搜索结果：overtakes

Cell growth and division are tightly coordinated to cell size. In budding yeast, increasing cell size promotes the G1/S transition, called Start, by activating the transcription factor SBF, which drives a large fraction of cell-cycle-dependent gene expression. Part of this regulation arises because the concentration of the SBF inhibitor Whi5 decreases as cells grow. However, cells lacking Whi5 can still maintain a relatively accurate size when the SBF activator Cln3 is also removed, indicating that there are additional size control mechanisms. To understand how cell size is mechanistically translated into the activity of SBF-regulated promoters, we quantified the binding kinetics of Whi5 and SBF in live cells using single-molecule fluorescence microscopy. We found that increasing cell size is associated with both a decreased chromatin affinity of Whi5 and an increased chromatin affinity of SBF, accompanied by a higher SBF:Whi5 cell copy-number ratio. Chromatin-binding trends under basal and Whi5 overexpression conditions indicate that Whi5 restricts SBF association with chromatin. The transition point at which SBF binding overtakes Whi5 binding coincides with the onset of the expression of the G1 cyclins CLN1 and CLN2, two SBF targets that are important for committing cells to division. Reduced Whi5 binding reflects changes in its chromatin-association rate, as Whi5 and SBF dwell times on chromatin remain ~10 s and are largely independent of cell size. Together, these results show how changes in SBF and Whi5 abundance and chromatin association transmit cell size information to the genome to regulate the size-dependent Start transition in budding yeast.

The Mpemba effect, an example of anomalous thermal relaxation, occurs when a system prepared at a higher temperature overtakes an identical system prepared at a lower temperature and cools down faster to the environment's temperature. We explore the Mpemba effect within Markov jump processes on linear reaction networks and study the effect as a function of the relaxation dynamics. The dynamics are characterized by a load distribution factor introduced to modulate the transition rates in a manner that obeys detailed balance. We analytically diagonalize the dynamical generator of three-species unimolecular reactions and, through graphic exploration of parameters, identify the regimes in which the Mpemba effect occurs. In particular, we find that the regions of the strong variant of the Mpemba effect, known as the strong Mpemba effect, in cooling and heating are nonoverlapping and that there is, at most, a single strong Mpemba temperature. Furthermore, we demonstrate our findings using a Maxwell demon setup. In this context, we demonstrate that leveraging the strong Mpemba effect can lead to shorter cycles of the Maxwell demon device, thereby enhancing power output without compromising the stability of device operation or its efficiency.

The "neck" region of kinesin is a structurally conserved element critical for force generation, stepping directionality, and cargo transport along microtubules, yet its atomic-scale structure in a functional context remains unresolved. Here, we employ all-atom replica exchange molecular dynamics simulations to resolve a high-confidence neck-region conformation of the dimeric human kinesin-1 bound to a structurally realistic microtubule lattice and subsequently use this structure to simulate kinesin's initial stepping motion. Our simulations reveal that the neck coiled coil is oriented perpendicular to the microtubule's long axis and positioned in close proximity to the microtubule surface-a conformation consistent with earlier experimental proposals but previously lacking high-resolution validation. Importantly, simulations of kinesin's initial stepping indicate that interactions between the neck region and the microtubule surface decisively bias the stepping trajectory, directing the rear kinesin head to overtake the front head from the right side (counterclockwise stepping). These findings establish a direct structural mechanism by which neck region-microtubule interactions govern the directional bias of kinesin's initial stepping, providing fundamental new insight into the molecular basis of its motility.

