Article
Thermodynamics
Noele Bissoli Perini de Souza, Jose Vicente Cardoso dos Santos, Erick Giovani Sperandio Nascimento, Alex Alisson Bandeira Santos, Davidson Martins Moreira
Summary: The objective of this study is to analyze the scaling behavior and cross-over phenomena of wind speed in the state of Bahia, northeastern Brazil. The results show the existence of scaling behavior and double crossovers, which are dependent on the time period and location of the analyzed data, and correlate with Atlantic and Pacific oscillations. The study highlights the influence of local, mesoscale, and macroscale effects on wind speed in the region.
Article
Neurosciences
C. Markus Brahms, Yang Zhao, David Gerhard, John M. Barden
Summary: This study assessed stride parameters, variability, and long-range correlations in runners of different skill levels during prolonged running. The results showed a significant decrease in long-range correlations and constant variability throughout the run, regardless of skill level.
Article
Environmental Studies
Menghao Huang, Wei Shao, Jian Wang
Summary: This paper analyzes the impact of the Russia-Ukraine conflict on the crude oil market and the chain effect on stock markets in importing and exporting countries. Using the multi-fractal detrended fluctuation analysis (MF-DFA), the study explores the efficiency of the crude oil market before and after the conflict outbreak. The results show that the crude oil market has become less efficient after the conflict, and the cross correlations between the crude oil market and stock markets have increased for importers but remained unchanged for exporters. The study also highlights the weaker persistence of cross correlations between the crude oil and capital markets in importing countries compared to exporting countries.
Article
Multidisciplinary Sciences
Daniel A. Martin, Tiago L. Ribeiro, Sergio A. Cannas, Tomas S. Grigera, Dietmar Plenz, Dante R. Chialvo
Summary: The scaling of correlations provides important clues for understanding critical phenomena in various systems. The study of biological structures faces challenges due to their finite size and inability to vary dimensions, but an experimental system of fixed and small extent can approximate finite-size scaling by computing correlations within a reduced field of view of various widths. Numerical simulations verify these approximations and suggest the heuristic approach is useful for characterizing critical phenomena in biological systems.
SCIENTIFIC REPORTS
(2021)
Article
Business
Walid Mensi, Imran Yousaf, Xuan Vinh Vo, Sang Hoon Kang
Summary: This paper examines the asymmetric multifractality (A-MF) in the Middle East and North Africa (MENA) stock markets during different turbulent periods. The study finds that there are different patterns of multifractality during upward and downward trends, with higher inefficiency during upward trends in most of the stock markets in the whole sample period, and the opposite is true during financial crises. The intensity of A-MF intensifies with an increase in scales, and the evolution of excessive A-MF for MENA stock returns is heterogeneous. Most of the stock markets are more inefficient during a pandemic crisis than during an oil crash and other financial crises. However, the inefficiency of the Saudi Arabia and Qatar stock markets is highly sensitive to oil price crashes. The findings provide valuable insights for investors and policymakers for efficient investment strategies, risk management, and financial stability.
INTERNATIONAL JOURNAL OF EMERGING MARKETS
(2023)
Article
Quantum Science & Technology
Nicolas Staudenmaier, Anjusha Vijayakumar-Sreeja, Santiago Oviedo-Casado, Genko Genov, Daniel Cohen, Daniel Dulog, Thomas Unden, Nico Striegler, Alastair Marshall, Jochen Scheuer, Christoph Findler, Johannes Lang, Ilai Schwartz, Philipp Neumann, Alex Retzker, Fedor Jelezko
Summary: Diffusion noise is the main cause of spectral line broadening in liquid-state nano-scale nuclear magnetic resonance with shallow nitrogen-vacancy centers, resulting in limited resolution. However, a more accurate analysis of diffusion reveals that correlations persist for a longer time at the nano-scale, allowing for improved resolution and challenging our understanding of diffusion. Through experiments using different setups and measurement techniques, we provide overwhelming evidence of power-law decay of correlations, leading to sharp-peaked spectral lines where diffusion broadening is no longer a limitation to resolution.
NPJ QUANTUM INFORMATION
(2022)
Article
Environmental Studies
Walid Mensi, Xuan Vinh Vo, Sang Hoon Kang
Summary: This study investigates the multifractality behavior, time-varying efficiency, and long memory in leading precious and industrial metals futures markets. Results show significant asymmetric multifractality, with variations in behavior among different metals. Additionally, both precious and industrial metals markets exhibit persistence under negative scales and anti-persistence at positive scales.
