3,592 research outputs found

    In Situ ATR-SEIRAS of Carbon Dioxide Reduction at a Plasmonic Silver Cathode.

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    Illumination of a voltage-biased plasmonic Ag cathode during CO2 reduction results in a suppression of the H2 evolution reaction while enhancing CO2 reduction. This effect has been shown to be photonic rather than thermal, but the exact plasmonic mechanism is unknown. Here, we conduct an in situ ATR-SEIRAS (attenuated total reflectance-surface-enhanced infrared absorption spectroscopy) study of a sputtered thin film Ag cathode on a Ge ATR crystal in CO2-saturated 0.1 M KHCO3 over a range of potentials under both dark and illuminated (365 nm, 125 mW cm-2) conditions to elucidate the nature of this plasmonic enhancement. We find that the onset potential of CO2 reduction to adsorbed CO on the Ag surface is -0.25 VRHE and is identical in the light and the dark. As the production of gaseous CO is detected in the light near this onset potential but is not observed in the dark until -0.5 VRHE, we conclude that the light must be assisting the desorption of CO from the surface. Furthermore, the HCO3- wavenumber and peak area increase immediately upon illumination, precluding a thermal effect. We propose that the enhanced local electric field that results from the localized surface plasmon resonance (LSPR) is strengthening the HCO3- bond, further increasing the local pH. This would account for the decrease in H2 formation and increase the CO2 reduction products in the light

    Luminescent Syllid (Odontosyllis sp.) Courtship Display Densities Vary Across Marine Habitats around South Water Caye, Belize

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    Bright—green luminescent clouds frequently occur at the surface of shallow waters of the Caribbean Sea. These clouds are produced by syllid polychaetes during courtship. Although temporal variation in the occurrence of these courtship displays has been documented throughout the diurnal and lunar cycle, other factors such as habitat type have not been well studied. In this study, we investigated how syllid courtship—display densities varied across 3 substrate types (grassbed, rubble and coral) over a 3 day period. In line with previous studies, we found that syllid courtship displays occurred over seagrass and rubble substrates; however, we also found that display densities were significantly higher over shallow coral substrates than over either seagrass or rubble habitats. These findings reflect published observations and newly collected observational data from other locations throughout the Caribbean. Future work across species, time and regions is required in order to better understand the factors underlying syllid display densities

    Spatial Interpolants

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    We propose Splinter, a new technique for proving properties of heap-manipulating programs that marries (1) a new separation logic-based analysis for heap reasoning with (2) an interpolation-based technique for refining heap-shape invariants with data invariants. Splinter is property directed, precise, and produces counterexample traces when a property does not hold. Using the novel notion of spatial interpolants modulo theories, Splinter can infer complex invariants over general recursive predicates, e.g., of the form all elements in a linked list are even or a binary tree is sorted. Furthermore, we treat interpolation as a black box, which gives us the freedom to encode data manipulation in any suitable theory for a given program (e.g., bit vectors, arrays, or linear arithmetic), so that our technique immediately benefits from any future advances in SMT solving and interpolation.Comment: Short version published in ESOP 201

    Adding New Tasks to a Single Network with Weight Transformations using Binary Masks

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    Visual recognition algorithms are required today to exhibit adaptive abilities. Given a deep model trained on a specific, given task, it would be highly desirable to be able to adapt incrementally to new tasks, preserving scalability as the number of new tasks increases, while at the same time avoiding catastrophic forgetting issues. Recent work has shown that masking the internal weights of a given original conv-net through learned binary variables is a promising strategy. We build upon this intuition and take into account more elaborated affine transformations of the convolutional weights that include learned binary masks. We show that with our generalization it is possible to achieve significantly higher levels of adaptation to new tasks, enabling the approach to compete with fine tuning strategies by requiring slightly more than 1 bit per network parameter per additional task. Experiments on two popular benchmarks showcase the power of our approach, that achieves the new state of the art on the Visual Decathlon Challenge

    Spatial heterogeneity enhances and modulates excitability in a mathematical model of the myometrium

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    The muscular layer of the uterus (myometrium) undergoes profound changes in global excitability prior to parturition. Here, a mathematical model of the myocyte network is developed to investigate the hypothesis that spatial heterogeneity is essential to the transition from local to global excitation which the myometrium undergoes just prior to birth. Each myometrial smooth muscle cell is represented by an element with FitzHugh–Nagumo dynamics. The cells are coupled through resistors that represent gap junctions. Spatial heterogeneity is introduced by means of stochastic variation in coupling strengths, with parameters derived from physiological data. Numerical simulations indicate that even modest increases in the heterogeneity of the system can amplify the ability of locally applied stimuli to elicit global excitation. Moreover, in networks driven by a pacemaker cell, global oscillations of excitation are impeded in fully connected and strongly coupled networks. The ability of a locally stimulated cell or pacemaker cell to excite the network is shown to be strongly dependent on the local spatial correlation structure of the couplings. In summary, spatial heterogeneity is a key factor in enhancing and modulating global excitability

    Efficacy of weekly teriparatide does not vary by baseline fracture probability calculated using FRAX

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    Summary The aim of this study was to determine the efficacy of once-weekly teriparatide as a function of baseline fracture risk. Treatment with once-weekly teriparatide was associated with a statistically significant 79 % decrease in vertebral fractures, and in the cohort as a whole, efficacy was not related to baseline fracture risk. Introduction Previous studies have suggested that the efficacy of some interventions may be greater in the segment of the population at highest fracture risk as assessed by the FRAX® algorithms. The aim of the present study was to determine whether the antifracture efficacy of weekly teriparatide was dependent on the magnitude of fracture risk. Methods Baseline fracture probabilities (using FRAX) were computed from the primary data of a phase 3 study (TOWER) of the effects of weekly teriparatide in 542 men and postmenopausal women with osteoporosis. The outcome variable comprised morphometric vertebral fractures. Interactions between fracture probability and efficacy were explored by Poisson regression. Results The 10-year probability of major osteoporotic fractures (without BMD) ranged from 7.2 to 42.2 %. FRAX-based hip fracture probabilities ranged from 0.9 to 29.3 %. Treatment with teriparatide was associated with a 79 % (95 % CI 52–91 %) decrease in vertebral fractures assessed by semiquantitative morphometry. Relative risk reductions for the effect of teriparatide on the fracture outcome did not change significantly across the range of fracture probabilities (p = 0.28). In a subgroup analysis of 346 (64 %) participants who had FRAX probabilities calculated with the inclusion of BMD, there was a small but significant interaction (p = 0.028) between efficacy and baseline fracture probability such that high fracture probabilities were associated with lower efficacy. Conclusion Weekly teriparatide significantly decreased the risk of morphometric vertebral fractures in men and postmenopausal women with osteoporosis. Overall, the efficacy of teriparatide was not dependent on the level of fracture risk assessed by FRAX in the cohort as a whole

    Pseudorehearsal in value function approximation

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    Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters
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