A case study investigation of the learning needs of the Niagara grape and wine community

The Niagara Grape and Wine Community (NGWC) is an industry that has undergone rapid change and expansion as a result of changes in governmental regulations and consumer preferences. As a result of these changes, the demands of the wine industry workforce have changed to reflect the need to implement new strategies and practices to remain viable and competitive. The influx of people into the community with little or no prior practical experience in grape growing (viticulture) or winemaking (oenology) has created a need for additional training and learning opportunities to meet workforce needs. This case study investigated the learning needs of the members of this community and how these needs are currently being met. The barriers to, and the opportunities for, members acquiring new knowledge and developing skills were also explored. Participants were those involved in all levels of the industry and sectors (viticulture, processing, and retail), and their views on needs and suggestions for programs of study were collected. Through cross analyses of sectors, areas of common and unique interest were identified as well as formats for delivery. A common fundamental component was identified by all sectors - any program must have a significant applied component or demonstration of proficiency and should utilize members as peer instructors, mentors, and collaborators to generate a larger shared collective of knowledge. Through the review of learning organizations, learning communities, communities of practices, and learning networks, the principles for the development of a Grape and Wine Learning Network to meet the learning needs of the NGWC outside of formal institutional or academic programs were developed. The roles and actions of members to make such a network successful are suggested.

Intellectual property rights and the campaign for access to essential medicines : the advocacy role assumed by Médecins Sans Frontières

Non-governmental organizations and transnational networks have been increasingly successful a t gaining influence within issue areas traditionally controlled by the state. In many instances, non-state actors have been instrumental in forcing issues onto the global agenda, have aided in the development or transformation of global regimes, and have participated in securing state compliance for the adoption of new international norms. This paper argues that, consistent with social constructivist theory, ideas are important in influencing state preferences and change may be possible when certain factors are present. I f non-state actors can influence states, it is meaningful to understand how this happens. This paper focuses on a campaign led by Medecins Sans Frontieres that began in the late 1990s to acquire affordable medicines for patients in developing states that could not afford patented drugs. The campaign reached a measure of success in that member states of the World Trade Organization re-negotiated contested terms and meanings within the trade agreement for intellectual property rights and allowed concessions that would benefit lower income states. What factors contributed to the success of the campaign? And what were the most important factors - the issue, the actors or the mechanisms used?

Synthesis of 3', 5'-cyclic diguanylic acid (c-di-GMP) analogues

In the past few years, interest in signaling networks involving 3ʹ, 5ʹ -cyclic diguanylic acid (c-di-GMP) has increased dramatically. Evidence started to emerge that connects c-di-GMP to the regulation of a range of biological processes in bacteria, such as bacterial biofilm formation, virulence, extracellular polysaccharide synthesis, however, much remains to be explored in the signaling pathways that involve this secondary messenger. This molecule has also been shown to be a very powerful immunostimulating agent and potent mucosal vaccine adjuvant.

Community Detection in Multi-Layer Networks

In the scope of the current thesis we review and analyse networks that are formed by nodes with several attributes. We suppose that different layers of communities are embedded in such networks, besides each of the layers is connected with nodes' attributes. For example, examine one of a variety of online social networks: an user participates in a plurality of different groups/communities – schoolfellows, colleagues, clients, etc. We introduce a detection algorithm for the above-mentioned communities. Normally the result of the detection is the community supplemented just by the most dominant attribute, disregarding others. We propose an algorithm that bypasses dominant communities and detects communities which are formed by other nodes' attributes. We also review formation models of the attributed networks and present a Human Communication Network (HCN) model. We introduce a High School Texting Network (HSTN) and examine our methods for that network.