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Abstract LHPP, a novel, recognized tumor suppressor, exerts a critical influence on the regulation of tumor cell proliferation and survival by modulating various signaling pathways with its phosphatase activity. Here, we unveil a robust correlation between reduced LHPP expression and adverse prognosis in prostate cancer. We demonstrate that LHPP interacts with AKT, thereby dampening AKT phosphorylation and subsequently inhibiting ACSL4 phosphorylation at the T624 site. This interaction impedes phosphorylation-dependent ubiquitination, thwarting SKP2 from recognizing and binding to ACSL4 at the K621 site. As a result, ACSL4 is spared from lysosomal degradation, leading to its accumulation and the promotion of lipid peroxidation, and ferroptosis. Moreover, our findings reveal that Panobinostat, a potent histone-deacetylase inhibitor, intricately regulates LHPP expression at multiple levels through the inhibition of HDAC3. This complex modulation enhances the ferroptosis pathway, offering a novel mechanism for curtailing the growth of prostate tumors and highlighting its significant translational potential for clinical application.

The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’ merging and lane-changing behaviors, while ensuring safety and optimizing traffic flow. However, there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization strategies. To tackle this issue, this study adopts a cyber-physical integration perspective and proposes a graph-based solution approach. First, the information of vehicle groups in the physical plane is mapped to the cyber plane, and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle groups. Subsequently, graph decomposition and search strategies are employed to obtain the optimal solution, including the set of mainline vehicles changing lanes, passing sequences for each route, and corresponding trajectories. Finally, the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities, and its performance is compared with the default algorithm in SUMO. The results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency, particularly in high traffic density scenarios, providing valuable insights for future research in multi-lane merging strategies.

Abstract Heat shock protein family B [small] member 6 (HSPB6), widely found in various muscles, has been recently identified as a tumor suppressor gene. However, its role in prostate cancer remains unexplored. Herein, we investigated the expression of HSPB6 in prostate cancer and its association with prognosis. Our findings revealed that HSPB6 downregulation in prostate cancer correlated with a poor prognosis. Moreover, we discovered that HSPB6 can be phosphorylated and activated by 8-Br-cGMP, leading to apoptosis in prostate cancer cells by activating Cofilin. Additionally, we demonstrated that knocking down E2F1 by quinidine administration enhances the transcriptional level of HSPB6. Furthermore, we evaluated the combination of quinidine and 8-Br-cGMP as a potential therapeutic strategy for prostate cancer. Our results revealed that the combined treatment was more effective than either treatment alone in inhibiting the growth of prostate cancer through the HSPB6 pathway, both in vitro and in vivo. Overall, our study provides compelling evidence that HSPB6 suppresses malignant behavior in prostate cancer by inducing apoptosis. The combination of quinidine and 8-Br-cGMP emerges as a promising approach for the treatment of prostate cancer.

Abstract Background Upper tract urothelial carcinoma (UTUC) is a rare disease, belonging to the same category of urothelial cancers as bladder cancer (BC). Despite sharing similar non-surgical treatment modalities, UTUC demonstrates a higher metastasis propensity than BC. Furthermore, although both cancers exhibit similar molecular disease emergence mechanisms, sequencing data reveals some differences. Our study investigates the transcriptomic distinctions between UTUC and BC, explores the causes behind UTUC's heightened metastatic tendency, constructs a model for UTUC metastasis and prognosis, and propose personalized treatment strategies for UTUC. Methods In our research, we utilized differential gene expression analysis, interaction networks, and Cox regression to explore the enhanced metastatic propensity of UTUC. We formulated and validated a prognostic risk model using diverse techniques, including cell co-culture, reverse transcription quantitative polymerase chain reaction (rt-qPCR), western blotting, and transwell experiments. Our methodological approach also involved survival analysis, risk model construction, and drug screening leveraging the databases of CTRPv2, PRISM and CMap. We used the Masson staining technique for histological assessments. All statistical evaluations were conducted using R software and GraphPad Prism 9, reinforcing the rigorous and comprehensive nature of our research approach. Results Screening through inflammatory fibrosis revealed a reduction of extracellular matrix and cell adhesion molecules regulated by proteoglycans in UTUC compared with BC, making UTUC more metastasis-prone. We demonstrated that SDC1, LUM, VEGFA, WNT7B, and TIMP3, are critical in promoting UTUC metastasis. A risk model based on these five molecules can effectively predict the risk of UTUC metastasis and disease-free survival time. Given UTUC's unique molecular mechanisms distinct from BC, we discovered that UTUC patients could better mitigate the issue of poor prognosis associated with UTUC's easy metastasis through tyrosine kinase inhibitors (TKIs) alongside the conventional gemcitabine and cisplatin chemotherapy regimen. Conclusions The poor prognosis of UTUC because of its high metastatic propensity is intimately tied to inflammatory fibrosis induced by the accumulation of reactive oxygen species. The biological model constructed using the five molecules SDC1, LUM, VEGFA, WNT7B, and TIMP3 can effectively predict patient prognosis. UTUC patients require specialized treatments in addition to conventional regimens, with TKIs exhibiting significant potential.

