An advanced telerobotic system for shuttle payload changeout room processing applications

To potentially alleviate the inherent difficulties in the ground processing of the Space Shuttle and its associated payloads, a teleoperated, semi-autonomous robotic processing system for the Payload Changeout Room (PCR) is now in the conceptual stages. The complete PCR robotic system as currently conceived is described and critical design issues and the required technologies are discussed

Block synchronization for quantum information

Locating the boundaries of consecutive blocks of quantum information is a fundamental building block for advanced quantum computation and quantum communication systems. We develop a coding theoretic method for properly locating boundaries of quantum information without relying on external synchronization when block synchronization is lost. The method also protects qubits from decoherence in a manner similar to conventional quantum error-correcting codes, seamlessly achieving synchronization recovery and error correction. A family of quantum codes that are simultaneously synchronizable and error-correcting is given through this approach.Comment: 7 pages, no figures, final accepted version for publication in Physical Review

Validation of the Implementation Climate Scale (ICS) in substance use disorder treatment organizations.

BackgroundOne critical factor in the implementation of evidence-based practice (EBP) in substance use disorder treatment organizations is an inner organizational context that clearly supports implementation efforts. The Implementation Climate Scale (ICS) has been developed to allow researchers and organizations to assess climate for EBP implementation in health and allied health service organizations. The ICS consists of 18 items and measures six dimensions of implementation climate: focus on EBP, educational support for EBP, recognition for EBP, rewards for EBP, selection for EBP, and selection for openness. The ICS was initially developed in a mental health context; thus, the goal of this study was to provide initial validation of the ICS in substance use disorder (SUD) treatment settings.MethodsConfirmatory factor analysis (CFA) was used to assess the psychometric functioning of the ICS using survey data from 326 providers in 65 teams in SUD treatment programs. Cronbach's alpha was examined to assess internal consistency of the ICS, and individual and team level construct-based validity was examined by comparing its correlations with service climate, molar climate, and organizational change.ResultsWe found evidence for the reliability, factor structure, and validity of the ICS in SUD services. The psychometric functioning of the ICS in SUD treatment settings was comparable to that found in mental health contexts.ConclusionsThe ICS is a brief and pragmatic tool for researchers to better understand a critical antecedent for implementation effectiveness in SUD treatment and for organizational leaders in SUD treatment organizations to evaluate the extent to which providers perceive that their organization supports EBP implementation

A new test procedure of independence in copula models via chi-square-divergence

We introduce a new test procedure of independence in the framework of parametric copulas with unknown marginals. The method is based essentially on the dual representation of $\chi^2$-divergence on signed finite measures. The asymptotic properties of the proposed estimate and the test statistic are studied under the null and alternative hypotheses, with simple and standard limit distributions both when the parameter is an interior point or not.Comment: 23 pages (2 figures). Submitted to publicatio

A multivariate framework to study spatio-temporal dependency of electricity load and wind power

With massive wind power integration, the spatial distribution of electricity load centers and wind power plants make it plausible to study the inter-spatial dependence and temporal correlation for the effective working of the power system. In this paper, a novel multivariate framework is developed to study the spatio-temporal dependency using vine copula. Hourly resolution of load and wind power data obtained from a US regional transmission operator spanning 3 years and spatially distributed in 19 load and two wind power zones are considered in this study. Data collection, in terms of dimension, tends to increase in future, and to tackle this high-dimensional data, a reproducible sampling algorithm using vine copula is developed. The sampling algorithm employs k-means clustering along with singular value decomposition technique to ease the computational burden. Selection of appropriate clustering technique and copula family is realized by the goodness of clustering and goodness of fit tests. The paper concludes with a discussion on the importance of spatio-temporal modeling of load and wind power and the advantage of the proposed multivariate sampling algorithm using vine copula

Testing fluvial erosion models using the transient response of bedrock rivers to tectonic forcing in the Apennines, Italy

The transient response of bedrock rivers to a drop in base level can be used to discriminate between competing fluvial erosion models. However, some recent studies of bedrock erosion conclude that transient river long profiles can be approximately characterized by a transport‐limited erosion model, while other authors suggest that a detachment‐limited model best explains their field data. The difference is thought to be due to the relative volume of sediment being fluxed through the fluvial system. Using a pragmatic approach, we address this debate by testing the ability of end‐member fluvial erosion models to reproduce the well‐documented evolution of three catchments in the central Apennines (Italy) which have been perturbed to various extents by an independently constrained increase in relative uplift rate. The transport‐limited model is unable to account for the catchments’response to the increase in uplift rate, consistent with the observed low rates of sediment supply to the channels. Instead, a detachment‐limited model with a threshold corresponding to the field‐derived median grain size of the sediment plus a slope‐dependent channel width satisfactorily reproduces the overall convex long profiles along the studied rivers. Importantly, we find that the prefactor in the hydraulic scaling relationship is uplift dependent, leading to landscapes responding faster the higher the uplift rate, consistent with field observations. We conclude that a slope‐ dependent channel width and an entrainment/erosion threshold are necessary ingredients when modeling landscape evolution or mapping the distribution of fluvial erosion rates in areas where the rate of sediment supply to channels is low

Predicting the temporal activity patterns of new venues.

Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners