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Abstract To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P

Abstract The interactions between white-to-white corneal diameter (WTW) and other ocular biometrics are important for planning of refractive surgery and understanding of ocular structural changes in myopia, but such interactions are rarely investigated in young myopic adults. This is a retrospective study involving 7893 young myopic adults from five centers. WTW and other ocular biometrics were measured by Pentacam. The ocular biometrics included anterior corneal curvature (AK) and posterior corneal curvature (PK), central corneal thickness (CCT) and corneal volume (CV), anterior and corneal eccentricity and asphericity, anterior corneal astigmatism (ACA) and posterior corneal astigmatism, anterior chamber depth (ACD), and anterior chamber volume (ACV). The ocular biometrics were compared among eyes of different WTW quartiles. Multivariate linear regression was used to assess the linear associations between WTW and other ocular biometrics adjusting for age, gender and spherical equivalent. In eyes of different WTW quartiles, other ocular biometrics were also significantly different (all P

Summary: Cooperative vehicle-infrastructure system (CVIS) is an important part of the intelligent transport system (ITS). Autonomous vehicles have the potential to improve safety, efficiency, and energy saving through CVIS. Although a few CVIS studies have been conducted in the transportation field recently, a comprehensive analysis of CVIS is necessary, especially about how CVIS is applied in autonomous vehicles. In this paper, we overview the relevant architectures and components of CVIS. After that, state-of-the-art research and applications of CVIS in autonomous vehicles are reviewed from the perspective of improving vehicle safety, efficiency, and energy saving, including scenarios such as straight road segments, intersections, ramps, etc. In addition, the datasets and simulators used in CVIS-related studies are summarized. Finally, challenges and future directions are discussed to promote the development of CVIS and provide inspiration and reference for researchers in the field of ITS.

Through vehicle-to-vehicle (V2V) communication, autonomizing a vehicle platoon can significantly reduce the distance between vehicles, thereby reducing air resistance and improving road traffic efficiency. The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions, thereby permitting large-scale vehicle platoon scheduling and planning, which is essential for industrialized platoon applications and generates significant economic benefits. Scheduling and planning are required in many aspects of vehicle platoon operation; here, we outline the advantages and challenges of a number of the most important applications, including platoon formation scheduling, lane-change planning, passing traffic light scheduling, and vehicle resource allocation. This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications. To this end, we first summarize the general techniques of vehicle platoon scheduling and planning, then list the primary scenarios for scheduling and planning technique application, and finally discuss current challenges and future development trends in platoon scheduling and planning. We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.

Abstract Background To characterize the quality of vision after SMILE, FS-LASIK, and ICL implantation and evaluate the related factors. Methods 131 eyes of 131 myopic patients (90 female, 41 male) who underwent refractive surgeries including SMILE (35 patients), FS-LASIK (73 patients), and ICL implantation (23 patients) were analyzed. The Quality of Vision questionnaires were completed 3 months after surgery, and the results were characterized and analyzed with baseline characteristics, treatment parameters, and postoperative refractive outcomes using logistic regression analysis to find out predicted factors. Results Mean age was 26.5 ± 4.6 years (range: 18 to 39 years) and mean preoperative spherical equivalent was − 4.95 ± 2.04 diopters (D) (range: -1.5 to -13.5). Safety and efficacy index was comparable between different techniques: the safety index was 1.21 ± 0.18, 1.22 ± 0.18, and 1.22 ± 0.16 and the efficacy index were 1.18 ± 0.20, 1.15 ± 0.17, 1.17 ± 0.15 for SMILE, FS-LASIK and ICL respectively. The mean overall QoV score was 13.40 ± 9.11, with mean frequency, severity, and bothersome score of 5.40 ± 3.29, 4.53 ± 3.04, and 3.48 ± 3.18 respectively, and there was no significant difference between different techniques. Overall, the symptom with the highest scores was glare, following fluctuation in vision and halos. Only the scores of halos were significantly different among different techniques (P

The research on high-performance vector control of permanent magnet synchronous motor (PMSM) drive system plays an extremely important role in electrical drive system. To further improve the speed control performance of the system, a fast non-singular end sliding mode (FNTSM) surface function based on traditional NTSM control is developed. The theoretical analysis proves that the FNTSM surface function has a faster dynamic response and more finite-time convergence. In addition, for the self-vibration problem caused by high sliding mode switching gain, an FNTSM control method with anti-disturbance capability was designed based on the linear disturbance observer (DO), i.e. the FNTSMDO method was employed to devise the PMSM speed regulator. The comparative simulation and experiment results with traditional PI control and NTSM control methods indicate that the FNTSMDO method could improve the dynamic performance and anti-interference of the system.

Objective: The objective of this study was to examine the effect of the postsurgical administration of Shenyi capsules on the outcome and overall survival of patients with nonsmall cell lung cancer (NSCLC). Materials and Methods: This was a multicenter, randomized, placebo-controlled, double-blind clinical trial. Patients with stages I–IIIA NSCLC were randomized to Shenyi or placebo groups (treatment duration: 6 months) and followed up for 10 years. One-year, 2-year, 5-year, and 10-year survival rates and survival times were calculated. Symptoms, quality of life, traditional Chinese medicine (TCM) syndrome, and recurrence were evaluated. Results: A total of 361 patients (treatment group, n = 185; placebo group, n = 176) were randomized and followed up for 10 years. The two groups had similar baseline demographic and clinical characteristics. Among all 361 patients, the treatment group had significantly longer median survival (31 months, respectively) than the placebo group (22.3 months, P < 0.01). In stage II or III patients, recurrence and metastasis rates in the treatment group were lower than those in the placebo group (P < 0.05). The treatment group also had significantly longer 1-year and 2-year survival rates based on the full analysis set and per-protocol set; however, there was no statistically significant difference in the 5-year and 10-year survival rates (P < 0.01 for all comparisons). Multivariate analysis of variance showed that the interaction between stage and age had a significant impact on overall survival (P < 0.05). Compared with the placebo group, the treatment group showed a significant decrease in TCM syndrome (P < 0.01) and a significant increase in the Karnofsky Performance Score (P < 0.01) and body weight (P < 0.05). Conclusions: Adjunctive therapy with Shenyi capsules significantly prolonged the 1-year and 2-year survival rates after surgery and improved the quality of life. Moreover, none of the patients experienced severe adverse effects. These results suggest that Shenyi capsules may have clinical applications in treating patients with NSCLC.

