Periodic Behavior Research Articles

STATISTICAL INFERENCE ON SINE-EXPONENTIAL DISTRIBUTION PARAMETER

The Sine-Exponential (Sine-E) distribution is a probability distribution that combines the periodic behavior of the sine function with the decay characteristic of the exponential function. This study addresses the problem of identifying the most accurate and reliable estimation method for the parameter of the Sine-E distribution. The objective is to evaluate various parameter estimation techniques, including Maximum Likelihood Estimation (MLE), Least Squares Estimation (LSE), Weighted Least Squares Estimation (WLSE), Maximum Product of Spacing Estimation (MPSE), Cramer-von-Mises Estimation (CVME), and Anderson-Darling Estimation (ADE), using Mean Square Error (MSE) as the criterion for determining the technique with the minimum error. The study’s findings reveal that as sample size increases, the parameter estimates for all techniques converge to the true parameter value, with decreases in bias, MSE, and mean relative estimates. Among the techniques evaluated, the MPSE method consistently provides estimates closest to the true parameter value and exhibits the least bias and lowest MSE across small, moderate, and large sample sizes, making it the best estimator for the Sine-E distribution.

Turing instability induced by crossing curves in network-organized system

Several factors significantly contribute to the onset of infectious diseases, including direct and indirect transmissions and their respective impacts on incubation periods. The intricate interplay of these factors within social networks remains a puzzle yet to be unraveled. In this study, we conduct a stability analysis within a network-organized SIR model incorporating dual delays to explore the influence of direct and indirect incubation periods on disease spread. Additionally, we investigate how compound networks affect the critical incubation period. Our findings reveal several vital insights. First, by examining crossing curves and the dispersion equation, we establish the conditions for Turing instability and delineate the stable regions associated with dual delays. Second, we ascertain that the critical incubation value exhibits an inverse relationship with a network’s eigenvalues, indicating that the Laplacian matrix does not solely dictate periodic behavior in the context of delays. Furthermore, our study elucidates the impact of delays and networks on pattern formation, revealing distinct pattern types across different regions. Specifically, our observations suggest that effectively curtailing the spread of infectious diseases during an outbreak is more achievable when the incubation period for indirect contact is shorter and for direct contact is longer. Namely, our network framework enables regulation of the optimal combination of (τ1,τ2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$(\ au _{1},\ au _{2})$\\end{document} to mitigate the risk of infectious diseases. In summary, our results offer valuable theoretical insights that can inform strategies for preventing and managing infectious diseases.

Transient frequency preference responses in cell signaling systems

Ligand–receptor systems, covalent modification cycles, and transcriptional networks are the fundamental components of cell signaling and gene expression systems. While their behavior in reaching a steady-state regime under step-like stimulation is well understood, their response under repetitive stimulation, particularly at early time stages is poorly characterized. Yet, early-stage responses to external inputs are arguably as informative as late-stage ones. In simple systems, a periodic stimulation elicits an initial transient response, followed by periodic behavior. Transient responses are relevant when the stimulation has a limited time span, or when the stimulated component’s timescale is slow as compared to the timescales of the downstream processes, in which case the latter processes may be capturing only those transients. In this study, we analyze the frequency response of simple motifs at different time stages. We use dose-conserved pulsatile input signals and consider different metrics versus frequency curves. We show that in ligand–receptor systems, there is a frequency preference response in some specific metrics during the transient stages, which is not present in the periodic regime. We suggest this is a general system-level mechanism that cells may use to filter input signals that have consequences for higher order circuits. In addition, we evaluate how the described behavior in isolated motifs is reflected in similar types of responses in cascades and pathways of which they are a part. Our studies suggest that transient frequency preferences are important dynamic features of cell signaling and gene expression systems, which have been overlooked.

