Assessment of assimilating SMOS soil moisture information into a distributed hydrologic model

The role that soil moisture plays in terms of modulating hydrologic processes including infiltration and runoff generation makes it an essential component to capture for hydrologic modeling. This work aims to leverage information gained from SMOS to improve surface soil moisture simulations in the Russian River Basin (California, U.S.A). The basin's complex terrain offers a rigorous testing ground for SMOS soil moisture products. Data from seven in situ observation sites are used to assess model performance after assimilating SMOS-based soil saturation ratios. For a comparison of "best case" scenarios, the in situ observations themselves are assimilated. Results show that SMOS assimilated simulations shows modest improvement at most in situ locations. Despite the observed decrease in model performance at some locations, overall performance of simulations assimilated with SMOS-based saturation ratios remains high. Findings suggest that even in a complex environment, useful information may be extracted from SMOS estimates for hydrologic modeling

A review of Monte Carlo simulations of polymers with PERM

In this review, we describe applications of the pruned-enriched Rosenbluth method (PERM), a sequential Monte Carlo algorithm with resampling, to various problems in polymer physics. PERM produces samples according to any given prescribed weight distribution, by growing configurations step by step with controlled bias, and correcting "bad" configurations by "population control". The latter is implemented, in contrast to other population based algorithms like e.g. genetic algorithms, by depth-first recursion which avoids storing all members of the population at the same time in computer memory. The problems we discuss all concern single polymers (with one exception), but under various conditions: Homopolymers in good solvents and at the $\Theta$ point, semi-stiff polymers, polymers in confining geometries, stretched polymers undergoing a forced globule-linear transition, star polymers, bottle brushes, lattice animals as a model for randomly branched polymers, DNA melting, and finally -- as the only system at low temperatures, lattice heteropolymers as simple models for protein folding. PERM is for some of these problems the method of choice, but it can also fail. We discuss how to recognize when a result is reliable, and we discuss also some types of bias that can be crucial in guiding the growth into the right directions.Comment: 29 pages, 26 figures, to be published in J. Stat. Phys. (2011

Avalanche-Induced Current Enhancement in Semiconducting Carbon Nanotubes

Semiconducting carbon nanotubes under high electric field stress (~10 V/um) display a striking, exponential current increase due to avalanche generation of free electrons and holes. Unlike in other materials, the avalanche process in such 1D quantum wires involves access to the third sub-band, is insensitive to temperature, but strongly dependent on diameter ~exp(-1/d^2). Comparison with a theoretical model yields a novel approach to obtain the inelastic optical phonon emission length, L_OP,ems ~ 15d nm. The combined results underscore the importance of multi-band transport in 1D molecular wires

Overview on new psychoactive substances in Portugal

This working paper provides an overview of the phenomenon of new psychoactive substances (NPS) in Portugal, including suggested definitions of NPS, a review of drug policy in Portugal, NPS markets, NPS demand and supply, prevention strategies and insights from expert interviews. NPS emerged in Portugal in 2007, and despite the closure of NPS physical selling points in 2013 and decreasing rates of NPS consumption, the market seems to be continuing with new particularities: a rise in unintentional consumers and the increasing association with problematic drug use. The new trends in users and consumption patterns as well as new forms of communication, acquisition, and production of substances have challenged conventional mechanisms of drug control in Portugal

A high resolution coupled hydrologic–hydraulic model (HiResFlood-UCI) for flash flood modeling

