Language use in consultation: Can “we” help teachers and students?

Analyzing the use of function words such as pronouns in conversation is an increasingly popular approach in social psychology, but has not yet been applied to the study of school-based consultation. The two central purposes of this study were to: (1) examine how language is used by consultants-in-training (CITs) and consultees within a collaborative model of consultation, and (2) to explore the relation between language use and the collaborative relationship, consultee outcomes, and client outcomes. Analyses focused on CITs’ (n = 18) and consultees’ (n = 18) use of pronouns in a problem identification and analysis (PID/PA) session of problem solving. Data indicated CITs and consultees used pronouns differently during PID/PA, particularly first-person plural words (e.g., we, us, our), and some of these differences were related to consultation outcomes. Implications of this research for school consultation practice and potential avenues for future research are explored

Efficient Immunization Strategies for Computer Networks and Populations

We present an effective immunization strategy for computer networks and populations with broad and, in particular, scale-free degree distributions. The proposed strategy, acquaintance immunization, calls for the immunization of random acquaintances of random nodes (individuals). The strategy requires no knowledge of the node degrees or any other global knowledge, as do targeted immunization strategies. We study analytically the critical threshold for complete immunization. We also study the strategy with respect to the susceptible-infected-removed epidemiological model. We show that the immunization threshold is dramatically reduced with the suggested strategy, for all studied cases.Comment: Revtex, 5 pages, 4 ps fig

Greedy Connectivity of Geographically Embedded Graphs

We introduce a measure of {\em greedy connectivity} for geographical networks (graphs embedded in space) and where the search for connecting paths relies only on local information, such as a node's location and that of its neighbors. Constraints of this type are common in everyday life applications. Greedy connectivity accounts also for imperfect transmission across established links and is larger the higher the proportion of nodes that can be reached from other nodes with a high probability. Greedy connectivity can be used as a criterion for optimal network design

Global landscape of phenazine biosynthesis and biodegradation reveals species-specific colonization patterns in agricultural soils and crop microbiomes

Phenazines are natural bacterial antibiotics that can protect crops from disease. However, for most crops it is unknown which producers and specific phenazines are ecologically relevant, and whether phenazine biodegradation can counter their effects. To better understand their ecology, we developed and environmentally-validated a quantitative metagenomic approach to mine for phenazine biosynthesis and biodegradation genes, applying it to >800 soil and plant-associated shotgun-metagenomes. We discover novel producer-crop associations and demonstrate that phenazine biosynthesis is prevalent across habitats and preferentially enriched in rhizospheres, whereas biodegrading bacteria are rare. We validate an association between maize and Dyella japonica, a putative producer abundant in crop microbiomes. D. japonica upregulates phenazine biosynthesis during phosphate limitation and robustly colonizes maize seedling roots. This work provides a global picture of phenazines in natural environments and highlights plant-microbe associations of agricultural potential. Our metagenomic approach may be extended to other metabolites and functional traits in diverse ecosystems

Cross-Talk with Myeloid Accessory Cells Regulates Human Natural Killer Cell Interferon-γ Responses to Malaria

Data from a variety of experimental models suggest that natural killer (NK) cells require signals from accessory cells in order to respond optimally to pathogens, but the precise identity of the cells able to provide such signals depends upon the nature of the infectious organism. Here we show that the ability of human NK cells to produce interferon-γ in response to stimulation by Plasmodium falciparum–infected red blood cells (iRBCs) is strictly dependent upon multiple, contact-dependent and cytokine-mediated signals derived from both monocytes and myeloid dendritic cells (mDCs). Contrary to some previous reports, we find that both monocytes and mDCs express an activated phenotype following short-term incubation with iRBCs and secrete pro-inflammatory cytokines. The magnitude of the NK cell response (and of the KIR(−) CD56(bright) NK cell population in particular) is tightly correlated with resting levels of accessory cell maturation, indicating that heterogeneity of the NK response to malaria is a reflection of deep-rooted heterogeneity in the human innate immune system. Moreover, we show that NK cells are required to maintain the maturation status of resting mDCs and monocytes, providing additional evidence for reciprocal regulation of NK cells and accessory cells. However, NK cell–derived signals are not required for activation of accessory cells by either iRBCs or bacterial lipolysaccharide. Together, these data suggest that there may be differences in the sequence of events required for activation of NK cells by non-viral pathogens compared to the classical model of NK activation by virus-infected or major histocompatibility complex–deficient cells. These findings have far-reaching implications for the study of immunity to infection in human populations