As a typical biomimetic robotic system, quadruped robots replicate the flexible locomotion of quadruped mammals, outperforming wheeled robots in human-centered daily scenarios. To improve the social navigation adaptability of biomimetic quadruped robots in human-robot shared environments, this paper proposes a collision-aware orthogonal steering social force model (COSFM), an enhanced social force model that integrates collision prediction and social norms, inspired by human-like collision avoidance behaviors and social interaction rules. The model addresses key limitations of conventional social force models: delayed responses to dynamic pedestrians and inadequate consideration of pedestrians' comfort zones. It introduces a time-to-collision prediction mechanism to mimic human predictive decision-making in dynamic social interactions, enhancing the robot's anticipation of pedestrian motion intentions, and designs an orthogonal steering-based avoidance strategy for four typical human-robot interaction scenarios (head-on encounters, intersecting paths, active overtaking, passive yielding). This strategy replicates humans' natural priority of lateral steering over abrupt deceleration or retreat, generating socially compliant trajectories aligned with human behavioral expectations. The proposed method is validated via simulation and real-world experiments on a Unitree Aliengo quadruped robot. Results show that the COSFM algorithm achieves a higher navigation success rate and better performance in path length, navigation time, and minimum human-robot distance than existing approaches, while its human-like lateral avoidance priority effectively preserves pedestrians' psychological comfort zones, demonstrating robust social adaptability and great application potential for biomimetic legged robots.

Obesity, officially recognised as a global epidemic by the World Health Organization, will soon overtake smoking as the largest preventable risk factor for cancer. By 2035, more than half the world's population is expected to be overweight or obese with a significant increase in obesity-related health expenditures. However, despite the increase in prevalence and the overall lower life expectancy associated with obesity, mechanisms underpinning obesity-driven diseases are not well understood. Adipocytes pose many challenges for in vitro culture due to their poor cell-to-surface attachment and low viability. Their large size and high lipid content can also present methodological challenges for downstream experiments. Several mouse and human-derived primary pre-adipocyte cell lines have been established over the years. However, they show limited renewal capacity and they cannot be cultured long term in vitro. Commercial cell lines available, which can be cultured long term, fail to represent organ-specific adipocyte heterogeneity. Adipose tissue from different organs and fat depots can show significant heterogeneity in terms of metabolism and overall secretome and extracellular matrix production. The prostate, for example, is surrounded by peri-prostatic adipose tissue (PPAT), the volume of which is associated with an increased risk of lethal prostate cancer and a reduced therapy response. Here, we outline a protocol for ex vivo culture of fresh PPAT and non-prostatic adipose tissue (NPAT), which reflects donor- and depot-specific characteristics. Ex vivo culture of PPAT/NPAT explants maintains cell-cell interactions and preserves local tissue architecture within adipose tissue. We have also described establishment of immortalised, patient PPAT-derived pre-adipocytes and patient-matched NPAT pre-adipocytes that can be in vitro differentiated into mature adipocytes. The protocols outlined here could be readily adapted to other organ-specific fat depots, such as mammary/bone marrow adipose tissue, and to tissues of non-human origin.

Obesity-associated hypertension is a pressing and ever-growing public health concern. The prevalence of obesity has increased four-fold over the four preceding decades, with concomitantly rising rates of hypertension not far behind. Importantly, the interplay between these conditions exacerbates cardiovascular disease (CVD) risk, and optimal management strategies remain an evolving challenge. This review synthesizes recent advancements in understanding obesity-associated hypertension pathophysiology and explores emerging therapeutic options, highlighting their relevance in shaping future clinical practice. Emerging research into understanding obesity-associated hypertension has identified mechanisms, including dysregulated hormonal signaling, increased sympathetic activity, and enhanced inflammation as the key processes underlying obesity-associated hypertension development. With respect to management, new dietary interventions are poised to overtake traditional strategies as the ideal approach to achieving sustained weight loss for obesity-associated hypertension patients. Additionally, while conventional antihypertensive medications highlight the mainstay of standard pharmacotherapy, recent studies highlight the efficacy of diabetic agents and other novel therapies, which have the potential to further shape obesity-associated hypertension management guidelines. As an emphasis on precision medicine underscores contemporary research into obesity-associated hypertension management, targeted treatment strategies are emerging as promising alternatives for reducing CVD burden and improving patient outcomes. Ultimately, further research is necessary to continue to refine treatment guidelines and explore the full potential of evolving interventions.

