UK Upland Waters Monitoring Network (UKUWMN) Llyn Llagi, Llyn Cwm Mynach, Afon Hafren and Afon Gwy Annual Summary Progress Report April 2016 - March 2017

The funded chemical and biological sample collection, analysis and data collation, quality control and archiving proceeded without any problems at Llyn Llagi during the period from April 2016 to March 2017. In February 2017 the outflow logger and stageboard were removed pending building works for a National Trust micro-hydro scheme at the site. Subsequently plans for the scheme were withdrawn and it is hoped that the equipment can be reinstalled at the original location

Resolve survey Photometry and volume-limited calibration of the Photometric gas fractions technique

We present custom-processed ultraviolet, optical, and near-infrared photometry for the REsolved Spectroscopy of a Local VolumE (RESOLVE) survey, a volume-limited census of stellar, gas, and dynamical mass within two subvolumes of the nearby universe (RESOLVE-A and RESOLVE-B). RESOLVE is complete down to baryonic mass 10 ~ 9.1 9.3 - M, probing the upper end of the dwarf galaxy regime. In contrast to standard pipeline photometry (e.g., SDSS), our photometry uses optimal background subtraction, avoids suppressing color gradients, and employs multiple flux extrapolation routines to estimate systematic errors. With these improvements, we measure brighter magnitudes, larger radii, bluer colors, and a real increase in scatter around the red sequence. Combining stellar mass estimates based on our optimized photometry with the nearly complete H I mass census for RESOLVE-A, we create new z = 0 volume-limited calibrations of the photometric gas fractions (PGF) technique, which predicts gas-to-stellar mass ratios (G/S) from galaxy colors and optional additional parameters. We analyze G/S-color residuals versus potential third parameters, finding that axial ratio is the best independent and physically meaningful third parameter. We define a “modified color” from planar fits to G/S as a function of both color and axial ratio. In the complete galaxy population, upper limits on G/S bias linear and planar fits. We therefore model the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies. These distributions have two-component structure in the red color regime. Finally, we use the RESOLVE-B 21 cm census to test several PGF calibrations, finding that most systematically under- or overestimate gas masses, but the full probability density method performs well

Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms

Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events that can be non-exponentially distributed. Within parametric ACTMCs, the parameters of alarm-event distributions are not given explicitly and can be subject of parameter synthesis. An algorithm solving the $\varepsilon$-optimal parameter synthesis problem for parametric ACTMCs with long-run average optimization objectives is presented. Our approach is based on reduction of the problem to finding long-run average optimal strategies in semi-Markov decision processes (semi-MDPs) and sufficient discretization of parameter (i.e., action) space. Since the set of actions in the discretized semi-MDP can be very large, a straightforward approach based on explicit action-space construction fails to solve even simple instances of the problem. The presented algorithm uses an enhanced policy iteration on symbolic representations of the action space. The soundness of the algorithm is established for parametric ACTMCs with alarm-event distributions satisfying four mild assumptions that are shown to hold for uniform, Dirac and Weibull distributions in particular, but are satisfied for many other distributions as well. An experimental implementation shows that the symbolic technique substantially improves the efficiency of the synthesis algorithm and allows to solve instances of realistic size.Comment: This article is a full version of a paper accepted to the Conference on Quantitative Evaluation of SysTems (QEST) 201

Optimizing Performance of Continuous-Time Stochastic Systems using Timeout Synthesis

We consider parametric version of fixed-delay continuous-time Markov chains (or equivalently deterministic and stochastic Petri nets, DSPN) where fixed-delay transitions are specified by parameters, rather than concrete values. Our goal is to synthesize values of these parameters that, for a given cost function, minimise expected total cost incurred before reaching a given set of target states. We show that under mild assumptions, optimal values of parameters can be effectively approximated using translation to a Markov decision process (MDP) whose actions correspond to discretized values of these parameters

