Stopping Time Research Articles

The ability to inhibit and adapt our behavior in response to changing stimuli is a critical component of everyday life. Individuals with Parkinson’s disease (PD) may struggle to inhibit behavior, particularly in the presence of dopaminergic therapy, which can result in impulsive behavior. Impulse control disorders are often operationalized in the laboratory using motor inhibition tasks. However, deficits of motor inhibition tasks are not always observed in PD, perhaps because of the nature of the motor inhibition that is engaged in typical tasks (e.g., suppression of incipient movement such as a button press). We employed a novel continuous movement stop task to investigate planned and unplanned motor inhibition during ongoing movement. EEG was recorded during task performance from individuals with PD (OFF and ON dopaminergic medication) and age-matched healthy controls (HC). Participants were of any sex. We found that the time it took for participants to stop a continuous movement was impaired (i.e., longer) in PD patients ON medication compared with both patients OFF medication and HC. This finding was accompanied by diminished midfrontal theta power following the stop signal in PD (ON and OFF) compared with HC. Additionally, an increase in midfrontal beta power was observed, which was higher in unplanned stopping compared with planned for all groups. However, this increase in beta occurred late—after the time of outright stopping. Together, these findings demonstrate that stopping ongoing movements was impaired in PD patients ON medication and theta and beta power play distinct roles in inhibition of movement.

Abstract The streaming instability (SI), driven by aerodynamic coupling between solids and gas under a global radial pressure gradient, concentrates solids and facilitates planetesimal formation. Unstratified simulations are commonly used to study the SI, based on the assumption that they approximate conditions near the disk midplane. However, it remains unclear how accurately these unstratified simulations capture the midplane dust–gas dynamics in stratified disks. To address this, we examine the saturated state of the SI in stratified simulations and compare the dust–gas dynamics to those in unstratified simulations across various radial pressure gradients. To this end, we consider a dimensionless dust stopping time ( τ s ) of 0.1 and perform 2D axisymmetric, stratified simulations. We find that the formation of dust filaments during dust settling exhibits morphological similarities to those in unstratified simulations. Vertical gravity acts to redistribute momentum vertically in response to momentum flux, resulting in midplane velocities in the center-of-mass frame that are consistent with those from unstratified models at any given pressure gradient. Furthermore, the velocity dispersions and density distributions of the gas and dust near the midplane of our stratified simulations closely match those in unstratified simulations. While further exploration across the parameter space is needed, our results suggest that, for τ s = 0.1, unstratified simulations represent well the midplane dust–gas dynamics in stratified disks before any strong clumping occurs. Consequently, our results confirm that in the saturated state, the streaming turbulence in stratified simulations behaves similarly to that in unstratified simulations for the parameter values explored here.

Abstract A fuzzy logic rolling wheel unlocking algorithm that explicitly incorporates the instantaneous tyre road adhesion coefficient is presented. The controller uses vehicle speed, average deceleration, slip ratio error and its rate of change obtained after online road identification as fuzzy inputs to compute the optimal caliper release time. Hardware in the loop and proving ground tests were conducted at 30 km h−1 and 50 km h−1 on six road surfaces (high μ, low μ, jump μ and split μ). Compared with the conventional logic threshold RWU, the proposed scheme reduces vehicle stopping time by 0.88 s to 3.11 s and increases average deceleration by 9.03% to 45.39% under various road conditions. In summary, compared with the traditional logic threshold rear wheel unlocking control, the proposed fuzzy control algorithm achieves a lower slip ratio and better braking control under different road conditions.