Firing patterns and fast–slow dynamics in an N-type LAM-based FitzHugh–Nagumo circuit

The diversity of firing patterns and their bifurcation mechanisms of a neuron circuit are crucial for exploiting bionic applications. This paper constructs an N-type locally active memristor (LAM)-based FitzHugh–Nagumo (FHN) circuit by replacing the tunnel-diode in the original FHN circuit. Numerical simulations and hardware measurements reveal that the N-type LAM-based FHN circuit can reproduce rich neuromorphic firing patterns of quasi-periodic/periodic bursting behaviors and chaotic/periodic spiking behaviors. The bursting and spiking behaviors are triggered by a low-frequency stimulus and a high-frequency one, respectively. Besides, the fold and Hopf bifurcation sets are depicted. Then, the bifurcation mechanisms for the quasi-periodic and periodic bursting behaviors via Hopf/Hopf and Hopf/fold bifurcations are theoretically deduced by time-domain waveform and equilibrium trajectory. The numerical results and hardware experiments exhibit the effectiveness of the proposed memristive FHN circuit in reproducing abundant firing patterns of bursting and spiking behaviors.

Electrified Nano-Gaps Under AC Field: A Molecular Dynamics Study

Solid-Liquid Interfaces (SLIs) hold immense significance in various areas such as materials science, chemistry, physics, biology and medicine [1]. Many studies aim to decipher the molecular details of SLIs through analytical, computational or experimental methods [2]-[3], each optimized for different aspects of SLIs. Analytical methods are mainly based on the mean field approximation and work best for dilute solutions. Computational methods are bound by their maximum accessible time and length scales, while the limitation of experimental approach tend to lie in minimum values accessible of these scales. The concomitant deployment of both the approaches is a powerful tool in studying SLIs.In the current study both the computational and experimental tools are employed to study the interface of silica with aqueous saline solutions under electric fields. Molecular Dynamics (MD) simulation are utilized to investigate the relative response of the ions and waters exposed to an external AC field in a nanoscale silica-elecrolyte-gold system. Complementary experimental measurements are conducted with atomic force microscopy (AFM) which measures the dielectric force exerted on the nanoscale AFM probe. The impact of external factors such as salt concentration, AC voltage frequency and the system size is systematically investigated.Simulations reveal both the transient and stable response of water and ions as the main component of the system to the AC field. In the transient response, the water electric dipole increases monotonically with the voltage at the first cycle while it takes longer for ions to react to the field, limited by their diffusion time. When the ionic response becomes large enough to screen the field, the dipole moment of water molecules decreases and lead the phase of the applied field. The lag in the ionic response is owing to the time required for the ionic diffusion, while the lead in the water response is due to ionic lag.To obtain the stable response through MD simulation, Fourier transform was deployed with the results showing that electric dipole of ions and water have a periodic behavior with a frequency similar to the AC field and waters in lead and ions in lag. The dipole-voltage plots for ions and waters depicted an energy transfer between water and ions in each cycle. Decreasing the frequency to 10MHz, no energy exchange was observed concomitant to the removal of water lead. Besides, in the frequency range of 100MHz-200MHz in which the water phase lead reaches its maximum value, there is also a maximum in the energy exchange. Thus, there is a direct relation between the water-ion energy exchange and lead in the water response.The stable response is affected by various factors including the separation distance between the surfaces, the ionic concentration and the AC frequency. The MD observations of a decrease in the water lead and ionic lag with reducing the electrolyte gap could explain AFM measurements where the dielectric force appears to decrease for small gaps, a counter-intuitive result if bulk electrolyte properties are assumed. The simulation results also show that the sum of the electric dipole of water and ions is always in phase with the applied voltage implying that the field is totally screened by the combination of both of them. To provide the same amount of screening in larger separation distance the electric dipole of ions has to increase to counteract its larger lag which is observed in the ionic dipole values. As the ionic dipole despite water molecules are caused by translational entropy, larger ionic dipole translates to larger forces which is observed in the AFM experiments.[1] Taketoshi et al. Japanese Journal of Applied Physics (2021).[2] T. Fukuma and R. Garcia, ACS nano (2018).[3] J.M. Andanson and A. Baiker, Chemical Society Reviews (2010).

