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The rapid advancement in Unpiloted Robotic Vehicle technology has significantly influenced ground support operations at airports, marking a critical shift towards future development. This study presents a novel Unpiloted Ground Support Equipment (GSE) detection and control framework, comprising virtual channel delineation, boundary line detection, object detection, and navigation and docking control, to facilitate automated aircraft docking within the aircraft stand. Firstly, we developed a bespoke virtual channel layout for Unpiloted GSE, aligning with operational regulations and accommodating a wide spectrum of aircraft types. This layout employs turning induction markers to define essential navigation points, thereby streamlining GSE movement. Secondly, we integrated cameras and Lidar sensors to enable rapid and precise pose adjustments during docking. The introduction of a boundary line detection system, along with an optimized, lightweight YOLO algorithm, ensures swift and accurate identification of boundaries, obstacles, and docking sites. Finally, we formulated a unique control algorithm for effective obstacle avoidance and docking in varied apron conditions, guaranteeing meticulous management of vehicle pose and speed. Our experimental findings reveal an 89% detection accuracy for the virtual channel boundary line, a 95% accuracy for guiding markers, and an F1-Score of 0.845 for the YOLO object detection algorithm. The GSE achieved an average docking error of less than 3 cm and an angular deviation under 5 degrees, corroborating the efficacy and advanced nature of our proposed approach in Unpiloted GSE detection and aircraft docking.

This paper introduces a novel geometry-based synchrosqueezing S-transform (GSSST) for advanced gearbox fault diagnosis, designed to enhance diagnostic precision in both planetary and parallel gearboxes. Traditional time-frequency analysis (TFA) methods, such as the Synchrosqueezing S-transform (SSST), often face challenges in accurately representing fault-related features when significant mode closely spaced components are present. The proposed GSSST method overcomes these limitations by implementing an intuitive geometric reassignment framework, which reassigns time-frequency (TF) coefficients to maximize energy concentration, thereby allowing fault components to be distinctly isolated even under challenging conditions. The GSSST algorithm calculates a new instantaneous frequency (IF) estimator that aligns closely with the ideal IF, thus concentrating TF coefficients more effectively than existing methods. Experimental validation, including tests on simulated signals and real-world gearbox fault data, demonstrates that GSSST achieves high robustness and diagnostic accuracy across various types of gearbox faults even in the presence of noise. Moreover, unlike conventional reassignment method, GSSST supports partial signal reconstruction, a key advantage for applications requiring accurate signal recovery. This research highlights GSSST as a promising and versatile tool for diagnosing complex mechanical faults and provides new insights for the future development of TFA methods in mechanical fault analysis.

To promote the application of automated vehicles in large airports, in this study, we present an integrated optimization method for scheduling Unmanned follow-me cars. The scheduling process is divided into three phases: Dispatch, Guidance, and Recycle. For the Dispatch phase, we establish a vehicle assignment model, to allocate the vehicle resource equitably. For the Guidance phase, we offer an quantitative way, to measure the spacing between Unmanned follow-me car and aircraft. To optimize the efficiency of airport operation in the three phases and ensure safety, the collaborative planning model, and the conflict prediction model are established. An improved grey wolf optimization algorithm is adopted to enhance the convergence speed and generalization performance. A case study at Ezhou Huahu Airport in China demonstrates the effectiveness of the methods. The results show that the model of collaborative planning can make the balance of path selection, Unmanned follow-me car’s working time, and departure sequence. The convergence speed of the improved algorithm has been increased by 18.75%. The inequity index of vehicle assignment is only 0.015731, and the spatiotemporal distribution of conflicts is influenced by the airport’s surface layout.

The resilience and vulnerability of airport networks are significant challenges during the COVID-19 global pandemic. Previous studies considered node failure of networks under natural disasters and extreme weather. Herein, we propose a complex network methodology combined with data-driven to assess the resilience of airport networks toward global-scale disturbance using the Chinese airport network (CAN) and the European airport network (EAN) as a case study. The assessment framework includes vulnerability and resilience analyses from the network- and node-level perspectives. Subsequently, we apply the framework to analyze the airport networks in China and Europe. Specifically, real air traffic data for 232 airports in China and 82 airports in Europe are selected to form the CAN and EAN, respectively. The complex network analysis reveals that the CAN and the EAN are scale-free small-world networks, that are resilient to random attacks. However, the connectivity and vulnerability of the CAN are inferior to those of the EAN. In addition, we select the passenger throughput from the top-50 airports in China and Europe to perform a comparative analysis. By comparing the resilience evaluation of individual airports, we discovered that the factors of resilience assessment of an airport network for global disturbance considers the network metrics and the effect of government policy in actual operations. Additionally, this study also proves that a country’s emergency response-ability towards the COVID-19 has a significantly affectes the recovery of its airport network.

