Walk Process Research Articles

Superdiffusive transport in quasi-particle dephasing models

Investigating the behavior of noninteracting fermions subjected to local dephasing, we reveal that quasi-particle dephasing can induce superdiffusive transport. This superdiffusion arises from nodal points within the momentum distribution of local dephasing quasi-particles, leading to asymptotic long-lived modes. By studying the dynamics of the Wigner function, we rigorously elucidate how the dynamics of these enduring modes give rise to Lévy walk processes, a renowned mechanism underlying superdiffusion phenomena. Our research demonstrates the controllability of dynamical scaling exponents by selecting quasi-particles and extends its applicability to higher dimensions, underlining the pervasive nature of superdiffusion in dephasing models.

A novel high applicability link prediction based on biased random walks

Complex systems are prevalent in nature, and link prediction is crucial for analyzing these systems. This method has gained attention for its ability to uncover various irregular movements with underlying similarities. While individual particle behavior is unpredictable, the collective behavior of large groups can be forecasted more accurately. The variability at lower scales vs universal similarities at higher scales is often overlooked. To address this, we investigate the random walk process on directed networks at a global scale. We propose an improved link prediction method using biased random walks to enhance accuracy and applicability. We first define out-degree neighbors as valid transmission options to prevent conflicts with in-degree paths. We then analyze how out-degrees and in-degrees affect particle transition probabilities, guiding particles toward high out-degrees and low in-degrees for a sustainable process. Finally, we use particle stabilization probabilities at different nodes as a similarity measure for predicting potential connections. Our method improves prediction precision and practicality, as validated by experiments on nine real-world networks, showing significant gains in accuracy and AUC scores.

Unifying suspension and granular shear-induced self-diffusion

Shear-induced self-diffusion is a fundamental mode of transport in granular flows. Yet its critical behaviour and dependence on the particle solid fraction are still unclear. Here, we rationalize these dependencies by performing two-dimensional pressure-imposed numerical simulations of dense non-Brownian frictional suspensions. Our results, combined with existing numerical data on inertial granular flows, show that the shear-induced diffusion coefficients of both systems can be captured by a single function of the distance to jamming. They further show that the grain diffusive behaviour is underpinned by a specific random walk process, having a constant elementary step length driven at a frequency that increases with the solid fraction. The proposed scaling laws pave the way for a better understanding of mixing processes in granular media.

Quantum phenomena in biological systems

Quantum biology is a modern field of research that aims to understand how quantum effects can affect the chemistry underlying various biological processes. This paper reviews several examples of biological processes where quantum effects might play a notable role. Initially, the photon capture mechanism present in vision is discussed, where the energy of the photon is used to cause conformational changes to chromophoric proteins. The second example elaborates the highly efficient energy transfer process present in photosynthesis and discusses, in particular, how the random quantum walk process may enhance the performance drastically. Subsequently, the vertebrate magnetoreception, and the possible associated role of the radical pair mechanism in the process is considered. The review concludes with the discussion of some speculative ideas of putative quantum effects arising in neural processes.

Improved GPS tropospheric path delay estimation using variable random walk process noise

Accurate positioning using the Global Positioning System relies on accurate modeling of tropospheric delay. Estimated tropospheric delay must vary sufficiently to capture true variations; otherwise, systematic errors propagate into estimated positions, particularly the vertical. However, if the allowed delay variation is too large, the propagation of data noise into all parameters is amplified, reducing precision. Here we investigate the optimal choice of tropospheric constraints applied in the GipsyX software, which are specified by values of random walk process noise. We use the variability of 5-min estimated positions as a proxy for tropospheric error. Given that weighted mean 5-min positions closely replicate 24-h solutions, our ultimate goal is to improve 24-h positions and other daily products, such as precise orbit parameters. The commonly adopted default constraint for the zenith wet delay (ZWD) is 3 mm/√(hr) for 5-min data intervals. Using this constraint, we observe spurious wave-like patterns of 5-min vertical displacement estimates with amplitudes ~ 100 mm coincident with Winter Storm Ezekiel of November 27, 2019, across the central/eastern USA. Loosening the constraint suppresses the spurious waves and reduces 5-min vertical displacement variability while improving water vapor estimates. Further improvement can be achieved when optimizing constraints regionally, or for each station. Globally, results are typically optimized in the range of 6–12 mm/√(hr). Generally, we at least recommend loosening the constraint from the current default of 3 mm/√(hr) to 6 mm/√(hr) for ZWD every 300 s. Constraint values must be scaled by √(x/300) for alternative data intervals of x seconds.

