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In this paper, optimisation models and heuristic algorithms that address the off-line survivability-supported Traffic Engineering (TE) problem in multi-service backbone networks are presented. In such networks traffic demands with different Quality of Service (QoS) and survivability requirements (e.g. existence of a node disjoint backup path for each primary path) inhere. The optimisation models for engineering the QoS traffic with different survivability prerequisites and the Best-Effort (BE) traffic are based on novel admission control/routing Integer Linear Programming (ILP) and Linear Programming (LP) optimisation sub-problems, which are solved sequentially. LP relaxations of the ILP sub-problems are also provided. The optimisation models and heuristic algorithms are tested on two different networks and their performance is compared.

Objectives: Risk Management has been recognized as a critical issue in computer infrastructures, especially in medium to large scale organizations and enterprises. The goal of this research report is to provide a practical comprehensive virtual machine based framework for assessing the performance of vulnerability scanners applied to such enterprises, focused to small and medium size ones towards a risk evaluation analysis. Moreover, the purpose of this paper is to compare three of the most well-known free vulnerability scanners (Nessus, OpenVAS, Nmap Scripting Engine) with regards to how they can be used to systematise the process of Risk Assessment in an enterprise, based on the herein presented experimental evaluation framework involving virtual machine testing. Method: The proposed methodology is based on developing a framework for suitable setup and usage of virtual machines making risk analysis practical and being capable of comparing different vulnerability scanners. Findings: The herein developed framework is shown to be efficient with regards to comparison and selection of candidate risk analysis software with easily accessed and affordable infrastructure. Novelty: Although there might be few other similar comparisons of vulnerability scanners in the literature, the main herein contribution is the provision of a practical and above all easily reproducible framework for small business enterprises to establish proper selection procedures of such security software without spending a lot of money for expensive testing infrastructure. Keywords: Vulnerability Scanning; risk assessment; nessus; OpenVAS; Nmap scripting engine

Risk Assessment has been identified as a critical issue in computer infrastructures, especially in medium to large scale organizations and enterprises. The goal of this research report is to provide a virtual machine based framework for testing the performance of vulnerability scanners applied to such enterprises, focused to small and medium size ones. Moreover, the purpose of this paper is to compare three of the most well-known free vulnerability scanning solutions (Nessus, OpenVAS, Nmap Scripting Engine) in regards to how they can be used to automate the process of Risk Assessment in an organization, based on the herein presented experimental evaluation framework involving virtual machine testing.

The understanding of Business Process modelling is an essential approach for an Organization or Enterprise to achieve set objectives and improve its operations. Recent development has shown the importance of representing processes to carry out continuous improvement. One important aspect of enterprise modelling is actually its involvement in competition. The modelling and simulation of Business Processes has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimize the Business Process to reduce cost of running the Organization, and the required resources needed for an Organization. Although large scale organizations have already been involved in such BPM applications, on the other hand, Small Medium Enterprises (SME) have not drawn much attention with this respect. It seems that SME need more practical tools for modelling and analysis with minimum expenses if possible. One approach to make BPM more applicable to SME but, also, to larger scale organizations would be to properly integrate it with analytical management computational techniques, including the game-theoretic analysis, the Markov-chain modelling and the Cognitive Maps methodology. In BPM research the Petri Nets methodology has already been involved in theory, applications and BPM Software tools. However, this is not the case in the previously mentioned as well as to other analytical management techniques. It is, therefore, important in BPM research to take into account such techniques but focusing on specific modelling requirements. One such requirement is the modelling of market share competition. This paper presents an overview of some important analytical management computational techniques, as the above, that could be integrated in the BPM framework, based on the market share competition analysis paradigm. It provides an overview along with examples of market share competition analysis of the applicability of such methods in the BPM field. The major goal of this systematic overview is to propose steps for the integration of such analytical techniques in the BPM framework so that they could be widely applied.