Abstract Background As a novel necrosis manner, ferroptosis has been increasingly reported to play a role in tumor progression and treatment, however, the specific mechanisms underlying its development in prostate cancer remain unclear. Growing evidence showed that peroxisome plays a key role in ferroptosis. Herein, we identified a novel mechanism for the involvement of ferroptosis in prostate cancer progression, which may provide a new strategy for clinical treatment of prostate cancer. Methods Label-Free Mass spectrometry was used to screen and identify candidate proteins after ferroptosis inducer-ML210 treatment. Immunohistochemistry was undertaken to explore the protein expression of AGPS in prostate cancer tissues compared with normal tissues. Co-immunoprecipitation and GST pull-down were used to identify the directly binding of AGPS to MDM2 in vivo and in vitro. CCK8 assay and colony formation assay were used to illustrate the key role of AGPS in the progression of prostate cancer in vitro. The xenograft model was established to verify the key role of AGPS in the progression of prostate cancer in vivo. Results AGPS protein expression was downregulated in prostate cancer tissues compared with normal tissues from the first affiliated hospital of Zhengzhou University dataset. Lower expression was correlated with poorer overall survival of patients compared to those with high expression of AGPS. In addition, AGPS can promote ferroptosis by modulating the function of peroxisome-resulting in the lower survival of prostate cancer cells. Furthermore, it was shown that AGPS can be ubiquitinated and degraded by the E3 ligase-MDM2 through the proteasomal pathway. Meanwhile, kinase TrkA can promote the combination of AGPS and MDM2 by phosphorylating AGPS at Y451 site. It was verified that kinase TrkA inhibitor—Larotrectinib can increase the susceptibility of prostate cancer cells to ferroptosis, which leads to the inhibition of prostate cancer proliferation to a great extent in vitro and in vivo. Conclusion Based on these findings, we proposed the combination of ferroptosis inducer and TrkA inhibitor to synergistically exert anti-tumor effects, which may provide a new strategy for the clinical treatment of prostate cancer.

The use of computer vision to estimate the Body Condition Score for cow has demonstrated to be feasible. However, most research has been limited to fixed camera positions, which restricts the technique’s usefulness. This research acquired cow data at various distances and angles to investigate the impact of distance and different depth images restoration method on scoring accuracy. A U-Net neural network-based model was employed for background segmentation. The model proposed in this study performs best among SegNet, UNet, UNet++ and DeeplabV3, with significant performance improvement and superior overall segmentation accuracy, and has stronger foreground object identification capability. Additionally, we utilize the concept of human feature point localization to pinpoint the positions of cow feature points. The results show that compared to Hourglass, CPN, and Hrnet, the model in this study has significant advantages in three core indicators: accuracy, recall, and mAP. Moreover, we presented an unsupervised depth image reconstruction model based on the Denoising Diffusion Probabilistic Model and Unet++ Mode, facilitating the measurement and scoring of cow characteristics. Finally, the measurement results of cow body size using the Lerp model, autoregressive model, GAN model, and the depth image completion model proposed in this study were compared. The method proposed in this study was found to be effective and feasible for meeting actual production requirements at a camera distance of 1–2 m from the cow, achieving high accuracy with a coefficient of determination above 0.9. Additionally, the three models used were effective in handling small-scale depth deficits, with a high degree of agreement between machine and manual measurements. The DDPM-based depth image reconstruction model was found to produce the most accurate results when the camera distance from the cow was between 1-3m. Therefore, this research makes it possible to make flexible measurements in the near range using existing methods. Accurate measurements at longer ranges are influenced by depth image quality and feature point localization accuracy, which require more advanced techniques for further investigation.

Abstract Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

In this paper, we consider the symmetry properties of the positive solutions of a $ p $-Laplacian problem of the form $ \begin{eqnarray*} \begin{cases} -{{\Delta}}_p u = f(x,u),\ \ \ \ \ \ \ \mathrm{in}\ \ \ \ \ {{\Omega}},\\ \ \ \ \ \ \ \ u = g(x), \ \ \ \ \ \ \ \ \ \ \mathrm{on}\ \ \ \ \partial{{\Omega}}, \end{cases} \end{eqnarray*} $ where $ {{\Omega}} $ is an open smooth bounded domain in $ R^N, N\geq2 $, and symmetric w.r.t. the hyperplane $ T_0^\nu (\nu $ is a direction vector in $ R^N, |\nu| = 1 $$) $, $ f $: $ {{\Omega}}\times R^+\rightarrow R^+ $ is a continuous function of class $ C^1 $ w.r.t. the second variable, $ g\geq 0 $ is continuous, and both $ f $ and $ g $ are symmetric w.r.t. $ T^\nu_0 $, respectively. Introducing some assumptions on nonlinearities, we get that the positive solutions of the problem above are symmetric w.r.t. the direction $ \nu $ by a new simple idea even if $ {{\Omega}} $ is not convex in the direction $ \nu $.

Urinary tumors primarily consist of kidney, urothelial, and prostate malignancies, which pose significant treatment challenges, particularly in advanced stages. Antibody-drug conjugates (ADCs) have emerged as a promising therapeutic approach, combining monoclonal antibody specificity with cytotoxic chemotherapeutic payloads. This review highlights recent advancements, opportunities, and challenges in ADC application for urinary tumors. We discuss the FDA-approved ADCs and other novel ADCs under investigation, emphasizing their potential to improve patient outcomes. Furthermore, we explore strategies to address challenges, such as toxicity management, predictive biomarker identification, and resistance mechanisms. Additionally, we examine the integration of ADCs with other treatment modalities, including immune checkpoint inhibitors, targeted therapies, and radiation therapy. By addressing these challenges and exploring innovative approaches, the development of ADCs may significantly enhance therapeutic options and outcomes for patients with advanced urinary tumor.