The feasibility of carbon mineralization relies on the carbonation efficiency of CO 2 -reactive minerals, which is largely governed by the water content and state within material mesopores. Yet, the pivotal role of confined water in regulating carbonation efficiency at the nanoscale is not well understood. Here, we show that the maximum CO 2 intake occurs at an optimal relative humidity (RH opt ) when capillary condensation initiates within the hydrophilic mesopores. At this transition state, the pore becomes filled with metastable low-density water, providing an ideal docking site for CO 2 adsorption and forming a mixed metastable state of water/CO 2 . We prove that RH opt depends on the mesopore size through a Kelvin-like relationship, which yields a robust engineering model to predict RH opt for realistic mineral carbonation. Building upon classical theories of phase transition in hydrophilic mesopores, this study unveils the capacity of the metastable water in CO 2 intake and enhances the high-efficiency carbon mineralization with natural ore and industrial wastes in real-world applications. CO 2 can be captured in mesoporous alkaline waste materials. Here the authors provide atomistic insight for CO 2 adsorption in calcium hydroxide to identify optimal relative humidity conditions for maximum CO 2 intake.

Cancer is one of the leading causes of morbidity and mortality in the global population. The effective management of cancer-associated pain and anesthesia are critical aspects of comprehensive cancer treatment. However, the role and mechanism of anesthesia and analgesia-related drugs in tumors remain controversial. In this study, the efficacy of 16 commonly used analgesics and anesthetics against non-small cell lung cancer (NSCLC) was evaluated. Among the 16 examined injections, butorphanol tartrate injection significantly inhibited the proliferation of NSCLC cells and increased the sensitivity of the EGFR-TKI-resistant H1975 cell line to gefitinib. Benzethonium chloride (BC) is the main active antitumor ingredient of butorphanol tartrate injection. BC may regulate the cell cycle, apoptosis and EMT signaling pathways by modulating the P53 signaling pathway. Our study reveals the therapeutic value of butorphanol tartrate injection and BC in the treatment of NSCLC and provides a theoretical basis for comprehensive therapies for NSCLC.

Helminth-modulated macrophages contribute to attenuating inflammation in inflammatory bowel diseases. The programmed death 1 (PD-1) plays an important role in macrophage polarization and is essential in the maintenance of immune system homeostasis. Here, we investigate the role of PD-1-mediated polarization of M2 macrophages and the protective effects of excretory/secretory products from adult worms (AES) on DSS-induced colitis in mice. Colitis in mice was induced by oral administration of dextran sodium sulfate (DSS) daily. Mice with DSS-induced colitis were treated with AES intraperitoneally, and pathological manifestations were evaluated. Macrophages in mice were depleted with liposomal clodronate. Markers for M1-type (iNOS, TNF-α) and M2-type (CD206, Arg-1) macrophages were detected by qRT-PCR and flow cytometry. Macrophage expression of PD-1 was quantified by flow cytometry; RAW 264.7 cells and peritoneal macrophages were used for tests, and PD-1 gene knockout mice were used for investigation of the role of PD-1 in AES-induced M2 macrophage polarization. Macrophage depletion was found to reduce DSS-induced colitis in mice. Treatment with AES significantly increased macrophage expression of CD206 and Arg-1 and simultaneously attenuated colitis severity. We found AES to enhance M2 macrophage polarization; these findings were confirmed studying cultures of RAW264.7 cells and peritoneal macrophages from mice. Further experimentation revealed that AES upregulated PD-1 expression, primarily on M2 macrophages expressing CD206. The AES-induced M2 polarization was found to be decreased in PD-1 deficient macrophages, and the therapeutic effects of AES on colitis was reduced in PD-1 knockout mice. In conclusion, the protective effects of AES on DSS-induced colitis were found to associate with PD-1 upregulation and M2 macrophage polarization. Thus, PD-1-mediated M2 macrophage polarization is a key mechanism of helminth-induced modulation of the host immune system.