Article
Optics
Souradeep Sasmal, Shyam Sundar Mahato, A. K. Pan
Summary: The nonlocality revealed in a multiparty multisource network Bell experiment differs conceptually from the standard multiparty Bell nonlocality with a single common source. By introducing variants of asymmetric bilocal and trilocal network scenarios, this study explores different network setups where parties have unequal numbers of measurement settings. The study also demonstrates quantum violations of the proposed inequalities using a sum-of-squares technique and analyzes the robustness of these violations in the presence of white noise.
Article
Engineering, Biomedical
M. Meraz, E. J. Vernon-Carter, E. Rodriguez, J. Alvarez-Ramirez
Summary: This study used fractal scaling analysis to characterize the organization of the SARS-CoV-2 genome sequence. The detrended fluctuation analysis (DFA) was used to detect variations of long-range correlations over different regions of the genome sequence. The results showed that SARS-CoV-2 possessed a more efficient genomic structure for replication and infection compared to the SARS-CoV-1 strain. Early isolates from India and Italy showed more ordered sequence organization, particularly in the spike region, which may have contributed to their more efficient mechanism of spreading, replicating, and infecting. Overall, the DFA provided a suitable framework to assess long-term correlations hidden in the internal organization of the SARS-CoV-2 genome sequence.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Physics, Multidisciplinary
Huanhuan Gong, Zuntao Fu
Summary: In this study, a modified DFA (m-DFA) method with a newly defined fluctuation function is used to discriminate and characterize the correlation structures in short time series effectively. The m-DFA is able to distinguish and quantify the correlation strengths of both short-term and long-term correlations, even in datasets as short as 2000. Additionally, the m-DFA can successfully analyze time series with strong correlation, even when the length is as short as 500.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Mengdie Yang, Yudong Zhang, Jian Wang
Summary: In this paper, a one-dimensional multifractal sign retention detrending fluctuation analysis algorithm (MF-S-DFA) based on conventional MF-DFA is proposed. The method outperforms MF-DFA by considering sign retention in the calculation, leading to more accurate estimation of various parameters in time series analysis. The results from numerical experiments and ECG signal classification confirm the effectiveness and feasibility of MF-S-DFA.
FRACTAL AND FRACTIONAL
(2022)
Article
Materials Science, Multidisciplinary
Noam Schiller, Yuval Oreg, Kyrylo Snizhko
Summary: Fractional quantum Hall quasiparticles are characterized by electric charge and scaling dimension. The scaling dimension determines the anyonic statistics for simple states, while for more complex states, it helps distinguish different theoretical descriptions. A scheme for extracting the scaling dimension from tunneling noise is proposed.
Article
Materials Science, Multidisciplinary
K. Seetharam, A. Lerose, R. Fazio, J. Marino
Summary: This study investigates the spatiotemporal spreading of correlations in an ensemble of spins due to dissipation and discovers a novel pattern related to the dissipative nature and spatial profiles of the channel. Additionally, the study makes a methodological contribution by generalizing nonequilibrium spin-wave theory and deriving equations of motion for translationally invariant spin chains in dissipative systems.
Article
Astronomy & Astrophysics
S. Mahesh Chandran, S. Shankaranarayanan
Summary: In time-independent quantum systems, the entanglement entropy possesses a scaling symmetry that the energy of the system does not have. We extend this symmetry to time-dependent systems including coupled harmonic oscillators and quantum scalar fields. These time-dependent systems exhibit a dynamical scaling symmetry that preserves the evolution of various measures of quantum correlations. It is shown that instabilities in these systems can be quantified using scrambling time and Lyapunov exponents, and that the delayed decay of the Loschmidt echo is determined by inverted modes. We also discuss the implications of zero modes and inverted modes in time-dependent massive scalar fields in different spacetimes, such as cosmological and black hole spacetimes.
Article
Multidisciplinary Sciences
MohammadMehdi Kafashan, Anna W. Jaffe, Selmaan N. Chettih, Ramon Nogueira, Inigo Arandia-Romero, Christopher D. Harvey, Ruben Moreno-Bote, Jan Drugowitsch
Summary: Information about the direction of a moving visual stimulus is distributed across hundreds of neurons in mouse primary visual cortex, scaling sub-linearly due to correlated noise. The study predicts that tens of thousands of neurons encode 95% of the information, supporting the idea of a redundant code in the brain.
NATURE COMMUNICATIONS
(2021)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)