Some Simple Analytics of Trade and Labor Mobility

We study a simple, tractable model of labor adjustment in a trade model that allows us to analyze the economy's dynamic response to trade liberalization. Since it is a neoclassical market-clearing model, we can use duality techniques to study the equilibrium, and despite its simplicity a rich variety of properties emerge. The model generates gross flows of labor across industries, even in the steady state; persistent wage differentials across industries; gradual adjustment to a liberalization; and anticipatory adjustment to a pre-announced liberalization. Pre-announcement makes liberalization less attractive to export-sector workers and more attractive to import-sector workers, eventually making workers unanimous either in favor of or in opposition to liberalization. Based on these results, we identify many pitfalls to conventional methods of empirical study of trade liberalization that are based on static models.

Hierarchy in Gene Expression is Predictive for Adult Acute Myeloid Leukemia

Cancer progresses with a change in the structure of the gene network in normal cells. We define a measure of organizational hierarchy in gene networks of affected cells in adult acute myeloid leukemia (AML) patients. With a retrospective cohort analysis based on the gene expression profiles of 116 acute myeloid leukemia patients, we find that the likelihood of future cancer relapse and the level of clinical risk are directly correlated with the level of organization in the cancer related gene network. We also explore the variation of the level of organization in the gene network with cancer progression. We find that this variation is non-monotonic, which implies the fitness landscape in the evolution of AML cancer cells is nontrivial. We further find that the hierarchy in gene expression at the time of diagnosis may be a useful biomarker in AML prognosis.Comment: 18 pages, 5 figures, to appear in Physical Biolog

Linear and Nonlinear Bullets of the Bogoliubov-de Gennes Excitations

We report on the focalization of Bogoliubov–de Gennes excitations of the nonlinear Schrödinger equation in the defocusing regime (Gross-Pitaevskii equation for repulsive Bose-Einstein condensates) with a spatially modulated periodic potential. Exploiting the modification of the dispersion relation induced by the modulation, we demonstrate the existence of localized structures of the Bogoliubov–de Gennes excitations, in both the linear and nonlinear regimes (linear and nonlinear “bullets”). These traveling Bogoliubov–de Gennes bullets, localized both spatially and temporally in the comoving reference frame, are robust and propagate remaining stable, without spreading or filamentation. The phenomena reported in this Letter could be observed in atomic Bose-Einstein condensates in the presence of a spatially periodic potential induced by an optical lattice.Peer ReviewedPostprint (published version

Opportunistic Self Organizing Migrating Algorithm for Real-Time Dynamic Traveling Salesman Problem

Self Organizing Migrating Algorithm (SOMA) is a meta-heuristic algorithm based on the self-organizing behavior of individuals in a simulated social environment. SOMA performs iterative computations on a population of potential solutions in the given search space to obtain an optimal solution. In this paper, an Opportunistic Self Organizing Migrating Algorithm (OSOMA) has been proposed that introduces a novel strategy to generate perturbations effectively. This strategy allows the individual to span across more possible solutions and thus, is able to produce better solutions. A comprehensive analysis of OSOMA on multi-dimensional unconstrained benchmark test functions is performed. OSOMA is then applied to solve real-time Dynamic Traveling Salesman Problem (DTSP). The problem of real-time DTSP has been stipulated and simulated using real-time data from Google Maps with a varying cost-metric between any two cities. Although DTSP is a very common and intuitive model in the real world, its presence in literature is still very limited. OSOMA performs exceptionally well on the problems mentioned above. To substantiate this claim, the performance of OSOMA is compared with SOMA, Differential Evolution and Particle Swarm Optimization.Comment: 6 pages, published in CISS 201