Search Results (7,435)

Knowledge tracing (KT) is a core technology in intelligent tutoring systems that predicts students’ future responses by analyzing their historical interaction sequences. Although existing deep learning-based KT models achieve high predictive accuracy, their “black-box” nature severely hinders practical deployment in educational scenarios. To balance predictive performance and interpretability, this paper proposes AMDKT, an interpretable dual-stream Transformer model grounded in the Student Proficiency–Item Competency Matching (SPIM) mechanism. The model employs two parallel Transformer branches to separately model the temporal evolution of student proficiency and the competency demands of each item and defines the discrepancy between their outputs as “proficiency surplus.” A non-negative regularization loss is further introduced to constrain the proficiency surplus to be non-negative for correctly answered samples, thereby embedding pedagogical rules into the optimization objective and ensuring that the model outputs conform to educational cognitive priors. Experiments on five public datasets show that AMDKT achieves AUC performance comparable to the state-of-the-art AKT model, and obtains statistically superior results against DKT, DKVMN, DEEP-IRT, and DIMKT on most datasets, with relatively weaker performance observed on the KDD Cup 2010 dataset. Ablation studies verify the effectiveness of each component, and visualization results demonstrate that AMDKT produces smooth, coherent, and interpretable student proficiency trajectories, providing a fine-grained tool for quantifying individual learning progress. Therefore, AMDKT offers a feasible solution for applications such as weak knowledge point localization, adaptive exercise recommendation, and learning risk warning. Full article

Background: Sarcopenia, systemic inflammation, and malnutrition are established poor prognostic factors in renal cell carcinoma (RCC). This study investigated the utility of a novel preoperative score combining psoas muscle density (PMD)—an imaging-based indicator of muscle quality—and the albumin–bilirubin (ALBI) grade—a blood-based biomarker of liver reserve and systemic nutritional status—for predicting disease-free survival (DFS) and overall survival (OS) in patients undergoing curative surgery for RCC. Methods: This retrospective observational study included 274 patients with non-metastatic RCC treated with radical or partial nephrectomy. Preoperative computed tomography was utilized to measure PMD, defining “low PMD” as a value below the sex-specific median (males: 47.75 Hounsfield Units [HU]; females: 46.25 HU). “Worsened ALBI” was defined as an ALBI grade ≥ 2. Patients were stratified into three risk categories: Score 0 (both normal, n = 122), Score 1 (either abnormal, n = 114), and Score 2 (both abnormal, n = 38). Results: Kaplan–Meier analysis revealed a highly significant, stepwise decline in both DFS and OS as the risk score increased (log–rank p < 0.001 and p = 0.004, respectively). Multivariate Cox regression identified the combined risk score as a robust, independent prognostic factor for DFS (Score 1: HR 1.93, 95% CI 1.11–3.37, p = 0.020; Score 2: HR 3.58, 95% CI 1.82–7.02, p < 0.001). Furthermore, after adjusting for age and comorbidities, the score remained an independent predictor of poor OS (Score 1: HR 2.35, 95% CI 1.08–5.13, p = 0.032; Score 2: HR 3.01, 95% CI 1.16–7.82, p = 0.024). The combined model synergistically enhanced risk stratification accuracy compared to evaluating either factor independently. Conclusions: The concurrent presence of preoperative low PMD and a worsened ALBI grade is a powerful, independent predictor of poor prognosis in localized RCC. Derived solely from routine preoperative imaging and laboratory tests, this straightforward scoring system effectively captures the structural and immunometabolic dimensions of cancer cachexia and host vulnerability. This tool can significantly aid in personalizing postoperative surveillance strategies and identifying high-risk patients who may warrant closer postoperative surveillance or who might be considered as high-risk candidates for adjuvant therapy discussions. Full article

