Passage Time Research Articles

ПОВЫШЕНИЕ ПРОПУСКНОЙ СПОСОБНОСТИ РЕГУЛИРУЕМЫХ ПЕРЕКРЕСТКОВ НА ОСНОВЕ СИНЕРГИИ КОМПЬЮТЕРНОГО ЗРЕНИЯ И АДАПТИВНОГО РЕГУЛИРОВАНИЯ СКОРОСТИ

The paper discusses new approaches to the arrangement of non-stop traffic flows at signaled crossings using coordinated traffic management. The study objective is to develop a mathematical model for determining the recommended traffic speed on the stretches of the urban road network using computer vision to ensure the non-stop traffic of a group of vehicles when crossing a signaled intersection. The model is unique because it takes into account the queue parameters of out-of-group vehicles, as well as the condition of the road surface. The study presents a method for calculating the time of non-stop passage of cars over crossings of the road network using AIMS-Eco monitoring system. The system uses real-time video stream analysis technology based on YOLOv4 neural network to obtain data on traffic parameters. The coefficients of influence of the traffic flow structure and the condition of the road surface on the time of queuing outside the group vehicles are characterized, which makes it possible to more accurately assess the impact of these factors on traffic dynamics. The dependences studied include those of the recommended speed of the leading car and the capacity of the road network section on the number of extra-group vehicles, taking into account the travel time of the queue of extra-group vehicles. The developed mathematical model makes it possible to increase the average flow velocity in the section of the stop line by 10-15% due to the arrangement of non-stop passage of signaled intersections by group vehicles. The results achieved are of practical importance for increasing the traffic capacity of the road network, improving road and environmental safety of automobile traffic.

Random walks on scale-free flowers with stochastic resetting.

This study explores the impact of stochastic resetting on the random walk dynamics within scale-free (u,v)-flowers. Utilizing the generating function technique, we develop a recursive relationship for the generating function of the first passage time and establish a connection between the mean first passage time with and without resetting. Our investigation spans multiple scenarios, with the random walker starting from various positions and aiming to reach different target nodes, allowing us to identify the optimal resetting probability that minimizes the mean first passage time for each case. We demonstrate that stochastic resetting significantly improves search efficiency, especially in larger networks. These findings underscore the effectiveness of stochastic resetting as a strategy for optimizing search algorithms in complex networks, offering valuable applications in domains such as biological transport, data networks, and search processes where rapid and efficient exploration is vital.

Random walks with stochastic resetting in complex networks: A discrete-time approach.

We consider a discrete-time Markovian random walk with resets on a connected undirected network. The resets, in which the walker is relocated to randomly chosen nodes, are governed by an independent discrete-time renewal process. Some nodes of the network are target nodes, and we focus on the statistics of first hitting of these nodes. In the non-Markov case of the renewal process, we consider both light- and fat-tailed inter-reset distributions. We derive the propagator matrix in terms of discrete backward recurrence time probability density functions, and in the light-tailed case, we show the existence of a non-equilibrium steady state. In order to tackle the non-Markov scenario, we derive a defective propagator matrix, which describes an auxiliary walk characterized by killing the walker as soon as it hits target nodes. This propagator provides the information on the mean first passage statistics to the target nodes. We establish sufficient conditions for ergodicity of the walk under resetting. Furthermore, we discuss a generic resetting mechanism for which the walk is non-ergodic. Finally, we analyze inter-reset time distributions with infinite mean where we focus on the Sibuya case. We apply these results to study the mean first passage times for Markovian and non-Markovian (Sibuya) renewal resetting protocols in realizations of Watts-Strogatz and Barabási-Albert random graphs. We show nontrivial behavior of the dependence of the mean first passage time on the proportions of the relocation nodes, target nodes, and of the resetting rates. It turns out that, in the large-world case of the Watts-Strogatz graph, the efficiency of a random searcher particularly benefits from the presence of resets.

