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Red root rot disease is a devastating fungal disease of rubber trees caused by Ganoderma pseudoferreum (Wakef). Biocontrols using beneficial microorganisms are safe and sustainable. We isolated a DHR18 endophytic bacterium from a healthy rubber tree to obtain a new efficient antagonistic bacterium for red root rot disease affecting rubber trees and evaluated the mechanism of action involved using a double culture assay, genome annotation analysis, and the ethyl acetate extraction method. The results revealed that the DHR18 strain inhibits G. pseudoferreum growth and has broad-spectrum antifungal activity by secreting cell wall hydrolases (proteases and chitinases), indole-3-acetic acid, and siderophores. Furthermore, it fixes nitrogen and is involved in biofilm formation and phosphate solubilisation, improving disease resistance and tree growth. The results showed that the antifungal substances secreted by DHR18 are mainly lipopeptides. Simultaneously, DHR18 enhanced the rubber tree resistance to G. pseudoferreum by increasing the activities of defence enzymes superoxide dismutase, phenylalanine ammonia lyase, peroxidase, catalase, and polyphenol oxidase. The results indicate that B. arboris DHR18 has biocontrol potential and could be used as a candidate strain for the control of red root rot disease in rubber trees. [ABSTRACT FROM AUTHOR]

Acoustic graphene plasmons (GPs) exhibit an exceptional density of electromagnetic states within the mid-infrared (MIR) and terahertz frequency ranges, leading to a pronounced near-field amplification and localization at the nanometer scale. This characteristic renders them highly promising for the development of ultra-sensitive plasmon-enhanced MIR sensing and spectroscopic applications. However, the tight spatial confinement inherent to acoustic GPs results in a significant momentum mismatch, which in turn leads to poor coupling efficiency with light in free space. To overcome this limitation, we leverage numerical simulations to show that GPs can act as an intermediary to facilitate efficient excitation of acoustic GPs by incident MIR radiation, achieving an extinction spectrum peak value of approximately 0.9. The proposed gas sensor based on the acoustic GP resonator is composed of pristine, large-area graphene, an array of periodic metal nanocubes, and a slender polyethylenimine (PEI) layer that adsorbs CO2, situated between the nanocubes and the graphene sheet. The sensing performance of the proposed sensor is numerically investigated. It is demonstrated that by incorporating a CO2-absorbing material into the acoustic GPs, we can perform highly sensitive assessments of the absorption bands within the PEI layer upon CO2 adsorption. The observed behavior of the acoustic GPs indicates a weakening and broadening with increasing CO2 concentrations, a phenomenon attributed to the alteration in the permittivity of the PEI in the interstitial layer due to CO2 adsorption. Numerical simulation results indicate that the sensitivity of the proposed hybrid gas sensor can reach up to 0.0183% ppm−1, which offers a remarkable 95-fold enhancement over the gas sensor based on graphene nanoribbons. Our findings underscore the potential of acoustic GP nanoresonators as a transformative platform for ultrasensitive plasmon-enhanced sensing applications, particularly when integrated with various gas adsorption layers or molecular agents. [ABSTRACT FROM AUTHOR]

The current research mainly focuses on the influence of different voltage forms on partial discharge for the interturn insulation of a transformer, and the discharge characteristics and its mechanism of interturn insulation under the action of preload are unclear. Therefore, a partial discharge test platform under the synergistic action of preloading force and electrical stress is constructed based on the actual operation conditions of the interturn insulation of a 750 kV transformer. Then, the partial discharge characteristics and its mechanism is explored by using (OM, SEM, FTIR, XRD, EDS, FEA). It is found that the statistical parameters and damage degree of interturn insulation decrease first and then increase with the increase in preload. Moreover, there is an inflection point at 1000 N. The reason is that the preload causes the deformation of the holes and air gaps between the layers of insulating paper and in the insulating paper. As a result, the contact area and volume of partial discharge are changed, which further changes the characteristics of partial discharge for interturn insulation. This study can provide a reference for the maintenance and structural optimization of 750 kV transformers. [ABSTRACT FROM AUTHOR]

Formation control is a fundamental task in the realm of autonomous multiagent systems. To drive a group of agents to maneuver continuously with the desired formation, this paper studies the finite‐time affine formation control problem with disturbances, input constraints and safety guarantee. A non‐singular terminal sliding mode control (NTSMC) is implemented to achieve finite‐time convergence of all followers to their desired positions. Additionally, an auxiliary system is deployed to address input constraints resulting from the physical properties of the affine formation system. To mitigate the impact of lumped disturbances, a finite‐time disturbance observer (FTDO) is employed to estimate the disturbances and compensate for their effects. Based on FTDO, the auxiliary system and the above NTSMC, a finite‐time robust controller is developed as the nominal controller. By modifying the nominal controllers to comply with safety constraints, control barrier functions are employed to ensure the safety of the formation system in obstacle‐filled environment. Finally, the effectiveness and feasibility of this method are validated through simulations and real‐world experiments. [ABSTRACT FROM AUTHOR]