Bacterial meningitis remains a major, life-threatening infection in children and adolescents, with Streptococcus pneumoniae meningitis (SPM) and Neisseria meningitidis meningitis (NMM) accounting for most cases. This study aimed to quantify the global burden and spatiotemporal patterns of SPM and NMM in individuals aged 0 to 19 years from 1990 to 2021, and to provide evidence for integrated, cross-pathogen prevention and improved clinical pathways. Using Global Burden of Disease 2021 estimates for 204 countries and territories, we extracted deaths and disability-adjusted life years (DALYs) for SPM and NMM in individuals aged 0 to 19 years (1990-2021). Trends were assessed using estimated annual percentage change and Joinpoint regression. Spearman correlation and concentration indices quantified inequalities across socio-demographic index (SDI) levels, decomposition analysis identified burden drivers, and Bayesian age-period-cohort modeling projected trends to 2050. In 2021, SPM caused 20,718 deaths (95% UI 14,718-29,192) and 1,823,058 disability-adjusted life years (DALYs; 95% UI 1,301,814-2,561,107), while NMM caused 17,389 deaths (95% UI 12,705-23,603) and 1,552,383 DALYs (95% UI 1,146,164-2,096,751) among those aged 0 to 19. From 1990 to 2021, the overall burden of both pathogens fell substantially worldwide, with a steeper decline for NMM. Decomposition pointed to epidemiological change as the main driver. Burden clustered in children under 5; among those younger than ten, males exceeded females. The magnitude of decline diminished with age. NMM showed a brief global uptick around 1996. Around 2011, Streptococcus pneumoniae supplanted Neisseria meningitidis as the principal pathogen contributing to meningitis burden in this population. Relative inequality between high-SDI and low-SDI countries has continued to widen, with the burden becoming increasingly concentrated in low-SDI regions. From 1990 to 2021, the global burden of SPM and NMM in children and adolescents declined substantially, with NMM declining faster and SPM overtaking NMM around 2011. Burden is highest in children under 5, with males more affected than females under 10. Despite absolute reductions, relative inequality widened, concentrating burden in low-SDI regions such as Western Sub-Saharan Africa. Integrated strategies including expanded vaccination, rapid diagnostics, and strengthened pediatric critical care are essential to reduce burden and narrow inequities.

Understanding the dynamic risk of overtaking behaviors is essential for improving highway safety and guiding adaptive driving strategies. This study develops a stage-based overtaking risk framework, capturing longitudinal and lateral risks across Lane-change, Overtaking, and Back-to-lane stages. A comprehensive risk indicator is constructed by weighting risk metrics at specific stages, and overtaking trajectories are aligned via Dynamic Time Warping for time-series clustering. Three typical risk evolution patterns are identified: hesitant, aggressive, and robust, accounting for 42.45%, 10.07%, and 47.48%, respectively. These risk evolution patterns reveal distinct temporal peaks of risk: hesitant drivers exhibit dual peaks at both lane changes; aggressive drivers face the highest risk during Overtaking stage; while robust drivers complete the overtaking task with the lowest overall risk. To explain the formation of these patterns, random parameters multinomial logit models with heterogeneity in means are estimated using macroscopic traffic-flow indicators. Results show that truck presence significantly increases the likelihood of hesitant trajectories, while higher standard deviation of upstream speed exhibits a significant positive association with aggressive behaviors. Furthermore, heterogeneity analysis reveals that under higher upstream speeds, drivers become more sensitive to downstream disturbances, amplifying failed overtaking. Compared with conventional multinomial logit model, the counter model with random parameters with heterogeneity in means shows a substantially better fit, highlighting the necessity of accounting for unobserved heterogeneity in traffic flow. This study contributes a data-driven paradigm that integrates interpretable risk metrics, time-series clustering, and discrete choice modeling, offering practical insights for adaptive risk management in automated driving.