Ultrasonic Analysis for Monitoring Li-Ion Batteries

To seek for increasing accuracy in LIBs monitoring a new trend is to rely on data indicative of material properties whose variations are induced by Li ions intercalation and deintercalation. A wider variety of information can be achieved if data are referred to a specific layer of the battery. Since ultrasounds propagate at different speed according to materials properties and are reflected every time they hit an interface, ultrasonic analysis (UA) has the potential to improve the quality of LIB monitoring providing in operando and through thickness information.In this work NMC-graphite LIBs are cycled and monitored in operando via UA in pulse-echo and through-thickness modes with a temporal resolution of 7 ns (which to the best of our knowledge is the highest ever tested) and a 5 MHz frequency. First, the effect of (i) temperature and (ii) C-rate on the waveform evolution was investigated: (i) a 100% charged battery was kept at rest in a thermal chamber at fixed temperatures varying between 10 and 50°C, the ultrasonic signal was acquired after 30 min at rest; (ii) an initially 100% charged battery underwent two subsequent discharge-charge cycles at constant current with fixed C-rates varying between 0.2 and 2C. Then a series of cycles at 50°C aimed at causing battery degradation was performed while acquiring the ultrasonic signal every 2 min. The efficacy of the degradation protocol was assessed through EIS prior and post cycling the battery. Surprisingly, results show an opposite (but systemic) trend with respect to what is reported in literature, with an increasing time of flight (ToF) for increasing state of charge (SoC). Additionally, it is observed that most of the peaks increase their ToF with the number of cycles. Signal amplitude shows a periodical behavior as well but values vary as degradation has gone on. It is also observed that within a cycle some peaks increase their intensity during charge while others decrease, suggesting that they belong to opposite electrodes.

On the analyzing of bifurcation properties of the one‐dimensional Mackey–Glass model by using a generalized approach

The goal of this work is to look at how a nonlinear model describes hematopoiesis and its complexities utilizing commonly used techniques with historical and material links. Based on time delay, the Mackey–Glass model is explored in two instances. To offer a range, the relevance of the parameter impacting stability (bifurcation) is recorded. The power spectrum of the considered model is collected in order to analyze the periodic behavior of a solution in a differential equation. The complex nature of the system is relayed on a parameter which is illustrated in the bifurcation plot. Due to the fact that the considered model is associated with blood‐related diseases, the effect coefficients are effectively captured. The corresponding parameters‐based consequences of the generalized model in different order are deduced. The parametric charts for both examples reveal intriguing results. The current work enables investigations into complex real‐world problems as well as forecasts of essential techniques.

Exploring chaos and ergodic behavior of an inductorless circuit driven by stochastic parameters

There exist extensive studies on periodic and random perturbations of various smooth maps investigating their dynamics. Unlike smooth maps, non-smooth maps are yet to be studied extensively under a stochastic regime. This paper presents a stochastic piecewise-smooth map derived from a simple inductorless switching circuit. The stochasticity is introduced in parameter values. The distribution of the parameter values is bounded and randomly selected from uniform and triangular distributions and ranges between high and low bifurcation parameter values of the deterministic map. Due to this inherent stochasticity in parameter values, the time evolution of the state variable cannot be predicted at a specific time instant. We observe that the state variable exhibits completely ergodic behavior when the minimum value of the parameter is the same as the minimum bifurcation parameter of the deterministic system. However, the ensemble average of the state variable converges to a fixed value. The system demonstrates nonchaotic behavior for a particular range of parameter values but the deterministic map in that bifurcation range shows interplay between chaos and periodic orbits. The values of Lyapunov exponents decrease monotonically with increased asymmetry of the distribution from which the bifurcation parameter values are chosen. We determine the probability density function of the stochastic map and verify its invariance under initial conditions. The most noteworthy result is the disappearance of chaotic behavior when the lower range of the distribution is varied while maintaining a fixed upper threshold for a particular distribution, even though the deterministic map exhibits an array of periodic and chaotic behaviors within the range. As the period-incrementing cascade with chaotic inclusion only occurs in nonsmooth maps, this paper numerically shows the stochasticity of a piecewise-smooth map obtained from a practical system for the first time where randomness is introduced in the parameter space.