It is generally accepted that the vibration and noise of electrical motors mainly depend on radial electromagnetic forces. However, the relationship between electromagnetic forces and system modes becomes special when integrating the electrical motor into a coaxial electric axle (eAxle). This paper proposes a phase-based tangential electromagnetic force array analysis method to explain and optimize the noise spikes in a coaxial eAxle which is driven by a permanent magnet synchronous motor (PMSM) with a step-skewed rotor. Its electromagnetic force on each stator node is decomposed into radial and tangential forces as inputs for structural finite element simulation. Based on their contributions to the noise, the torsional vibration and noise of the eAxle are correlated with the tangential electromagnetic force array. Thus, the coupling effect of excitation and response is illustrated, and the electromagnetic force array could be optimized more targeted.

The deterioration characteristics of electric multiple units (EMUs) components can lead to complex and costly maintenance processes. This paper focuses on investigating the influence mechanism of the interaction between operation and maintenance (O&M) activities within the whole life cycle (WLC) of EMUs’ components on the maintenance strategy, based on the concept of lean maintenance (LM). A linear relationship is established between operating costs and the equivalent service age to reflect the trend of the component operating conditions dynamically in relation to deterioration level and maintenance activities, and a bi-level imperfect preventive maintenance (BIPM) strategy considering operating cost (OC) is proposed at the component level. At the system level, a multi-level preventive opportunity maintenance (POM) strategy based on the opportunity maintenance mileage window (OMMW) is proposed for the serial system of EMUs to reduce the number of system downtime and minimize value waste and achieve long-term economic benefits. The experimental results demonstrated that compared to maintenance strategies that do not consider operating costs, this strategy optimizes the total maintenance cost for multi-component systems of EMUs in the long term by implementing more aggressive measures while ensuring component reliability, system availability, and schedule rationality.

Eagle syndrome is a clinical condition that characterized by myriad of symptoms associated with the compression of neurovascular structures by an elongated styloid process. Herein we describe a rare case of Eagle syndrome who showed bilateral internal jugular venous occlusion duo the compression of the styloid process. A young man presented with headaches for six months. Lumbar puncture showed an opening pressure of 260 mmH2O and the cerebrospinal fluid analysis was normal. Catheter angiography revealed occlusion of bilateral jugular venous. Computed tomography venography demonstrated compression of bilateral jugular venous by bilateral elongated styloid processes. The patient was diagnosed with Eagle syndrome and suggested to undergo styloidectomy, after which he recovered completely. We emphasize that Eagle syndrome is a rare cause of intracranial hypertension and styloid resection can bring an excellent clinical outcome in patents with intracranial hypertension due to Eagle syndrome.

IntroductionOver the past few decades, advances in traumatic brain injury (TBI) pathology research have dynamically enriched our knowledge. Therefore, we aimed to systematically elucidate the safety and efficacy of erythropoietin (EPO) dosing regimens in patients with TBI.MethodsData search included PubMed, the Cochrane Library, Embase, Web of Science, and ClinicalTrials.gov for related research published before July 2022. The network meta-analysis was conducted using ADDIS 1.16.8, and the CINeMA tool was used to assess the quality level of evidence.ResultsA total of six RCTs involving 981 patients were included in the network meta-analysis. EPO did not significantly reduce mortality in patients with TBI, but its risk of death decreased with increasing dosage (odds ratio (OR) of 12,000u vs. placebo = 0.98, 95% CI: 0.03–40.34; OR of group 30,000u vs. placebo = 0.56, 95% CI: 0.06–5.88; OR of 40,000u vs. placebo = 0.35, 95% CI: 0.01–9.43; OR of 70,000u vs. placebo = 0.29, 95% CI: 0.01–9.26; OR of group 80,000u vs. placebo = 0.22, 95% CI: 0.00–7.45). A total of three studies involving 739 patients showed that EPO did not increase the incidence of deep vein thrombosis in patients with TBI. However, the risk tended to rise as the dosage increased. Another two studies demonstrated that EPO did not increase the incidence of pulmonary embolism. The quality of evidence for all outcomes was low to moderate.ConclusionAlthough the efficacy of EPO was not statistically demonstrated, we found a trend toward an association between EPO dosage and reduced mortality and increased embolic events in patients with TBI. More high-quality original studies should be conducted to obtain strong evidence on the optimal dosage of EPO.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=272500. The study protocol was registered with PROSPERO (CRD42021272500).

ObjectivesThe purpose is to analyze existing studies related to the field of demoralization through bibliometrics.MethodologyRelevant literature on demoralization was searched from PubMed, Web of Science, the Cochrane Library, and CINAHL Complete. Bibliometric analysis was performed using GraphPad Prisma 8.2.1, VOSviewer 1.6.18 and R software. Research publication trends, author-country collaboration, research hotspots and future trends were explored by generating network relationship maps.ResultsA total of 1,035 publications related to the field of demoralization were identified. The earliest relevant studies have been published since 1974, and the studies have grown faster since 2000. Psyche-oncology and Psychother Psychosom had the highest number of publications (n = 25). The United States, Italy and Australia have made outstanding contributions to the field and there was an active collaboration among leading scholars. Major research hotspots include the multiple ways of assessing demoralization, the specificity of various demographics and psychological disorders in different disease contexts, and the association and distinction of diverse clinical psychological abnormalities. The impact of COVID-19 on demoralization and subsequent interventions and psychological care may become a future research direction.ConclusionThere has been a significant increase in research in the field of demoralization after 2000. The United States provided the most publications. There is overall active collaboration between authors, countries, and institutions. In future research, more attention will be paid to the effects of COVID-19 on demoralization and intervention care for this psychology.

Introduction In recent years, the concept of living systematic review (LSR) has attracted the attention of many scholars and institutions. A growing number of studies have been conducted based on LSR methodology, but their focus direction is unclear. The objective of this study was to provide a comprehensive review of existing LSR-related studies and to analyse their whole picture and future trends with bibliometrics.Methods A comprehensive search strategy was used to construct a representative dataset of LSRs up to October 2021. GraphPad V.8.2.1 and Mindmaster Pro presented the basic information of the included studies and the timeline of LSR development, respectively. The author and country cooperation network, hotspot distribution clustering, historical citation network and future development trend prediction related to LSR were visualised by VOSviewer V.1.6.16 and R-Studio V.1.4.Results A total of 213 studies were eventually included. The concept of LSR was first proposed in 2014, and the number of studies has proliferated since 2020. There was a closer collaboration between author teams and more frequent LSR research development and collaboration in Europe, North America and Australia. Numerous LSR studies have been published in high-impact journals. COVID-19 is the predominant disease of concern at this stage, and the rehabilitation of its patients and virological studies are possible directions of research in LSR for a long time to come. A review of existing studies found that more than half of the LSR series had not yet been updated and that the method needed to be more standardised in practice.Conclusion Although LSR has a relatively short history, it has received much attention and currently has a high overall acceptance. The LSR methodology was further practised in COVID-19, and we look forward to seeing it applied in more areas.

Option pricing is an important research field in financial markets, and the American option is a common financial derivative. Fast and accurate pricing solutions are critical to the stability and development of the market. Computational techniques, especially the least squares Monte Carlo (LSMC) method, have been broadly used in optimizing the pricing algorithm. This paper discusses the application of distributed computing technology to enhance the LSMC in American option pricing. Although parallel computing has been used to improve the LSMC method, this paper is the first to explore distributed computing technology for LSMC enhancement. Compared with parallel computing, distributed computing has several advantages, including reducing the computational complexity by the “divide and conquer” method, avoiding the complicated matrix transformation, and improving data privacy as well as security. Moreover, LSMC is suitable for distributed computing because the price paths can be simulated and regressed separately. This research aims to show how distributed computing, particularly the divide and conquer approach implemented by Apache Spark, can be used to improve the efficiency and accuracy of LSMC in American option pricing. This paper provides an innovative solution to the financial market and could contribute to the advancement of American option pricing research.

In this paper, we developed a Shiny-based application called AutoReserve. This application serves as a tool used for a variety of types of loss reserving. The primary target audience of the app is personal auto actuaries, who are professionals in the insurance industry specializing in assessing risks and determining insurance premiums for personal vehicles. However, the app is not limited exclusively to actuaries. Other individuals or entities, such as insurance companies, researchers, or analysts, who have access to the necessary data and require insights or analysis related to personal auto insurance, can also benefit from using the app. It is the first web-based application of its kind that is free to use and deployable from the personal computer or mobile device. AutoReserve is a software solution that caters to the needs of insurance professionals where only a few existing web-based applications are available. The application is divided into three parts: a summary of the loss data, a classical loss reserving tool, and a machine learning loss reserving tool. Each component of the application functions differently and allows for inputs from the user to analyze the provided loss data. The user, in other words, individuals or entities who utilize the Auto Reserve application, can then use the outputs for these three sections to improve his or her risk management or loss reserving process. AutoReserve is unique compared to other loss reserving tools because of its ability to employ both traditional, spreadsheet-based and modern, machine-learning-based loss reserving tools. AutoReserve is accessible on the web. The app is currently usable and is still undergoing frequent updates with new features and bug fixes.

In-wheel motors for new energy vehicles are close to the brake, which results in a high ambient temperature. Thus, there is a high demand for cooling systems. This paper designs an oil-spray-cooled system based on the flat structural characteristics of an in-wheel motor. A computational fluid dynamics method with a two-phase volume-of-fluid model is applied to simulate the transient process of oil spraying from nozzles onto the stator carrier and then dripping to the end windings. The spatially distributed fluid interfaces with location and shape fidelity are derived. Considering the big difference of thermal inertia between the motor solid and oil fluid, the mixed timescale method is applied to calculate the temperature fields of the fluid and solid. Finally, a prototype is fabricated and tested to verify the proposed oil-cooling system and simulation method.

The fate of mesenchymal stem cells (MSCs) is regulated by biological, physical and chemical signals. Developments in biotechnology and materials science promoted the occurrence of bioactive materials which can provide physical and chemical signals for MSCs to regulate their fate. In order to design and synthesize materials that can precisely regulate the fate of MSCs, the relationship between the properties of materials and the fate of mesenchymal stem cells need to be clarified, in which the detection of the fate of mesenchymal stem cells plays an important role. In the past 30 years, a series of detection technologies have been developed to detect the fate of MSCs regulated by bioactive materials, among which high-throughput technology has shown great advantages due to its ability to detect large amounts of data at one time. In this review, the latest research progresses of detecting the fate of MSCs regulated by bone bioactive materials (BBMs) are systematically reviewed from traditional technology to high-throughput technology which is emphasized especially. Moreover, current problems and the future development direction of detection technologies of the MSCs fate regulated by BBMs are prospected. The aim of this review is to provide a detection technical framework for researchers to establish the relationship between the properties of BMMs and the fate of MSCs, so as to help researchers to design and synthesize BBMs better which can precisely regulate the fate of MSCs.

Abstract It is essential to know the normal range of the interocular symmetry of the cornea (ISC) for keratoconus diagnosis and corneal substitutes design. In the present study we investigated the interocular symmetry of corneal biometrics in 6,644 Chinese myopic patients from multiple ophthalmic centers. Corneal biometrics of both eyes were exported from the Pentacam instrument. Interocular symmetry of the corneal biometrics was analyzed by Spearman’s correlation test, intraclass correlation coefficient (ICC) analysis and Bland–Altman plot. Significantly strong interocular correlations were found in anterior and posterior corneal curvatures, corneal diameter, corneal thickness, corneal volume, corneal eccentricity, and corneal asphericity (r = 0.87–0.98, all P

In multi-robot simultaneous localization and mapping (SLAM) systems, the system must create a consistent global map with multiple local maps and loop closures between robot poses. However, false-positive loop closures caused by perceptual aliasing can severely distort the global map, especially in GNSS-denied areas, where a good prior of relative poses between robots is unavailable. In addition, the performance of the consistency metric in existing map fusion methods relies on accurate odometry from each robot. However, in practice, cumulative noise is inevitably present in robot trajectories, which leads to poor map fusion with existing methods. Thus, in this paper, we propose a robust consistency-based inter-robot and intra-robot loop closure selection algorithm for map fusion. We consider both pairwise-loop consistency and loop-odometry consistency to improve robustness against false-positive loop closures and accumulative noise in the odometry. Specifically, we select a reliable inter-robot loop closure measurement with a consistency-based strategy to provide an initial prior of relative pose between two robot trajectories and update the pose variables of the robot trajectories. The loop closure selection problem is formulated as a maximum edge weight clique problem in graph theory. A performance evaluation of the proposed method was conducted on the ManhattanOlson3500, modified CSAIL and Bicocca datasets, and the experimental results demonstrate that the proposed method outperforms the pairwise consistency measurement set maximization method (PCM) under severe accumulative noise and can be integrated with M-estimation methods.

