Search Results (3,951)

Background/Objectives: Accurate identification of dental malocclusions from routine clinical photographs can be time-consuming and subject to interobserver variability. A YOLOv11-based deep learning approach is presented and evaluated for automatic malocclusion detection on routine intraoral photographs, testing the hypothesis that training on a structured annotation protocol enables reliable detection of multiple clinically relevant malocclusions. Methods: An anonymized dataset of 5854 intraoral photographs (frontal occlusion; right/left buccal; maxillary/mandibular occlusal) was labeled according to standardized instructions derived from the Index of Orthodontic Treatment Need (IOTN) A total of 17 clinically relevant classes were annotated with bounding boxes. Due to an insufficient number of examples, two malocclusions (transposition and non-occlusion) were excluded from our quantitative analysis. A YOLOv11 model was trained with augmented data and evaluated on a held-out test set using mean average precision at IoU 0.5 (mAP50), macro precision (macro-P), and macro recall (macro-R). Results: Across 15 analyzed classes, the model achieved 87.8% mAP50, 76.9% macro-P, and 86.1% macro-R. The highest per-class AP₅₀ was observed for Deep bite (98.8%), Diastema (97.9%), Angle Class II canine (97.5%), Anterior open bite (92.8%), Midline shift (91.8%), Angle Class II molar (91.1%), Spacing (91%), and Crowding (90.1%). Moderate performance included Anterior crossbite (88.3%), Angle Class III molar (87.4%), Head bite (82.7%), and Posterior open bite (80.2%). Lower values were seen for Angle Class III canine (76%), Posterior crossbite (75.6%), and Big overjet (75.3%). Precision–recall trends indicate earlier precision drop-off for posterior/transverse classes and comparatively more missed detections in Posterior crossbite, whereas Big overjet exhibited more false positives at the chosen threshold. Conclusion: A YOLOv11-based deep learning system can accurately detect several clinically salient malocclusions on routine intraoral photographs, supporting efficient screening and standardized documentation. Performance gaps align with limited examples and visualization constraints in posterior regions. Larger, multi-center datasets, protocol standardization, quantitative metrics, and multimodal inputs may further improve robustness. Full article

To promote waste tyre resource utilisation and reduce environmental pressure, this study prepared five stone sample groups using waste tyre rubber fibre (RF) as a modifier, combined with blast furnace slag, fly ash, carbide slag, and calcium chloride, with RF contents of 0%, 6%, 10%, 14%, and 18%. Working performance was analysed via density, fluidity, and water separation rate tests, while mechanical properties and failure mechanisms were explored through uniaxial compression tests, acoustic emission (AE) monitoring, and SEM microstructure observations. Results showed that as RF content increased, slurry density and fluidity decreased nonlinearly, water separation rate first rose then fell, and uniaxial compressive strength dropped significantly (64.97% lower at 18% RF than 0%). Failure mode shifted from shear to tensile–shear mixed failure, AE signal activity weakened, energy release gentled, and crack propagation was delayed. Microstructurally, 6–10% RF ensured uniform fibre dispersion, blocking microcracks and optimising interfacial zones, while 14–18% RF caused agglomeration and pore defects. The optimal grouting material ratio was determined as 10% RF, blast furnace slag: fly ash = 4:1, 40% carbide slag, 1% calcium chloride, and a 0.7 water–cement ratio (total solid component 100%). Full article

With the deepening of oil and gas exploration and development into ultra-deep and ultra-high pressure environments, the pressure of wellhead equipment is becoming higher and higher. The sealing performance of the casing head hanger is directly related to the safety and reliability of the whole wellhead equipment. Firstly, based on the numerical simulation method, the sealing performance of three different metal seal rings—H-type, X-type, and U-type—under 175 MPa working conditions is compared and analyzed. The simulation results show that the sealing performance of the H-type metal sealing ring is better than that of the X-type and U-type. The parametric analysis method is further used to study the influence of the structural parameters of the convex radius and the bottom angle of the H-ring on its sealing performance. The results show that when the convex radius is designed to be 3 mm, and the bottom angle is 90°, the effective contact width reaches 5.91 mm, and the contact uniformity is the best. Finally, based on the H-type metal sealing ring sample trial-produced with optimized parameters, a 175 MPa nitrogen medium sealing pressure test was completed on an 8 1/8” all-metal sealed mandrel casing hanger. The test results show that the system pressure drop is 0.7 MPa during the 5-min pressure stabilization process, which has good sealing reliability. Full article

