Search Results (457)

Retention of foundational knowledge is critical in dental education, yet the implications of Ebbinghaus forgetting curve are often overlooked. This study examined how well dental students retained core periodontal concepts and how confident in their knowledge evolved over the dental school years. A standardized 20-question multiple-choice exam was administered to 120 students at six points: before and after each of three progressive periodontal courses. Students also rated their confidence for each answer. Data from 113 students were analyzed. During the first-year course, mean scores increased significantly from 42–46% to 76–81%. After a four-month gap, second-year pre-course scores dropped to 66–70% and then rebounded to 84–89% post-course. In the third year, despite a nine-month gap, pre-course scores remained relatively high (78–81%) and rose slightly to 80–83% post-instruction. Performance and confidence improved significantly over time (p < 0.001), and a strong positive correlation was observed between them (r = 0.87, p < 0.001). These findings support the value of repeated reinforcement in promoting long-term knowledge retention and increasing student confidence. Full article

To address the problem of inaccurate matching between personalized exercise recommendations and learners’ mastery of knowledge concepts/learning abilities, we propose the Dynamic Multidimensional Memory Augmented knowledge tracing model (DMMA). This model integrates a dynamic key-value memory neural network with the Ebbinghaus Forgetting Curve. By incorporating time decay factors and knowledge concept mastery speed factors, it dynamically adjusts knowledge update intensity, effectively resolving the insufficient personalized recommendation capabilities of traditional models. Experimental validation demonstrates its effectiveness: on Algebra 2006–2007, DMMA achieves 82% accuracy, outperforming CRDP-KT by 6%, while maintaining 53–55% accuracy for cold-start users (0–5 interactions), which is 25% higher than CoKT. The model’s integration of the Ebbinghaus forgetting curve and K-means-based concept classification enhances adaptability. Genetic algorithm optimization yields a diversity score of 0.79, with 18% higher 30-day knowledge retention. The FastDTW–Sigmoid hybrid similarity calculation (weight transition 0.27–0.88) ensures smooth cold-start adaptation, while novelty metrics reach 0.65 via random-forest-driven prediction. Ablation studies confirm component necessity: removing time decay factors reduces accuracy by 2.2%. These results validate DMMA’s superior performance in personalized education. Full article

Soil erosion in granite-derived weathering mantles poses serious threats to slope stability and ecological sustainability in subtropical regions. While polyacrylamide (PAM) is widely used to improve soil structure, its concentration-dependent effects on multiple soil functions remain unclear. This study developed a multifunctional Soil Function Index (SFI) framework integrating erosion resistance (SFI₁), water regulation (SFI₂), and ecological function (SFI₃) to evaluate the effects of PAM application (0‰, 1‰, 3‰, 5‰, 7‰) on gully-prone sandy material. Herein, SFI₁ was quantified through shear strength (τ) and soil erodibility (K_r); SFI₂ was assessed using soil hydraulic parameters (saturated hydraulic conductivity and water retention curves) and SFI₃ was derived from the grass root system analysis. The results showed that SFI₁ and SFI₂ increased nonlinearly with PAM concentration, reaching maximum values of 0.983 and 0.980 at 7‰, with K_r reduced by 77.3% and non-capillary porosity (NAP) increased by 8.1%. In contrast, SFI₃ peaked at 0.858 under 3‰ and declined sharply to 0.000 at 7‰, due to micropore over-compaction, reduced aeration, and limited plant-available water. The total SFI exhibited a unimodal trend, with a maximum of 0.755 at 3‰, beyond which ecological suppression offset physical improvements. These findings demonstrate that PAM modifies soil multifunctionality through pore-scale restructuring, inducing function-specific thresholds and trade-offs. A PAM concentration of 3‰ is identified as optimal, achieving a balance between erosion control, hydrological performance, and ecological viability in the management of subtropical granite-derived sandy slopes. Full article