In this paper, we are interested in the existence of multiple nontrivial $ T $-periodic solutions of the nonlinear second ordinary differential equation $ \ddot{x}+V_x(t, x) = 0 $ in $ N(\geq 1) $ dimensions. Using homological linking and morse theory, we get at least two critical points of the functional corresponding to our problem. And, we also prove that two critical points are different by critical groups. Then, we obtain there are at least two nontrivial $ T $-periodic solutions of the problem.

Abstract Soil and water assessment tool (SWAT) model was used to calculate the runoff, nitrogen and phosphorus emissions in the Dagu River Basin from 2002 to 2012 and provided preliminary suggestions on environmental protection measures. Calibration on hydrological watershed parameters was obtained from data obtained from multiple representative stations. Cluster analysis was used to group all stations, and the parameters of different representative stations were applied to the entire geographical area to reflect the hydrological conditions of the basin. Additionally, the spatiotemporal changes and pollution source characteristics of nitrogen and phosphorus were analyzed. Anthropogenic sources—chemical fertilizer loss and livestock breeding—accounted for 49.9–29.6% of total nitrogen (TN) and 41.4% and 40.3% of total phosphorus (TP), respectively. Non-point sources accounted for 85.8% of the TN and 89.4% of the TP. Six landscape management practices were set up to evaluate the reduction effect on non-point source pollution loads, and comprehensive measures were proposed to reduce TN (TP) by ~ 70%. According to water quality model, the response relationship between river control and nutrient distribution in Jiaozhou Bay is calculated. Based on the findings, we propose an optimal control scheme for non-point source pollution in the Dagu River Basin and other similar basins.

Abstract With an increasing number of vehicles on the road, multiple‐vehicle platoons have become a new solution under communication constraints. However, the existing studies seldom consider the effect of the tail vehicle on the information transfer and platoon control over long distances, and thus the control performance under time‐varying delays is unacceptable. In this study, a hierarchical multi‐platoon control architecture considering the backbone platoon and sub‐platoons is proposed under non‐ideal communication conditions, where the backbone platoon layer communication topology is designed to achieve backbone platoon control and appropriate coordination among sub‐platoons. Distributed model predictive controllers (DMPCs) for backbone‐ and sub‐platoons that integrate delay compensation have been proposed. Buffers and delay compensators in the proposed DMPC are designed to reduce the interference caused by non‐ideal communications. The asymptotic stability is analyzed at the sub‐ and multi‐platoon levels. The results show that compared with traditional DMPC without a compensator, the proposed DMPC can eliminate the velocity lag and steady‐state spacing errors and maintain the maximum velocity and spacing errors within 0.11 m/s and 0.17 m, respectively, under certain operating conditions. Thus, the proposed method guarantees the stability of multiple platoons under both the constant and time‐varying delay conditions.

Abstract Existing research has revealed that multi‐vehicle coordinated decision making and control can achieve an improvement in both traffic efficiency and driving safety. In the multi‐lane scenarios, a typical coordination method is multi‐vehicle formation control. The existing formation control methods predefine the formation switching process and have not considered or explained the collision‐free behaviour of vehicles in detail. In this paper, a multi‐lane formation control strategy for connected and automated vehicles (CAVs) is proposed. The planning framework is bi‐level, which can switch the structure of multi‐vehicle formation in different scenarios smoothly and effectively. In the upper‐level, the relative coordinate system is built to plan the collision‐free relative paths for vehicles. In the lower‐level, multi‐stage trajectory planning and tracking are modelled as an optimal control problem with path constraints. The case study verifies the function of the formation control method in three lane‐number‐changing scenarios. Large‐scale simulations in the lane‐drop bottleneck scenario are conducted under different input traffic volumes, and the numerical results indicate that the proposed formation control method reduces congestion and improves both traffic efficiency and fuel economy at high traffic volumes.

In mixed and dynamic traffic environments, accurate long-term trajectory forecasting of surrounding vehicles is one of the indispensable preconditions for autonomous vehicles to accomplish reasonable behavioral decisions and guarantee driving safety. In this paper, we propose an integrated probabilistic architecture for long-term vehicle trajectory prediction, which consists of a driving inference model (DIM) and a trajectory prediction model (TPM). The DIM is designed and employed to accurately infer the potential driving intention based on a dynamic Bayesian network. The proposed DIM incorporates the basic traffic rules and multivariate vehicle motion information. To further improve the prediction accuracy and realize uncertainty estimation, we develop a Gaussian process-based TPM, considering both the short-term prediction results of the vehicle model and the driving motion characteristics. Afterward, the effectiveness of our novel approach is demonstrated by conducting experiments on a public naturalistic driving dataset under lane-changing scenarios. The superior performance on the task of long-term trajectory prediction is presented and verified by comparing with other advanced methods.

