Search Results (2,455)

The disorderly charging of a large number of electric vehicles (EVs) intensifies the operational pressure on the distribution network and negatively impacts the users’ charging experience. This paper proposes an orderly-charging optimization strategy based on the Deep Deterministic Policy Gradient (DDPG) algorithm. First, a comprehensive EV charging behavior model is developed, incorporating regional functional characteristics, vehicle categories, and user behavioral diversity to more accurately reflect real-world charging patterns. Second, a closed-loop control architecture is designed, integrating charging load forecasting, dynamic energy storage regulation, and real-time power allocation. Finally, the DDPG algorithm is applied to enable intelligent dynamic power allocation, which effectively flattens peak–valley load disparities and minimizes user charging costs. The simulation results demonstrate that the proposed strategy significantly enhances distribution network performance and user satisfaction. Specifically, the strategy reduces peak load by 17.08% and achieves a total cost saving of USD 511.49 (17.08%). By considering real-world zones and diverse EV types, this strategy provides substantial engineering value for practical implementation in multi-zone charging systems. Full article

Background: The differentiation of pheochromocytoma (PCC) from other adrenal lesions, particularly in incidentalomas with non-benign radiological characteristics (size > 4 cm or density > 10 HU), remains a clinical challenge. The study aimed to develop and validate an interpretable machine learning (ML) model for pairwise differentiation of PCC from adrenocortical carcinomas (ACCs) and non-functioning adrenal adenomas (NAAs) and to identify the most important clinical features. Methods: We analyzed a dataset of 50 clinical, laboratory, and radiological parameters from 123 patients with histologically verified adrenal tumors (63 PCC, 30 ACC, 30 NAA). Four classifiers—Logistic Regression (LR), Random Forest (RF), Linear Discriminant Analysis (LDA), and Extreme Gradient Boosting (XGBoost)—were trained for binary classification tasks (PCC vs. ACC, PCC vs. NAA, ACC vs. NAA) using a robust nested stratified cross-validation pipeline to ensure generalizability and avoid overfitting. Results: All four models showed strong predictive performance, with discrimination (AUC) more than 0.8. Our analysis, based on the interpretable LR model, identified the key discriminators differentiated PCC from both ACC and NAA: maximum systolic blood pressure, grade 3 hypertension, headache, palpitation, tachycardia, male sex, and concomitant gastric and duodenal ulcers. In contrast, lower back pain and general weakness were strong signs of lower probability of PCC. The tumor density specifically differentiated PCC from NAA, whereas tumor size was an important marker for distinguishing PCC and ACC. Conclusions: We developed robust ML models capable of accurately differentiating PCC from other adrenal tumors in complex cases. The models provide a clinically actionable tool for pre-surgical decision support. Furthermore, the identification of key discriminative features enhances the clinical understanding of PCC and facilitates its differential diagnosis prior to histological verification. Full article