Interactions between surface water and groundwater in arid regions regulate their response to climate and human impacts. In the salar systems of the Altiplano-Puna plateau (Bolivia, Chile, Argentina), understanding how surface waters connect to groundwater is crucial for accurate modeling and assessment. This study introduces new data and analysis using subsurface thermal profiles and modeling to identify flow patterns and possible surface water links. We document, to our knowledge, for the first time in the literature, deep-seated cooling of the subsurface caused by extreme evaporation rates. The subsurface is cooled by 4–5 degrees Celsius below the mean annual air temperature to depths greater than 50 m, even though groundwater inflow waters are elevated by 10 degrees °C due to geothermal heating. Three thermal zones are observed along the southern edge of Salar de Atacama, with temperature dropping from 28 °C to about 12 °C over 2.5 km. A 2D numerical model of groundwater and heat flow was developed to test various hydrological scenarios and understand the factors controlling the thermal regime. Two flow scenarios at the southern margin were examined: a diffuse flow model with uniform flow and flux to the surface and a focused flow model with preferential discharge at a topographic slope break. Results indicate that the focused flow scenario matches thermal data, with warm inflow water discharging into a transition zone between freshwater and brine, cooling through evaporation, re-infiltration, and surface flow, then re-emerging near lagoons at the halite nucleus margin. This research offers valuable insights into the groundwater hydraulics in the Salar de Atacama and can aid in monitoring environmental changes causally linked to lithium mining and upgradient freshwater extraction. Full article

European plum (Prunus domestica) orchards in the Kashi region, Xinjiang, China, suffer from fruit brown spot disease. The disease typically appears as red spots on the fruit surface that expand into brown necrotic lesions; affected fruit flesh can shrink, and fruits can harden and drop. We isolate and identify pathogens associated with this disease in this plum from five Kashi counties. Of 210 fungal isolates obtained through standard tissue isolation, Alternaria accounted for 84.8%, with the remainder comprising species of Aspergillus (9.5%), Diplodia (3.3%), and Neoscytalidium (2.4%). Using PCR amplification and sequencing of five loci, pathogens were identified using multi-gene phylogenetic analyses, combined with observations of colony and spore morphology. Multi-locus sequences of Alternaria isolates were highly homologous to those of the Alternaria alternata type strain, and we refer them to an A. alternata species complex. Pathogenicity tests confirm that Alternaria isolates reproduce brown spot symptoms on European plum fruits. By demonstrating that Alternaria is the primary pathogen causing brown spot disease in European plum in Xinjiang, we clarify both the fungal species composition and taxonomic placement of the dominant pathogen associated with this disease. Full article

This study introduces a synergistic drop-casting, sonication, and thermal treatment (DSTT) method for fabricating multi-walled carbon nanotube (MWCNT)-coated conductive cotton fabrics. The process produced uniform MWCNT networks with a minimum sheet resistance of 0.072 ± 0.004 kΩ/sq. at ~30 wt.% loading. Scanning electron microscopy confirmed an improved MWCNT network. Reproducibility was demonstrated for different fabric sizes, with resistance values remaining consistent within experimental errors. Stability tests showed only minor changes in sheet resistance after 16 weeks of ambient storage and periodic manual bending. Compared to conventional methods such as room-temperature drying, vacuum drying, and sonication alone, DSTT consistently performed better, yielding fabrics with lower resistance and more reliable conductivity. These results highlight DSTT as a reproducible and scalable method for producing conductive cotton fabrics suitable for smart textiles and wearable electronics. Full article

The mechanical behavior of carbon-fiber-reinforced polymer (CFRP) laminates manufactured using plasma-assisted solvolysis recycled fibers was evaluated experimentally through a comprehensive mechanical testing campaign. The plasma-assisted solvolysis parameters were selected based on an earlier sensitivity analysis. Prepregs made from both virgin and recycled carbon fibers were fabricated via a hand lay-up process and manually stacked to produce unidirectional laminates. Longitudinal tension tests, longitudinal compression tests, and interlaminar shear strength (ILSS) tests were performed to assess the fundamental mechanical response of the recycled laminates and quantify the retention of mechanical properties relative to the virgin-reference material. Prior to mechanical testing, all laminates underwent ultrasonic C-scan inspection to assess manufacturing quality. While both laminate types exhibited generally satisfactory quality, the recycled-fiber laminates showed a higher density of defects. The recycled laminates preserved around 80% of their original tensile strength and maintained an essentially unchanged elastic modulus. Compressive strength was more susceptible to imperfections introduced during remanufacturing, with the recycled laminates exhibiting roughly a 14% decrease compared with the virgin material. On the contrary, the compressive modulus was largely retained. The most substantial reduction occurred in ILSS, which dropped by 58%. Overall, the results demonstrate that plasma-assisted solvolysis enables the recovery of carbon fibers suitable for remanufacturing CFRP laminates, while the observed reduction in mechanical properties of recycled CFRPs is mainly attributed to defects in manufacturing quality rather than to intrinsic degradation of the recycled carbon fibers. Full article

