Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

On producing and sharing knowledge across boundaries: experiences from the interfaces of an international development research network

The number of large research networks and programmes engaging in knowledge production for development has grown over the past years. One of these programmes devoted to generating knowledge about and for development is National Centre of Competence in Research (NCCR) North–South, a cross-disciplinary, international development research network funded by the Swiss Agency for Development and Cooperation and the Swiss National Science Foundation. Producing relevant knowledge for development is a core goal of the programme and an important motivation for many of the participating researchers. Over the years, the researchers have made use of various spaces for exchange and instruments for co-production of knowledge by academic and non-academic development actors. In this article we explore the characteristics of co-producing and sharing knowledge in interfaces between development research, policy and NCCR North–South practice. We draw on empirical material of the NCCR North–South programme and its specific programme element of the Partnership Actions. Our goal is to make use of the concept of the interface to reflect critically about the pursued strategies and instruments applied in producing and sharing knowledge for development across boundaries.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Knowledge transfer in software-maintenance offshore outsourcing

Software-maintenance offshore outsourcing (SMOO) projects have been plagued by tedious knowledge transfer during the service transition to the vendor. Vendor engineers risk being over-strained by the high amounts of novel information, resulting in extra costs that may erode the business case behind offshoring. Although stakeholders may desire to avoid these extra costs by implementing appropriate knowledge transfer practices, little is known on how effective knowledge transfer can be designed and managed in light of the high cognitive loads in SMOO transitions. The dissertation at hand addresses this research gap by presenting and integrating four studies. The studies draw on cognitive load theory, attributional theory, and control theory and they apply qualitative, quantitative, and simulation methods to qualitative data from eight in-depth longitudinal cases. The results suggest that the choice of appropriate learning tasks may be more central to knowledge transfer than the amount of information shared with vendor engineers. Moreover, because vendor staff may not be able to and not dare to effectively self-manage learn-ing tasks during early transition, client-driven controls may be initially required and subsequently faded out. Collectively, the results call for people-based rather than codification-based knowledge management strategies in at least moderately specific and complex software environments.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

Sharing evidence of sustainable land management impacts

Ensuring sustainable use of natural resources is crucial for maintaining the basis for our livelihoods. With threats from climate change, disputes over water, biodiversity loss, competing claims on land, and migration increasing worldwide, the demands for sustainable land management (SLM) practices will only increase in the future. For years already, various national and international organizations (GOs, NGOs, donors, research institutes, etc.) have been working on alternative forms of land management. And numerous land users worldwide – especially small farmers – have been testing, adapting, and refining new and better ways of managing land. All too often, however, the resulting SLM knowledge has not been sufficiently evaluated, documented and shared. Among other things, this has often prevented valuable SLM knowledge from being channelled into evidence-based decision-making processes. Indeed, proper knowledge management is crucial for SLM to reach its full potential. Since more than 20 years, the international WOCAT network documents and promotes SLM through its global platform. As a whole, the WOCAT methodology comprises tools for documenting, evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing, analysis and use for decision support in the field, at the planning level, and in scaling up identified good practices. In early 2014, WOCAT’s growth and ongoing improvement culminated in its being officially recognized by the UNCCD as the primary recommended database for SLM best practices. Over the years, the WOCAT network confirmed that SLM helps to prevent desertification, to increase biodiversity, enhance food security and to make people less vulnerable to the effects of climate variability and change. In addi- tion, it plays an important role in mitigating climate change through improving soil organic matter and increasing vegetation cover. In-depth assessments of SLM practices from desertification sites enabled an evaluation of how SLM addresses prevalent dryland threats. The impacts mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Among others, favourable local-scale cost-benefit relationships of SLM practices play a crucial role in their adoption. An economic analysis from the WOCAT database showed that land users perceive a large majority of the technologies as having benefits that outweigh costs in the long term. The high investment costs associated with some practices may constitute a barrier to adoption, however, where appropriate, short-term support for land users can help to promote these practices. The increased global concerns on climate change, disaster risks and food security redirect attention to, and trigger more funds for SLM. To provide the necessary evidence-based rationale for investing in SLM and to reinforce expert and land users assessments of SLM impacts, more field research using inter- and transdisciplinary approaches is needed. This includes developing methods to quantify and value ecosystem services, both on-site and off-site, and assess the resilience of SLM practices, as currently aimed at within the EU FP7 projects CASCADE and RECARE.