Over the past few decades, in situ transmission electron microscopy (TEM) has emerged as a powerful experimental technique for materials design and characterization. It offers unparalleled dynamic details of materials deformation under mechanical stimuli, providing fundamental insights into their deformation and failure mechanisms for various materials. In this review, we summarize recent advances on in situ TEM mechanical characterization techniques, including classical tension holders, nanoindentation holders, MEMS devices, thermal bimetallic-based techniques, and nanomanipulation techniques. The advantages and limitations of in situ TEM tests are also discussed. To provide a broader perspective, the article highlights promising opportunities for in situ TEM mechanical testing studies in characterization-processing-manufacturing based on nanomanipulation, ultrafast TEM, electron beam irradiation environmental conditions, data-driven machine learning, and integrated experimental and simulation characterization. This article aims to provide a comprehensive understanding of in situ TEM-based mechanical characterization techniques to promote the development of novel materials with improved mechanical properties for various applications.

Abstract Background This study aimed to examine the effect of Baduanjin exercise on COVID-19-related anxiety, psychological well-being, and the lower back pain of college students during the coronavirus pandemic in China. Setting The study was carried out in a temporary experimental center of four universities in Wenzhou city in Zhejiang Province, China. Population 387 participants who were college students were allocated to two groups: the Baduanjin exercise group(BEG, n = 195); and the Control group(CG,n = 192). Methods In this randomized controlled trial,387 participants who were college students were randomly allocated in a 1:1 ratio to 12-week Baduanjin exercise group (BEG, n = 195)and 12-week Control group(CG,n = 192).CAS(Coronavirus Anxiety Scale), PWBS(Psychological Well-being Scale),NMQ( Nordic Musculoskeletal Questionnaire), was used to assess COVID-19-related anxiety, psychological well-being, and lower back pain at second times ( before and after the intervention). The paired t-test and an independent t-test (with a 95% confidence interval) was used to compare the outcome variables of the two groups. Results Within-group comparison, there was no significant difference in the control group before and after the intervention. In contrast, the Baduanjin group had a significant improvement before and after the intervention. Between-group comparison, the Baduanjin group had a significant difference from the control group. The intervention effect on the Baduanjin exercise group was remarkably better than that of the control group (p

In this paper, we consider the solutions of the boundary blow-up problem $ \begin{eqnarray*} \begin{cases} \Delta u = \frac{1}{u^\gamma} +f(u) \ \ \ \ \mathrm{in}\ \ \ \Omega,\\ \ u>0 \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \mathrm{in}\ \ \ \Omega, \\ \ u = +\infty \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \mathrm{on} \ \ \partial\Omega, \end{cases} \end{eqnarray*} $ where $ \gamma > 0, \ \Omega $ is a bounded convex smooth domain and symmetric w.r.t. a direction. $ f $ is a locally Lipschitz continuous and non-decreasing function. We prove symmetry and monotonicity of solutions of the problem above by the moving planes method. A maximum principle in narrow domains plays an important role in proof of the main result.

BackgroundMobile applications (apps) are becoming increasingly prevalent as tools for improving maternal health behaviors. However, the recently updated content and quality of these apps remain unknown. This research investigated the fundamental characteristics, functional modules, and overall quality of maternal apps available in the United States and China to reveal critical nutrition and physical activity gaps.MethodsA systematic search was performed in Android and iOS app stores (China and the United States). Apps were eligible if they targeted pregnant or postpartum women, focused on nutrition or physical activity, and had interfaces in English or Chinese. The basic characteristics, functional modules, and overall quality of the apps were evaluated, and differences between apps available in China or the United States were determined using analysis of variance and chi-square tests. Pearson correlations were utilized to investigate links between objective quality and user rating.ResultsA total of 65 maternity-related nutrition and physical activity apps (34 from China and 31 from the United States) were eligible. Among them, 68% (21/31) of US apps and 56% (19/34) of Chinese apps did not provide supporting evidence for their content. A greater number of Chinese apps provided app-based general education modules, namely food nutrition knowledge (n = 0, 0% in the United States vs. n = 30, 88.2% in China). Meanwhile, a greater number of US apps provided exercise modules, namely pregnancy yoga (n = 21, 67.7% in the United States vs. n = 2, 5.9% in China). The overall app quality rating in the United States was lower than it was in China (mean: 3.5, SD: 0.6 in China vs. mean: 3.4, SD: 0.7 in the United States). There was no relationship between the overall app quality rating and the user rating in either country (rho = 0.11 in China and rho = –0.13 in the United States).ConclusionThe characteristics and functional modules of in-store apps for maternal nutrition and physical activity differed between the United States and China. Both countries’ apps, especially Chinese apps, lacked evidence-based information, and there was no correlation between app quality and user rating. The results therefore suggest that user ratings cannot be used as an objective indicator of app quality and that it is necessary to improve the empirical basis and credibility of apps in both countries.

Purpose – The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied. Design/methodology/approach – This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies. Findings – The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed. Originality/value – This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

The autonomous vehicles (AVs) need to share the driving environment with the human driving vehicles (HDVs) on expressway in the future. The non-humanlike lane changing (LC) behavior of AVs can mislead human drivers, which brings potential risks. Stronger humanlike ability requires a more complex algorithm. However, the requirement of the on-board vehicle computation resources limits the humanlike ability of LC algorithms. In this context, considering environmental risks, driver speed requirements and driver focus shifting process, this paper proposes a new type of LC algorithm based on artificial potential field (APF) aiming to improve the humanlike ability. The coupling relationship between the longitudinal and the lateral potential field forces is analyzed theoretically based on environmental risk APF. Based on the relationship, we proposed a conversion mechanism of the driver between the lateral and longitudinal potential field forces to mimic the driver’s speed requirement. Then a target lane selection strategy is designed to trade-off the driver’s speed requirement and safety between multiple lanes. Finally, to mimic the driver’s focus transfer process, the lateral forces of the ego vehicle are analyzed theoretically to further propose a moving virtual lane lines algorithm to build the lateral space varying potential field. The algorithm proposed in this paper is validated by comparing with other LC algorithms in the real traffic scenarios. The results indicate that the proposed algorithm has a better ability to mimic human driver’s LC decision-making and provides a smoother and safer humanlike trajectory.

