Probability distribution function for self-organization of shear flows

The first prediction of the probability distribution function (PDF) of self-organized shear flows is presented in a nonlinear diffusion model where shear flows are generated by a stochastic forcing while diffused by a nonlinear eddy diffusivity. A novel nonperturbative method based on a coherent structure is utilized for the prediction of the strongly intermittent exponential PDF tails of the gradient of shear flows. Numerical simulations using Gaussian forcing not only confirm these predictions but also reveal the significant contribution from the PDF tails with a large population of supercritical gradients. The validity of the nonlinear diffusion model is then examined using a threshold model where eddy diffusivity is given by discontinuous values, elucidating an important role of relative time scales of relaxation and disturbance in the determination of the PDFs

A structural approach to kernels for ILPs: Treewidth and Total Unimodularity

Kernelization is a theoretical formalization of efficient preprocessing for NP-hard problems. Empirically, preprocessing is highly successful in practice, for example in state-of-the-art ILP-solvers like CPLEX. Motivated by this, previous work studied the existence of kernelizations for ILP related problems, e.g., for testing feasibility of Ax <= b. In contrast to the observed success of CPLEX, however, the results were largely negative. Intuitively, practical instances have far more useful structure than the worst-case instances used to prove these lower bounds. In the present paper, we study the effect that subsystems with (Gaifman graph of) bounded treewidth or totally unimodularity have on the kernelizability of the ILP feasibility problem. We show that, on the positive side, if these subsystems have a small number of variables on which they interact with the remaining instance, then we can efficiently replace them by smaller subsystems of size polynomial in the domain without changing feasibility. Thus, if large parts of an instance consist of such subsystems, then this yields a substantial size reduction. We complement this by proving that relaxations to the considered structures, e.g., larger boundaries of the subsystems, allow worst-case lower bounds against kernelization. Thus, these relaxed structures can be used to build instance families that cannot be efficiently reduced, by any approach.Comment: Extended abstract in the Proceedings of the 23rd European Symposium on Algorithms (ESA 2015

Tight Kernel Bounds for Problems on Graphs with Small Degeneracy

In this paper we consider kernelization for problems on d-degenerate graphs, i.e. graphs such that any subgraph contains a vertex of degree at most $d$. This graph class generalizes many classes of graphs for which effective kernelization is known to exist, e.g. planar graphs, H-minor free graphs, and H-topological-minor free graphs. We show that for several natural problems on d-degenerate graphs the best known kernelization upper bounds are essentially tight.Comment: Full version of ESA 201

On the pathwidth of almost semicomplete digraphs

We call a digraph {\em $h$-semicomplete} if each vertex of the digraph has at most $h$ non-neighbors, where a non-neighbor of a vertex $v$ is a vertex $u \neq v$ such that there is no edge between $u$ and $v$ in either direction. This notion generalizes that of semicomplete digraphs which are $0$-semicomplete and tournaments which are semicomplete and have no anti-parallel pairs of edges. Our results in this paper are as follows. (1) We give an algorithm which, given an $h$-semicomplete digraph $G$ on $n$ vertices and a positive integer $k$, in $(h + 2k + 1)^{2k} n^{O(1)}$ time either constructs a path-decomposition of $G$ of width at most $k$ or concludes correctly that the pathwidth of $G$ is larger than $k$. (2) We show that there is a function $f(k, h)$ such that every $h$-semicomplete digraph of pathwidth at least $f(k, h)$ has a semicomplete subgraph of pathwidth at least $k$. One consequence of these results is that the problem of deciding if a fixed digraph $H$ is topologically contained in a given $h$-semicomplete digraph $G$ admits a polynomial-time algorithm for fixed $h$.Comment: 33pages, a shorter version to appear in ESA 201

An Ensemble Kalman-Particle Predictor-Corrector Filter for Non-Gaussian Data Assimilation

An Ensemble Kalman Filter (EnKF, the predictor) is used make a large change in the state, followed by a Particle Filer (PF, the corrector) which assigns importance weights to describe non-Gaussian distribution. The weights are obtained by nonparametric density estimation. It is demonstrated on several numerical examples that the new predictor-corrector filter combines the advantages of the EnKF and the PF and that it is suitable for high dimensional states which are discretizations of solutions of partial differential equations.Comment: ICCS 2009, to appear; 9 pages; minor edit

Characterization of developmental defects in the forebrain resulting from hyperactivated mTOR signaling by integrative analysis of transcriptomic and proteomic data

