A Bayesian-Based Approach for Public Sentiment Modeling

Public sentiment is a direct public-centric indicator for the success of effective action planning. Despite its importance, systematic modeling of public sentiment remains untapped in previous studies. This research aims to develop a Bayesian-based approach for quantitative public sentiment modeling, which is capable of incorporating uncertainty and guiding the selection of public sentiment measures. This study comprises three steps: (1) quantifying prior sentiment information and new sentiment observations with Dirichlet distribution and multinomial distribution respectively; (2) deriving the posterior distribution of sentiment probabilities through incorporating the Dirichlet distribution and multinomial distribution via Bayesian inference; and (3) measuring public sentiment through aggregating sampled sets of sentiment probabilities with an application-based measure. A case study on Hurricane Harvey is provided to demonstrate the feasibility and applicability of the proposed approach. The developed approach also has the potential to be generalized to model various types of probability-based measures

Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators

Robust velocity and position estimation is crucial for autonomous robot navigation. The optical flow based methods for autonomous navigation have been receiving increasing attentions in tandem with the development of micro unmanned aerial vehicles. This paper proposes a kernel cross-correlator (KCC) based algorithm to determine optical flow using a monocular camera, which is named as correlation flow (CF). Correlation flow is able to provide reliable and accurate velocity estimation and is robust to motion blur. In addition, it can also estimate the altitude velocity and yaw rate, which are not available by traditional methods. Autonomous flight tests on a quadcopter show that correlation flow can provide robust trajectory estimation with very low processing power. The source codes are released based on the ROS framework.Comment: 2018 International Conference on Robotics and Automation (ICRA 2018

Signatures of Bose-Einstein condensation in an optical lattice

We discuss typical experimental signatures for the Bose-Einstein condensation (BEC) of an ultracold Bose gas in an inhomogeneous optical lattice at finite temperature. Applying the Hartree-Fock-Bogoliubov-Popov formalism, we calculate quantities such as the momentum-space density distribution, visibility and peak width as the system is tuned through the superfluid to normal phase transition. Different from previous studies, we consider systems with fixed total particle number, which is of direct experimental relevance. We show that the onset of BEC is accompanied by sharp features in all these signatures, which can be probed via typical time-of-flight imaging techniques. In particular, we find a two-platform structure in the peak width across the phase transition. We show that the onset of condensation is related to the emergence of the higher platform, which can be used as an effective experimental signature.Comment: 5 pages, 3 figure

Nature of proton transport in a water-filled carbon nanotube and in liquid water

Proton transport (PT) in bulk liquid water and within a thin water-filled carbon nanotube has been examined with ab initio pathintegral molecular dynamics (PIMD). Barrierless proton transfer is observed in each case when quantum nuclear effects (QNEs) are accounted for. The key difference between the two systems is that in the nanotube facile PT is facilitated by a favorable prealignment of water molecules, whereas in bulk liquid water solvent reorganization is required prior to PT. Configurations where the quantum excess proton is delocalized over several adjacent water molecules along with continuous interconversion between different hydration states reveals that, as in liquid water, the hydrated proton under confinement is best described as a fluxional defect, rather than any individual idealized hydration state such as Zundel, Eigen, or the so-called linear H7O3+ complex along the water chain. These findings highlight the importance of QNEs in intermediate strength hydrogen bonds (HBs) and explain why H+ diffusion through nanochannels is impeded much less than other cations.Comment: 6 pages, 4 figure

On Transverse-Momentum Dependent Light-Cone Wave Functions of Light Mesons

Transverse-momentum dependent (TMD) light-cone wave functions of a light meson are important ingredients in the TMD QCD factorization of exclusive processes. This factorization allows one conveniently resum Sudakov logarithms appearing in collinear factorization. The TMD light-cone wave functions are not simply related to the standard light-cone wave functions in collinear factorization by integrating them over the transverse momentum. We explore relations between TMD light-cone wave functions and those in the collinear factorization. Two factorized relations can be found. One is helpful for constructing models for TMD light-cone wave functions, and the other can be used for resummation. These relations will be useful to establish a link between two types of factorization.Comment: add more discussions and reference

Strong Electron-Phonon Interaction and Colossal Magnetoresistance in EuTiO3_3

At low temperatures, EuTiO$_3$ system has very large resistivities and exhibits colossal magnetoresistance. Based on a first principle calculation and the dynamical mean-field theory for small polaron we have calculated the transport properties of EuTiO$_3$. It is found that due to electron-phonon interaction the conduction band may form a tiny subband which is close to the Fermi level. The tiny subband is responsible for the large resistivity. Besides, EuTiO$_3$ is a weak antiferromagnetic material and its magnetization would slightly shift the subband via exchange interaction between conduction electrons and magnetic atoms. Since the subband is close to the Fermi level, a slight shift of its position gives colossal magnetoresistance.Comment: 6 pages, 5 figure