Search Results (57)

Autonomous tractors have been shown to possess the capability to ensure a high degree of operational precision during seeding activities on flat terrain. However, in topographically challenging environments characterised by significant elevations and pronounced variations in slope, factors such as road gradients have been shown to compromise the precision of satellite-based positioning systems. This, in turn, can lead to alterations in vehicle posture and the generation of disparate longitudinal driving forces between the left and right tyres. It is important to note that this deviation from the predefined path has the potential to result in rollover accidents. Evidence has been presented that indicates a correlation between road gradient and vehicle roll motion. The proposed methodology is an algorithmic approach to the estimation of lateral slope, integrating inertial measurement unit (IMU) sensors and ground-based ultrasonic radars. This algorithmic approach is proposed as a means to achieve more accurate estimations of lateral slope. The initial development of the vehicle dynamics model was based on slope operation requirements, and the model was endowed with eight degrees of freedom. The utilisation of an unscented Kalman filter (UKF) facilitates the integration of inertial measurement unit (IMU) and ground-based ultrasonic radar measurements, thereby enabling real-time estimation of key motion states, such as lateral slope. The validity of the proposed algorithm was established through a combination of hardware-in-the-loop testing and field trials involving real tractors. The findings indicate that the implementation of this algorithm leads to a substantial enhancement in the trajectory tracking accuracy of tractors during slope operations. This enhancement is characterised by a substantial reduction in lateral deviation and an effective augmentation in the operational pass rate. In the course of empirical trials conducted in a mountainous environment, the lateral positioning deviation during straight-line driving was diminished from 10 cm to within 5 cm. Concurrently, the precision of lateral slope estimation was enhanced to 0.04 degrees. Full article

Traditional social recommendation methods often focus on static representations of users and items, neglecting dynamic changes in user interests and item attractiveness over time, which makes it challenging to adapt to temporal variations in user interests. Additionally, the propagation of information along explicit social relationships tends to over-smooth features and weaken individual preferences, while static implicit relationships may increase short-term noise. Thus, a Dual-channel Controllable Diffusion Network based on Hybrid Representations (HR-DCDN) is proposed for social recommendation. The HR-DCDN first incorporates temporal factors by combining dynamic and static representations to capture changes in user interests and item attractiveness. Then, our method proposes a dual-channel aggregation mechanism to obtain higher-order representations of users and items. Explicit social relationships serve as the social-influence channel, while implicit social relationships discovered via dynamic implicit relationship mining constitute the preference-homophily channel. In addition, a learnable polynomial spectral filter incorporates residual connections and dual-channel fusion information at each propagation step, stabilizing deep propagation and alleviating representation homogenization to a limited extent while preserving high-frequency preference information. Finally, we jointly optimize a cross-layer InfoNCE objective on the perturbed interaction branch with the supervised rating loss, which provides an additional empirical regularization effect, improves robustness, and helps preserve representation diversity without altering the graph structure. Experimental results demonstrate that our model outperforms baseline methods on two real-life social datasets. Full article

Demand-responsive transit (DRT) requires real-time vehicle assignment under dynamically arriving requests, where each decision may alter multi-stop routes and affect both onboard and newly arriving passengers. However, DRT simulations often face three key limitations: rapidly increasing computational complexity as fleet size and demand grow, insufficient integration of traffic congestion into routing decisions, and limited consideration of passenger-oriented service quality in final vehicle assignment. To address these issues, this study proposes an integrated DRT simulation incorporating three core algorithms: Fréchet Distance-based Candidate Vehicle Selection (FD-CVS), Congestion-Aware Path Planning (CA-PP), and Satisfaction-Aware Vehicle Assignment (SA-VA). FD-CVS reduces computational burden by filtering candidate vehicles based on route similarity. CA-PP extends conventional path planning by incorporating congestion-adjusted travel costs derived from public transportation data. SA-VA determines the final vehicle assignment by jointly evaluating passenger waiting time, in-vehicle travel time, and capacity constraints. The algorithms are implemented within a discrete-event simulation environment using real-world data. Experimental results demonstrate that FD-CVS significantly reduces execution time under high-demand conditions, while SA-VA improves passenger waiting time and acceptance rates. Overall, the proposed three-algorithm framework enables more realistic and computationally efficient DRT system evaluation. Full article

