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Abstract Artificial intelligence empowers the rapid development of autonomous intelligent systems (AISs), but it still struggles to cope with open, complex, dynamic, and uncertain environments, limiting its large-scale industrial application. Reliable human feedback provides a mechanism for aligning machine behavior with human values and holds promise as a new paradigm for the evolution and enhancement of machine intelligence. This paper analyzes the engineering insights from ChatGPT and elaborates on the evolution from traditional feedback to human feedback. Then, a unified framework for self-evolving intelligent driving (ID) based on human feedback is proposed. Finally, an application in the congested ramp scenario illustrates the effectiveness of the proposed framework.

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment. This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data- and model-driven method. First, a data-driven decision-making module based on deep reinforcement learning (DRL) is developed to pursue a rational driving performance as much as possible. Then, model predictive control (MPC) is employed to execute both longitudinal and lateral motion planning tasks. Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements. Finally, two principles of safety and rationality for the self-evolution of autonomous driving are proposed. A motion envelope is established and embedded into a rational exploration and exploitation scheme, which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent. Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted, and the results show that the proposed online-evolution framework is able to generate safer, more rational, and more efficient driving action in a real-world environment.

Abstract Plastic crystals as barocaloric materials exhibit the large entropy change rivalling freon, however, the limited pressure-sensitivity and large hysteresis of phase transition hinder the colossal barocaloric effect accomplished reversibly at low pressure. Here we report reversible colossal barocaloric effect at low pressure in two-dimensional van-der-Waals alkylammonium halides. Via introducing long carbon chains in ammonium halide plastic crystals, two-dimensional structure forms in (CH3–(CH2)n-1)2NH2X (X: halogen element) with weak interlayer van-der-Waals force, which dictates interlayer expansion as large as 13% and consequently volume change as much as 12% during phase transition. Such anisotropic expansion provides sufficient space for carbon chains to undergo dramatic conformation disordering, which induces colossal entropy change with large pressure-sensitivity and small hysteresis. The record reversible colossal barocaloric effect with entropy change ΔSr ~ 400 J kg−1 K−1 at 0.08 GPa and adiabatic temperature change ΔTr ~ 11 K at 0.1 GPa highlights the design of novel barocaloric materials by engineering the dimensionality of plastic crystals.

Abstract Background Glycemic gap, as a novel index of acute glycemic excursion, is associated with poor prognosis of different diseases. This study aimed to explore the association of the glycemic gap with long‐term stroke recurrence in patients with ischemic stroke. Methods This study included patients with ischemic stroke from the Nanjing Stroke Registry Program. The glycemic gap was calculated by subtracting the estimated average blood glucose from the blood glucose at admission. Multivariable Cox proportional hazards regression analysis was performed to explore the association between the glycemic gap and the risk of stroke recurrence. The Bayesian hierarchical logistic regression model was used to estimate the effects of the glycemic gap on stroke recurrence stratified by diabetes mellitus and atrial fibrillation. Results Among 2734 enrolled patients, 381 (13.9%) patients experienced stroke recurrence during a median follow‐up of 3.02 years. In multivariate analysis, glycemic gap (high group vs. median group) was associated with significantly increased risk for stroke recurrence (adjusted hazard ratio, 1.488; 95% confidence interval, 1.140–1.942; p = .003) and had varying effects on stroke recurrence depending on atrial fibrillation. The restricted cubic spline curve showed a U‐shaped relationship between the glycemic gap and stroke recurrence (p = .046 for nonlinearity). Conclusion Our study found that the glycemic gap was significantly associated with stroke recurrence in patients with ischemic stroke. The glycemic gap was consistently associated with stroke recurrence across subgroups and had varying effects depending on atrial fibrillation.

ObjectivesThe present study analyzed the impact of the COVID-19 pandemic on the prevalence and incidence of new leprosy cases, as well as the diversity, distribution, and temporal transmission of Mycobacterium leprae strains at the county level in leprae-endemic provinces in Southwest China.MethodsA total of 219 new leprosy cases during two periods, 2018–2019 and 2020–2021, were compared. We genetically characterized 83 clinical isolates of M. leprae in Guizhou using variable number tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). The obtained genetic profiles and cluster consequences of M. leprae were compared between the two periods.ResultsThere was an 18.97% decrease in the number of counties and districts reporting cases. Considering the initial months (January–March) of virus emergence, the number of new cases in 2021 increased by 167% compared to 2020. The number of patients with a delay of >12 months before COVID-19 (63.56%) was significantly higher than that during COVID-19 (48.51%). Eighty-one clinical isolates (97.60%) were positive for all 17 VNTR types, whereas two (2.40%) clinical isolates were positive for 16 VNTR types. The (GTA)9, (TA)18, (TTC)21 and (TA)10 loci showed higher polymorphism than the other loci. The VNTR profile of these clinical isolates generated five clusters, among which the counties where the patients were located were adjacent or relatively close to each other. SNP typing revealed that all clinical isolates possessed the single SNP3K.ConclusionCOVID-19 may have a negative/imbalanced impact on the prevention and control measures of leprosy, which could be a considerable fact for official health departments. Isolates formed clusters among counties in Guizhou, indicating that the transmission chain remained during the epidemic and was less influenced by COVID-19 preventative policies.

