Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.

Measuring the Diversity and the Integration of Film Production in Mercosur: A Social Network Analysis

Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.

Female employment from the household. Towards a comprehensive analysis of work-life articulation

Research on women’s employment has proliferated over recent decades, often under a perspective that conceptualizes female labour market activity as independent of male presences and absences in the productive and reproductive spheres. In the face of these approaches, the article argues the need to focus on the couple as the unit of analysis of work-life articulation. After referring to the main theoretical arguments that, from a gender perspective within labour studies, have pointed out the relevance of placing the household as the central space for the analysis of the sexual division of labour, the article reviews different empirical contributions that have incorporated such perspective in the international literature. Next, the state of the art in the Spanish literature is presented, before arguing the desirability of applying such framework of analysis to the study of employment and care work in Spanish households, which are at present undergoing major transformations.

Non-conventional advertising formats in television versus spots: An analysis based on the generated recall

Advertising investment and audience figures indicate that television continues to lead as a mass advertising medium. However, its effectiveness is questioned due to problems such as zapping, saturation and audience fragmentation. This has favoured the development of non-conventional advertising formats. This study provides empirical evidence for the theoretical development. This investigation analyzes the recall generated by four non-conventional advertising formats in a real environment: short programme (branded content), television sponsorship, internal and external telepromotion versus the more conventional spot. The methodology employed has integrated secondary data with primary data from computer assisted telephone interviewing (CATI) were performed ad-hoc on a sample of 2000 individuals, aged 16 to 65, representative of the total television audience. Our findings show that non-conventional advertising formats are more effective at a cognitive level, as they generate higher levels of both unaided and aided recall, in all analyzed formats when compared to the spot.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Feature Study on a Programmable Network Traffic Classifier

Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

Effective network security monitoring: from attribution to target-centric monitoring

Network security monitoring remains a challenge. As global networks scale up, in terms of traffic, volume and speed, effective attribution of cyber attacks is increasingly difficult. The problem is compounded by a combination of other factors, including the architecture of the Internet, multi-stage attacks and increasing volumes of nonproductive traffic. This paper proposes to shift the focus of security monitoring from the source to the target. Simply put, resources devoted to detection and attribution should be redeployed to efficiently monitor for targeting and prevention of attacks. The effort of detection should aim to determine whether a node is under attack, and if so, effectively prevent the attack. This paper contributes by systematically reviewing the structural, operational and legal reasons underlying this argument, and presents empirical evidence to support a shift away from attribution to favour of a target-centric monitoring approach. A carefully deployed set of experiments are presented and a detailed analysis of the results is achieved.

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

Use of social network analysis to identify the coopetition in a Commercial Cluster Plan

The cluster provides a greater commercial relationship between the companies that comprise it. This encourages companies to adopt competitive structures that allow solving problems that would hardly alone (Lubeck et. Al., 2011). With that this paper aims to describe the coopetition between companies operating on a commercial cluster planned, from the point of view of retailers, taking as a basis the theoretical models proposed by Bengtsson and Kock (1999) and Leon (2005) and operationalized by means of Social Network Analysis (SNA). Data collection consisted of two phases, the first exploratory aspect to identify the actors, and the second was characterized as descriptive as it aims to describe the coopetition among the enterprises. As a result we identified the companies that cooperate and compete simultaneously (coopetition), firms that only compete, companies just cooperate and businesses that do not compete and do not cooperate (coexistence).

Power relations and good governance: a social network analysis of the evolution of the integrity in public office act in the Commonwealth of Dominica