Accurate estimation of Total Phosphorus, referred to as “Phosphorus, Total” (PPUT; µg/L) in the sourced monitoring data, is essential for understanding eutrophication dynamics and guiding water-quality management in inland lakes. However, lake-wide PPUT mapping at high resolution is challenging to achieve using conventional in-situ sampling, and nearshore gradients are often poorly resolved by medium- or low-resolution satellite sensors. This study exploits multi-generation PlanetScope imagery (Dove Classic, Dove-R, and SuperDove; 3–5 m, near-daily revisit) to develop a hybrid AI framework for PPUT retrieval in Lake Simcoe, Ontario, Canada. PlanetScope surface reflectance, short-term meteorological descriptors (3 to 7-day aggregates of air temperature, wind speed, precipitation, and sea-level pressure), and in-situ Secchi depth (SSD) were used to train five ensemble-learning models (HistGradientBoosting, CatBoost, RandomForest, ExtraTrees, and GradientBoosting) across eight feature-group regimes that progressively extend from bands-only, to combinations with spectral indices and day-of-year (DOY), and finally to SSD-inclusive full-feature configurations. The inclusion of SSD led to a strong and systematic performance gain, with mean R² increasing from about 0.67 (SSD-free) to 0.94 (SSD-aware), confirming that vertically integrated optical clarity is the dominant constraint on PPUT retrieval and cannot be reconstructed from surface reflectance alone. To enable scalable SSD-free monitoring, a knowledge-distillation strategy was implemented in which an SSD-aware teacher transfers its learned representation to a student using only satellite and meteorological inputs. The optimal student model, based on a compact subset of 40 predictors, achieved R² = 0.83, RMSE = 9.82 µg/L, and MAE = 5.41 µg/L, retaining approximately 88% of the teacher’s explanatory power. Application of the student model to PlanetScope scenes from 2020 to 2025 produces meter-scale PPUT maps; a 26 July 2024 case study shows that >97% of the lake surface remains below 10 µg/L, while rare (<1%) but coherent hotspots above 20 µg/L align with tributary mouths and narrow channels. The results demonstrate that combining commercial high-resolution imagery with physics-informed feature engineering and knowledge transfer enables scalable and operationally relevant monitoring of lake phosphorus dynamics. These high-resolution PPUT maps enable lake managers to identify nearshore nutrient hotspots, tributary plume structures. In doing so, the proposed framework supports targeted field sampling, early warning for eutrophication events, and more robust, lake-wide nutrient budgeting. Full article

Late-stage sandstone reservoirs often exhibit flow behavior markedly different from early performance, reducing recovery. This study quantifies two-phase flow in Jilin Oilfield sandstone cores to support production optimization. An oil–water displacement apparatus was built and unsteady-state relative-permeability tests were performed on core plugs from multiple well blocks. Permeability, pressure gradient, water saturation, and displacement efficiency were tracked over a range of injection multiples. Water-phase relative-permeability curves classify three seepage types: concave-down (12 cores, 2.10–46.17 mD), linear (7 cores, 1.58–12.23 mD), and concave-up (3 cores, 8.74–30.73 mD). Permeability is strongly negatively correlated with irreducible water saturation (R² = 0.84) and positively correlated with residual oil saturation (R² = 0.58), two-phase flow interval (R² = 0.51), and movable oil saturation (R² = 0.89); other relationships are weak. An increasing pressure gradient markedly improves displacement efficiency in low-permeability cores. Higher injection multiples further raise displacement efficiency across all permeability classes, but gains diminish with increasing permeability. Displacement efficiency also increases with water cut when used as a flooding-stage indicator in these unsteady-state tests. Full article

Knowledge distillation achieves model compression by training a lightweight student network to mimic the output distribution of a larger teacher network. However, when the teacher becomes overconfident, its sharply peaked logits break the scale symmetry of supervision and induce high-variance gradients, leading to unstable optimization. Meanwhile, research that focuses only on final-logit alignment often fails to utilize intermediate semantic structure effectively. This causes weak discrimination of student representations, especially under class imbalance. To address these issues, we propose Scale Calibration and Pressure-Driven Knowledge Distillation (SPKD): a one-stage framework comprising two lightweight, complementary mechanisms. First, a dynamic scale calibration module normalizes the teacher’s logits to a consistent magnitude, reducing gradient variance. Secondly, an adaptive pressure-driven mechanism refines student learning by preventing feature collapse and promoting intra-class compactness and inter-class separability. Extensive experiments on CIFAR-100 and ImageNet demonstrate that SPKD achieves superior performance to distillation baselines across various teacher–student combinations. For example, SPKD achieves a score of 74.84% on CIFAR-100 for the homogeneous architecture VGG13-VGG8. Additional evidence from logit norm and gradient variance statistics, as well as representation analyses, proves the fact that SPKD stabilizes optimization while learning more discriminative and well-structured features. Full article