Abstract Model predictive control is widely used in the design of autonomous driving algorithms. However, its parameters are sensitive to dynamically varying driving conditions, making it difficult to be implemented into practice. As a result, this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller. Specifically, the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller. In this method, a risk threshold model is proposed to classify the risk level of the scenes based on the scene features, and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios. The proposed algorithm is compared to a pure model predictive controller in car-following case. According to the results, the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations, showing a good scenario adaptability with safety guaranteed.

In this study, the induction plasma spheroidization (IPS) technique was adopted to improve the microstructure and properties of the traditional agglomerated ZrO2-7wt%Y2O3 (YSZ) powders used in thermal barrier coating (TBC) applications. Compared with agglomerated YSZ powders, IPS-treated powder has a more desirable microstructure, and the overall performance of the spray powders for TBC preparation is significantly improved. Specifically, IPS-treated powder has a dense, solid, defect-free, and chemically uniform microstructure, and its apparent density, flowability, and powder strength are significantly improved, which is believed to substantially enhance the coating performance when prepared with this IPS-treated powder.

Context Momordica charantia L. (Cucurbitaceae), known as bitter melon, is an edible fruit cultivated in the tropics. In this study, an active compound, 5β,19-epoxycucurbita-6,23(E)-diene-3β,19(R),25-triol (ECDT), isolated from M. charantia was investigated in regard to its cytotoxic effect on human hepatocellular carcinoma (HCC) cells.Objective To examine the mechanisms of ECDT-induced apoptosis in HCC cells.Materials and methods The inhibitive activity of ECDT on HA22T HCC cells was examined by MTT assay, colony formation assay, wound healing assay, TUNEL/DAPI staining, annexin V-fluorescein isothiocyanate/propidium iodide (PI) staining and JC-1 dye. HA22T cells were treated with ECDT (5, 10, 15, 20 and 25 μM) for 24 h, and the molecular mechanism of cells apoptosis was examined by Western blot. Cells treated with vehicle DMSO were used as the negative control.Results ECDT inhibited the cell proliferation of HA22T cells in a dose-dependent manner. Flow cytometry showed that ECDT treatment at 10–20 μM increased early apoptosis by 10–14% and late apoptosis by 2–5%. Western blot revealed that ECDT treatment activated the mitochondrial-dependent apoptotic pathway, and ECDT-induced apoptosis was mediated by the caspase signalling pathway and activation of JNK and p38MAPK. Pre-treatment of cells with MAPK inhibitors (SB203580 or SP600125) reversed the ECDT-induced cell death, which further supported the involvement of the p38MAPK and JNK pathways.Discussion and conclusions Our results indicated that ECDT can induce apoptosis through the p38MAPK and JNK pathways in HA22T cells. The findings suggested that ECDT has a valuable anticancer property with the potential to be developed as a new chemotherapeutic agent for the treatment of HCC.

The instability of slopes and ground subsidence caused by the conversion from open-pit to underground mining are important aspects of mining disaster research. This study focuses on the instability of slopes and ground subsidence during the conversion from open-pit to underground mining in the Beiyi mining area of the Shilu iron ore mine. Using numerical simulation and analysis, this study establishes a mechanical analysis model to assess the rock stability and movement of rockfall. The research findings indicate that there are significant stress concentration phenomena in the surrounding and floor areas of the goaf during the mining process. The collapse zone mainly develops in the western area before and after a certain level of mining and then shifts to the eastern part of Beiyi area. Surface subsidence expands after mining at a certain level, resulting in a large-scale disturbance area. Furthermore, the eastern slope experiences extensive landslides. This study suggests the continued monitoring of landslides and slope stability in specific areas of the mine. The research results can help us to understand the stability of the open-pit to underground rock mass in Hainan, judge the development trend of the surface subsidence range, and provide a reference for the stability evaluation of the rock mass mined by the open-pit-to-underground caving method.

AbstractThe carbon market has gained widespread consensus as an important means to address the climate change. The legal system of the carbon market is the cornerstone of the stable operation, which currently relies on a top-down model promoted by the government. A question worth considering is, as the carbon trading is based on the market mechanism that depends on the autonomy of will, what kind of role does private law play in the legal system of the carbon market? This study sorts out various risks of the carbon market and point out that they are mainly originated from information asymmetry and the principal-agent problem. These two reasons of market risks indicate the imbalance of rights and obligations among market participants. Precisely, private law is a significant way to achieve equal and fair transactions between private entities. This paper conducts empirical analysis on China’s carbon market and finds that the carbon brokerage is based on the principal-agent relationship, the carbon asset management is belonging to the trust relationship, and the information consulting is according to the contract of mandate. The conclusion shows that information asymmetry and the principal-agent problem can be prevented and mitigated by the rights of intervention and option, fiduciary duty, and fault liability. Private law can rebalance rights and obligations between private entities of the carbon market. In addition, there are also limitations of private law, so the recommendation is to make a diversified mechanism of the legal governance to achieve a robust development of the carbon market.