The existence of information silos between vehicles and parking lots means that Unmanned Ground Vehicles (UGVs) repeatedly drive to seek available parking slots, resulting in wasted resources, time consumption and traffic congestion, especially in high-density parking scenarios. To address this problem, a novel UGV parking planning method is proposed in this paper, which consists of cooperative path planning, conflict resolution strategy, and optimal parking slot allocation, intending to avoid ineffective parking seeking by vehicles and releasing urban traffic pressure. Firstly, the parking lot induction model was established and the IACA–IA was developed for optimal parking allocation. The IACA–IA was generated using the improved ant colony algorithm (IACA) and immunity algorithm. Compared with the first-come-first-served algorithm (FCFS), the normal ant colony algorithm (NACA), and the immunity algorithm (IA), the IACA–IA was able to allocate optimal slots at a lower cost and in less time in complex scenarios with multi-entrance parking lots. Secondly, an improved conflict-based search algorithm (ICBS) was designed to efficiently resolve the conflict of simultaneous path planning for UGVs. The dual-layer objective expansion strategy is the core of the ICBS, which takes the total path cost of UGVs in the extended constraint tree as the first layer objective, and the optimal driving characteristics of a single UGV as the second layer objective. Finally, three kinds of load-balancing and unbalanced parking scenarios were constructed to test the proposed method, and the performance of the algorithm was demonstrated from three aspects, including computation, quality and timeliness. The results show that the proposed method requires less computation, has higher path quality, and is less time-consuming in high-density scenarios, which provide a reasonable and efficient solution for innovative urban mobility.

To investigate the evolution of the continental crust in the northern Tibetan Plateau, detrital zircon U–Pb geochronology and Hf isotopes analysis were performed on two fluvial sand samples from North Qaidam (the Yuka and Shaliu rivers). A total of 443 detrital zircon U–Pb ages and 244 Hf isotopic results were obtained and reveal that the South Qilian, North Qaidam, and East Kunlun terranes show affinity to the western Yangtze Block. Age distributions of detrital zircons from the Yuka River cluster mainly in two age intervals of 1,000–700 and 480–400 Ma. The corresponding εHf(t) values are mostly negative, with depleted two-stage Hf model ages (TDM2) of 2.1–1.6 Ga. In contrast, age data for the Shaliu River fall in the ranges of 1,000–700, 460–380, and 260–200 Ma, with TDM2 ages of 2.0–1.6 and 1.6–1.2 Ga. In addition, zircons with Neoproterozoic ages from both river samples possess common Paleoproterozoic TDM2 ages (2.0–1.6 Ga, with a peak of 1.8–1.7 Ga), indicating that the South Qilian, North Qaidam and East Kunlun terranes were probably part of the same Neoproterozoic continent. The East Kunlun and North Qaidam terranes are inferred to include Mesoproterozoic continental crust (1.6–1.0 Ga), suggesting differences in crustal evolution between the East Kunlun–North Qaidam and Qilian terranes. Phanerozoic magmatism in these three terranes was sourced mainly from the recycling of ancient continental crust with minor contributions from the juvenile crust.

Objectives: This study aimed to evaluate the predictive validity of the day‐1 PELOD‐2 and day‐1 “quick” PELOD‐2 (qPELOD‐2) scores for in‐hospital mortality in children with sepsis in a pediatric intensive care unit (PICU) of a developing country. Methods: The data of 516 children diagnosed as sepsis were retrospectively analyzed. The children were divided into survival group and non‐survival group, according to the clinical outcome 28 days after admission. Day‐1 PELOD‐2, day‐1 qPELOD‐2, pediatric SOFA (pSOFA), and P‐MODS were collected and scored. Receiver operating characteristic (ROC) curves were plotted, and the efficiency of the day‐1 PELOD‐2, day‐1 qPELOD‐2 score, pSOFA, and P‐MODS for predicting death were evaluated by the area under the ROC curve (AUC). Results: The day‐1 PELOD‐2 score, day‐1 qPELOD‐2 score, pSOFA, and P‐MODS in the non‐survivor group were significantly higher than those in the survivor group. ROC curve analysis showed that the AUCs of the day‐1 PELOD‐2 score, day‐1 qPELOD‐2 score, pSOFA, and P‐MODS for predicting the prognosis of children with sepsis in the PICU were 0.916, 0.802, 0.937, and 0.761, respectively (all p < 0.05). Conclusions: Both the day‐1 PELOD‐2 score and day‐1 qPELOD‐2 score were effective and able to assess the prognosis of children with sepsis in a PICU of a developing country. Additionally, the day‐1 PELOD‐2 score was superior to the day‐1 qPELOD‐2 score. Further studies are needed to verify the usefulness of the day‐1 qPELOD‐2 score, particularly outside of the PICU. Resumo: Objetivos: A finalidade de nosso estudo foi avaliar a validade preditiva dos escores PELOD‐2 no dia 1 e “quick” PELOD‐2 no dia 1 com relação à mortalidade hospitalar em crianças com sepse em uma UTIP de um país em desenvolvimento. Métodos: Foram analisados retrospectivamente os dados de 516 crianças diagnosticadas com sepse. As crianças foram divididas em grupo sobrevida e grupo não sobrevida de acordo com o desfecho clínico de 28 dias após internação. Foram coletadas e pontuadas as variáveis PELOD‐2 no dia 1, qPELOD‐2 no dia 1, pediatric Sequential Organ Failure Assessment (pSOFA) e Pediatric Multiple Organ Dysfunction Score (P‐MODS). A curva da característica de operação do receptor (ROC) foi plotada e a eficiência preditiva do PELOD‐2 no dia 1, o escore qPELOD‐2 no dia 1, pSOFA, P‐MODS com relação a óbito foram avaliados pela área abaixo da curva (AUC) da curva ROC. Resultados: O escore PELOD‐2 no dia 1, escore qPELOD‐2 no dia 1, pSOFA e P‐MODS no grupo não sobrevida foram significativamente maiores do que os no grupo sobrevida. A análise preditiva da curva ROC mostrou que as AUCs do escore PELOD‐2 no dia 1, escore qPELOD‐2 no dia 1, pSOFA e P‐MODS com relação ao prognóstico de crianças com sepse na UTIP foi 0,916, 0,802, 0,937 e 0,761, respectivamente (todas p < 0,05). Conclusões: Tanto o escore PELOD‐2 no dia 1 e o escore qPELOD‐2 no dia 1 foram válidos e conseguiram avaliar o prognóstico de crianças com sepse em uma UTIP de um país em desenvolvimento. Além disso, o escore PELOD‐2 no dia 1 foi superior ao escore qPELOD‐2 no dia 1. São necessários estudos adicionais para verificar a utilidade do escore qPELOD‐2 no dia 1, principalmente fora da UTIP.