Recycling water offers a powerful way to lower the environmental water impact of mining activities. Pressure-retarded osmosis (PRO) represents a promising pathway for simultaneous water reuse and clean energy generation from salinity gradients. In this study, the performance of a thin-film nanocomposite (TFN) membrane containing functionalized multi-walled carbon nanotubes (fMWCNTs) within a polyacrylonitrile (PAN) support layer, followed by polydopamine (PDA) surface modification, was investigated under a PRO operation using pretreated gold mining wastewater as the feed solution. Unlike most previous studies that rely on synthetic feeds, this work evaluates the membrane performance under a PRO operation using a real mining wastewater stream. The membrane with fMWCNTs and PDA exhibited a maximum power density of 25.22 W/m² at 12 bar, representing performance improvements of 23% and 68% compared with the pristine thin-film composite (TFC) and commercial cellulose triacetate (CTA) membranes, respectively. A high water flux of 75.6 L·m⁻²·h⁻¹ was also obtained, attributed to enhanced membrane hydrophilicity and reduced internal concentration polarization. The optimized membrane, containing 0.3 wt% fMWCNTs in the support layer and a PDA coating on the active layer, produced a synergistic enhancement in the PRO performance, resulting in a lower reverse salt flux and an improved flux–selectivity trade-off. Furthermore, the ultrafiltration (UF) and nanofiltration (NF) pretreatment effectively reduced the hardness and ionic content, enabling a stable PRO operation with real mining wastewater over a longer period of time. Overall, this study demonstrates the feasibility of achieving both reusable water and enhanced osmotic power generation using modified TFN membranes under realistic mining wastewater conditions. Full article

Currently, research on the hydrodynamic characteristics of artificial reef deployment still faces challenges such as insufficient environmental coupling, but accurate simulation of the deployment process holds significant engineering importance for optimizing deployment efficiency and ensuring reef stability. This study employs the Smoothed Particle Hydrodynamics (SPH) method to establish a 3D numerical model, focusing on the influence of key parameters—inflow velocity and water entry angle—on the hydrodynamic characteristics of cubic artificial reef deployment. The results indicate that under flow velocities of 0.4–0.5 m/s, pressure fluctuations are relatively minor, with peak pressure gradients below 15 kPa/m, exhibiting a gradual trend, while particle concentration remains high, and drag gradually increases. At flow velocities of 0.6–0.8 m/s, the maximum pressure at the bottom reaches up to 35 kPa, with low-pressure areas at the tail dropping to −10 kPa; particle concentration decreases compared to conditions at 0.4–0.5 m/s; settling time extends from 8.4 s to 12 s, representing a 42% increase. Under different water entry angles, drag varies nonlinearly with the angle, reaching its maximum at 20° and its minimum at 25°, with a reduction of approximately 47% compared to the maximum. The anti-sliding safety factor and anti-overturning safety factor are used to assess the stability of the cubic reef placed on the seabed. Across different inflow velocities, the anti-sliding safety factor of the cubic artificial reef significantly exceeds 1.2, whereas the anti-overturning safety factor is below 1.2 at 0.4 m/s but exceeds 1.2 at velocities of 0.5 m/s and above, indicating that the reef maintains stability under the majority of these flow conditions. Our findings provide a scientific basis for the deployment process, site selection, and geometric design of cubic artificial reefs, offering valuable insights for the precise deployment and structural optimization of artificial reefs in marine ranching construction. Full article

Background: Functional diversity of aquatic macrophytes can provide mechanistic insight into community assembly beyond taxonomic diversity metrics. Aims: We tested whether functional diversity indices can help infer the dominant processes shaping macrophyte communities along hydromorphological and physicochemical gradients, and whether these signals remain interpretable after accounting for species richness. Methods: We surveyed aquatic macrophytes in the Dnipro–Orilsky Nature Reserve (Ukraine) during four field campaigns in 2024 (453 sampling sites), measured key environmental characteristics, and calculated functional diversity indices from plant trait data. Results: The indices showed distinct responses consistent with environmental filtering, dispersal limitation related to reduced hydrological connectivity, and biotic interactions. Anthropogenic degradation was associated with functional simplification and shifts toward opportunistic trait syndromes. Conclusions: A complementary set of functional diversity indices can distinguish major community assembly mechanisms in macrophyte assemblages and supports more robust assessment of ecosystem condition under combined natural and anthropogenic pressures. Full article

