Search Results (237)

Coordinated swarms of low-cost commercial unmanned aerial vehicles (UAVs) pose a growing security threat to civil infrastructure, public events, and restricted airspace. Effective counter-UAV defense requires the real-time, cooperative scheduling of heterogeneous directed-energy systems, where high-energy lasers provide precise single-target engagement and high-power microwaves provide wide-area suppression. To address this threat, we formulate the defensive scheduling problem as a partially observable Markov game and propose the Heterogeneous Dual-Graph Multi-Agent Actor–Critic (HDG-MAAC). HDG-MAAC employs two graphs: a fixed-size local graph encoded by a graph attention network (GAT) actor for decentralized threat selection and a shared global graph with three semantic edge types encoded by a graph convolutional network (GCN) critic for stable credit assignment. This asymmetric design is tailored to decision-making and evaluation, respectively. In a two-system, four-target simulation benchmark with direct, zig-zag, and feint maneuver patterns, HDG-MAAC converges stably across eight seeds, with a final-stage return of $33.6\pm 4.0$, and neutralizes $2.79\pm 0.26$ targets over 1000 deterministic episodes, outperforming DDPG (2.20), MADDPG (2.13), and H2G-MAAC (1.64) with $p<0.01$. In analytically tractable geometric scenarios, the rule-based scheduler with exact geometric pointing still yields more raw interceptions. The learning method’s contribution is therefore limited to training stability, interpretability, and applicability beyond such scenarios, rather than the raw interception count. Ablation studies indicate that this robustness originates from the GCN critic, whose contribution lies in training stability rather than in raising the final performance ceiling. An attention analysis yields an overall target association rate of 42.0%, with 47.7% and 47.1% for direct and zig-zag maneuvers, respectively, compared to a 25% chance baseline, as well as a drop to 27.1% under feints. Without an explicit coordination reward, coordinated target convergence emerges in 34% of firing frames. HDG-MAAC provides a stable and interpretable decision support framework for civil security operators safeguarding public infrastructure from rogue drone groups. The framework is intended solely for protective civilian use, with responsible use considerations. Full article

African swine fever virus (ASFV) is a highly pathogenic agent that poses a severe threat to the global swine industry. The biological function of A859L, an ASFV-encoded RNA helicase, remains largely elusive. Here, we show that A859L is highly conserved across diverse ASFV isolates and belongs to the SF2 superfamily of RNA helicases, possessing characteristic Walker A (GKT) and Walker B (DECH) motifs. Transcriptomic profiling at multiple time points post-infection further revealed that A859L is a late-expressed gene. Functional assays demonstrated that siRNA-mediated knockdown of A859L significantly inhibited progeny virus production in both susceptible macrophages (PAMs and BMDMs) and WSL cells. This knockdown also markedly reduced the expression of viral proteins p30 and p72, as well as the intracellular mRNA levels of other viral helicase genes (QP509L, Q706L, D1133L, and B962L), underscoring the vital role of A859L in the viral life cycle. Conversely, A859L overexpression enhanced viral propagation. Notably, pharmacological inhibition of viral helicase activity effectively suppressed ASFV replication. Collectively, our data establish A859L as a critical determinant of ASFV replication and a promising candidate for antiviral development. Full article

Compared to conventional fuels, hydrogen fuel offers advantages such as high specific heat capacity, low boiling point, and zero carbon emissions, demonstrating significant potential for green energy conservation and sustainable development in the aviation field. This paper reviewed the latest advances, technical challenges, research hotspots, and future development directions related to the response and regulation of various components within the hydrogen transportation and thermal management systems for aeroengines, filling a gap in the existing literature. (1) As to the fuel of aeroengines, the heat exchanger efficiency of the heat exchanger employed for intercooling while utilizing hydrogen fuel can reach 10.63 times that of kerosene, and the turbine inlet temperature is significantly reduced under sea-level takeoff conditions. Under high-altitude supersonic flight conditions, its specific fuel consumption is approximately 0.33–0.40 times that of kerosene. However, aeroengines also confront challenges such as the requirement for high-efficiency thermal insulation and the control of cold energy losses. (2) When the pressure regulation accuracy of hydrogen storage containers, hydrogen supply stability, and thermal management coordination are ensured, the fuel weight index can be optimized to 0.62 during hydrogen transportation, significantly reducing the impact of the hydrogen storage system on the payload capacity of aircraft models. Nevertheless, crucial components involved in hydrogen transportation, such as cryogenic liquid hydrogen tanks, are vulnerable to significant temperature fluctuations, which can cause pressure oscillations, response delays, and seal failures, thereby affecting the stability of the hydrogen fuel supply. (3) In the thermal management system of hydrogen-fueled aeroengines, the fuel consumption and transportation cost of the engine compared with the unoptimized baseline system are reduced by 14.54% and 11.74% through regulating important component parameters such as heat exchanger power. However, the thermal management system confronts challenges during the heat exchange among hydrogen fuel, high-temperature airflow, and residual heat, including strong coupling among multiple components and insufficient real-time sensing capability for dynamic thermal loads. Future development should shift from “passive adaptation” to “active regulation and control,” aiming to achieve dynamic decoupling of temperature, pressure, and stress fields under strongly coupled multi-heat source operating conditions, along with coordinated regulation and matching of multi-component dynamic responses. Full article