Temporal variability of aridity in Argentina during the period 1961–2020

This paper examines the temporal variability of aridity in Argentina during the period 1961–2020. Monthly data from the Climatic Research Unit (CRU) were used to define climate types according to the Aridity Index (AI) from the United Nations Environment Programme (UNEP). Argentina presents a variety of climates ranging from arid and semiarid to subhumid and humid, suggesting simultaneous water deficit and excess conditions. However, an aridity increase in the past six decades has been observed in much of the country, contrasting with reduced areas that have become wetter. Since these changes were not uniform across the study area, a regional-level analysis was conducted to adequately capture the aridity temporal patterns, including trends, jumps, seasonality, and cycles. In general, there was a decrease in the annual AI in most regions, with non-linear patterns such as long-term oscillations, shorter-duration cycles, and abrupt variations in the average. Seasonal aridity changes showed variabilities according to the season, with higher humidity during summer and autumn, and greater aridity during winter and spring. Simultaneously, seasonal AI experienced periodic behavior with significant arid and humid cycles alternating every 10–15 years. These findings highlight the complexity of climate changes, which vary by region and season.

The Combined Effect of Tribulus terrestris Hydroalcoholic Extract and Swimming Exercise on Memory and Oxidative Stress in Old Male Rats

ABSTRACT Background and objective This study aims to assess the effect of swim exercise along with consumption of bindii hydroalcoholic extract on memory and the oxidative stress markers in old male rats. Materials and methods This study was conducted on 32 old (400–500 g) and eight young male Wistar rats. The groups included young, old, old bindii (200 mg/kg), old exercise, and old bindii exercise (concurrent swimming training). All interventions were performed within 14 days. The animals’ spatial memory was evaluated by the Y maze, radial maze, and shuttle box, Oxidative stress factors were also measured. Results Compared to the old control group, the bindii extract along with swimming exercise significantly increased the periodic behavior percentage in the Y maze and the delay time in entry into the dark chamber in the shuttle box but no significant difference was seen in the reference memory error in the radial maze. Also, a significant increase in the amount of catalase (CAT) and antioxidant capacity (TAC) and a significant decrease in the amount of malondialdehyde (MDA) were observed in all treatment groups. Conclusion These results show that exercise, along with the bindii extract consumption, can improve spatial and avoidance memory in old rats probably through the reduction of oxidative stress effects.

Time-dependent variations of groundwater radon: Insights from a twelve-year study in the Baikal region, East Siberia, Russia

Time-dependent variations of 222Rn concentration (Q) in groundwater have been monitored for twelve years (2012–2023) at eight sites of groundwater discharge within the Baikal region in East Siberia, Russia. The concentrations of radioactive gas at different sites vary from 30% to 60% of average values (Qav). The sampled waters are of three groups with Qav ≈ 15 Bq/l (I), ≈30 Bq/l (II1), and ≈50 Bq/l (II2). Cluster analysis shows closest linkage between the two subgroups of group II due to similarity in the discharge mechanisms. Fourier analysis of periodic 222Rn behavior reveals major cycles of 365, 180, 126, and 30 days correlated with variations of air temperature and pressure, as well as with the patterns of groundwater discharge. In addition, radon anomalies are related with seismicity. Earthquakes are reflected in the radon field as three distinct anomaly types, occurring either subsequent to or prior to the seismic event. The anomalies responding to earthquake nucleation can be considered as precursors and used in earthquake prediction. The revealed trends make basis for a model designed to predict Q variations in groundwater of the area to 80% average efficiency. The external and internal factors that affect the concentration of radioactive gas in groundwater are linked in a hierarchic system and are classified according to the degree and type of their influence.