Although Business process modelling is an increasingly popular research area for both organisations and enterprises due to its usefulness in optimizing resources management, business reengineering and business performance, it is not yet widely accepted in Small and Medium size Enterprises (SMEs), which are vital for sustainable economy development. The understanding of Business Process is an essential approach for an Organization to achieve set objectives and improve its operations. It has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimize the Business Process to reduce cost of running the Organization, and the required resources needed for an Organization. This is clear for large scale organizations and enterprises but under research investigation for SMEs. Business Process Modelling (BPM) is a representation of the processes of the Organization. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. This is even more accurate in the case of selecting proper BPM software tools to achieve those BPM modelling and simulation goals. This paper aims at presenting a comparative analysis of some relatively popular business process modelling techniques focusing on the associated software tools. The comparative framework proposed is based on the following major criteria: data flow capability, logical reasoning and understandability, specification of roles, and capability of simulation, flexibility and ease of use, simulation support and scope. However, the emphasis of this investigation is put on SME applicability of these tools and techniques. Therefore, the first goal is to define proper selection criteria for the application of BPM tools to SMEs. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures focusing on a comparison of existing tools to implement these techniques properly for SMEs. This is to enable a potential user/modeller choose the right technique and tool in modelling critical SME Business Processes in order to analyse and optimize its operations.

This paper presents two novel heuristic algorithms for the design of wireless access networks (QoS-HWNDA-1, QoSHWNDA-2) adapted in the case of QoS networks, which is the prevalent situation in the evolution of 5G technology. Emphasis was given to the design of CDMA based wireless networks and Fixed Wireless networks considering QoS architectures. The objectives of these methods are first to place a number of access points/base stations in a number of candidate sites and then to assign a number of fixed wireless terminals to the selected access points/base stations, while ensuring QoS requirements. Both methods are based on Graph Theory and they are essentially greedy algorithms. Except from capacity constraints, wireless reception characteristics are also considered. The algorithms are capable of designing medium and large-scale networks at polynomial time. Both algorithms were compared with a rival optimization problem through a series of tests. The results indicate that as regards design costs the performance of the proposed heuristic algorithms is very close to this of the equivalent optimization problem. The solution times for the proposed heuristic algorithms are smaller especially when the number of the candidate access points/base stations becomes large.

© 2016 The Auhtors. Published by Elsevier Inc. Reactive oxygen species, such as H2O2, can damage cells but also promote fundamental processes, including growth, differentiation and migration. The mechanisms allowing cells to differentially respond to toxic or signaling H2O2levels are poorly defined. Here we reveal that increasing external H2O2produces a bi-phasic response in intracellular H2O2. Peroxiredoxins (Prx) are abundant peroxidases which protect against genome instability, ageing and cancer. We have developed a dynamic model simulating in vivo changes in Prx oxidation. Remarkably, we show that the thioredoxin peroxidase activity of Prx does not provide any significant protection against external rises in H2O2. Instead, our model and experimental data are consistent with low levels of extracellular H2O2being efficiently buffered by other thioredoxin-dependent activities, including H2O2-reactive cysteines in the thiol-proteome. We show that when extracellular H2O2levels overwhelm this buffering capacity, the consequent rise in intracellular H2O2triggers hyperoxidation of Prx to thioredoxin-resistant, peroxidase-inactive form/s. Accordingly, Prx hyperoxidation signals that H2O2defenses are breached, diverting thioredoxin to repair damage.

Undoubtedly, Business process modelling is an increasingly popular research area for both organisations and enterprises due to its usefulness in facilitating better planning of resources, business re-engineering and optimized business performance. The understanding of Business Process is an essential approach for an Organization to achieve set objectives and improve its operations. Business Process Modelling is a representation of the processes of the organization. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, available techniques view business processes from different perspectives and have different features and capabilities. Furthermore, to date limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. Recent development has shown the importance of representing processes to carry out continuous improvement. The modelling and simulation of Business Processes has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimise the Business Process to reduce cost of running the organization, and the required resources needed for an organization. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on the following major criteria: data flow capability, logical reasoning and understandability, specification of roles, and capability of simulation, flexibility and ease of use, simulation support and scope. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures focusing on a comparison of existing tools to implement these techniques. This is to enable a potential user/modeller choose the right technique and tool in modelling critical Business Processes in order to analyse and optimise the operations of an organization.

The goal of this paper is to investigate the application of the Multi Agent technology in modeling and simulating large scale wireless communication systems. There are very few studies using the multi agent concept as an alternative approach for designing and simulating resource allocation in cellular systems and especially in large scale ones. Thus, a novel modeling methodology of wireless network services exploiting multi agent technology and investigating in depth critical agent issues is proposed in this paper. It is shown that the multi agent concept proves to be a suitable solution for modeling and implementing cellular network services simulation even in the case of large scale wireless networks. The whole investigation is divided in two phases: (a) multi agent modeling analysis and (b) multi agent model development for controlling network performance. Simulation results show the effectiveness of the proposed multi agent model when is applied in combination with the state of the art event scheduling mechanism.

