Visibility Graph Analysis of Reservoir-Triggered Seismicity: The Case of Song Tranh 2 Hydropower,Vietnam

In this study, the visibility graph analysis of seismicity triggered by Song Tranh 2 hydropower (Vietnam) is performed. The relationship between the seismic (the Gutenberg–Richter b-value) and topological (the k–M slope) parameters of seismicity is analysed. Our findings indicate that the relationship between the Gutenberg–Richter b-value and the k–M slope of the investigated seismicity is in agreement with that characterising the tectonic seismicity. The results obtained from analysing the reservoir-triggered seismicity of Song Tranh 2 area could contribute to better characterisation of the relationship between the seismological and topological parameters of seismicity, strengthening the universal character of the relationship between the b-value and the k–M slope.     

Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021–2022

Unemployment has risen as the economy has shrunk. The coronavirus crisis has affected many sectors in Romania, some companies diminishing or even ceasing their activity. Making forecasts of the unemployment rate has a fundamental impact and importance on future social policy strategies. The aim of the paper is to comparatively analyze the forecast performances of different univariate time series methods with the purpose of providing future predictions of unemployment rate. In order to do that, several forecasting models (seasonal model autoregressive integrated moving average (SARIMA), self-exciting threshold autoregressive (SETAR), Holt–Winters, ETS (error, trend, seasonal), and NNAR (neural network autoregression)) have been applied, and their forecast performances have been evaluated on both the in-sample data covering the period January 2000–December 2017 used for the model identification and estimation and the out-of-sample data covering the last three years, 2018–2020. The forecast of unemployment rate relies on the next two years, 2021–2022. Based on the in-sample forecast assessment of different methods, the forecast measures root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percent error (MAPE) suggested that the multiplicative Holt–Winters model outperforms the other models. For the out-of-sample forecasting performance of models, RMSE and MAE values revealed that the NNAR model has better forecasting performance, while according to MAPE, the SARIMA model registers higher forecast accuracy. The empirical results of the Diebold–Mariano test at one forecast horizon for out-of-sample methods revealed differences in the forecasting performance between SARIMA and NNAR, of which the best model of modeling and forecasting unemployment rate was considered to be the NNAR model.     

Temporal Variation of b Value with Statistical Test in Wenchuan Area,China Prior to the 2008 Wenchuan Earthquake

The Gutenberg–Richter b value describes the ratio between large and small events. A number of studies have suggested that the b value decreases before large earthquakes. In this study, we investigate the temporal variation of the b value of an area along the main rupture zone of the 2008 Wenchuan earthquake (M8.0) prior to the great event. Before estimating b values, we tested the earthquake catalog to make sure that we use the reliable frequency–magnitude distribution by the calculation of MC (completeness of magnitude). We define parameter P (ΔAIC ≧ 2) values to examine the significance level of b-value changes in the temporal variation by combining a boostrap method with Akaike’s Information Criterion (AIC). The b value in the main rupture zone shows a long-term decrease trend. We then focus on a smaller area where the initial rupture starts. The results show that b values significantly changed about 3 months before the 2008 Wenchuan earthquake in the initial rupture area, indicating that the b value has a potential capability to monitor and detect precursory phenomena of great earthquakes.     

A plausible explanation of the b-value in the Gutenberg-Richter law from first Principles

It is explained, from first Principles, why in the Gutenberg-Richter law (stating that the cumulative number of earthquakes N(>M) with magnitude greater than M is given by N(>M) ~ 10^−bM) the so called b-value is usually found to be around unity varying only slightly from region to region. The explanation is achieved just by applying the analysis in the natural time domain, without using any adjustable parameter.     