This work proposes a stochastic fractional power-law model for currency exchange rate forecasting. The model incorporates nonlocal temporal effects through the Caputo fractional derivative and nonlinear scaling dynamics via a power-law formulation, providing a flexible framework for representing complex temporal behavior in financial time series. Model parameters are estimated by fitting an explicit analytical calibration expression, constructed under the fractional chain-rule framework adopted in this study, to historical currency exchange-rate data using nonlinear optimization techniques. This expression is employed specifically as a tractable parameterization for model calibration and is not claimed as a general exact closed-form solution of the nonlinear problem involving the standard Caputo derivative. The forecasting stage is carried out through numerical simulations using a FORK-2-based stochastic discretization, with stochastic perturbations incorporated via a Wiener process. The proposed methodology is applied to daily EUR/MXN and EUR/CAD exchange rate series, and forecasts are generated through multiple Monte Carlo simulations over different prediction horizons. The results suggest that the fractional formulation can improve forecasting accuracy when longer training periods are employed. In addition, the nonlinear power-law structure increases the model’s flexibility and provides additional structural flexibility. Nevertheless, the integer-order formulation generally exhibits greater predictive stability, largely independent of the training period and the inclusion of the nonlinear power-law extension. Full article

Optical coherence tomography (OCT) is a high-resolution and non-contact optical imaging and sensing modality that provides depth-resolved cross-sectional visualization of retinal microstructures. It plays an important role in the assessment of retinal diseases, including age-related macular degeneration (AMD) and diabetic macular edema (DME). However, automated OCT image classification commonly relies on fully supervised models that require large-scale expert annotations, which are costly and time-consuming because of the complex layered anatomy and subtle pathological patterns present in retinal OCT images. To reduce annotation dependence, this study proposes a self-supervised representation learning framework with local dimensionality regularization for retinal OCT image classification. The proposed method estimates the local intrinsic dimensionality of learned representations and incorporates it into an asymptotic Fisher-Rao regularization objective to mitigate local dimensional degeneration and preserve fine-grained structural information. Logarithmic scaling and geometric averaging are further introduced to reduce sensitivity to outliers and improve optimization stability. Experiments on three independent OCT datasets achieved classification accuracies of 94.35%, 92.48%, and 92.56%, respectively, demonstrating competitive performance compared with mainstream self-supervised methods. These results demonstrate that explicitly modeling local feature geometry can improve the discrimination of sensor-acquired OCT images while reducing reliance on manual annotations, providing an effective approach for intelligent analysis of biomedical optical imaging data. Full article

During high-speed multi-joint coordination, the nonlinear joint-to-cylinder mapping may increase the velocity and jerk peaks of the hydraulic cylinders, while simultaneous multi-cylinder motion may cause flow-peak superposition and increase the risk of exceeding the pump-flow limit. Addressing the limitations of traditional joint-space trajectory planning, which struggles to balance actuator-space smoothness, nonlinear inverse kinematics robustness, and multi-cylinder total-flow constraints, this paper proposes a multi-objective trajectory-planning method in the hydraulic-cylinder actuator space. First, a kinematic model is constructed based on the modified Denavit–Hartenberg method and hydraulic-cylinder closed-loop cosine mapping to evaluate effective moment arms and transmission sensitivity. Subsequently, a method combining Monte Carlo global search and Levenberg–Marquardt local iteration is adopted to solve inverse kinematics without explicitly computing the Moore–Penrose pseudoinverse of the Jacobian. On this basis, analytic quintic splines incorporating asymmetric perturbation terms are constructed, and a non-dominated sorting genetic algorithm II bi-objective optimization model for minimizing the motion time and the maximum absolute jerk in the actuator space is established, incorporating the total-flow hard constraint. Simulation results demonstrate that the motion time of the compromise solution is 7.71 s, the maximum absolute jerk in the actuator space is 22.94 mm/s³, and the total flow throughout the process is lower than 105 L/min. This method keeps the planned total-flow demand within the pump-flow capacity and reduces the risk that the planned actuator speeds cannot be maintained because of insufficient flow supply, providing a planning basis for the stable operation of heavy-duty hydraulic demolition robots. Full article

