Facilitating dialogue and decision-making in a family business

This study examines the influence of dialogue on decision-making within the context of a family-owned business and how to facilitate dialogue in a family business setting. Action research and case study methodology were utilized. Datawere collected during six meetings with a management team over a nine-month period. A thematic analysis was conducted on all data sets. Analysis revealed the following eight themes that described the Influence of dialogue on decision making: environment, listening, learning, values, and practice. One theme, role and responsibilities described how the researcher facilitated dialogue with the management team. The study concludes with implications for research and practice In collaborative learning and family business practice

An Agent-Based Simulation API for Speculative PDES Runtime Environments

Agent-Based Modeling and Simulation (ABMS) is an effective paradigm to model systems exhibiting complex interactions, also with the goal of studying the emergent behavior of these systems. While ABMS has been effectively used in many disciplines, many successful models are still run only sequentially. Relying on simple and easy-to-use languages such as NetLogo limits the possibility to benefit from more effective runtime paradigms, such as speculative Parallel Discrete Event Simulation (PDES). In this paper, we discuss a semantically-rich API allowing to implement Agent-Based Models in a simple and effective way. We also describe the critical points which should be taken into account to implement this API in a speculative PDES environment, to scale up simulations on distributed massively-parallel clusters. We present an experimental assessment showing how our proposal allows to implement complicated interactions with a reduced complexity, while delivering a non-negligible performance increase

Perceptions of Heart-Healthy Behaviors among African American Adults: A Mixed Methods Study

African Americans have a disproportionately higher risk of chronic conditions such as cardiovascular disease (CVD), type 2 diabetes, and hypertension than other ethnic or racial groups. Data regarding CVD-related perceptions and beliefs among African Americans are limited, particularly in the Southwest US. Assessment of current views regarding health and health behaviors is needed to tailor interventions to meet the unique needs of specific populations. We sought to examine knowledge, attitudes, and perceptions of African Americans living in Arizona toward CVD and etiological factors associated with health behaviors and chronic disease development to inform state health agency program development. Transcripts from 14 focus groups (n = 103) were analyzed using Grounded Theory for perceived disease risk, knowledge of CVD risk factors, nutrition, preventative behaviors, and barriers and motivators to behavior change. Participants identified CVD, stroke, and diabetes as leading health concerns among African-Americans but were less certain about the physiological consequences of these diseases. Diet, stress, low physical activity, family history, hypertension, and stroke were described as key CVD risk factors, but overweight and obesity were mentioned rarely. Participants described low socio-economic status and limited access to healthy foods as contributors to disease risk. Focus group members were open to modifying health behaviors if changes incorporated their input and were culturally acceptable. Respondents were 41% male and 59% female with a mean age of 46 years. This study provides insight into CVD and associated disease-related perceptions, knowledge, and attitudes among African Americans in the Southwest and recommendations for interventions to reduce CVD risk

Dry Bean Preferences and Attitudes among Midwest Hispanic and Non-Hispanic White Women

Bean (Phaseolus vulgaris L.) intakes in the United States (US) lag behind dietary recommendations despite their positive nutrition profile, health benefits for reducing chronic disease risk, and inclusion in nutrition assistance programs. Low-income groups, including Hispanics, have an increased risk of cardiovascular disease, type 2 diabetes, obesity, and some cancers. Hispanic dietary quality and bean consumption may decline with increasing acculturation. Intakes at recommended levels could improve health in all vulnerable low-income populations. The study objectives were to describe dry and canned bean preferences, consumption frequency, and attitudes among low-income Hispanic and non-Hispanic white women, and to assess if these characteristics differed by ethnicity and acculturation level among the Latinas. A convenience sample of 158 women, aged 18–65 years, completed a written survey in English or Spanish at two healthcare clinics, one Special Supplemental Nutrition Program for Women, Infants and Children office, and five County Extension nutrition education and outreach programs in Iowa. Less acculturated Latinas consumed beans more often, preferred dry to canned, bought in bulk, valued color and shape in dry bean selection, and held less positive attitudes toward canned beans in contrast to bicultural/more acculturated and non-Hispanic white women. Ethnicity and acculturation level have a role in varying purchase patterns and attitudes regarding dry and canned beans. Culturally-held differences should be considered in nutrition programs and leveraged to increase consumption and improve health

Simulating heterogeneous behaviours in complex systems on GPUs

Agent Based Modelling (ABM) is an approach for modelling dynamic systems and studying complex and emergent behaviour. ABMs have been widely applied in diverse disciplines including biology, economics, and social sciences. The scalability of ABM simulations is typically limited due to the computationally expensive nature of simulating a large number of individuals. As such, large scale ABM simulations are excellent candidates to apply parallel computing approaches such as Graphics Processing Units (GPUs). In this paper, we present an extension to the FLAME GPU 1 [1] framework which addresses the divergence problem, i.e. the challenge of executing the behaviour of non-homogeneous individuals on vectorised GPU processors. We do this by describing a modelling methodology which exposes inherent parallelism within the model which is exploited by novel additions to the software permitting higher levels of concurrent simulation execution. Moreover, we demonstrate how this extension can be applied to realistic cellular level tissue model by benchmarking the model to demonstrate a measured speedup of over 4x

Remarkably High Reactivity of Pd(OAc) 2 /Pyridine Catalysts: Nondirected CH Oxygenation of Arenes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87023/1/9581_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/87023/2/ange_201103327_sm_miscellaneous_information.pd

PCT and beyond: toward a computational framework for ‘intelligent’ communicative systems

Recent years have witnessed increasing interest in ‘intelligent’ autonomous machines such as robots. However, there is a long way to go before autonomous systems reach the level of capabilities required for even the simplest of tasks involving human-robot interaction - especially if it involves communicative behavior such as speech and language. The field of Artificial Intelligence (AI) has made great strides in these areas, and has graduated from high-level rule-based paradigms to embodied architectures whose operations are grounded in real physical environments. What is still missing, however, is an overarching theory of intelligent communicative behavior that informs system-level design decisions. This chapter introduces a framework that extends the principles of Perceptual Control Theory (PCT) toward a remarkably symmetric architecture for a needs-driven communicative agent. It is concluded that, if behavior is the control of perception (the central tenet of PCT), then perception (for communicative agents) is the simulation of behavior

From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones – star network vs. equal network - led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies