BioSimulator.jl: Stochastic simulation in Julia

Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dynamics. Stochastic simulation algorithms are useful in generating time-evolution trajectories for these systems because they can adequately capture the influence of random fluctuations and quantify rare events. We present a simple and flexible package, BioSimulator.jl, for implementing the Gillespie algorithm, $\tau$-leaping, and related stochastic simulation algorithms. The objective of this work is to provide scientists across domains with fast, user-friendly simulation tools. We used the high-performance programming language Julia because of its emphasis on scientific computing. Our software package implements a suite of stochastic simulation algorithms based on Markov chain theory. We provide the ability to (a) diagram Petri Nets describing interactions, (b) plot average trajectories and attached standard deviations of each participating species over time, and (c) generate frequency distributions of each species at a specified time. BioSimulator.jl's interface allows users to build models programmatically within Julia. A model is then passed to the simulate routine to generate simulation data. The built-in tools allow one to visualize results and compute summary statistics. Our examples highlight the broad applicability of our software to systems of varying complexity from ecology, systems biology, chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages the use of stochastic simulation, minimizes tedious programming efforts, and reduces errors during model specification.Comment: 27 pages, 5 figures, 3 table

Public Service Media in a Digital Media Environment: Performance from an Audience Perspective

For decades, public service broadcasting has played an important role in the provision of news and information in many European countries. Today, however, public service media (PSM) are confronted with numerous challenges, including the need to legitimise their role in an increasingly digital media environment. Against this background, this study examines the audience perspective on the topic with an international comparative approach. It analyses the population’s assessment of, and attitudes towards, the performance of PSM. The aim is to identify what relevance is attributed to PSM by the public in the digital age and how they see PSM’s role in comparison to other more recent (digital) media offerings. An online survey was conducted in three specifically selected countries: Germany, France, and the UK. Overall, the findings show that respondents attribute a clear role to PSM and distinguish it from other media offerings in the increasingly digital media environment. They rate the information quality offered by PSM as higher than that of most other media offerings. Respondents are more likely to value social media platforms for entertainment purposes than PSM. The findings also reveal differences in the evaluation of PSM depending on PSM news use, interest in news, political interest, as well as on demographic variables. On the other hand, differences between the individual countries overall were surprisingly small, pointing to the fact that PSM across the countries sampled are—with deviations—perceived to be performing better than (most) other media, despite being confronted with changes and challenges in their environment

Tiermedizin in Berlin

Oktober 201

Mapping brain function associated with cue-reactivity and changes pre-to-post a mindfulness-based intervention in cannabis use disorder

