Passage Time Research Articles

Simulation of urban surface temperature and surface heat balance in the Tokyo metropolitan area

This study aimed to propose a method for simulating ground surface temperature and surface heat balance using thermal infrared remote sensing and an urban surface heat balance model and to conduct a simulation in the Tokyo metropolitan area. Previous studies have typically employed ground surface temperatures obtained through satellite remote sensing to analyze urban thermal environments. However, these studies were limited to using surface temperature data available only at the time of satellite passage. Therefore, in this study, we conducted a simulation for the Tokyo metropolitan area by integrating a one-dimensional heat balance model with ground surface temperatures observed by satellites. The novelty of this study lies in the utilization of parameters related to heat balance obtained through calculations of physical processes, as opposed to relying on empirical formulas or parameters. Consequently, realistic ground surface characteristics, including parameters such as evaporation efficiency and thermal inertia essential for the simulation, were derived by this combined method. Furthermore, diurnal variations in ground surface temperature distributions were accurately represented by using realistic surface temperature data based on satellite remote sensing, considering the effect of heat storage in urban areas—an aspect challenging to reproduce using conventional local meteorological models.

Delay Segmented Tristable Stochastic Resonance System Driven by Non-Gaussian Colored Noise and Its Application in Bearing Fault Detection

Abstract This study investigates the Delayed Segmented Tristable Stochastic Resonance (DSTSR) system under the influence of additive non-Gaussian colored noise. The research employs an improved segmented tristable potential function, wherein the equilibrium points and barrier heights can be independently controlled by parameters. Simultaneously, the segmented function on both sides reduces the restrictions of higher-order terms on the walls of the potential wells. The equivalent Langevin equation for the DSTSR system is obtained using the path integral method, the unified colored noise approximation method, and the small-delay approximation. Subsequently, the theoretical expressions for the steady-state probability density, mean first passage time (MFPT), and Signal-to-Noise Ratio (SNR) are derived from the resulting equations, and the impact of variations in system parameters on these performance metrics is discussed. Additionally, Monte Carlo simulations for MFPT are conducted to verify the accuracy of the theoretical derivations. Combining the results from the theoretical section and the impact of parameters on system performance, the article employs an adaptive genetic algorithm to optimize system parameters. This algorithm is then applied to simulation experiments and bearing fault detection. In the simulation experiments, the DSTSR system is compared with other systems. The results indicate that the DSTSR system exhibits the highest SNR improvement. Furthermore, in bearing fault detection under non-Gaussian colored noise, the DSTSR system shows higher spectral amplitude and SNR at the fault frequency compared to the tristable stochastic resonance system and the segmented tristable stochastic resonance system without time delay feedback. This suggests that stochastic resonance can effectively detect weak signals in non-Gaussian non-white noise scenarios, and the introduction of time delay contributes to the occurrence of stochastic resonance to a certain extent.

A non-oriented first passage percolation model and statistical invariance by time reversal

We introduce and study a non-oriented first passage percolation model having a property of statistical invariance by time reversal. This model is defined in a graph having directed edges and the passage times associated with each set of outgoing edges from a given vertex are distributed according to a generalized Bernoulli–Exponential law and i.i.d. among vertices. We derive the statistical invariance property by time reversal through a zero-temperature limit of the random walk in Dirichlet environment model.

Matrix numerical method for probability densities of stochastic delay differential equations

Stochastic processes with time delay are invaluable for modeling in science and engineering when finite signal transmission and processing speeds can not be neglected. However, they can seldom be treated with sufficient precision analytically if the corresponding stochastic delay differential equations (SDDEs) are nonlinear. This work presents a numerical algorithm for calculating the probability densities of processes described by nonlinear SDDEs. The algorithm is based on Markovian embedding and solves the problem by basic matrix operations. We validate it for a broad class of parameters using exactly solvable linear SDDEs and a cubic SDDE. Besides, we show how to apply the algorithm to calculate transition rates and first passage times for a Brownian particle diffusing in a time-delayed cusp potential.