Seismic action significantly affects the mechanical properties and failure characteristics of bridge pile foundations, soft rocks, and sediments. This study, by integrating shaking table tests, numerical simulations, and on-site monitoring, systematically analyzed the influence mechanisms of seismic intensity, sediment characteristics, and pile foundation layout on structural responses. Tests show that the 2.5-layer rock–sand pile exhibits nonlinear bearing degradation under seismic force: when the seismic acceleration increases from 0 to 100 m/s², the bearing capacity of the pile foundation decreases by 55.3%, and the settlement increases from 3.2 mm to 18.5 mm. When the acceleration is ≥2 m/s², the cohesion of the sand layer is destroyed, causing a semi-liquefied state. When it is ≥10 m/s², the resistance loss reaches 80%. The increase in pore water pressure leads to dynamic settlement. When the seismic acceleration is greater than 50 m/s², the shear modulus of the sand layer drops below 15% of its original value. The thickness of the sediment has a nearly linear relationship with the reduction rate of the bearing capacity. When the thickness increases from 0 to 1.4 cm, the reduction rate rises from 0% to 55.3%. When the thickness exceeds 0.8 cm, it enters the “danger zone”, and the bearing capacity decreases nonlinearly with the increase in thickness. The particle size is positively correlated with the reduction rate. The liquefaction risk of fine particles (<0.1 mm) is significantly higher than that of coarse particles (>0.2 mm). The load analysis of the pile cap shows that when the sediment depth is 140 cm, the final bearing capacity is 156,187.2 kN (reduction coefficient 0.898), and the maximum settlement is concentrated at the top point of the pile cap. Under the longitudinal seismic load of the pile group, the settlement growth rate of the piles containing sediment reached 67.16%, triggering the dual effect of “sediment–earthquake”. The lateral load leads to a combined effect of “torsional inclination”, and the stress at the top of the non-sediment pile reaches 6.41MPa. The seismic intensity (PGA) is positively correlated with the safety factor (FS) (FS increases from 1.209 to 37.654 when 10 m/s²→100 m/s²), while sediment thickness (h) is negatively correlated with FS (FS decreases from 2.510 to 1.209 when 0.05 m→0.20 m). The research results reveal the coupled control mechanism of sediment characteristics, seismic parameters, and pile foundation layout on seismic performance, providing key parameters and an optimization basis for bridge design in high-intensity areas. Full article

This study focuses on the diversity of phytoplankton in the Koh Yaa region of Thailand and their relationship with environmental variables, aiming to assess whether human activities (primarily tourism) pose potential threats to the marine ecosystem and provide scientific support for eco-sustainable tourism management decisions in the region. In April, August, and December 2024, corresponding to peak season, off-season, and shoulder season, a total of 156 discrete samples were collected from four coastal sites to analyze water quality parameters such as temperature, pH, total nitrogen (TN), and total phosphorus (TP), along with plankton diversity and abundance. Statistical analyses including two-way ANOVA with Duncan’s Multiple Range Test (DMRT), Pearson correlation analysis, and principal component analysis (PCA) were applied. The results showed a declining trend in plankton abundance over time, peaking at 1009 × 10⁶ cells/m³ in April and dropping to 281 × 10⁶ cells/m³ by December. A total of 15 types of phytoplankton were identified across four phyla: Bacillariophyta, Cyanobacteria, Dinoflagellata, and Chlorophyta. Notably, Chaetoceros from Bacillariophyta accounted for 47% of phytoplankton, while Oscillatoria from Cyanobacteria made up 29.6%. The diversity index and evenness index improved from 1.34 and 0.46 in April to 1.88 and 0.64 in December, respectively. Environmental factors like pH, temperature, and TP significantly affected phytoplankton abundance (p < 0.01), with TP levels ranging from 0.27 to 0.69 mg/L. These results indicate possible pollution in this region, and changes in phytoplankton abundance were linked to seasonal climate variations—especially during peak tourist seasons—which may exacerbate eutrophication affecting community structures. Full article