Multi-Trajectory Planning Control Strategy for Hydropower Plant Bridge Crane Based on Evaluation Algorithm

Currently, the research on crane trajectory planning mostly aims to, first, plan the trajectories of the crane and the trolley, and then to use a trial-and-error method or optimization algorithm to iteratively calculate the optimal trajectory parameters under the control of the optimal trajectory parameters to achieve the suppression of the swing angle. However, research on the fusion application of multi-trajectory planning algorithms is very rare. In addition, the existing methods are not suitable for the special operation control of hydropower plant bridge cranes. Based on the application scenario of hydropower plant bridge cranes, this paper proposes a comprehensive multi-trajectory control strategy based on the entropy weight technique for order preference, similarly to the ideal solution (TOPSIS) evaluation method. Specifically, the kinematic analysis of the crane is carried out and the trajectory evaluation index system is established. Secondly, under the walking constraint condition, four different trajectory planning algorithms are used to obtain the crane trajectory curve. In order to ensure the accuracy and comprehensiveness of the evaluation, the evaluation data are obtained through the Adams motion simulation platform. Finally, based on the entropy weight TOPSIS evaluation method, the optimal walking trajectory for each displacement is selected. The simulation and experimental results show that the evaluation method can select the optimal trajectory based on the motion characteristics of the trajectory algorithm in different displacement conditions, effectively reducing the load swing during the walking process of the crane and improving the positioning accuracy.

Does speculation impair informational efficiency? New evidence from the Indian agricultural commodity market

Purpose This study explores the association between market efficiency and speculation. The government of India temporarily banned the futures trading of various commodities several times citing the presence of speculation. Many controversies exist about this topic; thus, this study clarifies the association between market efficiency and speculation and investigates whether market reforms altered this association.Design/methodology/approach The data for nine commodities is collected from the National Commodity and Derivative Exchange (NCDEX) for 2005–2022. Regression analysis and Automatic Variance Ratio (AVR) were adopted to inspect the informational efficiency and influence of speculation in the commodity market. Furthermore, this study uses different sub-samples to understand the changes in the market microstructure and its effects on market quality.Findings The results confirm an inverse and significant relationship between information efficiency and speculation and a deviation from the random walk process observed. Therefore, return predictability exists in the market. This study confirms that market reforms do not reduce the influence of speculation on market efficiency. The study concludes that the market is not weak-form efficient.Research limitations/implications This study has certain limitations, since this study is empirical in nature, it may possess the limitations of empirical research.Originality/value This paper has dual novelty. First, this study investigates the effects of market reforms. Second, this study captures the influence of speculation in the Indian agricultural commodity market by considering the market microstructure aspects.

Outlier detection using local density and global structure

Outlier detection, a critical process for enhancing data quality, has been applied to a broad spectrum of real-world applications. This study introduces a novel and effective outlier detection method that incorporates both local density and global structural information. Specifically, we employ the concept of potential energy, a well-established principle in physics, to represent local densities or neighbor distributions of data. Additionally, we also exploit the notion of hubness, a measure explored in network science, to further capture global structural information of data. To facilitate this, we construct a strongly connected digraph by introducing a virtual node along with an associated set of virtual edges. This digraph underpins a tailored Markov random walk process that is used to estimate the hubness scores of data objects. Subsequently, the importance degrees of data objects are estimated according to their potential energies and hubness scores. The data objects with lower importance degrees are deemed to be outliers. Extensive experiments conducted on thirteen publicly accessible real-world datasets against nine popular outlier detection algorithms show that the proposed method achieved encouraging and competitive performance in comparing the state-of-the-art outlier detection algorithms.

Identification of Drought Stress-Responsive Genes in Rice by Random Walk with Multi-Restart Probability on MultiPlex Biological Networks.

