Reflections on the centrality of power in medical sociology: an empirical test and theoretical elaboration

This paper explores the contemporary relevance of sociological theorisations centred on medical power, including the medical dominance and deprofessionalisation theses. To achieve this it examines two issues that have been tentatively linked to the relative decline of the power and autonomy of biomedicine - complementary and alternative medicine (CAM) and the Internet-informed patient. Drawing on these two different but interconnected social phenomena, this paper reflects on the potential limitations of power-based theorisations of the medical profession and its relationship to patients and other non-biomedically situated professional groups. It is argued that power-based conceptual schemas may not adequately reflect the non-linear and complex strategic adaptations that are occurring among professional groups.

From therapeutic to political education: the centrality of affective sensibility in critical pedagogy

While the need for humanising education is pressing in neoliberal societies, the conditions for its possibility in formal institutions have become particularly cramped. A constellation of factors – the strength of neoliberal ideologies, the corporatisation of universities, the conflation of human freedom with consumer satisfaction, and a wider crisis of hope in the possibility or desirability of social change – make it difficult to apply classical theories of subject-transformation to new work in critical pedagogy. In particular, the growth of interest in pedagogies of comfort (as illustrated in certain forms of ‘therapeutic’ education and concerns about student ‘satisfaction’) and resistance to critical pedagogies suggest that subjectivty has become a primary site of political struggle in education. However, it can no longer be assumed that educators can (or should) liberate students’ repressed desires for ‘humanisation’ by politicising curricula, pedagogy or institutions. Rather, we must work to understand the new meanings and affective conditions of critical subjectivity itself. Bringing critical theories of subject transformation together with new work on ‘pedagogies of discomfort’, I suggest we can create new ways of opening up possibilities for critical education that respond to neoliberal subjectivities without corresponding to or affirming them.

Node centrality for continuous-time quantum walks

The study of complex networks has recently attracted increasing interest because of the large variety of systems that can be modeled using graphs. A fundamental operation in the analysis of complex networks is that of measuring the centrality of a vertex. In this paper, we propose to measure vertex centrality using a continuous-time quantum walk. More specifically, we relate the importance of a vertex to the influence that its initial phase has on the interference patterns that emerge during the quantum walk evolution. To this end, we make use of the quantum Jensen-Shannon divergence between two suitably defined quantum states. We investigate how the importance varies as we change the initial state of the walk and the Hamiltonian of the system. We find that, for a suitable combination of the two, the importance of a vertex is almost linearly correlated with its degree. Finally, we evaluate the proposed measure on two commonly used networks. © 2014 Springer-Verlag Berlin Heidelberg.

Measuring centrality by a generalization of degree

Network analysis has emerged as a key technique in communication studies, economics, geography, history and sociology, among others. A fundamental issue is how to identify key nodes in a network, for which purpose a number of centrality measures have been developed. This paper proposes a new parametric family of centrality measures called generalized degree. It is based on the idea that a relationship to a more interconnected node contributes to centrality in a greater extent than a connection to a less central one. Generalized degree improves on degree by redistributing its sum over the network with the consideration of the global structure. Application of the measure is supported by a set of basic properties. A sufficient condition is given for generalized degree to be rank monotonic, excluding counter-intuitive changes in the centrality ranking after certain modifications of the network. The measure has a graph interpretation and can be calculated iteratively. Generalized degree is recommended to apply besides degree since it preserves most favorable attributes of degree, but better reflects the role of the nodes in the network and has an increased ability to distinguish between their importance.

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.

A Study of Some Centrality Measures in Graphs

Centrality is in fact one of the fundamental notions in graph theory which has established its close connection with various other areas like Social networks, Flow networks, Facility location problems etc. Even though a plethora of centrality measures have been introduced from time to time, according to the changing demands, the term is not well defined and we can only give some common qualities that a centrality measure is expected to have. Nodes with high centrality scores are often more likely to be very powerful, indispensable, influential, easy propagators of information, significant in maintaining the cohesion of the group and are easily susceptible to anything that disseminate in the network.

Team Member’s Centrality, Cohesion, Conflict, and Performance in Multi-University Geographically Distributed Project Teams

This study examined team processes and outcomes among 12 multi-university distributed project teams from 11 universities during its early and late development stages over a 14-month project period. A longitudinal model of team interaction is presented and tested at the individual level to consider the extent to which both formal and informal network connections—measured as degree centrality—relate to changes in team members’ individual perceptions of cohesion and conflict in their teams, and their individual performance as a team member over time. The study showed a negative network centrality-cohesion relationship with significant temporal patterns, indicating that as team members perceive less degree centrality in distributed project teams, they report more team cohesion during the last four months of the project. We also found that changes in team cohesion from the first three months (i.e., early development stage) to the last four months (i.e., late development stage) of the project relate positively to changes in team member performance. Although degree centrality did not relate significantly to changes in team conflict over time, a strong inverse relationship was found between changes in team conflict and cohesion, suggesting that team conflict emphasizes a different but related aspect of how individuals view their experience with the team process. Changes in team conflict, however, did not relate to changes in team member performance. Ultimately, we showed that individuals, who are less central in the network and report higher levels of team cohesion, performed better in distributed teams over time.

