Medium Time Scales Research Articles

Automated Recognition of Sleep Apnea-Hypopnea Syndrome Using Continuous Wavelet Transform-Based Multiscale Dispersion Entropy of Single-Lead ECG Signal

A new method is proposed for recognition of the sleep apnea-hypopnea syndrome (SAHS) using electrocardiograms (ECG) signal in order to find an alternative with the same performance of polysomnography (PSG). Heart rate variability (HRV) signals generated from an ECG signal are used to examine a wide range of indices. A novel aspect of this work is the use of a method to decompose the HRV spectrum into total power spectrum (TP), high frequency (HF), low frequency (LF) and very low frequency (VLF) sub-band signals, and correlates their energy content with sympathetic and parasympathetic activity. The HRV signal was decomposed using the continuous wavelet transform (CWT) followed by the inverse continuous wavelet transform (ICWT), and sub-band signals were extracted from 5-minute episodes. In this regard, the suggested technique provides novel indices based on the mean of small (1 to 5), medium (6 to 10) and large (11 to 20) time scales of multiscal dispersion entropy (MDE) for each sub-band signals. In order to choose the best classifier, the indices of the MDE are submitted to a t-test technique and categorized using three classifiers: decision trees (DT), support vector machines (SVM-RBF) and K-nearest neighbor (KNN). The proposed method is evaluated using the combination of Physionet Apnea–ECG database and the University College Dublin Sleep Apnea Database. Using a 10-fold cross validation technique, the SVM-RBF classification approach achieves an average sensitivity, specificity, and accuracy of 93.91%, 96.92% and 93.94%, respectively. The results demonstrate that the approach presented is as precise as the best contemporary methods investigated using the same ECG datasets.

Direct Determination of Reduced Models of a Class of Singularly Perturbed Nonlinear Systems on Three Time Scales in a Bond Graph Approach

One of the most important features in the analysis of the singular perturbation methods is the reduction of models. Likewise, the bond graph methodology in dynamic system modeling has been widely used. In this paper, the bond graph modeling of nonlinear systems with singular perturbations is presented. The class of nonlinear systems is the product of state variables on three time scales (fast, medium, and slow). Through this paper, the symmetry of mathematical modeling and graphical modeling can be established. A main characteristic of the bond graph is the application of causality to its elements. When an integral causality is assigned to the storage elements that determine the state variables, the dynamic model is obtained. If the storage elements of the fast dynamics have a derivative causality and the storage elements of the medium and slow dynamics an integral causality is assigned, a reduced model is obtained, which consists of a dynamic model for the medium and slow time scales and a stationary model of the fast time scale. By applying derivative causality to the storage elements of the fast and medium dynamics and an integral causality to the storage elements of the slow dynamics, the quasi-steady-state model for the slow dynamics is obtained and stationary models for the fast and medium dynamics are defined. The exact and reduced models of singularly perturbed systems can be interpreted as another symmetry in the development of this paper. Finally, the proposed methodology was applied to a system with three time scales in a bond graph approach, and simulation results are shown in order to indicate the effectiveness of the proposed methodology.

Dynamic characteristics of proton exchange membrane fuel cell on a multiple time scale

