1,654 research outputs found

    Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation

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    We consider two neuronal networks coupled by long-range excitatory interactions. Oscillations in the gamma frequency band are generated within each network by local inhibition. When long-range excitation is weak, these oscillations phase-lock with a phase-shift dependent on the strength of local inhibition. Increasing the strength of long-range excitation induces a transition to chaos via period-doubling or quasi-periodic scenarios. In the chaotic regime oscillatory activity undergoes fast temporal decorrelation. The generality of these dynamical properties is assessed in firing-rate models as well as in large networks of conductance-based neurons.Comment: 4 pages, 5 figures. accepted for publication in Physical Review Letter

    Is the Digital Economy Driving the Economic Growth of the Sumatra Region During the Pandemic?

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    Digitalization has an essential role during the pandemic because it helps facilitate various economic activities. This study aims to analyze the economic digitization of financial technology on economic growth in the Sumatra region (North Sumatra, West Sumatra, and South Sumatra) in January 2020-June 2021. We also used macroeconomic indicators in the form of inflation, foreign direct investment (FDI), and domestic investment (DI) as a control to explain economic conditions. The analysis results using the Panel Vector Autoregression (P-VAR) showed that fintech contributed positively to economic growth. This result was supported by maintained inflation stability that created a conducive investment climate, thereby attracting FDI. We recommend that the regional government take advantage of existing fintech and that "prudent" policies on inflation management must always be adequately prioritized to support the acceleration of economic growth in the Sumatra region, especially North Sumatra, West Sumatra, and South Sumatra

    Statistical-Mechanical Measure of Stochastic Spiking Coherence in A Population of Inhibitory Subthreshold Neurons

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    By varying the noise intensity, we study stochastic spiking coherence (i.e., collective coherence between noise-induced neural spikings) in an inhibitory population of subthreshold neurons (which cannot fire spontaneously without noise). This stochastic spiking coherence may be well visualized in the raster plot of neural spikes. For a coherent case, partially-occupied "stripes" (composed of spikes and indicating collective coherence) are formed in the raster plot. This partial occupation occurs due to "stochastic spike skipping" which is well shown in the multi-peaked interspike interval histogram. The main purpose of our work is to quantitatively measure the degree of stochastic spiking coherence seen in the raster plot. We introduce a new spike-based coherence measure MsM_s by considering the occupation pattern and the pacing pattern of spikes in the stripes. In particular, the pacing degree between spikes is determined in a statistical-mechanical way by quantifying the average contribution of (microscopic) individual spikes to the (macroscopic) ensemble-averaged global potential. This "statistical-mechanical" measure MsM_s is in contrast to the conventional measures such as the "thermodynamic" order parameter (which concerns the time-averaged fluctuations of the macroscopic global potential), the "microscopic" correlation-based measure (based on the cross-correlation between the microscopic individual potentials), and the measures of precise spike timing (based on the peri-stimulus time histogram). In terms of MsM_s, we quantitatively characterize the stochastic spiking coherence, and find that MsM_s reflects the degree of collective spiking coherence seen in the raster plot very well. Hence, the "statistical-mechanical" spike-based measure MsM_s may be used usefully to quantify the degree of stochastic spiking coherence in a statistical-mechanical way.Comment: 16 pages, 5 figures, to appear in the J. Comput. Neurosc

    Delocalisation transition in quasi-1D models with correlated disorder

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    We introduce a new approach to analyse the global structure of electronic states in quasi-1D models in terms of the dynamics of a system of parametric oscillators with time-dependent stochastic couplings. We thus extend to quasi-1D models the method previously applied to 1D disordered models. Using this approach, we show that a ``delocalisation transition'' can occur in quasi-1D models with weak disorder with long-range correlations.Comment: 33 pages, no figure

    Plastic formulation is an emerging control of its photochemical fate in the ocean

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    © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Walsh, A. N., Reddy, C. M., Niles, S. F., McKenna, A. M., Hansel, C. M., & Ward, C. P. Plastic formulation is an emerging control of its photochemical fate in the ocean. Environmental Science & Technology, 55(18), (2021): 12383–12392, https://doi.org/10.1021/acs.est.1c02272.Sunlight exposure is a control of long-term plastic fate in the environment that converts plastic into oxygenated products spanning the polymer, dissolved, and gas phases. However, our understanding of how plastic formulation influences the amount and composition of these photoproducts remains incomplete. Here, we characterized the initial formulations and resulting dissolved photoproducts of four single-use consumer polyethylene (PE) bags from major retailers and one pure PE film. Consumer PE bags contained 15–36% inorganic additives, primarily calcium carbonate (13–34%) and titanium dioxide (TiO2; 1–2%). Sunlight exposure consistently increased production of dissolved organic carbon (DOC) relative to leaching in the dark (3- to 80-fold). All consumer PE bags produced more DOC during sunlight exposure than the pure PE (1.2- to 2.0-fold). The DOC leached after sunlight exposure increasingly reflected the 13C and 14C isotopic composition of the plastic. Ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry revealed that sunlight exposure substantially increased the number of DOC formulas detected (1.1- to 50-fold). TiO2-containing bags photochemically degraded into the most compositionally similar DOC, with 68–94% of photoproduced formulas in common with at least one other TiO2-containing bag. Conversely, only 28% of photoproduced formulas from the pure PE were detected in photoproduced DOC from the consumer PE. Overall, these findings suggest that plastic formulation, especially TiO2, plays a determining role in the amount and composition of DOC generated by sunlight. Consequently, studies on pure, unweathered polymers may not accurately represent the fates and impacts of the plastics entering the ocean.Funding was provided by the Seaver Institute, the Gerstner Family Foundation, Woods Hole Oceanographic Institution, and the National Science Foundation Graduate Research Fellowship Program (A.N.W.). The Ion Cyclotron Resonance user facility at the National High Magnetic Field Laboratory is supported by the National Science Foundation Division of Chemistry and Division of Materials Research through DMR-1644779 and the State of Florida
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