Edge centrality via the Holevo quantity

In the study of complex networks, vertex centrality measures are used to identify the most important vertices within a graph. A related problem is that of measuring the centrality of an edge. In this paper, we propose a novel edge centrality index rooted in quantum information. More specifically, we measure the importance of an edge in terms of the contribution that it gives to the Von Neumann entropy of the graph. We show that this can be computed in terms of the Holevo quantity, a well known quantum information theoretical measure. While computing the Von Neumann entropy and hence the Holevo quantity requires computing the spectrum of the graph Laplacian, we show how to obtain a simplified measure through a quadratic approximation of the Shannon entropy. This in turns shows that the proposed centrality measure is strongly correlated with the negative degree centrality on the line graph. We evaluate our centrality measure through an extensive set of experiments on real-world as well as synthetic networks, and we compare it against commonly used alternative measures.

Confidence intervals for large non- centrality parameter

We use asymptotic linearity to derive confidence intervals for large noncentrality parameters. These results enable us to measure relevance of effects and interactions in multifactors models when we get highly statistically significant the values of F tests statistics. We show how to use our approach by considering two sets of data as application examples.

Beam-energy and system-size dependence of dynamical net charge fluctuations

We present measurements of net charge fluctuations in Au+Au collisions at s(NN)=19.6, 62.4, 130, and 200 GeV, Cu+Cu collisions at s(NN)=62.4 and 200 GeV, and p+p collisions at s=200 GeV using the dynamical net charge fluctuations measure nu(+-,dyn). We observe that the dynamical fluctuations are nonzero at all energies and exhibit a modest dependence on beam energy. A weak system size dependence is also observed. We examine the collision centrality dependence of the net charge fluctuations and find that dynamical net charge fluctuations violate 1/N(ch) scaling but display approximate 1/N(part) scaling. We also study the azimuthal and rapidity dependence of the net charge correlation strength and observe strong dependence on the azimuthal angular range and pseudorapidity widths integrated to measure the correlation.

System-Size Independence of Directed Flow Measured at the BNL Relativistic Heavy-Ion Collider

We measure directed flow (v(1)) for charged particles in Au + Au and Cu + Cu collisions at root s(NN) = 200 and 62.4 GeV, as a function of pseudorapidity (eta), transverse momentum (p(t)), and collision centrality, based on data from the STAR experiment. We find that the directed flow depends on the incident energy but, contrary to all available model implementations, not on the size of the colliding system at a given centrality. We extend the validity of the limiting fragmentation concept to v(1) in different collision systems, and investigate possible explanations for the observed sign change in v(1)(p(t)).

Spin alignment measurements of the K*(0)(892) and phi(1020) vector mesons in heavy ion collisions at root S(NN)=200 GeV

We present the first spin alignment measurements for the K*(0)(892) and phi(1020) vector mesons produced at midrapidity with transverse momenta up to 5 GeV/c at root s(NN) = 200 GeV at RHIC. The diagonal spin-density matrix elements with respect to the reaction plane in Au+Au collisions are rho(00) = 0.32 +/- 0.04 (stat) +/- 0.09 (syst) for the K*(0) (0.8 < p(T) < 5.0 GeV/c) and rho(00) = 0.34 +/- 0.02 (stat) +/- 0.03 (syst) for the phi (0.4 < p(T) < 5.0 GeV/c) and are constant with transverse momentum and collision centrality. The data are consistent with the unpolarized expectation of 1/3 and thus no evidence is found for the transfer of the orbital angular momentum of the colliding system to the vector-meson spins. Spin alignments for K(*0) and phi in Au+Au collisions were also measured with respect to the particle's production plane. The phi result, rho(00) = 0.41 +/- 0.02 (stat) +/- 0.04 (syst), is consistent with that in p+p collisions, rho(00) = 0.39 +/- 0.03 (stat) +/- 0.06 (syst), also measured in this work. The measurements thus constrain the possible size of polarization phenomena in the production dynamics of vector mesons.

Enhanced strange baryon production in Au+Au collisions compared to p+p at root s(NN)=200 GeV

We report on the observed differences in production rates of strange and multistrange baryons in Au+Au collisions at s(NN)=200 GeV compared to p+p interactions at the same energy. The strange baryon yields in Au+Au collisions, when scaled down by the number of participating nucleons, are enhanced relative to those measured in p+p reactions. The enhancement observed increases with the strangeness content of the baryon, and it increases for all strange baryons with collision centrality. The enhancement is qualitatively similar to that observed at the lower collision energy s(NN)=17.3 GeV. The previous observations are for the bulk production, while at intermediate p(T),1 < p(T)< 4 GeV/c, the strange baryons even exceed binary scaling from p+p yields.