Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems

BACKGROUND: Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. RESULTS: We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. CONCLUSIONS: Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly

Preventing disease through opportunistic, rapid engagement by primary care teams using behaviour change counselling (PRE-EMPT): protocol for a general practice-based cluster randomised trial

BACKGROUND: Smoking, excessive alcohol consumption, lack of exercise and an unhealthy diet are the key modifiable factors contributing to premature morbidity and mortality in the developed world. Brief interventions in health care consultations can be effective in changing single health behaviours. General Practice holds considerable potential for primary prevention through modifying patients' multiple risk behaviours, but feasible, acceptable and effective interventions are poorly developed, and uptake by practitioners is low. Through a process of theoretical development, modeling and exploratory trials, we have developed an intervention called Behaviour Change Counselling (BCC) derived from Motivational Interviewing (MI). This paper describes the protocol for an evaluation of a training intervention (the Talking Lifestyles Programme) which will enable practitioners to routinely use BCC during consultations for the above four risk behaviours. METHODS/DESIGN: This cluster randomised controlled efficacy trial (RCT) will evaluate the outcomes and costs of this training intervention for General Practitioners (GPs) and nurses. Training methods will include: a practice-based seminar, online self-directed learning, and reflecting on video recorded and simulated consultations. The intervention will be evaluated in 29 practices in Wales, UK; two clinicians will take part (one GP and one nurse) from each practice. In intervention practices both clinicians will receive training. The aim is to recruit 2000 patients into the study with an expected 30% drop out. The primary outcome will be the proportion of patients making changes in one or more of the four behaviours at three months. Results will be compared for patients seeing clinicians trained in BCC with patients seeing non-BCC trained clinicians. Economic and process evaluations will also be conducted. DISCUSSION: Opportunistic engagement by health professionals potentially represents a cost effective medical intervention. This study integrates an existing, innovative intervention method with an innovative training model to enable clinicians to routinely use BCC, providing them with new tools to encourage and support people to make healthier choices. This trial will evaluate effectiveness in primary care and determine costs of the intervention

A randomized trial to assess the impact of opinion leader endorsed evidence summaries on the use of secondary prevention strategies in patients with coronary artery disease: the ESP-CAD trial protocol [NCT00175240]

BACKGROUND: Although numerous therapies have been shown to be beneficial in the prevention of myocardial infarction and/or death in patients with coronary disease, these therapies are under-used and this gap contributes to sub-optimal patient outcomes. To increase the uptake of proven efficacious therapies in patients with coronary disease, we designed a multifaceted quality improvement intervention employing patient-specific reminders delivered at the point-of-care, with one-page treatment guidelines endorsed by local opinion leaders ("Local Opinion Leader Statement"). This trial is designed to evaluate the impact of these Local Opinion Leader Statements on the practices of primary care physicians caring for patients with coronary disease. In order to isolate the effects of the messenger (the local opinion leader) from the message, we will also test an identical quality improvement intervention that is not signed by a local opinion leader ("Unsigned Evidence Statement") in this trial. METHODS: Randomized trial testing three different interventions in patients with coronary disease: (1) usual care versus (2) Local Opinion Leader Statement versus (3) Unsigned Evidence Statement. Patients diagnosed with coronary artery disease after cardiac catheterization (but without acute coronary syndromes) will be randomly allocated to one of the three interventions by cluster randomization (at the level of their primary care physician), if they are not on optimal statin therapy at baseline. The primary outcome is the proportion of patients demonstrating improvement in their statin management in the first six months post-catheterization. Secondary outcomes include examinations of the use of ACE inhibitors, anti-platelet agents, beta-blockers, non-statin lipid lowering drugs, and provision of smoking cessation advice in the first six months post-catheterization in the three treatment arms. Although randomization will be clustered at the level of the primary care physician, the design effect is anticipated to be negligible and the unit of analysis will be the patient. DISCUSSION: If either the Local Opinion Leader Statement or the Unsigned Evidence Statement improves secondary prevention in patients with coronary disease, they can be easily modified and applied in other communities and for other target conditions

Here's Johnny: a Methodology for Developing Attacker Personas

http://trove.nla.gov.au/work/870572

"Nur ein paar Milliönchen, Onkel!"

Rudolf Schöppe

Modeling Architectures of Cyber Physical Systems

Cyber-physical systems (CPS) in automotive or robotics industry comprise many different specific features, e.g., trajectory planning, lane correction, battery management or engine control, requiring a steady interaction with their environment over sensors and actuators. Assembling all these different features is one of the key challenges in the development of such complex systems. Component and connector (C&C) models are widely used for the design and development of CPS to represent features and their logical interaction. An advantage of C&C models is that complex features can be hierarchically decomposed into subfeatures, developed and managed by different domain experts. In this paper, we present the textual modeling family MontiCAR, Modeling and Testing of Cyber-Physical Architectures. It is based on the C&C paradigm and increases development efficiency of CPS by incorporating (i) component and connector arrays, (ii) name and index based autoconnections, (iii) a strict type system with unit and accuracy support, as well as (iv) an advanced Math language supporting BLAS operations and matrix classifications. Arrays and their autoconnection modes allow an efficient way of modeling redundant components such as front and rear park sensors or an LED matrix system containing hundreds of single dimmable lights. The strict type system and matrix classification provide means for integrated static verification of C&C architectures at compile time minimizing bug-fixing related costs. The capabilities and benefits of the proposed language family are demonstrated by a running example of a parking assistance system