uparrow\uparrow\downarrow\downarrow$ spin patterns. This E$^*$-type ordering breaks inversion symmetry and generates a ferroelectric polarization of few $\mu C/cm^2$. By analyzing a model Hamiltonian we understand the microscopic origin of this transition and show that an external electric field can be used to tune the transition, thus allowing electrical control of the magnetization.Comment: 4 pages, 3 figure

Geometric representations for minimalist grammars

We reformulate minimalist grammars as partial functions on term algebras for strings and trees. Using filler/role bindings and tensor product representations, we construct homomorphisms for these data structures into geometric vector spaces. We prove that the structure-building functions as well as simple processors for minimalist languages can be realized by piecewise linear operators in representation space. We also propose harmony, i.e. the distance of an intermediate processing step from the final well-formed state in representation space, as a measure of processing complexity. Finally, we illustrate our findings by means of two particular arithmetic and fractal representations.Comment: 43 pages, 4 figure

High frequency polarization switching of a thin ferroelectric film

We consider both experimentally and analytically the transient oscillatory process that arises when a rapid change in voltage is applied to a $Ba_xSr_{1-x}TiO_3$ ferroelectric thin film deposited on an $Mg0$ substrate. High frequency ($\approx 10^{8} rad/s$) polarization oscillations are observed in the ferroelectric sample. These can be understood using a simple field-polarization model. In particular we obtain analytic expressions for the oscillation frequency and the decay time of the polarization fluctuation in terms of the material parameters. These estimations agree well with the experimental results

Universal neural field computation

Turing machines and G\"odel numbers are important pillars of the theory of computation. Thus, any computational architecture needs to show how it could relate to Turing machines and how stable implementations of Turing computation are possible. In this chapter, we implement universal Turing computation in a neural field environment. To this end, we employ the canonical symbologram representation of a Turing machine obtained from a G\"odel encoding of its symbolic repertoire and generalized shifts. The resulting nonlinear dynamical automaton (NDA) is a piecewise affine-linear map acting on the unit square that is partitioned into rectangular domains. Instead of looking at point dynamics in phase space, we then consider functional dynamics of probability distributions functions (p.d.f.s) over phase space. This is generally described by a Frobenius-Perron integral transformation that can be regarded as a neural field equation over the unit square as feature space of a dynamic field theory (DFT). Solving the Frobenius-Perron equation yields that uniform p.d.f.s with rectangular support are mapped onto uniform p.d.f.s with rectangular support, again. We call the resulting representation \emph{dynamic field automaton}.Comment: 21 pages; 6 figures. arXiv admin note: text overlap with arXiv:1204.546

Ground State of Relaxor Ferroelectric Pb(Zn1/3Nb2/3)O3Pb(Zn_{1/3}Nb_{2/3})O_3

High energy x-ray diffraction measurements on Pb(Zn$_{1/3}$Nb$_{2/3}$)O$_3$ (PZN) single crystals show that the system does not have a rhombohedral symmetry at room temperature as previously believed. The new phase (X) in the bulk of the crystal gives Bragg peaks similar to that of a nearly cubic lattice with a slight tetragonal distortion. The Bragg profile remains sharp with no evidence of size broadening due to the polar micro crystals (MC). However, in our preliminary studies of the skin, we have found the expected rhombohedral (R) phase as a surface state. On the other hand, studies on an electric-field poled PZN single crystal clearly indicate a rhombohedral phase at room temperature.Comment: 11 pages with 3 figure

Tensors and compositionality in neural systems

Neither neurobiological nor process models of meaning composition specify the operator through which constituent parts are bound together into compositional structures. In this paper, we argue that a neurophysiological computation system cannot achieve the compositionality exhibited in human thought and language if it were to rely on a multiplicative operator to perform binding, as the tensor product (TP)-based systems that have been widely adopted in cognitive science, neuroscience and artificial intelligence do. We show via simulation and two behavioural experiments that TPs violate variable-value independence, but human behaviour does not. Specifically, TPs fail to capture that in the statements fuzzy cactus and fuzzy penguin, both cactus and penguin are predicated by fuzzy(x) and belong to the set of fuzzy things, rendering these arguments similar to each other. Consistent with that thesis, people judged arguments that shared the same role to be similar, even when those arguments themselves (e.g., cacti and penguins) were judged to be dissimilar when in isolation. By contrast, the similarity of the TPs representing fuzzy(cactus) and fuzzy(penguin) was determined by the similarity of the arguments, which in this case approaches zero. Based on these results, we argue that neural systems that use TPs for binding cannot approximate how the human mind and brain represent compositional information during processing. We describe a contrasting binding mechanism that any physiological or artificial neural system could use to maintain independence between a role and its argument, a prerequisite for compositionality and, thus, for instantiating the expressive power of human thought and language in a neural system

Modeling of dielectric hysteresis loops in ferroelectric semiconductors with charged defects

We have proposed the phenomenological description of dielectric hysteresis loops in ferroelectric semiconductors with charged defects and prevailing extrinsic conductivity. Exactly we have modified Landau-Ginsburg approach and shown that the macroscopic state of the aforementioned inhomogeneous system can be described by three coupled equations for three order parameters. Both the experimentally observed coercive field values well below the thermodynamic one and the various hysteresis loop deformations (constricted and double loops) have been obtained in the framework of our model. The obtained results quantitatively explain the ferroelectric switching in such ferroelectric materials as thick PZT films.Comment: 21 pages, 10 figures, sent to Journal of Physics: Condensed Matte