A Systematic Cooperation Method for In-Car Navigation Based on Future Time Windows

Traffic congestion has become a severe problem, af-fecting travellers both mentally and economically. To al-leviate traffic congestion, this paper proposes a method using a concept of future time windows to estimate the future state of the road network for navigation. Through our method, we can estimate the travel time not only based on the current traffic state, but the state that ve-hicles will arrive in the future. To test our method, we conduct experiments based on Simulation of Urban MO-bility (SUMO). The experimental results show that the proposed method can significantly reduce the overall travel time of all vehicles, compared to the benchmark Dijkstra algorithm. We also compared our method to the Dynamic User Equilibrium (DUE) provided by SUMO. The experimental results show that the performance of our method is a little better than the DUE. In practice, the proposed method takes less time for computation and is insensitive to low driver compliance: with as low as 40% compliance rate, our method can significantly im-prove the efficiency of the unsignalised road network. We also verify the effectiveness of our method in a signalised road network. It also demonstrates that our method can assign traffic efficiently

A Method for Traffic Flow Forecasting in a Large-Scale Road Network Using Multifeatures

Accurate traffic prediction on a large-scale road network is significant for traffic operations and management. In this study, we propose an equation for achieving a comprehensive and accurate prediction that effectively combines traffic data and non-traffic data. Based on that, we developed a novel prediction model, called the adaptive deep neural network (ADNN). In the ADNN, we use two long short-term memory (LSTM) networks to extract spatial-temporal characteristics and temporal characteristics, respectively. A backpropagation neural network (BPNN) is also employed to represent situations from contextual factors such as station index, forecast horizon, and weather. The experimental results show that the prediction of ADNN for different stations and different forecast horizons has high accuracy; even for one hour ahead, its performance is also satisfactory. The comparison of ADNN and several benchmark prediction models also indicates the robustness of the ADNN

Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort

Most existing public transit systems have a fixed dispatching and service mode, which cannot effectively allocate resources from the perspective of the interests of all participants, resulting in resource waste and dissatisfaction. Low passenger satisfaction leads to a considerable loss of bus passengers and further reduces the income of bus operators. This study develops an optimization model for bus schedules that considers vehicle types and offers two service levels based on heterogeneous passenger demands. In this process, passenger satisfaction, bus company income, and government subsidies are considered. A bilevel model is proposed with a lower-level passenger ride simulation model and an upper-level multiobjective optimization model to maximize the interests of bus companies, passengers, and the government. To verify the effectiveness of the proposed methodology, a real-world case from Guangzhou is presented and analyzed using the nondominated sorting genetic algorithm-II (NSGA-II), and the related Pareto front is obtained. The results show that the proposed bus operation system can effectively increase the benefits for bus companies, passengers, and the governmen

Eye-Tracking Metrics Predict Perceived Workload in Robotic Surgical Skills Training

Objective: The aim of this study is to assess the relationship between eye-tracking measures and perceived workload in robotic surgical tasks. Background: Robotic techniques provide improved dexterity, stereoscopic vision, and ergonomic control system over laparoscopic surgery, but the complexity of the interfaces and operations may pose new challenges to surgeons and compromise patient safety. Limited studies have objectively quantified workload and its impact on performance in robotic surgery. Although not yet implemented in robotic surgery, minimally intrusive and continuous eye-tracking metrics have been shown to be sensitive to changes in workload in other domains. Methods: Eight surgical trainees participated in 15 robotic skills simulation sessions. In each session, participants performed up to 12 simulated exercises. Correlation and mixed-effects analyses were conducted to explore the relationships between eye-tracking metrics and perceived workload. Machine learning classifiers were used to determine the sensitivity of differentiating between low and high workload with eye-tracking features. Results: Gaze entropy increased as perceived workload increased, with a correlation of .51. Pupil diameter and gaze entropy distinguished differences in workload between task difficulty levels, and both metrics increased as task level difficulty increased. The classification model using eye-tracking features achieved an accuracy of 84.7% in predicting workload levels. Conclusion: Eye-tracking measures can detect perceived workload during robotic tasks. They can potentially be used to identify task contributors to high workload and provide measures for robotic surgery training. Application: Workload assessment can be used for real-time monitoring of workload in robotic surgical training and provide assessments for performance and learning

Epidemiological/Disease and Economic Burdens of Cervical Cancer in 2010–2014: Are Younger Women at Risk?