Interest in the adoption of autonomous vehicles (AVs) continues to grow. It is essential to design new software architectures that meet stringent real-time, safety, and scalability requirements while integrating heterogeneous hardware and software solutions from different vendors and developers. This paper presents a lightweight, modular, and scalable architecture grounded in Service-Oriented Architecture (SOA) principles and implemented in ROS 2 (Robot Operating System 2). The proposed design leverages ROS 2's Data Distribution System-based Quality-of-Service model to provide reliable communication, structured lifecycle management, and fault containment across distributed compute nodes. The architecture is organized into Perception, Planning, and Control layers with decoupled sensor access paths to satisfy heterogeneous frequency and hardware constraints. The decision-making core follows an event-driven policy that prioritizes fresh updates without enforcing global synchronization, applying zero-order hold where inputs are not refreshed. The architecture was validated on a 1:10-scale autonomous vehicle operating on a city-like track. The test environment covered canonical urban scenarios (lane-keeping, obstacle avoidance, traffic-sign recognition, intersections, overtaking, parking, and pedestrian interaction), with absolute positioning provided by an indoor GPS (Global Positioning System) localization setup. This work shows that the end-to-end Perception-Planning pipeline consistently met worst-case deadlines, yielding deterministic behaviour even under stress. The proposed architecture can be deemed compliant with real-time application standards for our use case on the 1:10 test vehicle, providing a robust foundation for deployment and further refinement.

In 2022, the rate of daily smokers in Aotearoa New Zealand fell to 8 %, a historical low that reflected the efficacy of efforts and regulation to meet the NZ government's Smokefree 2025 goal. However, the use of e-cigarettes/vaping has rapidly increased over the past several years, overtaking cigarette use in 2021. This study employed wastewater-based epidemiology (WBE) to monitor and understand NZ nicotine consumption, with the aim of analysing both smoking and vaping habits in NZ. To this end, this research involved the development, validation and implementation of an SPE-LC-MS/MS method to analyse nicotine metabolites and tobacco-specific minor alkaloids in wastewater. A total of 142 wastewater samples from 12 different wastewater treatment plants (WWTPs) from nine settlements across NZ, collected twice a week for one week per month, from May to October 2023, were analysed. The population-weighted average nicotine consumption across all samples was 2467 mg/day/1000 people with no significant difference between weekday and weekend consumption, except for one site. The relative ratio of smoking-specific analytes and the total nicotine metabolites was analysed in order to obtain the relative proportion of nicotine obtained from tobacco vs vaping and other sources, with significant differences seen in both the total nicotine and mode of its consumption in different locations in Aotearoa New Zealand. This is the first study to investigate different modes of nicotine consumption in a NZ population using WBE, providing reliable and current data that will be useful information to the NZ government and health organisations.

Conditioning sensory signals endows persistent salience that influences attention, even after they no longer connect with rewards. As distractors shape multisensory target processing, conditioning phenomena remain poorly understood in relation to continuous sensory encoding. We investigate the effects of value-driven attentional capture by visual cues on the ability to reliably phase-lock cortical activity to temporal modulations of sound in audiovisual (AV) displays. Listening to periodically-modulated sound, observers discriminated between two visual object streams flickering at different rates, searching for an AV match. Also in view were peripheral color cues, used to evaluate how they modulate participant tracking fidelity as a result of color-reward associative training. Behavioral and electroencephalography (EEG) recordings (N=31) show that performance impoverished in presence of colors previously associated with reward, and so did tracking reliability measured by phase locking of AV responses. Decreased temporal precision predicted participants' reward-driven distraction, evidencing the attentional shift away from the multimodal target timing structure. Loss of consistency was furthermore present in auditory response estimates, suggesting value-driven attentional capture withdraws cortical tracking fidelity across the senses. The findings are consistent with inter-modal competition at times when incentive salience cues overtake top-down tracking of multisensory streams connected in time.

The transradial approach (TRA) using balloon guide catheters (BGCs) has emerged as a neurointerventional option. However, the use of large-bore BGCs may be limited because of the small size of the radial arteries (RAs) and difficulty in navigating BGCs from the right RA to the left anterior circulation. To determine the feasibility and safety of the overtake technique for navigating 8Fr EmboGuard BGCs using the TRA. We retrospectively reviewed consecutive patients primarily undergoing TRA using EmboGuard BGCs. The BGCs were placed using sheathless or sheath-based methods and navigated by overtaking long Simmons arm inner catheters hooked in the common carotid arteries under the guidance of a half-stiff wire. The minimum diameter of RAs was ≥2.8 mm in all patients. Patient demographics and procedural and clinical outcomes were evaluated at 90 d or later. Overall, 28 procedures were performed in 26 patients out of 364 procedures in 358 patients. Treatments were successfully completed with the 8Fr EmboGuard TRA in 27 procedures (96.4%) without conversion to the transfemoral approach. In one patient, exchanging the EmboGuard with another BGC was necessary due to herniation of the BGC into the aortic arch during navigation of the carotid stent system. RA occlusion occurred in 1 of 22 patients (3.8%) without ischemic complications. The overtake technique for navigating the 8Fr EmboGuard BGCs in patients having RAs ≥2.8 mm was feasible and safely performed regardless of the insertion methods.