Natural Disaster and Risk of Psychiatric Disorders in Puerto Rican Children

We examined the persistence of psychiatric disorders at approximately 18 and 30 months after a hurricane among a random sample of the child and adolescent population (4–17 years) of Puerto Rico. Data were obtained from caretaker-child dyads (N = 1,886) through in person interviews with primary caretakers (all children) and youth (11–17 years) using the Diagnostic Interview Schedule for Children IV in Spanish. Logistic regressions, controlling for sociodemographic variables, were used to study the relation between disaster exposure and internalizing, externalizing, or any disorder. Children’s disaster-related distress manifested as internalizing disorders, rather than as externalizing disorders at 18 months post-disaster. At 30 months, there was no longer a significant difference in rates of disorder between hurricane-exposed and non-exposed youth. Results were similar across age ranges. Rates of specific internalizing disorders between exposed and unexposed children are provided. Research and clinical implications are discussed

Distinct variation in vector competence among nine field populations of Aedes aegypti from a Brazilian dengue-endemic risk city

Background: In Brazil, dengue epidemics erupt sporadically throughout the country and it is unclear if outbreaks may initiate a sustainable transmission cycle. There are few studies evaluating the ability of Brazilian Aedes aegypti populations to transmit dengue virus (DENV). The aim of this study was to compare DENV susceptibility of field-captured Ae. aegypti populations from nine distinct geographic areas of the city of Belo Horizonte in 2009 and 2011. Infection Rate (IR), Vector Competence (VC) and Disseminated Infection Rate (DIR) were determined. Methods: Aedes aegypti eggs from each region were collected and reared separately in an insectary. Adult females were experimentally infected with DENV-2 and the virus was detected by qPCR in body and head samples. Data were analyzed with the Statistical Package for the Social Sciences version 17. Results: IR varied from 40.0% to 82.5% in 2009 and 60.0% to 100.0% in 2011. VC ranged from 25.0% to 77.5% in 2009 and 25.0% to 80.0% in 2011. DIR oscillated from 68.7% to 100.0% in 2009 and 38.4% to 86.8 in 2011. When the results were evaluated by a logistic model using IR as covariate, North, Barreiro, South-Central and Venda Nova showed the strongest association in 2009. In 2011, a similar association was observed for South-Central, Venda Nova, West and Northeast regions. Using VC as covariate, South-Central and Venda Nova showed the most relevant association in 2009. In 2011, South-Central, Venda Nova and Barreiro presented the greatest revelation associations. When DIR data were analyzed by logistic regression models, Pampulha, South-Central, Venda Nova, West, Northeast and East (2009) as well as South-Central, Venda Nova and West (2011) were the districts showing the strongest associations. Conclusions: We conclude that Ae. aegypti populations from Belo Horizonte exhibit wide variation in vector competence to transmit dengue. Therefore, vector control strategies should be adapted to the available data for each region. Further analysis should be conducted to better understand the reasons for this large variability in vector competence and how these parameters correlate with epidemiological findings in subsequent years

LNCS

Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting probabilities, discounted sum, and mean payoff. Although there are many techniques for computing these objectives in general MCs/MDPs, they have not been thoroughly studied in terms of parameterized algorithms, particularly when treewidth is used as the parameter. This is in sharp contrast to qualitative objectives for MCs, MDPs and graph games, for which treewidth-based algorithms yield significant complexity improvements. In this work, we show that treewidth can also be used to obtain faster algorithms for the quantitative problems. For an MC with n states and m transitions, we show that each of the classical quantitative objectives can be computed in O((n+m)⋅t2) time, given a tree decomposition of the MC with width t. Our results also imply a bound of O(κ⋅(n+m)⋅t2) for each objective on MDPs, where κ is the number of strategy-iteration refinements required for the given input and objective. Finally, we make an experimental evaluation of our new algorithms on low-treewidth MCs and MDPs obtained from the DaCapo benchmark suite. Our experiments show that on low-treewidth MCs and MDPs, our algorithms outperform existing well-established methods by one or more orders of magnitude