Due to multidrug resistance and the high risk of recurrence, effective and less toxic alternative pancreatic cancer treatments are urgently needed. Pancreatic cancer cells are highly resistant to apoptosis but sensitive to ferroptosis. In this study, an innovative nanoplatform (AsIr@PDA) was developed by electrostatic adsorption of a cationic iridium complex (IrFN) onto two‐dimensional (2D) arsenene nanosheets. This nanoplatform exhibits superior ferroptosis‐inducing effects with high drug loading capacity and, importantly, excellent anti‐cancer immune activation function, leading to efficient elimination of pancreatic tumors with no observable side effects. Interestingly, AsIr@PDA significantly prevents the recurrence of pancreatic cancer in vivo when compared with a cisplatin‐loaded nanoplatform. This designed nanoplatform demonstrated superior therapeutic efficacy by synergistic ferroptosis‐induced chemotherapy with immunotherapy via an all‐in‐one strategy, providing new insights for future pancreatic cancer therapy. [ABSTRACT FROM AUTHOR]

The ability to accurately predict the rheological behavior of the blends of two incompatible polymers is critical to the polymer industry. The constitutive modeling of incompatible polymer blends requires understanding the structure and dynamics of the blends across different length scales. The polydispersity of chain length at the molecular level and nonuniformity of flow field due to dispersed domains at the mesoscopic level present significant challenges to this industrially relevant problem. This work proposes a modeling framework for linear and nonlinear rheology of industrial incompatible polymer blends with sea-island morphology. For the individual components, we adopt the Rolie-Double-Poly model and generate the relaxation spectrum from an optimized molecular weight distribution. We derive a new mixing rule without empirical parameters from the flow field analysis inside and outside the droplets. The phase interface, modeled by an ellipsoidal model, contributes to the apparent rheology only at low shear rates. Our modeling approach is verified by the shear and extensional rheology of eight polymer blends with a broad range of viscosity ratios (0.01–100). We also show that the model has the ability to predict the nonlinear rheological behaviors of incompatible polymer blends with known molecular weight distributions and phase morphology. [ABSTRACT FROM AUTHOR]

Urban street greening, a key component of urban green spaces, significantly impacts residents' physical and mental well-being, contributing substantially to the overall quality and welfare of urban environments. This paper presents a novel framework that integrates street greenery with accessibility, enabling a detailed evaluation of the daily street-level greenery visible to residents. This pioneering approach introduces a new measurement methodology to quantify the quality of urban street greening, providing robust empirical evidence to support its enhancement. This study delves into Nanjing's five districts, employing advanced image semantic segmentation based on machine learning techniques to segment and extract green vegetation from Baidu Street View (BSV) images. Leveraging spatial syntax, it analyzes street network data sourced from OpenStreetMap (OSM) to quantify the accessibility values of individual streets. Subsequent overlay analyses uncover areas characterized by high accessibility but inadequate street greening, underscoring the pressing need for street greening enhancements in highly accessible zones, thereby providing valuable decision-making support for urban planners. Key findings revealed that (1) the green view index (GVI) of sampled points within the study area ranged from 15.79% to 38.17%, with notably better street greening conditions observed in the Xuanwu District; (2) the Yuhua District exhibited comparatively lower pedestrian and commuting accessibility than the Xuanwu District; and (3) approximately 139.62 km of roads in the study area demonstrated good accessibility but lacked sufficient greenery visibility, necessitating immediate improvements in their green landscapes. This research utilizes the potential of novel data and methodologies, along with their practical applications in planning and design practices. Notably, this study integrates street greenery visibility with accessibility to explore, from a human-centered perspective, the tangible benefits of green landscapes. These insights highlight the opportunity for local governments to advance urban planning and design by implementing more human-centered green space policies, ultimately promoting societal equity. [ABSTRACT FROM AUTHOR]