Arbuscular mycorrhizal fungi (AMF) have been widely recognized for their ability to enhance plant drought tolerance. However, the contribution of improved phosphorus (P) nutrition to AMF-mediated drought tolerance in citrus and its relationship with other physiological processes remain unclear. Here, we investigated the physiological mechanisms underlying AMF-mediated drought tolerance in trifoliate orange (Poncirus trifoliata) by combining AMF inoculation with exogenous phosphorus supplementation under drought stress. AMF inoculation markedly alleviated drought-induced growth inhibition, increased plant biomass, enhanced root and rhizosphere phosphatase activities, promoted phosphorus accumulation, and strongly induced the expression of the mycorrhiza-specific phosphate transporter genes PtaPT4 and PtaPT5. Exogenous phosphorus supplementation largely mimicked the beneficial effects of AMF on plant growth and drought tolerance, indicating that enhanced phosphorus acquisition contributes substantially to AMF-mediated drought tolerance in trifoliate orange. However, the combined application of AMF and exogenous phosphorus conferred greater drought tolerance than phosphorus supplementation alone, suggesting that, in addition to improved phosphorus nutrition, AMF further enhances drought adaptation through the regulation of multiple physiological processes. Furthermore, AMF promoted the accumulation of growth-related phytohormones, enhanced antioxidant capacity, and reduced reactive oxygen species (ROS) accumulation, thereby further improving plant drought tolerance. These findings demonstrate that enhanced phosphorus acquisition is an important component of AMF-mediated drought tolerance in trifoliate orange, whereas coordinated regulation of phytohormone homeostasis and antioxidant defense provides additional protection against drought stress. Full article

Fusarium solani is a major soil-borne pathogen responsible for root rot diseases, posing a significant threat to agricultural productivity. The development of environmentally sustainable alternatives to chemical fungicides is therefore urgently needed. This study evaluated the antifungal activity of fermentation broths and extracellular metabolites derived from Tilletia laevis fungi at different developmental stages against F. solani under in vitro conditions. Six test agents, including carbendazim (one positive fungicide control), caffeic acid, phenylacetylglycine, and 6-hydroxypyridine-2-carboxylic acid (candidate bioactive metabolites), were evaluated for mycelial growth inhibition, EC₅₀ values, and physiological responses. All treatments exhibited concentration-dependent inhibitory effects, with carbendazim showing the highest activity (EC₅₀ = 21.26 mg L⁻¹). Among the metabolites, 6-hydroxypyridine-2-carboxylic acid and phenylacetylglycine demonstrated notable antifungal efficacy, particularly at higher concentrations. Fermentation broths from the promycelial stage showed stronger inhibition than those from the teliospore stage, indicating stage-specific metabolite activity. Biochemical analyses of F. solani mycelia revealed significant changes in soluble protein, soluble sugar, and antioxidant enzyme activities (SOD and POD), suggesting that antifungal effects are mediated through metabolic disruption and oxidative stress. These findings highlight the potential of T. laevis-derived metabolites as eco-friendly biofungicides and provide a theoretical basis for sustainable management of soil-borne diseases. Further studies are required to identify active compounds and validate their efficacy under field conditions. Full article

