Motion primitives play an important role in motion planning for autonomous vehicles, as they effectively address the sampling challenges inherent in nonholonomic motion planning. Employing motion primitives (MPs) is a widely accepted approach in nonholonomic motion planning based on sampling. This study specifically addresses the problem of learning from human-driving data to create human-like trajectories from predefined start-to-end states, which then serve as MP within the sampling-based nonholonomic motion planning framework. In this paper, we propose a deep learning-based method for generating MP that capture human-driving trajectory data features. By processing human-driving trajectory data, we create a Motion Primitive dataset that uniformly covers typical urban driving scenarios. Based on this dataset, a vehicle model long short-term memory neural network model is constructed to learn the features of the human-driving trajectory data. Finally, a framework for the generation of MP for practical applications is given based on this neural network. Our experiments, which focus on the dataset, the MMP generation network, and the generation process, demonstrate that our method significantly improves the training efficacy of the MP generation network. Additionally, the MP generated by our method exhibit higher accuracy compared to traditional methods.

This study examined the sour grapes/sweet lemons rationalization through 2 conditions: ‘attainable’ (sweet lemons) and ‘unattainable’ (sour grapes), reflecting China’s 2019-nCoV vaccination strategy. The aim was to find ways to change people’s beliefs and preferences regarding vaccines by easing their safety concerns and encouraging more willingness to get vaccinated. An online survey was conducted from January 22 to 27, 2021, with 3,123 residents across 30 provinces and municipalities in the Chinese mainland. The direction of belief and preference changed in line with the sour grapes/sweet lemons rationalization. Using hypothetical and real contrasts, we compared those for whom the vaccine was relatively unattainable (‘sour grapes’ condition) with those who could get the vaccine easily (‘sweet lemons’). Whether the vaccine was attainable was determined in the early stage of the vaccine roll-out by membership in a select group of workers that was supposed to be vaccinated to the greatest extent possible, or, by being in the second stage when the vaccine was available to all. The attainable conditions demonstrated higher evaluation in vaccine safety, higher willingness to be vaccinated, and lower willingness to wait and see. Hence, we propose that the manipulation of vaccine attainability, which formed the basis of the application of sour grapes/sweet lemons rationalization, can be utilized as a means to manipulate the choice architecture to nudge individuals to ease vaccine safety concerns, reducing wait-and-see tendencies, and enhancing vaccination willingness. This approach can expedite universal vaccination and its associated benefits in future scenarios resembling the 2019-nCoV vaccine rollout.

The autonomous navigation and obstacle avoidance capabilities of autonomous underwater vehicles (AUVs) are essential for ensuring their safe navigation and long-term, efficient operation. However, the complexity of the marine environment poses significant challenges to safe and effective obstacle avoidance. To address this issue, this study proposes an AUV obstacle avoidance control algorithm based on offline reinforcement learning. This method adopts the Conservative Q-learning (CQL) algorithm, which is based on the Soft Actor-Critic (SAC) framework. It learns from obtained historical obstacle avoidance data and ultimately achieves a favorable obstacle avoidance control strategy. In this method, PID and SAC control algorithms are utilized to generate expert obstacle avoidance data to construct a diversified offline database. Additionally, based on the line-of-sight (LOS) guidance method and artificial potential field (APF) method, information regarding the distance and orientation of targets and obstacles is incorporated into the state space, and heading and obstacle avoidance reward terms are integrated into the reward function design. The algorithm successfully guides the AUV in autonomous navigation and dynamic obstacle avoidance in three-dimensional space. Furthermore, the algorithm exhibits a certain degree of anti-interference capability against uncertain disturbances and ocean currents, enhancing the safety and robustness of the AUV system. Simulation results fully demonstrate the feasibility and effectiveness of the intelligent obstacle avoidance method based on offline reinforcement learning. This study highlights the profound significance of offline reinforcement learning in enabling robust and reliable control systems for AUVs, paving the way for enhanced operational capabilities in challenging marine environments.