The number of users employing multimedia services in cellular networks has been increased dramatically in the last decade. Multimedia services are more demanding compared to traditional voice services in terms of bandwidth availability and integrity. The capacity and the bandwidth reservation on demand according to QoS requirements are key concepts in mobile cellular communications. The available frequency spectrum is limited and the demand for enhanced mobile user facilities is increasing day by day, hence the channels must be reused as much as possible to increase the system capacity. Existingand proposed channel assignment strategies have to be transformed to support efficiently the new demanding multimedia services. Through this paper we present a review of the most known channel assignment strategies, as well as their QoS aspects and we propose new DCA variations and a channel architecture adapted to QoS requirements for supporting multimedia services. We also present some strategies, models and conclusions for algorithm evaluation based on experimental results.

Heuristic schemes and algorithms are successfully used for solving optimization problems. A great challenge in large-scale wireless networks is the channel allocation adaptability to dynamic network traffic conditions, which can be formulated as a discrete optimization problem. Several approaches such as genetic algorithms and multi-agent techniques have been applied so far in the literature for solving the resource management problem focusing mainly on network base-stations representation. A very promising intelligent approach known as ant colony optimization (ACO) which constitutes a special form of swarm intelligence has been used for solving routing problems. This approach has been introduced by the authors for improving the channel allocation in large-scale wireless networks, focusing on network procedures as the basic model component and not on network nodes as so far found in the literature. A comprehensive intelligent model architecture based on multi-agent systems technology and ACO for channel allocation in cellular networks is herein analysed and proposed. Moreover, the decision making for channel allocation is presented as well as the network-ant agent communication model. The new methodology for integrating ACO schemes and decision making regarding spectrum reuse in a multi-agent framework, through a novel agent negotiation approach, is the main contribution of this research. Finally, the simulation results show the large-scale wireless network performance improvement in terms of efficient resource management.

Exon skipping is considered a principal mechanism by which eukaryotic cells expand their transcriptome and proteome repertoires, creating different splice variants with distinct cellular functions. Here we analyze RNA-seq data from 116 transcriptomes in fission yeast (Schizosaccharomyces pombe), covering multiple physiological conditions as well as transcriptional and RNA processing mutants. We applied brute-force algorithms to detect all possible exon-skipping events, which were widespread but rare compared to normal splicing events. Exon-skipping events increased in cells deficient for the nuclear exosome or the 5-3 exonuclease Dhp1, and also at late stages of meiotic differentiation when nuclear-exosome transcripts decreased. The pervasive exon-skipping transcripts were stochastic, did not increase in specific physiological conditions, and were mostly present at less than one copy per cell, even in the absence of nuclear RNA surveillance and during late meiosis. These exon-skipping transcripts are therefore unlikely to be functional and may reflect splicing errors that are actively removed by nuclear RNA surveillance. The average splicing rate by exon skipping was ∼ 0.24% in wild type and ∼ 1.75% in nuclear exonuclease mutants. We also detected approximately 250 circular RNAs derived from single or multiple exons. These circular RNAs were rare and stochastic, although a few became stabilized during quiescence and in splicing mutants. Using an exhaustive search algorithm, we also uncovered thousands of previously unknown splice sites, indicating pervasive splicing; yet most of these splicing variants were cryptic and increased in nuclear degradation mutants. This study highlights widespread but low frequency alternative or aberrant splicing events that are targeted by nuclear RNA surveillance.

In this paper, the perceived difficulty for students learning purely through auditory and visual means, such as via the standard lecture format, is highlighted through a literature review of learning styles and methods, and a solution based upon interactive computer case-based learning is proposed through a new and continuously evolving simulation environment called Management Laboratory, or simply MagLab. The software was developed using the open-source, high-level scripting language Tcl/Tk and it was designed to run under both Unix/Linux and Windows. An insight into the characteristics of MagLab brings out its many capabilities and strong points of simplicity, user friendliness, intelligence and extensibility.

