How Does Cognitive Conflict in Design Teams Support the Development of Creative Ideas?

Is cognitive conflict detrimental to the development of innovative ideas in design teams, or is it a precondition for innovative performance? Assuming that there is a relationship between cognitive conflict and innovation, what kind of strategies do teams use in situations of cognitive conflict and what are the consequences for creativity? This paper reports on a study analysing how design teams cope with cognitive conflict during idea generation in an experiment. The design process was captured in protocols that were generated from video recordings. We report the results of the analysis of verbal protocols according to the five styles of (cognitive) conflict behaviour: competing, collaborating, compromising, avoiding and accommodating. Out of six teams, the results of the two highest and two lowest scoring teams are compared as regards innovation and functionality, which we see as the two components of creative outcomes. We show that design teams, even in a laboratory environment, encounter a considerable amount of cognitive conflict. A statistical comparison between the groups with the highest and the lowest innovative/functional design concept scores reveals significant differences in their conflict behaviour styles. The high innovation and high functionality groups used a more competing and a more compromising style, whereas groups rated low on the same parameters used a more collaborating style. The high rating groups on both creativity components used a more associating and rejecting behaviour style; the high innovation groups also generated more new ideas than the low innovation groups. The low rating groups on both innovation and functionality tended to repeat ideas more frequently. The main finding is that, in contrast with reports in previous research, the groups with higher innovation and functionality scores collaborated less than their peers in the low rating groups on these parameters. We interpret these results as signifying that creative performance in teams is not achieved mainly by agreement but needs cognitive confrontation.     

Prenatal binge ethanol exposure on gestation days 19–20, but not on days 17–18, increases postnatal ethanol acceptance in rats.

Previous research shows that prenatal binge ethanol exposure during gestation days (GD) 17 to 20 of the rat, increases postnatal ethanol intake and enhances ethanol's palatability, both effects being mediated by the opioid system. The amniotic fluid of the last period of gestation (GD 20) of the rat has been found to activate the opioid system and to induce conditioned preference in fetal and neonatal rats. We aimed to investigate whether enhanced acceptance for ethanol is observed when rat fetuses are exposed to it either on GD 17–18 or on GD 19–20. The results show that 14-day old pups whose mothers received ethanol on GD 19–20 consumed more ethanol and found ethanol more palatable when compared to pups exposed to ethanol on GD 17–18, or to pups experiencing ethanol and naloxone on GD 19–20. The augmented ethanol intake was observed as well after weaning (PD 26–27). These data indicate that exposure to ethanol on GD 19–20, but not before, triggers appetitive learning related to ethanol's flavor. This prenatally acquired memory is retained for at least 4 weeks and can be detected postnatally as enhanced palatability of ethanol's flavor as well as increased intake of ethanol. This increased liking of ethanol is mediated by the opioid system, although it cannot be clearly determined whether the prenatal activation of the opioid system is induced by the action of ethanol or by the activity of amniotic fluid components at that gestational age. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

OZone: A SHARED INSTITUTIONAL REPOSITORY SERVICE

This paper provides an overview of the implementation and gradual growth of OZone as a shared institutional repository. Started in the fall of 2003 as a project of the Ontario Council of University Libraries (OCUL) trough the Scholars Portal program, OZone is the implementation of DSpace as a multi-institutional repository. This paper describes and underlines the features of the flexible and powerful platform that helped us model the service, and delineates policies and benefits provided by OZone.     

Logical analysis of data – the vision of Peter L. Hammer

Logical analysis of data (LAD) is a special data analysis methodology which combines ideas and concepts from optimization, combinatorics, and Boolean functions. The central concept in LAD is that of patterns, or rules, which were found to play a critical role in classification, ranked regression, clustering, detection of subclasses, feature selection and other problems. The research area of LAD was defined and initiated by Peter L. Hammer, who was the catalyst of the LAD oriented research for decades, and whose consistent vision and efforts helped the methodology to move from theory to data analysis applications, to achieve maturity and to be successful in many medical, industrial and economics case studies. This overview presents some of the basic aspects of LAD, from the definition of the main concepts to the efficient algorithms for pattern generation, and from the complexity analysis of the difficult problems embedded in LAD to its biomedical applications. We focus in this paper only on some recent developments in LAD which were of particular interest to Peter L. Hammer, who played a key role in obtaining all the results described here. The presentation in this overview is based on the original publications of Peter L. Hammer and his co-authors. We dedicate this paper to the memory of Peter L. Hammer.     