Anti-lock braking systems (ABSs) play a vital role in vehicle safety by preventing wheel lockup and maintaining stability during braking. However, their performance is strongly affected by variations in tire–road friction, which often limits the effectiveness of conventional controllers. This research proposes and evaluates a fuzzy logic controller (FLC)-based ABS using a quarter-vehicle model and the Burckhardt tire–road interaction, implemented in MATLAB/Simulink. Two input variables (slip error and slip rate) and one output variable (brake pressure adjustment) were defined, with triangular and trapezoidal membership functions and 15 linguistic rules forming the control strategy. Simulation results under diverse road conditions—including dry asphalt, concrete, wet asphalt, snow, and ice—demonstrate substantial performance gains. On high- and medium-friction surfaces, stopping distance and stopping time were reduced by more than 30–40%, while improvements of up to 25% were observed on wet surfaces. Even on snow and ice, the system maintained consistent, albeit modest, benefits. Importantly, the proposed FLC–ABS was benchmarked against two recent studies: one reporting that an FLC reduced stopping distance to 258 m in 15 s compared with 272 m in 15.6 s using PID, and another where PID outperformed an FLC, achieving 130.21 m in 9.67 s against 280.03 m in 16.76 s. In contrast, our system achieved a stopping distance of only 24.41 m in 7.87 s, representing over a 90% improvement relative to both studies. These results confirm that the proposed FLC–ABS not only demonstrates clear numerical superiority but also underscores the importance of rigorous modeling and systematic controller design, offering a robust and effective solution for improving braking efficiency and vehicle safety across diverse road conditions.

Abstract Background The demand for high-throughput molecular solutions in infectious diseases testing within high-performance laboratories is escalating. Economically sustainable molecular testing is crucial for ensuring effective public health management and patient care. As laboratories face increasing specimen volumes and complex diagnostic needs, leveraging cost-efficient, automated molecular platforms becomes imperative. These solutions facilitate rapid, accurate pathogen detection, thereby optimizing resource allocation and minimizing operational expenses. The integration of economically viable high-throughput molecular systems supports sustained diagnostic excellence and accessibility, ultimately enhancing healthcare outcomes and delivering long-term value in resource-constrained environments. This study evaluated the impact of cobas® 5800/6800 automated and integrated molecular systems on operational costs in Stopping Time, and Manual Data Management compared to previous molecular platforms in a high-throughput lab in Brazil. Methods Laboratory internal performance data were reviewed to collect the number of unplanned stops and manual data management for a total of 81,302 tests, including HIV (n=11,907), CMV (n=2,656), HPV (n=12,233), and CT/NG (n=54,506), conducted on three cobas® 5800 instruments and one cobas® 6800 instrument. The analysis was conducted considering a three-month period between May and July 2024 when the cobas® 5800/6800 was installed at full automation and integrated with lab management through the system*s digital solutions. Comparative data were obtained from the same period in 2023 when 58,788 tests—HIV (n=9,374), CMV (n=2,875), HPV (n=19,801), and CT/NG (n=26,698)—were performed using previous platforms at full potential. The operational costs involved in the parameters evaluated in the study were estimated considering the cost of manual activities of the Lab’s staff (BRL 31.73/Int$ 12.69). The Brazilian Real values were converted to International Dollars using the latest Purchasing Power Parity conversion rate (2.5) published by the World Bank. Results The automated and integrated cobas® 5800/6800 systems enabled gains in the volume of samples processed, reducing the hands-on time required for routine activities and the frequency of issues. With cobas® 5800/6800 molecular systems, the frequency of stops was reduced from 8 to 3, and the mean stop time was reduced from 87.51 (CI 95 42.98 – 132.49) hours to 17.61 (CI 95 10.01 – 25.20), resulting in a total operational cost saving of Int$ 8,213.88 (-92.4%) in three months. The integration of cobas® 5800/6800 systems with the Lab’s internal management system allowed for a reduction in the hands-on time for manual post-analytical data management. The average time for data management was 5.08 (CI 95 0.00 – 12.64) hours over three months versus 51.58 (CI 95 20.92 – 82.24) hours from the previous systems, resulting in a potential operational cost saving of Int$ 590.18 (-90.14%) in three months. Conclusion The study results demonstrated that cobas® 5800/6800 automated and integrated molecular systems generated substantial cost savings and efficiency improvements, enabling the staff of the high-throughput lab in Brazil to work at their full potential. These findings underscore the value of automated molecular platforms in enhancing laboratory performance and resource utilization. The results could be even better if material costs were estimated, ultimately supporting better healthcare outcomes.