The current research on the dynamic performance of the proton exchange fuel cell is mostly aimed at the influence of operating parameters on the system, but does not involve with the dynamic characteristics of the cell on a multiple time scale nor the study of the corresponding multiple time scale model. In order to detect the dynamic changes of the proton exchange membrane fuel cell, the effects of various factors in the system on the output performance on different time scales are investigated. The effective partial pressure of oxygen and hydrogen are obtained by the mass diffusion equation and the ideal gas state equation, and the dynamic model is established according to the law of conservation of energy, the law of thermodynamics, and the electrochemical reaction equation. By setting the load mutations with a large/medium/small time scale dynamic duration of 0.6 s, 165 s, and16 min, respectively, the mechanism with which voltage suddenly changes when the load current changes abruptly is studied. Starting from the long time constant during which the dynamic performance takes effect, the control variable is used to analyze the double-layer charge. The influences of layer effect capacitance <i>C</i>, fuel oxidant delay time constant <i>τ</i><sub>e</sub>, and thermodynamic characteristics (temperature <i>T</i>) on the dynamic performance ( initial values of variables: <i>C</i> = 4 F, <i>τ</i><sub>e</sub> = 80 s, and <i>T</i> = 307.7 K) clarify the action intensities on different time scales. With the help of Matlab/Sumlink platform the simulation results are obtained and the correctness and effectiveness of the built model are verified. The simulation results show that the sudden change in voltage is due to the open circuit voltage and Ohmic polarization resistance, and the Ohmic resistance is dominant (the Ohmic overvoltage change value is 2 V, and the open circuit voltage change is 0.05 V), and the <i>C</i> pair dynamics on a small time scale (ms). The performance plays a leading role. Specifically, <i>τ</i><sub>e</sub> has a greater effect on the dynamic characteristics on a medium time scale (s), and <i>T</i> has a stronger effect on a large time scale (10<sup>2</sup>–10<sup>3</sup> s). Based on the above deduction, a multi-time scale model of the battery is derived. The research provides the reference and theoretical support for subsequent battery energy management, evaluation of dynamic performance, and precise control.

Radionuclide geochemistry: solubility and thermodynamics in an HLW repository

Abstract. Deep geological disposal is the internationally favoured option to isolate high-level nuclear waste (HLW) from the biosphere and to minimise the potential radiological risk for future generations. Potentially contacting aqueous solutions such as groundwater may, however, lead to the corrosion of the solid casks containing the nuclear waste, and the formation of aqueous radionuclide systems in the near-field of the emplacement rooms. As dissolved species, radionuclides can in principle further migrate into the far-field and finally reach the biosphere on medium and long timescales. Like all chemical species, the radionuclides are subject to fundamental (geo)chemical laws. Relevant reactions that control retention and release, and hence, the migration behaviour and fate of radionuclides in a repository, are solubility equilibria, formation of soluble complexes, redox reactions, sorption on and incorporation into mineral surfaces, transport phenomena etc. These processes depend directly on the (geo)chemical boundary conditions, and, consequently, can differ greatly for various host rock systems such as clay rock, rock salt, and crystalline rock. Many of the radionuclides in HLW are heavy metals that are sparingly soluble under various repository-relevant conditions, e.g. actinides, lanthanides, transition metals, so that only partial dissolution (mobilisation) from the solid waste matrices is expected. This underlines the importance of evaluating the radionuclide solubility within a geochemically based safety assessment for repositories as it provides reliable upper-limit concentrations of the mobile, potentially migrating radionuclide fraction in the near-field. In this contribution, we discuss relevant aspects related to the topic radionuclide solubility and thermodynamics in a HLW repository. This includes a summary of recent laboratory studies on the solubility behaviour and speciation of key radionuclides in repository-relevant solutions, which are an important basis for obtaining (geo)chemical information and models, and the corresponding fundamental thermodynamic constants on aqueous radionuclide systems. National and international thermodynamic database projects, where quality-assured thermodynamic data (solubility products, complex formation constants, and ion-interaction parameters) are evaluated and compiled, e.g. the Nuclear Energy Agency Thermochemical Database (http://www.oecd-nea.org, last access: 1 November 2021) or the Thermodynamic Reference Database (http://www.thereda.de, last access: 1 November 2021), are highlighted and the main remaining uncertainties discussed. The experimental information and the quantitative thermodynamic data are applied within a generic case study to demonstrate the impact of different geochemical solution conditions representing different host rock systems considered as HLW repositories in Germany on the solubility and speciation of selected radionuclides.