La Banque mondiale propose la bonne gouvernance comme la stratégie visant à corriger les maux de la mauvaise gouvernance et de faciliter le développement dans les pays en développement (Carayannis, Pirzadeh, Popescu & 2012; & Hilyard Wilks 1998; Leftwich 1993; Banque mondiale, 1989). Dans cette perspective, la réforme institutionnelle et une arène de la politique publique plus inclusive sont deux stratégies critiques qui visent à établir la bonne gouvernance, selon la Banque et d’autres institutions de Bretton Woods. Le problème, c’est que beaucoup de ces pays en voie de développement ne possèdent pas l’architecture institutionnelle préalable à ces nouvelles mesures. Cette thèse étudie et explique comment un état en voie de développement, le Commonwealth de la Dominique, s’est lancé dans un projet de loi visant l’intégrité dans la fonction publique. Cette loi, la Loi sur l’intégrité dans la fonction publique (IPO) a été adoptée en 2003 et mis en œuvre en 2008. Cette thèse analyse les relations de pouvoir entre les acteurs dominants autour de évolution de la loi et donc, elle emploie une combinaison de technique de l’analyse des réseaux sociaux et de la recherche qualitative pour répondre à la question principale: Pourquoi l’État a-t-il développé et mis en œuvre la conception actuelle de la IPO (2003)? Cette question est d’autant plus significative quand nous considérons que contrairement à la recherche existante sur le sujet, l’IPO dominiquaise diverge considérablement dans la structure du l’IPO type idéal. Nous affirmons que les acteurs "rationnels," conscients de leur position structurelle dans un réseau d’acteurs, ont utilisé leurs ressources de pouvoir pour façonner l’institution afin qu’elle serve leurs intérêts et ceux et leurs alliés. De plus, nous émettons l’hypothèse que: d’abord, le choix d’une agence spécialisée contre la corruption et la conception ultérieure de cette institution reflètent les préférences des acteurs dominants qui ont participé à la création de ladite institution et la seconde, notre hypothèse rivale, les caractéristiques des modèles alternatifs d’institutions de l’intégrité publique sont celles des acteurs non dominants. Nos résultats sont mitigés. Le jeu de pouvoir a été limité à un petit groupe d’acteurs dominants qui ont cherché à utiliser la création de la loi pour assurer leur légitimité et la survie politique. Sans surprise, aucun acteur n’a avancé un modèle alternatif. Nous avons conclu donc que la loi est la conséquence d’un jeu de pouvoir partisan. Cette recherche répond à la pénurie de recherche sur la conception des institutions de l’intégrité publique, qui semblent privilégier en grande partie un biais organisationnel et structurel. De plus, en étudiant le sujet du point de vue des relations de pouvoir (le pouvoir, lui-même, vu sous l’angle actanciel et structurel), la thèse apporte de la rigueur conceptuelle, méthodologique, et analytique au discours sur la création de ces institutions par l’étude de leur genèse des perspectives tant actancielles que structurelles. En outre, les résultats renforcent notre capacité de prédire quand et avec quelle intensité un acteur déploierait ses ressources de pouvoir.

Using social network analysis to identify key stakeholders in agricultural biodiversity governance and related land-use decisions at regional and local level

In 2013 the European Commission launched its new green infrastructure strategy to make another attempt to stop and possibly reverse the loss of biodiversity until 2020, by connecting habitats in the wider landscape. This means that conservation would go beyond current practices to include landscapes that are dominated by conventional agriculture, where biodiversity conservation plays a minor role at best. The green infrastructure strategy aims at bottom-up rather than top-down implementation, and suggests including local and regional stakeholders. Therefore, it is important to know which stakeholders influence land-use decisions concerning green infrastructure at the local and regional level. The research presented in this paper served to select stakeholders in preparation for a participatory scenario development process to analyze consequences of different implementation options of the European green infrastructure strategy. We used a mix of qualitative and quantitative social network analysis (SNA) methods to combine actors’ attributes, especially concerning their perceived influence, with structural and relational measures. Further, our analysis provides information on institutional backgrounds and governance settings for green infrastructure and agricultural policy. The investigation started with key informant interviews at the regional level in administrative units responsible for relevant policies and procedures such as regional planners, representatives of federal ministries, and continued at the local level with farmers and other members of the community. The analysis revealed the importance of information flows and regulations but also of social pressure, considerably influencing biodiversity governance with respect to green infrastructure and biodiversity.

Development of a real time Image analysis system for traffic monitoring applications.

Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.