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Abstract For the ship motion with large inertia coupled system identification modeling inaccuracy, the ship scale effect and the existence of partial unmeasured ship data problems. In this paper, an auxiliary model nonlinear innovation least squares identification algorithm is proposed. The new algorithm uses the output of the auxiliary model instead of the unmeasurable variables in the full-scale test data of the ship, and optimizes the error using the tangent function. Compared with the existing algorithm, the error of the improved algorithm decreases with the increase of time and continuously approaches to zero, which greatly improves the identification accuracy and convergence efficiency. The results show that the improved algorithm has significant identification accuracy and reliability. The identification method designed in this paper can be applied to the field of ship intelligent navigation engineering.

ABSTRACT Fusarium oxysporum f. sp. cubense (Foc) poses a significant threat to banana crops as a lethal fungal pathogen. The global spread of Foc underscores the formidable challenges associated with traditional management methods in combating this pathogen. This study delves into the hypovirulence-associated mycovirus in Foc. From Foc strain LA6, we isolated and characterized a novel member of the Hadakaviridae family, named Hadaka virus 1 strain LA6 (HadV1-LA6). HadV1-LA6 comprises 10 genomic RNA segments, with RNA1 to RNA7 sharing 80.9%–95.0% amino acid sequence identity with known HadV1-7n, while RNA8 to RNA10 display significantly lower identity. HadV1-LA6 demonstrates horizontal transmission capabilities in an all-or-none fashion between different Foc strains via coculturing. Phenotypic comparisons highlight that HadV1-LA6 significantly reduces the growth rates of its host fungus under cell wall stress and oxidative stress conditions. Importantly, HadV1-LA6 attenuates Foc’s virulence in detached leaves and banana plants. This study represents the first introduction of a novel hypovirulence-associated Hadaka virus 1 in Foc.IMPORTANCEFusarium wilt of banana (FWB) is a severe fungal disease caused by soil-borne Fusarium oxysporum f. sp. cubense (Foc). Among various strategies, biocontrol emerges as a safe, ecologically friendly, and cost-effective approach to managing FWB. In this study, we focus on exploring the potential of a novel hypovirulent member of hadakavirid, HadV1-LA6. Previous reports suggest that HadV1 shows no apparent effect on the host. However, through phenotypic assessments, we demonstrate that HadV1-LA6 significantly impedes the growth rates of its host fungus under stress conditions. More importantly, HadV1-LA6 exhibits a remarkable capacity to attenuate Foc’s virulence in detached leaves and banana plants. Furthermore, HadV1-LA6 could be horizontally transmitted between different Foc strains, presenting a promising resource for revealing the molecular mechanism of the interaction between Hadaka virus 1 and its host.

Integrons are genetic components that are critically involved in bacterial evolution and antimicrobial resistance by assisting in the propagation and expression of gene cassettes. In recent decades, biochar has been introduced as a fertilizer to enhance physiochemical properties and crop yield of soil, while manure has been used as a fertilizer for centuries. The current study aimed to investigate the impact of biochar, manure, and a combination of biochar and manure on integrons, their gene cassettes, and relative antimicrobial resistance in paddy soil. Field experiments revealed class 1 (CL1) integrons were prevalent in all samples, with higher concentration and abundance in manure-treated plots than in biochar-treated ones. The gene cassette arrays in the paddy featured a broad pool of cassettes with a total of 35% novel gene cassettes. A majority of gene cassettes encoded resistance to aminoglycosides, heat shock protein, heavy metals, pilus secretory proteins, and twin-arginine translocases (Tat), TatA, TatB, and TatC. Both in combination and solo treatments, the diversity of gene cassettes was increased in the manure-enriched soil, however, biochar reduced the gene cassettes’ diversity and their cassettes array. Manure considerably enhanced CL1 integrons abundance and antimicrobial resistance, whereas biochar amendments significantly reduced integrons and antimicrobial resistance. The results highlighted the differential effects of biochar and manure on integrons and its gene cassette arrays, showing increased abundance of integrons and antibiotic resistance upon manure application and decrease of the same with biochar. The use of biochar alone or in combination with manure could be a beneficial alternative to mitigate the spread of antimicrobial resistance and bacterial evolution in the environment, specifically in paddy soils.