Coprophagous flies can convert livestock manure into protein-rich larval biomass for animal feed, but manure-based rearing raises biosafety concerns. This study characterized the internal bacterial community dynamics across development in Aldrichina grahami and Boettcherisca peregrina reared on swine manure, aiming to identify developmental stages with a lower microbial hazard profile. Using 16S rRNA gene amplicon sequencing of pooled internal samples, we analyzed communities from third-instar larvae, dispersing-stage larvae, pupae at multiple time points, and newly emerged adults. Developmental stage strongly structured bacterial composition and altered richness in both species. Communities were dominated by Bacillota and Pseudomonadota, reflecting substrate origin, with pronounced turnover during metamorphosis and stage-specific dominance patterns, indicating developmental filtering rather than uniform microbial clearance. Crucially, dispersing larvae did not show the marked dominance signatures seen in later pupal or adult stages, supporting this stage as a pragmatic harvest window with a comparatively lower microbial-hazard indicator profile. Since downstream processing such as drying or heating will further reduce viable hazards, stage selection serves as an effective upstream control to lower the initial hazard burden entering production. Full article

Ice accretion poses a threat to fixed-wing aerial vehicles as it alters the wings’ shape and thus degrades the aerodynamic performance. In manned aircraft, the icing detection system assists the pilot and utilises dedicated sensors. However, in unmanned aerial vehicles (UAVs), onboard icing detection can generally only be achieved using standard sensors in conjunction with dynamical models, because dedicated sensors are rarely available. In this paper, we propose two approaches based on the particle filter for both icing detection and accurate state and aerodynamic parameter estimation in the presence of icing, with different levels of severity. The first approach uses the observation likelihood for icing hypothesis testing with a complement of the Gaussian kernel to compute icing probability. The second approach uses a discrete jump approach based on a Bernoulli process and a subset of particles to test the icing hypothesis for faster icing detection by estimating changes in icing-related aerodynamic parameters. Using both approaches, the simulation results demonstrate improved estimation accuracy compared to an extended Kalman filter (EKF), under both moderate and severe icing conditions. With adequate tuning, the proposed approaches show potential for indirect icing detection in UAVs. They also enable the computation of icing severity and provide a more accurate and reliable estimate of the icing probability compared to the EKF. Full article

Climate warming—a key driver of global change—significantly affects soil microbial communities and network stability. Biological soil crusts (biocrusts) help mitigate these impacts while maintaining soil ecological functions and biodiversity. However, how microbial networks and community dynamics respond to warming remains poorly understood between biocrust types, namely cyanobacterial and moss biocrust. In this study, we investigated the effect of warming on microbial communities and network stability in these biocrusts within the Mu Us Sandland, China. Using structural equation modeling (SEM), we found that warming altered microbial network properties: compared to the control, warming increased network vulnerability and decreased robustness specifically in cyanobacterial biocrusts. Warming and decreased soil moisture acted as strong filtering factors, resulting in lower microbial network stability. Although overall network complexity remained unchanged, warming reduced connectivity in cyanobacterial biocrusts, thus undermining network stability. Moreover, under both warming and control conditions, moss biocrusts exhibited lower robustness but higher vulnerability than cyanobacterial biocrusts, indicating cyanobacterial biocrusts displayed greater microbial network stability in comparison. Additionally, warming reduced the number of module hubs and keystone phyla in both biocrust types, decreasing key taxa abundance and weakening direct microbial interactions. We concluded that warming impaired microbial network stability by reducing connectivity in cyanobacterial biocrusts. These findings highlight the superior capacity of cyanobacterial biocrusts to sustain soil microbial network stability under climate warming and identify shifts in network connectivity as a central mechanism driving biocrust responses to environmental stress. Full article