With the increasing conflict between economic and environmental objectives in power systems, the economic emission dispatch (EED) problem has become a highly constrained, nonlinear, and strongly non-convex multi-objective optimization problem due to valve-point effects and nonlinear constraints such as network losses. To address this challenge, this paper proposes an improved multi-objective Grey Wolf Optimizer (IMOGWO). The proposed method enhances search performance through four strategies: a hybrid initialization scheme combining circle chaotic mapping and Latin hypercube sampling to improve population diversity, a dream-inspired group perturbation mechanism to strengthen global exploration, a nonlinearly decreasing convergence factor to dynamically balance exploration and exploitation, and a hybrid update strategy incorporating Lévy flight to avoid local optima. Experimental results demonstrate that IMOGWO can effectively balance the trade-off between generation cost and pollutant emissions while exhibiting competitive performance in terms of convergence behavior, solution quality, and stability. Full article

Urban freshwater ecosystems are exposed to multiple anthropogenic pressures, but their effects on macroinvertebrate communities may vary depending on waterbody type and surrounding land use structure. This study analysed macroinvertebrate communities in three waterbody types of the Belgrade functional urban area. Land use was classified into agricultural, artificial, and semi-natural areas, and evaluated using LUI and HHI indices. A total of 187 macroinvertebrate taxa were recorded, indicating high diversity despite the urban setting. Community composition differed among waterbody types, with non-wadeable rivers characterised by a high proportion of Oligochaeta, wadeable rivers by a greater contribution of insects, and canals by the dominance of crustaceans. Land use further influenced community structure: semi-natural areas were associated with a higher proportion of crustaceans, artificial areas with Chironomidae, and agricultural areas with Oligochaeta. Alpha diversity was highest in wadeable rivers, while beta diversity showed that compositional differences were driven by species turnover. SPEAR indices indicated stress-related differences among waterbody types. CCA showed that community variation was associated with conductivity, temperature, oxygen saturation, pH, BOD, TOC, AOX, and phosphate. Overall, macroinvertebrate communities in the Belgrade urban area are shaped by the combined effects of waterbody type, land use structure, and local environmental conditions. Full article

Seed transfer guidelines are used in ecological restoration to reduce the maladaptation risk from non-local genotypes. Researchers often examine second-generation populations under uniform conditions to isolate adaptation from environmental responses. However, in outcrossing species, interpreting these traits may be challenging if uncontrolled gene flow and recombination among provenances influence offspring phenotypes. We compared seed germination and seedling traits of the wind-pollinated grass Festuca vaginata, a dominant species of open sand grasslands in Hungary, across seed transfer zones (STZs) and localities. We used a two-generation common garden experiment with uncontrolled gene flow. Our results reveal that under common garden cultivation, the transgenerational stability of population differentiation is traitspecific. While locality effects on germination disappeared in the second generation, phenotypic variation in biomass and leaf length persisted, suggesting that shared environments homogenize germination faster than vegetative traits. As wind-pollinated species often exhibit weak regional genetic structuring, STZs may not capture the primary axis of phenotypic variation in specific traits. While not invalidating the use of STZs, our findings suggest that seed sourcing strategies should, if feasible, consider locality-level variation when using wind-pollinated grasses for species reintroduction. Full article

