Search Results (45)

The Navel Orangeworm (Amyelois transitella Walker, 1863), a primary pest of nut crops native to North America, poses a significant potential threat to China’s agricultural biosecurity, yet its potential distribution dynamics under climate change remain unquantified. This study utilized the Biomod2 ensemble model platform to predict habitat suitability under current and future climate scenarios (SSP1-2.6 and SSP5-8.5). We evaluated the prediction accuracy of the ensemble model using calibration data, with TSS = 0.898 and AUC = 0.978, while spatially stratified cross-validation confirmed moderate spatial transferability to novel environments (median validation AUC = 0.60–0.75). The model identified thermal factors—Temperature Seasonality (Bio4) and the Mean Temperature of the Wettest Quarter (Bio8)—as the dominant drivers of distribution. While currently climatically suitable habitats are primarily confined to the tropical and subtropical regions of southern China, projections indicate a complex spatial shift driven by future warming: optimal southern habitats will undergo a net contraction due to heat stress, whereas low and moderately suitable areas will expand northward into key temperate agricultural areas. These results highlight that climate change will substantially alter the spatial topology of the pest’s climatic envelope, providing a critical scientific baseline of climatic suitability. These projections do not equate to realized invasion risk, which is further constrained by host availability, land use, irrigation, and human transport, offering a conservative framework for prioritizing early surveillance and optimizing quarantine measures. Full article

Systemic risk propagation in modern financial markets is characterized by non-linear contagion and rapid topological evolution, rendering traditional static monitoring methods ineffective. Existing Graph Neural Networks (GNNs) often struggle to capture “structural breaks” during crises due to their reliance on static adjacency assumptions and isotropic aggregation. To address these challenges, this study proposes the Temporal Attentive Graph Networks (TAGN), a dynamic framework designed for extreme volatility prediction and financial surveillance. TAGN constructs an incremental multi-scale graph by fusing high-frequency trading data, supply chain linkages, and institutional co-holdings to model heterogeneous risk transmission channels. Technically, it employs a deeply coupled GAT-GRU architecture, where the Graph Attention Network (GAT) dynamically assigns weights to contagion sources, and the Gated Recurrent Unit (GRU) memorizes the trajectory of structural evolution. Extensive experiments on the S&P 500 dataset (2018–2024) demonstrate that TAGN significantly outperforms state-of-the-art baselines, including WinGNN and PatchTST, achieving an AUC of 0.890 and a Precision at 50 of 61.5%. Notably, a risk early-warning index derived from TAGN exhibits a 1–2 week lead time over the VIX index during major market stress events, such as the Silicon Valley Bank collapse. This research facilitates a paradigm shift from historical statistical estimation to dynamic network-aware sensing, offering interpretable tools for RegTech applications. Full article

The evolution of next-generation urban infrastructure necessitates the deployment of intelligent pavement systems capable of real-time data acquisition, adaptive response, and predictive analytics. This article presents the design, implementation, and performance evaluation of the smart pavement system incorporating multimodal embedded sensors for traffic density analysis, structural health monitoring, and environmental surveillance. SPS integrates piezoelectric transducers, micro-electro-mechanical system accelerometers, inductive loop coils, fiber Bragg grating (FBG) sensors, and capacitive moisture and temperature sensors within the asphalt and sub-base layers, forming a distributed sensor network that interfaces with an edge-AI-enabled data acquisition and control module. Each sensor node performs localized pre-processing using low-power microcontrollers and transmits spatiotemporal data to a centralized IoT gateway over an adaptive mesh topology via long-range wide-area network or 5G-Vehicle-to-Everything protocols. Data fusion algorithms employing Kalman filters, sensor drift compensation models, and deep convolutional recurrent neural networks enable accurate classification of vehicular loads, traffic, and anomaly detection. Additionally, the system supports real-time air pollutant detection (e.g., NO₂, CO, and PM2.5) using embedded electrochemical and optical gas sensors linked to mobile roadside units. Field deployments on a 1.2 km highway testbed demonstrate the system’s capability to achieve 95.7% classification accuracy for vehicle type recognition, ±1.5 mm resolution in rut depth measurement, and ±0.2 °C thermal sensitivity across dynamic weather conditions. Predictive analytics driven by long short-term memory networks yield a 21.4% improvement in maintenance planning accuracy, significantly reducing unplanned downtimes and repair costs. The architecture also supports vehicle-to-infrastructure feedback loops for adaptive traffic signal control and incident response. The proposed SPS architecture demonstrates a scalable and resilient framework for cyber-physical infrastructure, paving the way for smart cities that are responsive, efficient, and sustainable. Full article

