Search Results (9,006)

Dendroctonus valens LeConte represents a major invasive pest species in China. Both larvae and adults primarily feed on the phloem of the tree trunk base and roots, disrupting nutrient transport and leading to host tree mortality, which poses a severe threat to forest ecosystems and the forestry economy. Juvenile hormone acid methyltransferase (JHAMT) is a key enzyme in insect juvenile hormone (JH) biosynthesis. In this study, we identified a JHAMT-encoding gene, DvJHAMT, in D. valens via bioinformatic analysis. RT-qPCR analysis revealed that DvJHAMT is predominantly expressed during the egg and larval stages. In the fourth-instar larvae, the highest expression levels were observed in the head and epidermis, suggesting a central regulatory role during this critical developmental period. To investigate its function via RNA interference (RNAi), a nanomaterial, star polycation (SPc), was employed for the transdermal delivery of dsRNA into the fourth-instar larvae. The results demonstrated that DvJHAMT knockdown significantly downregulated mRNA levels, resulting in marked decreases in larval survival, pupation, and eclosion rates. Notably, treatment with 0.7 µg dsDvJHAMT-SPc resulted in a 96.67% mortality rate and a reduced pupation rate of 41.67% at 34 days post-treatment. Furthermore, RNAi led to developmental deformities and significant weight loss in larvae. ELISA assays confirmed that DvJHAMT silencing led to reduced JHAMT enzyme activity and JH III titers in a dose-dependent manner. In conclusion, our findings demonstrate that DvJHAMT plays a vital role in JH biosynthesis and that its suppression exhibits potent lethal effects, suggesting that DvJHAMT is a promising candidate for RNAi-based management of D. valens. Full article

The sixth generation of mobile networks (6G) represents a paradigmatic shift in the conception of wireless communication systems, where Artificial Intelligence (AI) is not integrated as an additional feature but is conceived as a native and fundamental component of the physical layer (PHY). This paper presents a comprehensive survey of the state of the art in AI-native physical layer for 6G, synthesizing approximately 100 references from the period 1948–2025. The survey systematically covers 5 main PHY components (channel coding, channel estimation, signal detection, beamforming, and semantic communications) and analyzes 8 AI architectural families (autoencoders, CNN, RNN/LSTM, Transformers, GNN, GAN, Diffusion Models, and Foundation Models), addressing theoretical foundations, proposed architectures, learning algorithms, implementation challenges, and future research directions. A rigorous mathematical framework underpinning these developments is presented, including optimization formulations, convergence analysis, and theoretical performance characterization. Published results from the literature demonstrate that AI-native physical layer can improve conventional performance metrics and enable emerging capabilities essential to 6G, such as semantic communications, predictive environmental adaptation, and operation in previously inaccessible computational complexity regimes. However, such gains are conditional on adequate training resources, robust channel-matched data, and careful consideration of known limitations including generalization across channel distributions, sample inefficiency, model interpretability, and hardware implementation constraints—all of which are critically analyzed in this survey. A reproducible proof-of-concept benchmark further confirms that, under severe resource constraints, autoencoder-based codes currently underperform conventional schemes, highlighting the gap between theoretical potential and practical deployment readiness. Full article

Structural and functional soil degradation under conventional tillage has reached a critical point, requiring a shift towards conservation practices to mitigate the negative effects of climate change. This study evaluated the multi-year effects (2021–2024) of conventional tillage (CT), conservation deep tillage (CD), and conservation shallow tillage (CS) on soil physical properties (density, air capacity, and water content), water distribution, infiltration rate, and maize yield in a silty Gleysol. Soil water content (SWC), i.e., distribution, was monitored using PR2 profile probes at depths of 10, 20, 30, and 40 cm. CT treatment resulted in impaired soil physical properties, characterized by a significant increase in air capacity (+233.9%) and with a significant decrease in volumetric water content (qw, ≈40%). In contrast to CT (47.91 cm h⁻¹), the CS treatment resulted in more favorable hydraulic properties, i.e., and infiltration rate of 102.29 cm h⁻¹, by 2024. Statistical analysis (R², RMSE) confirmed that CS provides the most reliable and consistent environment for monitoring SWC. While maize yields were significantly higher in CT during the initial year (2021; 9.5 t ha⁻¹ vs. 8.4 t ha⁻¹ in CS), no significant differences were observed by 2024, and all tillage systems reached yields of ≈13.0 t ha⁻¹. The results suggest that after the four-year study period, CS tillage stabilized soil hydraulic properties and pore continuity, thereby resulting in maize yields equivalent to those of CT. Therefore, CS has proven to be a more resilient and effective strategy for sustainable water management in silty Gleysols. Full article

