Effect of Sinusoidal Surface Roughness and Energy on the Orientation of Cylinder-Forming Block Copolymer Thin Films

We explore the relative stability of three possible orientations of cylinder-forming di-block copolymer on a sinusoidally corrugated substrate. The cylinders can be aligned either parallel to the substrate, with their long axis being oriented along or orthogonal to the corrugation trenches, or perpendicular to the substrate. Using self-consistent field theory, we investigate the influence of substrate roughness and surface preference on the phase transition between the three orientations. When the substrate preference, $u$, towards one of components is small, increasing the substrate roughness induces a phase transition from parallel to perpendicular cylindrical phase. However, when $u$ is large, the parallel orientation is more stable than the perpendicular one. Within this parallel phase, increasing the substrate roughness leads to a transition of cylinder orientation changing from being orthogonal to parallel to the trench long axis. Increasing the substrate preference leads to an opposite transition from parallel to orthogonal to the trenches. Furthermore, we predict that the perpendicular cylinder phase is easier to be obtained when the unidirectional corrugation is along the longer unit vector of the hexagonal packing than when it is along the shorter unit vector. Our results qualitatively agree with previous experiments, and contribute towards applications of the cylinder-forming block copolymer in nanotechnology.Comment: 9 pages, 7 figure

Input-Output Analysis, Linear Programming and Modified Multipliers

The input-output (IO) analysis explores changes in final demand through the regional economy using multipliers. However, it isn’t flexible to investigate the regional impact from the capacity limitations which are directly imposed on production, not final demand. This is because the multipliers are changing with exogenous restrictions on production. Conventionally, the IO analysis is performed assuming exogenous production restrictions being the changes in final demands or assuming the sector being exogenous sector like the final demand. If researchers or policy makers are interested in only economic impacts from production restrictions, there is no need to look into the modified multipliers. The modified multipliers should be considered when researchers and policy makers attempt to analyze the compensation of impact, especially recovery of loss using government expenditure. We suggest that the linear programming is a useful and efficient tool to derive modified multipliers and estimate correct regional impact from the policy changes.Input-Output Analysis, Multipliers, Regional Impact Analysis, Community/Rural/Urban Development, C67, R15, R5,

Modeling US Counties’ Innovation Capacity with a Focus on Natural Amenities

Innovation Capacity, Natural Amenity, Community/Rural/Urban Development, O31, Q51,

Quantum-State Engineering of Multiple Trapped Ions for Center-of-Mass Mode

We propose a scheme to generate a superposition with arbitrary coefficients on a line in phase space for the center-of-mass vibrational mode of N ions by means of isolating all other spectator vibrational modes from the center-of-mass mode. It can be viewed as the generation of previous methods for preparing motional states of one ion. For large number of ions, we need only one cyclic operatin to generate such a superposition of many coherent states.Comment: 14 pages, revte

D3P : Data-driven demand prediction for fast expanding electric vehicle sharing systems

The future of urban mobility is expected to be shared and electric. It is not only a more sustainable paradigm that can reduce emissions, but can also bring societal benefits by offering a more affordable on-demand mobility option to the general public. Many car sharing service providers as well as automobile manufacturers are entering the competition by expanding both their EV fleets and renting/returning station networks, aiming to seize a share of the market and to bring car sharing to the zero emissions level. During their fast expansion, one determinant for success is the ability of predicting the demand of stations as the entire system is growing continuously. There are several challenges in this demand prediction problem: First, unlike most of the existing work which predicts demand only for static systems or at few stages of expansion, in the real world we often need to predict the demand as or even before stations are being deployed or closed, to provide information and decision support. Second, for the new stations to be deployed, there is no historical data available to help the prediction of their demand. Finally, the impact of deploying/closing stations on the other stations in the system can be complex. To address these challenges, we formulate the demand prediction problem in the context of fast expanding electric vehicle sharing systems, and propose a data-driven demand prediction approach which aims to model the expansion dynamics directly from the data. We use a local temporal encoding process to handle the historical data for each existing station, and a dynamic spatial encoding process to take correlations between stations into account with Graph Convolutional Neural Networks (GCN). The encoded features are fed to a multi-scale predictor, which forecasts both the long-term expected demand of the stations and their instant demand in the near future. We evaluate the proposed approach with real-world data collected from a major EV sharing platform for one year. Experimental results demonstrate that our approach significantly outperforms the state of the art, showing up to three-fold performance gain in predicting demand for the expanding EV sharing systems

Measuring Regional Economic Impacts from Wildfire: Case Study of Southeast Oregon Cattle-Ranching Business

public grazing, regional economic impact, Social Accounting Matrix, Southeast Oregon, wildfire

Hydrodynamic bound states of rotating micro-cylinders in a confining geometry

Many micro-swimmers propel themselves by rotating micro-cylindrical organelles such as flagella or cilia. These cylindrical organelles almost never live in free space, yet their motions in a confining geometry can be counter-intuitive. For example, one of the intriguing yet classical results in this regard is that a rotating cylinder next to a plane wall does not generate any net force in Newtonian fluids and therefore does not translate. In this work, we employ analytical and numerical tools to investigate the motions of micro-cylinders under prescribed torques in a confining geometry. We show that a cylinder pair can form four non-trivial hydrodynamic bound states depending on the relative position within the confinement. Our analysis shows that the distinct states are the results of competing effects of the hydrodynamic interactions within the cylinder pair and between the active cylinders and the confinement.Comment: 10 pages, 6 figure