Functional overlaps and conflicts between Electronic Power Steering (EPS) and Torque Vectoring Control (TVC) for Distributed Drive Electric Vehicles (DDEVs) are issues that need to be addressed urgently. This paper deals with the interaction between EPS and TVC from the view of the influence mechanism and control objectives. The disturbance steering torque caused by the differential torque is estimated and a unified steering characteristic is proposed. To validate the analysis results, a torque compensation strategy is modified based on the exiting control system. And a robust vehicle state estimator is built thanks to the aligning torque estimation to provide the necessary information. Typical ground test results show that the torque oscillation on the steering wheel is suppressed. A faster and more linear steering response can be seen, which means that the proposed disturbance compensation strategy can comfort the contradiction between EPS and TVC, also improve the handling performance of the vehicle.

Slip rate control is important in improving vehicle stability and driving efficiency. In this paper, a robust slip rate control system is designed for distributed drive electric vehicles that consists of two slip rate estimators for multi-driving conditions, a vehicle speed estimator, and an anti-windup robust variable structure slip rate tracking controller. Because there is no driven wheel in a four-in-wheel-motor distributed drive electric vehicle, the estimators for small and large slip rates are designed based on dynamic and kinematic methods, respectively, which can switch according to the slip conditions. The convergence of the estimation error is discussed with the Lyapunov stability law and is less than 2% under the condition of acceleration on a low-friction road. The slip rate tracking controller is designed based on the sliding mode control law and the proportional-integral (PI) control method to handle model nonlinearity, modelling and estimation errors, and disturbances and to control the input chattering and saturation. The asymptotic stability of the tracking error is proven by Lyapunov theory. A joint control variable composed of the wheel angular acceleration and slip rate is designed to improve the robustness of the controller against the slip rate estimation error. Simulations and experiments under various conditions are performed to verify the proposed anti-slip control method. The results show that compared with a distributed drive vehicle without a slip rate controller, the controlled vehicle can prevent serious wheel skid on low-adhesion roads and improve the driving performance.

Background: Ewing sarcoma (ES) of bone is accounting for the second most common type of primary bone cancer in children and adolescents. However, the patterns of distant metastasis (DM) and the effect of the sites of DM on survival outcomes were not investigated. Aims: This study aimed to investigate the patterns of DM and the prognostic factors related to outcomes in primary metastatic ES of the bone. Methods: Patients who were diagnosed with primary metastatic ES between 2010 and 2018 were identified from the Surveillance, Epidemiology, and End Results database. Kaplan–Meier analysis, log-rank tests, and Cox proportional-hazards regression models were used for statistical analyses. Results: We identified 277 patients in this study and 95.3% of them (n = 264) receiving chemotherapy. A total of 371 sites of DM were observed. Lung was the most common distant metastatic site (n = 182, 49.1%), followed by bone (n = 139, 37.5%), distant lymph node (n = 26, 7.0%), liver (n = 14, 3.8%), and brain (n = 10, 2.7%). Three-year cause-specific survival (CSS) was 56.1% in the entire cohort. Older age (hazard ratio [HR] 2.210, P

The tire-road peak adhesion coefficient (TRPAC), which cannot be directly measured by on-board sensors, is essential to road traffic safety. Reliable TRPAC estimation can not only serve the vehicle active safety system, but also benefit the safety of other traffic participants. In this paper, a TRPAC fusion estimation method considering model uncertainty is proposed. Based on virtual sensing theory, an image-based fusion estimator considering the uncertainty of the deep-learning model and the kinematic model is designed to realize the accurate classification of the road surface condition on which the vehicle will travel in the future. Then, a dynamics-image-based fusion estimator considering the uncertainty of visual information is proposed based on gain scheduling theory. The results of simulation and real vehicle experiments show that the proposed fusion estimation method can make full use of multisource sensor information, and has significant advantages in estimation accuracy, convergence speed and estimation robustness compared with other single-source-based estimators.

As the transportation industry develops new forms of energy and electrification, expressway dynamic wireless charging has become an attractive technology that has the potential to completely solve a range of anxieties associated with electric vehicles. The main objective of this paper was to analyze the economic feasibility of dynamic wireless charging projects on highways. First, the roadside cost of dynamic wireless charging was estimated in terms of equipment, construction, and maintenance costs. Then, various indicators of the national economy of expressway dynamic wireless charging were analyzed. Finally, using the GM (1,1) model, a prediction model for evaluating the associated economic benefits is proposed in this study. As a case study, a national economic evaluation of retrofitting a dynamic wireless charging infrastructure on the Guiyang to Xinzhai Expressway was calculated with the following results: the economic internal rate of return (EIRR) is 11.27% to 29.11%, the economic net present value (ENPV) is 321.59 million RMB to 733.51 million RMB, the economic benefit to cost ratio (EBCR) is 1.02 to 1.32, and the payback period is 3.15 years to 6.35 years. All indicators are higher than the benchmark value for the national economic evaluation, and the sensitivity analysis results are also higher than the benchmark. The results of this paper show that the project is economically feasible and has certain economic benefits. From the perspective of economic benefits, it is necessary to provide more effective information for investors and decision-makers to build dynamic wireless charging highway projects.

TiO2 nanotubes arrays with dominant (001) facets were fabricated by multi-anodic oxidation technology. The influence factor of the electrolyte composition on the ratio of different facets for anatase TiO2 and the bioactivity were investigated. Besides, the characterization of the surface morphologies and crystal structures were analyzed by scanning electron microscope (SEM) and X-ray diffraction (XRD),etc. Finally, the bioactivity was estimated by the CaP salt deposition vis biomin-eralization process and protein adsorption experiment. The results show that the relative proportions of different facets in the TiO2 nanotubes can be adjusted by changing the content of H2O in the electrolyte. The (004) facet texture coefficient of TiO2 nanotubes arrays prepared in 2% H2O(volume fraction) electrolyte reaches up to 4.76. The TiO2 nanotubes with dominant (001) facets can accelerate the deposition of hydroxyapatite and raise the amount of protein adsorption in the humanoid environment by providing more active sites for biomineralization and protein adsorption. The TiO2 nanotubes with a higher proportion of (001) facets have the more excellent biological activity.

