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Термоактивационная спектроскопия композитных полимерных пленок на основе ударопрочного полистирола
(2019)
С помощью метода токов термостимулированной деполяризации (ТСД) исследованы релаксационные процессы в пленках ударопрочного полистирола (УПС) без наполнителя и с различным содержанием диоксида титана TiO2 (2, 4, 6 об.%). На кривых тока ТСД, полученных для композитных пленок, обнаружено три пика. Первый (α-релаксация) возникает при температуре около 93 °C и соответствует переходу вещества из стеклообразного состояния в высокоэластическое. Второй (ρ-пик) появляется как высокотемпературное плечо α-пика и соответствует процессу высвобождения и движения избыточных носителей заряда. Наличие третьего пика при температуре около 150 ºС характерно только для композитных пленок УПС. Разделение перекрывающихся α- и ρ-пиков проведено методом частичной термоочистки. Последующее применение регуляризующих алгоритмов Тихонова позволило определить энергию активации второго процесcа и сравнить полученное значение с результатом, полученным методом диэлектрической спектроскопии.
Wings of the butterfly
(2017)
The spatio-temporal evolution of sunspot activity, the so-called Maunder butterfly diagram, has been continously available since 1874 using data from the Royal Greenwich Observatory, extended by SOON network data after 1976. Here we present a new extended butterfly diagram of sunspot group occurrence since 1826, using the recently digitized data from Schwabe (1826-1867) and Sporer (1866-1880). The wings of the diagram are separated using a recently developed method based on an analysis of long gaps in sunspot group occurrence in different latitude bands. We define characteristic latitudes, corresponding to the start, end, and the largest extent of the wings (the F, L, and H latitudes). The H latitudes (30 degrees-45 degrees) are highly significantly correlated with the strength of the wings (quantified by the total sum of the monthly numbers of sunspot groups). The F latitudes (20 degrees-30 degrees) depict a weak tendency, especially in the southern hemisphere, to follow the wing strength. The L latitudes (2 degrees-10 degrees) show no clear relation to the wing strength. Overall, stronger cycle wings tend to start at higher latitudes and have a greater wing extent. A strong (5-6)-cycle periodic oscillation is found in the start and end times of the wings and in the overlap and gaps between successive wings of one hemisphere. While the average wing overlap is zero in the southern hemisphere, it is two to three months in the north. A marginally significant oscillation of about ten solar cycles is found in the asymmetry of the L latitudes. The new long database of butterfly wings provides new observational constraints to solar dynamo models that discuss the spatio-temporal distribution of sunspot occurrence over the solar cycle and longer.
A very small fraction of (runaway) massive stars have masses exceeding 60-70 M-circle dot and are predicted to evolve as luminous blue variable and Wolf-Rayet stars before ending their lives as core-collapse supernovae. Our 2D axisymmetric hydrodynamical simulations explore how a fast wind (2000 km s(-1)) and high mass-loss rate (10(-5)M(circle dot) yr(-1)) can impact the morphology of the circumstellar medium. It is shaped as 100 pc-scale wind nebula that can be pierced by the driving star when it supersonically moves with velocity 20-40 km s(-1) through the interstellar medium (ISM) in the Galactic plane. The motion of such runaway stars displaces the position of the supernova explosion out of their bow shock nebula, imposing asymmetries to the eventual shock wave expansion and engendering Cygnus-loop-like supernova remnants. We conclude that the size (up to more than 200 pc) of the filamentary wind cavity in which the chemically enriched supernova ejecta expand, mixing efficiently the wind and ISM materials by at least 10 per cent in number density, can be used as a tracer of the runaway nature of the very massive progenitors of such 0.1Myr old remnants. Our results motivate further observational campaigns devoted to the bow shock of the very massive stars BD+43 degrees 3654 and to the close surroundings of the synchrotron-emitting Wolf-Rayet shell G2.4+1.4.
We consider the behavior of spherically symmetric Einasto halos composed of gravitating particles in the Fokker-Planck approximation. This approach allows us to consider the undesirable influence of close encounters in the N-body simulations more adequately than the generally accepted criteria. The Einasto profile with index n approximate to 6 is a stationary solution of the Fokker-Planck equation in the halo center. There are some reasons to believe that the solution is an attractor. Then the Fokker-Planck diffusion tends to transform a density profile to the equilibrium one with the Einasto index n approximate to 6. We suggest this effect as a possible reason why the Einasto index n approximate to 6 occurs so frequently in the interpretation of N-body simulation results. The results obtained cast doubt on generally accepted criteria of N-body simulation convergence.
Predicting the electron population of Earth's ring current during geomagnetic storms still remains a challenging task.
In this work, we investigate the sensitivity of 10 keV ring current electrons to different driving processes, parameterised by the Kp index, during several moderate and intense storms.
Results are validated against measurements from the Van Allen Probes satellites. Perturbing the Kp index allows us to identify the most dominant processes for moderate and intense storms respectively.
