Community asset mapping for violence prevention: A comparison of views in Erijaville, South Africa and Memphis, USA

In the context of addressing challenges relating to ongoing interpersonal violence, this article conducts a comparative analysis of findings from a community asset mapping process drawing responses from 100 community participants across the two sites of Erijaville, South Africa and Memphis, Tennessee in the USA. Specifically, we describe the similarities and differences across sites regarding community assets linked to safety and peace promotion, with a particular emphasis on tangible and intangible factors relevant to the promotion of safety and peace. The findings reveal a major emphasis on ‘intangible’ factors that relate to the promotion of safety  and peace, including personal values and behaviour (such as love, compassion and prayer), family relationships (such as family socialisation, care and supervision, role modelling, and peer guidance), and community connectedness (including community hope and trust, and the development of ethical leadership). The findings suggest that religious assets and spiritual capacity constitute important resources, which should be more intentionally mobilised and enhanced to promote safety and peace. This constitutes an important challenge in relation to violence prevention in both South Africa and the USA.Keywords: community-based participatory research, community asset mapping, interpersonal violence, violence prevention, positive forms of masculinity, peace and safety, religious assets, spiritual capacit

Application of Simple Smart Logic for Waterflooding Reservoir Management

A simple smart logic for controlling inflow control valves (ICV) in waterflooding reservoir management is implemented and analyzed, with the final objective of improving the long term financial return of a petroleum reservoir. Such a control is based in a reactive simple logic that responds to the watercut measured in the ICV. Basically, when the watercut increases, the ICV is set to close proportionally. For comparison purposes, four strategies are presented: base case scenario with conventional control, the best completion configuration found by trial-and-error, the reactive control, and a deterministic optimal control based on Nonlinear Gradient Method with adjoint-gradient formulation is shown for comparison purposes. Finally, all four strategies are tested again in different reservoir realizations in order to mimic the geological uncertainties. Two different synthetic reservoir models were studied. First, a simple cube with a five-spot well configuration, in which the permeability field has a horizontal pattern defined by lognormal distributions. The second model is a benchmark proposed by the Dutch university, TU delft, with 101 channelized permeability fields representing river patterns. For the first model, no significant relative gain is found neither in the variable control nor in the optimal control. Manly because of the high homogeneity of the reservoir models. Therefore, no intelligent completion is recommended. On the other hand, for the second and more complex case, the results indicate an expressive relative gain in the use of simple reactive logic. Besides, this type of control achieves results nearly as good as the optimal control. The test in different realizations, however, shows that reservoir characterization is still a key part of any attempt to improve production. Although the variable reactive control is semi-independent, with action being taken based on measurements, some parameters need a priori model to be tuned

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

The Relationship Between Service Learning And Medical Student Academic And Professional Outcomes

BACKGROUND: Little is known about the relationship between medical student participation in service and performance outcomes. PURPOSE: To examine relationships between involvement in required service learning and measures of academic and professional achievement and specialty choice. METHODS: Using preexisting, self-reported data for Tulane University School of Medicine\u27s class of 2004, we categorized students as low, moderate, or high on commitment and involvement in service learning (CISL) and compared to multiple outcomes: class rank; election to the Alpha Omega Alpha (AOA) Honor Society; election to the Gold Humanism in Medicine Honor Society; total percent scores on 2 multistation, structured, clinical examinations; and specialty choice per 2004 residency match results. RESULTS: Service learning involvement was related to class rank. There was a marginal relationship between CISL and election to AOA but no association with election to the Gold Humanism in Medicine Honor Society, Year 2 or 3 clinical skills examination results, or specialty choice. CONCLUSIONS: High participation in service learning and service learning leadership identify a group of students less likely to be in the top quartile of their class yet who are making important contributions to the community and profession

The Relationship Between Service Learning And Medical Student Academic And Professional Outcomes

BACKGROUND: Little is known about the relationship between medical student participation in service and performance outcomes. PURPOSE: To examine relationships between involvement in required service learning and measures of academic and professional achievement and specialty choice. METHODS: Using preexisting, self-reported data for Tulane University School of Medicine\u27s class of 2004, we categorized students as low, moderate, or high on commitment and involvement in service learning (CISL) and compared to multiple outcomes: class rank; election to the Alpha Omega Alpha (AOA) Honor Society; election to the Gold Humanism in Medicine Honor Society; total percent scores on 2 multistation, structured, clinical examinations; and specialty choice per 2004 residency match results. RESULTS: Service learning involvement was related to class rank. There was a marginal relationship between CISL and election to AOA but no association with election to the Gold Humanism in Medicine Honor Society, Year 2 or 3 clinical skills examination results, or specialty choice. CONCLUSIONS: High participation in service learning and service learning leadership identify a group of students less likely to be in the top quartile of their class yet who are making important contributions to the community and profession