The Cross-Sectional Intrinsic Entropy—A Comprehensive Stock Market Volatility Estimator

To take into account the temporal dimension of uncertainty in stock markets, this paper introduces a cross-sectional estimation of stock market volatility based on the intrinsic entropy model. The proposed cross-sectional intrinsic entropy (CSIE) is defined and computed as a daily volatility estimate for the entire market, grounded on the daily traded prices—open, high, low, and close prices (OHLC)—along with the daily traded volume for all symbols listed on The New York Stock Exchange (NYSE) and The National Association of Securities Dealers Automated Quotations (NASDAQ). We perform a comparative analysis between the time series obtained from the CSIE and the historical volatility as provided by the estimators: close-to-close, Parkinson, Garman–Klass, Rogers–Satchell, Yang–Zhang, and intrinsic entropy (IE), defined and computed from historical OHLC daily prices of the Standard & Poor’s 500 index (S&P500), Dow Jones Industrial Average (DJIA), and the NASDAQ Composite index, respectively, for various time intervals. Our study uses an approximate 6000-day reference point, starting 1 January 2001, until 23 January 2022, for both the NYSE and the NASDAQ. We found that the CSIE market volatility estimator is consistently at least 10 times more sensitive to market changes, compared to the volatility estimate captured through the market indices. Furthermore, beta values confirm a consistently lower volatility risk for market indices overall, between 50% and 90% lower, compared to the volatility risk of the entire market in various time intervals and rolling windows.     

Precursory phenomena associated with large avalanches in the long-range connective sandpile (LRCS) model

Reduction in b-values before a large earthquake is a very popular topic for discussion. This study proposes an alternative sandpile model being able to demonstrate reduction in scaling exponents before large events through adaptable long-range connections. The distant connection between two separated cells was introduced in the sandpile model. We found that our modified long-range connective sandpile (LRCS) system repeatedly approaches and retreats from a critical state. When a large avalanche occurs in the LRCS model, accumulated energy dramatically dissipates and the system simultaneously retreats from criticality. The system quickly approaches the critical state accompanied by the increase in the slopes of the power-law frequency-size distributions of events. Afterwards, and most interestingly, the power-law slope declines before the next large event. The precursory b-value reduction before large earthquakes observed from earthquake catalogues closely mimics the evolution in power-law slopes for the frequency-size distributions of events derived in the LRCS models. Our paper, thus, provides a new explanation for declined b-values before large earthquakes.     

Analysis of the spatial and temporal distributions between successive earthquakes: Nonextensive statistical mechanics viewpoint

The spatial and temporal distributions between successive earthquakes are treated in the framework of nonextensive statistical mechanics. We find temporal distributions exhibit the power law behavior; q-exponential with q>1. It means the earthquakes are strongly correlated in time. The spatial distributions obey the q-exponential form with q<1. We also examine the dependence of the q exponent on magnitude range, covering period, time interval and size of the region where data are gathered. The conjecture of Abe et al. [S. Abe, N. Suzuki, Physica A 350 (2005) 588] has been examined for different categories of data. The results show a strange relation between q values of the spatial and temporal distributions.     

EFFECT OF SEATING ON EXPOSURES TO WHOLE-BODY VIBRATION IN VEHICLES

The vibration isolation efficiency of seating has been evaluated in 100 work vehicles in 14 categories (cars, vans, lift trucks, lorries, tractors, buses, dumpers, excavators, helicopters, armoured vehicles, mobile cranes, grass rollers, mowers and milk floats). Seat isolation efficiency, expressed by the SEAT value, was determined for all seats (67 conventional seats and 33 suspension seats) from the vertical acceleration measured on the floors and on the seats of the vehicles.For most categories of vehicle, the average SEAT value was less than 100%, indicating that the average seat provided some attenuation of vibration. However, there were large variations in SEAT values between vehicles within categories. Two alternative vibration frequency weightings (W_b from BS 6841, 1987; W_k from ISO 2631, 1997) yielded SEAT values that differed by less than 6%. Overall, the SEAT values determined by two alternative methods (the ratio of r.m.s. values and the ratio of vibration dose values) differed by less than 4·5% when using weighting W_b, although larger differences may be expected in some situations. The median SEAT value for the suspension seats was 84·6%; the median SEAT value for the conventional seats was 86·9% (based on weighting W_b and the ratio of r.m.s. values).Predicted SEAT values were obtained assuming that each seat could be interchanged between vehicles without altering its transmissibility. The calculations suggest that 94% of the vehicles investigated might benefit from changing the current seat to a seat from one of the other vehicles investigated. Although the predictions are based on assumptions that will not always apply, it is concluded that the severity of whole-body vibration exposures in many work environments can be lessened by improvements to seating dynamics.     