Globally, cannabis is used by ~210 million people and 10-to-30% endorse symptoms consistent with a cannabis use disorder (CUD), which constitutes a substantial social burden including health and treatment services. CUD is characterised by a loss of control over cannabis consumption despite significant adverse outcomes including strong cravings when exposed to cannabis cues. Such outcomes have been (partly) ascribed to altered brain function in addiction related pathways. Preliminary functional magnetic resonance imaging (fMRI) evidence in cannabis users, show different brain activity when exposed to cannabis (vs neutral) cues, in prefrontal, striatal and parietal regions. However, no study has examined cannabis users with a DSM-5 diagnosis of CUD, or tested if psychological interventions targeting cravings (e.g., mindfulness-based interventions [MBI]) reduce neural cue-reactivity in CUD. This thesis comprises three studies aimed to examine brain activity during cannabis cue-reactivity in cannabis users and CUD, and whether such activity can be reduced with a MBI. Study 1 was a systematic review of the fMRI literature on brain function during cue-reactivity in cannabis users. It synthesised findings on brain function during fMRI cue-reactivity tasks (cannabis vs neutral stimuli) in regular cannabis users, and their association with behavioural variables (e.g., craving). Eighteen studies showed that cannabis users had greater activity in prefrontal, striatal, and parietal regions, some of which (orbitofrontal cortex [OFC]) correlated with and greater subjective craving. The literature was limited by the lack of assessment of CUD using the DSM-5 and the inclusion of a non-using control group. Study 2 aimed to examine differences in brain activity during a cue-reactivity task (cannabis vs neutral images), i) between 49 adults with moderate-to-severe CUD and 30 controls; and ii) their association with craving, cannabis exposure and mental health. CUD vs controls had greater activity in the lingual gyrus (FWE-corrected p 10), and in the MFG, medial OFC, and cerebellum (uncorrected, p 10). Greater MFG activity correlated with more past month cannabis grams. Overall, the findings from this thesis provide novel information on the current understanding of the neural correlates of cannabis cue-reactivity in CUD. The results of the first two studies suggest that CUD has a (partly) overlapping neurobiology with that of other SUDs as per prominent neuroscientific theories of addiction. Different brain function during cannabis cue-reactivity may reflect alterations in reward processing, including salience evaluation and attention pathways resulting from regular exposure to cannabis/related cues; or predating CUD. As such, interventions that target these regions may be effective at reducing cue-reactivity/craving in CUD. Study 3 was a double-blind fMRI experiment. It aimed to investigate for the first time if a brief MBI compared to both an active relaxation and passive no intervention placebo controls, reduces neural cue-reactivity in the regions of interest (ROIs) functionally different in Study 2 (i.e., MFG, OFC, lingual gyrus and cerebellum), in the same sample with CUD (N = 40). It also explored if changes in brain activity pre-to-post MBI were associated with changes in behaviour. It was hypothesised that the greater activity in the ROIs would significantly decrease pre-to-post the MBI only. A significant decrease in the activity of the OFC was observed pre-to-post all three interventions, as well as in subjective craving and arousal rating of cannabis images. No correlations emerged. Overall, the findings from the research in this thesis demonstrates that cannabis cue-reactivity in CUD is associated with different activity in selected brain pathway implicated in salience and reward processing; and the activity of some of these regions (e.g. OFC) can be reduced during a brief engagement with monitoring of daily cannabis use, cravings and mood. More research in larger samples is required to identify with precision the neurobiology of cannabis cue-reactivity in CUD and to reduce these with novel interventions. Such new knowledge is necessary to alleviate the harmful impacts of the increasing prevalence of CUD to both the individual and to society, particularly when cannabis products and related cues are increasingly accessible and visible to vulnerable members of the community

The creation of a multi-ethnic housing cooperative a social intervention

The present study documents the development of the Housing Working Group—a group which investigated strategies to improve the housing situation of new Canadians in Kitchener-Waterloo—and the subsequent formation of the founding board of directors of a multi-ethnic housing cooperative. It emphasizes the importance of new Canadian involvement in the intervention and the need to view their empowerment as a long-term goal, attainable only after a series of small, measurable successes. The research revealed two dilemmas in the practice of community development. First, though the empowerment of powerless people requires their active participation in self-help projects, the interventionist cannot force them to participate. Secondly, the awareness that inadequate housing is part of a wider problem had to be balanced with the need to keep the project focused on one issue (housing) in order to maintain the involvement of new Canadians. The research also pointed to the need for at least two interventionists in order to avoid burnout and to maintain a balanced view of the intervention. In terms of the more specific issue of creating non-profit housing, it was found that community groups involved in such projects must assert control over their proposals rather than allowing a community resource organization (which provides technical assistance in the development of housing projects) to take control for them. Ontario’s current non-profit housing program was praised for its involvement of community groups in the development of low-cost housing, but was found to suffer from too much red tape and a lack of program flexibility. It was suggested that groups should consider whether they are contributing to the problem of inadequate affordable housing by participating in a program which requires high numbers of subsidized units within projects and fails to enable access to centrally located land. Further research, including an evaluation of the completed intervention, is needed

