Intercity Trade and the Industrial Diversification of Cities

The industrial diversification of cities is explained without imposing linkages among industries. In each of two city-industries, a manufacture is produced competitively as the final good using labor and industry- specific differentiated services. Manufacturers import the services of their industry from all cities that produce them, since their technology favors variety. In specialized cities, the city-industry is large and many services are locally available but the two manufactures have to be traded among cities. In diversified cities the two manufactures are produced in the same city, and each industry crowds out half the local services of the other, but manufactures need not be imported. A lower cost of trading manufactures (e.g. railroads and intercity highways) favors a system of specialized cities, while a lower cost of trading services (e.g. telephone, the Internet) favors a system of diversified cities since the latter cities rely more on imported services, having fewer locally. A larger cost-share of services favors specialization, and high intracity commuting cost and population growth favor diversification.Trade, diversification, specialization, city systems

Time-dependent Aharonov-Bohm effect on the noncommutative space

We study the time-dependent Aharonov-Bohm effect on the noncommutative space. Because there is no net Aharonov-Bohm phase shift in the time-dependent case on the commutative space, therefore, a tiny deviation from zero indicates new physics. Based on the Seiberg-Witten map we obtain the gauge invariant and Lorentz covariant Aharonov-Bohm phase shift in general case on noncommutative space. We find there are two kinds of contribution: momentum-dependent and momentum-independent corrections. For the momentum-dependent correction, there is a cancellation between the magnetic and electric phase shifts, just like the case on the commutative space. However, there is a non-trivial contribution in the momentum-independent correction. This is true for both the time-independent and time-dependent Aharonov-Bohm effects on the noncommutative space. However, for the time-dependent Aharonov-Bohm effect, there is no overwhelming background which exists in the time-independent Aharonov-Bohm effect on both commutative and noncommutative space. Therefore, the time-dependent Aharonov-Bohm can be sensitive to the spatial noncommutativity. \draftnote{The net correction is proportional to the product of the magnetic fluxes through the fundamental area represented by the noncommutative parameter $\theta$, and through the surface enclosed by the trajectory of charged particle.} More interestingly, there is an anti-collinear relation between the logarithms of the magnetic field $B$ and the averaged flux $\Phi/N$ (N is the number of fringes shifted). This nontrivial relation can also provide a way to test the spatial noncommutativity. For $B\Phi/N\sim 1$, our estimation on the experimental sensitivity shows that it can reach the $\rm 10GeV$ scale. This sensitivity can be enhanced by using stronger magnetic field strength, larger magnetic flux, as well as higher experimental precision on the phase shift.Comment: 12 pages, 1 figure; v2, accepted version by PL

A key variant in the cis-regulatory element of flowering gene Ghd8 associated with cold tolerance in rice.

Variations in the gene promoter play critical roles in the evolution of important adaptive traits in crops, but direct links of the regulatory mutation to the adaptive change are not well understood. Here, we examine the nucleotide variations in the promoter region of a transcription factor (Ghd8) that control grain number, plant height and heading date in rice. We find that a dominant promoter type of subspecies japonica displayed a high activity for Ghd8 expression in comparison with the one in indica. Transgenic analyses revealed that higher expression levels of Ghd8 delayed heading date and enhanced cold tolerance in rice. Furthermore, a single-nucleotide polymorphism (T1279G) at the position -1279 bp that locates on the potential GA-responsive motif in the Ghd8 promoter affected the expression of this gene. The 1279 T variant has elevated expression of Ghd8, thus conferring increased cold tolerance of rice seedlings. Nucleotide diversity analysis revealed that the approximately 25-kb genomic region surrounding Ghd8 in the subspecies japonica was under significant selection pressure. Our findings demonstrate that the join effects of the regulatory and coding variants largely contribute to the divergence of japonica and indica and increase the adaptability of japonica to the cold environment

Changes from Classical Statistics to Modern Statistics and Data Science

A coordinate system is a foundation for every quantitative science, engineering, and medicine. Classical physics and statistics are based on the Cartesian coordinate system. The classical probability and hypothesis testing theory can only be applied to Euclidean data. However, modern data in the real world are from natural language processing, mathematical formulas, social networks, transportation and sensor networks, computer visions, automations, and biomedical measurements. The Euclidean assumption is not appropriate for non Euclidean data. This perspective addresses the urgent need to overcome those fundamental limitations and encourages extensions of classical probability theory and hypothesis testing , diffusion models and stochastic differential equations from Euclidean space to non Euclidean space. Artificial intelligence such as natural language processing, computer vision, graphical neural networks, manifold regression and inference theory, manifold learning, graph neural networks, compositional diffusion models for automatically compositional generations of concepts and demystifying machine learning systems, has been rapidly developed. Differential manifold theory is the mathematic foundations of deep learning and data science as well. We urgently need to shift the paradigm for data analysis from the classical Euclidean data analysis to both Euclidean and non Euclidean data analysis and develop more and more innovative methods for describing, estimating and inferring non Euclidean geometries of modern real datasets. A general framework for integrated analysis of both Euclidean and non Euclidean data, composite AI, decision intelligence and edge AI provide powerful innovative ideas and strategies for fundamentally advancing AI. We are expected to marry statistics with AI, develop a unified theory of modern statistics and drive next generation of AI and data science.Comment: 37 page