Cluster-based reduced-order modelling of a mixing layer

We propose a novel cluster-based reduced-order modelling (CROM) strategy of unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger's group (Burkardt et al. 2006) and and transition matrix models introduced in fluid dynamics in Eckhardt's group (Schneider et al. 2007). CROM constitutes a potential alternative to POD models and generalises the Ulam-Galerkin method classically used in dynamical systems to determine a finite-rank approximation of the Perron-Frobenius operator. The proposed strategy processes a time-resolved sequence of flow snapshots in two steps. First, the snapshot data are clustered into a small number of representative states, called centroids, in the state space. These centroids partition the state space in complementary non-overlapping regions (centroidal Voronoi cells). Departing from the standard algorithm, the probabilities of the clusters are determined, and the states are sorted by analysis of the transition matrix. Secondly, the transitions between the states are dynamically modelled using a Markov process. Physical mechanisms are then distilled by a refined analysis of the Markov process, e.g. using finite-time Lyapunov exponent and entropic methods. This CROM framework is applied to the Lorenz attractor (as illustrative example), to velocity fields of the spatially evolving incompressible mixing layer and the three-dimensional turbulent wake of a bluff body. For these examples, CROM is shown to identify non-trivial quasi-attractors and transition processes in an unsupervised manner. CROM has numerous potential applications for the systematic identification of physical mechanisms of complex dynamics, for comparison of flow evolution models, for the identification of precursors to desirable and undesirable events, and for flow control applications exploiting nonlinear actuation dynamics.Comment: 48 pages, 30 figures. Revised version with additional material. Accepted for publication in Journal of Fluid Mechanic

Country-of-origin-specific economic capital in neighbourhoods: Impact on immigrants’ employment opportunities

Does living in an area characterized by high concentrations of residents of the same country-of-origin deprive ethnic minority groups, or does potential access to an extended country-of-origin-specific network stimulate their integration? This paper takes a new approach to analysing the potential of country-of-origin-specific economic capital in neighbourhoods to increase employment opportunities. We add to the ‘ethnic enclave’ debate by measuring country-of-origin-specific economic capital as the rate of employed co-countrymen, while controlling for the presence of co-countrymen and general employment rates in the neighbourhood. Whereas many studies employ aggregated data to estimate the impact of neighbourhood, here we use individualized, scalable neighbourhoods. This allows for a flexible approach in studying the impact of country-of-origin-specific economic capital in neighbourhoods. We employ individual longitudinal Swedish registry data for 2000–2010 on working-age individuals of Iraqi, Iranian, Turkish, and Somalian backgrounds in Stockholm, Göteborg, and Malmö. We find that an increased share of employed co-countrymen positively influences individual employment prospects. We add to existing knowledge by showing that the impact of minority clustering on employment outcomes is conditional on the quality of local networks – i.e., country-of-origin-specific economic capital – and on the scale of measurement

Keeping Track of My Drinking : Patient Perceptions of Using Smartphone Applications as a Treatment Complement for Alcohol Dependence

Background: Alcohol dependence is common, yet highly undertreated. Smartphone applications (apps) have potential to enhance treatment accessibility and effectiveness, however evidence is limited, especially studies focussing on user experiences. The aim was to describe patient perceptions on the usability and acceptability of self-monitoring apps provided as treatment complement for alcohol dependence. Methods: Individual semi-structured interviews were conducted through video or phone calls with 21 participants, recruited from a randomized controlled trial at a dependency clinic in Stockholm. The participants had used two specific apps for self-monitoring consumption ("Glasklart" and "iBAC") during 12 wk prior to the interviews. Data was analyzed using Qualitative Content Analysis. Results: Two domains were identified: 1) Smartphone applications as facilitators to treatment, and 2) Barriers to smartphone application use. Using apps within the treatment context was believed to increase the accuracy of the reported consumption. Participants became more aware of their alcohol problem and described the apps as reinforcers that could increase both the motivation to change and the focus on the problem and commitment to treatment. The apps were further described as helpful to control alcohol consumption. However, app usage was constrained by technical problems, unfit app-specific features and procedures, and alcohol-related shame and stigma. Discussion and Conclusions: Self-monitoring alcohol apps have several beneficial features that can help assess, track, and control alcohol consumption, and improve communication with clinicians. The results indicate they can be useful complements to treatment for patients with alcohol dependence, but their use can be limited by different, foremost technical, issues. Smartphone applications for self-monitoring of alcohol consumption may help provide accurate data, increase consumption awareness, focus, motivation, and perceived control; Smartphone applications for self-monitoring of alcohol consumption are considered helpful complements to alcohol treatment; The use of smartphone applications for self-monitoring of alcohol consumption can be constrained by technical problems, and unfit app-specific features and procedures.Forskningsfinansiär: Systembolagets Alkoholforskningsråd</p