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Featured Application: This research delves into the cutting-edge domain of robotic automation, specifically focusing on the development and application of a six-degree-of-freedom refueling robotic arm guided by RGB-D (Red, Green, Blue—Depth) visual technology. The study explores the intricate processes involved in the accurate positioning and docking of a robotic arm in refueling tasks, leveraging the advanced capabilities of RGB-D sensors for enhanced spatial awareness and precise maneuvering. The current application areas of this technology predominantly reside in industrial automation, particularly in sectors requiring precise and repetitive tasks such as automotive manufacturing, aerospace, and logistics. The potential applications extend further into fields like unmanned service stations, military logistics, and remote operation environments where human intervention is limited or hazardous. This research contributes to the evolving landscape of robotic automation, offering insights into more efficient, more accurate, and safer automated refueling processes, potentially revolutionizing how these tasks are approached in various industrial and commercial sectors. The main contribution of this paper is the proposal of a six-degree-of-freedom (6-DoF) refueling robotic arm positioning and docking technology guided by RGB-D camera visual guidance, as well as conducting in-depth research and experimental validation on the technology. We have integrated the YOLOv8 algorithm with the Perspective-n-Point (PnP) algorithm to achieve precise detection and pose estimation of the target refueling interface. The focus is on resolving the recognition and positioning challenges of a specialized refueling interface by the 6-DoF robotic arm during the automated refueling process. To capture the unique characteristics of the refueling interface, we developed a dedicated dataset for the specialized refueling connectors, ensuring the YOLO algorithm's accurate identification of the target interfaces. Subsequently, the detected interface information is converted into precise 6-DoF pose data using the PnP algorithm. These data are used to determine the desired end-effector pose of the robotic arm. The robotic arm's movements are controlled through a trajectory planning algorithm to complete the refueling gun docking process. An experimental setup was established in the laboratory to validate the accuracy of the visual recognition and the applicability of the robotic arm's docking posture. The experimental results demonstrate that under general lighting conditions, the recognition accuracy of this docking interface method meets the docking requirements. Compared to traditional vision-guided methods based on OpenCV, this visual guidance algorithm exhibits better adaptability and effectively provides pose information for the robotic arm. [ABSTRACT FROM AUTHOR]

The traditional underwater integrated navigation system is based on an optical fiber gyroscope and Doppler Velocity Log, which is high-precision but also expensive, heavy, bulky and difficult to adapt to the development requirements of AUV swarm, intelligence and miniaturization. This paper proposes a low-cost, light-weight, small-volume and low-computation underwater integrated navigation system based on MEMS IMU/DVL/USBL. First, according to the motion formula of AUV, a five-dimensional state equation of the system was established, whose dimension was far less than that of the traditional. Second, the main source of error was considered. As the velocity observation value of the system, the velocity measured by DVL eliminated the scale error and lever arm error. As the position observation value of the system, the position measured by USBL eliminated the lever arm error. Third, to solve the issue of inconsistent observation frequencies between DVL and USBL, a sequential filter was proposed to update the extended Kalman filter. Finally, through selecting the sensor equipment and conducting two lake experiments with total voyages of 5.02 km and 3.2 km, respectively, the correctness and practicality of the system were confirmed by the results. By comparing the output of the integrated navigation system and the data of RTK GPS, the average position error was 4.12 m, the maximum position error was 8.53 m, the average velocity error was 0.027 m/s and the average yaw error was 1.41°, whose precision is as high as that of an optical fiber gyroscope and Doppler Velocity Log integrated navigation system, but the price is less than half of that. The experimental results show that the proposed underwater integrated navigation system could realize the high-precision and long-term navigation of AUV in the designated area, which had great potential for both military and civilian applications. [ABSTRACT FROM AUTHOR]

The effects of cyclic loading on the surface microstructure evolution of different contact locations in a used pearlitic rail were studied. Microstructures were analyzed using Scanning Electron Microscopy (SEM). Meanwhile, grain boundaries and crystallographic orientations were explored via Electron Backscatter Diffraction (EBSD). At last, wheel–rail contact probabilities and forces were calculated using rail profiles. The results indicate that the side wear region located in the gauge face was 71.5% in the high-angle grain boundaries (HAGBs) fraction, 0.88 in the Kernel Average Misorientation (KAM) value, 36% in the recrystallization (REX) fraction, and had a predominant orientation in grains. The rolling contact fatigue (RCF) region situated at the gauge corner was 66.3% in the HAGBs fraction, 0.92 in the KAM value, 33% in the REX fraction, and was mis-orientated in grains. The region located at the edge of the running band was 60.7% in the low-angle grain boundaries (LAGBs) fraction, 0.97 in the KAM value, 12% in the REX fraction, and was mis-orientated in grains. Continuous dynamic recrystallization (cDRX) took place in wear and RCF regions during the cyclic rolling contact loading, creating ultra-fine grains with a transformation from LAGBs to HAGBs, lower KAM values, and more REX. Grains oriented along [111] parallel to the vertical direction in the wear region were influenced by the dominant normal force, while grains in the RCF region were non-oriented, which was attributed to large lateral and vertical forces of similar magnitudes. [ABSTRACT FROM AUTHOR]