Autonomous underwater vehicles (AUVs) have played a pivotal role in advancing ocean exploration and exploitation. However, traditional AUVs face limitations when executing missions at minimal or near-zero forward velocities due to the ineffectiveness of their control surfaces, considerably constraining their potential applications. To address this challenge, this paper introduces an innovative vectored thruster system based on a 3RRUR parallel manipulator tailored for micro-sized AUVs. The incorporation of a vectored thruster enhances the performance of micro-sized AUVs when operating at minimal and low forward speeds. A comprehensive exploration of the kinematics of the thrust-vectoring mechanism has been undertaken through theoretical analysis and experimental validation. The findings from theoretical analysis and experimental confirmation unequivocally affirm the feasibility of the devised thrust-vectoring mechanism. The precise control of the vector device is studied using Physics-informed Neural Network and Model Predictive Control (PINN-MPC). Through the adoption of this pioneering thrust-vectoring mechanism rooted in the 3RRUR parallel manipulator, AUVs can efficiently and effectively generate the requisite motion for thrust-vectoring propulsion, overcoming the limitations of traditional AUVs and expanding their potential applications across various domains.

The purpose of this experiment was to evaluate the contribution of epiphytic microbiota on alfalfa (AL), oat (OT), and red clover (RC) to ensiling characteristics and bacterial community diversity of oat. With the irradiation of γ-ray, sterile OT (~233 g/kg dry matter (DM)) was inoculated by sterile water (STOT), epiphytic microbiota from OT (OTOT), AL (OTAL) and RC (OTRC), respectively. Triplicate silage-bags for each treatment were sampled after different days (1, 3, 7, 15, 30 and 60) of fermentation, respectively. Similar chemical compositions were found between fresh oat and STOT. Lower (P < 0.05) contents of ammonia nitrogen (NH3-N) and higher (P < 0.05) accumulation of lactic acid were found in OTAL compared with OTRC and OTOT on day 3. The greatest (P < 0.05) NH3-N, acetic acid concentrations and pH and the lowest (P < 0.05) concentration of lactic acid were found in OTRC on day 60. After 3 days of ensiling, Lactobacillus accounted for a big proportion in OTAL and OTOT, and Hafnia-Obesumbacterium was predominant in OTRC. The bacterial communities in OTAL and OTOT had lower (P < 0.05) abundances of ‘Genetic Information Processing’ than OTRC after 3 days. Overall, the composition, diversity, and activity of epiphytic microbiota can notably influence the ensiling characteristics of forage oat. The lactic acid bacteria (hetero-fermentative type) and Enterobacteriaceae species played an important role in producing ethanol contents during the ensiling of forage oat.

The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Psyllidae), is the key vector insect transmitting the Candidatus Liberibacter asiaticus (CLas) bacterium that causes the devastating citrus greening disease (Huanglongbing, HLB) worldwide. The D. citri salivary glands (SG) exhibit an important barrier against the transmission of HLB pathogen. However, knowledge on the molecular mechanism of SG defence against CLas infection is still limited. In the present study, we compared the SG transcriptomic response of CLas-free and CLas-infected D. citri using an illumine paired-end RNA sequencing. In total of 861 differentially expressed genes (DEGs) in the SG upon CLas infection, including 202 upregulated DEGs and 659 downregulated DEGs were identified. Functional annotation analysis showed that most of the DEGs were associated with cellular processes, metabolic processes, and the immune response. Gene ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses revealed that these DEGs were enriched in pathways involving carbohydrate metabolism, amino acid metabolism, the immune system, the digestive system, the lysosome, and endocytosis. A total of 16 DEGs were randomly selected to further validate the accuracy of RNA-Seq dataset by reverse-transcription quantitative polymerase chain reaction. This study provides substantial transcriptomic information regarding the SG of D. citri in response to CLas infection, which may shed light on the molecular interaction between D. citri and CLas, and provides new ideas for the prevention and control of citrus psyllid.

Chlorite is one of the most common Fe-bearing minerals and is susceptible to weathering in loess and soils. The conventional method for analyzing chlorite, based on XRD with the Rietveld technique, is quantitative, but very time consuming and expensive. In this paper we develop a new methodology based on diffuse reflectance spectroscopy (DRS) and selective chemical extractions to identify chlorite qualitatively in the Chinese loess sequence and present evidence suggesting that DRS may be used to quantify chlorite content. The spectral signature of chlorite in loess is obscured by Fe oxides, but becomes obvious when they are removed. Changes in the ferrous absorption band near 1140 nm vary consistently with changing chlorite content. Using this spectral feature, DRS can distinguish chlorite contents as small as 1 wt.% in loess sediments. Future possibilities for this method in other soil and sediment types need to be explored.