XMM-Newton and NuSTAR discovery of a likely IP candidate XMMU J173029.8--330920 in the Galactic disc

We aim to characterise the population of low-luminosity X-ray sources in the Galactic plane by studying their X-ray spectra and periodic signals in the light curves. We are performing an X-ray survey of the Galactic disc using and the source XMMU J173029.8--330920 was serendipitously discovered in our campaign. We performed a follow-up observation of the source using our pre-approved target of opportunity time. We used various phenomenological models in xspec for the X-ray spectral modelling. We also computed the Lomb-Scargle periodogram to search for X-ray periodicity. A Monte Carlo method was used to simulate 1000 artificial light curves in order to estimate the significance of the detected period. We also searched for X-ray, optical, and infrared counterparts of the source in various catalogues. The spectral modelling indicates the presence of an intervening cloud with $N_ H $ that partially absorbs the incoming X-ray photons. The X-ray spectra are best fit by a model representing emission from a collisionally ionised diffuse gas with a plasma temperature of $kT=26^ $ keV. Furthermore, an Fe $K_ alpha $ line at $6.47^ $ keV was detected with an equivalent width of the line of $312 eV. We discovered a coherent pulsation with a period of $521.7 s. The 3--10 keV pulsed fraction of the source is around sim 50--60<!PCT!>. The hard X-ray emission with plasma temperature $kT=26^ $ keV, iron $K_ alpha $ emission at 6.4 keV, and a periodic behaviour of $521.7 s suggest XMMU J173029.8--33092 to be an intermediate polar. We estimated the mass of the central white dwarf to be $0.94-1.4\ odot $ by assuming a distance to the source of $ kpc.

Generative Models for Periodicity Detection in Noisy Signals.

We present the Gaussian Mixture Periodicity Detection Algorithm (GMPDA), a novel method for detecting periodicity in the binary time series of event onsets. The GMPDA addresses the periodicity detection problem by inferring parameters of a generative model. We introduce two models, the Clock Model and the Random Walk Model, which describe distinct periodic phenomena and provide a comprehensive generative framework. The GMPDA demonstrates robust performance in test cases involving single and multiple periodicities, as well as varying noise levels. Additionally, we evaluate the GMPDA on real-world data from recorded leg movements during sleep, where it successfully identifies expected periodicities despite high noise levels. The primary contributions of this paper include the development of two new models for generating periodic event behavior and the GMPDA, which exhibits high accuracy in detecting multiple periodicities even in noisy environments.

Coherent manipulation of bright and dark solitons of reflection and transmission pulses through sodium atomic medium

Abstract The coherent manipulation and control of bright and dark solitons through sodium atomic medium have been investigated in this manuscript. Dark soliton is reported for reflection and bright soliton is reported for transmission pulses with variation in position and driving field parameters through sodium atomic medium. Further the transmission pulse is periodic dark and bright solitonic behaviors and reflection pulse is periodic bright solitonic behavior with variation in the incident angle and Rabi frequency of the control field. Elliptical dark and bright solitons as well as breather types solitons are also investigated for reflection and transmission pulses. The dark soliton in reflection is due to slow light propagation and bright soliton is obtained due to fast light propagation of transmission through the medium. The modified results of the dark and bright solitons are useful for telecommunication and ultra-fast signal routing system.