As one of the most promising nanomaterials, metal-organic framework (MOF) thin films (also known as surfacesupported MOF thin films, SURMOFs) have attracted much attention in recent years. The development of various synthetic methods makes it possible to obtain MOF thin films with controlled thickness, uniformity, morphology, and even dimensions, providing tremendous opportunities for more applications. Different synthesis methods of MOF thin films based on liquid phase or vacuum range were first introduced, and one of the most effective ways to fabricate quality thin films was depositing self-assembled monolayers (SAMs) on the primary substrate to further induce the nucleation and growth of MOF thin films. Furthermore, some traditional applications of MOF thin films (e. g. separation, catalysis, sensing) were summarized, as well as some newly-developed applications in photocatalysis, energy storage, photovoltaics, and electronic devices, which meet the demands for environmental sustainability and cleaner energy. Although the future is promising, MOF thin films still face some challenges. Therefore, some key factors those limit the MOF films' practical application were discussed, for example, the unclear growth mechanism of thin films, the poor quality and low film thermoe lectric performance. Based on the review of recent developments, this article will provide references for the future research of MOF thin films.

A novel driving behaviour oriented (DBO) trajectory planner and hierarchical analytic hierarchy process (HAHP) decision maker are presented for intelligent vehicle. Since driving on structural road should satisfy actuator constraints and improve comfortableness as soon as possible, which strictly obeys traffic rules other than making traffic mess, it is rather than purely pursuing the shortest route/time. By analysis traffic rules, the DBO framework is employed to produce trajectories. To make trajectory drivable, cubic B-spline and clothoid curve are modeled to keep continuous curvature, and cubic polynomial curve is to schedule velocity profile satisfying stability and comfort. To pick out the best trajectory, HAHP decision maker is developed to evaluate the candidates. The first layer selects optimal paths considering smoothness and economy, and the second layer selects best trajectory taking smoothness, comfortableness and economy in account. Moreover, DBO rapidly exploring random tree (RRT) replanner is embedded to ensure algorithm completeness. Finally, several typical scenarios are designed to verify the real-time and reliability of the algorithm. The results illustrate that the algorithm has highly real-time and stability evaluated by Statistical Process Control method as the probability for the peak time less than 0.1s is 100% except three obstacles avoidance scenario is 59.31% in 1000 cycles. Since the planned trajectory is smooth enough and satisfy the constraints of the actuator, the mean lateral tracking error is less than 0.2m with 0.5m peak error, and the mean speed error less than 0.5km/h with 1.5km/h peak error for all scenarios.

Cryptochrome 1 (CRY1) is an important light receptor essential for de-etiolation of Arabidopsis seedlings. However, its function in regulating plant architecture remains unclear. Here, we show that mutation in CRY1 resulted in increased branching of Arabidopsis plants. To investigate the underlying mechanism, we analyzed the expression profiles of branching-related genes and found that the mRNA levels of Phytochrome Interaction Factor 4 (PIF4) and PIF5 are significantly increased in the cry1 mutant. Genetic analysis showed that the pif4 or pif4pif5 mutant is epistatic to the cry1 mutant, and overexpression of PIF4 conferred increased branching. Moreover, we demonstrated that PIF4 proteins physically associate with the G-box motif within the PIF4 promoter to form a self-activated transcriptional feedback loop, while CRY1 represses this process in response to blue light. Taken together, this study suggests that the CRY1–PIF4 module regulates gene expression via forming a regulatory loop and shoot branching in response to ambient light conditions.

The glass fiber reinforced polypropylene (GF/PP) composite plate with different glass fiber contents was fabricated by the laminated hot-pressing experiment method using the glass fiber felt and polypropylene film, then tensile experiments were carried on under different loading rates. The strain rate sensitive properties of the composites were investigated, and the feasibility of the Burgers model fitting to predict the constitutive relation of the material was analyzed. The results show that the GF/PP composite in the low strain rates is sensitive to strain rate, with the increase of strain rate, the fracture stress and tensile strength increase, and with the increase of the glass fiber content, the strain rate effect decreases. Meanwhile, the Burgers model can effectively fit to predict the tensile stress-strain curves of the composites, then compared with the experimental curves, which further validates the strain rate sensitive properties of the GF/PP composites and its trend.

Stable maneuverability is extremely important for the overall safety and robustness of autonomous vehicles under extreme conditions, and automated drift is able to ensure the widest possible range of maneuverability. However, due to the strong nonlinearity and fast vehicle dynamics occurring during the drift process, drift control is challenging. In view of the drift parking scenario, this paper proposes a segmented drift parking method to improve the handling ability of vehicles under extreme conditions. The whole process is divided into two parts: the location approach part and the drift part. The model predictive control (MPC) method was used in the approach to achieve consistency between the actual state and the expected state. For drift, the open-loop control law was designed on the basis of drift trajectories obtained by professional drivers. The drift monitoring strategy aims to monitor the whole drift process and improve the success rate of the drift. A simulation and an actual vehicle test platform were built, and the test results show that the proposed algorithm can be used to achieve accurate vehicle drift to the parking position.

At present, the master cylinder pressure estimation algorithm (MCPE) of electro-hydraulic brake systems (EHB) based on vehicle dynamics has the disadvantages of poor condition adaptability, and there are delays and noise in the estimated pressure; however, the MCPE based on the characteristics of an EHB (i.e., the pressure–position relationship) is not robust enough to prevent brake pad wear. For the above reasons, neither method be applied to engineering. In this regard, this article proposes a MCPE that is based on signal fusion. First, a five-degree-of-freedom (5-DOF) vehicle model that includes longitudinal motion, lateral motion, yaw motion, and front and rear wheel rotation is established. Based on this, an algebraic expression for MCPE is derived, which extends the MCPE from a straight condition to a steering condition. Real vehicle tests show that the MCPE based on the 5-DOF vehicle model can effectively estimate the brake pressure in both straight and steering conditions. Second, the relationship between the hydraulic pressure and the rack position in the EHB is tested under different brake pad wear levels, and the results show that the pressure–position relationship will change as the brake pad is worn down, so the pressure estimated by the pressure–position model based on fixed parameters is not robust. Third, a MCPE based on the fusion the above two MCPEs through the recursive least squares algorithm (RLS) is proposed, in which the pressure-position model can be updated online by vehicle dynamics and the final estimated pressure is calculated based on the updated pressure–position model. Finally, several simulations based on vehicle test data demonstrate that the fusion-based MCPE can estimate the brake pressure accurately and smoothly with little delay and is robust enough to prevent brake pad wear. In addition, by setting the enabling conditions of RLS, the fusion-based MCPE can switch between driving and parking smoothly; thus, the fusion-based MCPE can be applied to all working conditions.