Multi-agent reinforcement learning has emerged as a promising paradigm for cooperative unmanned aerial vehicle (UAV) swarm coordination. However, existing communication-aware MARL methods primarily focus on communication topology, message routing, and message aggregation, while the information content of the exchanged messages is often only implicitly controlled. In realistic UAV networks, inter-agent communication is constrained by limited bandwidth, communication range, energy consumption, and packet loss. It is therefore desirable for each UAV to transmit compact and task-relevant information rather than dense and redundant latent features. In this paper, we propose IB-CEMARL, an information-bottleneck-guided, communication-efficient multi-agent reinforcement learning framework for UAV swarms. We formulate inter-UAV communication as a minimal sufficient message-learning problem in which each UAV encodes its local observation into a stochastic bottleneck message before exchanging information with its neighbors. Cauchy–Schwarz divergence-based quadratic mutual information is adopted as a unified dependence measure to jointly regularize message compression, preserve decision-relevant information, and reduce statistical redundancy among neighboring UAV messages. Extensive experiments demonstrate that IB-CEMARL achieves superior cooperative performance, reduced message redundancy, and stronger robustness compared with representative communication-aware MARL baselines. In particular, IB-CEMARL improves the average return by $4.9\%$ and reduces inter-message dependence by $29.0\%$ compared with the KL-IB-MARL baseline while maintaining efficient communication under constrained bandwidth settings. Full article

Accurate 3D semantic perception is essential for robotic operations in multi-tier caged-pigeon houses, where dense cage-mounted facilities, repetitive layouts, local geometric similarity, and dynamic objects make static-facility segmentation difficult. To address these issues, this study proposes GSR-PointNet++, a point cloud semantic segmentation method with dynamic suppression. A Hierarchical Dynamic Suppression Front-End (HDS-Front) is introduced before static map construction to reduce dynamic interference caused by pigeon activity and human movement. Based on the processed static point clouds, a semantic segmentation dataset for multi-tier caged-pigeon houses is constructed. GSR-PointNet++ is developed on the PointNet++ backbone and incorporates a Geometric Structure-Relationship Module (GSRM), which models local normal consistency and spatial relationships to enhance feature representation in structurally repetitive scenes. Geometry-aware Prototype Consistency Learning (GPCL) is further introduced during training to improve class separability and prediction stability. Independent testing on the annotated dataset collected from the second pigeon house showed that the proposed method achieved a mean intersection over union (mIoU) of 96.29% ± 0.25% and an overall accuracy (OA) of 98.62% ± 0.13% for the four target facility classes, outperforming PointNet++ by 5.92 and 2.54 percentage points, respectively. These results indicate that the proposed method improves point cloud semantic segmentation for static facilities and has potential to support robotic perception in structured livestock environments. Full article

Umbilical cord mesenchymal stem cell-derived extracellular vesicles (UCMSC-EVs) hold strong promise for regenerative medicine, yet their intrinsic size heterogeneity remains a critical barrier to clinical translation, as it obscures molecular and functional specialization within bulk EV preparations. Here, we pioneer the application of the automated EXODUS platform to directly fractionate EVs from cell culture supernatants, resolving bulk UCMSC-EVs into three size-defined subpopulations. By integrating this platform with high-resolution mass spectrometry, we systematically characterize the molecular and functional landscapes of these UCMSC-EV size subpopulations. We demonstrate that EV size is tightly linked to distinct biogenetic origins, biomolecular corona composition, and functional programs: smaller EVs are enriched in exosome-associated proteins, ECM–glycan interfaces, and corona-associated molecules, and preferentially engage endocytosis- and phagosome-related pathways, whereas larger EVs exhibit ectosomal signatures. These findings identify EV size as a critical determinant of molecular architecture and biological function, providing insight into size-dependent EV heterogeneity and informing the rational design and optimization of UCMSC-EV-based therapeutic strategies. Full article