Stochastic dynamics of phycocyanin in years of contrasting phosphorus load

AbstractResilience, measured by the distribution of passage times between alternate states, indicates persistence of a state in stochastic dynamic systems such as blooms of cyanobacteria in lakes. We used high‐frequency datasets to compare the resilience of low and high states of phycocyanin, a pigment indicator of cyanobacteria, in Lake Mendota, Wisconsin, USA, for three growing seasons that ranged sevenfold in external phosphorus (P) load. Each year we observed 139–265 passage times across the unstable threshold that separated the low‐ from high‐phycocyanin states. Each sample of passage times is highly skewed with low median, larger mean, much larger SD, and wide tails extending to long lifetimes of a state. About 25% of events, whether low or high phycocyanin, lasted a day or more. Among these 3 years of contrasting external P load, there were no discernible differences in the resilience of either ecosystem state. We attribute this lack of contrast to the sustained recycling of P from sediments and the high stochasticity of phycocyanin in this lake.

SEMG as complementary tool for VFSS: A synchronized study in patients with neurogenic oropharyngeal dysphagia

The neurogenic oropharyngeal dysphagia is a prevalent functional swallowing disorder resulting from neurological causes. The conventional diagnosis involves ionizing radiation in Videofluoroscopy Swallowing Studies (VFSS). Surface electromyography (sEMG) offers a non-invasive alternative by recording muscle activity. This research compares bolus passage timing through anatomical structures using VFSS and sEMG-related activation times. Fifty confirmed oropharyngeal dysphagia patients underwent synchronized VFSS and sEMG, evaluating muscle groups during cracker and fluid ingestion. sEMG revealed activation patterns in masseters, suprahyoid, and infrahyoid muscles, occurring before bolus passage through the mandibular line and concluding near the upper esophageal sphincter complex. sEMG identified differences in dysphagia severity (EAT-10 score), age, and diagnosis, contrasting VFSS results. Results indicate potential complementarity between sEMG and VFSS for dysphagia screening, diagnosis, and monitoring.

АНАЛИЗ ТЕХНИЧЕСКИХ РЕШЕНИЙ ДЛЯ ПОВЫШЕНИЯ ЭФФЕКТИВНОСТИ РАБОТЫ ВОДОГРЕЙНЫХ КОТЛОВ ДЛЯ СЖИГАНИЯ ОТХОДОВ В НЕПОДВИЖНОМ СЛОЕ И ВЫБОР КОНСТРУКЦИИ ГАЗОХОДА ДЛЯ РАЗРУШЕНИЯ ВРЕДНЫХ ВЕЩЕСТВ В ПРОДУКТАХ СГОРАНИЯ

The purpose of the work is to analyze technical solutions used to improve the efficiency of hot water boilers for waste combustion. As a result of the analysis of available design solutions for low-power water heating boilers, in which waste is burned in a fixed bed, their main disadvantages were identified: low combustion temperature; ineffective heat transfer from combustion products to the coolant; contamination of flues and heating surfaces; incomplete combustion of fuel; the impossibility of accurately regulating the combustion process, which leads to the formation of a large amount of harmful emissions and a decrease in the heat output and efficiency of the boiler. It is proposed to install a flue after firing the boiler, in which the gases will remain for more than 2 seconds and the organic harmful substances contained in the combustion products will be completely destroyed. To determine the passage time and select the optimal design of the gas duct, a numerical simulation of the movement of the gas flow was carried out using the developed numerical model implemented in the ANSYS Fluent software package. To ensure uniformity of the gas flow in the gas duct, options with different heights of the window between the firebox and the gas duct and the installation of a dividing partition in the gas duct to organize two-pass gas movement were considered. The best results were obtained for a horizontal flue. For further design development and search for ways to increase the residence time of gas in the gas duct, the most effective option with a horizontal gas duct was chosen.

Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook.

Confinement can substantially alter the physicochemical properties of materials by breaking translational isotropy and rendering all physical properties position-dependent. Molecular dynamics (MD) simulations have proven instrumental in characterizing such spatial heterogeneities and probing the impact of confinement on materials' properties. For static properties, this is a straightforward task and can be achieved via simple spatial binning. Such an approach, however, cannot be readily applied to transport coefficients due to lack of natural extensions of autocorrelations used for their calculation in the bulk. The prime example of this challenge is diffusivity, which, in the bulk, can be readily estimated from the particles' mobility statistics, which satisfy the Fokker-Planck equation. Under confinement, however, such statistics will follow the Smoluchowski equation, which lacks a closed-form analytical solution. This brief review explores the rich history of estimating profiles of the diffusivity tensor from MD simulations and discusses various approximate methods and algorithms developed for this purpose. Besides discussing heuristic extensions of bulk methods, we overview more rigorous algorithms, including kernel-based methods, Bayesian approaches, and operator discretization techniques. Additionally, we outline methods based on applying biasing potentials or imposing constraints on tracer particles. Finally, we discuss approaches that estimate diffusivity from mean first passage time or committor probability profiles, a conceptual framework originally developed in the context of collective variable spaces describing rare events in computational chemistry and biology. In summary, this paper offers a concise survey of diverse approaches for estimating diffusivity from MD trajectories, highlighting challenges and opportunities in this area.