Assessing the impacts of drought on net primary productivity of global land biomes in different climate zones

Drought is the most widespread event under climate change and is projected to lead to high uncertainties in quantifying the terrestrial carbon exchange. However, considering the complexity of drought quantification and the differences in the physiological responses to drought among different vegetation types, the potential mechanisms of vegetation in response to drought across different climate regions and their responses to drought at varying time scales remain unclear globally. Here, we analyzed the response of vegetation activity to drought at different time scales and determined the time scale dominating the drought-induced vegetation variations, then explored its potential driving factors (temperature, precipitation, potential evapotranspiration, and water balance) under different climatic conditions and vegetation types from 2000 to 2015 using the Standardized Precipitation Evapotranspiration Index (SPEI) and Net Primary Productivity (NPP). Our results indicated that the NPP-SPEI correlation was stronger under arid and semi-arid conditions compared to that in humid and sub-humid zones globally. Vegetation mainly responded to the drought from short to medium time scales and the shortest response time scale was observed for deciduous needle-leaf forests and closed shrublands, which mainly located in semi-arid regions of southeastern Australia, central Africa, and southern Russia. Moreover, grassland and cropland ecosystems were found to be also highly vulnerable to drought across the globe. Analysis of the effects of various meteorological factors on NPP-SPEI correlation and drought timescales showed that water balance was the most predominant factor affecting the response of vegetation to drought. In particular, the increase in water balance significantly reduced the response intensity of vegetation to drought and prolonged the response timescales. Analysis of the effects of various meteorological factors on NPP-SPEI correlation and drought time-scales showed that water balance was the most predominant factor affecting the response of vegetation to drought. In particular, the increase in water balance significantly reduces the response intensity of vegetation to drought and prolongs the response time-scales. Therefore, the identification of the dominant timescales at which drought mostly impact land biomes is projected to assist assessing the stability of terrestrial ecosystem and thus support drought mitigation to reduce land degradation.

Minimal warm inflation with complete medium response

If a homogeneous field evolves within a medium, with the lattergradually picking up a temperature, then the friction felt by thefield depends on how its evolution rate compares with medium timescales. We suggest a framework which permits toincorporate the contributions from all medium time scales. As anexample, we illustrate how warm axion inflation can be described byinputting the retarded pseudoscalarcorrelator of a thermal Yang-Mills plasma.Adopting a semi-realistic model for the latter,and starting the evolution at almost vanishing temperature,we show how the system heats up and then entersthe “weak” or “strong” regime of warm inflation.Previous approximate treatments are scrutinized.

Analyzing the connectedness between crude oil and petroleum products: Evidence from USA

AbstractThis paper investigates the connectedness, in time and frequency domain, between daily returns series of crude oil and petroleum products for the period January 11, 2003 to March 12, 2018. In doing so, we have applied DY (2012) and BK (2018) spillover method. The overall spillover index value obtained from DY (2012) method is 62.29% and from BK method index value fluctuates with frequency. Further empirical evidence shows that the total connectedness, in the time and frequency domain, as measured by a rolling‐window approach, has dynamic and volatile characteristics. Our overall results show that there is a high level of partial contemporaneous relationship between jet fuel, heating oil, US gasoline as well as diesel. Furthermore, results from the wavelet multiple correlations (WMCs) and cross‐correlation show that heating oil acts as a leader for a short time horizon, whereas gasoline at medium and longer time scale. The results from the DY spillover analysis suggest that among the series analyzed heating oil has the highest contribution to others, which is confirmed across frequencies by the BK spillover method (and the Brent contributes least to others at all frequency bands). These findings have important implications for a wide range of market participants, including investors, hedge funds, speculators, as well as for energy policy, with different temporal horizons.