We find that during moderate storms (Kp < 6) the drift velocities mostly control the behaviour of low energy electrons, while loss from wave-particle interactions is the most critical parameter for quantifying the evolution of intense storms (Kp > 6). Perturbations of the Kp index used to drive the boundary conditions at GEO and set the plasmapause location only show a minimal effect on simulation results over a limited L range.
It is further shown that the flux at L & SIM; 3 is more sensitive to changes in the Kp index compared to higher L shells, making it a good proxy for validating the source-loss balance of a ring current model.
What comes NeXT?
(2019)
Here, we report on a new record in the acquisition time for fast neutron tomography. With an optimized imaging setup, it was possible to acquire single radiographic projection images with 10 ms and full tomographies with 155 projections images and a physical spatial resolution of 200 mu m within 1.5 s. This is about 6.7 times faster than the current record. We used the technique to investigate the water infiltration in the soil with a living lupine root system. The fast imaging setup will be part of the future NeXT instrument at ILL in Grenoble with a great field of possible future applications. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Ice-core-based records of isotopic composition are a proxy for past temperatures and can thus provide information on polar climate variability over a large range of timescales. However, individual isotope records are affected by a multitude of processes that may mask the true temperature variability. The relative magnitude of climate and non-climate contributions is expected to vary as a function of timescale, and thus it is crucial to determine those temporal scales on which the actual signal dominates the noise. At present, there are no reliable estimates of this timescale dependence of the signal-to-noise ratio (SNR). Here, we present a simple method that applies spectral analyses to stable-isotope data from multiple cores to estimate the SNR, and the signal and noise variability, as a function of timescale. The method builds on separating the contributions from a common signal and from local variations and includes a correction for the effects of diffusion and time uncertainty. We apply our approach to firn-core arrays from Dronning Maud Land (DML) in East Antarctica and from the West Antarctic Ice Sheet (WAIS). For DML and decadal to multi-centennial timescales, we find an increase in the SNR by nearly 1 order of magnitude (similar to 0.2 at decadal and similar to 1.0 at multi-centennial scales). The estimated spectrum of climate variability also shows increasing variability towards longer timescales, contrary to what is traditionally inferred from single records in this region. In contrast, the inferred variability spectrum for WAIS stays close to constant over decadal to centennial timescales, and the results even suggest a decrease in SNR over this range of timescales. We speculate that these differences between DML and WAIS are related to differences in the spatial and temporal scales of the isotope signal, highlighting the potentially more homogeneous atmospheric conditions on the Antarctic Plateau in contrast to the marine-influenced conditions on WAIS. In general, our approach provides a methodological basis for separating local proxy variability from coherent climate variations, which is applicable to a large set of palaeoclimate records.
We study by Monte Carlo simulations a kinetic exchange trading model for both fixed and distributed saving propensities of the agents and rationalize the person and wealth distributions. We show that the newly introduced wealth distribution – that may be more amenable in certain situations – features a different power-law exponent, particularly for distributed saving propensities of the agents. For open agent-based systems, we analyze the person and wealth distributions and find that the presence of trap agents alters their amplitude, leaving however the scaling exponents nearly unaffected. For an open system, we show that the total wealth – for different trap agent densities and saving propensities of the agents – decreases in time according to the classical Kohlrausch–Williams–Watts stretched exponential law. Interestingly, this decay does not depend on the trap agent density, but rather on saving propensities. The system relaxation for fixed and distributed saving schemes are found to be different.
We introduce and study a family of lattice equations which may be viewed either as a strongly nonlinear discrete extension of the Gardner equation, or a non-convex variant of the Lotka-Volterra chain. Their deceptively simple form supports a very rich family of complex solitary patterns. Some of these patterns are also found in the quasi-continuum rendition, but the more intriguing ones, like interlaced pairs of solitary waves, or waves which may reverse their direction either spontaneously or due a collision, are an intrinsic feature of the discrete realm.
In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks over different timescales. Therefore, we propose to apply the wavelet multiscale correlation (WMC) similarity measure, which is a combination of two state-of-the-art methods, viz. wavelet and Pearson’s correlation, for investigating multiscale processes through complex networks. Firstly we decompose the data over different timescales using the wavelet approach and subsequently construct a corresponding network by Pearson’s correlation. The proposed approach is illustrated and tested on two synthetics and one real-world example. The first synthetic case study shows the efficacy of the proposed approach to unravel scale-specific connections, which are often undiscovered at a single scale. The second synthetic case study illustrates that by dividing and constructing a separate network for each time window we can detect significant changes in the signal structure. The real-world example investigates the behavior of the global sea surface temperature (SST) network at different timescales. Intriguingly, we notice that spatial dependent structure in SST evolves temporally. Overall, the proposed measure has an immense potential to provide essential insights on understanding and extending complex multivariate process studies at multiple scales.