Widely used in treating oil mist aerosols generated from metalworking processes, conventional gas–liquid coalescing filters face drawbacks such as increased energy consumption, performance limitations, and shortened service life due to high steady-state pressure drop. To address these issues, this study proposes an innovative design for a filter based on wettability-regulated gradient pore structure. Using glass fiber filter media with different pore size parameters as the substrate and incorporating an intermediate mesh layer, a three-layer filtration structure of “large-pore filtration layer—mesh layer—small-pore filtration layer” was constructed. The surface wettability of each layer was regulated by a self-developed surface modifier, producing gradient pore structure filters with different wettability configurations. The variations in key performance parameters, including steady-state pressure drop, filtration efficiency, saturation, and service life, were systematically evaluated for these configurations. Experimental results demonstrated that the configuration with an “oleophobic large-pore filtration layer—mesh layer—oleophilic small-pore filtration layer” yielded the best overall performance. Analysis based on the “jump-channel” model indicated that the gradient pore structure achieves progressive droplet filtration and optimizes droplet coalescence and capture through wettability differences. Consequently, while maintaining exceptional filtration efficiency (>99%), this configuration significantly reduces the steady-state pressure drop by over 34% and effectively extends the service life by more than 66%. This wettability-regulated gradient pore structure provides a novel technical pathway for addressing the challenges of balancing pressure drop and filtration efficiency, as well as extending the service life, in gas–liquid coalescing filters. Full article

Lost circulation in oil-based drilling fluids (OBDFs) remains difficult to mitigate because particulate lost circulation materials depend on bridging/packing and gel systems for aqueous media often lack OBDF compatibility and controllable in situ sealing. A dual-precursor oil–water biphasic metal–organic supramolecular gel enables rapid in situ sealing in OBDF loss zones. The optimized formulation uses an oil-phase to aqueous gelling-solution volume ratio of 10:3, with 2.0 wt% Span 85, 12.5 wt% TXP-4, and 5.0 wt% NaAlO₂. Apparent-viscosity measurements and ATR–FTIR analysis were used to evaluate the effects of temperature, time, pH, and shear on MOSG gelation. Furthermore, the structural characteristics and performances of MOSGs were systematically investigated by combining microstructural characterization, thermogravimetric analysis, rheological tests, simulated fracture-plugging experiments, and anti-shear evaluations. The results indicate that elevated temperatures (30–70 °C) and mildly alkaline conditions in the aqueous gelling solution (pH ≈ 8.10–8.30) promote P–O–Al coordination and strengthen hydrogen bonding, thereby facilitating the formation of a three-dimensional network. In contrast, strong shear disrupts the nascent network and delays gelation. The optimized MOSGs rapidly exhibit pronounced viscoelasticity and thermal resistance (~193 °C); under high shear (380 rpm), the viscosity retention exceeds 60% and the viscosity recovery exceeds 70%. In plugging tests, MOSG forms a dense sealing layer, achieving a pressure-bearing gradient of 2.27 MPa/m in simulated permeable formations and markedly improving the fracture pressure-bearing capacity in simulated fractured formations. Full article