Abstract The electrification of vehicle helps to improve its operation efficiency and safety. Due to fast development of network, sensors, as well as computing technology, it becomes realizable to have vehicles driving autonomously. To achieve autonomous driving, several steps, including environment perception, path-planning, and dynamic control, need to be done. However, vehicles equipped with on-board sensors still have limitations in acquiring necessary environmental data for optimal driving decisions. Intelligent and connected vehicles (ICV) cloud control system (CCS) has been introduced as a new concept as it is a potentially synthetic solution for high level automated driving to improve safety and optimize traffic flow in intelligent transportation. This paper systematically investigated the concept of cloud control system from cloud related applications on ICVs, and cloud control system architecture design, as well as its core technologies development. Based on the analysis, the challenges and suggestions on cloud control system development have been addressed.

Abstract Accidents between vehicles and pedestrians account for a large partition of severe traffic accidents. So, pedestrian motion prediction becomes a major concern for intelligent vehicles. However, current researches often neglect pedestrian behaviour and/or intention in motion prediction. Meanwhile, related works are scattered and divided into many small fields. No integrated system is proposed to connect the task of perception and decision. To solve these problems, a pedestrian motion prediction model is proposed in this paper. The proposed method predicts pedestrian motion based on the combination of pedestrian crossing behaviour and intention. Pedestrian behaviour is recognized using the Bayesian posterior model, and pedestrian intention is recognized by the dynamic Bayesian network. A modified particle filter and a behavioural motion model are used to integrate the behaviour and intention into motion prediction. The effectiveness of the proposed method is verified in our provided BPI dataset with eight typical scenarios defined by road type, vehicle velocity etc. The results show that this method can give an accurate distribution of pedestrians’ future trajectories.

Abstract This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

The rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challenges for existing modes of transportation. Currently, driving assistance systems of Level 3 and below have been widely produced, and several applications of Level 4 systems to specific situations have also been gradually developed. By improving the automation level and vehicle intelligence, these systems can be further advanced towards fully autonomous driving. However, general development concepts for Level 5 AVs remain unclear, and the existing methods employed in the development processes of Levels 0–4 have been mainly based on task-driven function development related to specific scenarios. Therefore, it is difficult to identify the problems encountered by high-level AVs. The essential logical and physical mechanisms of vehicles have hindered further progression towards Level 5 systems. By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essence of driving, we put forward a coordinated and balanced framework based on the brain–cerebellum–organ concept through reasoning and deduction. Based on a mixed mode relying on the crow inference and parrot imitation approach, we explore the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning, self-adaptation, and self-transcendence for AVs. From a systematic, unified, and balanced point of view and based on least action principles and unified safety field concepts, we aim to provide a novel research concept and develop an effective approach for the research and development of high-level AVs, specifically at Level 5.

We view the development of industries with various market competition levels as a dynamic process and investigate the game between a new entrant and the original market with variable market competition degrees under the premise of considering the entry and exit of companies in the industry. Based on this, we explore the prerequisites for the new firm to enter the initial market and construct a recursive formula for the optimal output of individual firms entering the market one at a time, as well as the conditions for the new firm to enter the market in the three scenarios of the original market being mixed strategy, low-carbon type, and traditional type, respectively, and the optimal decision-making behavior once entering the market. We create diversified carbon tax rates for various cost bands of low-carbon production patterns in order to modify the original traditional market and allow the new enterprise to enter the market using a low-carbon production strategy. We anticipate that our study will serve as a theoretical guide for accomplishing a low-carbon shift in production patterns.

A high load capacity non-pneumatic tire (HC tire) was designed and manufactured to solve the problems of air leakage, puncture, blowout, shoulder void, and delamination, which occur in traditional high load capacity tires, as well as significantly increase the unit load of tires. Experiments and numerical simulations were conducted to investigate the static stiffness properties of the HC tire. Additionally, the manufacturing process of the tire was highlighted. The tire mainly comprised polyurethane and silicon manganese steel, and a ‘π’-shaped support substructure was adopted. The tread structure was made up of a built-in spiral steel ring and a non-steel ring. The uniaxial tensile mechanical properties of the used metal and elastomer materials were tested, and the linear elastic constitutive model and Marlow constitutive model, respectively, were used to describe their mechanical characteristics. The stiffness properties of the HC tire, including torsional, longitudinal, vertical, and lateral stiffnesses, were evaluated using a tire comprehensive stiffness tester. Nonlinear finite element models of the HC tire were established, and their accuracies were verified through vertical stiffness tests. The stiffness properties of the HC tire in other directions were simulated as well. An in-depth comparative analysis of the simulation and experimental data was performed. The results demonstrated that the unit load of the unreinforced HC tire was 2.972 times and 1.615 times higher than that of the solid tire and pneumatic tire, respectively. The spiral steel ring embedded in the tread increased the vertical and longitudinal stiffness but reduced the torsional stiffness of the HC tire, thus reversing the variation trend of the lateral stiffness at the 0° and 5° test points. The findings can serve as a reference for theoretical research on, and the structural optimization of, non-pneumatic tires with a high load capacity.

