Search Results (189)

Swarm control technology, leveraging artificial intelligence algorithms to coordinate multiple devices, offers an effective solution for developing precision and intelligent operation systems in orchard management. This paper focuses on the core technologies underpinning swarm coordination and reviews the current state of research on collaborative communication, path planning, task allocation, and formation control, with reference to both domestic and international studies. Based on the full growth cycle of fruit trees, encompassing monitoring, precision management, and harvesting, the paper summarizes the applications and research progress of swarm control technology at each stage. Furthermore, it identifies key challenges in applying swarm technology to orchard environments, including low efficiency in heterogeneous system coordination, delayed responses to dynamic conditions, resource constraints in large-scale swarm systems, and limited adaptability to agricultural contexts, and offers strategic recommendations to address these limitations. Full article

Intestinal exposure and ocular opacity occur in cultured hybrid porcupinefish, but the associated pathological lesions and gut microecological changes remain poorly characterized. Hybrid porcupinefish were assigned to a healthy control group (CT-CD-JK), an intestinal exposure group (CT-CD-FB), or an ocular opacity group (CT-YQ-FB). Gut microbiota, histopathology, cultivable bacteria, and antimicrobial susceptibility were assessed using 16S rRNA sequencing, hematoxylin and eosin (H&E) staining, bacterial isolation and identification, and disk diffusion testing. Diseased fish showed evident intestinal and ocular tissue injury. Microbial richness was reduced in the CT-CD-FB group, and gut microbial community structure differed among groups (permutational multivariate analysis of variance [PERMANOVA], R² = 0.5058, p = 0.001). At the phylum level, Firmicutes increased in the CT-CD-FB group, whereas Proteobacteria accounted for a higher proportion in the CT-CD-JK group. Linear discriminant analysis effect size (LEfSe) further indicated group-specific enrichment patterns. A total of 23 cultivable isolates were obtained, among which isolates assigned as putative Vibrio harveyi based on 16S rRNA sequence alignment accounted for 90.9% of isolates derived from intestinal contents in the CT-CD-FB group, which was higher than the 16.7% observed in the CT-CD-JK group. Antimicrobial susceptibility testing suggested a potential multidrug-resistance risk among the isolates; however, higher proportions of susceptible (S) isolates were observed for ceftriaxone (CTR), quinolones, aminoglycosides, and chloramphenicol (C). These preliminary findings suggest that gut dysbiosis, intestinal tissue injury, and a higher detection proportion of putative Vibrio harveyi were associated with intestinal exposure in this small cohort of naturally diseased hybrid porcupinefish, providing a basis for subsequent pathogen-verification studies and antimicrobial-susceptibility assessment. Full article

The large-scale integration of renewable energy has significantly improved the low-carbon performance of power systems, but has also increased operational uncertainty. Under extreme weather conditions, wind and solar power may experience consecutive days of simultaneous output shortfalls—referred to as “renewable energy drought”—leading to persistently high net load and severe challenges to supply guarantee. To address this issue, this paper proposes a multi-source coordinated supply-guarantee dispatch strategy for consecutive-day renewable energy drought scenarios. First, net load is defined as the total system load minus the available wind and solar output. Based on magnitude and duration thresholds, renewable energy drought events are extracted from historical data to generate representative scarcity scenarios. Second, a multi-source coordinated optimization dispatch model is constructed, incorporating wind power, solar power, thermal units, battery energy storage, and pumped-storage hydro. The objective is to minimize the total system operating cost, which includes thermal fuel cost, start-up/shut-down costs, storage cycling cost, wind/solar curtailment penalty cost, and load shedding penalty cost. The load shedding penalty coefficient is set to a magnitude much higher than conventional costs to highlight the priority of supply guarantee. The model accounts for operational constraints such as minimum up/down times, deep regulation capability, ramping limits of thermal units, and charge/discharge power limits of storage. Taking a provincial power system in China for the year 2030 as a case study, a dispatch case covering four consecutive days (96 time periods) is designed. Based on a baseline scenario, eight groups of sensitivity analyses are conducted to comprehensively investigate the impacts of key factors on the supply-guarantee strategy, including: the minimum up/down time of thermal units, deep regulation capability, load shedding penalty cost, load level, rated energy capacity and charge/discharge efficiency of battery energy storage, rated energy capacity and pumping/generating efficiency of pumped-storage hydro, thermal fuel cost coefficient, and renewable energy capacity. Simulation results show that the proposed strategy can effectively coordinate multiple resources under consecutive-day drought conditions; reducing the minimum up/down time of thermal units improves supply flexibility but increases start-up/shut-down costs; enhancing deep regulation capability optimizes storage utilization and reduces total system cost; the load shedding penalty cost directly determines the trade-off between supply guarantee and economic efficiency; and as load level decreases by 5%, 10%, and 15%, the total system operating cost reduces by approximately 6.3%, 12.5%, and 18.8%, respectively. This study provides a quantitative method and technical support for supply-guarantee dispatch decisions and resource allocation in high-renewable power systems under persistent drought conditions. Full article