Traditional routing algorithms optimizing for distance or travel time are inadequate for electric vehicles (EVs), which require energy-aware planning considering battery constraints and charging infrastructure. This work presents an energy-optimal routing system for EVs that integrates personalized consumption modeling with real-time environmental data. The system employs a Long Short-Term Memory (LSTM) neural network to predict State-of-Charge (SoC) consumption from real-world driving data, learning directly from spatiotemporal features including velocity, temperature, road inclination, and traveled distance. Unlike physics-based models requiring difficult-to-obtain parameters, this approach captures nonlinear dependencies and temporal patterns in energy consumption. The routing framework integrates static map data, dynamic traffic conditions, weather information, and charging station locations into a weighted graph representation. Edge costs reflect predicted SoC drops, while node penalties account for traffic congestion and charging opportunities. An enhanced A* algorithm finds optimal routes minimizing energy consumption. Experimental validation on a Nissan Leaf shows that the proposed end-to-end SoC estimator significantly outperforms traditional approaches. The model achieves an RMSE of 36.83 and an $R^2$ of 0.9374, corresponding to a 59.91% reduction in error compared to physics-based formulas. Real-world testing on various routes further confirms its accuracy, with a Mean Absolute Error in the total route SoC estimation of 2%, improving upon the 3.5% observed for commercial solutions. Full article

The operating conditions of engines in motor vehicles used in conditions of high air dustiness resulting from sandy ground and helicopters using temporary landing sites were analyzed. The impact of mineral dust on accelerated abrasive and erosive wear of components and assemblies of piston and turbine engines was presented. Attention was drawn to the formation of dust deposits on turbine engine components. Possibilities for minimizing abrasive wear through the use of two-stage intake air filtration systems in motor vehicle engines were presented. Three forms of protection for helicopter engines against the intake of dust-laden air and for extending their service life are presented: intake barrier filters (IBF), tube separators (VTS), and particulate separators (IPS) called Engine Air Particle Separation (EAPS). It has been shown that pleating the filter bed significantly increases the filtration area. It has been shown that increasing the suction flow from inertial filters increases separation efficiency and flow resistance. IPS are characterized by a compact design, low external resistance, and no need for periodic maintenance, but it has a lower separation efficiency (86–91%) than VTS and IBF systems (up to 99.3–99.9%). The tested “cyclone-partition filter” filtration system achieves a filtration efficiency of 99.9%, reaching the acceptable pressure drop value four times slower than if it were operating without a cyclone. Two-stage filtration systems ensure high friction durability at the lowest possible energy costs. Full article

Designing thermal–fluid devices that reduce peak temperature while limiting pressure loss is challenging because high-fidelity (HF) Navier–Stokes–convection simulations make direct HF-driven topology optimization computationally expensive. This study presents a two-dimensional, steady, laminar multifidelity topology design framework for thermal–fluid devices operating in a low-to-moderate Reynolds number regime. A computationally efficient low-fidelity (LF) Darcy–convection model is used for topology optimization, where SEMDOT decouples geometric smoothness from the analysis field to produce CAD-ready boundaries. The LF optimization minimizes a P-norm aggregated temperature subject to a prescribed volume fraction constraint; the inlet–outlet pressure difference and the P-norm parameter are varied to generate a diverse candidate set. All candidates are then evaluated using a steady incompressible HF Navier–Stokes–convection model in COMSOL 6.3 under a consistent operating condition (fixed flow; pressure drop reported as an output). In representative single- and multi-channel case studies, SEMDOT designs reduce the HF peak temperature (e.g., ~337 K to ~323 K) while also reducing the pressure drop (e.g., ~18.7 Pa to ~12.6 Pa) relative to conventional straight-channel layouts under the same operating point. Compared with a conventional RAMP-based pipeline under the tested settings, the proposed approach yields a more favorable Pareto distribution (normalized hypervolume 1.000 vs. 0.923). Full article