FATMAS: a methodology to design fault-tolerant multi-agent systems

Un système multi-agent (SMA) est un système dans lequel plusieurs agents opèrent et interagissent. Chaque agent a la responsabilité d’exécuter des tâches. Cependant, chaque agent, pour diverses raisons, peut rencontrer des problèmes pendant l’exécution de ses tâches ; ce qui peut induire un disfonctionnement du SMA. Cependant, le SMA doit être en mesure de détecter les sources de problèms (d’erreurs) afin de les contrôler et ainsi continuer son exécution correctement. Un tel SMA est appelé un SMA tolérant aux fautes. Il existe deux types de sources d’erreurs pour un agent : les erreurs causées par son environnment et les erreurs dûes à sa programmation. Dans la littérature, il existe plusieurs techniques qui traitent des erreurs de programmation au niveau des agents. Cependant, ces techniques ne traitent pas des erreurs causées par l’environnement de l’agent. Tout d’abord, nous distinguons entre l’environnment d’un agent et l’environnement du SMA. L’environnement d’un agent représente toutes les composantes matérielles ou logicielles que l’agent ne peut contrôler mais avec lesquelles il interagit. Cependant, l’environnment du SMA représente toutes les composantes que le système ne contrôle pas mais avec lesquelles il interagit. Ainsi, le SMA peut contrôler certaines des composantes avec lesquelles un agent interagit. Ainsi, une composante peut appartenir à l’environnement d’un agent et ne pas appartenir à l’environnement du système. Dans ce travail, nous présentons une méthodologie de conception de SMA tolérants aux fautes, nommée FATMAS, qui permet au concepteur du SMA de détecter et de corriger, si possible, les erreurs causées par les environnements des agents. Cette méthodologie permettra ainsi de délimiter la frontière du SMA de son environnement avec lequel il interagit. La frontière du SMA est déterminée par les différentes composantes (matérielles ou logicielles) que le système contrôle. Ainsi, le SMA, à l’intérieur de sa frontière, peut corriger les erreurs provenant de ses composantes. Cependant, le SMA n’a aucun contrôle sur toutes les composantes opérant dans son environnement. La méthodologie, que nous proposons, doit couvrir les trois premières phases d’un développement logiciel qui sont l’analyse, la conception et l’implémentation tout en intégrant, dans son processus de développement, une technique permettant au concepteur du système de délimiter la frontière du SMA et ainsi détecter les sources d’erreurs et les contrôler afin que le système multi-agent soit tolérant aux fautes (SMATF). Cependant, les méthodologies de conception de SMA, référencées dans la littérature, n’intègrent pas une telle technique. FATMAS offre au concepteur du SMATF quatre modèles pour décrire et développer le SMA ainsi qu’une technique de réorganisation du système qui lui permet de détecter et de contrôler ses sources d’erreurs, et ainsi définir la frontière du SMA. Chaque modèle est associé à un micro processus qui guide le concepteur lors du développement du modèle. FATMAS offre aussi un macro-processus, qui définit le cycle de développement de la méthodologie. FATMAS se base sur un développement itératif pour identifier et déterminer les tâches à ajouter au système afin de contrôler des sources d’erreurs. À chaque itération, le concepteur évalue, selon une fonction de coût/bénéfice s’il est opportun d’ajouter de nouvelles tâches de contrôle au système. Le premier modèle est le modèle de tâches-environnement. Il est développé lors de la phase d’analyse. Il identifie les différentes tâches que les agents doivent exécuter, leurs préconditions et leurs ressources. Ce modèle permet d’identifier différentes sources de problèmes qui peuvent causer un disfonctionnement du système. Le deuxième modèle est le modèle d’agents. Il est développé lors de la phase de conception. Il décrit les agents, leurs relations, et spécifie pour chaque agent les ressources auxquelles il a le droit d’accéder. Chaque agent exécutera un ensemble de tâches identifiées dans le modèle de tâches-environnement. Le troisième modèle est le modèle d’interaction d’agents. Il est développé lors de la phase de conception. Il décrit les échanges de messages entre les agents. Le quatrième modèle est le modèle d’implémentation. Il est développé lors de la phase d’implémentation. Il décrit l’infrastructure matérielle sur laquelle le SMA va opérer ainsi que l’environnement de développement du SMA. La méthodologie inclut aussi une technique de réorganisation. Cette technique permet de délimiter la frontière du SMA et contrôler, si possible, ses sources d’erreurs. Cette technique doit intégrer trois techniques nécessaires à la conception d’un système tolérant aux fautes : une technique de prévention d’erreurs, une