Transitioning cultivated land from a narrowly defined production resource into a coordinated multifunctional asset is a cornerstone of agricultural modernization. Despite this imperative, current land utilization in China remains largely constrained by a singular production focus, resulting in suboptimal multifunctionality. Although digitally driven agricultural new quality productive forces (ANQPFs) are posited as a critical catalyst for functional restructuring, empirical evidence quantifying their relationship with cultivated land multifunctionality (CLM) remains limited. To examine the association between ANQPF and CLM, this study employs panel data from 115 prefecture-level cities across the Yangtze River Basin, China, spanning the period 2013–2023. The empirical results indicate that ANQPF is significantly and positively associated with CLM. These associations are robust to a battery of robustness checks, and endogeneity tests provide additional evidence supportive of a positive association. Transmission pathway analysis suggests that the positive association operates through three pathways: increasing the main business revenue of agricultural product processing enterprises above a designated size, expanding the number of agricultural technology patents, and improving the level of agricultural socialized services. Subgroup analyses, supplemented by Chow tests of coefficient equality, reveal that these associations tend to be larger in non-major grain-producing regions, areas with lower per capita GDP, and the upper and middle reaches of the Yangtze River Basin. Threshold effect analysis further demonstrates that once ANQPF exceeds a certain level, the positive association exhibits diminishing marginal returns; a similar but weaker pattern is observed for leading enterprises. These findings provide policy implications for developing ANQPF in accordance with local conditions and for synergistically optimizing CLM patterns. Full article

This study presents an electrothermal coating approach for synthesizing cell-imprinted polymers (CIPs) on metallic microwires through localized resistive heating-induced polymerization. Imprinted polymers (IPs) are robust, cost-effective synthetic affinity materials widely used in sensing applications. However, conventional fabrication methods, including bulk and suspension polymerization, often lack spatial control, producing non-specific polymerization, heterogeneous coatings, and reduced sensor reproducibility. Electrochemical polymerization provides improved spatial control but requires specialized instrumentation and restricts monomer selection. Here, applying direct current (DC) to metallic microwires immersed in a prepolymer solution generated localized Joule heating, enabling controlled in situ polymerization and uniform coatings while minimizing undesired bulk polymerization. By optimizing the applied current and polymerization time, CIP coatings with tunable thicknesses were fabricated on gold-coated microwires. Under optimized conditions, ~6 µm thick coatings were imprinted using Salmonella templates. Scanning electron microscopy revealed bacteria-shaped cavities consistent with template removal and the formation of imprinted cavities. Rebinding experiments demonstrated enhanced bacterial capture, with CIP-coated microwires achieving ~70% capture efficiency, compared to 22% for bare microwires and 33% for non-imprinted polymer (NIP) controls. These results support the effectiveness of the proposed method for localized polymerization and demonstrate the enhanced capture of the template species by CIP-coated microwires relative to bare microwires and NIP-coated controls. Full article

Natural fractures dominate fracturing effects and well production. Conventional fracturing fails to fully activate multi-scale fractures, and most simulations adopt homogeneous rock assumptions, lacking systematic analysis on fracture propagation and seepage evolution in heterogeneous fractured formations, while the natural fracture activation mechanism of pulsed fracturing remains unclear. This work constructs a pulsed fracturing model for heterogeneous fractured rock to simulate fracture growth and permeability evolution in intact rock and formations with various fracture attitudes, revealing the coupled laws of fracture propagation and seepage change. Results show rock mechanical heterogeneity determines fracture network complexity in intact rock; pulsed loading slows main fracture breakthrough and stimulates microcracks, creating a near-well dense and far-well sparse fracture distribution. Single-orientation fractures drive directional asymmetric fracture extension following near-weak-zone priority, with matrix heterogeneity merely causing local fracture deflection. Multi-orientation fractures display layered activation: low-angle and near-well fractures initiate first, and cross-fracture interactions raise network complexity and coverage. Fracture growth is jointly governed by weak bedding, pulse fatigue damage and matrix properties. Pulsed fracturing achieves remote non-contact activation of natural fractures, with fracture-permeability evolution showing strong spatiotemporal coupling; main fracture breakthrough triggers abrupt permeability growth. Serving as both mechanical weak planes and preferential flow paths, natural fractures build composite seepage systems of main channels and micro flow zones. This study provides theoretical support for parameter optimization and efficient permeability improvement in fractured reservoirs. Full article

