For complex diseases, the relationship between genotypes, environment factors and phenotype is usually complex and nonlinear. Our understanding of the genetic architecture of diseases has considerably increased over the last years. However, both conceptually and methodologically, detecting gene-gene and gene-environment interactions remains a challenge, despite the existence of a number of efficient methods. One method that offers great promises but has not yet been widely applied to genomic data is the entropy-based approach of information theory. In this paper we first develop entropy-based test statistics to identify 2-way and higher order gene-gene and gene-environment interactions. We then apply these methods to a bladder cancer data set and thereby test their power and identify strengths and weaknesses. For two-way interactions, we propose an information-gain approach based on mutual information. For three-ways and higher order interactions, an interaction-information-gain approach is used. In both case we develop one-dimensional test statistics to analyze sparse data. Compared to the naive chi-square test, the test statistics we develop have similar or higher power and is robust. Applying it to the bladder cancer data set allowed to investigate the complex interactions between DNA repair gene SNPs, smoking status, and bladder cancer susceptibility. Although not yet widely applied, entropy-based approaches appear as a useful tool for detecting gene-gene and gene-environment interactions. The test statistics we develop add to a growing body methodologies that will gradually shed light on the complex architecture of common diseases.

Recent surge of interest towards congestion control that relies on single-link feedback (e.g., XCP, RCP, MaxNet, EMKC, VCP), suggests that such systems may offer certain benefits over traditional models of additive packet loss. Besides topology-independent stability and faster convergence to efficiency/fairness, it was recently shown that any stable singlelink system with a symmetric Jacobian tolerates arbitrary fixed, as well as time-varying, feedback delays. Although delayindependence is an appealing characteristic, the EMKC system developed in exhibits undesirable equilibrium properties and slow convergence behavior. To overcome these drawbacks, we propose a new method called JetMax and show that it admits a low-overhead implementation inside routers (three additions per packet), overshoot-free transient and steady state, tunable link utilization, and delay-insensitive flow dynamics. The proposed framework also provides capacity-independent convergence time, where fairness and utilization are reached in the same number of RTT steps for a link of any bandwidth. Given a 1 mb/s, 10 gb/s, or googol (10 100 ) bps link, the method converges to within 1% of the stationary state in six RTTs. We finish the paper by comparing JetMax's performance to that of existing methods in ns2 simulations and discussing its Linux implementation.

[1] We present a comprehensive study of velocity interpolation methods in polygons. These methods are often used as postprocessing procedures for numerical schemes that do not directly calculate the velocity field but only provide cell boundary flux conditions, such as the finite volume schemes. These methods extend the widely used velocity interpolation algorithms, such as the Pollock's algorithm, to more complex geometries such as perpendicular bisection (PEBI) grids, unstructured triangular grids and grids with local refinement. Once the velocity field is interpolated, streamline trajectories and time of flight along the streamlines can be calculated for reservoir simulation, model calibration and waterflood management, for instance. These velocity interpolation methods assume known lower-order or higher-order cell boundary fluxes, which satisfy global mass conservation and normal flux continuity. However, they differ in the interpolation of velocities within the interior of the cells. The interpolating velocity may be locally conservative or nonconservative, continuous or discontinuous, lower order or higher order. Results show that the interpolated velocity field has to be locally conservative in order to guarantee the correct volumetric transformation for the calculated streamlines and the time of flight. Velocity continuity is not as important as local conservation for the purpose of streamline applications. Compared to higher-order interpolation for the streamline trajectories, lower-order interpolation has the advantage of an analytic solution and an efficient implementation. Based on our analysis, we recommend a lower-order locally conservative method for the most robust and numerically efficient calculation of streamline trajectories on unstructured grids.

No abstract

In this paper, we present a software framework, SπRITROOT, which is capable of track reconstruction and analysis of heavy-ion collision events recorded with the SπRIT time projection chamber. The track-fitting toolkit GENFIT and the vertex reconstruction toolkit RAVE are applied to a box-type detector system. A pattern recognition algorithm which performs helix track finding and handles overlapping pulses is described. The performance of the software is investigated using experimental data obtained at the Radioactive Isotope Beam Facility (RIBF) at RIKEN. This work focuses on data from 132 Sn + 124 Sn collision events with beam energy of 270 AMeV. Particle identification is established using dE/dx and magnetic rigidity, with pions, hydrogen isotopes, and helium isotopes. (G. Jhang) in a future paper. The main focus of this paper is on the reconstruction of tracks.Here we describe the process of reconstructing tracks from the raw data into information relevant to particle identification; specifically, the momentum vector, specific energy loss, and the collision vertex in events. We have adopted several open source C++ software packages into SπRITROOT such as GEN-FIT [10] for the momentum reconstruction and RAVE [11] for the vertex reconstruction. Although these packages have been mainly developed for cylindrical detector systems [12], we have successfully modified them to work with the box-type detector system such as the SπRIT-TPC.In April and May of 2016, Rare Isotope (RI) collision events were taken with SπRIT TPC inside the SAMURAI magnet [13]. The main collision systems were 132 Sn+ 124 Sn, 124 Sn+ 112 Sn, 108 Sn+ 124 Sn, and 108 Sn+ 112 Sn at 270 AMeV with beam rate of 10 kHz. The magnetic field produced by the SAMURAI magnet was 0.5 T. The performance of the SπRITROOT software described in this paper is based on the analysis of 132 Sn+ 124 Sn data. SπRIT-TPCThe SπRIT-TPC is a rectangular TPC operated with a Multi-Wire Proportional Chamber (MWPC) readout [2]. The geometry and dimensions of the SπRIT TPC field cage is shown in