technique de recouvrement d’erreurs, et une technique de tolérance aux fautes. La technique de prévention d’erreurs permet de délimiter la frontière du SMA. La technique de recouvrement d’erreurs permet de proposer une architecture du SMA pour détecter les erreurs. La technique de tolérance aux fautes permet de définir une procédure de réplication d’agents et de tâches dans le SMA pour que le SMA soit tolérant aux fautes. Cette dernière technique, à l’inverse des techniques de tolérance aux fautes existantes, réplique les tâches et les agents et non seulement les agents. Elle permet ainsi de réduire la complexité du système en diminuant le nombre d’agents à répliquer. Résumé iv De même, un agent peut ne pas être en erreur mais la composante matérielle sur laquelle il est exécuté peut ne plus être fonctionnelle. Ce qui constitue une source d’erreurs pour le SMA. Il faudrait alors que le SMA continue à s’exécuter correctement malgrè le disfonctionnement d’une composante. FATMAS fournit alors un support au concepteur du système pour tenir compte de ce type d’erreurs soit en contrôlant les composantes matérielles, soit en proposant une distribution possible des agents sur les composantes matérielles disponibles pour que le disfonctionnement d’une composante matérielle n’affecte pas le fonctionnement du SMA. FATMAS permet d’identifier des sources d’erreurs lors de la phase de conception du système. Cependant, elle ne traite pas des sources d’erreurs de programmation. Ainsi, la technique de réorganization proposée dans ce travail sera validée par rapport aux sources d’erreurs identifiées lors de la phase de conception et provenant de la frontière du SMA. Nous démontrerons formellement que, si une erreur provient d’une composante que le SMA contrôle, le SMA devrait être opérationnel. Cependant, FATMAS ne certifie pas que le futur système sera toujours opérationnel car elle ne traîte pas des erreurs de programmation ou des erreurs causées par son environnement.A multi-agent system (MAS) consists of several agents interacting together. In a MAS, each agent performs several tasks. However, each agent is prone to individual failures so that it can no longer perform its tasks. This can lead the MAS to a failure. Ideally, the MAS should be able to identify the possible sources of failures and try to overcome them in order to continue operating correctly ; we say that it should be fault-tolerant. There are two kinds of sources of failures to an agent : errors originating from the environment with which the agents interacts, and programming exceptions. There are several works on fault-tolerant systems which deals with programming exceptions. However, these techniques does not allow the MAS to identify errors originating from an agent’s environment. In this thesis, we propose a design methodology, called FATMAS, which allows a MAS designer to identify errors originating from agents’ environments. Doing so, the designer can determine the sources of failures it could be able to control and those it could not. Hence, it can determine the errors it can prevent and those it cannot. Consequently, this allows the designer to determine the system’s boundary from its environment. The system boundary is the area within which the decision-taking process of the MAS has power to make things happen, or prevent them from happening.We distinguish between the system’s environment and an agent’s environment. An agent’s environment is characterized by the components (hardware or software) that the agent does not control. However, the system may control some of the agent’s environment components. Consequently, some of the agent’s environment components may not be a part of the system’s environment. The development of a fault-tolerant MAS (FTMAS) requires the use of a methodology to design FTMAS and of a reorganization technique that will allow the MAS designer to identify and control, if possible, different sources of system failure. However, current MAS design methodologies do not integrate such a technique. FATMAS provides four models used to design and implement the target system and a reorganization technique to assist the designer in identifying and controlling different sources of system’s failures. FATMAS also provides a macro process which covers the entire life cycle of the system development as well as several micro processes that guide the designer when developing each model. The macro-process is based on an iterative approach based on a cost/benefit evaluation to help the designer to decide whether to go from one iteration to another. The methodology has three phases : analysis, design, and implementation. The analysis phase develops the task-environment model. This model identifies the different tasks the agents will perform, their resources, and their