On-orbit absolute radiometric calibration tracks sensor radiometric degradation and ensures accuracy for quantitative applications. Low-cost commercial satellites lack expensive on-board calibration systems, and traditional alternative methods cannot achieve automated, reliable calibration for large sensor fleets with low resource consumption. Pseudo-invariant calibration sites require no ground instruments, but commercial satellites’ heavy imaging schedules hinder frequent PICS observations. The Jilin-1 constellation is a large commercial constellation composed of satellites carrying multispectral imagers with resolution better than 1 m, and it has no on-board calibration system. Thus, an automated calibration method applicable to numerous imagers is needed, one that requires widely available clear-sky ground targets. Using MCD43A2 and MCD12Q1 products, we generate calibration region vectors to transfer the MODIS radiometric reference to Jilin-1. A look-up table (LUT) is constructed for the input parameters of the MODTRAN model. Calibration pixels and model input parameters are then extracted from Jilin-1 imagery using the region vectors, the LUT is interpolated to obtain the at-aperture radiance for each pixel and band, and on-orbit absolute radiometric calibration coefficients are calculated. The proposed method requires no ground-based synchronous experiments, achieves a high level of automation, and does not consume commercial imaging resources. The site calibration validation based on RadCalNet for the JL1GF02F PMS1 sensor shows that the maximum relative difference in the method across all bands is less than 4%. Full article

The PIN-LIKES (PILS) gene family is crucial for regulating auxin homeostasis and stress adaptation in plants; nevertheless, a comprehensive study on this family in alfalfa (Medicago sativa) remains insufficient. This research found 46 MsPILS genes within the tetraploid alfalfa genome and categorized them into four subfamilies. The genes are irregularly allocated throughout 16 chromosomes, with tandem duplications acting as a primary catalyst for family expansion. Analysis indicated that all MsPILS proteins contain the conserved Mem_trans domain. The promoter study revealed that MsPILS genes had many cis-elements that respond to abiotic stressors and hormones. qRT-PCR research indicated that MsPILS genes exhibit variable expression across several tissues and respond to multiple abiotic stressors. Protein–protein interaction (PPI) research revealed PIN3, PIN5, and PIN6 as principal interacting partners of the MsPILS proteins. Subcellular localization studies indicated that MsPILS1c is in the nucleus, plasma membrane, and endoplasmic reticulum (ER). This research offers significant genetic resources and a theoretical framework for elucidating the activities of PILS genes and for molecular breeding aimed at improving stress tolerance in alfalfa. Full article