Carbonatable minerals on earth have significant potential to act as gigatonne-scale CO 2 sinks. Many carbon removal managements rely on CO 2 mineralization on wetting mineral surfaces. Realizing their carbon removal potential requires a fundamental understanding of the atomic-scale mechanisms of mineral carbonation. This study employs reactive/non-reactive molecular simulations and well-tempered metadynamics to elucidate the complete interfacial CO 2 mineralization pathways within a portlandite mesopore adsorbed with a nanometric water film. Here we reveal quantitatively, for the first time, a global CO 2 mineralization spectrum describing the local molecular environment and the thermodynamics of the five critical steps: water adsorption, calcium dissolution, CO 2 adsorption, CO 2 speciation, and CaCO 3 ion pairing. We identify kinks as the primary reactive sites for surface dissolution and demonstrate how the water film’s acid-base environment modulates these processes, creating an energetically favorable reaction loop for sustained CO 2 mineralization. We uncover that quasi-neutral to slightly basic conditions optimize mineralization efficiency by balancing the opposing effects of pH on calcium dissolution and CO 2 speciation. Mineral carbonation could enable gigatonne-scale CO 2 removal. Here, the authors use molecular simulations to map a full CO 2 mineralization pathway at a wetting surface, revealing key reactive sites and optimal pH conditions for efficient carbonation.

Many evidences show the inverse correlation between helminth infection and allergic or autoimmune diseases. Identification and characterization of the active helminth-derived products responsible for the beneficial effects on allergic or inflammatory diseases will provide another feasible approach to treat these diseases. Colitis was induced in C57BL/6 mice by giving 3% DSS orally for 7 days. During this period, the mice were treated daily with the excretory/secretory products from T. spiralis adult worms (AES) intraperitoneally. The severity of colitis was monitored by measuring body weight, stool consistency or bleeding, colon length and inflammation. To determine the T. spiralis AES product-induced immunological response, Th1, Th2, Th17 and regulatory cytokine profiles were measured in lymphocytes isolated from colon, mesenteric lymph nodes (MLN), and the spleen of treated mice. The CD4+ CD25+ FOXP3+ regulatory T cells (Tregs) were also measured in the spleens and MLN of treated mice. Mice treated with AES significantly ameliorated the severity of the DSS-induced colitis indicated by the reduced disease manifestations, improved macroscopic and microscopic inflammation correlated with the up-regulation of Treg response (increased regulatory cytokines IL-10, TGF-beta and regulatory T cells) and down-regulation of pro-inflammatory cytokines (IFN-gamma, IL-6 and IL-17) in the spleens, MLN and colon of treated mice. Our results provide direct evidences that T. spiralis AES have a therapeutic potential for alleviating inflammatory colitis in mice. This effect is possibly mediated by the immunomodulation of regulatory T cells to produce regulatory and anti-inflammatory cytokines and inhibit pro-inflammatory cytokines.

, a bacterium widely distributed in the natural environment, causes multiple diseases in various animals. Exploring the mechanism of the host defense against can help develop efficient strategies against infection. Herein, we investigated the temporal influence of A. hydrophila on the Chinese soft-shelled turtle, an economically important species, at the biochemical, transcriptomic, and metabolomic levels. Plasma parameters were detected with the test kits. Transcriptome and metabolome were respectively applied to screen the differentially expressed genes and metabolites. The contents or activities of these plasma parameters were significantly increased at 24 hpi and declined at 96 hpi, indicating that 24 and 96 hpi were two important time points during infection. Totals of 3121 and 274 differentially expressed genes (DEGs) from the transcriptome while 74 and 91 differentially abundant metabolites (DAMs) from the metabolome were detected at 24 and 96 hpi. The top DEGs at 24 hpi included and while and were the most abundant at 96 hpi. The predominant DAMs included O-phospho-L-serine, γ-Aminobutyric acid, orotate, L-tyrosine, and L-tryptophan at 24 hpi, as well as L-glutamic acid, L-arginine, glutathione, glutathione disulfide, and citric acid at 96 hpi. The combined analysis of DEGs and DAMs revealed that tryptophan metabolism, nicotinate and nicotinamide metabolism, as well as starch and sucrose metabolism, were the most important signaling pathways at the early infective stage while tyrosine metabolism, pyrimidine metabolism, as well as alanine, aspartate and glutamate metabolism were the most crucial pathways at the later stage. In general, our results indicated that the Chinese soft-shelled turtle displays stage-specific physiological responses to resist infection.