A methodology to infer and refactor an object‐oriented model from C applications

When analyzing legacy code, generating a high‐level model of an application during the reverse engineering process helps the developers understand how the application is structured and how the dependencies relate the different software entities. Within the context of procedural programming languages (such as C), the existing approaches to get a model of the code require documentation and/or implicit knowledge that stakeholders acquire during the software building. These approaches use the code itself to build a syntactic model where we see the different software artifacts, such as variables, functions, and modules. However, there is no supporting methodology to detect and analyze if there are relationships/dependencies between those artifacts, such as which variable in a module is declared using an abstract data type described in another one, or which are the functions that are using parameters typed with an abstract data type; or any design decision taken by original developers, such as how the developer has implemented functions in different modules. On the other hand, current developers use object‐oriented (OO) paradigm to implement not only business applications but also useful methodologies/tools that allow semiautomatic analysis of any application. We must remark the legacy procedural code still has worth and is working in several industries, and as any evolving code, the developers have to be able to perform maintenance tasks minimizing the limitations offered by the language. Based on useful properties that the OO paradigm (and their supporting analysis tools) provide, such as UML models, we propose M2K as a methodology to generate a high‐level model from legacy procedural code, mainly written in Ansi C. To understand how C‐based applications were implemented is not a new problem in software reengineering. However, our contribution is based on building an OO model and suggesting different refactorings that help the developer to improve it and to eventually guide a new implementation of the target application. Specifically, the methodology builds cohesive software entities mapped from procedural code and makes the coupling between C entities explicit in the high‐level model. The result of our methodology is a set of refactored class candidates: a structure that groups a set of variables and a set of functions obtained from the C applications. Based on the class candidate model, we propose refactorings based on OO design principles to improve the design of the application. The most relevant design improvements were obtained with algorithm abstraction by applying the strategy pattern, attributes/methods relocalization, variables types generalization, and removing/renaming methods/attributes. Besides a methodology and the supporting tool, we provide 14 case studies based on real projects implemented in C, and we showed how the results validate our proposal.     

Characterizing contextual equivalence in calculi with passivation

We study the problem of characterizing contextual equivalence in higher-order languages with passivation. To overcome the difficulties arising in the proof of congruence of candidate bisimilarities, we introduce a new form of labeled transition semantics together with its associated notion of bisimulation, which we call complementary semantics. Complementary semantics allows to apply the well-known Howe?s method for proving the congruence of bisimilarities in a higher-order setting, even in the presence of an early form of bisimulation. We use complementary semantics to provide a coinductive characterization of contextual equivalence in the HOπP calculus, an extension of the higher-order π-calculus with passivation, obtaining the first result of this kind. We then study the problem of defining a more effective variant of bisimilarity that still characterizes contextual equivalence, along the lines of Sangiorgi?s notion of normal bisimilarity. We provide partial results on this difficult problem: we show that a large class of test processes cannot be used to derive a normal bisimilarity in HOπP, but we show that a form of normal bisimilarity can be defined for HOπP without restriction.     

Impact of the hypocaloric diet using food substitutes on the body weight and biochemical profile

Recent studies using balanced hypocaloric diets with food substitutes in some meals, have presented positive results. There are no studies with the Brazilian population on the efficacy of using food substitute, together with a hypocaloric diet. Main objective of this study was to verify the effects of a hypocaloric diet using food substitutes as meal replacement on the body weight, lipid profile, and glucose and insulin plasma levels. Seventy eight subjects of both genders were selected, 20-50 years old, and a body weight index between 25 kg/m2 and 35 kg/m2. The study lasted for six months and it was divided in 2 phases of three months each- mass reduction for 3 months and 3 months for maintenance. The sample was randomly divided in two groups: Group A (control- 3 months of general nutritional and physical orientation followed by 3 months with 1 meal replacement) and Group B (intervention- 2 meals replacement a day plus nutritional and physical orientation for 3 months followed by 3 months with 1 meal replacement). Anthropometric measurements, percent body fat (%BF), biochemical profile and intake survey were performed at moments 0, 3 and 6 months. Both groups showed a significant decrease in %BF, weight, and consequently in their BMI, in the third and sixth month of follow up. However, weight loss in group B was higher than in group A. At the end of the treatment, 0 and 25.0% of the patients of the group A and B, respectively, presented a weight loss higher than 10% of the initial weight. Comparing the triglycerides, LDL-cholesterol and glucose levels, between the beginning and after the three and six months of treatment, there was a significant reduction in the individuals only in group B. In conclusion, the use of food substitutes as meal replacement, together with a balanced, hypocaloric diet, proved to be efficient in weight loss for Brazilian overweighed individuals.