Search Results (17,585)

Pneumatic artificial muscles, including McKibben-type actuators, offer high power-to-weight ratio, compliance, and inherent safety, but their nonlinear pressure–contraction behavior, hysteresis, saturation, and load-dependent dynamics make accurate position control challenging. This study develops a practical data-driven workflow that derives a branchwise feedforward compensator and an LQI or PID controller from one open-loop characterization experiment. Quasi-static characterization first identifies a conservative control-ready voltage window. A bounded random excitation within this window is replayed with $4\mathrm{s}$ holds to expose terminal and transient behavior. The same experiment supplies branchwise discrete plant models and a feedforward lookup. Two open-loop-derived transient layers, voltage creep compensation and dynamic pressure referencing, are applied to the raw lookup before simulation. Four controller variants are compared on a common simulated closed-loop benchmark built from the identified plant: a feedforward-only baseline, a branchwise proportional–integral–derivative (PID) baseline, a base linear quadratic integral (LQI) controller with displacement and pressure feedback, and a velocity-state LQI extension with a filtered velocity estimate. A multi-metric optimization score balances tracking RMS, settled oscillation, command activity, saturation, and gain magnitude. The score selects the base LQI within the LQI family. The selected gains and transient layers are deployed in a real-time implementation with manually reduced position gains. The controllers are then evaluated on a common reference stream against the physical actuator. Although simulation metrics cannot be transferred directly to the real system, the combined-metric ranking of the controllers remains unchanged. Full article

Polystyrene nanoplastics (PS-NPs; nominal diameter, 100 nm; unmodified and negatively charged) and imidacloprid (IMI) are common freshwater contaminants, but little is known about their combined toxicity in benthic fish. In this study, loaches (Misgurnus anguillicaudatus) were exposed for 21 days to clean water, 100 μg/L PS-NPs, 78 μg/L IMI, or 78 μg/L IMI combined with 25, 50, or 100 μg/L PS-NPs. Each treatment contained 90 fish distributed among three replicate tanks. Survival, hepatic oxidative-stress indices, inflammatory gene expression, histopathology, and intestinal transcriptomic and metabolomic profiles were evaluated. Survival decreased across the co-exposure groups, with a significant overall difference among treatments (log-rank test, p = 0.0027). Hepatic CAT, SOD, and GSH levels decreased, whereas MDA increased, with the strongest changes observed in the higher PS-NP co-exposure groups. Pro-inflammatory genes, including IL-1β, IL-6, IL-8, and TNF-α, were upregulated, whereas IL-4 and IL-10 were downregulated. Histopathological injury of the gill, intestine, and liver was most pronounced in the NIH group. Transcriptomic analysis identified changes in pathways related to digestion, cell-cycle regulation, cholesterol metabolism, and lipid metabolism, while metabolomic analysis revealed alterations in glycerophospholipid, sphingolipid, fatty-acid, and carbohydrate metabolism. HMGCS1, CEL, CYP8B1, APOB, and APOC1 showed treatment-associated expression changes, with APOB displaying a non-linear response across the co-exposure groups. Overall, PS-NP co-exposure was associated with stronger IMI-related adverse responses under the tested conditions and substantial disruption of intestinal lipid homeostasis. Full article

With the rapid expansion of AR/VR-based digital platforms, there is an increasing demand for the automated generation of size-varied 3D shoe assets. However, conventional CAD-based linear scaling and PCA-based global statistical shape models are limited in their ability to capture the non-uniform and locally non-linear deformations observed in insole contours. This study proposes a size-adaptive insole contour generation framework that integrates image-based contour extraction, B-spline parametric representation, and type-specific SVR-based local displacement regression. By decomposing control-point displacements into tangent–normal components, the proposed method directly models non-linear curvature variations associated with size progression without relying on dimensionality reduction. Quantitative evaluations under an eight-fold leave-one-insole-out (LOIO) protocol show that the proposed method achieves a mean Hausdorff distance of 4.73 mm, a Chamfer distance of 1.76 mm, and an IoU of 0.929. It significantly outperforms the no-clustering ablation in both the Hausdorff distance (6.13 mm; $p=0.032$) and IoU ($p=0.033$), as well as the PCA-based kernel ridge regression baseline across all three metrics ($p<0.05$). No statistically significant differences were observed between the proposed method and the ratio scaling, Gaussian process, or thin plate spline baselines ($p>0.05$). PCA-Linear showed a small numerical advantage in the Hausdorff distance (4.16 mm), but the difference was not statistically significant ($p=0.187$). A sensitivity analysis further reveals the existence of a practical control-point density region that balances geometric fidelity and model complexity. This work provides a data-driven parametric approach for standard size-based digital grading automation and establishes a technical foundation for future extension to full 3D shoe mesh generation. Full article