Incorporating plant-based additives was a promising approach for modulating the microbial ecosystems of fermentation starters. This study investigated how adding Kuding tea (20% wt/wt) influenced the assembly and succession of fungal communities during Jiang-flavored Daqu production, compared to traditional wheat-based Daqu. Using amplicon sequencing of the ITS1 region and integrated measurements of endogenous factors, we analyzed community dynamics across a 40-day fermentation period. Results showed that tea addition significantly increased fungal diversity and altered succession trajectories. Community assembly shifted from stochastic towards deterministic processes, with homogeneous selection increasing from 0.47 in wheat-based Daqu to 0.62 in tea-added Daqu. Temporal species accumulation was stronger (STR exponent z: 0.565 vs. 0.436), while compositional turnover slowed (TDR slope w: −0.539 vs. −0.626). Random forest models revealed tea-specific fungal drivers and stronger correlations with endogenous factors (e.g., reducing sugar and moisture). We concluded that Kuding tea appears to function predominantly as an environmental filter that enhanced deterministic selection, stabilized community succession, and restructured the key microbial–physicochemical relationships, providing a potential strategy for steering Daqu fermentation. Full article

To address the issue that current ripple in traditional switching power amplifiers (SPA) for active magnetic bearing (AMB) systems is constrained by the switching frequency, this paper proposes a novel LCL filter-based switching power amplifier (LCL-SPA) along with its parameter design and high-performance control strategy. Without altering the original full-bridge topology or the switching frequency, the proposed scheme achieves superior ripple suppression. To tackle the inherent resonance problem of the LCL filter, a sensorless capacitor current feedback active damping (CCFAD) strategy is proposed. This approach effectively suppresses resonance without additional hardware sensors and ensures system stability under digital control delays. Furthermore, to overcome the limitations of traditional PI controllers in terms of the dynamic performance and parameter tuning of the LCL-SPA, a high-performance LESO-based control algorithm within the Linear Active Disturbance Rejection Control (LADRC) framework is designed. By utilizing a Linear Extended State Observer (LESO) to estimate and compensate for total lumped disturbances in real-time, the algorithm simplifies the parameter tuning process and achieves rapid current tracking with nearly zero overshoot. Experimental results demonstrate that the proposed LCL-SPA achieves extremely low current ripple across various reference currents, with the ripple minimized to 20 mA at a 3 A load. Frequency response tests confirm that the system possesses a closed-loop bandwidth of up to 2 kHz, satisfying the high dynamic requirements of magnetic bearings. Full article

This paper presents an adaptive virtual oscillator control in coordination with an adaptive filter to mitigate subsynchronous oscillations in grid-forming converters caused by series compensation. Although series compensation enhances power transfer capability and transient stability margins, it can introduce subsynchronous resonance, leading to subsynchronous oscillations. Virtual oscillator control fed with set points is made dispatchable for grid-forming control to ensure the power-sharing, fast-synchronization, and subsynchronous oscillation damping capability of inverters. In this paper, taking advantage of power reserves in grid-forming operation, virtual oscillator control law is modified to dynamically change the set power point during low-resonance conditions to mitigate subsynchronous oscillations. Moreover, to overcome the limited damping capability of adaptive VOC during severe-resonance conditions, a coordinated adaptive adjustment of the grid-side filter inductance based on the modified power set point is designed. The IEEE’s first benchmark model is altered by integration with a 1000 MW grid-forming inverter in a MATLAB R2024b/Simulink environment. The previously proposed dispatchable virtual oscillator control and electronic-based FACT device, i.e., thyristor-controlled series capacitor, are implemented and analyzed under the same test system for the sake of comparison with the designed coordinated strategy. The simulation results are investigated in the time domain and frequency domain, and by calculating performance indices to verify the effectiveness of the proposed scheme. The overall analysis justifies the mitigated, low transient overshoot and high power quality of subsynchronous oscillations by using the designed strategy with varying compensation levels. Full article