Whether for institutional investors or individual investors, there is an urgent need to explore autonomous models that can adapt to the non-stationary, low-signal-to-noise markets. This research aims to explore the two unique challenges in quantitative portfolio management: (1) the difficulty of representation and (2) the complexity of environments. In this research, we suggest a Markov decision process model-based deep reinforcement learning model including deep learning methods to perform strategy optimization, called SwanTrader. To achieve better decisions of the portfolio-management process from two different perspectives, i.e., the temporal patterns analysis and robustness information capture based on market observations, we suggest an optimal deep learning network in our model that incorporates a stacked sparse denoising autoencoder (SSDAE) and a long–short-term-memory-based autoencoder (LSTM-AE). The findings in times of COVID-19 show that the suggested model using two deep learning models gives better results with an alluring performance profile in comparison with four standard machine learning models and two state-of-the-art reinforcement learning models in terms of Sharpe ratio, Calmar ratio, and beta and alpha values. Furthermore, we analyzed which deep learning models and reward functions were most effective in optimizing the agent's management decisions. The results of our suggested model for investors can assist in reducing the risk of investment loss as well as help them to make sound decisions. [ABSTRACT FROM AUTHOR]

In the past decade, the application of deep reinforcement learning (DRL) in portfolio management has attracted extensive attention. However, most classical RL algorithms do not consider the exogenous and noise of financial time series data, which may lead to treacherous trading decisions. To address this issue, we propose a novel anti-risk portfolio trading method based on deep reinforcement learning (DRL). It consists of a stacked sparse denoising autoencoder (SSDAE) network and an actor–critic based reinforcement learning (RL) agent. SSDAE will carry out off-line training first, while the decoder will used for on-line feature extraction in each state. The SSDAE network is used for the noise resistance training of financial data. The actor–critic algorithm we use is advantage actor–critic (A2C) and consists of two networks: the actor network learns and implements an investment policy, which is then evaluated by the critic network to determine the best action plan by continuously redistributing various portfolio assets, taking Sharp ratio as the optimization function. Through extensive experiments, the results show that our proposed method is effective and superior to the Dow Jones Industrial Average index (DJIA), several variants of our proposed method, and a state-of-the-art (SOTA) method. [ABSTRACT FROM AUTHOR]

Accumulated evidence has revealed the mitigation effects of exogenous melatonin on cold stress in plants. In this study, to investigate the defensive roles of exogenous melatonin in banana under cold stress, we researched the influences of exogenous melatonin on the chlorophyll fluorescence parameters, antioxidant defense indexes and expression levels of cold-responsive genes in cold-stressed 'Brazil' banana seedlings. Results showed that 100 μM of exogenous melatonin achieved the best cold-resistance-promoting effect in banana. Exogenous melatonin treatment significantly increased the electron transfer rate, light harvesting efficiency, total antioxidant capacity, catalase and superoxidase activities and proline and soluble sugar contents and significantly reduced the accumulations of malondialdehyde, superoxide anion and hydrogen peroxide in the leaves of cold-stressed banana. In addition, under cold stress, melatonin significantly induced the expression of low-temperature-responsive genes, such as MaChiI1, MaCSD1C, MaWhy1, MaKIN10, MaADA1 and MaHOS1. It was concluded that the application of exogenous melatonin enhanced antioxidant defense and induced the expression of cold-responsive genes, thereby improving the cold resistance of banana. Our study will provide a basis for the application of exogenous melatonin in improving plant cold resistance. [ABSTRACT FROM AUTHOR]