With the acceleration of industrialization, water pollution caused by ammonia-nitrogen compounds has become a severe environmental challenge. In recent years, significant breakthroughs in biological nitrogen removal technology have been achieved alongside the discovery of novel ammonia-nitrogen-degrading bacterial strains. This study delves into the metabolic pathways and molecular mechanisms of ammonia-nitrogen degradation by Gordonia sp. TD-46. A comprehensive understanding of the strain’s nitrogen metabolic pathways and the functions of key genes was achieved by optimizing its ammonia-nitrogen degradation conditions, analyzing its whole-genome sequence, and conducting heterologous expression of crucial genes. The results demonstrated that when ammonium chloride served as the nitrogen source, sodium acetate as the carbon source, with a C/N ratio of 25, pH of 7, and an inoculum size of 15%, the strain achieved an ammonia-nitrogen degradation rate exceeding 80% under these conditions. Whole-genome sequencing analysis identified genes involved in nitrogen metabolism, including glnA, gdhA, narB, narGHI, nirBD, and nasBDE. These genes indicate that the nitrogen metabolism pathway of strain TD 46 follows the assimilatory nitrate reduction pathway (NO₃⁻ → NO₂⁻ → NH₄⁺) and the ammonia assimilation pathway (NH₄⁺ → Gln → Glu). Thus, strain TD-46 is capable of efficient nitrogen assimilation. Full article

With the continuous development of complex marine hydrocarbon reservoirs, broadband seismic data have shown growing advantages in revealing abundant stratigraphic information. Affected by acquisition conditions and stratigraphic attenuation, the acquired seismic data commonly suffer from narrow bandwidth, and conventional broadband processing techniques are incapable of optimizing the overall frequency band. This study proposes a coordinated high- and low-frequency broadband compensation method based on adaptive weight fusion to effectively extend the frequency bandwidth of seismic data. Firstly, wavefield separation is used to suppress ghost reflections, compensate low-frequency effective signals, and restore the continuity of the low-frequency spectrum. Then, based on the spectrum extrapolation method of maximum entropy spectrum estimation, a spectrum prediction model is established to achieve the continuation of high-frequency effective signals. Finally, in combination with the signal-to-noise ratio of each frequency band, the adaptive weight fusion algorithm is applied for weighted summation. The acquired broadband seismic data feature a continuous spectrum and balanced energy, greatly improving seismic imaging quality. Comparative results obtained using conventional processing methods verify that the proposed method can significantly improve stratigraphic continuity and wave group characteristics. Full article

Spaceborne interrupted frequency-modulated continuous-wave synthetic aperture radar (iFMCW SAR) employs a single antenna on a single spacecraft operating in a time-division transmit/receive mode, effectively avoiding mutual interference between transmitted and received signals and thereby overturning the design paradigm of spaceborne FMCW SAR systems. However, the periodic switching of the antenna between transmit and receive states results in periodic data gaps along the azimuth direction in the echo signal, leading to spurious artifacts in the reconstructed images and severely degrading image quality. Sparse signal recovery techniques based on compressive sensing models have been shown to effectively suppress such spurious targets. Nevertheless, the generalized orthogonal matching pursuit (GOMP) algorithm requires prior knowledge of the signal sparsity, a condition that is often impractical in real-world scenarios. To address this limitation, this paper investigates the variation pattern of the residual norm with respect to sparsity in the GOMP algorithm and proposes a modified GOMP algorithm based on binary search. This approach enables rapid and accurate determination of the true sparsity level without prior knowledge, thereby achieving sparsity-adaptive reconstruction with GOMP and significantly enhancing the imaging quality of iFMCW SAR. Simulation experiments involving both point and scene targets are provided to demonstrate the effectiveness and potential of the proposed algorithms for practical applications. Full article

Aging has a significant influence on the rheological behavior and service performance of asphalt binders. In this study, base asphalt binder (BAB) and rubberized asphalt binder (RAB) with different aging levels were investigated to clarify their aging evolution and performance correlations. Rheological tests were conducted to evaluate high-temperature rutting resistance, intermediate-temperature fatigue performance, and low-temperature cracking resistance. The 2S2P1D viscoelastic model was used to analyze the evolution of viscoelastic parameters, while gel permeation chromatography (GPC) was adopted to characterize molecular weight changes during aging. The results showed that aging increased the rutting resistance of both binders, but reduced fatigue performance and low-temperature cracking resistance. Among the 2S2P1D viscoelastic model parameters, G_∞, δ, and β were more sensitive to aging than the other parameters and exhibited relatively clear variation trends. Selected viscoelastic parameters also showed significant correlations with rheological performance indices. GPC results indicated that both binder systems progressively evolved toward higher molecular weight during aging, with the molecular weight distribution curves shifting toward the high-molecular-weight region. For RAB, M_w was more sensitive to aging than M_n and showed some fluctuation at intermediate aging stages, reflecting a more complex molecular evolution. Overall, the results indicate that selected 2S2P1D viscoelastic parameters can serve as sensitive indicators of aging evolution and provide a useful basis for interpreting the performance correlations and rheological changes of asphalt binders from a viscoelastic perspective. Full article

