Models for the two-phase flow of concentrated suspensions

A new two-phase model for concentrated suspensions is derived that incorporates a constitutive law combining the rheology for non-Brownian suspension and granular flow. The resulting model exhibits a yield-stress behavior for the solid phase depending on the collision pressure. This property is investigated for the simple geometry of plane Poiseuille flow, where an unyielded or jammed zone of finite width arises in the center of the channel. For the steady states of this problem, the governing equations are reduced to a boundary value problem for a system of ordinary differential equations and the conditions for existence of solutions with jammed regions are investigated using phase-space methods. For the general time-dependent case a new drift-flux model is derived using matched asymptotic expansions that takes into account the boundary layers at the walls and the interface between the yielded and unyielded region. The drift-flux model is used to numerically study the dynamic behavior of the suspension flow including the appearance and evolution of an unyielded or jammed region

Too Trivial To Test? An Inverse View on Defect Prediction to Identify Methods with Low Fault Risk

Background. Test resources are usually limited and therefore it is often not possible to completely test an application before a release. To cope with the problem of scarce resources, development teams can apply defect prediction to identify fault-prone code regions. However, defect prediction tends to low precision in cross-project prediction scenarios. Aims. We take an inverse view on defect prediction and aim to identify methods that can be deferred when testing because they contain hardly any faults due to their code being "trivial". We expect that characteristics of such methods might be project-independent, so that our approach could improve cross-project predictions. Method. We compute code metrics and apply association rule mining to create rules for identifying methods with low fault risk. We conduct an empirical study to assess our approach with six Java open-source projects containing precise fault data at the method level. Results. Our results show that inverse defect prediction can identify approx. 32-44% of the methods of a project to have a low fault risk; on average, they are about six times less likely to contain a fault than other methods. In cross-project predictions with larger, more diversified training sets, identified methods are even eleven times less likely to contain a fault. Conclusions. Inverse defect prediction supports the efficient allocation of test resources by identifying methods that can be treated with less priority in testing activities and is well applicable in cross-project prediction scenarios.Comment: Submitted to PeerJ C

Detecting directional coupling in the human epileptic brain: Limitations and potential pitfalls

We study directional relationships—in the driver-responder sense—in networks of coupled nonlinear oscillators using a phase modeling approach. Specifically, we focus on the identification of drivers in clusters with varying levels of synchrony, mimicking dynamical interactions between the seizure generating region (epileptic focus) and other brain structures. We demonstrate numerically that such an identification is not always possible in a reliable manner. Using the same analysis techniques as in model systems, we study multichannel electroencephalographic recordings from two patients suffering from focal epilepsy. Our findings demonstrate that—depending on the degree of intracluster synchrony—certain subsystems can spuriously appear to be driving others, which should be taken into account when analyzing field data with unknown underlying dynamics

Precision measurement of the local bias of dark matter halos

We present accurate measurements of the linear, quadratic, and cubic local bias of dark matter halos, using curved "separate universe" N-body simulations which effectively incorporate an infinite-wavelength overdensity. This can be seen as an exact implementation of the peak-background split argument. We compare the results with the linear and quadratic bias measured from the halo-matter power spectrum and bispectrum, and find good agreement. On the other hand, the standard peak-background split applied to the Sheth & Tormen (1999) and Tinker et al. (2008) halo mass functions matches the measured linear bias parameter only at the level of 10%. The prediction from the excursion set-peaks approach performs much better, which can be attributed to the stochastic moving barrier employed in the excursion set-peaks prediction. We also provide convenient fitting formulas for the nonlinear bias parameters $b_2(b_1)$ and $b_3(b_1)$, which work well over a range of redshifts.Comment: 23 pages, 8 figures; v2 : added references (sec. 1, 4, 5), results at higher redshifts on fig. 4 and updated fitting formulas (eqs 5.2-5.3), v3 : clarifications throughout, version accepted by JCA

South Asia in the corona crisis: economic and political consequences

In the countries of South Asia, the rampant coronavirus pandemic could affect more than 1.9 billion people - almost a quarter of the world’s population. Given the weaknesses of national health care systems, the fight against the virus seems to be lost before it has even begun. The economic damage will increase the levels of poverty and inequality, and it is likely to exacerbate rather than mitigate a number of existing conflicts. On the domestic front, it is feared that authoritarian tendencies will increase during the management of the crisis. In the regional context, China could further expand its influence at the expense of India