We propose a strictly causal early–warning framework for financial crises based on topological signal extraction from multivariate return streams. Sliding windows of daily log–returns are mapped to point clouds, from which Vietoris–Rips persistence diagrams are computed and summarised by persistence landscapes. A single, interpretable indicator is obtained as the $L_2$ norm of the landscape and passed through a causal decision rule (with thresholds $\alpha ,\beta$ and run–length parameters $s,t$) that suppresses isolated spikes and collapses bursts to time–stamped warnings. On four major U.S. equity indices (S&P 500, NASDAQ, DJIA, Russell 2000) over 1999–2021, the method, at a fixed strictly causal operating point $(\alpha =\beta =3.1,s=57,t=16)$, attains a balanced precision–recall ($F_1\approx 0.50$) with an average lead time of about 34 days. It anticipates two of the four canonical crises and issues a contemporaneous signal for the 2008 global financial crisis. Sensitivity analyses confirm the qualitative robustness of the detector, while comparisons with permissive spike rules and volatility–based baselines demonstrate substantially fewer false alarms at comparable recall. The approach delivers interpretable topology–based warnings and provides a reproducible route to combining persistent homology with causal event detection in financial time series. Full article

The aromaticity of small boron clusters remains under scrutiny due to persistent inconsistencies between magnetic and electronic descriptors. Here, we reexamine B₃⁻, B₃⁺, B₄, B₄²⁺, and B₄²⁻ using a multidimensional approach that integrates Adaptive Natural Density Partitioning, Electron Density of Delocalized Bonds, magnetically induced current density, and the z-component of the induced magnetic field. We introduce a model in which σ-aromaticity arises from two distinct delocalization topologies: a radial 2e⁻ σ-pathway and a tangential multicenter circuit formed by alternating filled and vacant sp² orbitals. This framework accounts for the evolution of aromaticity upon oxidation or reduction, preserving coherence between electronic structure and magnetic response. B₃⁻ features cooperative radial and tangential σ-delocalization, together with a delocalized 2e⁻ π-bond, yielding robust double aromaticity. B₃⁺ retains σ- and π-aromaticity, but only via a tangential 6e⁻ σ-framework, leading to a more compact delocalization and slightly attenuated ring currents. In B₄, the presence of a radial 2e⁻ σ-bond and a 4c–2e π-bond confers partial aromatic character, while the tangential 8e⁻ σ-framework satisfies the 4n rule and induces a paratropic current. In contrast, B₄²⁺ lacks the radial σ-component but retains a tangential 8e⁻ σ-circuit and a 2e⁻ 4c–2e π-bond, leading to a σ-antiaromatic and π-aromatic configuration. Finally, B₄²⁻, exhibits delocalized π- and σ-circuits, yielding consistent diatropic ring currents, which confirms its fully doubly aromatic nature. Altogether, this analysis underscores the importance of resolving σ-framework topology and demonstrates that, when radial and tangential contributions are correctly distinguished, Hückel’s rule remains a powerful tool for interpreting aromaticity in small boron rings. Full article

As Industry 5.0 progresses, the demand for zero-touch configuration in industrial automation and smart manufacturing is increasing. This paper proposes a dynamic configuration management framework for Time-Sensitive Networking (TSN), aiming to address the challenges of flexibility and adaptability in dynamic network environments. A zero-touch configuration model is presented for TSN by incorporating a Delay-Aware Shortest Path Search (DASPS) algorithm to improve scheduling success rates. Simulation results demonstrate the ability of the framework to reconfigure networks within 2.67 milliseconds. The DASPS algorithm achieves a scheduling success rate of 70.22% for 1000 TSN flows, in contrast to only 22.23% achieved by the Shortest Path Search (SPS) algorithm. The proposed model effectively adapts to dynamic network changes, guaranteeing real-time data transmission. To further evaluate system adaptability, path entropy is introduced as a metric to quantitatively assess the balance of scheduling outcomes under topological changes. In the event of link failures, path entropy experiences a sharp decline but rapidly recovers after reconfiguration, demonstrating the system’s strong self-healing capability. Full article

Straw application (SP) is a promising strategy for the improvement of soil fertility, but the biological effects and the mechanisms of its effects on microorganisms remain unclear. The investigation into the tea plantations (CK/S) in southern Henan, China, without/with straw amendment was carried out to assess the effects of SP on the soil bacterial communities using high-throughput sequencing. SP induced the community restructuring of the dominant phyla, e.g., Acidobacteriota, Pseudomonadota, Chloroflexota, with significantly increasing Nitrospirota, Vicinamibacterales and Anaerolineaceae (p < 0.05), while reducing Terriglobales (p < 0.05). These transitions correlated with significantly enhanced α-diversity and β-diversity divergence (p < 0.05). The linear discriminant analysis effect size (LEfSe) results confirmed the significant selective enrichment of nitrogen-cycling taxa (Nitrospira), copiotrophs (Chryseotalea), and anaerobic degraders (Anaerolineaceae), along with the suppression of the oligotrophic lineage (Ellin6067) by SP (p < 0.05). The co-occurrence networks of S had lower topological properties and negative cohesion (p < 0.05), which exhibited intensified simplified complexity and competition. The soil water content (WC) and pH were the main drivers of β-diversity variation and the keystone taxa assembly, as calculated out by distance-based redundancy analysis (dbRDA). This study demonstrates that SP can enhance bacterial network stability and functional redundancy by resource-driven niche partitioning between copiotrophic taxa and nitrogen-cycling guilds through a competition–cooperation equilibrium. Full article