Desert plants host specialized microbiomes that contribute to their survival under extreme conditions; yet, niche and specific microbial dynamics remain poorly understood. In this study, we used 16S rRNA amplicon sequencing to characterize the bacterial communities associated with Leptadenia pyrotechnica, which is a desert-adapted shrub. Five representative sample types were analyzed: rhizospheric soil from a non-arid adjacent location (control; S1); rhizospheric soil from the arid site (S4); and stem endosphere from the arid site (S5, S6, and S7). For each sample type, three biological replicates were collected from different healthy plants to ensure independence. Sequencing yielded high-quality datasets (89,000–134,000 reads/sample) with ASV retention ratios of 68–80%, confirming their sufficient depth for diversity profiling. Alpha diversity indices revealed a markedly greater richness in rhizospheric samples (e.g., S1 Shannon: 3.04; 530 ASVs) than in endosphere samples (Shannon < 1.0; ASVs ≤ 33), consistent with known gradients in desert plant microbiomes. Rarefaction curves confirmed the completeness of sampling. Beta diversity analyses, including PCoA and hierarchical clustering, showed clear segregation between rhizospheric and endophytic communities, indicating strong compartment-specific structuring. The rhizosphere was dominated by Actinobacteria (48%), Proteobacteria (32%), and Firmicutes (10%), whereas the stem endosphere was enriched in Proteobacteria (45%) and Actinobacteria (40%). Taxonomic profiling revealed that Bacillota and Actinomycetota dominated rhizospheric soils, including Bacillus licheniformis, while stem tissues were enriched in Cyanobacteriota and Alphaproteobacteria, suggesting host-driven filtering. Genera such as Cupriavidus, Massilia, and Noviherbaspirillum were exclusive to the rhizosphere, while Paracholeplasma appeared uniquely in stem sample S6. Archaea and rare phyla were nearly absent. The current findings indicate that L. pyrotechnica harbors distinct microbial assemblages in rhizospheric and endophytic niches, reflecting microhabitat-driven selection. These microbial communities may contribute to host resilience by harboring taxa with potential stress-tolerance traits, offering insights for microbiome-informed strategies in arid land restoration. Full article

Crop leaves naturally exhibit a curved morphology and primarily display bending deformation and vibrational responses under wind load. The curved surface structure of leaves plays a critical role in the deposition and retention of pesticide droplets. In this study, wind tunnel experiments combined with high-speed photography and digital image analysis were conducted to systematically investigate the curvature and flexibility distributions of three typical crop leaves: walnut, peach, and pepper, across a range of wind speeds. The results indicate that with increasing wind speed, all three types of leaves gradually transition from smooth, uniform bending to a multi-peak pattern of pronounced local curvature, with increasingly prominent nonlinear deformation characteristics. Moreover, once the wind speed exceeds the critical threshold of 6 m/s, the primary deformation region generally shifts from the leaf base to the tip. For example, the maximum curvature of walnut leaves increased from 0.018 mm⁻¹ to 0.047 mm⁻¹, and that of pepper leaves from 0.031 mm⁻¹ to 0.101 mm⁻¹, both more than double their original values. In addition, all three types of leaves demonstrated a distinct structural gradient characterized by strong basal rigidity and high apical flexibility. The tip flexibility values exceeded 1.5 × 10⁻⁵, 4 × 10⁻⁴, and 5.6 × 10⁻⁴ mm⁻²·mN⁻¹ for walnut, peach, and pepper leaves, respectively. These findings elucidate the mechanical response mechanisms of non-uniform flexible crop leaves under wind-induced bending and provide a theoretical basis and data support for the optimization of air-assisted spraying parameters. Full article