Blast-induced traumatic brain injury is a prevalent and underreported condition, particularly among military service members, for whom effective prophylactic interventions are lacking. Nano-pulsed laser therapy (NPLT) is a non-invasive neuromodulatory approach that delivers short pulses of near-infrared light to generate optoacoustic effects within cerebral tissue and has previously demonstrated therapeutic benefit following TBI. In this study, we evaluated whether a single pre-exposure application of NPLT could confer protection against neurological, cognitive, and cellular sequelae of mild blast injury. Adult male Sprague-Dawley rats were randomized to receive NPLT or Sham treatment 24 h prior to either Sham or mild blast exposure using the Advanced Blast Simulator. Neurological reflexes and vestibulomotor function were assessed on post-injury days (PIDs) 1–5, while cognitive performance was evaluated using the Morris Water Maze on PIDs 13–17. Histological analyses of microglia, astrocytes, and myelination were performed on PID 17. A single mild blast did not significantly alter gross neurological function but was associated with deficits in fine motor coordination and cognitive performance. Pre-exposure NPLT modestly attenuated blast-associated fine motor dysfunction, with a significant improvement compared with TBI on PID 4. In the Morris Water Maze, TBI animals exhibited significantly increased latency compared with Sham on PIDs 13 and 17, whereas NPLT + TBI animals did not significantly differ from Sham across the testing period, consistent with preservation of cognitive performance. Histological responses were regionally heterogeneous: NPLT alone produced distinct glial alterations, while NPLT + TBI animals exhibited a mixture of treatment- and injury-associated responses rather than uniform normalization to uninjured controls. NPLT did not prevent localized blast-associated reductions in corpus callosum myelin staining. In naive animals, NPLT significantly increased hippocampal brain-derived neurotrophic factor (BDNF) mRNA expression 24 h after treatment. A single pre-injury application of NPLT was associated with functional resilience following mild blast exposure despite persistent and regionally heterogeneous histopathological alterations. Increased hippocampal BDNF 24 h after NPLT, together with region-specific glial changes following NPLT in the absence of injury, demonstrates that a single treatment produces sustained molecular and cellular effects before blast exposure. These findings are consistent with the hypothesis that prophylactic NPLT establishes an altered pre-injury biological state that may modify the subsequent response to blast and support further investigation of NPLT as a prophylactic strategy and of the mechanisms underlying NPLT-associated preconditioning. Full article

Photovoltaic converters operate under varying climatic conditions and non-ideal grid regimes, but factor importance is often assessed either through isolated local metrics or through pooled operating data that hide regime shifts and interaction effects. This study develops a hierarchical framework for sensitivity analysis of operating profiles of grid-connected PV converters under climatic and grid uncertainty. A compact operating-profile formulation is introduced that relates solar radiation, cell and ambient temperature, grid voltage, load, and selected design/control parameters to active power, efficiency, power factor, harmonic distortion, DC bus ripple, clipping behavior, and thermal headroom. The proposed workflow combines local normalized sensitivities for fast ranking around nominal conditions, Morris screening for factor reduction, and Sobol/Saltelli variance-based indices for global prioritization under uncertainty. The framework is demonstrated on a 100 kW synthetic reduced-order benchmark representing a three-phase two-level grid-connected PV inverter with an LCL filter. To clarify the scope of validity, the reduced-order model is cross-checked against switching-level simulations for representative nominal, clipping-prone, high-temperature and grid-stress operating windows. The results show that factor importance is not universal, but depends on the selected KPI, operating regime and uncertainty scenario. In the considered benchmark, grid voltage, cell temperature and equivalent thermal resistance are the dominant total-effect contributors, while the strongest second-order contribution appears between grid voltage and filter inductance under grid-stress conditions. The proposed framework is therefore intended as a reproducible, regime-aware sensitivity workflow rather than as a universal ranking of PV converter parameters. Full article