Optimizing cost through dynamic stochastic resetting

Abstract The cost of stochastic resetting is considered within the context of a discrete random walk (RW) model. In addition to standard stochastic resetting, for which a reset occurs with a certain probability after each step, we introduce a novel resetting protocol which we dubbed dynamic resetting. This protocol entails an additional dynamic constraint related to the direction of successive steps of the RW. We study this novel protocol for a one-dimensional RW on an infinite lattice. We analyze the impact of the constraint on the walker’s mean-first passage time and the cost (fluctuations) of the resets as a function of distance of target from the resetting location. Further, cost optimized search strategies are discussed.

Bearing fault signal detection based on non-negative matrix factorization and dual-feedback segmented unsaturated tristable stochastic resonance system

Abstract Stochastic resonance is widely used in bearing fault detection due to its ability to enhance weak signals. This paper proposes a fault detection method that combines noise reduction with stochastic resonance. Firstly, a segmented unsaturated potential function based on the classic potential function is constructed, and a dual-feedback structure is introduced to feed the system output back to the input, thereby enhancing system performance. Secondly, the theoretical expressions for the Mean First Passage Time (MFPT) and the Spectral Amplification (SA) of the Dual-feedback Segmented Unsaturated Tristable Stochastic Resonance (DSUTSR) system are derived and analyzed. Additionally, a numerical simulation comparison using the fourth-order Runge-Kutta method is performed between the DSUTSR system and its predecessor systems to verify the improvements brought by the dual-feedback structure. Subsequently, Non-negative Matrix Factorization (NMF) is introduced as a noise reduction method, with cross-validation used to determine the decomposition rank of NMF to guide the decomposition of the fault signal matrix. Finally, the combination of NMF and the DSUTSR system is used to detect bearing fault frequencies under white noise and Lévy noise backgrounds. Experimental results demonstrate the superiority and effectiveness of the proposed method in fault signal detection. This system holds significant potential for future weak signal detection, effectively enhancing and identifying fault signals hidden within noisy backgrounds.

Методы оптимизации и алгоритм маршрутизации в транспортной логистике

The article analyzes the key optimization and planning methods used for transport logistics. An algorithm using graph models for the formation of optimal transportation routes, taking into account the main logistical factors, is considered. In contrast to the classical routing problem for transport logistics, the authors use multifactorial assessment and adap-tive heuristics in the presented work. The heuristics proposed by the authors takes into account not only the distance, but also important logistic parameters, such as fuel costs and the time of passage of the route section. The applied mul-tifactorial assessment allows us to build a refined graph model and obtain optimal routes that take into account many factors, which increases efficiency, reduces costs and delivery time. The problem of multi-criteria route optimization solved by the authors has practical application for routing the delivery of goods from large marketplaces to pick-up points taking into account many factors. To solve the problem, the authors present a multi-factor route optimization method A* with adaptive heuristics. For instrumental support of logistics systems in the object-oriented programming language C#, an algorithm is implemented in the form of a library. The developed algorithm and software allow solving problems of optimization, planning and development of the transport and logistics services sector.

The Effect of Chewing Gum on the Return of Bowel Activity after Colorectal Cancer Surgery.

Enhanced recovery after surgery (ERAS) protocols advocate for early enteral feeding to prevent postoperative ileus. Chewing gum acts as a type of sham feeding that triggers the cephalic phase of digestion by stimulating the cephalic vagus nerve. This can enhance gastrointestinal motility and may lead to quicker recovery of gas and bowel movements. To assess how chewing gum during the early postoperative phase affects the duration of postoperative ileus in terms of time to appreciation of first flatus, time to passage of first stools, and duration of hospital stay. The study was conducted in our division of colorectal surgery. This is a case-control study carried out over three years (2020-2023). A total of 100 patients were included, the first 50 were allocated to the control group, and another 50 were allocated to the chewing gum group. All patients above the age of 14 years who underwent resection for colorectal cancers were included. The average age in the control group was 51.44 years and that in the chewing gum group was 50.04 years. The average duration of surgery for the control group was 156.3 minutes (2.6 hours) and 163.8 minutes (2.7 hours) in the chewing gum group. The average time of passage of the first flatus in the chewing gum group was 51.28 hours compared to 66.26 hours in the control group (p = 0.0002). The average time to first bowel movement in the chewing gum group was 71.42 hours. In comparison, the time to first bowel movement in the control group was 85.78 hours (p = 0.000011). The average hospital stay in the chewing gum group was 6.3 days and that in the control group was 6.4 days (p = 0.274254). Chewing gum as a means of sham feeding is a cost-friendly method that significantly decreases the postoperative ileus but has no effect on postoperative hospital stay. Zargar T, Wagay BA, Banday I, et al. The Effect of Chewing Gum on the Return of Bowel Activity after Colorectal Cancer Surgery. Euroasian J Hepato-Gastroenterol 2024;14(2):210-213.

