Marx, Globalization, and the Falling Rate of Profit: A Critical Study.

This paper argues that Marx’s views on globalization and its supposed inevitability underwent a substantial evolution and revision after the publication of the Communist Manifesto. His writings relating to India, and particularly China and Russia, show that he was no longer certain that “the country that is more developed industrially only shows, to the less developed, the image of its own future” (Vol. I, p. 13). In the case of China, a prime example of the Asiatic mode of production, Marx even doubted whether globalization (capitalism) would ever be able to accomplish its historical mission of developing the forces of production and creating the material conditions for a higher mode of production, viz., Communism. While in the Russian case, he seriously entertained the notion that it could bypass the hardships and vicissitudes of capitalism and forge its own unique path to socialism. If accepted, this interpretation represents a serious challenge to the universality and validity of Marx’s materialist conception of history. The paper also addresses the role of the law of the tendency of the falling rate of profit in the geographic expansion of competitive capitalism. It contends that Marx did not believe there was an iron-clad connection between the falling rate of profit and globalization; in addition, it argues that Marx believed that the capitalists’ insatiable search for colonial markets was driven by their desire to overcome recurrent (and growing) realization problems in the home market arising from deficient aggregate demand on the part of both workers and capitalists.Asiatic Mode of Production, Globalization, Law of the Falling Tendency of the Rate of Profit, Materialist Conception of History, Underconsumptionist Tendencies.

Precession and Recession of the Rock'n'roller

We study the dynamics of a spherical rigid body that rocks and rolls on a plane under the effect of gravity. The distribution of mass is non-uniform and the centre of mass does not coincide with the geometric centre. The symmetric case, with moments of inertia I_1=I_2, is integrable and the motion is completely regular. Three known conservation laws are the total energy E, Jellett's quantity Q_J and Routh's quantity Q_R. When the inertial symmetry I_1=I_2 is broken, even slightly, the character of the solutions is profoundly changed and new types of motion become possible. We derive the equations governing the general motion and present analytical and numerical evidence of the recession, or reversal of precession, that has been observed in physical experiments. We present an analysis of recession in terms of critical lines dividing the (Q_R,Q_J) plane into four dynamically disjoint zones. We prove that recession implies the lack of conservation of Jellett's and Routh's quantities, by identifying individual reversals as crossings of the orbit (Q_R(t),Q_J(t)) through the critical lines. Consequently, a method is found to produce a large number of initial conditions so that the system will exhibit recession

Economic and Institutional Determinants of FDI Flows to Latin America: A Panel Study

This paper estimates a pooled (fixed-effects) FDI investment function that seeks to identify some of the major economic and institutional determinants of FDI flows to nine major Latin American countries during the 1980-2001 period. First, it develops a conceptual framework of analysis that seeks to identify some of the major economic and institutional determinants of FDI. Second, the paper gives an overview of FDI flows to Latin America during the 1990-2006 period, with particular emphasis on their contribution to the financing of gross capital formation. Third, an empirical model for FDI flows to Latin America is outlined and an economic rationale is provided for the included variables and their expected signs. Fourth, the estimates from a panel regression designed to explain the variation in FDI flows to Latin America during the 1980-2001 period suggests that market size (proxied by real GDP), credit provided by the private banking sector, government expenditures on education, the real exchange rate, and the level of economic freedom have a positive and significant effect. On the other hand, public investment spending, the debt-service ratio, and the volatility of the real exchange rate have a negative and significant effect on FDI flows. The panel unit root tests on the residuals of the relevant panel regressions also suggest that there is a stable, long-term relationship among the included variables; i.e., the selected variables in the reported regressions are cointegrated over the relevant time period. Finally, the paper summarizes the major findings and offers some policy prescriptions for attracting FDI flows to the region and enhancing their positive direct and indirect effectsADF Fisher statistic. Economic Freedom Index (EFI), Foreign Direct Investment (FDI), Latin America, Panel Unit Root Tests, Pedroni Residual Cointegration Test, Pooled Regression, and Seemingly Unrelated Regression (SUR)

Complete classification of discrete resonant Rossby/drift wave triads on periodic domains