Exploring drought stress-responsive genes in rice is essential for breeding drought-resistant varieties. Rice drought resistance is controlled by multiple genes, and mining drought stress-responsive genes solely based on single omics data lacks stability and accuracy. Multi-omics correlation analysis and biological molecular network analysis provide robust solutions. This study proposed a random walk with a multi-restart probability (RWMRP) algorithm, based on the Restarted Random Walk (RWR) algorithm, to operate on rice MultiPlex biological networks. It explores the interactions between biological molecules across various levels and ranks potential genes. RWMRP uses eigenvector centrality to evaluate node importance in the network and adjusts the restart probabilities accordingly, diverging from the uniform restart probability employed in RWR. In the random walk process, it can be better to consider the global relationships in the network. Firstly, we constructed a MultiPlex biological network by integrating the rice protein-protein interaction, gene pathway, and gene co-expression network. Then, we employed RWMRP to predict the potential genes associated with rice tolerance to drought stress. Enrichment and correlation analyses resulted in the identification of 12 drought-related genes. We further conducted quantitative real-time polymerase chain reaction (qRT-PCR) analysis on these 12 genes, ultimately identifying 10 genes responsive to drought stress.

Enzyme-Powered, Label-Free DNA Walker for Uracil-DNA Glycosylase Detection at Single-Cell Level.

Uracil-DNA glycosylase (UDG) plays a crucial role in the removal of damaged uracil bases, thereby upholding genetic stability and integrity. An enzyme-powered, label-free DNA walker was devised for UDG activity detection. Initially, a label-free DNA track, incorporating a gold nanoparticle (AuNP), multiple hairpin structures, and various swing arms, was engineered for walking mechanism. The hairpin structure was meticulously crafted to include a G-quadruplex sequence, enabling the generation of a label-free fluorescence signal. The swing arm remained inert in the absence of UDG, but became activated upon the introduction of UDG, thereby initiating the enzyme-powered walking process and generating significant dissociative G-quadruplex sequences. By integrating a selective fluorescent dye into the design, an enhanced label-free fluorescence response was achieved. The proposed DNA walker presented a direct and label-free approach for UDG detection, demonstrating exceptional sensitivity with a detection limit of 0.00004 U/mL. Using the uracil glycosylase inhibitor (UGI) as an inhibitory model, inhibitor assay was conducted with satisfactory precision. Furthermore, successful analysis of cellular UDG at the single-cell level was accomplished. Consequently, the developed DNA walker serves as a label-free, selective, and sensitive tool for UDG activity assessment, showing great potential for applications in disease diagnosis, inhibitor screening, and biomedical investigations.

Transfer entropy on collective motion with undeclared loose leader–follower (LLF) structure

During an emergency or evacuation, individuals focus on the movement of their neighbors and follow those in sight, even without social affiliation, forming the undeclared Loose Leader-Follower (LLF) group, rather than the usual assumption of following certain rules in most of evacuation models. Inspired by the real-life experience and experimental data, the study develops a novel stochastic process-based evacuation model, integrated the LLF structure in collective motion to clarify the mechanism underlying individual interaction and refine the walking process according to attainable information. Transfer entropy (TE), a model-free measure of the direction of information flow, is used to detect the role of the individuals in the LLF structure from the time-series reconstructed motion information (e.g., the walking coordinate series). To reduce the error of the role detection, according to the 3σ principle for TE values, the detection threshold is decided based on the surrogate walking data. For simulation of their motion decision in the LLF structure, the TE is integrated into the walking behavior mode (TE-POMDP) using the Partially Observable Markov Decision Process (POMDP), that produces their motion behavior under the typical attained information condition. The results show that the TE-POMDP can provide more realistic trajectories. Additionally, we find that a ‘Delta-like’ formation of leading group distribution was presented and remained stable in the procession after a short period of confusion in early stage.

On the Boundary Functional of a Semi-Markov Process

In this paper, we consider the semi-Markov random walk process with negative drift, positive jumps. An integral equation for the Laplace transform of the conditional distribution of the boundary functional is obtained. In this work, we define the residence time of the system by generalized exponential distributions with different parameters via fractional order integral equation. The purpose of this paper is to reduce an integral equation for the Laplace transform of the conditional distribution of a boundary functional of the semi-Markov random walk processes to fractional order differential equation with constant coefficients.

Rate of Weak Convergence of Random Walk with a Generalized Reflecting Barrier

In this study, a random walk process with generalized reflecting barrier is considered and an inequality for rate of weak convergence of the stationary distribution of the process of interest is propounded. Under some conditions, the weak convergence theorem for the stationary distribution of the considered process is obtained in literature, however, the rate of the convergence is not studied sufficiently. Nonetheless, one of the most crucial issues in probability theory is the convergence rate in limit theorems, as it affects the precision and effectiveness of using these theorems in practice. Therefore, for the rate of convergence for the examined process, comparatively simple inequality is represented. The obtained inequality demonstrates that the rate of convergence is correlated with the tail of the distribution of ladder heights of the random walk.