HiResFlood-UCI was developed by coupling the NWS's hydrologic model (HL-RDHM) with the hydraulic model (BreZo) for flash flood modeling at decameter resolutions. The coupled model uses HL-RDHM as a rainfall-runoff generator and replaces the routing scheme of HL-RDHM with the 2D hydraulic model (BreZo) in order to predict localized flood depths and velocities. A semi-automated technique of unstructured mesh generation was developed to cluster an adequate density of computational cells along river channels such that numerical errors are negligible compared with other sources of error, while ensuring that computational costs of the hydraulic model are kept to a bare minimum. HiResFlood-UCI was implemented for a watershed (ELDO2) in the DMIP2 experiment domain in Oklahoma. Using synthetic precipitation input, the model was tested for various components including HL-RDHM parameters (a priori versus calibrated), channel and floodplain Manning n values, DEM resolution (10 m versus 30 m) and computation mesh resolution (10 m+ versus 30 m+). Simulations with calibrated versus a priori parameters of HL-RDHM show that HiResFlood-UCI produces reasonable results with the a priori parameters from NWS. Sensitivities to hydraulic model resistance parameters, mesh resolution and DEM resolution are also identified, pointing to the importance of model calibration and validation for accurate prediction of localized flood intensities. HiResFlood-UCI performance was examined using 6 measured precipitation events as model input for model calibration and validation of the streamflow at the outlet. The Nash–Sutcliffe Efficiency (NSE) obtained ranges from 0.588 to 0.905. The model was also validated for the flooded map using USGS observed water level at an interior point. The predicted flood stage error is 0.82 m or less, based on a comparison to measured stage. Validation of stage and discharge predictions builds confidence in model predictions of flood extent and localized velocities, which are fundamental to reliable flash flood warning

Dragging a polymer chain into a nanotube and subsequent release

We present a scaling theory and Monte Carlo (MC) simulation results for a flexible polymer chain slowly dragged by one end into a nanotube. We also describe the situation when the completely confined chain is released and gradually leaves the tube. MC simulations were performed for a self-avoiding lattice model with a biased chain growth algorithm, the pruned-enriched Rosenbluth method. The nanotube is a long channel opened at one end and its diameter $D$ is much smaller than the size of the polymer coil in solution. We analyze the following characteristics as functions of the chain end position $x$ inside the tube: the free energy of confinement, the average end-to-end distance, the average number of imprisoned monomers, and the average stretching of the confined part of the chain for various values of $D$ and for the number of monomers in the chain, $N$. We show that when the chain end is dragged by a certain critical distance $x^*$ into the tube, the polymer undergoes a first-order phase transition whereby the remaining free tail is abruptly sucked into the tube. This is accompanied by jumps in the average size, the number of imprisoned segments, and in the average stretching parameter. The critical distance scales as $x^*\sim ND^{1-1/\nu}$. The transition takes place when approximately 3/4 of the chain units are dragged into the tube. The theory presented is based on constructing the Landau free energy as a function of an order parameter that provides a complete description of equilibrium and metastable states. We argue that if the trapped chain is released with all monomers allowed to fluctuate, the reverse process in which the chain leaves the confinement occurs smoothly without any jumps. Finally, we apply the theory to estimate the lifetime of confined DNA in metastable states in nanotubes.Comment: 13pages, 14figure

Structure optimization in an off-lattice protein model

We study an off-lattice protein toy model with two species of monomers interacting through modified Lennard-Jones interactions. Low energy configurations are optimized using the pruned-enriched-Rosenbluth method (PERM), hitherto employed to native state searches only for off lattice models. For 2 dimensions we found states with lower energy than previously proposed putative ground states, for all chain lengths $\ge 13$. This indicates that PERM has the potential to produce native states also for more realistic protein models. For $d=3$, where no published ground states exist, we present some putative lowest energy states for future comparison with other methods.Comment: 4 pages, 2 figure

Average-Case Optimal Approximate Circular String Matching

Approximate string matching is the problem of finding all factors of a text t of length n that are at a distance at most k from a pattern x of length m. Approximate circular string matching is the problem of finding all factors of t that are at a distance at most k from x or from any of its rotations. In this article, we present a new algorithm for approximate circular string matching under the edit distance model with optimal average-case search time O(n(k + log m)/m). Optimal average-case search time can also be achieved by the algorithms for multiple approximate string matching (Fredriksson and Navarro, 2004) using x and its rotations as the set of multiple patterns. Here we reduce the preprocessing time and space requirements compared to that approach