Accessible autonomous racing can engage undergraduate students emersed in artificial intelligence (AI) and robotics to receive an education through the excitement of maneuvering sharp corners and overtaking opponents. In particular, the construction and programming of miniature mobile racing robots can facilitate head-to-head racing competitions for use indoors within classrooms and hallways. Unfortunately, existing racing platforms remain inaccessible for overtaking maneuvers in such confined settings because they are physically large or expensive due to the computational cost of enabling such high performance. In an attempt to address these issues, we present Pocket Racer, an open-source, pocket-sized racing robot capable of head-to-head racing within indoor environments in education, i.e. university hallways or classrooms. We demonstrate head-to-head autonomous racing with our Pocket Racer platforms, enabling high speed overtaking upwards of 15 km/h. Designed to be easily assembled with off the shelf components and a low-cost edge device (Raspberry Pi Zero 2 W), our Pocket Racer platform is made accessible through an open source website and dataset detailing build instructions. By making a pocket-sized head-to-head autonomous racing platform accessible for undergraduate students, our work hopes to further hands on education in the age of physical AI.

The automated truck platoon is one of the most promising connected autonomous vehicle technologies and is expected to become mainstream in the future. It is foreseeable that automated truck platoons and human drivers will share the roads and interact regularly. As a new traffic element, the truck platoon may influence other drivers' behaviors and mental states, potentially compromising the safety of mixed traffic. While existing studies have extensively explored drivers' behavioral responses to truck platoons, little is known about their psychophysiological states during such interactions, particularly how platoon organization influences drivers' mental workload and attention. To address this gap, a comprehensive set of platoon organization factors was considered, and a high-fidelity driving simulator experiment was conducted. The study employed a 2 (platoon speed: 80 km/h vs. 100 km/h) × 2 (platoon size: three vs. five trucks) × 2 (inner gap: 5 m vs. 25 m) × 2 (traffic environment: presence vs. absence of a lead vehicle) within-subjects factorial design. Drivers' heart rate, pupil diameter, gaze dispersion, and subjective mental workload ratings were recorded and analyzed, with data collected from 35 participants. Results showed that compared to the baseline, drivers' horizontal gaze dispersion was more concentrated during interactions with the truck platoon. Furthermore, an inner gap of 5 m can significantly increase drivers' mental workload compared to an inner gap of 25 m, as indicated by mean heart rate and mean pupil diameter. Regarding platoon speed, drivers' horizontal gaze was more dispersed at a platoon speed of 100 km/h compared to 80 km/h, likely due to greater attention to maintain lateral distance from the median divider and the platoon. Moreover, drivers' mental workload showed a significant decreasing trend with repeated interactions with the truck platoon. These findings provide insights into the operational strategies of truck platoons from a human factors perspective.

We report a measurement of the cosmic ray helium energy spectrum in the energy interval 0.16-13 PeV, derived by subtracting the proton spectrum from the light component (proton and helium) spectrum obtained with observations made by the Large High Altitude Air Shower Observatory (LHAASO) under a consistent energy scale. The helium spectrum shows a significant hardening centered at E≃1.1  PeV, followed by a softening at ∼7  PeV, indicating the appearance of a helium "knee." Comparing the proton and helium spectra in the LHAASO energy range reveals some remarkable facts. In the lower part of this range, in contrast to the behavior at lower energies, the helium spectrum is significantly softer than the proton spectrum. This results in protons overtaking helium nuclei and becoming the largest cosmic ray component at E≃0.7  PeV. A second crossing of the two spectra is observed at E≃5  PeV, above the proton knee, when helium nuclei overtake protons to become the largest cosmic ray component again. These results have important implications for our understanding of the Galactic cosmic ray sources.