Energy loss of protons with 90 and 100 keV energies penetrating through a hydrogen plasma target has been measured, where the electron density of the plasma is about 1016 cm−3 and the electron temperature is about 1-2 eV. It is found that the energy loss of protons in the plasma is obviously larger than that in cold gas and the experimental results based on the Bethe model calculations can be demonstrated by the variation of effective charge of protons in the hydrogen plasma. The effective charge remains 1 for 100 keV protons, while the value for 90 keV protons decreases to be about 0.92. Moreover, two empirical formulae are employed to extract the effective charge.

Laser-induced damage threshold is the main limitation for fused silica optics in high-power laser applications. The existence of various defects near the surface is the key factor for the degradation of the threshold. In this work, the photoluminescence spectra at different regions of the damaged and recovered fused silica samples are recorded to analyze the correlation between photoluminescence of surface defects and laser-induced damage threshold. The experimental data concluded the inverse proportional correlation between fluorescence and laser-induced damage threshold value. The weak photoluminescence is the guarantee of the high laser-induced damage threshold, and then the higher local Si nanocluster concentration corresponds with the higher laser-induced damage threshold value for the fused silica optics after CO2 laser treatment. The investigation reveals that photoluminescence measurement can be employed to check the quality of pristine fused silica and evaluate the tendency of the laser-induced damage threshold value. The current results are helpful for understanding the evolution of interaction from CO2 laser treatment and fused silica optics and can provide the guide of process technology for the high quality of fused silica optics.

Typical ophiolitic rock assemblages such as siliciclastic rocks, basalts and gabbros, together with the subduction-related intermediate-acidic intrusive rocks, are newly discovered in the Tongjiang-Fuyuan area of the Heilongjiang Provence, NE China. To determine the formation age and genesis of the mafic rocks (basalts and gabbros) and intermediate-acidic intrusive rocks (granodiorites) in the area, as well as their geodynamic settings, the whole-rock geochemical analysis and zircon LA-ICP-MS U-Pb dating were carried out. Zircon U-Pb results suggest that the granodiorites are 93–95 Ma and gabbro is 95 Ma, respectively. Geochemical results show that the gabbros and basalts exhibit characteristics of ocean island basalt (OIB) affinity and are typically related to having originated from mantle plumes. While the granodiorites show the nature of the island-arc magmatic rocks and may originate from the lower crust. Based on the coeval igneous rock associations and regional tectonic evolution, we conclude that the late Cretaceous magmatic rocks in the Tongjiang-Fuyuan area are the product of continuous subduction of the Palaeo-Pacific plate and reflect the subduction rollback process of the Palaeo-Pacific plate.

This experiment was conducted to investigate whether dietary chenodeoxycholic acid (CDCA) could attenuate high-fat (HF) diet-induced growth retardation, lipid accumulation and bile acid (BA) metabolism disorder in the liver of yellow catfish Pelteobagrus fulvidraco. Yellow catfish (initial weight: 4·40 (sem 0·08) g) were fed four diets: the control (105·8 g/kg lipid), HF diet (HF group, 159·6 g/kg lipid), the control supplemented with 0·9 g/kg CDCA (CDCA group) and HF diet supplemented with 0·9 g/kg CDCA (HF + CDCA group). CDCA supplemented in the HF diet significantly improved growth performance and feed utilisation of yellow catfish (P < 0·05). CDCA alleviated HF-induced increment of hepatic lipid and cholesterol contents by down-regulating the expressions of lipogenesis-related genes and proteins and up-regulating the expressions of lipololysis-related genes and proteins. Compared with the control group, CDCA group significantly reduced cholesterol level (P < 0·05). CDCA significantly inhibited BA biosynthesis and changed BA profile by activating farnesoid X receptor (P < 0·05). The contents of CDCA, taurochenodeoxycholic acid and glycochenodeoxycholic acid were significantly increased with the supplementation of CDCA (P < 0·05). HF-induced elevation of cholic acid content was significantly attenuated by the supplementation of CDCA (P < 0·05). Supplementation of CDCA in the control and HF groups could improve the liver antioxidant capacity. This study proved that CDCA could improve growth retardation, lipid accumulation and BA metabolism disorder induced by HF diet, which provided new insight into understanding the physiological functions of BA in fish.