Effects of transcutaneous electrical nerve stimulation on recovery of gastrointestinal motility after laparotomy: Arandomized controlled trial.

Postoperative Ileus (POI) negatively impacts patient outcomes and increases healthcare costs. Transcutaneous electrical nerve stimulation (TENS) has been found to improve gastrointestinal (GI) motility following abdominal surgery. However, its effectiveness in this context is not well-established. This study was designed to evaluate the role of TENS on the recovery of GI motility after exploratory laparotomy. Patients undergoing exploratory laparotomy were randomized in a 1:1 ratio into control (standard treatment alone) and experimental (standard treatment+TENS) arms. TENS was terminated after 6days or after the passage of stool or stoma movement. The primary outcome was time for the first passage of stool/functioning stoma. Non-passage of stool or nonfunctioning stoma beyond 6days was labeled as prolonged POI. Patients were monitored until discharge. Median (interquartile range) time to first passage of stool/functioning stoma was 82.6 (49-115) hours in the standard treatment group and 50 (22-70.6) hours in the TENS group [p<0.001]. Prolonged POI was noted in 11 patients in the standard treatment group (35.5%) and one in the TENS group (3.2%) [p=0.003]. Postoperative hospital stay was similar in the two groups. TENS resulted in early recovery of GI motility by shortening the duration of POI without any improvement in postoperative hospital stay. CTRI/2021/10/037054.

Qi Lang formula relieves constipation via targeting SCF/c-kit signaling pathway: An integrated study of network pharmacology and experimental validation

BackgroundConstipation is one of the chronic gastrointestinal functional diseases that affects the quality of life. While Qi Lang Formula (QLF) has demonstrated effectiveness in alleviating constipation symptoms, its precise mechanism remains elusive. MethodsQLF was analyzed using UPLC-MS/MS. Targets for QLF were collected from SwissADME, Herb, ITCM databases, and constipation-related targets from scRNA-seq and Genecards databases. Overlapping targets suggested potential QLF therapy targets for constipation. Enrichment analysis used the KOBAS database. A "drug-ingredient-target" network was constructed with Cytoscape, and AutoDock verified active ingredient binding. H&E staining assessed colonic mucosa changes, TEM examined ICC structural changes. ELISA measured neurotransmitter levels, and Western blot verified QLF's effect on target proteins. ICC proliferation was observed through immunofluorescence. ResultsWe identified 89 targets of QLF associated with ICC-related constipation, with c-Kit emerging as the pivotal target. Molecular docking studies revealed that Atractylenolide Ⅲ, Apigenin, Formononetin, Isorhamnetin, Naringenin, and Ononin exhibited strong binding affinities for the c-Kit structural domain. QLF significantly enhanced first stool passage time, fecal frequency, fecal moisture content, and intestinal propulsion rate. Further analysis unveiled that QLF not only restored neurotransmitter levels but also mitigated colon muscular fiber ruptures. ICC ultrastructure exhibited partial recovery, while Western blot confirmed upregulated c-Kit expression and downstream targets. Immunofluorescence results indicated ICC proliferation post QLF treatment in rat colon. ConclusionOur findings suggest that QLF may promote ICC proliferation by targeting SCF/c-Kit and its downstream signaling pathway, thereby regulating intestinal motility.

Pricing vulnerable lookback options using Laplace transforms

This study develops a closed-form solution for pricing vulnerable lookback options, which combines the Black–Scholes model for the underlying asset and a correlated jump–diffusion model for the issuer’s asset to account for default risks. Our approach relies on applying Laplace transforms to establish a closed-form solution and compute them numerically using Laplace inversion algorithms. To determine the price, we derive the joint distribution of the first passage time of a drifted Brownian motion and the value of the correlated jump–diffusion. Through numerical examples, we demonstrate the accuracy of the numerical solutions obtained through our method and the stability of the algorithm. Subsequently, we conduct a numerical analysis to understand how counterparty risk influences option prices based on our formula.