Sequential decision-making is critical for applications ranging from personalized recommendations to resource allocation. This study evaluates three decision policies—Greedy, Thompson Sampling (via Monte Carlo Dropout), and a zero-shot Large Language Model (LLM)-guided policy (Gemini-1.5-Pro)—within a contextual bandit framework. To address covariate shift and assess subpopulation performance, we utilize a Collective Conditional Diffusion Network (CCDN) where covariates are partitioned into $B=10$ homogeneous blocks. Evaluating these policies across a high-dimensional treatment space ($K=5$, resulting in $2^5=32$ actions), we tested performance in a simulated environment and three benchmark datasets: Boston Housing, Wine Quality, and Adult Income. Our results demonstrate that the Greedy strategy achieves the highest Model-Relative Optimal (MRO) coverage, reaching 1.00 in the Wine Quality and Adult Income datasets, though performance drops significantly to 0.05 in the Boston Housing environment. Thompson Sampling maintains competitive regret and, in the Boston Housing dataset, marginally outperforms Greedy in action selection precision. Conversely, the zero-shot LLM-guided policy consistently underperforms in numerical tabular settings, exhibiting the highest median regret and near-zero MRO coverage across most tasks. Furthermore, Wilcoxon tests reveal that differences in empirical outcomes between policies are often not statistically significant (ns), suggesting an optimization ceiling in zero-shot tabular settings. These findings indicate that while traditional model-driven policies are robust, LLM-guided approaches currently lack the numerical precision required for high-dimensional sequential decision-making without further calibration or hybrid integration. Full article

Balancing safety with computational speed is a persistent challenge in autonomous navigation. While optimal pathfinders like A* are efficient, they fail to define the navigable “buffer” zone required for safe motion. Existing corridor generation methods attempt to bridge this gap but often suffer from heavy computational overhead or geometric instability. This paper introduces the Manhattan d-corridor, a framework that constructs strictly bounded, collision-free regions around a reference path. By combining systematic expansion with topological pruning, the algorithm guarantees structural minimality without sacrificing coverage. Experiments confirmed that the method is over two orders of magnitude faster than standard baselines. Crucially, while traditional methods suffered geometric collapse at high resolutions and dropped to unsafe collision ratios, the d-corridor maintained invariant safety (1.0) across all tests. This establishes the framework as a highly robust, real-time solution for resource-constrained robotics. Full article

Organophilic acidic magadiites were prepared after an acidic magadiite (A-Mgd) reaction with cetyltrimethylammonium solutions containing different anions, such as cetyltrimethylammonium bromide (C16TMABr), cetyltrimethylammonium chloride (C16TMACl), and cetyltrimethylammonium hydroxide (C16TMAOH). The resulting materials were studied as adsorbents for Eosin Y removal from artificially contaminated solution. Successful preparation of oganophilic A-Mgd was achieved using C16TMAOH solution with an increased basal spacing from 1.21 nm to 3.15 nm and uptake C16TMA amount of 1.16 mmol/g. Meanwhile, no variation in the basal spacing of 1.20 nm occurred using C16TMACl and C16TMA Br solutions with an uptake mount of 0.07 to 0.09 mmol/g, respectively. Other techniques supported the behavior of the counteranion of surfactant solution on the synthesis of organophilic A-Mgd samples. 13C CP/MAS NMR data revealed that C16TMA cations displayed all-trans conformation comparable to C16TMABr solid, and ²⁹Si MAS NMR confirmed the stability of the host silicate layers during the reaction. The specific surface area of A-Mgd was reduced after the intercalation of C16TMA cations from 38 m²/g to 11 m²/g. The removal properties of organophilic samples were investigated under different conditions, including the Eosin Y pH solution, initial concentration, dosage mass, and content of C16TMA cations. The maximum removal amount was 70 mg/g at acidic pH and using A-Mgd prepared from C16TMAOH solution, while the other organophilic A-Mgds exhibited low removal amounts of 3 to 5 mg/g. The regeneration tests indicated that the efficiency was maintained after four reuse tests with a drop of 30 to 50% from the initial value after seven cycles. The adsorber batch design was employed to estimate theoretically the required masses of used samples to treat an effluent volume of 10 L at a removal percentage of 95% at a fixed initial concentration of 200 mg/L. In total, 20 g of organophilic prepared from A-Mgd and C16TMAOH solution was needed, while 243 g of sample prepared from C16TMABr solution was required. This study proposes the development of a cost-effective, sustainable solution for dye-contaminated wastewater treatment. Full article