Colligative Properties of Solutions: II. Vanishing Concentrations

We continue our study of colligative properties of solutions initiated in ref. 1. We focus on the situations where, in a system of linear size L, the concentration and the chemical potential scale like c=ξ/L and h=b/L, respectively. We find that there exists a critical value ξt such that no phase separation occurs for ξ≤ξt while, for ξ>ξt, the two phases of the solvent coexist for an interval of values of b. Moreover, phase separation begins abruptly in the sense that a macroscopic fraction of the system suddenly freezes (or melts) forming a crystal (or droplet) of the complementary phase when b reaches a critical value. For certain values of system parameters, under “frozen” boundary conditions, phase separation also ends abruptly in the sense that the equilibrium droplet grows continuously with increasing b and then suddenly jumps in size to subsume the entire system. Our findings indicate that the onset of freezing-point depression is in fact a surface phenomenon.     

Evaluation of noncirrhotic hepatic parenchyma with and without significant portal vein stenosis using diffusion-weighted echo-planar MR on the basis of multiple-perfusion-components theory

To determine whether diffusion-weighted echo-planar MR images are sensitive to liver perfusion difference.Noncirrhotic livers of 71 patients (43 males, 28 females; age range, 22-87 years; mean, 61 years) without (n=51) and with (n=20) significant (>70%) portal vein stenosis (accompanying proximal hepatic arterial stenosis and/or biliary tract obstruction in 10) by tumors were examined with diffusion-weighted echo-planar sequences (modified for b factors of 1, 28, 66, 288 and 600 s/mm²). On the basis of multiple-perfusion-components theory, i.e., assuming logarithm of signal intensity for liver perfusion is linearly attenuated versus logarithm of a smaller b factor, we defined the slope of the line as the perfusion-related D′ value. The D′ values of these livers were calculated from images with b factors of 1, 28, and 66 s/mm². The livers' apparent diffusion coefficient values for diffusion (ADC_d values) were calculated from images with b factors of 288 and 600 s/mm².The livers with significant portal vein stenosis had statistically lower mean D′ values than the livers without portal vein stenosis (P<.001 on the Mann-Whitney U test). However, there was no significant difference in ADC_d values between these liver types (P>.05).The D′ value calculated from diffusion-weighted echo-planar sequences with plural smaller b factors may be sensitive to liver perfusion difference.     

Meson exchange and the theory of finite fermi systems

The spin-dependent parameters g₀ and g'₀ in Migdal's theory of finite Fermi systems are studied. Assuming their values to be such as to reproduce the M1 states in ²⁰⁸Pb at 7 and 8 MeV, the origin of these (large) values in meson-exchange contributions to the nucleon-nucleon force is studied. Pion exchange contributes little, because of cancellation between matrix elements from the spin-spin and tensor components. The largest, nearly equal, contributions to g₀ and g'₀ come from p-meson exchange. In order to explain the large values needed for g₀ and g'₀, the tensor coupling of the ρ-meson must be substantially larger than the effective ones found in current phenomenological potentials, such as the Reid soft-core and Hamada-Johnston ones. The large value of the coupling needed follows from work analyzing nucleon form factors.     