The mesoscopic-scale discrete element method (DEM) modeling approach demonstrated high compatibility with macroporous recycled concrete (MRC). However, existing DEM models failed to adequately balance modeling accuracy and computational efficiency for recycled aggregate (RA), replicate the three distinct interfacial transition zone (ITZ) types and pore structure of MRC, or establish a systematic calibration methodology. In this study, PFC 3D was employed to establish a randomly polyhedral RA composite model and an MRC model. A systematic methodology for parameter testing and calibration was proposed, and compressive test simulations were conducted on the MRC model. The model incorporated all components of MRC, including three types of ITZs, achieving an aggregate volume fraction of 57.7%. Errors in simulating compressive strength and elastic modulus were 3.8% and 18.2%, respectively. Compared to conventional concrete, MRC exhibits larger strain and a steeper post-peak descending portion in stress–strain curves. At peak stress, stress is concentrated in the central region and the surrounding arc-shaped zones. After peak stress, significant localized residual stress persists within specimens; both toughness and toughness retention capacity increase with rising porosity and declining compressive strength. Failure of MRC is dominated by tension rather than shear, with critical bonds determining strength accounting for only 1.4% of the total. The influence ranking of components on compressive strength is as follows: ITZ (new paste–old paste) > ITZ (new paste–natural aggregates) > new paste > old paste > ITZ (old paste–natural aggregates). The Poisson’s ratio of MRC (0.12–0.17) demonstrates a negative correlation with porosity. Predictive formulas for peak strain and elastic modulus of MRC were established, with errors of 2.6% and 3.9%, respectively. Full article

Large language models (LLMs) pose significant challenges to content authentication, as their sophisticated generation capabilities make distinguishing AI-produced text from human writing increasingly difficult. Current detection methods suffer from limited information capture, poor rate–distortion trade-offs, and vulnerability to adversarial perturbations. We present CurveMark, a novel dual-channel detection framework that combines probability curvature analysis with dynamic semantic watermarking, grounded in information-theoretic principles to maximize mutual information between text sources and observable features. To address the limitation of requiring prior knowledge of source models, we incorporate a Bayesian multi-hypothesis detection framework for statistical inference without prior assumptions. Our approach embeds imperceptible watermarks during generation via entropy-aware, semantically informed token selection and extracts complementary features from probability curvature patterns and watermark-specific metrics. Evaluation across multiple datasets and LLM architectures demonstrates 95.4% detection accuracy with minimal quality degradation (perplexity increase < 1.3), achieving 85–89% channel capacity utilization and robust performance under adversarial perturbations (72–94% information retention). Full article

Nanoparticle floating gate (NPFG) transistors have gained attention as synaptic devices due to their discrete charge storage capability, which minimizes leakage currents and enhances the memory window. In this study, we propose and evaluate a mesh-type floating gate transistor (Mesh-FGT) designed to emulate the characteristics of NPFG transistors. Individual floating gates with dimensions of 3 µm × 3 µm are arranged in an array configuration to form the floating gate structure. The Mesh-FGT is composed of an Al/Pt/Cr/HfO₂/Pt/Cr/HfO₂/SiO₂/SOI (silicon-on-insulator) stack. Threshold voltages (Vth) extracted from the transfer and output curves followed Gaussian distributions with means of 0.063 V (σ = 0.100 V) and 1.810 V (σ = 0.190 V) for the erase (ERS) and program (PGM) states, respectively. Synaptic potentiation and depression were successfully demonstrated in a multi-level implementation by varying the drain current (I_ds) and Vth. The Mesh-FGT exhibited high immunity to leakage current, excellent repeatability and retention, and a stable memory window that initially measured 2.4 V. These findings underscore the potential of the Mesh-FGT as a high-performance neuromorphic device, with promising applications in array device architectures and neuromorphic neural network implementations. Full article