Recharge response and kinematics of an unusual earthflow in Liechtenstein

Understanding landslide behavior over medium and long timescales is crucial for predicting landslide hazard and constructing accurate landscape evolution models. The behavior of landslides in soil that undergo periodic displacements, termed earthflows or compound soil slides, is especially difficult to forecast at these timescales. This is because velocities can increase by orders of magnitude over annual to decadal timescales, due to processes such as changing recharge conditions, erosion of the landslide toe, and retrogression of the landslide head. In this paper, we provide a detailed analysis of the Schlucher landslide, an unusual earthflow that is perched above the village of Malbun, Liechtenstein. This landslide had been displacing by 10 to 20 cm/year until 2015, when displacements on the order of 2 m/year occurred from 2016 to 2018. These large displacements damaged landslide mitigation measures, caused numerous surface deformation features, and threatened the local population downstream of the earthflow. This landslide has an unusually long monitoring record, with accurate displacement and climatic data available since 1983. We analyze this nearly 40-year monitoring time series to estimate recharge from snowmelt and rainfall, and its correlation with displacement. We also analyze recently collected, high-resolution surface and subsurface data in order to understand landslide response to recharge, landslide kinematics through time, and catastrophic failure potential. We find that interannual displacements can be explained with variations in recharge; however, periodic surges with recurrence times of tens of years must be explained by other mechanisms. In particular, recharge into the landslide during the recent acceleration (2016 to 2018) was not anomalously high. Instead, we argue that loss of internal strength is responsible for this recent acceleration period, and that this mechanism should be considered when forecasting the surge potential for certain earthflows and soil slides.

Impact Analysis of Increased Penetration of Variable Speed Constant Frequency Wind Power Generation on Power System Stability

Wind energy has the characteristics of randomness and intermittency. The simulation of the dynamic process on the medium and long-term time scale caused by this is of great significance to the planning and operation of power systems containing wind power. The paper discusses the operating principle of AC-excited variable-speed constant-frequency wind power generation system, analyzes the operating characteristics and control objectives of doubly-fed asynchronous wind generators before and after grid connection, and studies the grid connection of generators based on stator flux-oriented vector control technology Control and tracking control of maximum wind energy. The simulation analysis of the fault disturbance process of the power grid system with variable speed and constant frequency wind turbines, the results verify the correctness of the modeling.

Can habitat suitability estimated from MaxEnt predict colonizations and extinctions?

AbstractAimMaxEnt has been widely used to model species’ geographic distributions as functions of environmental variables and to predict changes in distributions in response to environmental change. Here, we test the predictive ability of MaxEnt models through time by modelling colonizations and extinctions.LocationNorth America.MethodsUsing data for 21 species from the North American Breeding Bird Survey, we first related avian species’ geographic distributions to the spatial variation in environmental conditions. Then, we modelled site‐specific colonizations and extinctions between 1979 and 2009 as functions of MaxEnt‐estimated habitat suitability and neighbourhood occupancy.ResultsWe found that colonization and extinction probabilities were related to spatial variation in habitat suitability, and to neighbourhood occupancy, in the expected directions. However, change in habitat suitability (which is much smaller through time than through space) is a weak predictor of extinction and worse for colonization. This is because a) for most species and most sites, climatic suitability did not change dramatically between 1979 and 2009, and b) the relationship between colonization or extinction probability and change in climatic variables is very weak (r2 = 0.02). Most colonizations and extinctions are apparently unrelated to climate change.Main conclusionsMaxEnt models apparently capture a real effect of habitat suitability on North American bird species’ distributions, but over short and medium time scales, occupancy of neighbouring sites by conspecifics predicts changes in occupancy as well as, or better than changes in climatic habitat suitability, as characterized by MaxEnt. One would not expect species’ distributions to track climate change closely. Prediction of species’ responses to climate change should 1) recognize that the process of colonization and extinction are not equally well predicted by species distribution models and 2) account for the spatial structure of species’ distributions.