This study addressed the critical role of isolating switches in controlling circuit connections for the stable operation of the substation. Our research introduced an innovative state detection system that utilized depth information guidance, comprising a controllable pan-tilt mechanism, a depth camera, and an industrial computer. The software component employed a two-stage strategy for precise isolating switch detection. Initially, the red green blue with depth (RGB-D) saliency network identified the approximate area of the isolating switch target. Subsequently, a fully connected conditional random field was applied to extract accurate detection results. The real-time state of the isolating switch was determined based on the geometric relationship between its arms. This approach enhanced the accuracy of isolating switch detection, ensuring practical applicability in engineering scenarios. The significance of this research lies in its contribution to advancing isolating switch monitoring through depth information guidance, promoting a more robust and reliable power system. The key improvement is implementing a two-stage strategy, combining RGB-D saliency analysis and conditional random field processing, resulting in enhanced accuracy in isolating switch detection. As validated through extensive experiments, the proposed system's successful application in practical engineering underscores its effectiveness in meeting the accuracy requirements for isolating switch detection and state detection. This innovation holds promise for broader applications in power systems, showcasing its potential to elevate the reliability and efficiency of electrical networks. Code of the proposed system is available at: https://github.com/miaomiao0909/Isolating-Switch-Detection/tree/master. [ABSTRACT FROM AUTHOR]

Natural rubber is an important national strategic and industrial raw material. The leaf anthracnose of rubber trees caused by the Colletotrichum species is one of the important factors restricting the yields of natural rubber. In this study, we isolated and identified strain Bacillus velezensis SF334, which exhibited significant antagonistic activity against both C. australisinense and C. siamense, the dominant species of Colletotrichum causing rubber tree leaf anthracnose in the Hainan province of China, from a pool of 223 bacterial strains. The cell suspensions of SF334 had a significant prevention effect for the leaf anthracnose of rubber trees, with an efficacy of 79.67% against C. siamense and 71.8% against C. australisinense. We demonstrated that SF334 can lead to the lysis of C. australisinense and C. siamense mycelia by causing mycelial expansion, resulting in mycelial rupture and subsequent death. B. velezensis SF334 also harbors some plant probiotic traits, such as secreting siderophore, protease, cellulase, pectinase, and the auxin of indole-3-acetic acid (IAA), and it has broad-spectrum antifungal activity against some important plant pathogenic fungi. The genome combined with comparative genomic analyses indicated that SF334 possesses most genes of the central metabolic and gene clusters of secondary metabolites in B. velezensis strains. To our knowledge, this is the first time a Bacillus velezensis strain has been reported as a promising biocontrol agent against the leaf anthracnose of rubber trees caused by C. siamense and C. australisinense. The results suggest that B. velezensis could be a potential candidate agent for the leaf anthracnose of rubber trees. [ABSTRACT FROM AUTHOR]

In challenging environments, feature-based visual SLAM encounters frequent failures in frame tracking, introducing unknown poses to robotic applications. This paper introduces an immediate approach for recovering untracked camera poses. Through the retrieval of key information from elapsed untracked frames, lost poses are efficiently restored with a short time consumption. Taking account of reconstructed poses and map points during local optimizing, a denser local map is constructed around ambiguous frames to enhance the further SLAM procedure. The proposed method is implemented in a SLAM system, and monocular experiments are conducted on datasets. The experimental results demonstrate that our method can reconstruct the untracked frames in nearly real time, effectively complementing missing segments of the trajectory. Concurrently, the accuracy and robustness for subsequent tracking are improved through the integration of recovered poses and map points. [ABSTRACT FROM AUTHOR]

In response to the absence of standardized work practices, work safety measures, efficient work procedures, and suitable line planning methods for exploring seabed topography using autonomous underwater vehicles (AUVs) equipped with side-scan sonar systems, this paper proposes a design framework for side-scan sonar measurement technology based on AUVs. Detailed research has been conducted on line planning methods that differ significantly from those used in shipborne operations. The new line planning method was developed based on the performance characteristics of AUV equipment, the principles of motion modes, and shipborne side-scan sonar operations. The validity of the line planning method was verified through actual sea experiments using different types of AUVs in various terrains. The experimental results demonstrate that the new survey line planning method is distinct from existing AUV path planning methods and is highly applicable for conducting seabed topography exploration operations. Furthermore, the technical design scheme studied in this article is applicable in different sea areas and ensures the safety, operational efficiency, and data quality of AUVs. It holds significant importance for marine science engineering and practical applications. The article also features an analysis of successful data collected from AUVs equipped with side-scan sonar for conducting seabed topography exploration operations. [ABSTRACT FROM AUTHOR]