Long landing hazardous events (long landings) are regarded as the most common unsafe events during an aircraft’s landing phase and are significantly influenced by pilots’ leveling operations. This paper proposes a pre-warning method for long aircraft landings based on operation characteristics clustering to better prevent the occurrence of long landing events and develop pre-warning technology for long aircraft landings applicable to actual civil aviation aircraft operations. Based on the quick access recorder (QAR) flight data of a Boeing B737-800 fleet, the Gaussian mixture model (GMM) clustering method was employed to cluster, group, analyze, and evaluate the pilot operation characteristics utilizing the relative indicators of aircraft speed in the takeoff and landing phases as the measurement indices. Moreover, a long landing pre-warning model was developed based on the eXtreme Gradient Boosting (XGBoost) algorithm to account for the overall characteristics of various operations. The complete accuracy, recall ratio, and precision of the long landing pre-warning method based on pilot operation characteristics clustering reached 89.66%, 89.16%, and 92.50%, respectively, in the test of the pre-warning model, demonstrating a significant improvement over those of the pre-warning model without considering the operation characteristics and presenting a more effective pre-warning effect. Optimizing the long landing pre-warning model with pilot operation characteristics can effectively improve the model’s pre-warning capabilities, assist the crew in making accurate decisions, and prevent unsafe events during aircraft landing.

For the first time, a nanobiosensor was established for Sorghum mosaic virus (SrMV) detection. The biosensor consists of cadmium telluride quantum dots (CdTe QDs) conjugated to the specific antibody (Ab) against SrMV coat protein (CP) and carbon quantum dots (C QDs) labeled with SrMV coat protein. The formation of the fluorophore-quencher immunocomplex CdTe QDs-Ab+C QDs-CP led to a distinct decrease in the fluorescence intensity of CdTe QDs. Conversely, the emission intensity of CdTe QDs recovered upon the introduction of unlabeled CP. The developed biosensor showed a limit of detection of 44 nM in a linear range of 0.10–0.54 μM and exhibited the strongest fluorescence intensity (about 47,000 a.u.) at 552 nm. This strategy was applied to detect purified CP in plant sap successfully with a recovery rate between 93–103%. Moreover, the feasibility of the proposed method was further verified by the detection of field samples, and the results were consistent with an enzyme-linked immunosorbent assay (ELISA). Contrarily to ELISA, the proposed biosensor did not require excessive washing and incubation steps, thus the detection could be rapidly accomplished in a few minutes. The high sensitivity and short assay time of this designed biosensor demonstrated its potential application in situ and rapid detection. In addition, the fluorescence quenching of CdTe QDs was attributed to dynamic quenching according to the Stern-Volmer equation.

A new elevated-temperature high-strength Mg−4Er−2Y−3Zn−0.4Mn (wt %) alloy was developed by semi-continuous casting, solid solution treatment, and hot extrusion. W phase (Mg3(Er,Y)2Zn3) with fcc structure, long period stacking ordered phases with 18R (Mg10(Er,Y)1Zn1) and 14H (Mg12(Er,Y)1Zn1) structures, and basal plane stacking faults (SFs) was formed in the as-cast alloy, mainly due to the alloy component of (Er + Y)/Zn = 1:1 and Er/Y = 1:1 (at %). After solid solution treatment and hot extrusion, the novel microstructure feature formed in as-extruded alloy is the high number-density nanospaced basal plane SFs throughout all the dynamically recrystallized (DRXed) and un-DRXed grains, which has not been previously reported. The as-extruded alloy exhibits superior tensile properties from room temperature to 300 °C. The tensile yield strength can be maintained above 250 MPa at 300 °C. The excellent elevated-temperature strength is mainly ascribed to the formation of nanospaced basal plane SFs throughout the whole Mg matrix, fine DRXed grains ~2 μm in size, and strongly basal-textured un-DRXed grains with profuse substructures. The results provide new opportunities for the development of deformed Mg alloys with satisfactory mechanical properties for high-temperature services.

Autonomous underwater vehicles (AUVs) are widely used, but it is a tough challenge to guarantee the underwater location accuracy of AUVs. In this paper, a novel method is proposed to improve the accuracy of vision-based localization systems in feature-poor underwater environments. The traditional stereo visual simultaneous localization and mapping (SLAM) algorithm, which relies on the detection of tracking features, is used to estimate the position of the camera and establish a map of the environment. However, it is hard to find enough reliable point features in underwater environments and thus the performance of the algorithm is reduced. A stereo point and line SLAM (PL-SLAM) algorithm for localization, which utilizes point and line information simultaneously, was investigated in this study to resolve the problem. Experiments with an AR-marker (Augmented Reality-marker) were carried out to validate the accuracy and effect of the investigated algorithm.