Reconstruction of the Interannual to Millennial Scale Patterns of the Global Surface Temperature

Climate changes are due to anthropogenic factors, volcano eruptions and the natural variability of the Earth’s system. Herein the natural variability of the global surface temperature is modeled using a set of harmonics spanning from the inter-annual to the millennial scales. The model is supported by the following considerations: (1) power spectrum evaluations show 11 spectral peaks (from the sub-decadal to the multi-decadal scales) above the 99% confidence level of the known temperature uncertainty; (2) spectral coherence analysis between the independent global surface temperature periods 1861–1937 and 1937–2013 highlights at least eight common frequencies between 2- and 20-year periods; (3) paleoclimatic temperature reconstructions during the Holocene present secular to millennial oscillations. The millennial oscillation was responsible for the cooling observed from the Medieval Warm Period (900–1400) to the Little Ice Age (1400–1800) and, on average, could have caused about 50% of the warming observed since 1850. The finding implies an equilibrium climate sensitivity of 1.0–2.3 °C for CO2 doubling likely centered around 1.5 °C. This low sensitivity to radiative forcing agrees with the conclusions of recent studies. Semi-empirical models since 1000 A.D. are developed using 13 identified harmonics (representing the natural variability of the climate system) and a climatic function derived from the Coupled Model Intercomparison Project 5 (CMIP5) model ensemble mean simulation (representing the mean greenhouse gas—GHG, aerosol, and volcano temperature contributions) scaled under the assumption of an equilibrium climate sensitivity of 1.5 °C. The harmonic model is evaluated using temperature data from 1850 to 2013 to test its ability to predict the major temperature patterns observed in the record from 2014 to 2020. In the short, medium, and long time scales the semi-empirical models predict: (1) temperature maxima in 2015–2016 and 2020, which is confirmed by the 2014–2020 global temperature record; (2) a relatively steady global temperature from 2000 to 2030–2040; (3) a 2000–2100 mean projected global warming of about 1 °C. The semi-empirical model reconstructs accurately the historical surface temperature record since 1850 and hindcasts mean surface temperature proxy reconstructions since the medieval period better than the model simulation that is unable to simulate the Medieval Warm Period.

Tracking the recent dynamics of Mt. Vesuvius from joint investigations of ground deformation, seismicity and geofluid circulation

We reconstruct the composite dynamics of Mt. Vesuvius volcano in the period 2012–2019 from the study of ground deformation, seismicity, and geofluid (groundwater and fumarolic fluids) circulation and recognize complex spatio-temporal variations in these observables at medium (years) and short (months) time-scales. We interpret the observed patterns as the combined effect of structural changes affecting the volcanic edifice and variations of the dynamics of the hydrothermal system. In particular, we identify a change in the activity state of Mt. Vesuvius. After the activity reached minimum levels in 2014, the centroid of the surface manifestations migrated towards the SE. Episodic variations of co-seismic and aseismic deformation and fluid release, if analysed separately, would likely have been interpreted as pseudo-random oscillations of the background geophysical and geochemical signals. When organised in a comprehensive, multiparametric fashion, they shed light on the evolution of the volcano in 4D (x,y,z, time) space. These inferences play a crucial role in the formulation of civil protection scenarios for Mt. Vesuvius, a high risk, densely urbanized volcanic area which has never experienced unrest episodes in the modern era of instrumental volcanology.

Inertia and Damping Analysis of Grid-Tied Photovoltaic Power Generation System With DC Voltage Droop Control

Photovoltaic power generation relies on power electronics and therefore does not have natural inertia and damping characteristics. In order to make the capacitance of the medium time scale participate in the grid frequency response without adding additional equipment, this paper takes the grid-connected photovoltaic power generation system based on DC voltage droop control as the research object, and establishes the static synchronous generator (SSG) model of the system. The model is used to analyze the main parameters affecting the inertia, damping and synchronization characteristics of the system and their influence laws. The research results show that the energy storage effect of the capacitor on the medium time scale can also make the system exhibit certain inertia characteristics. From the point of view of control parameters, as the droop coefficient D <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> decreases, the inertia characteristic exhibited by the system is stronger. The larger the DC voltage outer loop proportional coefficient K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> is, the stronger the damping effect of the system is. The larger the DC voltage outer loop integral coefficient K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , the stronger the synchronization capability of the system. In addition, the MATLAB/Simulink simulation platform is used to verify the correctness of the theoretical analysis results.

