Safe Compositional Network Sketches: NetSketch Tool Implementation

Numerous problems exist that can be modeled as traffic through a network in which constraints exist to regulate flow. Vehicular road travel, computer networks, and cloud based resource distribution, among others all have natural representations in this manner. As these networks grow in size and/or complexity, analysis and certification of the safety invariants becomes increasingly costly. The NetSketch formalism introduces a lightweight verification framework that allows for greater scalability than traditional analysis methods. The NetSketch tool was developed to provide the power of this formalism in an easy to use and intuitive user interface.

Computing regular equivalence: practical and theoretical issues

Social network analysts have tried to capture the idea of social role explicitly by proposing a framework that precisely gives conditions under which group actors are playing equivalent roles. They term these methods positional analysis techniques. The most general definition is regular equivalence which captures the idea that equivalent actors are related in a similar way to equivalent alters. Regular equivalence gives rise to a whole class of partitions on a network. Given a network we have two different computational problems. The first is how to find a particular regular equivalence. An algorithm exists to find the largest regular partition but there are not efficient algorithms to test whether there is a regular k-partition. That is a partition in k groups that is regular. In addition, when dealing with real data, it is unlikely that any regular partitions exist. To overcome this problem relaxations of regular equivalence have been proposed along with optimisation techniques to find nearly regular partitions. In this paper we review the algorithms that have developed to find particular regular equivalences and look at some of the recent theoretical results which give an insight into the complexity of finding regular partitions.

Dynamic evolution in information sharing networks

This study examines the roll-out of a collaborative information repository or 'knowledge-base' in a medium-sized UK professional services firm over a six year period. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an 's-curve' and usage exhibits something of a power law distribution, both attributable to network effects and network opposition is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Fourier analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed.

Social Networks Usage Profile: Descriptive study with students in the University of Murcia

Telematic tools are very important for our lives in the present era and moreover this idea is made more evident if we analyse young people behaviours. However, it seems that the possibilities that these tools allow subjects from a professional point of view, beyond the purely playful aspects, are still not fully exploited both by subjects, neither by educational institutions where they learn. Our work studies the uses of social media in the context of university students. In order to this we have designed a research based on quantitative methodology with a survey. We have applied a questionnaire to students in the University of Murcia. The questionnaire was answered by 487 students in the first half of 2014. The survey results confirm our hypothesis that social networks are part of the basic and habitual tools of communication between the youth of our university and eminently used for leisure purposes, and that the tools used for more academic activities are those allowing greater control of privacy.

Trusting Groups in Coalition Formation using Social Distance

In environments where distributed team formation is key, and defections are possible, the use of trust as social capital allows social norms to be defied and compared. An agent can use this information, when invited to join a group or collation, to decide whether or not its utility will be increased by joining. In this work a social network approach is used to define and reason about the relationships contained in the agent community. Previous baseline work is extended with two decision making mechanisms. These are compared by simulating an abstract grid-like environment, and preliminary results are reported.

The level playing field: the impact of assessment practice on professional development

Context: The effects of assessment practice on students’ learning are unclear, particularly regarding professional development. Corralling in objective structured clinical examinations (OSCEs) is designed to reduce illicit passing of examination information. Candidates completing an examination are kept secluded until the next cohort of examinees has begun. We used the introduction of corralling as a context in which to explore social influences on examination misconduct, with the aims of improving understanding of the hidden effects of assessment, and evaluating the acceptability of corralling from the student perspective.

Methods: A questionnaire was administered to students corralled post-OSCE for the first time. Eleven semi-structured interviews were subsequently conducted. Questionnaire data were analysed for descriptive statistics and thematic analysis of interview transcripts was carried out.

Results: The questionnaire response rate was 95.4% (251/263). Before corralling, 80.9% (203/251) of students were aware of the sharing of information among peers and 78.5% (197/251) agreed that such misconduct was unprofessional. The majority were in favour of corralling (90.8%, 228/251). Four themes emerged from the semi-structured interviews: the student network versus the individual; assessment-driven culture; the deferring of professionalism, and the ‘level playing field’. Students saw interaction within the student network, on a background of assessment-driven culture, as the key driver in examination misconduct. Conforming to the rules of the social network was prioritised over individual agency, although the mismatch between the rules of the network and the dominant professional discourse caused some conflict for individuals. Deferred professionalism (described as the practice of taking on the norms of professional behaviour only when qualified) was a rationalisation used to minimise this conflict. Corralling provided a ‘level playing field’ in which the influences of the network were minimised.

