An Adaptive Dictionary Learning Approach for Modeling Dynamical Textures

Video representation is an important and challenging task in the computer vision community. In this paper, we assume that image frames of a moving scene can be modeled as a Linear Dynamical System. We propose a sparse coding framework, named adaptive video dictionary learning (AVDL), to model a video adaptively. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. The proposed method is compared with state of the art video processing methods on several benchmark data sequences, which exhibit appearance changes and heavy occlusions

Quitting patterns and success rates of a tobacco cessation program led by New Mexico Pharmaceutical Care Foundation

The objective of the present study was to assess the effectiveness of a pharmacists-assisted tobacco cessation program led by New Mexico Pharmaceutical Care Foundation (NMPCF) and to characterize participants quitting patterns during the study period. Data from the program from 2004 to 2011 consisting of 1486 participants were combined for analysis. Point prevalence quit rates were calculated and survival analysis was performed to evaluate program effectiveness. A qualitative case study with participating pharmacists was conducted to explore intervention elements that could impact participants\u27 likelihood of successfully quitting tobacco. Four quitting patterns were defined including immediate quitters, delayed quitters, once quitters, or never quitters. Multinomial logistic regression was performed to identify patient characteristics associated with quitting patterns. The average point prevalence quit rate at 6 months was 18.7%. The average abstinent time was 76.8 days (standard error = 3.59 days). The probability of a patient being continuously abstinent for 7 days was 89.1%, while the likelihood of being abstinent for 30 days and 180 days were 46.0% and 16.5%, respectively. Patients who were under 18 years old, less educated, less dependent on nicotine, and had higher confidence to quit were more likely to be immediate quitters rather than never quitters. Pharmacists are capable of delivering tobacco cessation services. Patients\u27 likelihood of quitting tobacco depends both on themselves and the intervention they receive. Intensive counseling and close follow-up are important elements of an effective tobacco cessation intervention. Different quitting patterns exist among patients. Patients with different quitting patterns have distinctive characteristics in terms of level of nicotine dependence, pharmacotherapy used, motivational factors and demographic factors. Interventions need to be tailored for patients with different quitting patterns

On the Value of Multistage Risk-Averse Stochastic Facility Location With or Without Prioritization

We consider a multiperiod stochastic capacitated facility location problem under uncertain demand and budget in each period. Using a scenario tree representation of the uncertainties, we formulate a multistage stochastic integer program to dynamically locate facilities in each period and compare it with a two-stage approach that determines the facility locations up front. In the multistage model, in each stage, a decision maker optimizes facility locations and recourse flows from open facilities to demand sites, to minimize certain risk measures of the cost associated with current facility location and shipment decisions. When the budget is also uncertain, a popular modeling framework is to prioritize the candidate sites. In the two-stage model, the priority list is decided in advance and fixed through all periods, while in the multistage model, the priority list can change adaptively. In each period, the decision maker follows the priority list to open facilities according to the realized budget, and optimizes recourse flows given the realized demand. Using expected conditional risk measures (ECRMs), we derive tight lower bounds for the gaps between the optimal objective values of risk-averse multistage models and their two-stage counterparts in both settings with and without prioritization. Moreover, we propose two approximation algorithms to efficiently solve risk-averse two-stage and multistage models without prioritization, which are asymptotically optimal under an expanding market assumption. We also design a set of super-valid inequalities for risk-averse two-stage and multistage stochastic programs with prioritization to reduce the computational time. We conduct numerical studies using both randomly generated and real-world instances with diverse sizes, to demonstrate the tightness of the analytical bounds and efficacy of the approximation algorithms and prioritization cuts

Link between K-absorption edges and thermodynamic properties of warm-dense plasmas established by improved first-principles method

A precise calculation that translates shifts of X-ray K-absorption edges to variations of thermodynamic properties allows quantitative characterization of interior thermodynamic properties of warm dense plasmas by X-ray absorption techniques, which provides essential information for inertial confinement fusion and other astrophysical applications. We show that this interpretation can be achieved through an improved first-principles method. Our calculation shows that the shift of K-edges exhibits selective sensitivity to thermal parameters and thus would be a suitable temperature index to warm dense plasmas. We also show with a simple model that the shift of K-edges can be used to detect inhomogeneity inside warm dense plasmas when combined with other experimental tools

Extended First-Principles Molecular Dynamics Method From Cold Materials to Hot Dense Plasmas

An extended first-principles molecular dynamics (FPMD) method based on Kohn-Sham scheme is proposed to elevate the temperature limit of the FPMD method in the calculation of dense plasmas. The extended method treats the wave functions of high energy electrons as plane waves analytically, and thus expands the application of the FPMD method to the region of hot dense plasmas without suffering from the formidable computational costs. In addition, the extended method inherits the high accuracy of the Kohn-Sham scheme and keeps the information of elec- tronic structures. This gives an edge to the extended method in the calculation of the lowering of ionization potential, X-ray absorption/emission spectra, opacity, and high-Z dense plasmas, which are of particular interest to astrophysics, inertial confinement fusion engineering, and laboratory astrophysics