Electromagnetic spectrum planning is a critical challenge in modern wireless communication systems, characterized by multiple conflicting objectives including spectrum utilization efficiency, interference minimization, and fairness among users. This paper proposes an Enhanced Discrete Multi-Objective Particle Swarm Optimization (EDMOPSO) algorithm specifically designed for spectrum assignment problems. The proposed method introduces a novel probabilistic discrete velocity update mechanism with adaptive dynamic bounds, an adaptive inertia weight strategy based on normalized population diversity, and an improved archiving technique with enhanced diversity preservation. To handle the discrete nature of spectrum allocation, we develop a binary encoding scheme combined with a problem-specific repair mechanism for constraint satisfaction. The algorithm is evaluated on both synthetic benchmark problems and real-world spectrum planning scenarios. Experimental results demonstrate that EDMOPSO achieves competitive performance advantages over seven established multi-objective evolutionary algorithms, with Hypervolume improvements of 18.7% and Inverted Generational Distance reductions of 23.4% compared to the second-best-performing algorithm. A comprehensive ablation study with 15 configurations validates the synergistic interaction between components. The proposed method provides an effective solution for macro-level periodic spectrum management in complex electromagnetic environments. Full article

Background/Objectives: Cortical spreading depolarization (SD) is recognized as the pathophysiological substrate of migraine aura. Suppression of ongoing cortical activity produced by SD is thought to underlie the transient neurological deficits characteristic of the aura phase. While cortical hyperexcitability is a well-established feature of migraine brain, the effect of SD on spontaneous electrical activity in the hyperexcitable cortex remains poorly understood. Here, we investigate how SD and SD-induced depression of cortical activity are modulated by a state of mildly enhanced excitability. Methods: Using freely behaving rats, we assessed characteristics of SDs, electrocorticographic spectral power in the frontal and occipital cortices during interictal period and after SD initiation, under both drug-free conditions and following mild pharmacological disinhibition. Results: Mild cortical disinhibition resulted in a significant increase in baseline oscillatory power relative to control conditions. While cortical hyperexcitability did not alter the properties of SD itself, it differentially modulated the impact of SD on spontaneous activity in a region-specific manner. Notably, under conditions of enhanced excitability, the duration of SD-induced depression was markedly reduced in the frontal cortex but prolonged in the occipital cortex. Conclusions: These findings demonstrate that the effects of SD on spontaneous cortical activity are critically dependent on the baseline level of cortical excitability and exhibit distinct regional heterogeneity. In the awake, hyperexcitable state, the occipital cortex shows heightened vulnerability to SD-induced depression, a finding that may provide a mechanistic basis for the disproportionate involvement of the occipital cortex in aura generation and the predominance of visual symptoms in migraine aura. Full article

Secure real-time communication is a critical requirement in modern electric vehicle (EV) networks. These networks transmit safety-critical control commands through vulnerable in-vehicle communication channels. This study proposes a novel three-dimensional symmetric chaotic system for high-security EV communication. The system exhibits extensive multistability and symmetric double-wing attractors. To enhance dynamical complexity, its parameters are optimized using chaotic-enhanced particle swarm optimization (C-PSO). The largest Lyapunov exponent is used as the optimization objective. A fixed-time nonlinear controller is designed for rapid drive–response synchronization. The settling-time bound is independent of the initial conditions. The proposed method is evaluated through realistic Controller Area Network (CAN) bus simulations. These simulations include 12-bit quantization and a 1 ms sampling period. The experimental results show synchronization within 0.057 s. The recovered signal achieves an MSE of $1.202\times {10}^{-4}$. The encrypted signal reaches a Shannon entropy of 7.9904. These results confirm accurate recovery, strong randomness, and improved resistance to cryptographic attacks. Full article