Sinusoidal Phase-Modulating Superluminescent Diode Interferometer with Fabry-Perot Etalone for Step-Profile Measurement

In this paper we use a superluminescent diode (SLD) as the light source of an interferometer and extract a narrow spectrum from a wide spectrum of the SLD with a Fabry-Perot Etalone (FPE). By varying sinusoidally the distance between the two mirrors of FPE, the central wavelength of the narrow spectrum is scanned sinusoidally. The distance between the mirrors is exactly set by a feedback control system, and sinusoidal phase-modulated SLD light that has a large scanning width of about 10 nm can be obtained with high stability and spatial uniformity. The phase of the interference signal has two different components. One is amplitude Z_b of sinusoidal phase modulation, which is proportional to the optical path difference (OPD) and the scanning width. The other is conventional phase α, which provides a fractional value of the OPD in the range of the wavelength. By combining the two values of the OPD obtained from Z_b and α, an exact OPD larger than the wavelength can be measure with ment accuracy in α. Characteristics of the interferometer are made clearly through step-profile measurements.     

Soil radon concentration and effective stress variation at Mt. Etna (Sicily) in the period January 2003–April 2005

In this study we discuss the relationship between the in-soil radon concentration and the effective stress variation at Mt. Etna volcano in the period January 2003–April 2005. The acquired radon concentration trend was compared with the one obtained by the b-value variation analysis in the frequency–magnitude relationship for earthquakes that occurred at Mt. Etna volcano (Sicily) during the investigation period. The b-value calculated using both the maximum likelihood and the least square methods shows a similar trend and, in particular, an increase starting a few months before the 7th September 2004 eruption and a decrease during the following 9 months. A similar trend was recorded during 2003 when a recharging magma phase of the volcano occurred. Results obtained by studying the b-value trend and the comparison with in-soil radon concentration are also discussed.     

Analyzing Transverse Momentum Spectra of Pions,Kaons and Protons in p–p,p–A and A–A Collisions via the Blast-Wave Model with Fluctuations

The transverse momentum spectra of different types of particles, π±, K±, p and p¯, produced at mid-(pseudo)rapidity in different centrality lead–lead (Pb–Pb) collisions at 2.76 TeV; proton–lead (p–Pb) collisions at 5.02 TeV; xenon–xenon (Xe–Xe) collisions at 5.44 TeV; and proton–proton (p–p) collisions at 0.9, 2.76, 5.02, 7 and 13 TeV, were analyzed by the blast-wave model with fluctuations. With the experimental data measured by the ALICE and CMS Collaborations at the Large Hadron Collider (LHC), the kinetic freeze-out temperature, transverse flow velocity and proper time were extracted from fitting the transverse momentum spectra. In nucleus–nucleus (A–A) and proton–nucleus (p–A) collisions, the three parameters decrease with the decrease of event centrality from central to peripheral, indicating higher degrees of excitation, quicker expansion velocities and longer evolution times for central collisions. In p–p collisions, the kinetic freeze-out temperature is nearly invariant with the increase of energy, though the transverse flow velocity and proper time increase slightly, in the considered energy range.     

A Spatial–Temporal Causal Convolution Network Framework for Accurate and Fine-Grained PM2.5 Concentration Prediction

Accurate and fine-grained prediction of PM_2.5 concentration is of great significance for air quality control and human physical and mental health. Traditional approaches, such as time series, recurrent neural networks (RNNs) or graph convolutional networks (GCNs), cannot effectively integrate spatial–temporal and meteorological factors and manage dynamic edge relationships among scattered monitoring stations. In this paper, a spatial–temporal causal convolution network framework, ST-CCN-PM_2.5, is proposed. Both the spatial effects of multi-source air pollutants and meteorological factors are considered via spatial attention mechanism. Time-dependent features in causal convolution networks are extracted by stacked dilated convolution and time attention. All the hyper-parameters in ST-CCN-PM_2.5 are tuned by Bayesian optimization. Haikou air monitoring station data are employed with a series of baselines (AR, MA, ARMA, ANN, SVR, GRU, LSTM and ST-GCN). Final results include the following points: (1) For a single station, the RMSE, MAE and R² values of ST-CCN-PM_2.5 decreased by 27.05%, 10.38% and 3.56% on average, respectively. (2) For all stations, ST-CCN-PM_2.5 achieve the best performance in win–tie–loss experiments. The numbers of winning stations are 68, 63, and 64 out of 95 stations in RMSE (MSE), MAE, and R², respectively. In addition, the mean MSE, RMSE and MAE of ST-CCN-PM_2.5 are 4.94, 2.17 and 1.31, respectively, and the R² value is 0.92. (3) Shapley analysis shows wind speed is the most influencing factor in fine-grained PM_2.5 concentration prediction. The effects of CO and temperature on PM_2.5 prediction are moderately significant. Friedman test under different resampling further confirms the advantage of ST-CCN-PM_2.5. The ST-CCN-PM_2.5 provides a promising direction for fine-grained PM_2.5 prediction.     