Laser Speckle Imaging (LSI) is a non-invasive optical technique used to assess biological activity by detecting dynamic variations in speckle patterns. These patterns exhibit statistical symmetry in static regions, while biological activity induces symmetry breaking that can be captured through the Graphic Absolute Value of Differences (GAVD), producing the activity map $I_{GAVD}$. This work evaluates the effect of four contrast enhancement algorithms: Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Multiscale Morphological Contrast Enhancement (MMCE), and Multiscale Top-Hat Transform with an Open-Close Close-Open (OCCO) filter, applied to intermediate LSI images, with the final activity map used for quantitative evaluation. Each method represents a distinct enhancement paradigm: HE and CLAHE are histogram-based techniques for global and local contrast adjustment, whereas MMCE and OCCO-MTH are morphological approaches that emphasize structural preservation and local detail enhancement. The dataset consisted of images of Phaseolus vulgaris (SP) and Lactuca sativa (SL) seeds. Evaluation was conducted through expert visual inspection and quantitative analysis using contrast, entropy, spatial frequency (SF), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and contrast improvement ratio (CIR). All metrics were computed on $I_{GAVD}$ activity maps, which reflect bioactivity through the disruption of statistical symmetry. Non-parametric statistical tests (Friedman, aligned Friedman, and Quade) revealed that CLAHE and MMCE significantly improved image quality compared to the original images ($p<0.05$). Among the evaluated algorithms, CLAHE increased global contrast by approximately 25% and entropy by 6% relative to the original speckle frames, enhancing the visibility of bioactive regions. MMCE achieved the highest bioactivity contrast ratio (CIR = 0.64), while OCCO-MTH provided the best structural fidelity (SSIM = 0.91) and noise suppression (PSNR = 30.7 dB). These results demonstrate that suitable contrast enhancement can substantially improve the interpretability of LSI activity maps without altering acquisition hardware. This finding is particularly relevant for experimental applications aiming to maximize information quality without modifying acquisition hardware. Full article

Jeju lava (Yongam) seawater, naturally filtered through multi-layered basaltic strata, represents a distinctive marine water type that combines mineral enrichment with isolation from surface contaminants. This study aimed to evaluate its microbial purity and ecological transition during mineral water production. Using 16S rRNA-based metagenomic sequencing, the microbial communities of Yongam seawater, its derived mineral water, and adjacent natural seawater were analyzed and compared. The Yongam seawater microbiome was dominated by Neptuniibacter pectenicola (≈89%), indicating an extremely pristine and selective microbial environment. In contrast, the mineral water exhibited the emergence of Nocardioides marinus and Limnobacter alexandrii, species associated with oxidative metabolism and environmental adaptability, reflecting microbial adjustment to altered ionic and nutrient conditions. Adjacent seawater contained the highest taxonomic diversity, consistent with its dynamic environmental exposure. These results demonstrate the exceptional microbial purity of Jeju Yongam seawater and the ecological stability of its derived mineral water following processing. The pristine nature of Yongam seawater suggests its potential as a naturally uncontaminated marine resource, while the derived mineral water, maintaining a stable microbial profile, may be suitable for safe and functional utilization in marine-based cosmetic, nutraceutical, and biotechnology applications. Full article

Urban ecosystems are structurally and functionally distinct from their natural counterparts, with anthropogenic management potentially altering fundamental ecological processes such as seasonal community dynamics and impairing their sustainability. However, the mechanisms through which management filters plant diversity across seasons remain poorly understood. This study tested the hypothesis that management acts as an abiotic filter, dampening seasonal community variations and increasing biotic homogenization in urban green spaces. In this respect, through an intensive, multi-seasonal case study comparing two Mediterranean urban green spaces under contrasting management regimes, we analysed plant communities across 120 plots over four seasons. Results reveal a contingency cascade under management: while the species composition remains relatively stable (+26% variability, p < 0.001), the demographic success becomes more contingent (+41%, p < 0.001), and the ecological dominance becomes highly stochastic (+90%, p < 0.001). This hierarchy demonstrates that management primarily randomizes which species achieve dominance, in terms of biomass and cover, from a pool of disturbance-tolerant generalists. A 260% increase in alien and cosmopolitan species and persistent niche pre-emption dominance–diversity patterns also indicate biotic homogenization driven by management filters (mowing, trampling, irrigation, and fertilization) that favors species resistant to mechanical stresses and induces a breakdown of deterministic community assembly. These processes create spatially and temporally variable assemblages of functionally similar species, explaining both high structural variability and persistent functional redundancy. Conversely, seasonally structured, niche-based assemblies with clear dominance–diversity progressions are observed in the unmanaged area. Overall, findings demonstrate that an intensive management homogenizes urban plant communities by overriding natural seasonal filters and increasing stochasticity. The study provides a mechanistic basis for sustainable urban green space management, indicating that reduced intervention can help preserve the seasonal dynamics crucial for sustaining biodiversity and ecosystem functioning. Full article