Heterogeneous catalytic ozonation has attracted increasing research attention as a strategy for advanced wastewater polishing; yet the recent literature has advanced the attribution of non-radical pathways at a pace that has outstripped rigorous demonstration of their practical process advantage. This article constitutes an evidence-centered critical review—rather than a formal systematic review—organized around a central evaluative question: under what conditions are non-radical mechanistic claims in catalytic ozonation sufficiently persuasive, wastewater-relevant, and defensible to warrant consideration for process translation. Recent studies, drawn primarily from the period 2023–2026, are evaluated through an explicit evidence-grading framework that distinguishes among radical, singlet-oxygen-mediated, surface-bound oxygen-transfer, direct electron-transfer, and high-valent metal-oxo pathways. The review further examines whether reported parent-compound removal is corroborated by complementary lines of evidence encompassing bromate formation, transformation product characterization, effluent toxicity assessment, catalyst leaching quantification, operational durability, and reactor-scale performance. The synthesis reveals that single-atom catalysts currently provide the most robust active-site mechanistic evidence; however, even these systems remain constrained by their reliance on simplified aqueous matrices, incomplete transformation byproduct accounting, and unresolved long-term stability. Accordingly, the article proposes standardized reporting protocols and benchmark performance metrics—including a bromate-normalized treatment benefit index—to delineate mechanistic elegance from process realism. Full article

Deformation monitoring of bridges is essential to ensure the structural integrity and serviceability of these critical civil infrastructures. In this context, geodetic measurements using total stations and 3D terrestrial laser scanning (TLS) surveys can provide accurate and reliable data. Multitemporal geodetic observations from total stations enable the tracking of displacements at discrete points, whereas TLS surveys allow for the extension of deformation analysis to entire surfaces. Both techniques can achieve comparable millimeter-level precision. These methods were applied to monitor the deformation of the Ponte della Costituzione (PdC), the most recent pedestrian arch bridge spanning the Grand Canal in Venice (Italy). A total station was used to measure the displacements of six control points installed on structurally significant locations of the bridge. Between 3 October 2023 and 2 February 2026, 28 multitemporal measurement campaigns were conducted. In addition, four TLS surveys, using two different laser scanners, were carried out on 1 August 2025 and 2 February 2026, in order to capture conditions corresponding to maximum annual thermal deformation. The results derived from geodetic measurements reveal a strong correlation among: (i) variations in the distance between the abutments (on the order of 6–7 mm); (ii) vertical displacements of the central upper points of the arch (ranging from 9 to 12 cm); and (iii) fluctuations in ambient temperature. TLS data highlighted a spatially homogeneous deformation pattern extending from the crown of the arch to the abutments, demonstrating that longitudinal displacements affect the entire lateral structure. Mid-term deformation analysis over the two-year period from 6 February 2024 to 2 February 2026 indicates displacement rates of approximately 1.4 mm/year for increasing separation between the abutments and 16.2 mm/year for the decrease in elevation of the central arch point. However, these trends are significantly influenced by environmental temperature variations, as evidenced by an estimated temperature change rate of −3.5 °C/year over the same period. Therefore, continued deformation monitoring of the PdC bridge is recommended in the coming years, particularly in light of ongoing climate change and the associated increase in temperature variability. Full article