Abstract With an aim to improve the performances of intelligent‐connected electric vehicle platoon with communication delay, we present a distributed adaptive robust H∞ control scheme in this paper. First, the longitudinal non‐linear dynamic model of vehicle i is established, and in order to reduce the difficulty of analysing such a non‐linear system, a simplified uncertain dynamic model of vehicle i is obtained via a feedback linearisation method. Second, a novel distributed state‐feedback robust platoon controller is designed by using the relative information between neighbouring electric vehicles. Third, we derive the sufficient condition that the presented distributed robust platoon controller exists under the influence of communication delay. This condition is given in the form of a linear matrix inequality, which is low dimensional and whose dimension is independent of the length of the intelligent electric vehicle platoon. Furthermore, the closed‐loop platoon system controlled by the presented controller is proved stable subject to communication delay by using the Lyapunov stability theory. In addition, an adaptive control term is added to the robust platoon controller. We present the sufficient condition that such a modified controller exists and prove the platoon string stability. Finally, the effectiveness of the presented adaptive robust platoon control scheme is verified by conducting numerical simulation tests.

In an increasingly aged global population, achieving healthy life expectancy through natural and safe drug interventions is highly desirable. Here we show that total ginsenosides (TGGR), the main active components in the traditional Chinese medicine, ginseng, promote longevity across species. In Drosophila, an intriguing effect of TGGR on lifespan was the relatively narrow treatment window to elicit long-term benefits. TGGR administration during early adulthood, and especially during midlife, was sufficient to extend lifespan in both sexes. TGGR did not increase lifespan by reducing food intake or reproductive capacity; rather, TGGR increased the fertility of male Drosophila. TGGR augmented healthspan readouts associated with youth and with healthy aging, such as motility, intestinal barrier integrity, and biorhythm homeostasis. TGGR treatment also improved some types of stress resistance in both sexes, including increased tolerance to starvation and oxidation, and shifting “aged” gene expression patterns toward “healthy” patterns seen in the young. Gene expression, pharmacological and genetic epistatic analyses demonstrated that TGGR effects require normal expression of genes involved in insulin, TOR and MAPK signaling. The positive effects of TGGR on both healthspan and lifespan, coupled with its mechanism of action via evolutionarily conserved signaling pathways, demonstrate it to be a promising anti-aging drug.

Globally, many bays have been subjected to water quality (WQ) deterioration, due to excessive discharge of terrigenous total nitrogen (TN). In China, several projects have been implemented to control TN loads; however, due to the lack of linkage between a bay’s polluted segments and its basin’s jurisdictions, the WQ improvement efficiency usually is lower than expected. In this study, we focus on the basin of Laizhou Bay (LZB), China. A series of differentiated TN reduction indicators for 13 cities in the basin of LZB were developed on the base of the total maximum allocated loads (TMALs), which meets the WQ standard of LZB. Four land-sea synchronous investigations were conducted to discern seasonally polluted segments of LZB in 2017. The seriously nitrogen-polluted segments located at southwest and southeast of LZB and the largest area accounted for about 70% of LZB. Due to the heterogeneity of the terrigenous TN load and TMALs of the 13 jurisdictions in the basin, the responsibility apportionment rate for the nitrogen-polluted segments showed a spatial disparity, the city of Weifang with the highest value of 32%, followed by Zibo (28%), Ji’nan (20%), and the other 10 cities (19%). Accordingly, the TN load reduction rate among the 13 jurisdictions varied from 1% to 99%, with an average of 62%. The average values for reduction rate of TN generation, increase rate of TN removal by wastewater treatment, increase rate of TN retention in soil matrix, and TN attenuation in riverway were 44% (21%-69%), 53% (0–88%), 31% (0–61%), and 63% (15–84%), respectively. The three-dimensional seawater quality model simulation results showed that the “precise reduction indicator scheme” was six years earlier than the “equal percent reduction indicator scheme” in each jurisdiction to achieve the WQ standard. Seven cities need to cut emissions more than the current rate. The precise indicators throughout the land-based pollutant entire migration pathway will help implement the TN reduction plan more efficiently.

Abstract In this paper, a unified multi‐vehicle formation control framework for intelligent and connected vehicles (ICVs) that can apply to multiple traffic scenarios is proposed. In the one‐dimensional scenario, different formation geometries are analysed, and the interlaced structure is mathematically modellised to improve driving safety while making full use of the lane capacity. The assignment problem for vehicles, and target positions is solved using Hungarian algorithm to improve the flexibility of the method in multiple scenarios. In the two‐dimensional scenario, an improved virtual platoon method is proposed to transfer the complex two‐dimensional passing problem to the one‐dimensional formation control problem based on the idea of rotation projection. Besides, the vehicle regrouping method is proposed to connect the two scenarios. Simulation results prove that the proposed multi‐vehicle formation control framework can apply to multiple typical scenarios, and have better performance than existing methods.