Objective: Cervical cancer is an important factor threatening women’s health in China. This study examined the epidemiological and economic burden of cervical cancer among the medically insured population, which could provide data support for government departments to formulate policies. Methods: All new cases of cervical cancer under the Urban Employee Basic Medical Insurance (UEBMI) plan in a provincial capital city in eastern China from 2010 to 2014 were collected. The Cox proportional hazard model was used to analyze the factors affecting the survival rates for cervical cancer. Outpatient and hospitalization expenses were used to assess the direct economic burden, and the Potential Years of Life Loss (PYLL) and potential economic loss were calculated by the direct method to assess indirect burden. Results: During the observation period, there were 1115 new cases and 137 deaths. The incidence rate was 14.85/100,000 person years, the mortality was 1.82/100,000 person years, and the five-year survival rate was 75.3%. The age of onset was mainly concentrated in the 30–59 age group (82.9%) and the tendency was towards younger populations. The age of onset (HR = 1.037, 95% CI = 1.024–1.051), the frequency of hospitalization services (HR = 1.085, 95% CI = 1.061–1.109), and the average length of stay (ALOS) (HR = 1.020, 95% CI = 1.005–1.051) were the related factors affecting overall survival. Among the direct economic burden, the average outpatient cost was $4314, and the average hospitalization cost was$12,007. The average outpatient and hospitalization costs within 12 months after onset were $2871 and$8963, respectively. As for indirect burden, the average Potential Years of Life Loss (PYLL) was 27.95 years, and the average potential economic loss was $95,200. Conclusions: The epidemiological and economic burden reported in the study was at a high level, and the onset age of cervical patients gradually became younger. The age of onset, the frequency of hospitalization services and the ALOS of cervical cancer patients should be given greater attention. Policymakers and researchers should focus on the trend of younger onset age of cervical cancer and the survival situation within 12 months after onset. Early intervention for cervical cancer patients, particularly younger women, may help reduce the burden of cervical cancer

Internal Elastic Strains of AZ31B Plate during Unloading at Twinning-Active Region

Magnesium alloys, being the lightest structural metals, have garnered significant attention in various fields. The characterization of inelastic behavior has been extensively investigated by researchers due to its impact on structural component performance. However, the occurrence of twinning in the absence of any applied driving force during unloading has lacked reasonable explanations. Moreover, the influence of deformation mechanisms other than twinning on inelastic behavior remains unclear. In this study, uniaxial tension and compression tests were conducted on hot-rolled magnesium alloy plates, and neutron diffraction experiments were employed to characterize the evolution of macroscopic mechanical response and microscopic mechanisms. Additionally, a twinning and detwinning (TDT) model based on the elastic visco-plastic self-consistent (EVPSC) model has been proposed, incorporating back stress to describe the deformation behavior during stress relaxation. This approach provides a comprehensive understanding of the inelastic behavior of magnesium alloys from multiple perspectives and captures the influence of microscale mechanisms. A thorough understanding of the inelastic behavior of magnesium alloys and a reasonable explanation for the occurrence of twinning under zero-stress conditions offer valuable insights for the precise design of magnesium alloy structures

Comparative Pathogenomic Analysis of Two Banana Pathogenic Dickeya Strains Isolated from China and the Philippines

Dickeya is a major and typical member of soft rot Pectobacteriaceae (SRP) with a wide range of plant hosts worldwide. Previous studies have identified D. zeae as the causal agent of banana soft rot disease in China. In 2017, we obtained banana soft rot pathogen strain FZ06 from the Philippines. Genome sequencing and analysis indicated that FZ06 can be classified as D. dadantii and represents a novel subspecies of D. dadantii, which we propose to name as subsp. paradisiaca. Compared with Chinese banana soft rot pathogenic strain D. zeae MS2, strain FZ06 has a similar host range but different virulence; FZ06 is significantly less virulent to banana and potato but more virulent to Chinese cabbage and onion. Characterization of virulence factors revealed obviously less production of pectate lyases (Pels), polygalacturonases (Pehs), proteases (Prts), and extrapolysaccharides (EPSs), as well as lower swimming and swarming motility and biofilm formation in strain FZ06. Genomic comparison of the two strains revealed five extra gene clusters in FZ06, including one Stt-type T2SS, three T4SSs, and one T4P. Expression of cell wall degrading enzyme (CWDE)-encoding genes is significantly lower in FZ06 than in MS2

Microevolution of the mexT and lasR Reinforces the Bias of Quorum Sensing System in Laboratory Strains of Pseudomonas aeruginosa PAO1

The Pseudomonas aeruginosa strain PAO1 has routinely been used as a laboratory model for quorum sensing (QS). However, the microevolution of P. aeruginosa laboratory strains resulting in genetic and phenotypic variations have caused inconsistencies in QS research. To investigate the underlying causes of these variations, we analyzed 5 Pseudomonas aeruginosa PAO1 sublines from our laboratory using a combination of phenotypic characterization, high throughput genome sequencing, and bioinformatic analysis. The major phenotypic variations among the sublines spanned across the levels of QS signals and virulence factors such as pyocyanin and elastase. Furthermore, the sublines exhibited distinct variations in motility and biofilm formation. Most of the phenotypic variations were mapped to mutations in the lasR and mexT, which are key components of the QS circuit. By introducing these mutations in the subline PAO1-E, which is devoid of such mutations, we confirmed their influence on QS, virulence, motility, and biofilm formation. The findings further highlight a possible divergent regulatory mechanism between the LasR and MexT in the P. aeruginosa. The results of our study reveal the effects of microevolution on the reproducibility of most research data from QS studies and further highlight mexT as a key component of the QS circuit of P. aeruginosa