Conclusions: Examination misconduct is thus a complex social construction with implications for individual learners in terms of professional development. Corralling is one mechanism for addressing misconduct that is acceptable to students, but assessment processes have important hidden effects which educators should acknowledge.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

Improving Patient Safety Through Formal and Informal Learning Networks

This paper explores a novel perspective on patient safety improvements, which draws on
contemporary social network and learning theories. A case study was conducted at a Portuguese
acute university hospital. Data collection followed a staged approach, whereby 46 interviews
were conducted involving 49 respondents from a broad array of departments and professional
backgrounds. This case study highlights the importance of two major interlinked factors in
contributing to patient safety improvements. The first of these is the crucial role of formal and
informal, internal and external social networks. The second is the importance and the possible
advantage of combining formal and informal learning. The analysis suggests that initiatives
rooted in formal learning approaches alone do not necessarily lead to the creation of long-term
grounded internal safety networks, and that patient safety improvements can crucially depend on
bottom-up initiatives of communities of practice and informal learning. Traditional research on
patient safety places a strong emphasis on top-down and managerialist approaches and is often
based on the assumption that „safety? learning is primarily formal and context-independent. This
paper suggests that bottom-up initiatives and a combination of formal and informal learning can
make a major contribute to patient safety improvements.

Towards a general framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

CSFinder: A Cold-Start Friend Finder in Large-Scale Social Networks

Recommending users for a new social network user to follow is a topic of interest at present. The existing approaches rely on using various types of information about the new user to determine recommended users who have similar interests to the new user. However, this presents a problem when a new user joins a social network, who is yet to have any interaction on the social network. In this paper we present a particular type of conversational recommendation approach, critiquing-based recommendation, to solve the cold start problem. We present a critiquing-based recommendation system, called CSFinder, to recommend users for a new user to follow. A traditional critiquing-based recommendation system allows a user to critique a feature of a recommended item at a time and gradually leads the user to the target recommendation. However this may require a lengthy recommendation session. CSFinder aims to reduce the session length by taking a case-based reasoning approach. It selects relevant recommendation sessions of past users that match the recommendation session of the current user to shortcut the current recommendation session. It selects relevant recommendation sessions from a case base that contains the successful recommendation sessions of past users. A past recommendation session can be selected if it contains recommended items and critiques that sufficiently overlap with the ones in the current session. Our experimental results show that CSFinder has significantly shorter sessions than the ones of an Incremental Critiquing system, which is a baseline critiquing-based recommendation system.

Finding Relevant Tweets

When a user of a microblogging site authors a microblog
post or browses through a microblog post, it provides cues as to what
topic she is interested in at that point in time. Example-based search
that retrieves similar tweets given one exemplary tweet, such as the one
just authored, can help provide the user with relevant content. We investigate
various components of microblog posts, such as the associated
timestamp, author’s social network, and the content of the post, and
develop approaches that harness such factors in finding relevant tweets
given a query tweet. An empirical analysis of such techniques on real
world twitter-data is then presented to quantify the utility of the various
factors in assessing tweet relevance. We observe that content-wise similar
tweets that also contain extra information not already present in the
query, are perceived as useful. We then develop a composite technique
that combines the various approaches by scoring tweets using a dynamic
query-specific linear combination of separate techniques. An empirical
evaluation establishes the effectiveness of the composite technique, and
that it outperforms each of its constituents.

A compendium of modelling techniques

This Integration Insight provides a brief overview of the most popular modelling techniques used to analyse complex real-world problems, as well as some less popular but highly relevant techniques. The modelling methods are divided into three categories, with each encompassing a number of methods, as follows: 1) Qualitative Aggregate Models (Soft Systems Methodology, Concept Maps and Mind Mapping, Scenario Planning, Causal (Loop) Diagrams), 2) Quantitative Aggregate Models (Function fitting and Regression, Bayesian Nets, System of differential equations / Dynamical systems, System Dynamics, Evolutionary Algorithms) and 3) Individual Oriented Models (Cellular Automata, Microsimulation, Agent Based Models, Discrete Event Simulation, Social Network
Analysis). Each technique is broadly described with example uses, key attributes and reference material.

