A complete decision-support infrastructure for food waste valorisation

The quantity of energy and materials embodied in food means that wasting a third of it, which is the level of inefficiency reached according to studies in recent years, impacts negatively on living standards at whatever level they are around the world. An increased level of consciousness about the issue has stimulated initiatives to address it, leading, sensibly, to the development of decision-making systems to support proper management of the materials. Here, we present the first review and evaluation of four recently developed systems targeting food waste. These tools broadly embody a logical model which identifies and quantifies food waste flows at different scales, characterises them, identifies appropriate conversion technologies, and enables assessment of the economic, environmental and social effects of different pathway options, along with other factors to provide a final fit with the circumstances of each owner of the food waste. Our review concludes that these tools are necessary but not sufficient to lift the management of food waste from a grossly sub-optimal level to a system which would be recognised by pre-and emerging-industrial generations but with valorisations of much higher value. Specifically, we identify knowledge-based elements of a management system which would be free of specific supply chain context and therefore have much greater power to direct resources affordably for maximum economic, environmental and social value

Current established risk assessment methodologies and tools

The technology behind information systems evolves at an exponential rate, while at the same time becoming more and more ubiquitous. This brings with it an implicit rise in the average complexity of systems as well as the number of external interactions. In order to allow a proper assessment of the security of such (sub)systems, a whole arsenal of methodologies, methods and tools have been developed in recent years. However, most security auditors commonly use a very small subset of this collection, that best suits their needs. This thesis aims at uncovering the differences and limitations of the most common Risk Assessment frameworks, the conceptual models that support them, as well as the tools that implement them. This is done in order to gain a better understanding of the applicability of each method and/or tool and suggest guidelines to picking the most suitable one

Prove It! Let the Data Tell the Story

Prove It! Let the Data Tell the Story is a hands-on course focusing on the use of data and basic statistics commonly used in public health. NH community leaders expressed the need for training about using data to support their efforts to improve the health of their communities and Prove It! was conceptualized by the Empowering Communities project to meet that need. Prove It! provides a basic understanding of why we use data and how to use data in community health assessment and monitoring, using the specific focus on writing grant applications as the example