The characteristics exhibited by livestock product price fluctuation should be characterized, and the trend of price fluctuation should be forecasted in times, which are critical to developing the animal husbandry market. The current mainstream forecasting methods have limited ability to deal with multi-source, multi-modal and heterogeneous input data. Moreover, the current mainstream forecasting methods ignored the impact of static non-time series such as variety, growth cycle, latitude and longitude on the price fluctuation of livestock products, so it can not accurately predict the livestock product price and fluctuation trend. To introduced the influence of static information on price fluctuation into the forecasting process while improved the ability to process heterogeneous data. A novel price forecasting method was proposed by complying with GRU neural network and the principle of energy decomposition. First, to acquire the price fluctuation at different frequencies, this study proposed a variation mode decomposition method based on actual signal energy (AE-VMD) and a multi-scale adaptive Lempel-Ziv complexity calculation method (MA-LZ). Second, to preserve the information of multimodal data, this study developed a heterogeneous GRU neural network (AH-GRU) in accordance with attention mechanism. Lastly, the effect of static information on price fluctuations was introduced in the forecasting, and the final forecasting result was outputted via the dense layer. The experimental results showed that the RMSE of the forecasting method for beef, mutton and pork prices were 0.726, 0.535 and 0.738, the MAE were 0.607, 0.412 and 0.621, and the R2 were 0.954, 0.995 and 0.991, respectively. The trend forecasting statistics $D_{stat} $ were 87.097, 90.909 and 90.566, the correct upward trend (CP) were 68.805, 41.818 and 42.875, and the correct downward trend (CD) were 63.326, 59.091 and 47.619, respectively. The proposed method outperformed the mainstream livestock product price forecasting method in forecasting accuracy, trend forecasting and method convergence.

The platooning technique has shown potential to bring pronounced benefits to road traffic, including higher safety, better fuel economy, and greater comfort. However, an overlong platoon may jeopardize the overall traffic efficiency because of the unintentional obstruction to other traffic participants. Hence, this paper proposes an advance adjustment strategy for the truck platoon in the off-ramp scenarios to reduce the impact on the predictable lane changes of other vehicles. We derive the appropriate platoon length with an analytic method and verify the effectiveness of conclusions via simulations. Both theoretical calculation and simulation experiment results prove that controlling the platoon length within a reasonable range can significantly improve traffic efficiency near a ramp. This study highlights the importance of truck platoon length management on traffic dynamics and provides a valuable reference for future researchers.

With the rapid development of distributed transactional databases in recent years, there is an urgent need for fair performance evaluation and comparison. Though there are various open-source benchmarks built for databases, it is lack of a comprehensive study about the applicability for distributed transactional databases. This paper presents a review of the state-of-art benchmarks with respect to distributed transactional databases. We first summarize the representative architectures of distributed transactional databases and then provide an overview about the chock points in distributed transactional databases. Then, we classify the classic transactional benchmarks based on their characteristics and design purposes. Finally, we review these benchmarks from schema and data definition, workload generation, and evaluation and metrics to check whether they are still applicable to distributed transactional databases with respect to the chock points. This paper exposes a potential research direction to motivate future benchmark designs in the area of distributed transactional databases.

To accommodate the exponentially increasing computation demands of vehicle-based applications, vehicular edge computing (VEC) system was introduced. This paper considers a three-layer VEC architecture and proposes an online offloading scheduling and resource allocation (OOSRA) algorithm to improve the system performance. Specifically, this study designs a game-theoretic online algorithm to solve the problem of computation task offloading scheduling, and employs an online bin-packing algorithm to compute the resource allocation modified from the First Fit algorithm, which can be adapted to various traffic flow and service attributes. Extensive simulations are conducted, and a numerical analysis of simulation results verifies the effectiveness of the OOSRA-VEC system. The algorithms proposed in this paper are online, adaptive, and distributed, which can provide useful references for future development in VEC system protocols.

Abstract In this paper, we investigate the unique continuation properties for multi-dimensional heat equations with inverse square potential in a bounded convex domain Ω of Rd $\mathbb{R}^{d}$. We establish observation estimates for solutions of equations. Our result shows that the value of the solutions can be determined uniquely by their value on an open subset ω of Ω at any given positive time L.

Understanding the thermal transport in nanostructures has important applications in fields such as thermoelectric energy conversion, novel computing and heat dissipation. Using non-homogeneous equilibrium molecular dynamic simulations, we studied the thermal transport in pristine and resonant Si membranes bounded with {110} facets. The break of symmetry by surfaces led to the anisotropic thermal transport with the thermal conductivity along the [110]-direction to be 1.78 times larger than that along the [100]-direction in the pristine structure. In the pristine membranes, the mean free path of phonons along both the [100]- and [110]-directions could reach up to ∼100 µm. Such modes with ultra-long MFP could be effectively hindered by surface resonant pillars. As a result, the thermal conductivity was significantly reduced in resonant structures, with 87.0% and 80.8% reductions along the [110]- and [100]-directions, respectively. The thermal transport anisotropy was also reduced, with the ratio κ110/κ100 decreasing to 1.23. For both the pristine and resonant membranes, the thermal transport was mainly conducted by the in-plane modes. The current work could provide further insights in understanding the thermal transport in thin membranes and resonant structures.