Environmental regulations and stricter emission limits are driving the development of advanced fuel supply systems. Precise fuel metering under varying engine loads has become critical, with modern strategies using multiple injections of very short duration. However, injector behavior, particularly nonlinear flow characteristics, is not fully understood. This study presents an experimental analysis of the flow characteristics Q = f (t_inj) and opening dynamics of five low-pressure gas injectors with different valve system designs. The tests were conducted for injection times t_inj = 0–20 ms. For t_inj > 2.5 ms, the characteristics were very well described by a linear model (R² > 0.995), whereas for t_inj < 2.5 ms, there was a clear deviation from the linear relationship between flow rate and injection time. Analysis of the electrical signals, outlet pressure, and body vibrations made it possible to identify the mechanistic sources of the observed nonlinearity. It was demonstrated that the initial lack of flow results from an electromechanical delay associated with the rise in current and the electromagnetic force required to overcome the spring force, friction, and inertia of the valve element. The subsequent movement of the valve contributing factors a dynamic change in the flow cross-sectional area and, consequently, a nonlinear change in flow rate. Additionally, the change in the position of the valve element affects the inductance of the coil and the nature of the electromagnetic force. Near the maximum lift, the element bounces off the stop, causing a momentary change in its position and a local decrease in flow rate. Only after the valve element’s motion stabilizes does the flow transition to a nearly linear relationship. The response times of the injectors ranged from 0.60 to 1.30 ms, and the times to reach full opening ranged from 1.08 to 2.14 ms, corresponding, respectively, to the onset and the transition to the steady-state region of the characteristic curve. The results indicate that the nonlinearity of the short-time portion of the characteristic has a mechanistic, electromechanical nature and results from the coupling of electromagnetic phenomena, the motion of the valve element, and the varying flow cross-section. This means that accurately modeling it requires taking into account the actual dynamics of valve-opening, particularly in the case of strategies that use short and repeated injection pulses. These findings highlight a significant limitation in fuel dosing precision and emphasize the need to incorporate nonlinear injector models or dynamic corrections in ECU control algorithms—an essential step for further reducing exhaust emissions. Full article

Grounded in a human–land coupling framework, this study takes Purple Mountain, a representative composite urban mountain heritage site, as the research object. It integrates historical archives, field survey data, and multi-source geospatial data, and adopts a set of GIS-based spatial statistical methods, including the nearest neighbour index, kernel density estimation, standard deviational ellipse, coupling coordination degree model, and Geodetector. This paper systematically explores the spatial differentiation, spatiotemporal evolution, human–land coupling patterns, and multidimensional driving mechanisms of four heritage types: geomorphological relics, ritual architecture, modern commemorative heritage, and eco-scenic heritage. The results show that: (1) Heritage resources across Purple Mountain display statistically significant clustering, with ritual architectural heritage exhibiting the highest agglomeration degree; heritage sites form an east–west high-density corridor along the southern foothills, presenting a consistent northeast–southwest spatial orientation. (2) Purple Mountain heritage has undergone multi-stage diachronic evolution. Jointly driven by topographic constraints and socio-cultural forces, its heritage quantity, spatial coverage, and functions fluctuated across dynasties, with an overall expanding trend. (3) A total of 63.07% of the study area’s grid units are in a near-dissonant human–land coupling state, while highly coordinated units are concentrated in the southern core corridor of the Ming Xiaoling Mausoleum, Sun Yat-sen Mausoleum, and Linggu Temple, with remarkable disparities among heritage types in coupling patterns among the four heritage categories. (4) Historical and cultural aggregation density dominates heritage spatial differentiation, while topographic factors show weak explanatory power, and all influencing factor interactions present prominent non-linear enhancement effects. This study establishes a three-level quantitative framework of “spatial pattern—coupling coordination—driving mechanism”, enriching the theoretical framework of human–land coupling for urban mountain heritage, and provides scientific support for refined coordinated governance of mountain heritage embedded in high-density urban environments. Full article