Urbanization reshapes bird communities by filtering species according to their ecological traits, often reducing richness, altering relative abundances, and favoring a subset of functionally tolerant species that dominate urban assemblages. Some native taxa are able to inhabit cities, even using them as stepping stones for range expansion. We examined urban habitat use, microhabitat selection, and potential niche partitioning between two range-expanding thrushes (Austral Thrush [Turdus falcklandii] and Rufous-bellied Thrush [Turdus rufiventris]) in two urban settlements in the Pampas region, Argentina. Using 131 transects across green areas and urbanized zones, we related abundance patterns to habitat features at the transect scale and evaluated microhabitat selection at the individual level. Austral Thrush abundance increased with herbaceous cover, tree cover, and even concrete surfaces, suggesting a relatively high tolerance to fragmented green spaces within dense urban matrices. In contrast, Rufous-bellied Thrush showed a positive association with tree cover, avoided tall buildings, and reached higher abundance in the smaller city, consistent with its recent arrival in the region and preference for less intensively urbanized environments. Microhabitat data revealed marked vertical stratification: Austral Thrush foraged almost exclusively at ground level on grassy or bare substrates, while Rufous-bellied Thrush used trees, shrubs, and vines more frequently. These differences reflect fine-scale resource partitioning that may contribute to reducing niche overlap and favor the coexistence of both species in recently colonized urban areas, while recognizing that such dynamics occur within broader bird assemblages where multiple species interact and compete for space and resources. Our findings highlight that even closely related species can respond divergently to urban structure, and that maintaining structural and substrate heterogeneity within cities may help support native bird diversity. Full article

Urban expansion alters environmental conditions, influencing tree physiology and performance. Urban trees provide cooling, sequester carbon, support biodiversity, filter contaminants, and enhance human health. This study examines how two common urban trees—Norway Maple (Acer platanoides L.) and Little-leaved Linden (Tilia cordata Mill.)—respond to urban site conditions by assessing leaf morphology, stomatal, and gas exchange traits across street and urban park sites in Chicago, IL. Street trees exhibited structural trait adjustments, including smaller leaf area, reduced specific leaf area, and increased stomatal density, potentially reflecting acclimation to more compact and impervious conditions. Norway Maple showed stable photosynthetic assimilation (A), stomatal conductance (g_s), and transpiration (E) across sites, alongside higher intrinsic water-use efficiency (_iWUE), indicating a conservative water-use strategy. In contrast, Little-leaved Linden maintained A and g_s but showed elevated E and _iWUE at street sites, suggesting adaptive shifts in water-use dynamics under street microenvironments. These findings highlight how species-specific physiological strategies and local site conditions interact to shape tree function in cities and underscore the importance of incorporating functional traits into urban forestry planning to improve ecosystem services and climate resilience. Full article

Riparian zones, located at the interface between terrestrial and aquatic systems, are among the most dynamic and ecologically valuable landscapes. These transitional areas play a pivotal role in maintaining environmental health by supporting biodiversity, regulating hydrological processes, filtering pollutants, and stabilizing streambanks. At the core of these functions lie the unique characteristics of riparian soils, which result from complex interactions between water dynamics, sedimentation, vegetation, and microbial activity. This paper provides a comprehensive overview of the origin, structure, and functioning of riparian soils, with particular attention being paid to their physical, chemical, and biological properties and how these properties are shaped by periodic flooding and vegetation patterns. Special emphasis is placed on Mediterranean riparian environments, where marked seasonality, alternating wet–dry cycles, and increasing climate variability enhance both the importance and fragility of riparian systems. A bibliographic study, covering 25 years (2000–2025), was carried out through Scopus and Web of Science. The results highlight that riparian areas are key for carbon sequestration, nutrient retention, and ecosystem connectivity in water-limited regions, yet they are increasingly threatened by land use change, water abstraction, pollution, and biological invasions. Climate change exacerbates these pressures, altering hydrological regimes and reducing soil resilience. Conservation requires integrated strategies that maintain hydrological connectivity, promote native vegetation, and limit anthropogenic impacts. Preserving riparian soils is therefore fundamental to sustain ecosystem services, improve water quality, and enhance landscape resilience in vulnerable Mediterranean contexts. Full article