This dataset contains high-resolution bicycle trajectory data collected during a controlled mass-cycling experiment conducted on a circular test track at ETH Zurich. A total of 28 cyclists were recorded using aerial video over approximately 30 minutes. The experiment systematically varied the number of simultaneous cyclists and the effective lane width to capture a range of traffic density conditions, including free-flow, disturbed flow, and stop-and-go regimes. Bicycle positions were extracted from drone footage using computer vision-based object detection and tracking, followed by state estimation and Kalman filtering to obtain smooth Cartesian trajectories at frame level. The dataset includes raw video recordings, object annotations, and processed trajectories with spatial and temporal attributes. By isolating cyclist interactions from complex road geometry and mixed traffic, the dataset provides a controlled basis for studying bicycle traffic flow, lateral movement, overtaking manoeuvres, and collective dynamics. The dataset is suitable for use in traffic flow analysis, microscopic modelling, and the development and evaluation of bicycle-specific trajectory prediction methods.

ObjectiveThis study investigates the factors influencing drivers' decisions to intervene in conditional driving automation (SAE Level 3) without system alerts or failures.BackgroundIn complex traffic environments, mismatches between drivers' perception of traffic situations and the response of automation can lead to driver-initiated disengagements, even when the system can safely manage events. While such interventions may be safety conservative, they can also disrupt system operations, compromise safety, and reduce user trust.MethodA driving simulation with 23 participants was conducted in which a conditionally automated vehicle encountered a stopped vehicle blocking its lane, with oncoming traffic present in the adjacent lane. The system was programmed to safely overtake using the opposing lane considering the distance to the oncoming traffic. Participants could either remain in automated mode or override the system.ResultsDrivers intervened in more than 20% of events, most often by pressing the brake pedal while approaching the stopped vehicle when the gap to the oncoming traffic was perceived as insufficient. In challenging overtaking gaps, discrepancies between the behavior of a leading human-driven vehicle and the system further increased intervention likelihood, with some drivers misunderstanding the system's ability to detect oncoming vehicles. Although drivers who intervened completed overtaking faster than the system, their maneuvers were marked by abrupt steering and acceleration, raising concerns about encroaching into opposing traffic.ConclusionEnhancing system feedback and better aligning automation behavior with driver expectations may reduce unnecessary disengagements.ApplicationThe findings provide guidance for designing more intuitive automated driving systems that enhance user trust and safety.

ObjectiveTo evaluate the feasibility of electromyography (EMG)-based human-machine interfaces (HMIs) for high-demand activities such as driving based on performance, cognitive workload, usability, and safety measures.BackgroundUpper-limb amputees face challenges in performing everyday tasks, including driving. EMG-based HMIs offer potential solutions, particularly for wrist disarticulated and trans-radial amputee, but their effectiveness in complex tasks like driving requires further investigation.MethodNineteen able-bodied participants completed a driving simulation study using an EMG-based HMI, dominant hand, and both hands. Participants performed various driving maneuvers including straight lane driving, overtaking, and 90-degree turns at intersections. Driver performance, cognitive workload (measured by blink rate and subjective measures), usability (USE questionnaire), and safety were assessed.ResultsUsing the EMG-based HMI led to higher lane offset and steering angle compared to conventional methods, but demonstrated lower steering entropy in some situations. Cognitive workload was higher for EMG-based HMI, while usability scores were lower. Safety measures were mixed, with EMG-based HMI showing better performance at intersections but lower lane offset and steering angle safety scores overall.ConclusionThe study highlights both limitations and opportunities presented by EMG-based HMIs in high-demand tasks such as driving. While the system exhibited lower performance in some conditions, it demonstrated potential for controlled driving, particularly during specific maneuvers. The higher cognitive workload and lower usability scores indicate areas for improvement.ApplicationThe findings provide valuable insights for the development of more effective EMG-based HMIs, supporting future research and clinical trials aimed at enhancing mobility and independence for individuals with upper-limb amputations.