Effect of WW-domain transcription regulator 1 on aging regulation of human dental pulp stem cells

Objective: Investigating the changes of phenotype and moleculars associated with aging with the increase of passage times of human dental pulp stem cells (hDPSC), to explore the role of WW-containing transcriptional regulator 1 (WWTR1) in the aging mechanism. Methods: hDPSCs were cultured by tissue block method, and were divided into 4 groups according to the age, algebra, cell knockdown and overexpression of WWTR1 in hDPSCs. Group Ⅰ: hDPSCs from human teeth were further divided into youth group (15-25 years old) and group middle-aged group (40-50 years old) according to different ages. Group Ⅱ: according to different passage, hDPSCs were divided into young cells group (hDPSCs were transmitted to P3 generation), and old cells group (hDPSCs were transmitted to P10 generation). Group Ⅲ: hDPSCs were knocked down of WWTR1, which were further divided into knockdown group and knockdown carrier group. Group Ⅳ: hDPSCs were overexpressed of WWTR1, which were further divided into overexpression group and overexpression carrier group. Real-time fluorescence quantitative PCR (RT-qPCR) was used to detect the changes of WWTR1 expression in groups Ⅰ and Ⅱ, and cell counting kit-8 (CCK-8) was used for groups Ⅱ, Ⅲ, and Ⅳ. Cell proliferation capacity was detected by CCK-8 assay. The ability of osteogenic differentiation was detected by alizarin red staining. Cell senescence positive rate was detected by age-related β-galactosidase staining. The expression levels of age-related genes p53 and p21 were detected by RT-qPCR. Results: The proportion of senescent cells increased gradually with continuous culture. The proliferation and osteogenic differentiation of hDPSCs in the old group were significantly lower than those in the young group (P<0.001). The expression levels of senescence related genes p53 (2.09±0.24) and p21 (4.91±0.54) in old cell group were higher than those in young cell group respectively [p53: (1.08±0.09) and p21: (1.09±0.08)] (P<0.01, P<0.001). The WWTR1 expression levels of hDPSCs in middle-aged group and old cells group were both decreased compared with those in young group and young cells group (P<0.01). The proportion of senescent cells in knockdown group (44.50±2.42) was higher than that in knockdown carrier group (22.27±0.56) (P<0.001). After knocking down WWTR1 in hDPSCs, the expression levels of age-related genes p53 and p21 were up-regulated (P<0.001), and the abilities of proliferation and osteogenic differentiation in the knockdown group were lower than those in the knockdown carrier group (P<0.001). The proportion of senescent cells in overexpression empty carrier group (20.40±0.79) was higher than that in overexpression group (10.07±0.61) (P<0.001). After WWTR1 overexpression ins hDPSCs, the expression levels of age-related genes p53 and p21 were down-regulated, and the proliferation and osteogenic differentiation ability in overexpression group were higher than those in overexpression carrier group (P<0.001). Conclusions: WWTR1 can inhibit the expression levels of age-related genes p53 and p21, thus delaying the aging process as well as promoting the proliferation and osteogenic differentiation of hDPSCs.

Cerebral, Splanchnic, and Renal Transit Time Measurement and Blood Volume Estimation Using Contrast-Enhanced Ultrasonography.