High-density urban renewal requires blue–green infrastructure (BGI) strategies that address surface warming and stormwater runoff under land constraints. This study examined how BGI area and interface configuration regulate water–thermal performance across three purposively selected 100 ha urban fabrics in Beijing. Multi-year Landsat observations and matched 30 m land-cover data quantified radiometric land-surface-temperature (LST) contrasts and distance gradients, while a transparent Python event-runoff model evaluated relative hydrological scenarios using wet-day rainfall-depth quantiles, storage, impervious-area capture, and terrain-informed connectivity. The evidence streams were compared using the scenario cooling–storage index (SCSI), descriptive half-response area (A50), and interface–area substitution ratio (SAR). Stable surface-cooling contrasts occurred in Xicheng and Daxing; Chaoyang supported only exploratory thermal comparison because mapped BGI was sparse. Hydrological outputs represented configuration-dependent simulated runoff-volume responses, not calibrated predictions. In equal-weight 100 ha analyses, bootstrap intervals supported SAR above one across 1–10 ha in Xicheng and 1–3 ha in Daxing, while nested 50 ha windows and thermal weights of 0.2–0.8 shifted transition ranges. Corridor A50 was not identifiable within the tested 1–10 ha range in Daxing, so corridor saturation remains unresolved. Interface compensation was therefore morphology-, scale-, and weighting-dependent. The framework enables conditional comparison of BGI configurations while preserving the distinction between observed thermal and scenario-based hydrological evidence. Full article

Multiple-criteria decision analysis (MCDA) is a branch of operations research concerned with choices based on several quantifiable factors. Here, we focus on high-dimensional markets, in which each available product is described by a large number of features. Taking a probabilistic approach, we define a market as a collection of alternatives in a decision-making scenario governed by a linear utility function. Analytic approximations for the market share and its moments are derived in the limit of a large population and a large number of measured features. We identify a single parameter, termed the degree of subjectivity, that places markets on a continuous spectrum ranging from fully objective to fully subjective. At an intermediate value, the market is competitive in the sense that it maximizes the entropy of the market-share distribution. Empirical analysis of several real markets indicates that they can indeed be classified by this parameter, yielding predictable decision patterns and a unified, relative measure of competitiveness across markets. Simulations involving non-linear utility functions and a trained machine-learning classifier provide preliminary evidence that similar behavior may also arise beyond the linear model, suggesting that the degree of subjectivity may be useful as a diagnostic in some broader multi-feature decision problems. Full article

Background/Objectives: Alginate hydrogels are widely used in tissue engineering; however, their reported properties vary significantly due to differences in formulations and processing conditions, which limits direct comparison across studies. This study aims to systematically evaluate the relative and combined effects of alginate viscosity grade, polymer concentration, and CaCl₂ crosslinking concentration on hydrogel structural, mechanical, and biological behaviour. Methods: Hydrogels were prepared using three commercially available alginates of low, medium, and high viscosity. Polymer concentration (0.5–2% w/v) and CaCl₂ concentration (2.5–10% w/v) were systematically varied under controlled fabrication conditions. Morphology was analysed using scanning electron microscopy, swelling and water uptake were quantified, mechanical properties were assessed via dynamic mechanical analysis, and cell viability was evaluated using Chinese hamster ovary (CHO) cells encapsulation over 20 days. Statistical analysis was performed using two-way ANOVA. Results: Hydrogel properties were governed by non-linear interactions between formulation parameters. CaCl₂ concentration was identified as the dominant factor influencing structural and biological outcomes, with increasing crosslinking concentration reducing pore size, swelling, and water uptake, and decreasing cell viability by up to ~60%. In contrast, polymer concentration and alginate viscosity grade primarily controlled mechanical behaviour, with increased polymer content and viscosity resulting in higher storage and Young’s moduli. Significant interaction effects confirmed that hydrogel properties are not independently tunable but depend on the combined influence of all parameters. Conclusions: Crosslinking concentration dominates structural and biological responses in alginate hydrogels, while polymer parameters modulate mechanical properties within this constraint. These findings establish a formulation-dependent trade-off between mechanical stiffness and cytocompatibility, providing a comparative framework for rational selection of alginate systems based on application-specific requirements. Full article