Envolvimento dos estudantes na escola e perceção de suporte social: um estudo com alunos dos 2º e 3º ciclos do ensino básico

O envolvimento dos estudantes na escola tem ganho relevância no âmbito da comunidade científica. Apesar de não existir um consenso face à sua definição, todas apontam para o facto do envolvimento se relacionar com a forma como os estudantes se identificam e valorizam os resultados escolares, bem como, a sua participação em atividades escolares curriculares e extracurriculares. O suporte social visto como a perceção que o indivíduo tem de ser valorizado e aceite pelos outros contidos na sua rede social. A investigação tem demonstrado a relação existente entre estes dois conceitos. A existência de suporte social, mais especificamente o estabelecimento de relações positivas com o grupo de pares parece estar relacionada com um maior envolvimento dos estudantes na escola. O objetivo do presente estudo é compreender a relação entre o envolvimento dos estudantes na escola e a perceção de suporte social. O mesmo foi realizado numa escola em Évora, com alunos do 2º e 3º ciclos do ensino básico (335 alunos). Foram utilizados dois questionários: o QEEE – Questionário acerca do Envolvimento dos Estudantes na Escola e o QPSS – Questionário de Percepção de Suporte Social. Os resultados do presente estudo apontam para correlações estatisticamente significativas entre o suporte social e o envolvimento dos estudantes na escola, corroborando assim investigações já realizadas; ABSTRACT: Students engagement with school has won relevance within the scientific community. Although there is no consensus over its definition, all point to the fact that the engagement relate to how the students to identify and value the school results as well as their participation in curricular and extracurricular activities. The social support seen as the perception that the individual must be valued and accepted by others contained in your social network. The research has demonstrated the relationship between these both. The existence of social support, specifically the establishment of good relations with the peer group seems to be related to greater student engagement with school. The aim of this study is to understand the link between student engagement with school and perceived social support. It was conducted in a school in Évora, with students from 2nd and 3th cycles of middle school (335 students). We used two questionnaires: QEEE – Questionnaire about the Student Engagement with School and QPSS – Questionnaire for Perceived Social Support. The results of this study show statistically significant correlations between social support and students engagement with school, thus confirming previous research.

Comportamentos de agressão e vitimação em contexto escolar e a percepção de suporte social: um estudo com alunos do 3º e 4º anos de escolaridade

O bullying descreve-se como um abuso sistemático de poder entre pares, de carácter intencional e repetitivo. O suporte social descreve comportamentos que funcionam como um reforço na rede social. A existência de suporte social parece ser um factor protector para o envolvimento em situações de vitimação e agressão. O objectivo deste estudo é compreender a relação entre o bullying e a percepção de suporte social. Realizou-se em quatro escolas do Agrupamento de Escolas nº1 de Évora, com alunos do 3º e 4ºanos de escolaridade (262 alunos). Utilizaram-se dois questionários: o QVEIS – Questionário de Violência Escolar e Isolamento Social e o QPSP – Questionário de Percepção de Suporte Social. Os resultados deste estudo não se revelaram conclusivos, sendo reduzida a prevalência de comportamentos de vitimação e agressão. Existem correlações estatisticamente significativas entre as dimensões da vitimação e da agressão e a percepção de existência de suporte social e, a vitimação e a percepção de ausência de suporte social; ABSTRACT: Bullying is described as a systematic abuse of power among peers, intentional and repetitive. Social support describes behaviors that act as reinforcement in a social network. The existence of social support seems to be a protective factor for involvement in situations of victimization and aggression. The aim of this study is to understand the relationship between bullying and perceived social support. It was conducted in four elementary schools, with students from 3rd and 4th grade (262 students). We used two questionnaires: QVEIS – Questionnaire for School Violence and Social Isolation and QPSP - Questionnaire for Perceived Social Support. The results were inconclusive, with a fair prevalence of risk of victimization and aggression. There are statistically significant correlations between the dimensions of victimization and aggression and the perception of the existence of social support and the perception of victimization and lack of social support.