Extremism propagation in social networks with hubs

One aspect of opinion change that has been of academic interest is the impact of people with extreme opinions (extremists) on opinion dynamics. An agent-based model has been used to study the role of small-world social network topologies on general opinion change in the presence of extremists. It has been found that opinion convergence to a single extreme occurs only when the average number of network connections for each individual is extremely high. Here, we extend the model to examine the effect of positively skewed degree distributions, in addition to small-world structures, on the types of opinion convergence that occur in the presence of extremists. We also examine what happens when extremist opinions are located on the well-connected nodes (hubs) created by the positively skewed distribution. We find that a positively skewed network topology encourages opinion convergence on a single extreme under a wider range of conditions than topologies whose degree distributions were not skewed. The importance of social position for social influence is highlighted by the result that, when positive extremists are placed on hubs, all population convergence is to the positive extreme even when there are twice as many negative extremists. Thus, our results have shown the importance of considering a positively skewed degree distribution, and in particular network hubs and social position, when examining extremist transmission

Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

Dynamic phase transition properties and hysteretic behavior of a ferrimagnetic core-shell nanoparticle in the presence of a time dependent magnetic field

We have presented dynamic phase transition features and stationary-state behavior of a ferrimagnetic small nanoparticle system with a core-shell structure. By means of detailed Monte Carlo simulations, a complete picture of the phase diagrams and magnetization profiles have been presented and the conditions for the occurrence of a compensation point $T_{comp}$ in the system have been investigated. According to N\'{e}el nomenclature, the magnetization curves of the particle have been found to obey P-type, N-type and Q-type classification schemes under certain conditions. Much effort has been devoted to investigation of hysteretic response of the particle and we observed the existence of triple hysteresis loop behavior which originates from the existence of a weak ferromagnetic core coupling $J_{c}/J_{sh}$, as well as a strong antiferromagnetic interface exchange interaction $J_{int}/J_{sh}$. Most of the calculations have been performed for a particle in the presence of oscillating fields of very high frequencies and high amplitudes in comparison with exchange interactions which resembles a magnetic system under the influence of ultrafast switching fields. Particular attention has also been paid on the influence of the particle size on the thermal and magnetic properties, as well as magnetic features such as coercivity, remanence and compensation temperature of the particle. We have found that in the presence of ultrafast switching fields, the particle may exhibit a dynamic phase transition from paramagnetic to a dynamically ordered phase with increasing ferromagnetic shell thickness.Comment: 12 pages, 12 figure

The three-dimensional random field Ising magnet: interfaces, scaling, and the nature of states

The nature of the zero temperature ordering transition in the 3D Gaussian random field Ising magnet is studied numerically, aided by scaling analyses. In the ferromagnetic phase the scaling of the roughness of the domain walls, $w\sim L^\zeta$, is consistent with the theoretical prediction $\zeta = 2/3$. As the randomness is increased through the transition, the probability distribution of the interfacial tension of domain walls scales as for a single second order transition. At the critical point, the fractal dimensions of domain walls and the fractal dimension of the outer surface of spin clusters are investigated: there are at least two distinct physically important fractal dimensions. These dimensions are argued to be related to combinations of the energy scaling exponent, $\theta$, which determines the violation of hyperscaling, the correlation length exponent $\nu$, and the magnetization exponent $\beta$. The value $\beta = 0.017\pm 0.005$ is derived from the magnetization: this estimate is supported by the study of the spin cluster size distribution at criticality. The variation of configurations in the interior of a sample with boundary conditions is consistent with the hypothesis that there is a single transition separating the disordered phase with one ground state from the ordered phase with two ground states. The array of results are shown to be consistent with a scaling picture and a geometric description of the influence of boundary conditions on the spins. The details of the algorithm used and its implementation are also described.Comment: 32 pp., 2 columns, 32 figure

A measure of centrality based on the spectrum of the Laplacian

We introduce a family of new centralities, the k-spectral centralities. k-Spectral centrality is a measurement of importance with respect to the deformation of the graph Laplacian associated with the graph. Due to this connection, k-spectral centralities have various interpretations in terms of spectrally determined information. We explore this centrality in the context of several examples. While for sparse unweighted networks 1-spectral centrality behaves similarly to other standard centralities, for dense weighted networks they show different properties. In summary, the k-spectral centralities provide a novel and useful measurement of relevance (for single network elements as well as whole subnetworks) distinct from other known measures.Comment: 12 pages, 6 figures, 2 table