Simple Summary: By using 'Zhongjiao No.3' and 'Zhongjiao No.4' banana seedlings as plant materials, we investigated the influences of Serendipita indica and bamboo fungus (Dictyophorae echinovolvata) culture substrates on the growth and wilt disease resistance of banana. S. indica colonization significantly enhanced the growth of the two banana cultivars, while banana seedlings grown in nutrient soil containing bamboo fungus culture substrates inoculated with D. echinovolvata showed suppressed growth. Moreover, both S. indica colonization and D. echinovolvata culture substrates addition can alleviate the disease symptoms caused by Fusarium oxysporum f. sp. cubense tropical race 4 (FocTR4), and their combined application showed the best disease resistance enhancement effect. The results obtained in this study can provide a basis for the application of S. indica and bamboo fungus in the prevention and control of banana Fusarium wilt disease in the future. Recently, many control methods have been tried and applied in the Fusarium wilt disease control of banana and have achieved definite progresses. In this study, by using 'Zhongjiao No.3' and 'Zhongjiao No.4' banana seedlings as materials, the effects of Serendipita indica and bamboo fungus (Dictyophorae echinovolvata) culture substrates on the growth and Fusarium wilt disease resistance of banana were investigated. Results showed that the plant height, leaf length, leaf width, root length and root thickness, aboveground part fresh weight, root fresh weight, and relative chlorophyll content and nitrogen content in leaves of banana seedlings colonized with S. indica were all greater than those of non-colonized controls, while these parameters of banana seedlings grown in nutrient soil containing D. echinovolvata culture substrates were significantly suppressed. Both S. indica non-colonized and colonized seedlings cultivated in nutrient containing 1/4 D. echinovolvata culture substrates showed much milder symptoms compared with those cultivated in normal nutrient soil, indicating that the addition of bamboo fungus substrates to the soil can enhance the Fusarium wilt resistance of banana. The results obtained in this study can provide a basis for the application of S. indica and bamboo fungus in the prevention and control of banana Fusarium wilt disease. [ABSTRACT FROM AUTHOR]

A leaf blight disease with an incidence level of about 50% was found on Robusta banana in Guangdong province of China in September 2020. The early symptom appeared as pale gray to black brown, irregular, small, necrotic lesions mainly on the top 3–5 leaves. Severely infected leaves were withered and necrotic. Two representative fungus strains, strain L1 and strain L2, were isolated from affected banana leaves, and morphological and molecular identification analysis confirmed that the two fungi were both Alternaria jacinthicola. Many Alternaria species have been reported to cause wilting, decay, leaf blight and leaf spots on plants and lead to serious economic losses in their production, including A. alternata, causing leaf blight and leaf sport diseases on banana. The Koch's postulates of A. jacinthicola causing the leaf blight disease was further fulfilled, which confirmed that it is the causal agent of this disease. To our knowledge, this is the first report of A. jacinthicola causing leaf blight on banana in China. [ABSTRACT FROM AUTHOR]

Basic helix-loop-helix proteins (bHLHs) play very important roles in the anthocyanin biosynthesis of many plant species. However, the reports on blueberry anthocyanin biosynthesis-related bHLHs were very limited. In this study, six anthocyanin biosynthesis-related bHLHs were identified from blueberry genome data through homologous protein sequence alignment. Among these blueberry bHLHs, VcAN1, VcbHLH42-1, VcbHLH42-2 and VcbHLH42-3 were clustered into one group, while VcbHLH1-1 and VcbHLH1-2 were clustered into the other group. All these bHLHs were of the bHLH-MYC_N domain, had DNA binding sites and reported conserved amino acids in the bHLH domain, indicating that they were all G-box binding proteins. Protein subcellular location prediction result revealed that all these bHLHs were nucleus-located. Gene structure analysis showed that VcAN1 gDNA contained eight introns, while all the others contained seven introns. Many light-, phytohormone-, stress- and plant growth and development-related cis-acting elements and transcription factor binding sites (TFBSs) were identified in their promoters, but the types and numbers of cis-elements and TFBSs varied greatly between the two bHLH groups. Quantitative real-time PCR results showed that VcAN1 expressed highly in old leaf, stem and blue fruit, and its expression increased as the blueberry fruit ripened. Its expression in purple podetium and old leaf was respectively significantly higher than in green podetium and young leaf, indicating that VcAN1 plays roles in anthocyanin biosynthesis regulation not only in fruit but also in podetium and leaf. VcbHLH1-1 expressed the highest in young leaf and stem, and the lowest in green fruit. The expression of VcbHLH1-1 also increased as the fruit ripened, and its expression in blue fruit was significantly higher than in green fruit. VcbHLH1-2 showed high expression in stem but low expression in fruit, especially in red fruit. Our study indicated that the anthocyanin biosynthesis regulatory functions of these bHLHs showed certain spatiotemporal specificity. Additionally, VcAN1 might be a key gene controlling the anthocyanin biosynthesis in blueberry, whose function is worth exploring further for its potential applications in plant high anthocyanin breeding. [ABSTRACT FROM AUTHOR]