Under alkaline conditions, most commonly used preservatives exhibit limited efficacy and fail to meet the preservation requirements of coated tofu. This study aims to investigate the effects of metal-phenolic networks (MPNs) on quality deterioration, protein oxidation, conformation, and gel microstructure of coated tofu during cold storage (4 °C and 10 °C). The results showed that, compared with the untreated control group, MPNs treatment effectively inhibited protein oxidation, alleviated quality deterioration, delayed the degradation of color and texture, and reduced protein degradation, as evidenced by soluble protein contents that were 63.55% (4 °C) and 66.65% (10 °C) lower than those of the control group after 20 days of storage. MPNs treatment also improved the orderliness and stability of the protein secondary structure. In addition, electrophoretic analysis showed that MPNs markedly retarded the decline in band optical density of the 11S protein A subunit by 96.19% and 97.28% at 4 °C and 10 °C, respectively, and suppressed the increase in the B subunit by 13.28% and 73.20%, respectively. Moreover, MPNs treatment helped maintain a more compact gel network. Based on physicochemical characterization and Pearson correlation analysis, the preservative effect of MPNs on coated tofu under alkaline conditions was elucidated, revealing the internal correlation between the inhibition of quality deterioration and the regulation of protein oxidation. Specifically, MPNs mitigate protein disulfide bond loss, increase the β-sheet content, preserve the natural protein conformation and the relative proportion of 11S subunits, stabilize the gel microstructure, and thereby achieve quality preservation. These findings provide theoretical support and strategic reference for the development of preservation technologies for alkaline high-protein gel foods. Full article

Mobile robot path planning in complex environments remains challenging due to obstacle constraints, high-dimensional search space, and the need to balance path optimality and safety. To address these challenges, this paper proposes an improved Red-Billed Blue Magpie Optimizer (IRBMO) with multi-strategy cooperation. Specifically, a territorial awareness mechanism enhances global exploration to avoid premature path convergence, a representative individual learning strategy improves exploitation to refine path quality, and a random subpopulation diffusion strategy helps escape local optima in complex obstacle environments. The proposed method is applied to grid-based path planning problems with different map sizes and obstacle densities. Experimental results show that IRBMO significantly reduces path length compared with other algorithms, while achieving faster convergence and better stability. Parameter sensitivity analysis, ablation study, and convergence analysis further verify the effectiveness of the proposed strategies. In addition, benchmark tests on CEC2017 and CEC2022 functions against 19 competitors further confirm its optimization capability. Overall, IRBMO provides an effective and robust solution for robot path planning problems. Full article

This work numerically reveals a novel strategy to modulate two ionic conductance state in a nanochannel via pressure-dependent fluidic motion inside the channel. Steady and transient simulations based on Poisson–Nernst–Planck–Stokes equations demonstrate that the two states with distinct ionic conductance and ion selectivity can be reversibly switched by external pressure, with a characteristic time of ~100 μs. Furthermore, the two conductance states are found to depend on the transversal electric field, which gives rise to two distinct intrachannel fluidic flow patterns, namely laminar flow and vortex flow, respectively. This finding suggests the potential of pressure-controlled ionic conductance switching for applications in nanofluidic ionic circuits, flow-regulated sensing, and integrated micro/nanoscale devices. It also provides insights into nonlinear ionic current–voltage behaviors. Full article

