Plant-Made Bet v 1 for Molecular Diagnosis

Allergic disease diagnosis is currently experiencing a breakthrough due to the use of allergenic molecules in serum-based assays rather than allergen extracts in skin tests. The former methodology is considered a very innovative technology compared with the latter, since it is characterized by flexibility and adaptability to the patient’s clinical history and to microtechnology, allowing multiplex analysis. Molecular-based analysis requires pure allergens to detect IgE sensitization, and a major goal, to maintain the diagnosis cost-effective, is to limit their production costs. In addition, for the production of recombinant eukaryotic proteins similar to natural ones, plant-based protein production is preferred to bacterial-based systems due to its ability to perform most of the post-translational modifications of eukaryotic molecules. In this framework, Plant Molecular Farming (PMF) may be useful, being a production platform able to produce complex recombinant proteins in short time-frames at low cost. As a proof of concept, PMF has been exploited for the production of Bet v 1a, a major allergen associated with birch (Betula verrucosa) pollen allergy. Bet v 1a has been produced using two different transient expression systems in Nicotiana benthamiana plants, purified and used in a new generation multiplex allergy diagnosis system, the patient-Friendly Allergen nano-BEad Array (FABER). Plant-made Bet v 1a is immunoreactive, binding IgE and inhibiting IgE-binding to the Escherichia coli expressed allergen currently available in the FABER test, thus suggesting an overall similar though non-overlapping immune activity compared with the E. coli expressed form

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Automatic Verification of Timeliness Constraints in a Public Mobile Network

Automatic Verification of Timeliness Constraints in a Public Mobile Networ

Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Dependable systems; Probabilistic methods; Bayesian networks; Fault tree analysis 1

Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system

Active distribution grids: A MatLab-Simulink tool for energy performance analysis

The present paper deals with the topic of the planning of distribution networks, equipped with Dispersed Generation (DG), and so active grids. Different issues related of this topic are widely present in the scientific literature of the last years, due to the big spread of renewable energy sources (RES), typically in small generation power plants connected to the Medium Voltage (MV) and Low Voltage (LV) systems. The research team, authoring this paper, has been involved in a National Project, named SINERGREEN (Smart INtelligent EneRgy GREEN) dealing with the topic of the smart grids and energy efficiency. In the framework of the project, the researchers have developed a simulation tool, dedicated to the electrical grids, able to calculate some energy performance indicators, that can be used for evaluating operation of the network and so for addressing the decisions of a Distribution System Operator (DSO) in terms of planning and development of its grids for a better integration of RES power plants in DG. In the present paper the tool is presented, the main Indicators are reported and the results of the application of the methodology implemented to a case study are reported

Reliability Analysis of Multi-source Multi-sink Critical Interacting Systems

Traditional reliability studies on probabilistic networks are devoted to evaluate the probability that two nodes or K nodes are connected, assuming that nodes are undifferentiated. In flow networks, however, we need to distinguish between source nodes where the flow is generated and sink nodes where the flow is utilized. Sink nodes may usually be fed by many sources. To this end, we have extended the traditional studies to include multi-source multi-sink networks. A case study is analysed consisting in a portion of an electrical grid controlled by a its SCADA system through a public telecommunication network