Abstract Background High-performance molecular tests are critical for improving disease detection and management in Brazil, where diverse health challenges exist. Rapid and accurate identification of pathogens is essential for effective treatment strategies and public health interventions. However, transitioning to a new testing platform in Brazilian high-performance laboratories requires a thorough analysis of key factors affecting test lead time. This study compares the turnaround time, number of unplanned stops, and manual data management time for the automated cobas® 5800 and cobas® 6800 molecular systems with the previous routine using platforms from other suppliers for the detection of infectious diseases (HIV, CMV, HPV, and CT/NG). The findings aim to provide insights for optimizing laboratory workflows and enhancing diagnostic throughput. Methods Laboratory internal performance data were reviewed to collect turnaround time, number of unplanned stops, and manual data management for a total of 81,302 tests, including HIV (n=11,907), CMV (n=2,656), HPV (n=12,233), and CT/NG (n=54,506), on three cobas® 5800 instruments and one cobas® 6800 instrument. The analysis was conducted considering a three-month period between May and July 2024 when the cobas® 5800/6800 was installed at its full automation and integration with lab management through the system*s digital solutions. Comparative data were obtained from the same period in 2023 when 58,788 tests—HIV (n=9,374), CMV (n=2,875), HPV (n=19,801), and CT/NG (n=26,698)—were performed using previous platforms at their full potential. The results were analyzed for both timeframes. Results The average turnaround time for the cobas® 5800/6800 systems was 1.88 days (CI 95 1.73 – 1.95), whereas it was 4.09 days (CI 95 2.79 – 5.39) with the previous molecular routine, marking an average reduction of 2.21 days (p<0.05). These improvements in TAT contributed to enhanced laboratory performance, achieving an average release of 1,662.7 (CI 95 1,518 – 1,806) test results per day with cobas® 5800/6800, compared to 781.2 (CI 95 704 – 858) results per day using the previous systems. The automated functionality of cobas® 5800/6800 also led to fewer unplanned stops, with average stop time reduced to 17.61 (CI 95 10.01 – 25.20) hours from 87.51 (CI 95 42.98 – 132.49) hours previously, resulting in an average decrease of 69.89 hours (p<0.05) in the three months observed. Additionally, post-analytical data management time was significantly reduced due to automation and system integration; the average time for data management was 5.08 (CI 95 0.00 – 12.64) hours over three months versus 51.58 (CI 95 20.92 – 82.24) hours from the previous systems. Conclusion Implementing automated molecular systems such as cobas® 5800/6800 can substantially enhance the performance of high-throughput infectious disease molecular testing in Brazil. Data integration through digital solutions promoted better management of processes and eventual issues and improved the data management of results. The transition results in significant reductions in TAT, unplanned stopping time, and manual data management, all contributing to improved laboratory efficiency and diagnostic capacity. These gains underscore the value of technological advancements in supporting effective disease management in diverse healthcare settings.

Braking systems are critical for vehicle safety, with brake pads influencing performance, durability, and environmental impact. This study compares organic and sintered brake pads, analyzing tribological properties, thermal stability, and wear resistance. Organic pads, made from synthetic fibers and resins, offer low noise and environmental benefits but degrade faster under heat. Sintered pads, composed of fused powdered metals, exhibit superior heat resistance, durability, and braking consistency under extreme conditions. Testing included dynamometer evaluations, measuring stopping distance, deceleration, braking pressure, and temperature variations. Sintered pads maintained a stable coefficient of friction, lower stopping distances, and consistent deceleration over time, requiring less hydraulic pressure for equivalent braking force. Organic pads wore faster and showed increased stopping times. The findings highlight sintered pads as ideal for high-performance applications, while organic pads remain suitable for cost-sensitive, noise-conscious environments, contributing to advancements in automotive safety and sustainable braking solutions.

This study proposes a novel and cohesive framework to address stochastic finite-time consensus (FTC) problems, with the following main contributions: (1) We first introduce the original stochastic delay systems and, based on this, analyze the effects of Lévy noise, actuator faults, and Markov switching. Both leaderless and leader-follower topologies are considered, and a new control algorithm is proposed to investigate the fault-tolerant control problem under the influence of communication delays and Markov switching dynamics. (2) To ensure that the states converge to a bounded compact set, the convergence analysis uses strong mathematical techniques, such as stopping time theory and the evolution of finite-time stochastic theory, to achieve mean-square and almost certain consensus. (3) An important aspect of this study is the consideration of Markov-switching actuator faults, where fault occurrence and recovery evolve randomly according to a Markov process, introducing additional stochastic uncertainties into the system dynamics. Additionally, two numerical examples are provided to validate the correctness of the theoretical results.