First passage times for continuous quantum measurement currents

First passage times for continuous quantum measurement currents

Hydrogen bonding heterogeneity correlates with protein folding transition state passage time as revealed by data sonification

Protein-protein and protein-water hydrogen bonding interactions play essential roles in the way a protein passes through the transition state during folding or unfolding, but the large number of these interactions in molecular dynamics (MD) simulations makes them difficult to analyze. Here, we introduce a state space representation and associated "rarity" measure to identify and quantify transition state passage (transit) events. Applying this representation to a long MD simulation trajectory that captured multiple folding and unfolding events of the GTT WW domain, a small protein often used as a model for the folding process, we identified three transition categories: Highway (faster), Meander (slower), and Ambiguous (intermediate). We developed data sonification and visualization tools to analyze hydrogen bond dynamics before, during, and after these transition events. By means of these tools, we were able to identify characteristic hydrogen bonding patterns associated with "Highway" versus "Meander" versus "Ambiguous" transitions and to design algorithms that can identify these same folding pathways and critical protein-water interactions directly from the data. Highly cooperative hydrogen bonding can either slow down or speed up transit. Furthermore, an analysis of protein-water hydrogen bond dynamics at the surface of WW domain shows an increase in hydrogen bond lifetime from folded to unfolded conformations with Ambiguous transitions as an outlier. In summary, hydrogen bond dynamics provide a direct window into the heterogeneity of transits, which can vary widely in duration (by a factor of 10) due to a complex energy landscape.

Exploring Biomolecular Conformational Dynamics with Polarizable Force Field AMOEBA and Enhanced Sampling Method Milestoning.

Conformational dynamics play a crucial role in determining the behavior of the biomolecules. Polarizable force fields, such as AMOEBA, can accurately capture electrostatic interactions underlying the conformational space. However, applying a polarizable force field in molecular dynamics (MD) simulations can be computationally expensive, especially in studying long-time-scale dynamics. To overcome this challenge, we incorporated the AMOEBA potential with Milestoning, an enhanced sampling method in this work. This integration allows us to efficiently sample the rare and important conformational states of a biomolecule by using many short and independent molecular dynamics trajectories with the AMOEBA force field. We applied this method to investigate the conformational dynamics of alanine dipeptide, DNA, and RNA A-B form conversion. Well-converged thermodynamic and kinetic properties were obtained, including the free energy difference, mean first passage time, and critical transitions between states. Our results demonstrate the power of integrating polarizable force fields with enhanced sampling methods in quantifying the thermodynamic and kinetic properties of biomolecules at the atomic level.

Smoothing in linear multicompartment biological processes subject to stochastic input.

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before the eventual accumulation and release of replicated virions. While such systems may have some control over the internal dynamics that make up this progression, a challenge for many is to regulate behavior under what are often highly variable external environments acting as system inputs. In this work, we study a simple analog of this problem through a linear multicompartment model subject to a stochastic input in the form of a mean-reverting Ornstein-Uhlenbeck process, a type of Gaussian process. By expressing the system as a multidimensional Gaussian process, we derive several closed-form analytical results relating to the covariances and autocorrelations of the system, quantifying the smoothing effect discrete compartments afford multicompartment systems. Semianalytical results demonstrate that feedback and feedforward loops can enhance system robustness, and simulation results probe the intractable problem of the first passage time distribution, which has specific relevance to eventual cell lysis in the viral replication cycle. Finally, we demonstrate that the smoothing seen in the process is a consequence of the discreteness of the system, and does not manifest in systems with continuous transport. While we make progress through analysis of a simple linear problem, many of our insights are applicable more generally, and our work enables future analysis into multicompartment processes subject to stochastic inputs.

Label-free detection and profiling of individual solution-phase molecules.

Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques1 are uniquely suited to resolving molecular diversity and new label-free approaches are reshaping the power of single-molecule measurements. A label-free single-molecule method2-16 capable of revealing details of molecular conformation in solution17,18 would allow a new microscopic perspective of unprecedented detail. Here we use the enhanced light-molecule interactions in high-finesse fibre-based Fabry-Pérot microcavities19-21 to detect individual biomolecules as small as 1.2 kDa, a ten-amino-acid peptide, with signal-to-noise ratios (SNRs) >100, even as the molecules are unlabelled and freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of subpopulations in mixed samples. Notably, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight and composition but different conformation can also be resolved. Detection is based on the creation of a new molecular velocity filter window and a dynamic thermal priming mechanism that make use of the interplay between optical and thermal dynamics22,23 and Pound-Drever-Hall (PDH) cavity locking24 to reveal molecular motion even while suppressing environmental noise. New in vitro ways of revealing molecular conformation, diversity and dynamics can find broad potential for applications in the life and chemical sciences.