This study aims to deeply understand the effect of contact stress and slip ratio on wear performances of bainitic rail steels. The results showed that the wear loss increased as the contact stress and slip ratio increased. Based on the surface damage morphology and microstructural analyses, it revealed that the rolling contact fatigue wear mechanism played a significant role under the low slip ratio, but the dominant wear mechanism transferred to the abrasive wear at the high slip ratio. Meanwhile, the bainitic steel specifically presented worse wear resistance under the abrasive wear mode. Compared with the influence of a slip ratio, the increase in contact stress led to severer plastic flows and contributed to the propagation of cracks. In addition, the contact stress and slip ratio had the opposite effect on the friction coefficient, that is, the friction coefficient of bainitic steels behaved the inverse proportion with the contact stress, but positive proportion with the slip ratio. At last, the increase in slip ratio had more significant effect on the reduction of retained austenite (RA) than the enlargement of contact stress due to the fact that the RA would probably be removed before the martensitic transformation occurred under the abrasive wear mechanism. [ABSTRACT FROM AUTHOR]

Introns exist not only in coding sequences (CDSs) but also in untranslated regions (UTRs) of a gene. Recent studies in animals and model plants such as Arabidopsis have revealed that the UTR-introns (UIs) are widely presented in most genomes and involved in regulation of gene expression or RNA stability. In the present study, we identified introns at both 5′UTRs (5UIs) and 3′UTRs (3UIs) of sweet orange genes, investigated their size and nucleotide distribution characteristics, and explored the distribution of cis-elements in the UI sequences. Functional category of genes with predicted UIs were further analyzed using GO, KEGG, and PageMan enrichment. In addition, the organ-dependent splicing and abundance of selected UI-containing genes in root, leaf, and stem were experimentally determined. Totally, we identified 825 UI- and 570 3UI-containing transcripts, corresponding to 617 and 469 genes, respectively. Among them, 74 genes contain both 5UI and 3UI. Nucleotide distribution analysis showed that 5UI distribution is biased at both ends of 5′UTR whiles 3UI distribution is biased close to the start site of 3′UTR. Cis- elements analysis revealed that 5UI and 3UI sequences were rich of promoter-enhancing related elements, indicating that they might function in regulating the expression through them. Function enrichment analysis revealed that genes containing 5UI are significantly enriched in the RNA transport pathway. While, genes containing 3UI are significantly enriched in splicesome. Notably, many pentatricopeptide repeat-containing protein genes and the disease resistancegenes were identified to be 3UI-containing. RT-PCR result confirmed the existence of UIs in the eight selected gene transcripts whereas alternative splicing events were found in some of them. Meanwhile, qRT-PCR result showed that UIs were differentially expressed among organs, and significant correlation was found between some genes and their UIs, for example: The expression of VPS28 and its 3UI was significantly negative correlated. This is the first report about the UIs in sweet orange from genome-wide level, which could provide evidence for further understanding of the role of UIs in gene expression regulation. [ABSTRACT FROM AUTHOR]

With the increasing consumption of electric energy, how to improve the capacity of transmission lines within safe margins is an urgent problem to be solved. This paper presents a transient thermal rating method under real-time meteorological conditions. The result of thermal ratings under different conditions shows that this rating approach can significantly increase the capacity of the line. As some of the most critical variables are remaining time and initial temperature, their influence upon the rating is studied. The method of statistical analysis is used to determine the ampacity at different risk levels. The result indicates that with smaller remaining time, the ampacities are larger, and with larger ampacities, the risk of thermal overload is greater. The choice of risk level would heavily affect the values of ampacity. [ABSTRACT FROM AUTHOR]

A portion of dodecyl amine (DDA) in a muscovite flotation system was replaced with alcohols with different carbon-chain lengths. These alcohols included octanol (OCT); decanol (DEC); dodecanol (DOD); and tetradecanol (TER). The muscovite adsorption behavior of the mixed DDA and alcohol systems were investigated through zeta potential; contact angle; and adsorption quantity tests. Single-mineral flotation tests showed that the muscovite-collecting power of the mixed DDA/alcohol (OCT, DEC, or DOD) system was stronger than that of the pure DDA system. The muscovite-collecting power of the collector systems decreased in the following order: DDA/DEC > DDA/OCT > DDA/DEC > DDA > DDA/TER. Zeta potential and contact angle analysis indicated that when combined with DDA; alcohols physically adsorbed on the surfaces of muscovite. This behavior improved the hydrophobicity of muscovite. Furthermore, adsorption analysis revealed that synergy between DDA and alcohol enhanced the adsorption of alcohol on muscovite. DDA has a dominant role in synergistic adsorption; whereas alcohol has a supporting role. Among all tested alcohols; DDA and DOD exhibit the highest synergetic adsorption effect because of their similar carbon-chain lengths. This similarity promotes the formation of a compact adsorption layer on the muscovite surface. [ABSTRACT FROM AUTHOR]