Psychological factors surrounding disagreement in multicultural design team meetings

Abstract

Our research contrasts two theories of creativity in multicultural teams. The dual-process model focuses on the degree of diversity, whereas cross-cultural psychology focuses on specific cultural compositions. In individualistic cultures, team members express more conflicts and benefit from it, compared to in collectivistic cultures that emphasise harmony. The relative representation of members from these cultures may affect team dynamics, conflict and creativity. We coded over 3100 speaker turns in the 11th Design Thinking Research Symposium data-set for the presence of disagreements and examined the effects of conflict phase and team diversity on creativity, promotion and prevention approaches using Linguistic Inquiry Word Count measures. We found that micro-conflicts increased insight words in the moment of the conflict. Individuals in more diverse team meetings of Scandinavians and South-East Asians expressed fewer conflicts than teams dominated by Scandinavians and were less likely to focus on potential gains when experiencing micro-conflicts. Regardless of conflict, the more culturally diverse teams were more likely to use insight and promotion words overall. There were no effects for prevention. These findings extend extant theory to different types of heterogeneous teams in a real-world design setting. This study is novel in combining theory on team cultural diversity with a micro-process method.     

Characterizing Energy Usage of a Commercially Available Ground Robot: Method and Results

Energy usage by mobile robots is becoming a larger concern as autonomous systems increase mission durations. Understanding and characterizing energy usage is key to reliable mission operation. This paper presents a methodology for characterizing energy usage of a ground robot traveling at a constant speed applicable to both open and “black box” (proprietary) platforms. To address testing area limitations, we introduce a “rounded box” path to approximate straight line travel. For a case study, this methodology was applied to an iRobot Packbot on grass and asphalt surfaces. Our results show a decrease in electrical energy used with increasing speed for soft grass and constant energy usage on asphalt. For both surfaces, a similar electrical‐to‐mechanical efficiency curve is obtained.     

Measures of Population Ageing in Australia from 1950 to 2050

This study utilises annual historic and forecasted population figures from the UN World Population Prospects (2015 Revision) to describe Australia’s population changes for the period 1950–2050. A number of population indices have been employed to describe these changes. Specifically, we constructed population pyramids and computed measures including economic dependency ratios, support ratios, ageing/Billeter indices and coefficients of inflow, outflow and exchange of productive populations. Our results suggest that a combination of factors including declining fertility and mortality have contributed to Australia’s ageing population. The implications of these changes are broad and raise major challenges for Australia’s economy and infrastructure. To tackle both the drivers and impacts of population ageing, multi-faceted approaches are needed together with prompt evaluation to ensure that current and future challenges posed by population changes in Australia are fully contained.     

Review of Learning process in psychoanalytic supervision: Complexities and challenges.

Reviews the book, Learning process in psychoanalytic supervision: Complexities and challenges by Paul A. DeWald (see record 1987-97784-000). This book is a wonderful contribution to the field of supervision. It is the only book available that presents the actual supervision sessions of one ongoing supervisee with one long-term psychoanalytic patient as they were transcribed. DeWald also offers a review of the supervisory literature, his view of the supervisory process, his supervisory reports, and a chapter from the supervisee discussing her experience. The book is refreshing in that the supervisor does not present himself as perfect, and he does acknowledge mistakes he made in the comments after each set of process notes. There are some criticisms of the book to be made. First, the reviewer was not able to determine the frequency of the patient's sessions or the supervisory sessions. Second, the author's framework is classically Freudian. While this is not a problem, it is important that the reader be aware of the point of view. Third, the author seems ambivalent about the role of the patient's ethnicity and culture in her neurotic stance. These comments aside, Learning process in psychoanalytic supervision is an excellent book, and certainly one any supervisor would want to read. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modified Hyaluronic Acid-Laminin-Hydrogel as Luminal Filler for Clinically Approved Hollow Nerve Guides in a Rat Critical Defect Size Model

Hollow nerve guidance conduits are approved for clinical use for defect lengths of up to 3 cm. This is because also in pre-clinical evaluation they are less effective in the support of nerve regeneration over critical defect lengths. Hydrogel luminal fillers are thought to improve the regeneration outcome by providing an optimized matrix inside bioartificial nerve grafts. We evaluated here a modified hyaluronic acid-laminin-hydrogel (M-HAL) as luminal filler for two clinically approved hollow nerve guides. Collagen-based and chitosan-based nerve guides were filled with M-HAL in two different concentrations and the regeneration outcome comprehensively studied in the acute repair rat sciatic nerve 15 mm critical defect size model. Autologous nerve graft (ANG) repair served as gold-standard control. At 120 days post-surgery, all ANG rats demonstrated electrodiagnostically detectable motor recovery. Both concentrations of the hydrogel luminal filler induced improved regeneration outcome over empty nerve guides. However, neither combination with collagen- nor chitosan-based nerve guides resulted in functional recovery comparable to the ANG repair. In contrast to our previous studies, we demonstrate here that M-HAL slightly improved the overall performance of either empty nerve guide type in the critical defect size model.     

New opportunities for gluten-free diet:teff (Eragrostis tef) as fibre source in baking products

This study assessed physicochemical parameters of high fibre and gluten-free breads made with teff and associated flours. Four breads samples were developed: wheat flour (T1), teff flour (T2), teff flour + cassava starch + rice flour (T3 and T4). Hedonic evaluation of sensory attributes characterising the samples was performed by coeliac and non-coeliac subjects. Breads made with different percentages of teff flour showed huge amount of total and insoluble fibres. The wheat bread presented the highest values for pH and the texture parameters analysed, except for crumb hardness and elasticity. The sensory analysis showed that all samples made with teff were well accepted by coeliac and non-coeliac subjects. Purchase intention and the acceptability index suggested a potential market success for the developed products. Teff flour showed promising use for its technological and nutritional values as well as sensory properties, supporting the hypothesis that it is possible to develop new gluten-free bakery products without decreasing consumers’ satisfaction.     

A line search approach for high dimensional function optimization

This paper proposes a modified line search method which makes use of partial derivatives and re-starts the search process after a given number of iterations by modifying the boundaries based on the best solution obtained at the previous iteration (or set of iterations). Using several high dimensional benchmark functions, we illustrate that the proposed Line Search Re-Start (LSRS) approach is very suitable for high dimensional global optimization problems. Performance of the proposed algorithm is compared with two popular global optimization approaches, namely, genetic algorithm and particle swarm optimization method. Empirical results for up to 10,000 dimensions clearly illustrate that the proposed approach performs very well for the tested high dimensional functions.