This paper proposes an optimized trajectory planner and motion planner framework, which aim to deal with obstacle avoidance along a reference road for autonomous driving in unstructured environments. The trajectory planning problem is decomposed into lateral and longitudinal planning sub-tasks along the reference road. First, a vehicle kinematic model with road coordinates is established to describe the lateral movement of the vehicle. Then, nonlinear optimization based on a vehicle kinematic model in the space domain is employed to smooth the reference road. Second, a multilayered search algorithm is applied in the lateral-space domain to deal with obstacles and find a suitable path boundary. Then, the optimized path planner calculates the optimal path by considering the distance to the reference road and the curvature constraints. Furthermore, the optimized speed planner takes into account the speed boundary in the space domain and the constraints on vehicle acceleration. The optimal speed profile is obtained by using a numerical optimization method. Furthermore, a motion controller based on a kinematic error model is proposed to follow the desired trajectory. Finally, the experimental results show the effectiveness of the proposed trajectory planner and motion controller framework in handling typical scenarios and avoiding obstacles safely and smoothly on the reference road and in unstructured environments.

Based on the feasibility of the discharge machining of the semiconductor material,it analyze several major factors which influences the material removal rate,including the open circuit voltage,peak current,pulse width and pulse interval.Using central composite design experiments,it inspects the influence of the three factors peak current、pulse width and pulse interval to the material removal rate of the monocrystalline silicon in the course of the electrical discharge machining and establishes a response model of the material removal rate of the monocrystalline silicon in the course of the electrical discharge machining and makes analysis to the response surface. The result of the variance analysis indicate that the model has good fitting degree and adaptability. It uses satisfactory rate function（ DFA） to determine the optimum technology parameters of the monocrystalline silicon in the course of the electrical discharge When the value of the peak current is 18. 5 A,the value of the pulse width is 358. 62μs,the value of the pulse interval is 20μs and the degree of satisfaction is 0. 912,then the optimal value of the material removal rate is 76. 26 mm~3/min It has measured the average MRR of the P type monocrystalline silicon is 73. 86mm~3/min through repeated experiments many times on the electrical discharge shaping machine with the optimal processing parameters which are identified The average relative error of the model prediction results compare with experimental results under the optimum technological parameters is 3. 4%. The verification test indicates that this model can achieve the prediction of the material removal rate of the corresponding semiconductor material in the course of the discharge machining.

Tripartite motif (TRIM) proteins are RING E3 ubiquitin ligases defined by a shared domain structure. Several of them are implicated in rare genetic diseases, and mutations in TRIM32 and TRIM-like malin are associated with Limb-Girdle Muscular Dystrophy R8 and Lafora disease, respectively. These two proteins are evolutionary related, share a common ancestor, and both display NHL repeats at their C-terminus. Here, we revmniew the function of these two related E3 ubiquitin ligases discussing their intrinsic and possible common pathophysiological pathways.

To mitigate the issue of low accuracy and poor robustness of the master cylinder pressure estimation (MCPE) of the electro-hydraulic brake system (EHB) by adopting EHB’s own information, a MCPE algorithm based on vehicle information considering the evolution of the brake linings’ coefficient of friction (BLCF) is proposed. First, the MCPE algorithm was derived combining the vehicle longitudinal dynamics and the wheel dynamics, in which the inertial measurement unit (IMU) was adopted to adapt the MCPE algorithm to road slope change. In order to estimate the brake pressure accurately, the driving resistance of the vehicle was obtained through a vehicle test under coasting condition. After that, with the active braking function of EHB, the evolution of the BLCF was acquired through extensive real vehicle test under different initial temperatures, different initial vehicle speeds, and different brake pressures. According to the test results, a revised model of the BLCF is proposed. Finally, the performance of the MCPE based on the revised BLCF model was compared with that based on a fixed BLCF model. Vehicle test demonstrates that the former MCPE algorithm is not only more accurate at low vehicle speed than the later, but also robust to road slope change.

Background/Aims: Different genotypes of HCV may differ in both disease progression and response to antiviral therapies. Hainan Island has been inhabited by the “Li” aboriginal minority for centuries. We aimed to provide a better understanding of HCV infection on Hainan Island, so that the information would help improve strategies for HCV prevention and control on the island and in the wider country. Methods: Using RT-PCR and DNA sequencing, we determined HCV sequences from 100 patients living on Hainan Island. Results: Phylogenetic analysis classified these sequences into six subtypes: 6a (n=35), 1b (n=31), 3b (n=16), 2a (n=8), 3a (n=6), and 1a (n=4). By including reference sequences reported from elsewhere in China, phylogeographic trees were reconstructed to indicate their migration patterns. While the predominant 6a isolates were estimated to have origins in Guangdong and Guangxi provinces, the increase in 3b strains must have resulted from IDU network transmission from the southwest. A Bayesian Skyline Plot for subtype 1a, which is rare in China, showed a rapid population growth since 1998. Although slowed in rate around 2005, this growth continued to the present. Not found for any other HCV lineage. Conclusions: Overall, a delayed growth pattern may indicate the unique history of 1a dissemination in China and its recently increasing prevalence, despite measures taken to improve HCV prevention.

Perception of road structures especially the traffic intersections by visual sensors is an essential task for automated driving. However, compared with intersection detection or visual place recognition, intersection re-identification (intersection re-ID) strongly affects driving behavior decisions with given routes, yet has long been neglected by researchers. This paper strives to explore intersection re-ID by a monocular camera sensor. We propose a Hybrid Double-Level re-identification approach which exploits two branches of Deep Convolutional Neural Network to accomplish multi-task including classification of intersection and its fine attributes, and global localization in topological maps. Furthermore, we propose a mixed loss training for the network to learn the similarity of two intersection images. As no public datasets are available for the intersection re-ID task, based on the work of RobotCar, we propose a new dataset with carefully-labeled intersection attributes, which is called “RobotCar Intersection” and covers more than 30,000 images of eight intersections in different seasons and day time. Additionally, we provide another dataset, called “Campus Intersection” consisting of panoramic images of eight intersections in a university campus to verify our updating strategy of topology map. Experimental results demonstrate that our proposed approach can achieve promising results in re-ID of both coarse road intersections and its global pose, and is well suited for updating and completion of topological maps.