Climate change poses an increasing threat to the functionality of forest transportation infrastructure, particularly in northern regions where seasonal access and ground conditions are critical for wood mobilization. The objective of this study was to assess how projected changes in temperature and precipitation may compromise accessibility to forest resources. In addition, it aimed to develop targeted adaptation recommendations to support resilient transportation systems. These actions are essential to ensure the continuity of wood supply under future climatic conditions. Climate projections were extracted from the climatedata.ca platform based on the CMIP6 (CanDCS-M6) model under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Using a GIS-based workflow, projected temperature and precipitation data were spatially matched to the selected Forest Management Units (FMUs) in Quebec, Canada, and the study area was divided into three latitudinal subregions to capture spatial temperature variation. Classified road network maps were then overlaid with projected climate data for 2020, 2040, 2060, and 2080 to evaluate winter road usability, precipitation-related exposure of road classes, and changes in effective winter road density. Results showed a consistent shortening of the winter road operational period under all scenarios, with the most severe reductions under SSP5-8.5. In highly affected areas, the winter road usability window may decrease from 90 days in 2020 to only 21 days by 2080. Increased precipitation is also expected to affect numerous road segments, raising risks of erosion, sedimentation, and loss of accessibility. A reduction of approximately 7% in effective winter road density is projected across the study area under the high-emission scenario (SSP5-8.5), reflecting the most severe impact of future temperature increases. Based on these findings, targeted road upgrades, climate-informed infrastructure design, and alternative access planning are proposed to help sustain wood flow and support year-round forest operations under future climatic conditions. Full article

To address peak-period congestion in high-density air route networks and the high cost and limited precision of traditional global control methods, this study proposes a congestion mitigation method based on pinning control theory. First, a comprehensive evaluation index system for critical waypoints is constructed from complex-network structural characteristics, traffic flow characteristics, and congestion-state information. Pearson correlation analysis is used to examine redundancy among candidate indicators, and the entropy-weighted TOPSIS method is then employed to evaluate waypoint importance and identify critical pinning nodes. Second, a GA-PID pinning control optimization model is established to realize closed-loop optimization of network congestion by dynamically regulating a small number of critical nodes. Finally, simulation experiments are conducted using actual operational trajectory data from the Yangtze River Delta airspace. The results show that the proposed method reduces the network congestion coefficient from 176 to 137, representing a decrease of 22.16%, and increases airspace resource utilization from 70.76% to 84.41%, representing an improvement of 19.29%. Compared with the baseline GA method, the proposed method achieves better optimization performance and requires adjustments at only 13 waypoints, whereas the baseline GA method requires adjustments at 25 waypoints, demonstrating lower control costs and higher regulation efficiency. Full article

In the face of intensifying climate change, agricultural water security in semi-arid zones has emerged as a critical frontier for water governance. This study provides a systematic and critical analysis of the scientific literature to map current research frontiers and structural gaps. The methodology integrated the PRISMA 2020 protocol and a modified Methodi Ordinatio, spanning a search period from 2014 to 2026 across the Science Direct and SciELO databases. From an initial broad screening, 136 high-impact articles were selected based on rigorous inclusion and exclusion criteria. The findings reveal a significant fragmentation of knowledge, characterized by a high prevalence of small-scale studies (25 articles) and limited interdisciplinarity. Notably, a governance-centric approach is present in only 20% of the literature, while the Water–Energy–Food Nexus appears in just 6%, signaling a major disconnect in holistic management. Based on these results, this study identifies water governance and socioeconomic integration as the most pressing research gaps. Consequently, an integrated conceptual framework is proposed, built upon three pillars: Governance, Technology, and Environment (GET). This study concludes that advancing the frontiers of agricultural water security requires moving beyond isolated solutions toward a structured, systemic, and interdisciplinary integration. Full article

This work involves the building occupants of a smart building during a period of hybrid working, with the purpose of co-designing data-rich workplaces that support wellbeing. Through the design of a custom card-kit based on PROWELL Model of Workplace Wellbeing Assessment, this work provides insights from an online 90 min co-design workshop with six building occupants utilizing the card-kit to speculate on the design of data-driven physical interventions that support workplace wellbeing. Transcript data from the video-recorded workshop were thematically analyzed, producing findings namely framing novel socio-technical dimensions for biophilic and biomimetic designs in the built environment. Contributing to discourses on Human-Building Interaction (HBI) research, findings were synthesized into a design agenda and considerations for supporting wellbeing in the hybrid workplace that utilizes physical feedback and passive sensing. Composed under the premise of co-creating smart environments together with their occupants, the proposed agenda highlights areas of critical research interest for HBI, Biophilic Design and Soft Robotics in the built environment. Full article