A strong sociocultural context could affect an individual’s aesthetic standards. In order to achieve a socially recognized ideal appearance, obligatory exercisers might increase dieting behavior when exercise actions are disturbed, thereby placing the individual at risk of eating disorders. The current study mainly examined the relationship between obligatory exercise and eating attitudes during the COVID-19 pandemic, and considered the mediating role of externalized sociocultural attitudes towards appearance between the two. A total of 342 participants (175 females, 167 males) from various regions of China were invited to fill out the questionnaires including the Obligatory Exercise Questionnaire, the Sociocultural Attitudes Toward Appearance Questionnaire-3, and the Eating Attitudes Test. In total, 51.5% of the participants presented symptoms of an obligatory exercise behavior. Among them, males, young adults, and the participants with lower BMI had higher OEQ scores, whereas females and young adults had higher EAT-26 scores. Meanwhile, 9.4% of the participants might have had an eating disorder. The OEQ score was positively correlated with the EAT-26 total score as well as SATAQ-3 ‘Pressures’ and ‘Information’ subscales. In addition, the EAT-26 total score was positively correlated with the SATAQ-3 ‘Pressures’ and ‘Information’ subscales. Externalized sociocultural attitudes towards appearance served as a mediator between obligatory exercise behavior and eating attitudes, and the mediation effect accounted for 56.82% of the total effect. Obligatory exercise behavior may have an indirect effect on eating attitudes through sociocultural attitudes towards appearance. Given the sociocultural information and pressures, in order to maintain or pursue an ideal appearance, many people tend to keep a pathological diet. Thus, forming a positive and healthy social aesthetic orientation is beneficial in helping obligatory exercisers to develop reasonable eating habits.

For a driving motor stator of EDU (Electric Drive Unit) intelligent electric transmission of a domestic plug-in hybrid electric vehicle, modal tests are performed on the motor stator with or without motor shell. Either the hammering method or the frequency sweeping method is used in the test. The modal frequencies, modal shapes, and damping ratios of the first five orders that meet the requirements of the modal confidence criterion are obtained. The influence of the motor shell on the low-order radial modal of the motor stator is discussed. The results show that similar results are obtained in the modal parameter estimation respectively using the hammering method and the frequency sweeping method. They can both be used for low-order radial modal test of the motor stator. The motor stator without shell exhibits a linear structure in the frequency domain. Each modal frequency obtained by the frequency sweeping method is slightly higher than that obtained by the hammering method.

Abstract In this paper, we established a quantitative unique continuation results for a coupled heat equations, with the homogeneous Dirichlet boundary condition, on a bounded convex domain Ω of R d $\mathbb{R}^{d}$ with smooth boundary ∂Ω. Our result shows that the value of the solutions can be determined uniquely by its value on an arbitrary open subset ω of Ω at any given positive time T.

Compared with automatic collision avoidance systems, collision avoidance assistance systems have attracted more research interest because they help avoid collisions in near-accident situations. However, ensuring the robustness and reliability of collision avoidance assistances is difficult because of problems in reliable environment recognition, accurate collision avoidance decision making, and driver acceptance. This article reviews and analyzes three essential technologies for collision avoidance assistance systems in intelligent environment-friendly vehicles. The architecture of the human-in-loop system is summarized, and available environment recognition methods used in collision avoidance assistances are compared. Moreover, the characteristics of path planning and collision avoidance decision making applied in emergency collision avoidance assistance systems are reviewed, and the advantages of applying haptic share control and yaw moment active intervention during path tracking are analyzed. The emergency collision avoidance assistance systems based on driver behavior models and HSC were found to be the most suitable for high-speed emergency conditions. Such systems are not only highly robust but also more likely to be accepted by drivers.

This paper proposed an RFID-based vehicle positioning approach to facilitate connected vehicles applications. When a vehicle passes over an RFID tag, the vehicle position is given by the accurate position stored in the tag. At locations without RFID coverage, the vehicle position is estimated from the most recent tag location using a kinematics integration algorithm till updates from the next tag. The accuracy of RFID positioning is verified empirically in two independent ways with one using radar and the other a photoelectric switch. The former is designed to verify whether the dynamic position obtained from RFID tags matches the position measured by radar that is regarded as accurate. The latter aims to verify whether the position estimated from the kinematics integration matches the position obtained from RFID tags. Both means supports the accuracy of RFID-based positioning. As a supplement to GPS which suffers from issues such as inaccuracy and loss of signal, RFID positioning is promising in facilitating connected vehicles applications. Two conceptual applications are provided here with one in vehicle operational control and the other in Level IV intersection control.

Tracked vehicles have been widely used in construction, agriculture, and the military. Major problems facing the industry, however, are high emissions and fuel consumption. Hybrid electric tracked vehicles have thus become increasingly popular because of their improved fuel economy and reduced emissions. While the series hybrid system has drawn the most attention and has been applied in most cases, the low efficiency caused by energy conversion losses and large propulsion motors has limited its development. A novel multi-mode powertrain with two output shafts controlling each side of the track independently is first proposed. The powertrain is a three-planetary-gear power-split system with one engine, three motors, and an ultracapacitor pack. Compared with the existing technologies, the proposed powertrain can realize skid steering without an extra steering mechanism, and significantly improve the overall efficiency. To demonstrate the advantages of the novel powertrain, a topology-control-size integrated optimization problem is solved based on drivability, fuel economy, and cost. Final simulation results show that the optimized design with downsized components can produce about a 30% improvement in drivability and a 15% improvement in fuel economy compared with the commonly used series hybrid benchmark. Moreover, the optimized design is verified to be much more economical taking cumulative cost into account, which is very attractive for potential industrial applications in the future.