We aimed to measure cerebral, splanchnic, and renal transit times and the associated blood volumes using contrast ultrasound. In healthy individuals, regional transit times were calculated from time-intensity curves generated as ultrasound contrast passed through the associated inflow and outflow vessels. These included the internal carotid artery and internal jugular vein (brain), the superior mesenteric artery and portal vein (intestines), and the renal artery and renal vein (kidney). An organ's blood volume relative to the stroke volume delivered to that organ with each cardiac cycle was calculated from the product of heart rate and transit time of contrast passage through the associated vascular bed. The fraction of systemic stroke volume received by each organ was calculated from the respective velocity-time integral and inflow vessel cross-sectional area and used to estimate absolute organ blood volume. The cohort consisted of 16 participants (age: 42 ± 13 years; 5 female) without known cerebrovascular, gastrointestinal, or renal disease. Cerebral, splanchnic, and renal transit times were obtained for 15, 14, and 8 individuals, respectively. Anatomic variability of the renal vessels confounded the acquisition of renal transit times. For all organs, transit times were reproducible and the associated blood volumes were generally comparable to reference values. Cerebral, gastrointestinal, and renal transit times/blood volumes can be reasonably acquired from contrast ultrasound, although the latter is less reliably available. Assessment of the impact on regional blood volumes of pharmacologic or other interventions is a next step toward clinical application of this technique.

Péclet‐Number‐Dependent Longitudinal Dispersion in Discrete Fracture Networks

AbstractDispersion in fractured media impacts many environmental and geomechanical practices. It is mainly controlled by the structure of fracture networks and the Péclet number , but predicting it remains challenging. In this study, numerous three‐dimensional stochastic discrete fracture networks (DFNs) were generated, where the density, size, and orientation vary significantly. The aperture and conductivity are proportional to the size, following power‐laws. Through flow and transport simulation, we evaluated the longitudinal dispersion coefficients . We found that, as density increases, the tortuosity decreases and the first passage time distributions approximate bell‐shaped curves more closely, which suggests, but does not fully guarantee, that an asymptotic dispersion regime may emerge for denser DFNs, as solute particles traverse more fractures and the macroscopic inter‐fracture mixing is more homogeneous. We then determined the values for DFNs in which the time evolution of the variance of particle displacements becomes linear and hence asymptotic. The results show that both and fracture density affect , but the former has a much stronger influence than the latter. A new Péclet number was recalculated for all DFNs, where the characteristic length scale accounts for the influence of large fractures. Dimensionless values show a unique power‐law relationship with high values. Furthermore, when advection dominates, the dimensionless can be described by a universal finite‐size scaling function depending on fracture density and domain sizes. The findings of this study enhance the understanding of transport in fracture networks and imply the potential for predicting in a broad range of scenarios using statistics on fracture parameters obtainable at the field scale.

Interspike interval statistics for quadratic integrate-and-fire neurons subject to alpha-stable noise

The statistics of interspike intervals is one of the principle characteristics of the synaptic activity of neurons. This statistics can be presented with the values of the moments of these intervals. For the integrate-and-fire type models, the formalism of first passage time provides partial differential equations for a rigorous calculation of these values for neurons subject to a white Gaussian noise. However, the procedure of derivation of these equations is quite sophisticated and the results for Gaussian noise are not as trivial as they can appear if one does not look at the rigorous derivation procedure. The derivation of analogous partial differential equations for the case of alpha-stable (Lévy) noise is even more involved. In this paper, the equations providing moments of interspike intervals are derived for quadratic integrate-and-fire neurons subject to symmetric alphastable noise. The results are presumably generalizable to other integrate-and-fire type models (e.g., leakage ones). The paper was presented at the 11th International Scientific Conference on Physics and Control (PhysCon 2024), September 9–12, 2024, Istanbul, Turkey.

Random Walk on T-Fractal with Stochastic Resetting

In this study, we explore the impact of stochastic resetting on the dynamics of random walks on a T-fractal network. By employing the generating function technique, we establish a recursive relation between the generating function of the first passage time (FPT) and derive the relationship between the mean first passage time (MFPT) with resetting and the generating function of the FPT without resetting. Our analysis covers various scenarios for a random walker reaching a target site from the starting position; for each case, we determine the optimal resetting probability γ* that minimizes the MFPT. We compare the results with the MFPT without resetting and find that the inclusion of resetting significantly enhances the search efficiency, particularly as the size of the network increases. Our findings highlight the potential of stochastic resetting as an effective strategy for the optimization of search processes in complex networks, offering valuable insights for applications in various fields in which efficient search strategies are crucial.