Sensitivity of surface albedo derived from METEOSAT data to drought episodes in a semi-arid region (M’Sila, north center of Algeria)

Drought is a natural phenomenon that affects ecological processes, land productivity, and human life. The phenomenon is slow to settle down and its impacts are not instantaneous, requiring an early monitoring of their signs of appearance. In order to track the effect drought on the land surface dynamics by means of surface albedo changes, we intend to exploit the VIS-channel reference image from the METEOSAT satellite data, which is an associated product of the new version of the Infrared Difference Dust Index (IDDI). The surface albedo is retrieved from the calibrated VIS-channel reference radiance, atmospherically corrected by the radiative transfer code 6S (Second Simulation of a Satellite Signal in the Solar Spectrum). In this study, we inspect the sensitivity of monthly surface albedo to drought events over a semi-arid region (M’Sila, center of northern Algeria) during the period covered by three METEOSAT satellites (5, 6, and 7). Two drought indices, SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index), were calculated at multiple timescales and were correlated with surface albedo over the study region. The results show that the correlation of surface albedo with the two drought indices at the timescale of 1 month (current month) is not necessarily the best indicator of the installation of a drought event. Additionally, we find that the sensitivity of surface albedo to drought indices at a medium timescales class (average of correlation coefficient at 6, 9, and 12 months), is more sensitive to SPEI index (principally 6-month timescale), during the growing season (April to September). It is also more sensitive to SPI index (principally 12-month timescale), during the supplying and charging period of water resources (October to March).

A Multi-Method Approach for Quantification of In- and Exfiltration Rates from the Subterranean Estuary of a High Energy Beach

Accurate SGD (submarine groundwater discharge) mass export calculations require detailed knowledge of the spatial and temporal variability in SGD rates. In coastal aquifers, SGD includes a terrestrial freshwater component as well as a saline component originating from circulating seawater. Representative field measurements of SGD rates are difficult to conduct, because SGD is often patchy, diffuse, and temporally variable, especially under tidal influence and high wave activity. In this study, a combination of lysimeters, seepage meters, temperature sensors, pore water radon, and numerical modeling was used to estimate the volumes of infiltrating seawater and exfiltrating groundwater in the intertidal zone of a mesotidal, high energy beach on Spiekeroog Island, northern Germany. Additionally, a 3D-laser scanner was used over short (days) and medium time scales (months) to determine changes in beach topography. The results showed net water infiltration above mean sea level (MSL) and net exfiltration below MSL. Water exchange rates fluctuated between 0.001 and 0.61 m day−1, showing similar ranges within the multiple method approaches. The beach topography was subject to strong fluctuation caused by waves, currents, wind driven erosion and sedimentation, even over short time scales. A comparison of extrapolated in- and exfiltrating water volumes along a beach transect from the mean high water to mean low water line at different times highlights the variability of total in or outflow. The results show that exchange rates depend on beach topography, which in turn changes significantly over time.

Biochemical indicators drive soil quality in integrated crop–livestock–forestry systems

Integrated crop, livestock, and forestry systems (iCLF) have been widely heralded as a sustainable farming method in comparison to conventional pastures. However, intensive soil use and management modify ecosystem function, particularly biogeochemical cycling. The aim of this study was to determine whether there are changes in soil chemistry or biochemistry after the conversion of pasture into iCLF in the Brazilian Cerrado. Additionally, we compared three iCLF areas initiated 3, 5, and 8 years before this study to test the effect of time since conversion to iCLF (age) on soil chemistry and biochemistry and on microbial carbon (C). Conventional pasture and native Cerrado soils were used as controls. Microbial C and biochemical activity were dependent on the plant cover and age of the iCLF, but soil physicochemical properties were sensitive only to the agroecosystem type. Enzyme activity and microbial C were higher in native Cerrado soils, followed by iCLF and pasture soils, respectively. There was an inverse relationship between iCLF age and microbial C and β-Glucosidase and phenol oxidase activities. The results suggest that the response of the microbial community depends on the soil composition and the iCLF age. Nutrient cycling in iCLF increases with age of the system and varies by management subtype within the iCLF (i.e., forestry or grazing areas). The implementation of iCLF changes soil conditions, which generates a positive response in the microbial community. The adoption of iCLF increases microbial activity and enhances soil quality over short–medium timescales (5 years).

