Designing a Web-Based Knowledge Repository in A Virtual Team and Exploring Its Usefulness

By using a computer network, geographically distributed people with common goals can communicate and collaborate their work efforts across time and space barriers. These groups has been called virtual teams (Geber, 1995). The virtual teams are used to support various kinds of collaborative efforts ranging from routine, mundane works to complex, creative works (Geber, 1995; Snizek, 1995). Because the virtual teams can bring together the right mix of people who have the appropriate set of knowledge, skills, information, and authority to solve difficult problems quickly and easily, they are receiving considerable attention from knowledge workers (Boldyreff et al., 1996; McGuire, 1996). These knowledge workers are characterized as highly qualified individuals who need to make decisions under non- routine, unstructured, and uncertain environments (Knight et al., 1993). As the numerous benefits and advantages of the virtual teams in increasing effectiveness and efficiency of knowledge workers becomes widely recognized, organizations face a new challenge in coping with their new organizational structure (Davidow & Malone, 1993). The challenge is to turn the scattered, diverse knowledge of their knowledge workers who are working in a virtual team into a well-structured knowledge repository (Spek & Spijkervet, 1996; Wiig, 1993)

Understanding the Motivations of Consumer Knowledge Sharing in Online Community

Today’s advanced web-based technologies create expanded opportunities for collaboration and customer knowledge sharing. However, research on customer knowledge sharing in web-based communication remains new. This study aims at proposing a theoretical framework for understanding customer sharing behaviors, which we define as voluntary acts of contributions by providing information or sharing experiences, from a motivational perspective. Our focus is on why people are motivated to make contributions in online community where contributions occur primarily through internet and communication technologies. We apply Maslow’s hierarchy of needs (the motivation theory) to explore how individual motivations influence customer knowledge sharing in online community. Particularly, customer knowledge sharing is modeled as a response to varied motivations. These motivations are proposed to be influenced by the availability of reputation systems. Given the importance of global knowledge sharing in today’s world, we expect the research findings can be useful for outlining some generic guidelines for promoting customer knowledge sharing in online community

Using Reputation System to Motivate Knowledge Contribution Behavior in Online Community

In this study, we present a theoretical model of motivations explaining the relationship between reputation system and knowledge contribution in online communities. Knowledge contribution is modeled as a response to varied motivations (base on Maslow’s hierarchy of needs). These motivations are proposed to be influenced by the availability of reputation systems. We test this model in an experiment. Given the importance of global knowledge sharing in today’s world, we expect our findings will be useful to inform the design of online knowledge-sharing communities

Family structure, parent-child conversation time and substance use among Chinese adolescents

<p>Abstract</p> <p>Background</p> <p>The family plays a vital role in shaping adolescent behaviours. The present study investigated the associations between family structure and substance use among Hong Kong Chinese adolescents.</p> <p>Methods</p> <p>A total of 32,961 Form 1 to 5 (grade 7-12 in the US) Hong Kong students participated in the Youth Smoking Survey in 2003-4. An anonymous questionnaire was used to obtain information about family structure, daily duration of parent-child conversation, smoking, alcohol drinking and drug use. Logistic regression was used to calculate the adjusted odds ratios (OR) for each substance use by family structure.</p> <p>Results</p> <p>Adjusting for sex, age, type of housing, parental smoking and school, adolescents from non-intact families were significantly more likely to be current smokers (OR = 1.62), weekly drinkers (OR = 1.72) and ever drug users (OR = 1.72), with significant linear increases in ORs from maternal, paternal to no-parent families compared with intact families. Furthermore, current smoking (OR = 1.41) and weekly drinking (OR = 1.46) were significantly more common among adolescents from paternal than maternal families. After adjusting for parent-child conversation time, the ORs for non-intact families remained significant compared with intact families, but the paternal-maternal differences were no longer significant.</p> <p>Conclusions</p> <p>Non-intact families were associated with substance use among Hong Kong Chinese adolescents. The apparently stronger associations with substance use in paternal than maternal families were probably mediated by the poorer communication with the father.</p

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security