The effects of monolaurin (ML) on the health of piglets infected with porcine epidemic diarrhoea virus (PEDV) have not been fully understood. This study aimed to investigate its role in blood biochemical profile, intestinal barrier function, antioxidant function and the expression of antiviral genes in piglets infected with PEDV. Thirty-two piglets were randomly divided into four groups: control group, ML group, PEDV group and ML + PEDV group. Piglets were orally administrated with ML at a dose of 100 mg/kg·BW for 7 d before PEDV infection. Results showed that PEDV infection significantly decreased D-xylose content and increased intestinal fatty acid-binding protein content, indicating that PEDV infection destroyed intestinal barrier and absorption function. While it could be repaired by ML administration. Moreover, ML administration significantly decreased plasma blood urea nitrogen and total protein content upon PEDV infection. These results suggested ML may increase protein utilisation efficiency. ML administration significantly decreased the number of large unstained cells and Hb and increased the number of leucocytes and eosinophils in the blood of PEDV-infected piglets, indicating ML could improve the immune defense function of the body. In the presence of PEDV infection, ML administration significantly increased superoxide dismutase and catalase activities in blood and colon, respectively, indicating ML could improve antioxidant capacity. Besides, ML administration reversed the expression of ISG15, IFIT3 and IL-29 throughout the small intestine and Mx1 in jejunum and ileum, indicating the body was in recovery from PEDV infection. This study suggests that ML could be used as a kind of feed additive to promote swine health upon PEDV infection.

The advent of time-domain sky surveys has generated a vast amount of light variation data, enabling astronomers to investigate variable stars with large-scale samples. However, this also poses new opportunities and challenges for the time-domain research. In this paper, we focus on the classification of variable stars from the Catalina Surveys Data Release 2 and propose an imbalanced learning classifier based on Self-paced Ensemble (SPE) method. Compared with the work of Hosenie et al. (2020), our approach significantly enhances the classification Recall of Blazhko RR Lyrae stars from 12% to 85%, mixed-mode RR Lyrae variables from 29% to 64%, detached binaries from 68% to 97%, and LPV from 87% to 99%. SPE demonstrates a rather good performance on most of the variable classes except RRab, RRc, and contact and semi-detached binary. Moreover, the results suggest that SPE tends to target the minority classes of objects, while Random Forest is more effective in finding the majority classes. To balance the overall classification accuracy, we construct a Voting Classifier that combines the strengths of SPE and Random Forest. The results show that the Voting Classifier can achieve a balanced performance across all classes with minimal loss of accuracy. In summary, the SPE algorithm and Voting Classifier are superior to traditional machine learning methods and can be well applied to classify the periodic variable stars. This paper contributes to the current research on imbalanced learning in astronomy and can also be extended to the time-domain data of other larger sky survey projects (LSST, etc.).

Although ethanol treatment is widely used to activate oocytes, the underlying mechanisms are largely unclear. Roles of intracellular calcium stores and extracellular calcium in ethanol-induced activation (EIA) of oocytes remain to be verified, and whether calcium-sensing receptor (CaSR) is involved in EIA is unknown. This study showed that calcium-free ageing (CFA) in vitro significantly decreased intracellular stored calcium (sCa) and CaSR expression, and impaired EIA, spindle/chromosome morphology and developmental potential of mouse oocytes. Although EIA in oocytes with full sCa after ageing with calcium does not require calcium influx, calcium influx is essential for EIA of oocytes with reduced sCa after CFA. Furthermore, the extremely low EIA rate in oocytes with CFA-downregulated CaSR expression and the fact that inhibiting CaSR significantly decreased the EIA of oocytes with a full complement of CaSR suggest that CaSR played a significant role in the EIA of ageing oocytes. In conclusion, CFA impaired EIA and the developmental potential of mouse oocytes by decreasing sCa and downregulating CaSR expression. Because mouse oocytes routinely treated for activation (18 h post hCG) are equipped with a full sCa complement and CaSR, the present results suggest that, while calcium influx is not essential, CaSR is required for the EIA of oocytes.