In this study, we describe a new genus, Luciargentis Yu and Wang, gen. nov. based on the new species, Luciargentis obesa Yu and Wang, sp. nov. Additionally, the genus is placed within the subfamily Crocanthinae, satisfying the criteria of Crocanthinae. We conducted a phylogenetic analysis of the family Lecithoceridae using a concatenated dataset that includes one mitochondrial marker (COI) and six nuclear markers (EF-1α, GAPDH, RpS5, CAD, wingless, and MDH), incorporating 17 exemplars from NCBI and 7 newly sequenced exemplars from this study. The yield tree topologies showed that Luciargentis obesa forms a strongly supported monophyletic group with Crocanthes prasinopis, a species of Crocanthinae. Moreover, Luciargentis + Crocanthes were found to be sister groups to Torodorinae. Images of the adults, wing venation, and genitalia of the new species are provided. Full article

The multi-sublattice ferrimagnet Co₂FeO₂BO₃, a prominent example of lanthanide-free magnets, was the subject of element-selective studies using X-ray magnetic circular dichroism (XMCD) observations at the L- and K- X-ray absorption edges. Research findings indicate that the distinct magnetic characteristics of Co₂FeO₂BO₃, namely its remarkable high coercivity (which surpasses 7 Tesla at low temperatures), originate from an atypical arrangement of magnetic ions in the crystal structure (sp.gr. Pbam). The antiferromagnetic nature of the Co²⁺-O-Fe³⁺ exchange interaction was confirmed by identifying the spin and orbital contributions to the total magnetization from Co (m_L = 0.27 ± 0.1 μ_B/ion and m^eff_S = 0.53 ± 0.1 μ_B/ion) and Fe (m_L = 0.05 ± 0.1 μ_B/ion and m^eff_S = 0.80 ± 0.1 μ_B/ion) ions through element-selective XMCD analysis. Additionally, the research explicitly revealed that the strong magnetic anisotropy is a result of the significant unquenched orbital magnetic moment of Co, a feature that is also present in the related compound Co₃O₂BO₃. A complex magnetic structure in Co₂FeO₂BO₃, with infinite Co²⁺O₆ layers in the bc-plane and strong antiferromagnetic coupling through Fe³⁺ ions, is suggested by element-selective hysteresis data, which revealed that Co²⁺ ions contribute both antiferromagnetic and ferromagnetic components to the total magnetization. The findings underline the suitability of Co₂FeO₂BO₃ for applications in extreme environments, such as low temperatures and high magnetic fields, where its unique magnetic topology and anisotropy can be harnessed for advanced technologies, including materials for space exploration and quantum devices. This XMCD study opens the door to the production of novel high-coercivity, lanthanide-free magnetic materials by showing that targeted substitution at specific crystallographic sites can significantly enhance the magnetic properties of such materials. Full article

In order to reduce the sensitivity of an inductive power transfer (IPT) system to the misalignment coupling coil, an S-SP-compensated IPT system with high misalignment tolerance based on a switch-controlled capacitor (SCC) is proposed. Firstly, the mathematical model of the S-SP compensation topology is established, the output characteristics and impedance characteristics of the system are analyzed, and a sensitivity analysis of the compensation element parameters is carried out using the compensation topology. An improved switching capacitor structure is proposed to dynamically compensate the S-SP IPT system. Finally, an experimental prototype was set up to validate the correctness of the theoretical analysis. The experimental results show that the proposed method can ensure that the system can operate in the resonant state with high efficiency when the coupling pad’s horizontal misalignment is within 30% (with the coupling coefficient varying from 0.22 to 0.14). Full article

The remote sensing-based inversion of sound speed profile (SSP) enables the acquisition of high-spatial-resolution SSP without in situ measurements. The spatial division of the inversion grid is crucial for the accuracy of results, determining both the number of samples and the consistency of inversion relationships. The result of our research is the introduction of a physics-inspired self-organizing map (PISOM) that facilitates SSP inversion by clustering samples according to the physical perturbation law. The linear physical relationship between sea surface parameters and the SSP drives dimensionality reduction for the SOM, resulting in the clustering of samples exhibiting similar disturbance laws. Subsequently, samples within each cluster are generalized to construct the topology of the solution space for SSP reconstruction. The PISOM method significantly improves accuracy compared with the SOM method without clustering. The PISOM has an SSP reconstruction error of less than 2 m/s in 25% of cases, while the SOM method has none. The transmission loss calculation also shows promising results, with an error of only 0.5 dB at 30 km, 5.5 dB smaller than that of the SOM method. A physical interpretation of the neural network processing confirms that physics-inspired clustering can bring better precision gains than the previous spatial grid. Full article

