共找到 20 条结果
暂无摘要（点击查看详情）
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.
暂无摘要（点击查看详情）
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.
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.
Pancreatitis is a serious worldwide public health concern, with a currently increasing disease burden. Up-to-date information on pancreatitis burden can provide new strategies for its screening, diagnosis, treatment, and rational allocation of resources. Based on the Global Burden of Diseases (GBD) 2021, this study estimated the number of cases, age-standardized rates (ASRs) per 100,000 population, and risk factors of pancreatitis in 204 countries and regions. Joinpoint regression analysis was used to calculate the Average Annual Percentage Changes (AAPCs) in the incidence, mortality, and Disability-Adjusted Life Years (DALYs) of pancreatitis. In comparison to GBD 2017 and 2019, our analysis based on GBD 2021 reveals new epidemiological trends in pancreatitis. Eastern Europe has surpassed other regions (notably overtaking previously leading North America) and recorded the highest age-standardized incidence rate (ASIR) and age-standardized death rate (ASDR) in 2021. ASIR and ASDR in high-middle social demographic index (SDI) regions have increased compared with earlier estimates, whereas both rates showed a marked decline in high-SDI regions. In addition, males were disproportionately affected (ASIR 36.75 vs. 28.82 per 100,000), consistent with higher alcohol exposure among men. Notably, Eastern Europe has surpassed North America to become the region with the highest ASIR and ASMR of pancreatitis. Furthermore, projections for the next 15 years indicate that the incidence rate will gradually decrease in men but is expected to increase in women. Pancreatitis poses a high public health burden globally and has significant regional differences. These regional and population differences are constantly changing over time, which is essential for developing focused public health interventions and policies.
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.
This study proposes a GTS-PF (Gradient-based Time-Sequential Potential Field)-based path generation method for real-time reference-path planning at infrastructure-based RSUs in cooperative driving automation environments. Conventional path planning approaches exhibit limitations in computational lightweight characteristics or responsiveness to dynamic environments, which restrict their suitability for negotiation-oriented reference-path generation and dissemination. To address these limitations, the proposed GTS-PF framework interprets the prediction time horizon as a sequence of updated temporal layers, enabling adaptive responses to dynamic obstacle variations. The method is formulated based on potential field principles to allow efficient computation while incorporating diverse interaction effects. A key feature of the proposed approach is the separation of direction planning and speed planning for obstacle avoidance, wherein a candidate acceleration set is generated based on future risk evaluation. Simulation results in an overtaking scenario involving a low-speed preceding vehicle demonstrate that the proposed method satisfies predefined safety and path-quality criteria. Moreover, the computation time was reduced by 81% compared to the baseline method, confirming computational lightweight feasibility for RSU-level implementation and demonstrating applicability in infrastructure-led cooperative driving automation.
The fatality due to breast cancer is one of the most universal causes among women worldwide. The limited interpretation is due to tissue overlapping, high breast density and delicate lesion characteristics even though mammography is the standard screening tool. To overcome this universal challenges, we propose a multi-model deep learning framework that integrates mammographic image with structured clinical data (note: synthetic clinical variables were employed based on the known distributions of the risk factors due to the lack of real paired data) to achieve the accuracy in the diagnostics. Architectural developments establish promising directions for future multi-modal tactic with reliable clinical data. The architecture utilize a hierarchical fusion approach that incorporates with cross model attention mechanism and dynamic modality weighting to efficiently integrate heterogeneous features. Moreover, a region of interest care module is integrated to highlight crucial anatomical regions in mammograms. Experimental evaluations on a benchmark dataset validate a classification accuracy of 94.6% (95% CI: 92.8-96.4%) and an AUC of 0.963 (95% CI: 0.951-0.975), expressively overtaking prevailing baseline models (p < 0.01). These results suggested the significant potential of projected architectural framework as a proof-of-concept for steadfast and easily explainable clinical decision supporting tools.
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.
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.
Fracture risk in mid-life (ages 35-65) is under-recognised despite its implications for long-term skeletal health. Using UK Biobank data, we aimed to characterize fracture epidemiology in this critical age group through two complementary approaches. We conducted two studies: a cross-sectional analysis of self-reported fractures (2006-2010) to estimate annualized incidence risk per 10,000 people, and a longitudinal cohort analysis using linked Hospital Episode Statistics (2001-2022) to calculate incidence rates per 10,000 person years, both stratified by sex, skeletal site, and 10-year age bands. Fracture incidence varied substantially by age and sex. Among women, risk increased from age 35 years and accelerated notably from the mid-40s, peaking at 246 per 10,000 people in the 56-65 age group. This female trajectory, emerging earlier than previously recognized, contrasts with men, whose highest fracture risk occurred in early mid-life (peak: 232 per 10,000 people, ages 35-45). Across both sexes and age bands, the most reported fracture sites were: "other" (including digits and facial bones), wrist, ankle, arm, leg, spine, and hip, in descending order. In HES-linked data, 43,572 fractures were identified. Incidence patterns mirrored those from self-report: higher early mid-life fracture rates in men, followed by a transition to female predominance from around age 45. This large-scale, dual-method analysis offers the first clear evidence that female fracture risk begins to rise from age 35, with a marked acceleration from 45 onward. These sex-specific trajectories in mid-life fracture incidence are not fully captured in current clinical models and indicate that further work is needed to determine whether earlier or tailored approaches to risk assessment could provide cost-effective benefit in reducing the burden of fracture in mid-life. Breaking a bone in mid-life (between the ages of 35 and 65) is an important health issue that is under-appreciated. We looked at hospital records and self-reported data from the UK Biobank, a large study involving thousands of people in the UK and found that in younger mid-life (ages 35–45), men had higher rates of broken bones than women, similar to that seen in teenagers. From age 45 onwards, rates in women rose sharply, eventually overtaking men. This suggests we need to start paying attention to bone health in mid-life, especially for younger middle-aged men, and women approaching menopause.