Thermal stability is a key factor in determining the phenomena of deep chlorophyll maxima (DCM) in stratified lakes, as it mediates the vertical balance between light and nutrients required by phytoplankton. While it is well established that lake stratification is sensitive to latitude gradients, the ways in which thermal stability modulates DCM characteristics (i.e., depth, thickness, and concentration) and nutrient–chlorophyll relationships across different latitude classifications remain unclear. In this study, data on thermocline depth, DCM feature, and water quality parameters were collected from 88 globally distributed stratified lakes. Our findings indicate that (1) higher-latitude lakes exhibit strong thermoclines, with light and nitrogen serving as the primary drivers of thermal stratification; (2) in high-latitude lakes, surface chlorophyll a concentrations are more tightly linked to total phosphorus than that at DCM depth in low-latitude lakes; and (3) structural equation modeling (SEM) results demonstrate that higher-latitude lakes form shallower and thinner DCM structures, where low light levels contribute to reduced peaks in algal biomass. These findings provide valuable insights for the management of stratified lakes facing the dual pressures of climate change and eutrophication. Full article

The abnormal pore pressure is possibly generated through a comprehensive process including geological, physical, geochemical, or hydrodynamic factors. Generally, all mechanisms are abstracted as four typical categories, namely skeleton deformation, pore fluid mass increase, temperature change, and other mechanisms. Traditional methods for evaluating reservoir overpressure often only consider the influence of a single factor and lack mathematical methods for a comprehensive explanation of reservoir overpressure. Therefore, this article is dedicated to proposing a comprehensive mathematical model, incorporating effective mean stress, shear stress, temperature, pore collapse-induced plastic deformation, time-dependent skeleton deformation, and pore fluid mass increase, to account for pore pressure generation in sedimentary basins. The effects of various factors on pore pressure generation are analyzed, and case studies are conducted. Main conclusions are drawn that both the compressibility of sediments and the porosity at the surface control the pore pressure generation rate and vertical gradient. The pore pressure generation rate and vertical gradient in deep formation are larger than those in shallow formation. The higher compressibility and lower porosity at the surface lead to a greater pore pressure generation rate and vertical gradient during the skeleton deformation. The lower compressibility and a lower porosity at the surface can cause a higher pore pressure change rate and vertical gradient during the pore pressure mass increase and temperature change. By comparison, mechanical loading plays a more important role in pore pressure generation rate and vertical gradient than aquathermal pressuring. Full article

This study demonstrates the positive impact of scatterometer wind-based bogus vortex initialization on forecasts of Typhoon Doksuri (2023). In this scheme, the NCEP analysis vortex in the initial conditions is replaced with a bogus vortex. A regression model links the scatterometer wind-derived 34 kt wind radius with the radius of maximum sea-level pressure gradient, a required parameter in Fujita’s bogus formula. The cyclonic circulation center identified in the scatterometer wind field is designated as the typhoon center. The resulting bogus vortex provides a more realistic representation of the low-level circulation, center location, and intensity. Numerical experiments with the WRF model, configured with two-way nested domains (9–3 km) and 115 vertical levels below the model top at 1 hPa, show that the scatterometer wind-bogus scheme effectively improves the initial vortex position and minimum sea-level pressure, slightly enhances track forecasts, and substantially improves intensity forecasts, particularly during rapid intensification and weakening stages of Typhoon Doksuri over the western North Pacific. Furthermore, comparisons with Himawari-9 AHI infrared observations indicate that forecasts with bogus vortex initialization better reproduce the eye, eyewall, and spiral rainband structures than forecasts without it. These results underscore the value of scatterometer observations for improving typhoon forecasts. Full article