The dynamic non-equilibrium effect (DNE) describes the non-unique character of saturation–capillary pressure relationships observed under static, steady-state, or monotonic hydrodynamic conditions. Macroscopically, the DNE manifests as variations in soil hydraulic characteristic curves arising from varying hydrodynamic testing conditions and is fundamentally governed by soil matrix particle size distribution. Changes in the DNE across porous media with discrete particle size fractions are investigated via stepwise drying experiments. Through quantification of saturation–capillary pressure hysteresis and DNE metrics, three critical signatures are identified: (1) the temporal lag between peak capillary pressure and minimum water saturation; (2) the pressure gap between transient and equilibrium states; and (3) residual water saturation. In the four experimental sets, with the finest material (Test 1), the peak capillary pressure consistently precedes the minimum water saturation by up to 60 s. Conversely, with the coarsest material (Test 4), peak capillary pressure does not consistently precede minimum saturation, with a maximum lag of only 30 s. The pressure gap between transient and equilibrium states reached 14.04 cm H₂O in the finest sand, compared to only 2.65 cm H₂O in the coarsest sand. Simultaneously, residual water saturation was significantly higher in the finest sand (0.364) than in the coarsest sand (0.086). The results further reveal that the intensity of the DNE scales inversely with particle size and linearly with wetting phase saturation (Sw), exhibiting systematic decay as Sw decreases. Coarse media exhibit negligible hysteresis due to suppressed capillary retention; this is in stark contrast with fine sands, in which the DNE is observed to persist in advanced drying stages. These results establish pore geometry and capillary dominance as fundamental factors controlling non-equilibrium fluid dynamics, providing a mechanistic framework for the refinement of multi-phase flow models in heterogeneous porous systems. Full article

This study aims to predict the purpose of the use of IC card data in LRT immediately after its opening by means of a questionnaire survey and to understand the changes in the number of commuters to better understand the growth in LRT commuter ridership, which has not been fully clarified in Japan. Furthermore, to assess long-term commuter retention for LRT systems, the analysis revealed the following three points. First, a discriminant analysis based on a national PT survey revealed that commuting and leisure or business activities can be classified with high accuracy. Second, it was found that commuter numbers increased immediately after opening, while the number of leisure or business users decreased in the first few months after opening and then leveled off. Third, the increase in the number of commuters was modeled using a logistic curve, and the annual rate of change in ridership was predicted to be less than 1% in the first three to four years after opening. Full article

This review provides a comprehensive overview of the closed-form expressions developed for estimating the soil water retention curve (SWRC) from 1964 to the present. Since the concept of the SWRC was introduced in 1907, numerous closed-form functions have been proposed to describe the relationship between soil matric suction and volumetric water content, each with distinct strengths and limitations. Given the variability in SWRC shapes influenced by soil texture, structure, and organic matter, models in the form of sigmoidal, multi-exponential, lognormal, hyperbolic, and hybrid functions have been designed to fit experimental SWRC data. Based on the number of adjustable parameters, these models are categorized into three main groups: three-, four-, and five-parameter models. They can also be classified as one-, two-, or three-segment functions depending on their structural complexity. A review of the developed models indicates that most are effective in representing the SWRC between the residual and saturated water content range. To capture the full range of the SWRC, hybrid functions have been proposed by combining traditional models. This review presents and discusses these models in chronological order of publication. Full article

Occupational exposure to commercial formic and acetic acids through dermal contact and inhalation during rubber sheet processing poses significant health risks to workers. Additionally, the use of these acids contributes to environmental pollution by contaminating water sources and soil. This study investigates the potential of three types of wood vinegar—derived from para-rubber wood, bamboo, and eucalyptus—obtained through biomass pyrolysis under anaerobic conditions, as sustainable alternatives to formic and acetic acids in the production of ribbed smoked sheets (RSSs). The organic constituents of each wood vinegar were characterized using gas chromatography and subsequently mixed with fresh natural latex to produce coagulated rubber sheets. The physical and chemical properties, equilibrium moisture content, and drying kinetics of the resulting sheets were then evaluated. The results indicated that wood vinegar derived from para-rubber wood contained a higher concentration of acetic acid compared to that obtained from bamboo and eucalyptus. As a result, rubber sheets coagulated with para-rubber wood and bamboo vinegars exhibited moisture sorption isotherms comparable to those of sheets coagulated with acetic acid, best described by the modified Henderson model. In contrast, sheets coagulated with eucalyptus-derived vinegar and formic acid followed the Oswin model. In terms of physical and chemical properties, extended drying times led to improved tensile strength in all samples. No statistically significant differences in tensile strength were observed between the experimental and reference samples. The concentration of acid was found to influence Mooney viscosity, the plasticity retention index (PRI), the thermogravimetric curve, and the overall coagulation process more significantly than the acid type. The drying kinetics of all five rubber sheet samples displayed similar trends, with the drying time decreasing in response to increases in drying temperature and airflow velocity. Full article