Streptomyces is a genus of Gram-positive bacteria with high GC content. It remains attractive for studying and discovering new antibiotics, antifungals, and chemotherapeutics. Streptomyces genomes can contain more than 30 cryptic and expressed biosynthetic gene clusters (BGC) encoding secondary metabolites. In this study, three Streptomyces strains isolated from jungle rhizospheric soil exhibited supernatants that can inhibit sensitive and fluconazole-resistant Candida spp. The genomes of the strains Streptomyces sp. A1, J25, J29 ori2 were sequenced, assembled de novo, and analyzed. The genome assemblies revealed that the size of the genomes was 6.9 Mb, with linear topology and 73.5% GC. A phylogenomic approach identified the strains with high similitudes between 98.5 and 98.7% with Streptomyces albidoflavus SM254 and R-53649 strains, respectively. Pangenomic analysis of eight genomes of S. albidoflavus strains deposited in the Genomes database recognized 4707 core protein orthogroups and 745 abundant accessory and exclusive protein orthogroups, suggesting an open pangenome in this species. The antiSMASH software detected candicidin and surugamide BGC-encoding polyene and octapeptide antifungal secondary metabolites in other S. albidoflavus. CORASON software was used to compare the synteny, and the abundance of genes harbored in the clusters was used. In conclusion, although the three strains belong to the same species, each possesses a distinct genome, as evidenced by the different phenotypes, including antifungal and extracellular enzymatic activities. Full article

Adopting Wireless Power Transfer (WPT) technology to an Unmanned Aerial Vehicle (UAV) involves adding extra components, which may impact the drone’s overall weight and performance. This paper aims to enhance UAV performance by designing a lightweight WPT system through a parametric design approach. This method explores novel perspectives by identifying the most suitable combination of parameters in terms of efficiency, weight, and feasibility. Various parameters such as the compensation topology, number of turns of coils, and frequency were studied. The system was analyzed through a coupled simulation approach, where electromagnetic modeling of the coupler using the finite element method (FEM) was combined with electrical circuit simulations, providing a more accurate assessment of the overall system efficiency and behavior considering variations in the coupling factor due to misalignment. A prototype of the resulting configuration was designed and tested experimentally versus misalignment at reduced power using a specific test bench. The results show a 70% efficiency level with SP compensation that was improved to 80% with SS compensation. Full article

To protect the battery, radio energy transmission charging typically uses constant current (CC) charging before switching to constant voltage (CV) charging to enhance battery durability. This paper proposes adding an auxiliary clamp coil to the original circuit topology. The IPT battery charger designed with the auxiliary clamp coil can achieve both constant current (CC) and constant voltage (CV) outputs. The mutual inductance between the auxiliary clamp coil and the primary side coil greatly influences the output performance of the entire IPT system, so the auxiliary clamp coil should not be too large. To solve this problem, an S-S-PS circuit with secondary compensation topology in the secondary coil is proposed. This circuit topology reduces the size of the auxiliary clamp coil, allowing it to be placed in an optimal position. When the constant voltage output critical position is reached, the IPT system can still automatically, continuously, and smoothly switch between CC and CV modes. Consequently, this approach avoids increased cost consumption associated with detecting CC-CV switching thresholds, adding wireless transmission communication modules, real-time control of the power transmitter, and active protection of the circuit during constant current charging. Finally, a 48 V/2.5 A prototype was built to verify that the IPT system has CC-CV conversion functionality. Full article

Enhancing the output power of stratospheric airship photovoltaic arrays during months with weak irradiance is crucial for extending the endurance of airships. Models for predicting the output power of photovoltaic arrays and the phenomenon of mismatch losses have been proposed. However, static reconstruction schemes to reduce or eliminate mismatch losses have not been studied. In this paper, an output power model for stratospheric airship arrays including the solar radiation and irradiance distribution is established. The characteristics of the irradiance distribution for the photovoltaic array (PV) are investigated through simulation. Furthermore, an innovative reverse combination configuration is developed and compared to the SP and TCT configurations in terms of performance, mismatch loss and fill factor. Finally, simulations are conducted for a full-day irradiance period of 4 days in a real wind field. The simulation results demonstrate that the proposed RC configuration significantly reduces mismatch losses and output power fluctuations, thereby enhancing the PV array’s output power. This research provides interesting insights for the design of PV array topologies for stratospheric airships. Full article