Enhancing Social Connectedness in Anxiety and Depression Through Amplification of Positivity: Preliminary Treatment Outcomes and Process of Change.

BackgroundAnxiety and depressive disorders are often characterized by perceived social disconnection, yet evidence-based treatments produce only modest improvements in this domain. The well-established link between positive affect (PA) and social connectedness suggests that directly targeting PA in treatment may be valuable.MethodA secondary analysis of a waitlist-controlled trial (N=29) was conducted to evaluate treatment response and process of change in social connectedness within a 10-session positive activity intervention protocol-Amplification of Positivity (AMP)-designed to increase PA in individuals seeking treatment for anxiety or depression (ClinicalTrials.gov Identifier: NCT02330627). Perceived social connectedness and PA/negative affect (NA) were assessed throughout treatment. Time-lagged multilevel mediation models examined the process of change in affect and connectedness throughout treatment.ResultsThe AMP group displayed significantly larger improvements in social connectedness from pre- to post-treatment compared to waitlist; improvements were maintained through 6-month follow-up. Within the AMP group, increases in PA and decreases in NA both uniquely predicted subsequent increases in connectedness throughout treatment. However, experiencing heightened NA throughout treatment attenuated the effect of changes in PA on connectedness. Improvements in connectedness predicted subsequent increases in PA, but not changes in NA.ConclusionsThese preliminary findings suggest that positive activity interventions may be valuable for enhancing social connectedness in individuals with clinically impairing anxiety or depression, possibly through both increasing positive emotions and decreasing negative emotions

Web Services Support for Dynamic Business Process Outsourcing

Outsourcing of business processes is crucial for organizations to be effective, efficient and flexible. To meet fast-changing market conditions, dynamic outsourcing is required, in which business relationships are established and enacted on-the-fly in an adaptive, fine-grained way unrestricted by geographic distance. This requires automated means for both the establishment of outsourcing relationships and for the enactment of services performed in these relationships over electronic channels. Due to wide industry support and the underlying model of loose coupling of services, Web services increasingly become the mechanism of choice to connect organizations across organizational boundaries. This paper analyzes to which extent Web services support the dynamic process outsourcing paradigm. We discuss contract -based dynamic business process outsourcing to define requirements and then introduce the Web services framework. Based on this, we investigate the match between the two. We observe that the Web services framework requires further support for cross - organizational business processes and mechanisms for contracting, QoS management and process-based transaction support and suggest ways to fill those gaps

Evaluating Maximum Likelihood Estimation Methods to Determine the Hurst Coefficient

A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficient (H) is evaluated. The Hurst coefficient, with 0.5\u3cHS-MLE was developed to estimate H for fractionally differenced (fd) processes. However, in practice it is difficult to distinguish between fd processes and fractional Gaussian noise (fGn) processes. Thus, the method is evaluated for estimating H for both fd and fGn processes. S-MLE gave biased results of H for fGn processes of any length and for fd processes of lengths less than 210. A modified method is proposed to correct for this bias. It gives reliable estimates of H for both fd and fGn processes of length greater than or equal to 211

An Integrated Design and Simulation Environment for Rapid Prototyping of Laminate Robotic Mechanisms

Laminate mechanisms are a reliable concept in producing lowcost robots for educational and commercial purposes. These mechanisms are produced using low-cost manufacturing techniques which have improved significantly during recent years and are more accessible to novices and hobbyists. However, iterating through the design space to come up with the best design for a robot is still a time consuming and rather expensive task and therefore, there is still a need for model-based analysis before manufacturing. Until now, there has been no integrated design and analysis software for laminate robots. This paper addresses some of the issues surrounding laminate analysis by introducing a companion to an existing laminate design tool that automates the generation of dynamic equations and produces simulation results via rendered plots and videos. We have validated the accuracy of the software by comparing the position, velocity and acceleration of the simulated mechanisms with the measurements taken from physical laminate prototypes using a motion capture system

Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM modeling good research practices task force working group - 6

A model’s purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value-of-information analysis. The article also makes extensive recommendations around the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis

Modeling Adversaries in a Logic for Security Protocol Analysis

Logics for security protocol analysis require the formalization of an adversary model that specifies the capabilities of adversaries. A common model is the Dolev-Yao model, which considers only adversaries that can compose and replay messages, and decipher them with known keys. The Dolev-Yao model is a useful abstraction, but it suffers from some drawbacks: it cannot handle the adversary knowing protocol-specific information, and it cannot handle probabilistic notions, such as the adversary attempting to guess the keys. We show how we can analyze security protocols under different adversary models by using a logic with a notion of algorithmic knowledge. Roughly speaking, adversaries are assumed to use algorithms to compute their knowledge; adversary capabilities are captured by suitable restrictions on the algorithms used. We show how we can model the standard Dolev-Yao adversary in this setting, and how we can capture more general capabilities including protocol-specific knowledge and guesses.Comment: 23 pages. A preliminary version appeared in the proceedings of FaSec'0