The study of bubble pulsation from underwater explosions is critical for applications in marine resource exploration, underwater demolition, and offshore engineering. However, the existing research methods have significant limitations: Laboratory experiments struggle to replicate the dynamic decompression during the process of bubble rising. Field experiments in seas or lakes find it difficult to systematically cover complex parameter ranges. Furthermore, theoretical calculations face the problems of accurately coupling the bubble pulsation with its buoyancy-driven ascent. Therefore, this paper proposes a novel method for calculating the bubble pulsation period of underwater explosions. This method accurately simulates the pulsation and buoyancy-driven ascent of an underwater explosion bubble. Based on the bubble’s energy attenuation characteristics, it establishes the relationship between the pulsation period, TNT equivalent, and ambient hydrostatic pressure. To verify the accuracy of the method, we conducted underwater explosion experiments in the South China Sea with varying TNT equivalents and detonation depths. Abundant bubble pulsation period data of underwater explosions were obtained spatially by deploying hydrophone arrays at various depths. The close agreement between the theoretical predictions and the experimental results confirms the accuracy of the proposed method. By matching the measured values of the first pulsation period and the ratio of the second pulsation period to the first against a database of theoretical curves, a combination of depth and charge equivalent that satisfies both values can be identified, thereby enabling the inversion of the explosion parameters. Full article

The perinatal period is a critical window of susceptibility for fetal development and awareness for women’s health. Pregnant women are highly motivated to reduce environmental health risks, yet often lack personalized, actionable guidance on mitigating endocrine-disrupting chemicals and other household hazards. Grounded in Motivational Interviewing theory, a digital assessment was developed to empower parents to identify and reduce exposures. The tool screens for home-based and environmental risks across several domains: air quality, lead, tobacco, cleaning agents, pesticides, and plastics (BPA/phthalates). Based on user inputs, a defined algorithm generates a positive index score paired with prioritized, low-cost behavioral recommendations designed to shift users from risk awareness to active mitigation. Since its launch in Spring 2024, the tool has had over 1900 views. Preliminary analytics suggest promising engagement, and feedback more so suggests that the motivational-interview-based framing, which emphasizes empowerment over fear, facilitates immediate behavioral changes, such as switching to safer personal care products and improving indoor ventilation. Digital health interventions that translate complex environmental data into a single, manageable score can bridge the gap between clinical knowledge and household practice. This article details the score’s calculation methodology and underlying datasets, and reports usage analytics and user feedback, discussing how digital screening can scale environmental health literacy and improve maternal and child health outcomes. Full article

The steno-endemic Verbascum rupicola faces a precarious future due to its extreme habitat specialization on tectonically active hydrothermal quartz veins. This study presents a long-term assessment based on periodic population censuses spanning 18 years (2007, 2016, and 2025) to assess the demographic and spatial trends of its global population in the Tahtalı Dam basin, Türkiye. Field surveys, GIS-based habitat mapping, and controlled pollination experiments were integrated with seed germination kinetics and ex situ cultivation trials. Results reveal a precipitous 69.12% global population decline, primarily driven by a 33.41% habitat loss from agricultural expansion in 2011 and the total extirpation of three sub-populations by a major wildfire in 2017. Furthermore, a “reproductive squeeze” was identified, where climate-induced reductions in flower production (18.87%) are compounded by intensifying floral predation by Pieris rapae. Reproductive analysis revealed random monomorphic enantiostyly—reported for the first time in the genus—which functions as a flexible mating system prioritizing outcrossing while providing reproductive assurance. Despite high intrinsic seed viability (69.12%), ex situ cultivation largely failed (3.5% survival; 1 out of 28 transplanted individuals), underscoring the species’ obligate chasmophytic nature. Consequently, V. rupicola meets the criteria for Critically Endangered (CR) status, necessitating urgent “micro-reserve” protection of its remaining habitat and in situ restoration efforts. Full article