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.

Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring.

The connectivity structure of neuronal networks in cortex is highly dynamic. This ongoing cortical rewiring is assumed to serve important functions for learning and memory. We analyze in this article a model for the self-organization of synaptic inputs onto dendritic branches of pyramidal cells. The model combines a generic stochastic rewiring principle with a simple synaptic plasticity rule that depends on local dendritic activity. In computer simulations, we find that this synaptic rewiring model leads to synaptic clustering, that is, temporally correlated inputs become locally clustered on dendritic branches. This empirical finding is backed up by a theoretical analysis which shows that rewiring in our model favors network configurations with synaptic clustering. We propose that synaptic clustering plays an important role in the organization of computation and memory in cortical circuits: we find that synaptic clustering through the proposed rewiring mechanism can serve as a mechanism to protect memories from subsequent modifications on a medium time scale. Rewiring of synaptic connections onto specific dendritic branches may thus counteract the general problem of catastrophic forgetting in neural networks.

Dynamic evolution of sentiments in Never Let Me Go: Insights from multifractal theory and its implications for literary analysis

Abstract The moods, feelings, and attitudes represented in a novel will resonate in the reader by activating similar sentiments. It is generally accepted that sentiment analysis can capture aspects of such moods, feelings, and attitudes and can be used to summarize a novel’s plot in a story arc. With the availability of a number of algorithms to automatically extract sentiment-based story arcs, new approaches for their utilization becomes pertinent. We propose to use nonlinear adaptive filtering and fractal analysis in order to analyze the narrative coherence and dynamic evolution of a novel. Using Never Let Me Go by Kazuo Ishiguro, the winner of the 2017 Nobel Prize for Literature as an illustrative example, we show that: (1) nonlinear adaptive filtering can extract a story arc that reflects the tragic trend of the novel; (2) the story arc displays persistent dynamics as measured by the Hurst exponent at short and medium timescales; (3) the plot’s dynamic evolution is reflected in the time-varying Hurst exponent. We argue that these findings are indicative of the potential that multifractal theory has for computational narratology and large-scale literary analysis. Specifically that the global Hurst exponent of a story arc is an index of narrative coherence that can identify bland, incoherent, and coherent narratives on a continuous scale. And, further, that the local time-varying Hurst exponent captures variation of a novel’s plot such that the extrema have specific narratological interpretations.

Observed heterogeneities after hydration of MX-80 bentonite under pellet/powder form

Bentonite is considered for engineered barriers in radioactive waste geological repositories due to its low permeability, swelling pressure and radionuclide retention properties. The French concept favors the use of bentonite under granular form - pellets and crushed pellets mix - for an easier building of plugs and seals relatively to bricks. However, this introduces a significant degree of macroscopic initial heterogeneity (at several scales) that is expected to disappear via mass redistribution during resaturation in order to obtain homogeneous hydraulic and mechanical performance. This also may have practical effects on the reliability of results from tests with small volumes of bentonite compatible with the time scales manageable at the laboratory. In this study, isochoric swelling pressure tests at various densities and sample sizes were carried out and evidenced bias mainly due to the size of the cell compared to the size of the pellets, although the average density is equivalent, pointing towards incomplete homogenization. Large-scale swelling pressure tests, however, converged towards values previously measured for more finely grained materials. Local pressure measurements also evidenced some stress heterogeneities that do not seem to disappear at medium time-scales. These stress heterogeneities could be correlated to local density variations of the final state assessed using destructive measurements and X-ray computed tomography.