Stretched Exponential Relaxation in the Biased Random Voter Model

We study the relaxation properties of the voter model with i.i.d. random bias. We prove under mild condions that the disorder-averaged relaxation of this biased random voter model is faster than a stretched exponential with exponent $d/(d+\alpha)$, where $0<\alpha\le 2$ depends on the transition rates of the non-biased voter model. Under an additional assumption, we show that the above upper bound is optimal. The main ingredient of our proof is a result of Donsker and Varadhan (1979).Comment: 14 pages, AMS-LaTe

THE DECAY OF NEPTUNIUM-238

>A study was made of the energy levels of Pu/sup 238/ which are populated by Np/sup 238/ beta decay, by an examination of the Np/sup 238/ conversion electron spectrum in high-resolution beta spectrographs. The general features of the level scheme as previously given were unchanged but several new transitions were observed, with energies of 119.8, 871, 943, 989, and 1034 kev. Two new levels are postulated at 915 and 1034 kev which accommodate all but the 943-kev transition. A possible assignment of the 943-kev transition to the (0+.0) state of the beta vibrational band is discussed. In addition, the weak 885-kev transition from the 2+ state of the gamma -vibrational band to the 4+ state of the ground band was seen and its relative intensity determined. Comparisons were made of the experimental relative transition intensities of the three photons depopulating this band with those predicted from the rules of Alaga et al.; only fair agreement was noted. A discussion is given of the beta decay branchings and log ft values of Np/sup 238/ decay in terms of the postulated characters of the Pu/sup 238/ states and the measured spin of Np/sup 238/. (auth

RAPIDLY-LABELLED, ACIDIC PHOSPHOLIPIDS OF THE GOLDFISH BRAIN 1

Homogenates and particulate fractions of goldfish brain incorporated radioactivity from Γ-[ 32 P]ATP selectively into acidic phospholipids during brief periods of incubation. Phosphatidate and lysophosphatidate became strongly labelled and activity was also found in phosphatidyl inositol phosphate and in phosphatidyl inositol diphosphate. When tetraphenylborate (a K + -complexing agent) was added, a selective stimulation of incorporation of 32 P into phosphatidate occurred. The addition of perchlorate (also known to bind K + ) did not produce a similar stimulation, nor did the addition of K + block the stimulation by tetraphenylborate. The stimulation of the labelling of phospholipids by tetraphenylborate appeared to be the result of multiple actions. Besides the evidence that it acted by stimulating the phosphoinositide phosphodiesterase of brain, data were obtained suggesting that it stimulated diglyceride kinase and blocked endogenous destruction of ATP as well. The stimulation by tetraphenylborate was blocked by addition of atropine but not of arecoline.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65711/1/j.1471-4159.1970.tb03374.x.pd

Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the machine learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods we tested. In our experiments we consider a specific problem instance and real-world dataset relevant to predicting snow properties in high-mountain Asia

The Potential of Restarts for ProbSAT

This work analyses the potential of restarts for probSAT, a quite successful algorithm for k-SAT, by estimating its runtime distributions on random 3-SAT instances that are close to the phase transition. We estimate an optimal restart time from empirical data, reaching a potential speedup factor of 1.39. Calculating restart times from fitted probability distributions reduces this factor to a maximum of 1.30. A spin-off result is that the Weibull distribution approximates the runtime distribution for over 93% of the used instances well. A machine learning pipeline is presented to compute a restart time for a fixed-cutoff strategy to exploit this potential. The main components of the pipeline are a random forest for determining the distribution type and a neural network for the distribution's parameters. ProbSAT performs statistically significantly better than Luby's restart strategy and the policy without restarts when using the presented approach. The structure is particularly advantageous on hard problems.Comment: Eurocast 201

A bulky glycocalyx fosters metastasis formation by promoting G1 cell cycle progression.

Metastasis depends upon cancer cell growth and survival within the metastatic niche. Tumors which remodel their glycocalyces, by overexpressing bulky glycoproteins like mucins, exhibit a higher predisposition to metastasize, but the role of mucins in oncogenesis remains poorly understood. Here we report that a bulky glycocalyx promotes the expansion of disseminated tumor cells in vivo by fostering integrin adhesion assembly to permit G1 cell cycle progression. We engineered tumor cells to display glycocalyces of various thicknesses by coating them with synthetic mucin-mimetic glycopolymers. Cells adorned with longer glycopolymers showed increased metastatic potential, enhanced cell cycle progression, and greater levels of integrin-FAK mechanosignaling and Akt signaling in a syngeneic mouse model of metastasis. These effects were mirrored by expression of the ectodomain of cancer-associated mucin MUC1. These findings functionally link mucinous proteins with tumor aggression, and offer a new view of the cancer glycocalyx as a major driver of disease progression

Measuring degree-degree association in networks

The Pearson correlation coefficient is commonly used for quantifying the global level of degree-degree association in complex networks. Here, we use a probabilistic representation of the underlying network structure for assessing the applicability of different association measures to heavy-tailed degree distributions. Theoretical arguments together with our numerical study indicate that Pearson's coefficient often depends on the size of networks with equal association structure, impeding a systematic comparison of real-world networks. In contrast, Kendall-Gibbons' $\tau_{b}$ is a considerably more robust measure of the degree-degree association

Relaxation Height in Energy Landscapes: an Application to Multiple Metastable States

The study of systems with multiple (not necessarily degenerate) metastable states presents subtle difficulties from the mathematical point of view related to the variational problem that has to be solved in these cases. We introduce the notion of relaxation height in a general energy landscape and we prove sufficient conditions which are valid even in presence of multiple metastable states. We show how these results can be used to approach the problem of multiple metastable states via the use of the modern theories of metastability. We finally apply these general results to the Blume--Capel model for a particular choice of the parameters ensuring the existence of two multiple, and not degenerate in energy, metastable states

Geometric and dynamic perspectives on phase-coherent and noncoherent chaos

Statistically distinguishing between phase-coherent and noncoherent chaotic dynamics from time series is a contemporary problem in nonlinear sciences. In this work, we propose different measures based on recurrence properties of recorded trajectories, which characterize the underlying systems from both geometric and dynamic viewpoints. The potentials of the individual measures for discriminating phase-coherent and noncoherent chaotic oscillations are discussed. A detailed numerical analysis is performed for the chaotic R\"ossler system, which displays both types of chaos as one control parameter is varied, and the Mackey-Glass system as an example of a time-delay system with noncoherent chaos. Our results demonstrate that especially geometric measures from recurrence network analysis are well suited for tracing transitions between spiral- and screw-type chaos, a common route from phase-coherent to noncoherent chaos also found in other nonlinear oscillators. A detailed explanation of the observed behavior in terms of attractor geometry is given.Comment: 12 pages, 13 figure

Limiting Behaviour of the Mean Residual Life

In survival or reliability studies, the mean residual life or life expectancy is an important characteristic of the model. Here, we study the limiting behaviour of the mean residual life, and derive an asymptotic expansion which can be used to obtain a good approximation for large values of the time variable. The asymptotic expansion is valid for a quite general class of failure rate distributions--perhaps the largest class that can be expected given that the terms depend only on the failure rate and its derivatives.Comment: 19 page