Accurate precipitation nowcasting plays an important role in disaster prevention and hydrometeorological applications, yet it remains highly challenging due to the complex spatiotemporal variability and multi-scale structural characteristics of precipitation systems. Existing deep learning methods are largely data-driven and often struggle to effectively exploit multi-source observations or learn physically meaningful representations. To address these limitations, this study proposes a Multi-Scale Frequency–Temporal Network (MS-FTNet) for precipitation nowcasting. The framework leverages Fourier transform-based frequency-domain modeling to achieve an interpretable multi-scale decomposition of precipitation dynamics. Specifically, low-frequency components capture large-scale stratiform patterns and their temporal evolution, while high-frequency components represent localized convective structures and abrupt variations. Building on this, a Global Feature Collaboration (GFC) module integrates global frequency-domain representations with multi-scale convolutional features, and an Adaptive Temporal Fusion (ATF) module enhances temporal dependency modeling. Experiments on the SEVIR dataset demonstrate that MS-FTNet consistently outperforms representative baseline models in terms of MSE, CSI, and LPIPS, particularly for heavy precipitation events and longer forecast lead times. Full article

Immune-mediated inflammatory diseases, such as rheumatoid arthritis, multiple sclerosis, and systemic lupus erythematosus, impose a severe and growing global health burden, where current therapies are limited by poor specificity and significant side effects. The peptidylarginine deiminase (PAD)/citrullination axis, in which protein citrullination catalyzed by PADs drives autoantigen generation and sustains inflammation, has emerged as a critical therapeutic target. This review outlines a comprehensive strategy for targeting this axis using natural products. We first detail the established role of natural compounds as direct PAD inhibitors, covering their chemical diversity, inhibitory mechanisms, and therapeutic applications in disease models. Subsequently, the discussion extends to their broader, indirect modulatory functions, highlighting how these compounds can suppress pathogenic citrullination by regulating upstream processes like NETosis and inflammatory signaling. Furthermore, the review introduces the innovative substrate-centric intervention strategy, which represents a paradigm shift toward shielding key arginine residues on autoantigens, thereby preventing the formation of immunogenic neoepitopes. The translational challenges and future directions for each of these avenues are outlined, addressing persistent obstacles including achieving isoform selectivity and biomarker validation. By integrating these multifaceted strategies, from direct inhibition and indirect modulation to substrate protection, this work provides a strategic roadmap for advancing the next generation of more precise, effective, and safe anti-citrullination therapies, ultimately moving beyond conventional enzyme inhibition toward targeted immunomodulation in immune-mediated inflammatory diseases. Full article

Munronia pinnata (Meliaceae), a medicinal plant used in Zhuang traditional medicine, is recognized as a rich source of structurally diverse limonoids. In our continuing investigation of bioactive constituents from Guangxi medicinal plants, four new prieurianin-type limonoids, munropins G–J (1–4), were isolated from their aerial parts. Their structures were determined through comprehensive spectroscopic analysis, including nuclear magnetic resonance and high-resolution mass spectrometry, and further supported by quantum chemical calculations for electronic circular dichroism and statistical probability analysis. Munropins G (1) and H (2) feature an unprecedented C-12 β-D-glucosylated α-methyl-2′-hydroxypentanoate side chain and a C-17 β-substituted furan ring, with 1 being the 7-O-acetyl derivative of 2. Munropins I (3) and J (4) possess a formyl group at C-11, a 3-methyl-2-hydroxypentanoate ester at C-12, and a C-17 γ-hydroxy-α,β-unsaturated γ-lactone unit (21-hydroxy for 3, 23-hydroxy for 4), each existing as an equilibrating mixture of C-21 epimers—a phenomenon observed for the first time within a prieurianin-type framework. The absolute configurations of 1 and 2 were established by quantum chemical electronic circular dichroism calculations, while those of 3 and 4 remain to be assigned. All compounds were evaluated for cytotoxicity against human lung (A549), liver (HepG2), breast (MCF-7), and colon (HCT116) cancer cell lines and for anti-inflammatory activity in lipopolysaccharide-induced RAW 264.7 murine macrophages, but none exhibited significant effects at a concentration of 80 μM. This study expands the chemical diversity of Munronia limonoids and provides new molecular scaffolds for future structure–activity relationship investigations and chemotaxonomic markers for the Meliaceae family. Full article