Wearable accelerometers reveal objective assessment of walking symmetry and regularity in idiopathic scoliosis patients.

Scoliosis is a multifaceted three-dimensional deformity that significantly affects patients' balance function and walking process. While existing research primarily focuses on spatial and temporal parameters of walking and trunk/pelvic kinematics asymmetry, there remains controversy regarding the symmetry and regularity of bilateral lower limb gait. This study aims to investigate the symmetry and regularity of bilateral lower limb gait and examine the balance control strategy of the head during walking in patients with idiopathic scoliosis. The study involved 17 patients with idiopathic scoliosis of Lenke 1 and Lenke 5 classifications, along with 17 healthy subjects for comparison. Three-dimensional accelerometers were attached to the head and L5 spinous process of each participant, and three-dimensional motion acceleration signals were collected during a 10-meter walking test. Analysis of the collected acceleration signals involved calculating five variables related to the symmetry and regularity of walking: root mean square (RMS) of the acceleration signal, harmonic ratio (HR), step regularity, stride regularity, and gait symmetry. Our analysis reveals that, during the walking process, the three-dimensional motion acceleration signals acquired from the lumbar region of patients diagnosed with idiopathic scoliosis exhibit noteworthy disparities in the RMS of the vertical axis (RMS-VT) and the HR of the vertical axis (HR-VT) when compared to the corresponding values in the healthy control (RMS-VT: 1.6±0.41 vs. 3±0.47, P<0.05; HR-VT: 3±0.72 vs. 3.9±0.71, P<0.05). Additionally, the motion acceleration signals of the head in three-dimensional space, including the RMS in the anterior-posterior and vertical axis, the HR-VT, and the values of step regularity in both anterior-posterior and vertical axis, as well as the values of stride regularity in all three axes, are all significantly lower than those in the healthy control group (P<0.05). The findings of the analysis suggest that the application of three-dimensional accelerometer sensors proves efficacious and convenient for scrutinizing the symmetry and regularity of walking in individuals with idiopathic scoliosis. Distinctive irregularities in gait symmetry and regularity manifest in patients with idiopathic scoliosis, particularly within the antero-posterior and vertical direction. Moreover, the dynamic balance control strategy of the head in three-dimensional space among patients with idiopathic scoliosis exhibits a relatively conservative nature when compared to healthy individuals.

Asymmetric 1,n‐Remote Aminoacetoxylation of Unactivated Internal Alkenes Enabled by Palladium Catalysis**

AbstractA palladium‐catalyzed asymmetric 1,n‐remote aminoacetoxylation of cis‐alkenes has been developed using PhI(OAc)2 as an oxidant, providing the acetoxylated lactams with excellent enantioselectivities under mild reaction conditions. The sterically hindered pyridine‐oxazoline (Pyox) L3 with a tert‐butyl group in oxazoline ring and propyl group in C6 position of pyridinyl is vital for the reaction, where the former is good for asymmetric aminopalladation step and the latter for the chain walking process. The enantioenriched lactam products were proven to be good building blocks for the synthesis of azabicycles.

Asymmetric 1,n-Remote Aminoacetoxylation of Unactivated Internal Alkenes Enabled by Palladium Catalysis.

A palladium-catalyzed asymmetric 1,n-remote aminoacetoxylation of cis-alkenes has been developed using PhI(OAc)2 as an oxidant, providing the acetoxylated lactams with excellent enantioselectivities under mild reaction conditions. The sterically hindered pyridine-oxazoline (Pyox) L3 with a tert-butyl group in oxazoline ring and propyl group in C6 position of pyridinyl is vital for the reaction, where the former is good for asymmetric aminopalladation step and the latter for the chain walking process. The enantioenriched lactam products were proven to be good building blocks for the synthesis of azabicycles.