Effects of Match Location,Quality of Opposition and Match Outcome on Match Running Performance in a Portuguese Professional Football Team

The aim of this study was to analyze the effects of match location, quality of opposition and match outcome on match running performance according to playing position in a Portuguese professional football team. Twenty-three male professional football players were monitored from eighteen Portuguese Football League matches during the 2019–2020 season. Global positioning system technology (GPS) was used to collect time-motion data. The match running performance was obtained from five playing positions: central defenders (CD), fullbacks (FB), central midfielders (CM), wide midfielders (WM) and forwards (FW). Match running performance was analyzed within specific position and contextual factors using one-way analysis of variance (ANOVA) for repeated measures, standardized (Cohen) differences and smallest worthwhile change. CM and WM players covered significantly greater total distance (F = 15.45, p = 0.000, η² = 0.334) and average speed (F = 12.79, p < 0.001, η² = 0.294). WM and FB players covered higher distances at high-speed running (F = 16.93, p = 0.000, η² = 0.355) and sprinting (F = 13.49; p < 0.001, η² = 0.305). WM players covered the highest number of accelerations (F = 4.69, p < 0.001, η² = 0.132) and decelerations (F = 12.21, p < 0.001, η² = 0.284). The match running performance was influenced by match location (d = 0.06–2.04; CI: −0.42–2.31; SWC = 0.01–1.10), quality of opposition (d = 0.13–2.14; CI: –0.02–2.60; SWC = 0.01–1.55) and match outcome (d = 0.01–2.49; CI: −0.01–2.31; SWC = 0.01–0.35). Contextual factors influenced the match running performance with differential effects between playing positions. This study provides the first report about the contextual influence on match running performance in a Portuguese professional football team. Future research should also integrate tactical and technical key indicators when analyzing the match-related contextual influence on match running performance.     

Effects of Tau and Sampling Frequency on the Regularity Analysis of ECG and EEG Signals Using ApEn and SampEn Entropy Estimators

Electrocardiography (ECG) and electroencephalography (EEG) signals provide clinical information relevant to determine a patient’s health status. The nonlinear analysis of ECG and EEG signals allows for discovering characteristics that could not be found with traditional methods based on amplitude and frequency. Approximate entropy (ApEn) and sampling entropy (SampEn) are nonlinear data analysis algorithms that measure the data’s regularity, and these are used to classify different electrophysiological signals as normal or pathological. Entropy calculation requires setting the parameters r (tolerance threshold), m (immersion dimension), and τ (time delay), with the last one being related to how the time series is downsampled. In this study, we showed the dependence of ApEn and SampEn on different values of τ, for ECG and EEG signals with different sampling frequencies (F_s), extracted from a digital repository. We considered four values of F_s (128, 256, 384, and 512 Hz for the ECG signals, and 160, 320, 480, and 640 Hz for the EEG signals) and five values of τ (from 1 to 5). We performed parametric and nonparametric statistical tests to confirm that the groups of normal and pathological ECG and EEG signals were significantly different (p < 0.05) for each F and τ value. The separation between the entropy values of regular and irregular signals was variable, demonstrating the dependence of ApEn and SampEn with F_s and τ. For ECG signals, the separation between the conditions was more robust when using SampEn, the lowest value of F_s, and τ larger than 1. For EEG signals, the separation between the conditions was more robust when using SampEn with large values of F_s and τ larger than 1. Therefore, adjusting τ may be convenient for signals that were acquired with different F_s to ensure a reliable clinical classification. Furthermore, it is useful to set τ to values larger than 1 to reduce the computational cost.     