Gut physiology and environment explain variations in human gut microbiome composition and metabolism

The human gut microbiome is highly personal. However, the contribution of gut physiology and environment to variations in the gut microbiome remains understudied. Here we performed an observational trial using multi-omics to profile microbiome composition and metabolism in 61 healthy adults for 9 consecutive days. We assessed day-to-day changes in gut environmental factors and measured whole-gut and segmental intestinal transit time and pH using a wireless motility capsule in a subset of 50 individuals. We observed substantial daily fluctuations, with intra-individual variations in gut microbiome and metabolism associated with changes in stool moisture and faecal pH, and inter-individual variations accounted for by whole-gut and segmental transit times and pH. Metabolites derived from microbial carbohydrate fermentation correlated negatively with the gut passage time and pH, while proteolytic metabolites and breath methane showed a positive correlation. Finally, we identified associations between segmental transit time/pH and coffee-, diet-, host- and microbial-derived metabolites. Our work suggests that gut physiology and environment are key to understanding the individuality of the human gut microbial composition and metabolism.

Narrow escape with imperfect reactions.

The imperfect narrow escape problem considers the mean first passage time (MFPT) of a Brownian particle through one of several small, partially reactive traps on an otherwise reflecting boundary within a confining domain. Mathematically, this problem is equivalent to Poisson's equationwith mixed Neumann-Robin boundary conditions. Here, we obtain this MFPT in general three-dimensional domains by using strong localized perturbation theory in the small trap limit. These leading-order results involve factors, which are analogous to electrostatic capacitances, and we use Brownian local time theory and kinetic Monte Carlo (KMC) algorithms to rapidly compute these factors. Furthermore, we use a heuristic approximation of such a capacitance to obtain a simple, approximate MFPT, which is valid for any trap reactivity. In addition, we develop KMC algorithms to efficiently simulate the full problem and find excellent agreement with our asymptotic approximations.

Active motion can be beneficial for target search with resetting in a thermal environment.

Stochastic resetting has recently emerged as an efficient target-searching strategy in various physical and biological systems. The efficiency of this strategy depends on the type of environmental noise, whether it is thermal or telegraphic (active). While the impact of each noise type on a search process has been investigated separately, their combined effects have not been explored. In this work, we explore the effects of stochastic resetting on an active system, namely a self-propelled run-and-tumble particle immersed in a thermal bath. In particular, we assume that the position of the particle is reset at a fixed rate with or without reversing the direction of self-propelled velocity. Using standard renewal techniques, we compute the mean search time of this active particle to a fixed target and investigate the interplay between active and thermal fluctuations. We find that the active search can outperform the Brownian search when the magnitude and flipping rate of self-propelled velocity are large and the strength of environmental noise is small. Notably, we find that the presence of thermal noise in the environment helps reduce the mean first passage time of the run-and-tumble particle compared to the absence of thermal noise. Finally, we observe that reversing the direction of self-propelled velocity while resetting can also reduce the overall search time.

Methods of Calculation of Daily Flooded Areas in the Volga Delta During the Flood Periods Based on the Remote Sensing Data

We developed methods for calculating the daily flooded areas in the Volga delta (VD) for the entire flood period using satellite data. The methodology is based on the construction of dependences of the flooding areas of the hydrographic network and interchannel spaces of VD (Ftotal) on the means of daily water levels in the channels of watercourses (НР). Ftotal for individual flood dates were determined using satellite images. Data on НР were taken at hydrological stations (h/s) on the same dates from the State Water Cadastre. These dependencies were used to calculate the daily flooding areas of DV with high accuracy for flood periods of different water contents (high-water, low-water and medium-water contents). This method was developed in two modifications: 1 – modification for the case of the sufficient number of satellite images to cover all the main changes in the course of each phase of the flood, 2 – modification for the case of the insufficient number of satellite images to cover all the main changes in the course of each phase of the flood. We conducted a comparative analysis of daily Ftotal obtained with high accuracy using modification 1 for floods of different water contents (high-water, low-water, medium-water contents). We revealed how floods of different water contents differ in characteristics including timing of passage, amplitude, area of maximum flooding area, duration of the rise phase, decline phase and flood plateau phase. Such calculations have never been conducted before. The results of calculations by this method allow us to identify the spatial-temporal patterns of the VD flooding under different types of water contents. Our method enables to predict the dynamics of floods and to calculate the water balance of the Volga delta.