A New Timescale–Mass Scaling for the Optical Variation of Active Galactic Nuclei across the Intermediate-mass to Supermassive Scales

The variability of active galactic nuclei (AGNs) has long been servicing as an essential avenue of exploring the accretion physics of a black hole (BH). There are two commonly used methods for analyzing AGN variability. First, the AGN variability, characterized by the structure function (SF) of a single band, can be well described by a damped random walk (DRW) process on timescales longer than ∼weeks, shorter than which departures have been reported. Second, the color variation (CV) between two bands behaves timescale dependent, raising challenges to the widely accepted reprocessing scenario. However, both the departure from the DRW process and the timescale-dependent CV are hitherto limited to AGNs, mainly quasars, at the supermassive scale. Here, utilizing the high-cadence multiwavelength monitoring on NGC 4395 harboring an intermediate-mass BH, we unveil at the intermediate-mass scale for the first time, prominent departures from the DRW process at timescales shorter than ∼hours in all three nights and bands, and plausible timescale-dependent CVs in the two longest nights of observation. Furthermore, comparing SFs of NGC 4395 to four AGNs at the supermassive scale, we suggest a new scaling relation between the timescale (τ; across nearly 3 orders of magnitude) and the BH mass (M BH): τ∝MBHγ where the exponent γ is likely ≃0.6–0.8. This exponent differs from most previous measurements, but confirms a few, and is consistent with a recent theoretical prediction, suggesting a similar accretion process in AGNs across different mass scales.

Tehran Stock Market efficiency: A quantile autoregression approach

The purpose of this paper is to evaluate the price efficiency of the Tehran Stock Market. For this aim, we used daily stock prices of 30 large companies on the Stock Exchange. In the first stage, a unit root test with the endogenous break and without a structural break was performed using augmented dickey-fuller test (ADF) tests and Phillips-perron (PP) tests. The results indicate that the price of 9 companies has a random walk process with intercept and 21 companies follow a random walk without intercept and trend component process which is known as the pure random walk process. Thus, considering the ADF and PP tests, most companies’ stock prices are efficient. Quantile autoregression results in the second stage show that the stock prices in the middle price deciles have weak efficiency, but in the lower and upper price deciles, the stock price does not follow the weak efficiency conditions. So, if the stock price deviates (up or down) from the long-term mean, the market becomes inefficient, but when the stock price is at the median level, the market is efficient. The general conclusion is that median prices are the long-term average prices that change over time, and stock prices tend to move toward that price.

TESTING MEAN REVERSION OF STOCK PRICES IN OECD COUNTRIES: EVIDENCE FROM FOURIER THRESHOLD UNIT ROOT TEST

Researchers focus on whether stock prices have a unit root, that is, whether they contain a random walk process. If stock prices have a stationary process, that is, if they return to the mean, the effects of shocks are temporary, and it is interpreted that they will return to the trend path over time. If stock prices have transitory shocks, it allows for the prediction of future movements based on past behavior in terms of investment. This study investigates whether stock prices revert to the mean and thus have a random walk process. For this purpose, the Fourier Threshold Unit Root (FTUR) test based on the test methodology of Caner and Hansen (2001) for the period January 1990–January 2021 for 26 OECD countries is applied. The FTUR test takes into account both structural breaks and nonlinearities. The purpose of using Fourier functions to account for structural changes is that they are not affected by the number, location, or shape of breaks. Thus, the power of the test increases. According to the results of this test, stock prices in Austria, Canada, Germany, Italy, New Zealand, Spain, and the UK are linear. Therefore, Fourier Augmented Dickey-Fuller (FADF) unit root analysis was performed for these countries. The FTUR test was performed in other countries. According to the results of FTUR and FADF unit root tests, stock prices are found to contain unit roots in some countries except Italy. In some countries, stock prices have a partial unit root structure. In other words, the effects of shocks are permanent, and it is concluded that future returns cannot be predicted in these countries with the random walk process.

Dependent Competing Failure Processes in Reliability Systems.

This paper deals with a reliability system hit by three types of shocks ranked as harmless, critical, or extreme, depending on their magnitudes, being below H1, between H1 and H2, and above H2, respectively. The system's failure is caused by a single extreme shock or by a total of N critical shocks. In addition, the system fails under occurrences of M pairs of shocks with lags less than some δ (δ-shocks) in any order. Thus, the system fails when one of the three named cumulative damages occurs first. Thus, it fails due to the competition of the three associated shock processes. We obtain a closed-form joint distribution of the time-to-failure, shock count upon failure, δ-shock count, and cumulative damage to the system on failure, to name a few. In particular, the reliability function directly follows from the marginal distribution of the failure time. In a modified system, we restrict δ-shocks to those with small lags between consecutive harmful shocks. We treat the system as a generalized random walk process and use an embellished variant of discrete operational calculus developed in our earlier work. We demonstrate analytical tractability of our formulas which are also validated, through Monte Carlo simulation.