Variability and predictability of a reduced-order land–atmosphere coupled model

Abstract. This study delves into the predictability of atmospheric blocking, zonal, and transition patterns utilizing a simplified coupled model. This model, implemented in Python, emulates midlatitude atmospheric dynamics with a two-layer quasi-geostrophic channel atmosphere on a β plane, encompassing simplified land effects. Initially, we comprehensively scrutinize the model's responses to environmental parameters like solar radiation, surface friction, and atmosphere–ground heat exchange. Our findings confirm that the model faithfully replicates real-world Earth-like flow regimes, establishing a robust foundation for further analysis. Subsequently, employing Gaussian mixture clustering, we successfully delineate distinct blocking, zonal, and transition flow regimes, unveiling their dependencies on surface friction. To gauge predictability and persistence, we compute the averaged local Lyapunov exponents for each regime. Our investigation uncovers the presence of zonal, blocking, and transition regimes, particularly under conditions of reduced surface friction. As surface friction increases further, the system transitions to a state characterized by two blocking regimes and a transition regime. Intriguingly, periodic behavior emerges under specific surface friction values, returning to patterns observed under low friction coefficients. A model resolution increase impacts the system in such a way that only two regimes are then obtained with the clustering: the transition phase disappears and the predictability drops to roughly 2 d for both of the remaining regimes. In accordance with previous research findings, our study underscores the fact that when all three regimes coexist, zonal patterns exhibit a more extended predictability horizon compared to blocking patterns. Remarkably, transition patterns exhibit reduced predictability when coexisting with the other regimes. In addition, within a specified range of surface friction values where two blocking regimes are found, it is observed that blocked atmospheric situations in the west of the applied topography are marked by instabilities and reduced predictability in contrast to the blockings appearing on the eastern side of the topography.

Inner fission barriers of uranium isotopes in the deformed relativistic Hartree-Bogoliubov theory in continuum

Abstract The inner fission barriers of the even-even uranium isotopes from the proton to the neutron drip line are studied with the deformed relativistic Hartree-Bogoliubov theory in continuum. A periodic evolution for the ground state shapes is shown with the neutron number, i.e., spherical shapes at shell closures N=126, 184, 258, and prolate dominated shapes between them. In analogy to the shape evolution, the inner fission barriers also exhibit a periodic behavior: peaks at the shell closures and valleys in the mid-shells. The triaxial effect to the inner fission barrier is evaluated using the triaxial relativistic mean field calculations plus a simple BCS method for pairing. With the triaxial correction included, good consistency in the inner barrier heights is found with the available empirical data.
Besides, the evolution from the proton to the neutron drip line is in accord with the results by the multi-dimensionally constrained relativistic mean field theory. A flat valley in the fission barrier height is predicted around the neutron-rich nucleus 318U which may play a role of fission recycling in the astrophysical r-process nucleosynthesis.

Natural Convection Fluid Flow and Heat Transfer in a Valley-Shaped Cavity

The phenomenon of natural convection is the subject of significant research interest due to its widespread occurrence in both natural and industrial contexts. This study focuses on investigating natural convection phenomena within triangular enclosures, specifically emphasizing a valley-shaped configuration. Our research comprehensively analyses unsteady, non-dimensional time-varying convection resulting from natural fluid flow within a valley-shaped cavity, where the inclined walls serve as hot surfaces and the top wall functions as a cold surface. We explore unsteady natural convection flows in this cavity, utilizing air as the operating fluid, considering a range of Rayleigh numbers from Ra = 100 to 108. Additionally, various non-dimensional times τ, spanning from 0 to 5000, are examined, with a fixed Prandtl number (Pr = 0.71) and aspect ratio (A = 0.5). Employing a two-dimensional framework for numerical analysis, our study focuses on identifying unstable flow mechanisms characterized by different non-dimensional times, including symmetric, asymmetric, and unsteady flow patterns. The numerical results reveal that natural convection flows remain steady in the symmetric state for Rayleigh values ranging from 100 to 7 × 103. Asymmetric flow occurs when the Ra surpasses 7 × 103. Under the asymmetric condition, flow arrives in an unsteady stage before stabilizing at the fully formed stage for 7 × 103 < Ra < 107. This study demonstrates that periodic unsteady flows shift into chaotic situations during the transitional stage before transferring to periodic behavior in the developed stage, but the chaotic flow remains predominant in the unsteady regime with larger Rayleigh numbers. Furthermore, we present an analysis of heat transfer within the cavity, discussing and quantifying its dependence on the Rayleigh number.