Non-Markovian gene expression

We study two non-Markovian gene-expression models in which protein production is a stochastic process with a fat-tailed nonexponential waiting time distribution (WTD). For both models, we find two distinct scaling regimes separated by an exponentially long time, proportional to the mean first passage time (MFPT) to a ground state (with zero proteins) of the dynamics, from which the system can only exit via a nonexponential reaction. At times shorter than the MFPT the dynamics are stationary and ergodic, entailing similarity across different realizations of the same process, with an increased Fano factor of the protein distribution, even when the WTD has a finite cutoff. Notably, at times longer than the MFPT the dynamics are nonstationary and nonergodic, entailing significant variability across different realizations. The MFPT to the ground state is shown to directly affect the average population sizes and we postulate that the transition to nonergodicity is universal in such non-Markovian models. Published by the American Physical Society 2024

Droplet dynamics passing through the flexible constriction in the channel

We conducted a numerical investigation into droplet dynamics within a flexible constriction using the phase-field lattice Boltzmann method. Our study focused on constriction bending stiffness, Weber number, and constriction-to-droplet diameter ratio. Flexibility impedes droplet passage at low Weber numbers but significantly facilitates it at moderate and high Weber numbers. Passage times decrease with increasing Weber numbers and are proportional to the droplet's maximum deformed length. An anomalous phenomenon is observed: “more haste, less speed.” The underlying mechanics arising from the interaction between the flexible constriction and the droplet are elucidated. The findings enhanced our understanding of droplet behavior in constrained environments.

More Is Faster: Why Population Size Matters in Biological Search.

Many biological scenarios have multiple cooperating searchers, and the timing of the initial first contact between any one of those searchers and its target is critically important. However, we are unaware of biological models that predict how long it takes for the first of many searchers to discover a target. We present a novel mathematical model that predicts initial first contact times between searchers and targets distributed at random in a volume. We compare this model with the extreme first passage time approach in physics that assumes an infinite number of searchers all initially positioned at the same location. We explore how the number of searchers, the distribution of searchers and targets, and the initial distances between searchers and targets affect initial first contact times. Given a constant density of uniformly distributed searchers and targets, the initial first contact time decreases linearly with both search volume and the number of searchers. However, given only a single target and searchers placed at the same starting location, the relationship between the initial first contact time and the number of searchers shifts from a linear decrease to a logarithmic decrease as the number of searchers grows very large. More generally, we show that initial first contact times can be dramatically faster than the average first contact times and that the initial first contact times decrease with the number of searchers, while the average search times are independent of the number of searchers. We suggest that this is an underappreciated phenomenon in biology and other collective search problems.

Effect of total dissolved gas supersaturation on the passage behavior of silver carp (Hypophthalmichthys molitrix) and ya-fish (Schizothorax prenanti) through an experimental vertical slot fishway

Total dissolved gas (TDG) supersaturation caused by flood discharge water poses a threat to vital activities such as migration, foraging, and evasion in fish species upstream of the Yangtze River, which may impair the ability of fish to pass through fishways during the migration period, causing poor utilization of fishways. Previous studies have shown that TDG supersaturation reduces the critical and burst swimming abilities of fish, suggesting potential adverse effects on swimming performance. However, studies focusing on the impact of TDG on fish swimming behavior in experimental vertical-slot fishways remain scarce. Therefore, in this study, silver carp (Hypophthalmichthys molitrix) and ya-fish (Schizothorax prenanti) were used as the study species, and comparative passage experiments were carried out in an experimental vertical slot fishway to systematically analyze the effects of TDG supersaturation on their passage behavior. The passage success of the silver carp was 57%, 39%, 26%, and 27% at TDG levels of 100%, 110%, 120%, and 130%, respectively. Passage success of ya-fish was 73%, 37%, 31%, and 35% at TDG concentrations of 100%, 110%, 120%, and 130%, respectively. The passage time for both species increased significantly with increasing TDG levels. Furthermore, the passage routes of silver carp changed significantly compared to the control group, whereas the passage routes of ya-fish changed insignificantly. High levels of TDG supersaturation (≥120%) also contributed to a higher mortality rate of ya-fish passing through the vertical slot fishway. The research results provide valuable data on the influence of TDG supersaturation on fish movement behavior responses in experimental vertical slot fishways, offering a reference for the design of fishways and the formulation of reservoir operation schemes.