Hyperactivated mTOR signaling in the developing brain has been implicated in multiple forms of pathology including tuberous sclerosis complex (TSC). To date, various phenotypic defects such as cortical lamination irregularity, subependymal nodule formation, dysmorphic astrocyte differentiation and dendritic malformation have been described for patients and animal models. However, downstream networks affected in the developing brain by hyperactivated mTOR signaling have yet to be characterized. Here, we present an integrated analysis of transcriptomes and proteomes generated from wild-type and Tsc1/Emx1-Cre forebrains. This led to comprehensive lists of genes and proteins whose expression levels were altered by hyperactivated mTOR signaling. Further incorporation of TSC patient data followed by functional enrichment and network analyses pointed to changes in molecular components and cellular processes associated with neuronal differentiation and morphogenesis as the key downstream events underlying developmental and morphological defects in TSC. Our results provide novel and fundamental molecular bases for understanding hyperactivated mTOR signaling-induced brain defects which can in turn facilitate identification of potential diagnostic markers and therapeutic targets for mTOR signaling-related neurological disorders. ? The Author(s) 2017.11Ysciescopu

Transport of Surface States in the Bulk Quantum Hall Effect

The two-dimensional surface of a coupled multilayer integer quantum Hall system consists of an anisotropic chiral metal. This unusual metal is characterized by ballistic motion transverse and diffusive motion parallel (\hat{z}) to the magnetic field. Employing a network model, we calculate numerically the phase coherent two-terminal z-axis conductance and its mesoscopic fluctuations. Quasi-1d localization effects are evident in the limit of many layers. We consider the role of inelastic de-phasing effects in modifying the transport of the chiral surface sheath, discussing their importance in the recent experiments of Druist et al.Comment: 9 pages LaTex, 9 postscript figures included using eps

Graft immaturity and safety concerns in transplanted human kidney organoids

For chronic kidney disease, regeneration of lost nephrons with human kidney organoids derived from induced pluripotent stem (iPS) cells is proposed to be an attractive potential therapeutic option. It remains unclear, however, whether organoids transplanted into kidneys in vivo would be safe or functional. Here, we purified kidney organoids and transplanted them beneath the kidney capsules of immunodeficient mice to test their safety and maturity. Kidney organoid grafts survived for months after transplantation and became vascularized from host mouse endothelial cells. Nephron-like structures in grafts appeared more mature than kidney organoids in vitro, but remained immature compared with the neighboring mouse kidney tissue. Ultrastructural analysis revealed filtration barrier-like structures, capillary lumens, and tubules with brush border in the transplanted kidney organoids, which were more mature than those of the kidney organoids in vitro but not as organized as adult mammalian kidneys. Immaturity was a common feature of three separate differentiation protocols by immunofluorescence analysis and single cell RNA sequencing. Stroma of transplanted kidney organoid grafts were filled with vimentin-positive mesenchymal cells, and chondrogenesis, cystogenesis, and stromal expansion were observed in the long term. Transcription profiles showed that long-term maintenance after kidney organoid transplantation induced transcriptomic reprogramming with prominent suppression of cell-cycle-related genes and upregulation of extracellular matrix organization. Our data suggest that kidney organoids derived from iPS cells may be transplantable but strategies to improve nephron differentiation and purity are required before they can be applied in humans as a therapeutic option.11Ysciescopuskc

Optical Evidence of Multiphase Coexistence in Single Crystalline (La,Pr,Ca)MnO3

We investigated temperature (T)- and magnetic field-dependent optical conductivity spectra (\s\w) of a La_5/8-yPr_yCa_3/8MnO_3 (y~0.35) single crystal, showing intriguing phase coexistence at low T. At T_C < T < T_CO, a dominant charge-ordered phase produces a large optical gap energy of ~0.4 eV. At T < T_C, at least two absorption bands newly emerge below 0.4 eV. Analyses of (\s\w) indicate that the new bands should be attributed to a ferromagnetic metallic and a charge-disordered phase that coexist with the charge-ordered phase. This optical study clearly shows that La_5/8-yPrCa_3/8MnO_3 (y~0.35) is composed of multiphases that might have different lattice strains.Comment: A single file with 9 figures embedded, to appear in Phys. Rev.

Large Deviations Principle for a Large Class of One-Dimensional Markov Processes

We study the large deviations principle for one dimensional, continuous, homogeneous, strong Markov processes that do not necessarily behave locally as a Wiener process. Any strong Markov process $X_{t}$ in $\mathbb{R}$ that is continuous with probability one, under some minimal regularity conditions, is governed by a generalized elliptic operator $D_{v}D_{u}$, where $v$ and $u$ are two strictly increasing functions, $v$ is right continuous and $u$ is continuous. In this paper, we study large deviations principle for Markov processes whose infinitesimal generator is $\epsilon D_{v}D_{u}$ where $0<\epsilon\ll 1$. This result generalizes the classical large deviations results for a large class of one dimensional "classical" stochastic processes. Moreover, we consider reaction-diffusion equations governed by a generalized operator $D_{v}D_{u}$. We apply our results to the problem of wave front propagation for these type of reaction-diffusion equations.Comment: 23 page