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.
Two critical factors in the success of the response to a threatening epidemic outbreak are the degree of responsibility of the main political actors involved in the response and the population compliance to the proposed measures. The Behavioural epidemiology literature has focused on the latter factor but largely disregarded the former. The multiple failures in COVID-19 control and the lack of consensus that still surround the main response options (i.e., the elimination-suppression-mitigation trichotomy) highlight the importance of considering the political layer in preparedness activities. We integrate a simple transmission model into a game-theoretic framework for the interaction between the main political actors involved in the response, namely a government, its opposition and lobbies. The aim is to provide a conceptual framework allowing one to identify the political factors promoting a timely and effective response. Low degrees of responsibility (i.e., prioritizing consensus over health protection) of political agents can delay or de-potentiate the response until when epidemic growth eventually overtakes the agents' payoffs, thereby forcing them to switch towards the higher degree of responsibility needed to promote an adequate response. When both the government and the opposition are only "partly" responsible, a stall in the response decision-making process likely arises, further delaying the response. Policy and epidemiological parameters amplifying the response delay are ranked by a sensitivity analysis. Promoting a high degree of responsibility of political actors and lobbies during emergency situations should be a key target of preparedness. Therefore, future pandemic plans should also include, beyond technical indications, ethical statements "guiding" political entities to cooperation.
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.
We report molecular dynamics simulations of infrared (IR) and Raman spectra of H5O2+ and its deuterium-substituted analogs. We use the well-tested HBB potential and dipole surfaces along with a recently fitted polarizability surface of CCSD(T)/aug-cc-pVTZ quality. The focus of the present work is to provide new insights into the O···O stretch region, located in the [500-700] cm-1 spectral range, by means of analyzing the spectra over a broad range of temperatures: from 50 to 300 K. Also, rovibrational thermal averaging was performed to untangle the unusually complex spectra of partially deuterated isotopologues DH4O2+ and D4HO2+ with H and D minority species in both internal (int) and external (ext) positions. Our findings show that DH4O2+ (ext) is at least 90% prevalent at the [50-300] Kelvin temperatures, predominantly due to its low zero-point energy (ZPE). Furthermore, contrary to previous reports that the mixed isotopologue D4HO2+ (int) should be favored over D4HO2+ (ext) due to its lower ZPE, the present calculations indicate that while the D4HO2+ (ext) species is "invisible" at lower temperatures, it overtakes D4HO2+ (int) as the dominant species at 84.9 K and higher.
Many liquids display water-like anomalies-such as density maxima, diffusion anomalies, and nonmonotonic structural order-that originate from the competition between interaction ranges or local motifs. Isotropic core-softened (CS) models capture these effects but often neglect intrinsic anisotropy and internal flexibility. Here, we investigate how bond stiffness k reshapes anomalous behavior in dimeric CS fluids. By tuning k from highly flexible to effectively rigid, we show that rigidity shifts the temperature of maximum density , narrows the diffusion anomalies to lower temperatures, and modifies the structural order. Most importantly, increased stiffness introduces emergent geometric length scales in the center-of-mass radial distribution function. In the rigid limit, the anisotropy-induced peak at r ≃ 1.5 overtakes the intrinsic CS feature at r ≃ 1.2, reorganizing the hierarchy of relevant distances. This three-scale competition (two radial and one geometric) provides a unified explanation for the correlated shifts of anomalies across the P-T plane, establishing bond stiffness as a key control parameter to tune anomaly-driven behavior in anisotropic soft matter.
We investigate a quasi-one-dimensional (Q1D) system of hard spheres confined within a cylindrical pore so narrow that only nearest-neighbor interactions occur. By mapping this Q1D system onto a one-dimensional polydisperse mixture of nonadditive hard rods, we obtain exact thermodynamic and structural properties, including the radial distribution function, which had remained elusive in previous studies. We derive analytical results for limiting cases, such as small pore diameters, virial expansions, and the high-pressure regime. In particular, we identify a crossover in the anisotropic pressure components: at high densities, the transverse pressure overtakes the longitudinal one when the pore diameter exceeds a critical threshold. We also examine spatial correlations in particle arrangements and radial fluctuations, shedding light on the emergence of ordering in confined systems.
Lee et al. (2025) presented their "forced-response method", in which performance in a cognitive control task is assessed as a function of the time a target stimulus is visible (within a reaction time), in a situation with time pressure for responding. In the existing literature, this experimental approach has been referred to as the compelled-response paradigm or the urgent paradigm. Replicating earlier findings by also applying the method to the flanker task of cognitive control, Lee et al. found that urgency opens up a time window in which stimulus-driven processing overtakes cognitively controlled processing and leads to actions against current intentions (as per task instructions). Taken together, this demonstrates how the method captures the temporal evolution of performance in high resolution, providing a window into the dynamics of cognitive processing in cognitive control tasks. However, urgency may induce a specific mental state, akin to phasic alertness as a state of response and perceptual readiness. Therefore, it is an open question how the method differs from standard assessments of cognitive control and in what way it provides a better alternative.