Back to Basics:A Theory of the Emergence of institutional Facts

In order to account for the mode of existence of social rules and norms, the author develops a theory of the emergence of institutional facts. Just as other kinds of institutional fact, rules and norms are meanings. Therefore, insight into the emergence of social rules and norms can be achieved by studying the recognition and the communication of meanings. Following accounts of meaning and factuality, institutional facts are characterized as unquestionable shared typifications. It is argued that, in becoming an institutional fact, a typification goes through two phases. First, it becomes a social habit. Second, this habit turns into an obligation by being objectified

DeepVenn -- a web application for the creation of area-proportional Venn diagrams using the deep learning framework Tensorflow.js

Motivation: The Venn diagram is one of the most popular methods to visualize the overlap and differences between data sets. It is especially useful when it is are 'area-proportional'; i.e. the sizes of the circles and the overlaps are proportional to the sizes of the data sets. There are some tools available that can generate area-proportional Venn Diagrams, but most of them are limited to two or three circles, and others are not available as a web application or accept only numbers and not lists of IDs as input. Some existing solutions also have limited accuracy because of outdated algorithms to calculate the optimal placement of the circles. The latest machine learning and deep learning frameworks can offer a solution to this problem. Results: The DeepVenn web application can create area-proportional Venn diagrams of up to ten sets. Because of an algorithm implemented with the deep learning framework Tensorflow.js, DeepVenn automatically finds the optimal solution in which the overlap between the circles corresponds to the sizes of the overlap as much as possible. The only required input is two to ten lists of IDs. Optional parameters include the main title, the subtitle, the set titles and colours of the circles and the background. The user can choose to display absolute numbers or percentages in the final diagram. The image can be saved as a PNG file by right-clicking on it and choosing "Save image as". The right side of the interface also shows the numbers and contents of all intersections. Availability: DeepVenn is available at https://www.deepvenn.com. Contact: [email protected]: 2 pages, 1 figur

Browsing the Pacific

A popular wide-ranging Pacific Internet report covers the region. However, it is just one element of a larger journalism project that includes advanced, on-the-job training for Pacific Island journalists; and internships for US journalists wanting to learn more about the region.&nbsp

Response to "Comment on: `Thermodynamics of viscoelastic fluids: the temperature equation'"

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Numerical simulation of a viscoelastic fluid with anisotropic heat conduction

For the nonisothermal flow of a viscoelastic fluid we have taken into account temperature dependency of the relaxation times and the viscosities in the constitutive equation for the stress. In the energy equation the heat flux is specified by Fourier's law, where anisotropic heat conduction has been taken into account. Furthermore one has to specify which part of the stress work is dissipated and which part is stored as elastic energy. The equations are solved with a finite element method for the balance equations and a streamline integration method for the constitutive equation. The influence of the Deborah number, the Péclet number and the cooling temperature are examined in a flow through a 4 to 1 contraction

Turbulent channel flow near maximum drag reduction: simulations, experiments and mechanisms

It is well known that the drag in a turbulent flow of a polymer solution is significantly reduced compared to Newtonian flow. Here we consider this phenomenon by means of a direct numerical simulation of a turbulent channel flow. The polymers are modelled as elastic dumbbells using the FENE-P model. In the computations the polymer model is solved simultaneously with the flow equations, i.e. the polymers are deformed by the flow and in their turn influence the flow structures by exerting a polymer stress. We have studied the results of varying the polymer parameters, such as the maximum extension, the elasticity and the concentration. For the case of highly extensible polymers the results of our simulations are very close to the maximum drag reduction or Virk (1975) asymptote. Our simulation results show that at approximately maximum drag reduction the slope of the mean velocity profile is increased compared to the standard logarithmic profile in turbulent wall flows. For the r.m.s. of the streamwise velocity fluctuations we find initially an increase in magnitude which near maximum drag reduction changes to a decrease. For the velocity fluctuations in the spanwise and wall-normal directions we find a continuous decrease as a function of drag reduction. The Reynolds shear stress is strongly reduced, especially near the wall, and this is compensated by a polymer stress, which at maximum drag reduction amounts to about 40% of the total stress. These results have been compared with LDV experiments of Ptasinski et al. (2001) and the agreement, both qualitatively and quantitatively, is in most cases very good. In addition we have performed an analysis of the turbulent kinetic energy budgets. The main result is a reduction of energy transfer from the streamwise direction, where the production of turbulent kinetic energy takes place, to the other directions. A substantial part of the energy production by the mean flow is transferred directly into elastic energy of the polymers. The turbulent velocity fluctuations also contribute energy to the polymers. The elastic energy of the polymers is subsequently dissipated by polymer relaxation. We have also computed the various contributions to the pressure fluctuations and identified how these change as a function of drag reduction. Finally, we discuss some cross-correlations and various length scales. These simulation results are explained here by two mechanisms. First, as suggested by Lumley (1969) the polymers damp the cross-stream or wall-normal velocity fluctuations and suppress the bursting in the buffer layer. Secondly, the ‘shear sheltering’ mechanism acts to amplify the streamwise fluctuations in the thickened buffer layer, while reducing and decoupling the motions within and above this layer. The expression for the substantial reduction in the wall drag derived by considering the long time scales of the nonlinear fluctuations of this damped shear layer, is shown to be consistent with the experimental data of Virk et al. (1967) and Virk (1975)