preconditions. It identifies several possible sources of system failures. The design phase develops the agent model and the agent interaction model. The agent model describes the agents and their resources. Each agent performs several tasks identified in the task-environment model. The agent interaction model describes the messages exchange between agents. The implementation phase develops the implementation model, and allows an automatic code generation of Java agents. The implementation model describes the infrastructure upon which the MAS will operate and the development environment to be used when developing the MAS. The reorganization technique includes three techniques required to design a fault-tolerant system : a fault-prevention technique, a fault-recovery technique, and a fault-tolerance technique. The fault-prevention technique assists the designer in delimiting the system’s boundary. The fault-recovery technique proposes a MAS architecture allowing it to detect failures. The fault-tolerance technique is based on agent and task redundancy. Contrary to existing fault-tolerance techniques, this technique replicates tasks and agents and not only agents. Thus, it minimizes the system complexity by minimizing the number of agents operating in the system. Furthermore, FATMAS helps the designer to deal with possible physical component failures, on which the MAS will operate. It proposes a way to either control these components or to distribute the agents on these components in such a way that if a component is in failure, then the MAS could continue operating properly. The FATMAS methodology presented in this dissertation assists a designer, in its development process, to build fault-tolerant systems. It has the following main contributions : 1. it allows to identify different sources of system failure ; 2. it proposes to introduce new tasks in a MAS to control the identified sources of failures ; 3. it proposes a mechanism which automatically determines which tasks (agents) should be replicated and in which other agents ; 4. it reduces the system complexity by minimizing the replication of agents ; Abstract vii 5. it proposes a MAS reorganization technique which is embedded within the designed MAS and assists the designer to determine the system’s boundary. It proposes a MAS architecture to detect and recover from failures originating from the system boundary. Moreover, it proposes a way to distribute agents on the physical components so that the MAS could continue operating properly in case of a component failure. This could make the MAS more robust to fault prone environments. FATMAS alows to determine different sources of failures of a MAS. The MAS controls the sources of failures situated in its boundary. It does not control the sources of failures situated in its environments. Consequently, the reorganization technique proposed in this dissertation will be proven valid only in the case where the sources of failures are controlled by the MAS. However, it cannot be proven that the future system is fault-tolerant since faults originating from the environment or from coding are not dealt with

Winning the SDG battle in cities : how an integrated information ecosystem can contribute to the achievement of the 2030 sustainable development goals

In 2015, the United Nations adopted an ambitious development agenda composed of 17 sustainable development goals (SDGs), which are to be reached by 2030. Beyond SDG 11 concerning the development of sustainable cities, many of the SDGs target activities falling within the responsibility of local governments. Thus, cities will play a leading role in the achievement of these goals, and we argue that the information systems (IS) community must be an active partner in these efforts. This paper aims to contribute to the achievement of the SDGs by developing a conceptual model to explain the role of IS in building smart sustainable cities and providing a framework of action for IS researchers and city managers. To this end, we conduct grounded theory studies of two green IS used by an internationally recognized smart city to manage water quality and green space. Based on these findings, we articulate a model explaining how an integrated information ecosystem enables the interactions between three interrelated spheres – administrative, political and sustainability – to support the development of smart sustainable cities. Moving from theory to practice, we use two real‐world scenarios to demonstrate the applicability of the model. Finally, we define an action framework outlining key actions for cities and suggest corresponding questions for future research. Beyond a simple call‐to‐action, this work provides a much‐needed foundation for future research and practice leading to a sustainable future for all