Sea level variabilities in the southwest Pacific contribute to the variations of equatorial current bifurcation and the Indonesian Throughflow transport. These processes are closely related to the recharge/discharge of equatorial heat content and dynamic distribution of anthropogenic ocean heating over the Indo-Pacific basin, thus being of profound significance for climate variability and change. Here we identify the major features of seasonal and interannual sea level variabilities in this region, confirming the dominance of the first baroclinic mode in the tropics (contributing 60%–80% of the variances) and higher baroclinic modes in the extratropics (40%–60% of the seasonal variance). Seasonally, except in the western Coral Sea where the Ekman pumping is significant, the wind-driven first-mode baroclinic Rossby waves originating to the east of the date line control the sea level variations over most tropical Pacific regions. In the domain where the 1.5-layer reduced gravity model becomes deficient, the surface heat fluxes dominate, explaining ∼40%–80% of sea level variance. For interannual variability, ∼40%–60% of the variance are El Niño–Southern Oscillation (ENSO) related. The wind-driven Rossby and Kelvin waves east of the date line explain ∼40%–78% of the interannual variance in the tropical Pacific. Outside the tropics, small-scale diffusive processes are presumed critical for interannual variability according to a thermodynamic analysis using an eddy-permitting ocean model simulation. Further process and predictive understandings can be achieved with the coupled climate models properly parameterizing the subgrid-scale processes. [ABSTRACT FROM AUTHOR]

In light of the prevailing approach in which data from side-scan sonar (SSS) from Autonomous Underwater Vehicles (AUVs) are primarily processed and visualized post mission, failing to meet the requirements in terms of timeliness for on-the-fly image acquisition, this paper introduces a novel method for real-time processing and superior imaging of navigation strip data from SSS aboard AUVs. Initially, a comprehensive description of the real-time processing sequence is provided, encompassing the integration of multi-source navigation data using Kalman filtering, and high-pass filtering of attitude and heading data to exclude anomalies, as well as the use of bidirectional filtering techniques within and between pings, ensuring real-time quality control of raw data. In addition, this study adopts the semantic segmentation Unet network for automatic real-time tracking of seafloor lines, devises a real-time correction strategy for radial distortion based on historical echo data, and utilizes the alternating direction multiplier method for real-time noise reduction in strip images. With the combined application of these four pivotal techniques, we adeptly address the primary challenges in real-time navigation data processing. In conclusion, marine tests conducted in Bohai Bay substantiate the efficacy of the methodologies delineated in this research, offering a fresh paradigm for real-time processing and superior visualization of SSS navigation strip data on AUVs. [ABSTRACT FROM AUTHOR]

In recent years, smart homes have garnered extensive attention as a prominent application scenario of IoT technology. However, the unique characteristics of smart homes have brought forth serious security threats, emphasizing the paramount importance of identity authentication and access control. The conventional centralized approach is plagued by the issue of having a "single point of failure," while existing distributed solutions are constrained by limited device resources and the complexities of identity authentication. To tackle these challenges, this paper proposes a smart home authentication and access control model based on decentralized identifiers (DIDs). By leveraging the inherent decentralization of DIDs, which rely on blockchain, a distributed environment is constructed, effectively mitigating the problem of the "single point of failure." In this model, every participant in the smart home system, including users and smart devices, is uniquely identified by DIDs and through the integration of an improved capability-based access control scheme, which streamlines the user identity authentication process, reduces authentication complexity, and enables convenient cross-household access with a single registration. Our experimental results demonstrate that the application of decentralized identifiers provides the model with various security attributes, including confidentiality, integrity, and traceability. Additionally, the model exhibits low time costs for each module, ensuring timely responses to access service requests and incurring lower gas consumption compared to other Ethereum-based methods. Thus, our research proposes a lightweight authentication and access control solution suitable for smart home environments. [ABSTRACT FROM AUTHOR]

Given the lack of systematic research on bathymetric surveys with multi-beam sonar carried by autonomous underwater vehicles (AUVs) in unfamiliar waters, this paper proposes a method for multi-beam bathymetric surveys based on the constant-depth mode of AUVs, considering equipment safety, operational efficiency, and data quality. Firstly, basic principles for multi-beam bathymetric surveys under the constant-depth mode are proposed based on multi-beam operational standards and AUV constant-depth mode characteristics. Secondly, a vertical effective height model for the vehicle is established, providing vertical constraints and a basis for determining fixed depth in constant-depth missions. Subsequently, according to these basic principles and the vertical effective height model, the operational process for multi-beam bathymetric surveys in unfamiliar waters under the AUV constant-depth mode is outlined. Finally, we validate the proposed method through sea trials in the Xisha Sea of the South China Sea. The test results show that the method proposed in this paper not only ensures the vehicle safety operation and multi-beam data quality, but also improves the operation efficiency by about 68%, demonstrating the reliability of the proposed method and its significant engineering value and guidance implications. [ABSTRACT FROM AUTHOR]