We consider the set of Diophantine equations that arise in the context of the barotropic vorticity equation on periodic domains, when nonlinear wave interactions are studied to leading order in the amplitudes. The solutions to this set of Diophantine equations are of interest in atmosphere (Rossby waves) and Tokamak plasmas (drift waves), because they provide the values of the spectral wavevectors that interact resonantly via three-wave interactions. These come in "triads", i.e., groups of three wavevectors. We provide the full solution to the Diophantine equations in the case of infinite Rossby deformation radius. The method is completely new, and relies on mapping the unknown variables to rational points on quadratic forms of "Minkowski" type. Classical methods invented centuries ago by Fermat, Euler, Lagrange and Minkowski, are used to classify all solutions to our original Diophantine equations, thus providing a computational method to generate numerically all the resonant triads in the system. Our method has a clear computational advantage over brute-force numerical search: on a 10000^2 grid, the brute-force search would take 15 years using optimised C++ codes, whereas our method takes about 40 minutes. The method is extended to generate quasi-resonant triads, which are defined by relaxing the resonant condition on the frequencies, allowing for a small mismatch. Quasi-resonances are robust with respect to physical perturbations, unlike exact resonances. Therefore, the new method is really valuable in practical terms. We show that the set of quasi-resonances form an intricate network of clusters of connected triads, whose structure depends on the value of the allowed mismatch. We provide some quantitative comparison between the clusters' structure and the onset of fully nonlinear turbulence in the barotropic vorticity equation, and provide perspectives for new research.Comment: Improved version, accepted in Commun. Nonlinear Sci. Numer. Simula

Image Encryption Using Elliptic Curves and Rossby/Drift Wave Triads

We propose an image encryption scheme based on quasi-resonant Rossby/drift wave triads (related to elliptic surfaces) and Mordell elliptic curves (MECs). By defining a total order on quasi-resonant triads, at a first stage we construct quasi-resonant triads using auxiliary parameters of elliptic surfaces in order to generate pseudo-random numbers. At a second stage, we employ an MEC to construct a dynamic substitution box (S-box) for the plain image. The generated pseudo-random numbers and S-box are used to provide diffusion and confusion, respectively, in the tested image. We test the proposed scheme against well-known attacks by encrypting all gray images taken from the USC-SIPI image database. Our experimental results indicate the high security of the newly developed scheme. Finally, via extensive comparisons we show that the new scheme outperforms other popular schemes.Comment: Accepted and published version (Entropy 2020, 22, 454

Equation of state of metallic hydrogen from Coupled Electron-Ion Monte Carlo simulations

We present a study of hydrogen at pressures higher than molecular dissociation using the Coupled Electron-Ion Monte Carlo method. These calculations use the accurate Reptation Quantum Monte Carlo method to estimate the electronic energy and pressure while doing a Monte Carlo simulation of the protons. In addition to presenting simulation results for the equation of state over a large region of phase space, we report the free energy obtained by thermodynamic integration. We find very good agreement with DFT calculations for pressures beyond 600 GPa and densities above $\rho=1.4 g/cm^3$. Both thermodynamic as well as structural properties are accurately reproduced by DFT calculations. This agreement gives a strong support to the different approximations employed in DFT, specifically the approximate exchange-correlation potential and the use of pseudopotentials for the range of densities considered. We find disagreement with chemical models, which suggests a reinvestigation of planetary models, previously constructed using the Saumon-Chabrier-Van Horn equations of state.Comment: 9 pages, 7 figure

Lautum Regularization for Semi-supervised Transfer Learning

Transfer learning is a very important tool in deep learning as it allows propagating information from one "source dataset" to another "target dataset", especially in the case of a small number of training examples in the latter. Yet, discrepancies between the underlying distributions of the source and target data are commonplace and are known to have a substantial impact on algorithm performance. In this work we suggest a novel information theoretic approach for the analysis of the performance of deep neural networks in the context of transfer learning. We focus on the task of semi-supervised transfer learning, in which unlabeled samples from the target dataset are available during the network training on the source dataset. Our theory suggests that one may improve the transferability of a deep neural network by imposing a Lautum information based regularization that relates the network weights to the target data. We demonstrate the effectiveness of the proposed approach in various transfer learning experiments