Under the background of the green transformation and energy conservation in the aviation field, hydrogen-fueled aero-engines are the primary direction for achieving sustainable aviation power development. However, the unique thermophysical properties of hydrogen fuel induce extreme thermal load challenges to engine thermal management. Based on the requirements of energy conservation and digital-intelligent technologies, this paper reviewed the recent research progress, important challenges, and future development directions in the thermal management field for hydrogen-fueled aero-engines, and filled the gaps in existing related reviews. (1) As for the liquid hydrogen thermal properties and thermal management requirements, the unique thermal physical properties of liquid hydrogen can easily cause fluctuations in heat load, large temperature differences, and material compatibility issues such as hydrogen embrittlement during storage, transportation, and combustion. The application of thermal barrier coatings, the design of targeted cooling structures, and the regulation of heat loss in the pipeline of the hydrogen supply system require particular attention. (2) As for the technical architecture and optimization of thermal management, the optimization of the high-pressure side manifolds in the cooled cooling air heat exchanger increases the flow uniformity by 18.8% and reduces the weight by 22.5%. The intercooled recuperated engine with the optimum area ratio reduces specific fuel consumption by 5.3% compared to the baseline engine in cruise. However, the system-level optimization research of the above widely recognized solutions is relatively limited in terms of coordinating the energy flow of engines. The baseline engine employed the method of system integration optimization to achieve a 2.99% increase in thrust and a 6.78% reduction in fuel consumption. (3) As for the thermal management modeling and simulation, the intelligent optimization method based on computational fluid dynamics reduces the pressure loss coefficient of the vane-integrated heat exchanger by 36%. Nevertheless, the multiphysics coupling model confronts a contradiction between computational cost and accuracy. (4) As for the comprehensive evaluation method, the advanced configuration of the hydrogen-fueled aero-engine can approximately reduce specific fuel consumption by 68.5% and NOx emission by 12.7% under the same maximum thrust condition. The hydrogen consumption of the proton exchange membrane fuel cells system model compared with the baseline system, optimized by the multi-objective optimization algorithm, has decreased by 15%, while the thermal uniformity has improved by 20–30%. However, the current evaluation system mostly focuses on a single dimension, lacking the analysis of nonlinear coupling among multiple factors and a closed-loop mechanism for evaluation, optimization, and verification. Future research should focus on the matching model of liquid hydrogen’s thermophysical properties and full flight conditions, global multi-energy flows optimization methods, multidimensional collaborative numerical simulation, multiphysics coupling models, and multidimensional comprehensive evaluation systems, to provide closed-loop theoretical support for the efficient, intelligent, and reliable thermal management system for hydrogen-fueled aero-engines. Full article

Accurate pig counting during herd transfers is fundamental to effective livestock management in large-scale swine production, yet existing methods struggle with bidirectional passages, boundary oscillations, and occlusion in real corridor environments. This study proposes an integrated system combining an improved YOLO-based detection model with a Hysteresis-based Multi-frame Temporal Confirmation Counting Strategy (HMTC). The YOLO11s baseline was enhanced using lightweight RepViT blocks, dynamic upsampling (DySample), and shape-aware bounding box regression (Shape-IoU). The resulting model achieves a mAP₅₀ of 0.982 with a compact architecture of 8.28M parameters, representing a 12.3% reduction relative to the baseline while improving detection accuracy. To address bidirectional counting challenges, the HMTC strategy utilizes hysteresis-based region classification, temporal confirmation, and trajectory verification to suppress boundary jitter and ensure directional correctness. Evaluated on nine videos from a single transfer corridor, the proposed system achieves an overall counting accuracy of 99.21% on this test set and runs in real time on an embedded edge device at over 30 FPS without loss of counting accuracy. Together, the improved detection model and HMTC counting strategy provide a cohesive approach to pig passage counting, validated here under a single transfer-corridor condition; these results offer a promising basis for automated animal inventory management, pending further validation across more diverse farm environments. Full article

Diabetic wounds are characterized by persistent hyperglycemia, excessive ROS accumulation, sustained inflammation, and impaired angiogenesis, yet current treatments remain suboptimal. To address these challenges, we developed a mild heat stimulating and microenvironment reprogramming hydrogel (termed C-4-N) via a green synthetic strategy. L-Arginine (L-Arg) triggered the spontaneous self-polymerization of protocatechuic aldehyde (PA) into poly (protocatechuic aldehyde) (PPA) nanoparticles, onto which ginsenoside Compound K (CK) was subsequently loaded, yielding CK/L-Arg/PPA nanoparticles. These nanoparticles were then uniformly embedded into a dynamic disulfide network composed of α-lipoic acid (LA)-modified chitosan (CS-LA) and 4-arm-PEG-SH under UV irradiation without toxic photo-initiators, forming the C-4-N hydrogel. The C-4-N hydrogel reprogrammed the diabetic wound microenvironment through three synergistic mechanisms, lowering blood glucose and scavenging ROS via the coordinated actions of LA, CK and PPA, promoting M1-to-M2 macrophage polarization via downregulation of pro-inflammatory cytokines (TNF-α, IL-6) and upregulation of anti-inflammatory cytokines (IL-10, TGF-β1), further amplified by mild photothermal stimulation of 40–43 °C. In a diabetic rat model, the C-4-N hydrogel achieved a near-complete wound closure rate of 99.49 ± 0.10% on day 13 upon mild photothermal stimulation, accompanied by enhanced re-epithelialization, organized collagen deposition, vascular maturation, and systemic glucose regulation. In summary, this green synthesized, mild heat-stimulating hydrogel establishes a synergistic microenvironment reprogramming paradigm for chronic diabetic wound managements. Full article