Periodic Energy Optimization Using IOT and ML

The rapid expansion of Internet of Things (IoT) applications across various sectors generates an enormous volume of continuous time-series data. However, transmitting this massive amount of sensor data from energy constrained IoT nodes poses a significant challenge. The continuous transmission of such data consumes vast amounts of energy.In this work, we present a solution to this problem by predicting the periodic behavior of sensor data through a higher-level view of continuous transmission data from nodes in IoT at server side. Our system is composed of an IoT sensor network and a data processing unit. The local sensor network: temperature and humidity data is collected using 4 different nodes, as well, which afterward this info is transferred into a data processing unit built on the Raspberry Pi device. We use the machine learning model Autoregressive Integrated Moving Average (ARIMA) on the processing unit. This model is then applied individually to the data from each of the four nodes, predicting processed sensor values in the future accurately. In short, after getting highly accurate prediction, then we settle down proper energy saving pattern which reduces the data transmission requirements hence results in energy saving pattern.By utilizing the predictive capabilities of the ARIMA model, we minimize the need for constant transmission of raw sensor data. Instead, we transmit only essential updates or deviations from the predicted values. This approach substantially reduces energy consumption by eliminating the transmission of redundant information. In summary, our project aims to overcome the energy limitations of IoT sensor nodes by leveraging predictive modelling techniques, specifically the ARIMA model. By accurately predicting periodic patterns in sensor data, we can optimize energy usage by transmitting only the necessary information, while still ensuring effective monitoring of temperature and humidity in the IoT network.

3D deformation velocity field analysis and TEM method to detect the tectonic influence on the land subsidence in Zamora, Mexico

The city of Zamora is situated in a tectonic basin and, according to previous interferometric studies, has been experiencing sinking up to 13 cm/yr (2007-2011). Although the reported subsidence pattern (WNW-ESE) is similar to the orientation of the regional fault system, there is a lack of detailed studies to establish the connection between this phenomenon, the thickness of sediments, and the basement geometry. Therefore, this paper presents a 3D deformation velocity field analysis for the period of 2014–2021, using 130 images from the Sentinel-2 satellite to calculate the vertical and east-west components of the subsidence. Likewise, a campaign of 28 Transient Electromagnetic soundings was carried out around the city to determine the thickness of sediments and bedrock geometry. The results of the interferometric analysis reveal a WNW-ESE sinking pattern with the maximum vertical velocities observed near the Zamora Museum, amounting to 108 mm/yr (2014–2017) and 102 mm/yr (2018–2021). Meanwhile, the horizontal component has a heterogeneous behavior in both periods with rates reaching up to 1 cm/year. The Transient Electromagnetic survey results show the presence of two grabens, a horst, and a series of half-grabens. The thickness of sediments varies between 94 and 314 m, with the latter corresponding to the main graben located beneath the city. The axis of this structure and the largest sediment deposits are linked to the area of maximum sinking and the spatial pattern of subsidence.

Quasi periodic oscillations around Kerr-type black hole in the Starobinsky–Bel–Robinson theory of gravity

In this study of Kerr-type black hole within the Starobinsky–Bel–Robinson gravity, we unveil intriguing dynamics. We observe that the black hole spin weakens the effective potential, while the stringy parameter β of the Starobinsky–Bel–Robinson gravity, strengthens it, notably near the black hole. We further see that the deviations from the Kerr paradigm affect Innermost Stable Circular Orbit (ISCO) and Outermost Stable Circular Orbit (OSCO) regions. Moreover, the fundamental frequencies reveal the dominance of the β parameter near the black hole. Our analysis provides valuable insights into the possible black hole mass and β parameter for GRO J1655-40, XTE J1550-564, XTE J1859+226, GRS 1915+105 and H1743-322 under the Starobinsky–Bel–Robinson gravity, highlighting the role of quasi periodic oscillations behavior and black hole spin in defining these constraints. These findings have significant implications, highlighting the potential of the parameter β to rival or surpass the influence of the spin of the black hole, offering new insights into the behavior of black hole and spacetime beyond General Relativity.