Nd2O3 doped Al2O3–Na2O–WO3–B2O3 glasses which were produced by melt quenching technique was studied for determining their charged particle, neutron and gamma-ray shielding characteristics. In this context, the radiation-attenuating parameters were calculated by the help of PENELOPE, Phy-X/PSD, SRIM and PAGEX codes. The effect of neodymium on the glasses were evaluated and compared comprehensively. The results demonstrated a linear correlation between the shielding efficiencies of charged particles - specifically alpha, electron, proton particles; gamma rays; and neutrons - and the neodymium content present in the samples. The glasses with the higher content of neodymium displayed better protection potential. The order of mass stopping power results of the glasses were found for the charged particles as MSPalpha > MSPprotons > MSPpositrons > MSPelectrons. The glass without Nd composition showed maximal range values for charged particles, whereas the glass with higher Nd composition demonstrated the minimal values. The largest stopping time values were obtained in the following order: Stpositron > Stelectron. The biggest stopping time value was observed for the glass without Nd. The glass with higher Nd exhibits the highest fast neutron attenuation. It can be posited that each of the glasses in question could be employed as shields in various application fields.

Molecular motors are in charge of almost every process in the life cycle of cells, such as protein synthesis, DNA replication, and cell locomotion, hence being of crucial importance for understanding the cellular dynamics. However, given their size scales on the order of nanometers, direct measurements are rather challenging, and the information that can be extracted from them is limited. In this work, we propose strategies based on martingale theory in stochastic thermodynamics to infer thermodynamic properties of molecular motors using a limited amount of available information. In particular, we use two recent theoretical results valid for systems arbitrary far of equilibrium: the integral fluctuation theorem at stopping times and a family of bounds to the maximal excursions of entropy production. The potential of these strategies is illustrated with a simple model for the F1-ATPase rotary molecular motor, where our approach is able to estimate several quantities determining the thermodynamics of the motor, such as the rotational work of the motor performed against an externally applied force or the effective environmental temperature.

Stopping time and control for impulsive stochastic differential equations and biosciences applications

Abstract We prove two-sided bounds on the expected values of several geometric functionals of the convex hull of Brownian motion in $\mathbb {R}^n$ and their inverse processes. This extends some recent results of McRedmond and Xu (2017), Jovalekić (2021), and Cygan, Šebek, and the first author (2023) from the plane to higher dimensions. Our main result shows that the average time required for the convex hull in $\mathbb {R}^n$ to attain unit volume is at most $n\sqrt [n]{n!}$ . The proof relies on a novel procedure that embeds an n-simplex of prescribed volume within the convex hull of the Brownian path run up to a certain stopping time. All of our bounds capture the correct order of asymptotic growth or decay in the dimension n.

Abstract In a finite-horizon optimal stopping problem the optimal stopping time is typically given by the first moment at which a sufficient statistic, namely a process containing all the relevant information on the problem, exceeds an unknown time-dependent boundary. This boundary often turns out to be the solution of a highly nonlinear integral equation involving the transition density of the sufficient statistic. When this density cannot be computed directly or easily, standard methods for solving the integral equation must be modified. This situation arises in sequential detection problems and in the pricing of certain derivative securities, where the corresponding sufficient statistics follow the so called Shiryaev process. In this context, we analyze and implement three distinct numerical methods for solving the integral equations characterizing the associated optimal stopping boundaries: two of them rely on solutions to partial differential equations, while the third is based on approximating the distribution of the sufficient statistic using a log-normal distribution. We demonstrate that these approaches return accurate results and are generally efficient.

Abstract We consider the piecewise-deterministic Markov process obtained by randomly switching between the flows generated by a finite set of smooth vector fields on a compact set. We obtain Hörmander-type conditions on the vector fields guaranteeing that the stationary density is: Ck whenever the jump rates are sufficiently fast, for any k < ∞ ; unbounded whenever the jump rates are sufficiently slow and lower semicontinuous regardless of the jump rates. Our proofs are probabilistic, relying on a novel application of stopping times.