Implementation of First Passage Time Method as a Warning System to Measure the Probability of Default in Bond

Within the rise of bond investors, an in-depth analysis of risk in bond investment will be continually needed. A lot of research mostly overviewed how a bond acts in the maturity date, while the First Passage Time is developed from the Merton Model, which helps to see credit risk from the issuing date to the maturity date. The First Passage Time Method lets us know when the model hits a certain point we call a Barrier value as the lower benchmark for the first time. It initiates a better understanding of a bond, as it does not only analyze a bond in its maturity date but also during the ongoing period. This method is applied in the Commonwealth Bank Bond I 2020, using company asset data from September 2020 to February 2023. According to R Programming output, if the barrier value is 75% of the total face value, the probability of default is 0.00003145407% with the market value of equity of IDR 21,991,492,000,000. This method will help us see a deeper view of the bond as we can set the Barrier and find whether our bond is “risky” enough, implying that investor losses will not exceed 5,06% of the initial investment within one week.

Thermodynamics and kinetics of state switching for the asymptotically flat black hole in a cavity

We propose that the thermodynamics and the kinetics of state switching for the asymptotically flat black hole enclosed by a cavity can be studied in terms of the free energy landscape formalism. The generalized free energy for the black hole enclosed by a cavity in the canonical ensemble is derived by using the York’s approach, where the temperature on the cavity and the charges inside the cavity are kept as the fixed parameters. By quantifying the corresponding free energy landscape, we obtain the phase diagrams for the black hole in cavity, which reveal a Hawking–Page type transition for the uncharged black hole and a Van der Waals type transition for the charged black hole. We further assume that the dynamics of black hole state switching is mutually determined by the gradient force and the stochastic force arising from the free energy landscape and the thermal noises respectively. We then derive a recurrence relation for the n-momentum of the first passage time distribution function, which enables the calculation of the kinetic times characterized by the mean first passage time and its relative fluctuation. Our analysis illustrates that the kinetics of black hole state switching is determined by the ensemble temperature and the barrier height on the free energy landscape.

Charting the Unknown: First Passage Time Probabilities for Pearson Diffusion Process and Application to Options Risk Management

The first passage time probabilities have applications in many fields, including Finance, Marketing, Economics, Physics, and Statistics. In this paper, we study the first passage time probabilities for a Pearson diffusion process and obtain the lower and upper bounds of the first passage time density. We show that the density may be approximated by the upper bound with an error of approximately five percent. We present an application by modelling the profit and loss function of the S&amp;P 500, FTSE 100 and DAX 40 index options using a Pearson diffusion process. Further, we establish the relation between first passage time probabilities and MaxVaR, i.e., the intra-horizon risk and obtain the MaxVaR for various index options based on first passage time probabilities. This is important as MaxVaR can capture the risk and potential losses incurred at any time of the trading horizon. In addition, we conduct a sensitivity analysis on the parameters for the purpose of robustness.

Sequestration of gene products by decoys enhances precision in the timing of intracellular events

Expressed gene products often interact ubiquitously with binding sites at nucleic acids and macromolecular complexes, known as decoys. The binding of transcription factors (TFs) to decoys can be crucial in controlling the stochastic dynamics of gene expression. Here, we explore the impact of decoys on the timing of intracellular events, as captured by the time taken for the levels of a given TF to reach a critical threshold level, known as the first passage time (FPT). Although nonlinearity introduced by binding makes exact mathematical analysis challenging, employing suitable approximations and reformulating FPT in terms of an alternative variable, we analytically assess the impact of decoys. The stability of the decoy-bound TFs against degradation impacts FPT statistics crucially. Decoys reduce noise in FPT, and stable decoy-bound TFs offer greater timing precision with less expression cost than their unstable counterparts. Interestingly, when both bound and free TFs decay at the same rate, decoy binding does not directly alter FPT noise. We verify these results by performing exact stochastic simulations. These results have important implications for the precise temporal scheduling of events involved in the functioning of biomolecular clocks, development processes, cell-cycle control, and cell-size homeostasis.