Efficient design and evaluation of complex wireless communication systems in terms of spectrum reuse can be accomplished using advanced simulation environments. To this goal, network modelling and simulation methodologies are the most critical issues, thus, several Discrete Event Simulation (DES) schemes have been introduced in the literature. In a real wireless network,services such as new call admission, reallocation, etc, should be offered at the same time for different mobile users in the network coverage area. Thus, the network modelling must be based on the network operational concurrency and services independence. The simulation model adaptation to real network behaviour is a challenging goal. Herein, a novel simulation methodology based on multi-threading for simulating wireless networks, compared to the state of the art approach, is presented, preliminarily analyzed and discussed. Moreover, various implementations based on multi-threading and multi-agent concepts are also presented and evaluated.

The greatest risk factor for Alzheimer's disease (AD) is age, and changes in the ageing nervous system are likely contributors to AD pathology. Amyloid beta (Abeta) accumulation, which occurs as a result of the amyloidogenic processing of amyloid precursor protein (APP), is thought to initiate the pathogenesis of AD, eventually leading to neuronal cell death. Previously, we developed an adult-onset Drosophila model of AD. Mutant Abeta42 accumulation led to increased mortality and neuronal dysfunction in the adult flies. Furthermore, we showed that lithium reduced Abeta42 protein, but not mRNA, and was able to rescue Abeta42-induced toxicity. In the current study, we investigated the mechanism/s by which lithium modulates Abeta42 protein levels and Abeta42 induced toxicity in the fly model. We found that lithium caused a reduction in protein synthesis in Drosophila and hence the level of Abeta42. At both the low and high doses tested, lithium rescued the locomotory defects induced by Abeta42, but it rescued lifespan only at lower doses, suggesting that long-term, high-dose lithium treatment may have induced toxicity. Lithium also down-regulated translation in the fission yeast Schizosaccharomyces pombe associated with increased chronological lifespan. Our data highlight a role for lithium and reduced protein synthesis as potential therapeutic targets for AD pathogenesis.

This paper presents an overview of three information‐theoretic methods, which have been used extensively in many areas such as signal/image processing, pattern recognition and statistical inference. These are: the maximum entropy (ME), minimum cross‐entropy (MCE) and mutual information (MI) methods. The development history of these techniques is reviewed, their essential philosophy is explained, and typical applications, supported by simulation results, are discussed.

In this paper, the perceived difficulty for students learning purely through auditory and visual means, such as via the standard lecture format, is highlighted through a literature review of learning styles and methods, and a solution based upon interactive computer case-based learning through worksheets is proposed. A brief history of Information Theory is discussed and a review of the various software packages available is made and Mathematica selected. The contents of the worksheets are described and conclusions made.

In recent years, mobile telephony, computing and services have emerged as an important field of research. The rapid evolution of cellular technology and the augmentative user demand for advanced mobile services leads the industry to develop more efficient network structures. The increasing number of cellular users and the demand for broadband mobile communications (3rd and 4th generation) drives to the research of new methodologies for the design of cellular networks and services. One of the issues in such a design is selection of channel allocation schemes. This paper thoroughly reviews centralized and mainly distributed DCA schemes and presents several new efficient variations suitable for large scale cellular systems. On the other hand, Simulation environments more than ever offer the opportunity to develop and study with low cost new structures and methods for the implementation of new services. To this end, this paper proposes a comprehensive simulation system for evaluating channel assignment schemes incorporating their principles, entities and concepts involved. The proposed system is implemented in Java, in order to create a high performance generic simulation environment with the future capability of internetworking. The system is designed with the goal to be efficient in simulating large scale generic cellular telecommunication systems. Moreover, another goal of the proposed system is to serve as a test bed for the evaluation and development of DCA schemes (especially for educational purposes) involved in such large scale cellular systems towards their planning as effective cellular mobile radio networks.

Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area of interest of the network. In addition, coverage is associated with connectivity and energy consumption, both important aspects in the design process of a Wireless Sensor Network (WSN). On the other hand, simulating a WSN involves taking into account different software and hardware aspects. In this paper we attempt to present a simulation framework suitable for integrating coverage mechanisms in WSN emulation using a layered architecture and a fitting scheduling model. The suggested model is derived after a critical overview and presentation of the coverage strategies as well as the simulation approaches for WSN developed so far. The main advantage of the proposed framework is its capability to handle concurrent events occurring at WSN deployment and operation through the suitable layered scheduler integrated.