We consider the d-posterior approach to the classical problem of estimating the Poisson distribution parameter for a 1-0 type loss function. A constraint on the relative error is imposed, and a prior gamma distribution of the estimated parameter is assumed. We construct a Bayesian estimator and a continuous analogue of an estimator with a uniformly minimal d-risk. The d-risk functions of these estimators are calculated. It is established that for small values of the prior distribution shape parameter and fixed sample size, there is no estimate that guarantees the given constraint on the d-risk. We propose to use a universal sequential d-guaranteed estimation procedure, and we find the distribution of the stopping time and the average sample size for this procedure.

In this paper, we address the optimal consumption, investment, and labor-leisure decision of an economic agent who does not allow a decrease in consumption. The agent has a Cobb-Douglas utility function dependent on consumption and leisure. Additionally, the agent's income is determined proportionally to the working time, which is the remaining time after enjoying leisure from the total available time for labor and leisure. Since consumption is a non-decreasing process, the agent's utility maximization problem is formulated as a two-dimensional stochastic and singular control problem. To tackle this non-trivial problem, we apply the dual-martingale approach to derive a dual problem represented as a two-dimensional pure singular control problem. By utilizing the relationship between the non-decreasing process and a collection of stopping times, we obtain the explicit-form solution for the dual problem. Finally, by establishing the duality theorem, we also derive the explicit-form optimal strategies.

We propose a sequential monitoring scheme to detect changes in dynamic semiparametric risk models that capture Value–at–Risk (VaR) and Expected Shortfall (ES) jointly. The monitoring scheme is based on a gradient–based detector and a boundary function, and a change is detected when the detector crosses the boundary function. We derive the asymptotic limit of the stopping time of detection under the null hypothesis of no change. Monte Carlo simulations show that the proposed test has reasonable size control under the null hypothesis and high power under alternative hypotheses of various change point scenarios in finite samples. Empirical applications based on the S&P 500 index and the GBP/EUR exchange rate illustrate that our proposed test is able to detect change points in real–time.

Abstract In this paper we study the optimal multiple stopping problem with weak regularity for the reward, where the reward is given by a set of random variables indexed by stopping times. When the reward family is upper semicontinuous in expectation along stopping times, we construct the optimal multiple stopping strategy using the auxiliary optimal single stopping problems. We also obtain the corresponding results when the reward is given by a progressively measurable process.

This report documents the unimodal shape of two discrete functions related to the number of binary sequences under a certain bit-scoring scheme along with some attempts to prove the unimodality rigorously. While a completely general proof is not yet in hand, we state several monotonicity properties for certain related, novel discrete distributions which imply the main results and which we conjecture hold true in general. Connections to sequential stopping times under required conditioning events are discussed and evaluated for their ability to establish the results. The “blimpy” shape of the number of bit strings with a given score as a function of the score is explained and accurately approximated with a four-parameter model.

This study presents a modular brake disc assembly designed to improve the performance characteristics of automotive spot-type disc brake systems. We examined disc brake system configurations in 2017 fifth-generation Ford Explorer vehicles. Three principal limitations of conventional brake discs were identified: excessive thermal gradients and internal stresses within disc components, non-repairable structural designs, and insufficient heat transfer from friction surfaces during operation. To address these challenges, we employed the theory of inventive problem solving (TRIZ), which led to the development of a modular decomposition approach for principal structural elements of the brake disc. The design process involved 3D modelling techniques within the KOMPAS-3D v21 educational software package, which facilitates comprehensive virtual prototyping and analysis. Finite element meshing and subsequent static strength calculations, using the von Mises criteria, revealed stress-strain distribution zones in the developed components of the modular brake disc assembly. The findings underscore the importance of enhancing structural design and selecting materials with optimal physical properties, including density, yield strength, elastic modulus, and thermal conductivity. This approach would reduce the inertial masses of components and the unsprung masses of the vehicle, while increasing the guaranteed safety factor and improving heat dissipation from the friction pairs in spot-type disc brake systems. In addition, 3D printing methods with wax-like filaments, essential for investment casting in steel production, were reviewed and applied. The study demonstrates that the selection of optimal materials enhances braking efficiency and reduces the stopping distance and time of a vehicle when using the proposed design. Recommendations for print settings and modes are also provided.