Wildlife-origin viral diseases are an increasing One Health challenge in Australia, with climate change emerging as a key driver of disease emergence, transmission, and spillover. Australian wildlife, particularly marsupials, birds, and bats, serve as important reservoirs of zoonotic and vector-borne viruses. However, the combined influence of wildlife reservoirs and climate change on viral disease ecology in Australia has not been comprehensively synthesised. This review examines the epidemiology, significance, and climate sensitivity of wildlife-associated viral diseases and evaluates how climate change and variability affect reservoir host ecology, vector biology, viral persistence, and host–pathogen–vector interactions. Thirteen major wildlife-associated viruses of One Health importance were identified, with transmission predominantly involving wildlife reservoirs and mosquito vectors. Temperature and rainfall were the principal climatic drivers influencing the transmission of Ross River virus (RRV), Barmah Forest virus (BFV), Murray Valley encephalitis virus (MVEV), Japanese encephalitis virus (JEV), West Nile virus/Kunjin virus (WNV/KUNV), and avian influenza A virus (AIV). For most mosquito-borne viruses (MBVs), temperature exhibited a non-linear relationship with transmission, while above-average rainfall generally increased outbreak risk by promoting mosquito abundance, habitat availability, and reservoir host activity. Significant knowledge gaps remain in wildlife virome surveillance, climate–disease pathways, and integrated One Health surveillance. Strengthening climate-informed surveillance that integrates wildlife, vectors, genomics, epidemiology, and predictive modelling will improve outbreak preparedness and reduce the risk of viral emergence and spillover in Australia. Full article

The Pinglu Canal, the first river-to-sea canal project since the founding of the People’s Republic of China, reshapes basin-scale ecosystem services by altering land use/land cover, landscape patterns, and soil–water processes. This study assesses spatiotemporal variations in net primary production (NPP), soil conservation, water yield, and nitrogen/phosphorus output in the Pinglu Canal Basin from 2000 to 2024. Hotspot analysis, the interannual fluctuation index, Random Forest and Shapley additive explanations, climate–NPP residual analysis, and Geodetector were integrated. The results indicate that: (1) Over the past 25 years, ecosystem services have generally improved, with NPP increasing significantly and nitrogen/phosphorus outputs declining; northern hilly and low-mountain forests formed stable service supply areas, whereas water yield was more prominent in southern plains and river valleys. Water yield showed the strongest interannual fluctuation, while soil conservation remained relatively stable. (2) Hotspot stability was mainly regulated by population density, normalized difference vegetation index (NDVI), elevation, and precipitation, with evident nonlinear threshold effects. When the NDVI reaches about 0.63, the NPP and nutrient retention capacity are significantly enhanced, indicating that vegetation coverage and community structure can exert their ecological regulation functions effectively after reaching a certain level. (3) During construction, negative NPP disturbances expanded along the canal. The Geodetector results showed that while the explanatory power of population density was enhanced during the construction stage of the Pinglu Canal, precipitation, NDVI, and topographic/hydrothermal conditions remain foundational constraints for ecosystem services spatial differentiation. Furthermore, interactions, such as population–NDVI and population–precipitation, generally manifest as bivariate enhancement. This study supports ecological monitoring, risk warning, and zoned restoration for large linear infrastructure projects. Full article

The economically important species Phyllanthus emblica L. has received increasing attention, yet its climate-driven distributional shifts across China remain unexplored. Using 446 occurrence records and a parameter-optimized MaxEnt model (RM = 0.1, FC = LQ), we forecasted habitat changes under three SSP scenarios (126, 370, 585) across the 2050s, 2070s, and 2090s. Three temperature variables, namely temperature seasonality (Bio4), temperature annual range (Bio7), and mean temperature of the driest quarter (Bio9), collectively contributed 90.2% to the model, confirming that thermal conditions, particularly during dry seasons, dominate habitat suitability. Current suitable habitat covers 86.43 × 10⁴ km², largely confined to South China’s tropical and southern subtropical belts. Future projections indicate non-linear range responses, with a general northwestward centroid shift, although intermediate periods exhibit oscillatory northeastward and southwestward fluctuations. Under the high-emission SSP585 scenario, modest expansion occurs in high-elevation areas of southeastern Tibet, while contraction affects less than 1% of current suitable low-elevation zones. Based on these findings, we recommend designating long-term core conservation areas (southern Yunnan, southern Guangxi, and Hainan), conducting adaptive introduction trials in expansion zones (e.g., Panzhihua, Sichuan), and implementing planting controls in contraction zones (e.g., northern Guizhou). These insights provide a scientific basis for climate-adaptive management of P. emblica in China. Full article