In order to conduct risk assessment for collision-free decision making of intelligent vehicles in a complex road traffic environment, it is essential to conduct stable tracking and state estimation of multiple vehicle targets. Therefore, this paper proposes a multitarget tracking method in line with the priority data association rule. Firstly, a standard coordinate turn process model is deduced as the existence of translation and rotation of the vehicle on the two-dimensional ground plane. Secondly, an unscented Kalman filter algorithm is developed due to the nonlinear radar measurement model. Thirdly, a priority data association rule, which puts the targets in a priority queue according to the number of times they are associated, is designed to filter out noise, given that it is unlikely for a vehicle target as an inertial system to appear or disappear instantly in practice. In addition, the data association rule specifies that the closer the target is to the front of the queue, the more prioritized the association with the newly observed target would be. Finally, the track management algorithm is constructed. On this basis, a series of real vehicle tests were conducted on real roads with four typical scenarios. According to the test results, the proposed algorithm is effective in filtering out noise and is suboptimal as the nearest neighbor data association.

As one of the core issues of autonomous vehicles, vehicle motion control directly affects vehicle safety and user experience. Therefore, it is expected to design a simple, reliable, and robust path following the controller that can handle complex situations. To deal with the longitudinal motion control problem, a speed tracking controller based on sliding mode control with nonlinear conditional integrator is proposed, and its stability is proved by the Lyapunov theory. Then, a linear parameter varying model predictive control (LPV-MPC) based lateral controller is formulated that the optimization problem is solved by CVXGEN. The nonlinear active disturbance rejection control (ADRC) method is applied to the second lateral controller that is easy to be implemented and robust to parametric uncertainties and disturbances, and the pure pursuit algorithm serves as a benchmark. Simulation results in different scenarios demonstrate the effectiveness of the proposed control schemes, and a comparison is made to highlight the advantages and drawbacks. It can be concluded that the LPV-MPC has some trouble to handle uncertainties while the nonlinear ADRC performs slight worse tracking but has strong robustness. With the parallel development of the control theory and computing power, robust MPC may be the future direction.

Ochratoxin A (OTA) is a toxic secondary metabolite produced mainly by Penicillium spp. and Aspergillus spp. and commonly found in foodstuffs and feedstuffs. Carboxypeptidase A (CPA) can hydrolyze OTA into the non-toxic product ochratoxin α, with great potential to realize industrialized production and detoxify OTA in contaminated foods and feeds. This study constructed a P. pastoris expression vector of mature CPA (M-CPA) without propeptide and signal peptide. The results showed that the degradation rate of OTA by M-CPA was up to 93.36%. Its optimum pH was 8, the optimum temperature was 40 °C, the value of Km was 0.126 mmol/L, and the maximum reaction rate was 0.0219 mol/min. Compared with commercial CPA (S-CPA), the recombinant M-CPA had an improve stability, for which its optimum temperature increased by 10 °C and stability at a wide range pH, especially at pH 3–4 and pH 11. M-CPA could effectively degrade OTA in red wine. M-CPA has the potential for industrial applications, such as can be used as a detoxification additive for foods and feeds.

We propose a completely unsupervised approach to simultaneously estimate scene depth, ego-pose, ground segmentation and ground normal vector from only monocular RGB video sequences. In our approach, estimation for different scene structures can mutually benefit each other by the joint optimization. Specifically, we use the mutual information loss to pre-train the ground segmentation network and before adding the corresponding self-learning label obtained by a geometric method. By using the static nature of the ground and its normal vector, the scene depth and ego-motion can be efficiently learned by the self-supervised learning procedure. Extensive experimental results on both Cityscapes and KITTI benchmark demonstrate the significant improvement on the estimation accuracy for both scene depth and ego-pose by our approach. We also achieve an average error of about 3 ∘ for estimated ground normal vectors. By deploying our proposed geometric constraints, the IOU accuracy of unsupervised ground segmentation is increased by 35% on the Cityscapes dataset.

How to make a controller robust and stable to reject the disturbance of uncertainty is an inevitable challenge. Aiming at addressing the lateral control problem for an autonomous road sweeper, a heading-error-based first order linear active disturbance rejective controller (HFO-LADRC) is proposed in this paper. To eliminate the lateral error and the heading error at the same time, a new model, called the heading-error-based model, is proposed for lateral motion, and the Lyapunov function was employed to explore the convergence ability of the heading error and lateral error. Since the heading-error-based model is first order, the ADRC is designed as first order and linear, and each module of the HFO-LADRC has been devised in detail. To ensure solution accuracy, the fourth order Runge–Kutta method was adopted as the differential system solver, and a typical ring scenario and a double lane-changing scenario were designed referencing the standard. Considering the obvious influence, wheelbase uncertainty, steering ratio uncertainty and Gaussian white noise disturbance were taken into account for the tests. The results illustrate that, in the case of both wheelbase uncertainty and steer ratio uncertainty, the HFO-LADRC has strong robustness and stability compared with a typical pure pursuit controller and classical SO-LADRC.

According to the existing mainstream automatic parking system (APS), a parking path is first planned based on the parking slot detected by the sensors. Subsequently, the path tracking module guides the vehicle to track the planned parking path. However, since the vehicle is non-linear dynamic, path tracking error inevitably occurs, leading to inclination and deviation of the parking. Accordingly, in this paper, a reinforcement learning-based end-to-end parking algorithm is proposed to achieve automatic parking. The vehicle can continuously learn and accumulate experience from numerous parking attempts and then learn the command of the optimal steering wheel angle at different parking slots. Based on this end-to-end parking, errors caused by path tracking can be avoided. Moreover, to ensure that the parking slot can be obtained continuously in the process of learning, a parking slot tracking algorithm is proposed based on the combination of vision and vehicle chassis information. Furthermore, given that the learning network output is hard to converge, and it is easy to fall into local optimum during the parking process, several reinforcement learning training methods in terms of parking conditions are developed. Lastly, by the real vehicle test, it is proved that using the proposed method can achieve a better parking attitude than using the path planning and path tracking-based method.