LATE TRIASSIC OBLIQUE EXTRUSION OF UHP/HP COMPLEXES IN THE ATBASHI ACCRETIONARY COMPLEX OF SOUTH TIANSHAN, KYRGYZSTAN

The exhumation and tectonic emplacement of eclogites and blueschists take place in forearc accretionary complexes by either forearc- or backarc-directed extrusion, but few examples have been well analysed in detail. Here we present an example of oblique wedge extrusion of UHP/HP rocks in the Atbashi accretionary complex of the Kyrgyz South Tianshan.The exhumation and tectonic emplacement of eclogites and blueschists take place in forearc accretionary complexes by either forearc- or backarc-directed extrusion, but few examples have been well analysed in detail. Here we present an example of oblique wedge extrusion of UHP/HP rocks in the Atbashi accretionary complex of the Kyrgyz South Tianshan

Order Statistics Approaches to Unobserved Heterogeneity in Auctions

We establish nonparametric identification of auction models with continuous and nonseparable unobserved heterogeneity using three consecutive order statistics of bids. We then propose sieve maximum likelihood estimators for the joint distribution of unobserved heterogeneity and the private value, as well as their conditional and marginal distributions. Lastly, we apply our methodology to a novel dataset from judicial auctions in China. Our estimates suggest substantial gains from accounting for unobserved heterogeneity when setting reserve prices. We propose a simple scheme that achieves nearly optimal revenue by using the appraisal value as the reserve price

Ultrafast fluorescent decay induced by metal-mediated dipole-dipole interaction in two-dimensional molecular aggregates

Two-dimensional molecular aggregate (2DMA), a thin sheet of strongly interacting dipole molecules self-assembled at close distance on an ordered lattice, is a fascinating fluorescent material. It is distinctively different from the single or colloidal dye molecules or quantum dots in most previous research. In this paper, we verify for the first time that when a 2DMA is placed at a nanometric distance from a metallic substrate, the strong and coherent interaction between the dipoles inside the 2DMA dominates its fluorescent decay at picosecond timescale. Our streak-camera lifetime measurement and interacting lattice-dipole calculation reveal that the metal-mediated dipole-dipole interaction shortens the fluorescent lifetime to about one half and increases the energy dissipation rate by ten times than expected from the noninteracting single-dipole picture. Our finding can enrich our understanding of nanoscale energy transfer in molecular excitonic systems and may designate a new direction for developing fast and efficient optoelectronic devices.Comment: 9 pages, 6 figure

Space-Time Fading Correlation Functions of a 3-D MIMO Channel Model

Space-time correlation functions between the links of MIMO Rayleigh fading channels are derived using a new three-dimensional (3-D) cylinder scattering model. Closed form, mathematically tractable formulas are obtained for the space-time correlation functions for general MIMO systems where the base station and mobile station antennas may be arranged in 3-D space. It is shown that the correlation functions computed by the 3-D cylinder model are of significant difference than those of the conventional 2-D Clarke\u27\u27s isotropic scattering model for vertically placed antennas. The general formulas of the correlation functions includes the 2-D Clarke\u27\u27s model and the 3-D SIMO, MISO models as special cases

Does China’s increasing coupling of ‘urban population’ and ‘urban area’ growth indicators reflect a growing social and economic sustainability?

Over the last four decades, China has experienced rapid parallel economic development and urbanization, leading to internal mass -migrations of its people from increasingly marginalized rural areas to urban centers where job opportunities and wealth are now concentrated. We compare the relative temporal growth trends in population-related and land-(i.e., area-) related urbanization systems to evaluate China's urbanization in the context of the ‘New-Type’ Urbanization Program (2014–2020). Based on coupling coordination models, we observed that the two systems were overall slightly decoupled since spatial urban expansion commonly outgrew urban population growth, but the degree of coordination between the two parameters was increasing. Employing exploratory spatial data analysis, we revealed that a high degree of coupling coordination has spread from Eastern to Western provinces. Urban planning and land policies have contributed to an increasing urban vegetation cover and the control of excessive urban land expansions. While China's urbanization appears to have become increasingly sustainable due to the increasing degree of coupling coordination between its subsystems, ongoing urban expansions require strong oversight to limit the environmental impacts of the country's sprawling mega-cities

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This progress has been accompanied by an exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extract information from atomically resolved images including location of the atomic species and type of defects. We develop a 'weakly-supervised' approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular 'rotor'. This deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data