To understand the mechanisms underlying species assemblage along salt gradients in intertidal zones, we measured the xylem hydraulic vulnerability curves (HVCs), leaf water potential (ψ), stomatal conductance (g_s), specific leaf area (SLA), and wood density (WD) for six mangrove species of Avicennia marina, Bruguiera gymnorrhiza, Aegiceras corniculatum, Kandelia obovata, Sonneratia apetala, and Sonneratia caseolaris. We found the following: (1) A. marina and B. gymnorhiza had the most negative P₅₀ (water potential at which 50% of hydraulic conductivity was lost), while S. caseolaris and S. apetala had the least negative P₅₀, indicating different resistance to embolism in xylem; (2) P₅₀ and P₈₈ (water potential at which 88% of hydraulic conductivity was lost) declined with increasing salinity from the onshore to offshore species, as their water regulation strategy meanwhile transitioned from isohydry to anisohydry; (3) B. gymnorhiza had smaller SLA but larger hydraulic safety margin (HSM), implying potentially higher capacity of water retention in leaves and lower risk of hydraulic failure in xylem. These results suggest that hydraulic traits play an important role in shaping the salt-driven niche segregation of mangroves along intertidal zones. Our research contributes to a more comprehensive understanding of the hydraulic physiology of mangroves in salt adaption and may facilitate a general modeling framework for examining and predicting mangrove resilience to a changing climate. Full article

Inkjet printing has become a primary technique for manufacturing flexible and conformal electronics due to its digital control, design flexibility, and material compatibility. However, its direct deposition nature results in weak adhesion between metal films and substrates, as it mainly relies on van der Waals or capillary forces, which severely limits its broader application in these fields. To address this limitation, we proposed an additive–subtractive manufacturing method based on a water-soluble sacrificial layer. First, the sacrificial material is inkjet-printed onto the substrate. Then, ion sputtering is employed to bombard the surface with high-energy ions, enabling metal atoms to embed into the substrate and form a strongly adhered conductive layer. Finally, the substrate is immersed in water, dissolving the sacrificial layer and detaching the undesired metal, thereby achieving selective retention of the conductive pattern. Experimental results demonstrate that the optimized water-soluble material, with tailored viscosity and surface tension, enables a patterning resolution of ±10 μm. The adhesion strength of the sputtered metal layer is 5.2 times greater than that of inkjet-printed silver nanoparticles. This method was further applied to fabricate conductive patterns on a curved surface with a 91 mm radius confirming its feasibility and adaptability for complex 3D surfaces. Full article

Heat storage in compacted soil embankments is a promising technology in energy geotechnics, but its impact on the thermo-hydraulic behavior of unsaturated soils remains insufficiently understood. This paper investigates coupled heat and moisture transfer in unsaturated soil under different thermal conditions using a new bottom-heating method. The thermo-hydraulic response is monitored along the soil column and compared to an isothermal drying test. Variations in suction and water content were analyzed to determine water retention curve and to derive unsaturated hydraulic conductivity using the instantaneous profile method. The water retention curve exhibited deviations under thermal conditions, with reduced water contents observed only at intermediate suctions. Unsaturated hydraulic conductivity decreased significantly at moderate suctions but increased by up to one order of magnitude at high suctions. Heat-driven moisture redistribution was examined through flux calculations, highlighting that vapor-phase transport contributed significantly, up to 88%, to the upward water migration. These findings contribute to a better understanding of thermo-hydraulic interactions in unsaturated soils, which is essential for optimizing thermal storage applications in compacted embankments. Full article