Psychometric properties of the Mental Health Recovery Star.

BACKGROUND: The Mental Health Recovery Star (MHRS) is a popular outcome measure rated collaboratively by staff and service users, but its psychometric properties are unknown. AIMS: To assess the MHRS's acceptability, reliability and convergent validity. METHOD: A total of 172 services users and 120 staff from in-patient and community services participated. Interrater reliability of staff-only ratings and test-retest reliability of staff-only and collaborative ratings were assessed using intraclass correlation coefficients (ICCs). Convergent validity between MHRS ratings and standardised measures of social functioning and recovery was assessed using Pearson correlation. The influence of collaboration on ratings was assessed using descriptive statistics and ICCs. RESULTS: The MHRS was relatively quick and easy to use and had good test-retest reliability, but interrater reliability was inadequate. Collaborative ratings were slightly higher than staff-only ratings. Convergent validity suggests it assesses social function more than recovery. CONCLUSIONS: The MHRS cannot be recommended as a routine clinical outcome tool but may facilitate collaborative care planning

A Constraint Programming Approach for Non-Preemptive Evacuation Scheduling

Large-scale controlled evacuations require emergency services to select evacuation routes, decide departure times, and mobilize resources to issue orders, all under strict time constraints. Existing algorithms almost always allow for preemptive evacuation schedules, which are less desirable in practice. This paper proposes, for the first time, a constraint-based scheduling model that optimizes the evacuation flow rate (number of vehicles sent at regular time intervals) and evacuation phasing of widely populated areas, while ensuring a nonpreemptive evacuation for each residential zone. Two optimization objectives are considered: (1) to maximize the number of evacuees reaching safety and (2) to minimize the overall duration of the evacuation. Preliminary results on a set of real-world instances show that the approach can produce, within a few seconds, a non-preemptive evacuation schedule which is either optimal or at most 6% away of the optimal preemptive solution.Comment: Submitted to the 21st International Conference on Principles and Practice of Constraint Programming (CP 2015). 15 pages + 1 reference pag

The convergent validity of two sensory processing scales used with school - age children : comparing the sensory profile and the sensory processing measure

Abstract: Aim: To investigate the convergent validity between the Sensory Profile, the Sensory Profile School Companion, and the Home and Main Classroom Forms of the Sensory Processing Measure. Method: Thirty mothers completed the Sensory Profile and the Sensory Processing Measure - Home Form on one child each. Nineteen teachers of the same children completed the Sensory Profile School Companion and the Sensory Processing Measure - Main Classroom Form. Results: The Sensory Profile and the Sensory Processing Measure - Home Form were significantly correlated (rho=0.86, p less-than .01). The Sensory Profile School Companion and Sensory Processing Measure - Main Classroom Form were also significantly correlated (rho=.74, p less-than .01). Conclusion: The two sets of sensory processing scales had moderate levels of convergent validity.<br /

Pilot study: evaluation of the use of the convergent interview technique in understanding the perception of surgical design and simulation

BACKGROUND: It is important to understand the perceived value of surgical design and simulation (SDS) amongst surgeons, as this will influence its implementation in clinical settings. The purpose of the present study was to examine the application of the convergent interview technique in the field of surgical design and simulation and evaluate whether the technique would uncover new perceptions of virtual surgical planning (VSP) and medical models not discovered by other qualitative case-based techniques. METHODS: Five surgeons were asked to participate in the study. Each participant was interviewed following the convergent interview technique. After each interview, the interviewer interpreted the information by seeking agreements and disagreements among the interviewees in order to understand the key concepts in the field of SDS. RESULTS: Fifteen important issues were extracted from the convergent interviews. CONCLUSION: In general, the convergent interview was an effective technique in collecting information about the perception of clinicians. The study identified three areas where the technique could be improved upon for future studies in the SDS field

A recursively feasible and convergent Sequential Convex Programming procedure to solve non-convex problems with linear equality constraints

A computationally efficient method to solve non-convex programming problems with linear equality constraints is presented. The proposed method is based on a recursively feasible and descending sequential convex programming procedure proven to converge to a locally optimal solution. Assuming that the first convex problem in the sequence is feasible, these properties are obtained by convexifying the non-convex cost and inequality constraints with inner-convex approximations. Additionally, a computationally efficient method is introduced to obtain inner-convex approximations based on Taylor series expansions. These Taylor-based inner-convex approximations provide the overall algorithm with a quadratic rate of convergence. The proposed method is capable of solving problems of practical interest in real-time. This is illustrated with a numerical simulation of an aerial vehicle trajectory optimization problem on commercial-of-the-shelf embedded computers

Deep Residual Reinforcement Learning

We revisit residual algorithms in both model-free and model-based reinforcement learning settings. We propose the bidirectional target network technique to stabilize residual algorithms, yielding a residual version of DDPG that significantly outperforms vanilla DDPG in the DeepMind Control Suite benchmark. Moreover, we find the residual algorithm an effective approach to the distribution mismatch problem in model-based planning. Compared with the existing TD($k$) method, our residual-based method makes weaker assumptions about the model and yields a greater performance boost.Comment: AAMAS 202

Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic

Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic (March 25 - 27, 2018 -- The University of New Hampshire) paired two of NSF\u27s 10 Big Ideas: Navigating the New Arctic and Growing Convergence Research at NSF. During this event, participants assessed economic, environmental, and social impacts of Arctic change on New England and established convergence research initiatives to prepare for, adapt to, and respond to these effects. Shipping routes through an ice-free Northwest Passage in combination with modifications to ocean circulation and regional climate patterns linked to Arctic ice melt will affect trade, fisheries, tourism, coastal ecology, air and water quality, animal migration, and demographics not only in the Arctic but also in lower latitude coastal regions such as New England. With profound changes on the horizon, this is a critical opportunity for New England to prepare for uncertain yet inevitable economic and environmental impacts of Arctic change