This paper presents a hybrid ARX-LSTM forecasting framework for the Spanish Continuous Intraday Market (MIC), targeting the hourly volume-weighted average price two hours ahead. A correlation analysis over 2024 data identifies Day-Ahead Market and Intraday Auction prices as the dominant predictors, while renewable generation forecasts provide complementary information. The proposed architecture combines a linear autoregressive model with exogenous inputs to capture market-driven dependencies and a Long Short-Term Memory network to model residual nonlinear dynamics. Evaluated using a rolling-origin procedure, the hybrid model achieves an RMSE of 9.02 €/MWh and R² of 0.961, outperforming standalone benchmark models. Full article

To address the quantitative distortion problem caused by the primary internal filtration effect (PIFE) resulting from coexisting substances in the fluorescence detection of aromatic pollutants, this study proposes a multi-component concentration quantification correction model that integrates transmittance absorbance and lateral (90°) fluorescence intensity. Using styrene as the target analyte and anthracene/phenanthrene as representative interferents, by establishing a coupled framework of excitation light decay dynamics and fluorescence emission, the nonlinear PIFE problem was transformed into a linear regression task. The experimental results show that: under the coexistence of anthracene and phenanthrene, the model reduces the detection deviation of styrene from 40 to 63% to within 10%, and the correction accuracy of the three-component mixed system is increased by 3–5 times. This work provides a theoretical framework for fluorescence quantitative analysis in complex systems, and also offers a new method for high-precision online monitoring of aromatic organic pollutants. Full article

Accurate cross-dataset state-of-health prediction for lithium-ion batteries remains challenging due to distribution shifts arising from diverse cathode chemistries, operating temperatures, and charge–discharge protocols across heterogeneous battery fleets. Drawing upon established machine learning paradigms, this study tailors a Domain-Adaptive Mixture-of-Experts (DA-MoE) framework to the battery prognostic context, automatically selecting the optimal domain adaptation strategy for each target domain through a physics-aware, lightweight linear gating network comprising merely 32 learnable parameters. The framework integrates a shared Transformer-based backbone with four adaptation strategies spanning the full spectrum of target-domain information utilization, namely zero-shot transfer, Test-Time Adaptation, Fine-Tuning, and Model-Agnostic Meta-Learning. A comprehensive evaluation on 564 battery cells from seven publicly available datasets under Leave-One-Domain-Out Cross-Validation protocol demonstrates that the proposed framework achieves an average coefficient of determination of 0.864 with perfect oracle strategy alignment under full domain training and maintains competitive generalization at an average R² of 0.795 when each target domain is held out during gating network training. Hard argmax selection consistently outperforms weighted fusion across all seven domains with an average margin of +0.027 in R², confirming that the four adaptation strategies compete rather than cooperate in this application context. A feature ablation analysis identifies sample count as the dominant determinant of strategy selection with performance degradation of ΔR² = −0.182 upon removal, followed by the early-cycle degradation slope and early-cycle nonlinearity index as secondary signals, all of which are computable at deployment time without future ground-truth SOH information. The proposed framework provides a practically deployable solution for battery management systems operating across heterogeneous fleets with minimal computational overhead and strong cross-dataset generalization capability. Full article

The rubber cylinder is the core sealing element of a compression packer, and its structural stability directly determines downhole sealing reliability. The rubber cylinder is made of HNBR, while the central tube, support rings, and casing are made of 35 CrMo steel. During axial compression, the rubber cylinder may undergo localized creasing instability characterized by sharp self-contacting folds, inducing severe stress concentration and degrading sealing performance. This paper presents a systematic finite element investigation of creasing behavior in rubber cylinders, focusing on meshing strategy, interfacial friction, and geometric parameters. A refined meshing strategy is proposed that captures creasing and self-contact, demonstrating that a mesh size less than 0.5 mm is required. A zone-specific friction model distinguishes the tribological roles of different interfaces: increasing friction at the support ring suppresses shoulder protrusion, while increasing friction at the central tube reduces contact stress. For the packer geometries and operating conditions investigated, the critical expansion ratio at which the crease initiates is approximately 1.13. Increasing rubber cylinder length and reducing radial clearance are identified as effective measures to suppress creasing. The logarithmic strain at crease nucleation is approximately −0.66, which is more negative than the Biot linear bifurcation threshold (−0.61). This deeper strain is mechanically attributed to bulging-induced curvature and superimposed bending compression, confirming the crease as a nonlinear instability. This work provides numerical references for the anti-creasing design of packer rubber cylinders under quasi-static setting. Full article