Numerical Study of Entropy Generation in Fully Developed Turbulent Circular Tube Flow Using an Elliptic Blending Turbulence Model

As computational fluid dynamics (CFD) advances, entropy generation minimization based on CFD becomes attractive for optimizing complex heat-transfer systems. This optimization depends on the accuracy of CFD results, such that accurate turbulence models, such as elliptic relaxation or elliptic blending turbulence models, become important. The performance of a previously developed elliptic blending turbulence model (the SST k–ω–φ–α model) to predict the rate of entropy generation in the fully developed turbulent circular tube flow with constant heat flux was studied to provide some guidelines for using this class of turbulence model to calculate entropy generation in complex systems. The flow and temperature fields were simulated by using a CFD package, and then the rate of entropy generation was calculated in post-processing. The analytical correlations and results of two popular turbulence models (the realizable k–ε and the shear stress transport (SST) k–ω models) were used as references to demonstrate the accuracy of the SST k–ω–φ–α model. The findings indicate that the turbulent Prandtl number (Pr_t) influences the entropy generation rate due to heat-transfer irreversibility. Pr_t = 0.85 produces the best results for the SST k–ω–φ–α model. For the realizable k–ε and SST k–ω models, Pr_t = 0.85 and Pr_t = 0.92 produce the best results, respectively. For the realizable k–ε and the SST k–ω models, the two methods used to predict the rate of entropy generation due to friction irreversibility produce the same results. However, for the SST k–ω–φ–α model, the rates of entropy generation due to friction irreversibility predicted by the two methods are different. The difference at a Reynolds number of 100,000 is about 14%. The method that incorporates the effective turbulent viscosity should be used to predict the rate of entropy generation due to friction irreversibility for the SST k–ω–φ–α model. Furthermore, when the temperature in the flow field changes dramatically, the temperature-dependent fluid properties must be considered.     

The exchange bias and coercivity of FM/AFM films: Monte Carlo simulation

The exchange bias (H_E) and coercivity (H_C) of the ferromagnet/antiferromagnet (FM/AFM) films have been simulated with Monte Carlo method. The simulated results indicate that, the value of H_E decreases with increasing temperature, and the values of H_E and the blocking temperature T_b at which H_E=0 reduce evidently with decreasing absolute value of interlayer exchange coupling JI. It also is found that for the large absolute values of JI, the maximum in H_C occurs very close to T_b. At the same time, it is observed that the diluted ratio of FM at FM/AFM interface influences clearly the value of H_E. The simulated results are consistent with the experimental facts. The maximum behaviour in the H_C−T curves has been explained by the interplay of the softening of some fraction of the spins in the AFM layer near T_N′ and the disorder of the spins in FM layer near Curie temperature T_C.     

When,why, and how does like like like?: Electrostatic attraction between similarly charged species

In the Derjaguin-Landau-Verwey-Overbeek (DLVO) framework of the past 60 years, colloidal interaction between similarly charged particles has been claimed to be simply repulsive, and an attraction such as the van der Waals interaction is attached to the Coulombic repulsion. Statistical-thermodynamic considerations show that the electrostatic Helmholtz free energy ΔF^el is generally not equal to the electrostatic Gibbs free energy ΔG^el for simple ionic solutions, and the difference ΔG^el–ΔF^el (corresponding to the electrostatic osmotic pressure p^el) becomes larger with increasing charge number. Thus, it is expected that ΔG^el–ΔF^el be large for highly charged macroions. In the DLVO framework, however, ΔG^el = ΔF^el was postulated. Sogami showed that a mean field approach reproduced repulsion at the level of ΔF^el but resulted in (repulsion and) attraction at the level of ΔG^el. Overbeek’s critique of Sogami theory is shown to be in error. If this criticism were correct, then not only the Sogami theory but also the Debye-Hückel theory would be wrong. The attraction is thus confirmed to exist not only for multi-valent but also mono-valent counterions.