We develop a reaction–diffusion–chemotaxis model for spatial tumour–immune–chemokine dynamics that couples logistic tumour growth, immune-mediated killing, chemokine-dependent immune recruitment, chemotactic migration, and signal production. For the non-dimensional system, we establish local classical solvability, nonnegativity, a uniform tumour-density bound, and global mass estimates for the immune and chemokine components. The tumour-free equilibrium is stable precisely when the baseline immune-control index satisfies ${\sigma }_0/\delta >1$, whereas positive homogeneous coexistence is characterized by a scalar nonlinear equation. Linearization in the Neumann Laplacian eigenbasis yields a mode-dependent cubic dispersion relation, showing that chemotaxis does not alter the tumour-invasion threshold but can destabilize homogeneous coexistence through a finite-wavelength oscillatory instability above a critical sensitivity ${\xi }_c$. A conservative finite-volume discretization with upwind chemotactic fluxes and implicit backward differentiation formula time integration is used to test these predictions. Numerical experiments recover the analytical equilibria and growth rates, identify the dominant unstable mode, reproduce the transition to spatial heterogeneity, and quantify the effects of immune recruitment, decay, and diffusion on the stability boundary. Grid-refinement, mass-balance, residual, and nonnegativity diagnostics support the computational reliability of the results. Full article

Background: Executive functions (EFs) decline with aging, impacting functional independence. While resistance training (RT) is a promising non-pharmacological intervention, the optimal modality and duration for cognitive benefits remain unclear. Flywheel RT (FRT) imposes greater motor control and attentional demands than traditional RT (TRT), potentially enhancing EFs. Objective: To compare the effects of a 36-week FRT versus TRT program on executive function and serum insulin-like growth factor 1 (IGF-1) levels in healthy older women. Methods: This parallel-group randomized controlled trial allocated 64 older women (overall mean age 66.8 ± 4.6 years; FRT group: 68.0 ± 4.8 years; TRT group: 65.5 ± 4.1 years) to either FRT (n = 25) or TRT (n = 21) for two weekly sessions over 36 weeks. Executive function was assessed using the Victoria Stroop Test (inhibitory control), Digit Span Test (working memory), and Trail Making Test (cognitive flexibility). Serum IGF-1 was quantified via chemiluminescence. Intention-to-treat analyses with ANCOVA were performed. Results: After 36 weeks, both groups showed significant within-group improvements in inhibitory control (mean reduction from pre to post: FRT: 15.2 ± 10.4 to 14.8 ± 7.4 s; TRT: 20.4 ± 11.8 to 15.6 ± 7.3 s; p = 0.028, ηp² = 0.38) and working memory (Digit Span Forward: FRT: 6.2 ± 1.7 to 7.9 ± 2.0; TRT: 6.7 ± 1.5 to 8.7 ± 1.8; p < 0.001, ηp² = 0.84). The B/A ratio of the Trail Making Test improved significantly more in the FRT group (73.0 ± 65.2 to 87.5 ± 68.1 s) compared to the TRT group (67.3 ± 54.1 to 137.7 ± 83.6 s; group × time interaction: p = 0.001, ηp² = 0.13). No significant changes in serum IGF-1 concentrations were observed in either group (FRT: 112.9 ± 25.4 to 115.3 ± 21.3 ng/mL; TRT: 104.7 ± 27.5 to 103.0 ± 28.9 ng/mL; p = 0.88, ηp² = 0.002). Adherence was high (only 4 out of 46 participants did not complete all 72 sessions), and no severe adverse events were reported. Conclusions: Flywheel training appears particularly effective for enhancing cognitive flexibility, likely due to its higher cognitive-motor demands. The absence of significant changes in circulating IGF-1 suggests that the observed cognitive benefits may not be mediated by systemic endocrine pathways, although this does not exclude the possibility of local central nervous system adaptations or changes in other neurotrophic factors not assessed in this study. Full article