The ubiquitin-26S proteasome system provides a key mechanism for regulating protein turnover in plants and contributes to the control of diverse developmental and stress-related processes. Within this system, Skp1-Cullin1-F-box (SCF) E3 ligases rely on F-box proteins to confer substrate specificity, enabling selective and dynamic regulation of target protein stability. The large size and structural diversity of the F-box protein family in plants suggest extensive functional specialization, although many members remain poorly characterized. Here, we review recent advances in the understanding of F-box protein function, with a focus on their roles in plant development, stress adaptation, and immunity. Specifically, this review integrates findings across development, abiotic stresses, and immunity to highlight shared and diverging regulatory nodes and critically assesses the strength of substrate evidence to distinguish bona fide from putative F-box targets. We highlight how F-box proteins modulate key regulatory pathways, including phytohormone signaling, reproductive development, root architecture, and secondary metabolism, as well as responses to abiotic and biotic stresses. Emerging evidence indicates that F-box-mediated proteolysis acts as an important layer of control linking environmental signals to downstream transcriptional and physiological outputs. A better understanding of F-box protein substrates and regulatory networks is important for dissecting plant adaptive mechanisms and may provide molecular targets for future crop improvement strategies. Full article

Efficient and durable non-noble catalysts are crucial for alkaline hydrogen evolution (HER), and high-entropy alloys (HEAs) offer a promising platform due to their multicomponent synergy and tunable surface chemistry. Herein, self-supported nanoporous high-entropy alloy electrodes, Fe₃₅Co₂₅Ni₃₀Mo₁₀ and Fe₃₅Co₂₅Ni₃₀Mo₇W₃, were prepared by arc melting followed by electrochemical dealloying in 1 M HCl. XRD results show that both alloys retain an FCC framework after dealloying, whereas SEM reveals that W promotes a more continuous sponge-like nanoporous structure. In 1 M KOH, dealloyed Fe₃₅Co₂₅Ni₃₀Mo₇W₃ shows enhanced HER activity, requiring an overpotential of 178 mV at 10 mA cm⁻², which is lower than that of dealloyed Fe₃₅Co₂₅Ni₃₀Mo₁₀ and the precursors. Dealloyed Fe₃₅Co₂₅Ni₃₀Mo₇W₃ also exhibits faster kinetics (Tafel slope 98.5 mV dec⁻¹; Rct 3.33 Ω) and a larger C_dl (19.2 mF cm⁻²) than dealloyed Fe₃₅Co₂₅Ni₃₀Mo₁₀. These results highlight W-enabled dealloying-induced reconstruction as an effective route to robust nanoporous HEA electrodes for alkaline HER. Full article

A Cayley graph $\Sigma =Cay(G,S)$ is called 1-regular core-free if G is core-free in some $Y⩽Aut\Sigma$ and $Aut\Sigma$ acts regularly on the set of 1-arcs of $\Sigma$. In this paper, we classify the 14-valent 1-regular core-free Cayley graphs. In particular, we discover a non-normal Cayley graph on a non-abelian simple group. That is, 14-valent 1-regular Cayley graph on the alternating group $A_6$, with full automorphism group isomorphic to $S_7$. To our knowledge, this is the first example of a non-normal Cayley graph on a non-abelian simple group with even valency greater than 10. Full article

Relaxor ferroelectric single crystals, such as Pb(In₁/₂Nb₂/₃)O₃–Pb(Mg₁/₂Nb₂/₃)O₃–PbTiO₃, possess extraordinary electro-optic (EO) coefficients, offering immense potential for next-generation integrated modulators. However, the application of PIN-PMN-PT in fiber-optic gyroscopes (FOGs) is hindered by the challenge of fabricating high-quality optical waveguides with strict mode selectivity, as conventional diffusion typically excites multi-mode propagation. Here, the fabrication of high-quality, mode-selective waveguides is achieved in rhombohedral PIN-PMN-PT via a nickel in-diffusion technique. The resulting graded-index structures exhibit a Gaussian profile with a maximum refractive index change (∆n) of 1.53% while preserving the single crystal structure. Under specific processing conditions, we achieve precise mode selectivity, enabling exclusive transverse electric (TE) mode transmission. This mode selectivity fulfills the requirements for single-mode Y-branch geometries, establishing a robust platform for ultra-compact, low driving voltage modulators and advancing the miniaturization of inertial navigation and integrated photonic systems. Full article