Anthropogenic stressors increasingly threaten freshwater biodiversity, with fish communities particularly sensitive to habitat modification. This study evaluates how river morphological alterations influence fish assemblage structure in 114 mountain rivers of the Southern Carpathians, assessing whether such changes cause species loss or drive shifts toward disturbance-tolerant communities. Using a multi-scale analytical framework integrating non-metric multidimensional scaling, redundancy analysis, and variance partitioning, we quantified the contributions of spatial, catchment, and local habitat variables to community patterns. Spatial- and catchment-scale factors explained the largest variance in fish assemblages (12% in adults and 17% in small-bodied fish). However, morphological pressures proved significant in shaping community structure with clear ecological consequences. Weirs and embankments reduced abundances of rheophilic species (flow-dependent) by 27–38%, potamodromous by 23–42%, invertivorous by 26–49%, benthic by 40–46% and lithophilic taxa by 27–41%, indicating the loss of habitat specialists. In contrast, limnophilic taxa (preferring slow or still water) increased 25 times, phytophilic spawners by 17–41%, and tolerant species by 10%, reflecting biotic homogenization. By integrating a trait-based approach, this study highlights functional shifts that may be overlooked in species-level assessments. It underscores the need to couple local habitat restoration with catchment-scale management to conserve fish biodiversity and maintain natural ecological gradients in mountain river systems. Full article

Background/Objectives: The vestibular labyrinth is classically viewed as a sensor of low-frequency head motion—linear acceleration for the otoliths and angular velocity/acceleration for the semicircular canals. However, there is now substantial evidence that air-conducted sound (ACS) can also activate vestibular receptors and afferents in mammals and other vertebrates. This sound sensitivity underlies sound-evoked vestibular-evoked myogenic potentials (VEMPs), sound-induced eye movements, and several clinical phenomena in third-window pathologies. The cellular and biophysical mechanisms by which a pressure wave in the cochlear fluids is transformed into a vestibular neural signal remain incompletely integrated into a single framework. This study aimed to provide a narrative synthesis of how ACS activates the vestibular labyrinth, with emphasis on (1) the anatomical and biophysical specializations of the maculae and cristae, (2) the dual-channel organization of vestibular hair cells and afferents, and (3) the encoding of fast, jerk-rich acoustic transients by irregular, striolar/central afferents. Methods: We integrate experimental evidence from single-unit recordings in animals, in vitro hair cell and calyx physiology, anatomical studies of macular structure, and human clinical data on sound-evoked VEMPs and sound-induced eye movements. Key concepts from vestibular cellular neurophysiology and from the physics of sinusoidal motion (displacement, velocity, acceleration, jerk) are combined into a unified interpretative scheme. Results: ACS transmitted through the middle ear generates pressure waves in the perilymph and endolymph not only in the cochlea but also in vestibular compartments. These waves produce local fluid particle motions and pressure gradients that can deflect hair bundles in selected regions of the otolith maculae and canal cristae. Irregular afferents innervating type I hair cells in the striola (maculae) and central zones (cristae) exhibit phase locking to ACS up to at least 1–2 kHz, with much lower thresholds than regular afferents. Cellular and synaptic specializations—transducer adaptation, low-voltage-activated K⁺ conductances (K_LV), fast quantal and non-quantal transmission, and afferent spike-generator properties—implement effective high-pass filtering and phase lead, making these pathways particularly sensitive to rapid changes in acceleration, i.e., mechanical jerk, rather than to slowly varying displacement or acceleration. Clinically, short-rise-time ACS stimuli (clicks and brief tone bursts) elicit robust cervical and ocular VEMPs with clear thresholds and input–output relationships, reflecting the recruitment of these jerk-sensitive utricular and saccular pathways. Sound-induced eye movements and nystagmus in third-window syndromes similarly reflect abnormally enhanced access of ACS-generated pressure waves to canal and otolith receptors. Conclusions: The vestibular labyrinth does not merely “tolerate” air-conducted sound as a spill-over from cochlear mechanics; it contains a dedicated high-frequency, transient-sensitive channel—dominated by type I hair cells and irregular afferents—that is well suited to encoding jerk-rich acoustic events. We propose that ACS-evoked vestibular responses, including VEMPs, are best interpreted within a dual-channel framework in which (1) regular, extrastriolar/peripheral pathways encode sustained head motion and low-frequency acceleration, while (2) irregular, striolar/central pathways encode fast, sound-driven transients distinguished by high jerk, steep onset, and precise spike timing. Full article