Search Results (9,023)

Electronic coupling within InAs/InP quantum dots (QDs) influences carrier lifetime and thus QD laser performance. In this work, vertical electronic coupling between QDs is theoretically investigated based on a structure of five-layer QD stacks. This analysis illustrates that the resonant tunneling, a consequence of coherent coupling between QDs, should be considered for carrier redistribution. The carrier tunneling time of ground states is estimated by studying two structures of uniform and chirped five-layer QD stacks. The impact of resonant tunneling on optical properties of InAs/InP QD Fabery–Perot (FP) lasers, such as threshold current, light power-current temperature dependence, and relative intensity noise, is investigated through a comparison of uniform and chirped QD lasers. It is found that the carrier resonant tunneling leads to an increase in the threshold current, low characteristic temperature, and high relative intensity noise. By using the chirped QD stacks, the optical properties are improved thanks to less resonant tunneling. Full article

The limited self-starting capability of H-type Darrieus Vertical-Axis Wind Turbines (VAWT) remains one of the main obstacles to their deployment in low-power and urban applications, where wind conditions are typically weak and intermittent. Although several passive geometric modification strategies have been proposed to enhance initial torque generation, most available studies rely predominantly on numerical simulations, with limited systematic experimental validation under low tip-speed ratio (TSR) conditions. In this work, the influence of passive blade modifications on self-starting performance is assessed through a combined numerical–experimental approach. An integrated numerical–experimental framework was used to systematically compare passive blade configurations under equivalent low-wind conditions. Two modified configurations, a biomimetic profile incorporating passive trailing-edge devices and an asymmetric J-type geometry, were optimized using transient CFD simulations of the first rotation cycle and a Design of Experiments (DOE) framework. Additively manufactured full-rotor test blades were then manufactured via additive manufacturing and tested in a controlled wind tunnel at 3.0 m/s and 2.25 m/s. Start-up time, azimuthal robustness, tip-speed-ratio evolution, and static start-up torque (interpreted through its corresponding torque coefficient) were measured and compared against a baseline NACA0018 profile. The biomimetic configuration consistently produced higher start-up torque and shorter acceleration times, achieving self-starting in 66.7% of the evaluated azimuthal positions at 2.25 m/s, compared to 22.2% for the baseline profile. Within the investigated operating range, this configuration emerged as the most robust passive strategy. The agreement between CFD predictions and experimental measurements supports the use of first-cycle maximum torque as a representative indicator of self-starting performance. These findings highlight the comparative value of first-cycle maximum torque as a practical metric for passive self-starting design assessment in low-TSR Darrieus turbines. These findings provide direct experimental evidence to guide the rational design of Darrieus turbines intended for marginal wind conditions. Full article

Airfoil flow-field prediction is important for aerodynamic design, but wind-tunnel testing and computational fluid dynamics (CFD) remain costly and time-consuming. Deep learning enables fast inference, yet many existing models still rely on fixed grid representations, which may lead to insufficient learning in high-gradient regions and larger local errors. This study proposes Spatial Multilayer Perceptron (Spatial MLP) together with an Error-Gradient-Guided Data Sampling (EGDS) strategy for airfoil flow-field prediction. Spatial MLP adopts a coordinate-based point-wise prediction framework. A spatial decoder is introduced as an auxiliary branch to enhance global flow consistency during pretraining, while channel-wise multi-head attention is incorporated to improve cross-variable feature coupling. EGDS prioritizes physically informative points according to relative prediction error and gradient magnitude, while retaining random samples to preserve data diversity. Experiments on an independent test set show that Spatial MLP reduces the mean relative error (averaged over the velocity components u, v, and pressure p) by 15.2% relative to the MLP baseline. With EGDS, the overall mean relative error is further reduced by 34.5% relative to the MLP baseline. These results demonstrate that combining global consistency constraints with targeted sampling effectively improves both global prediction accuracy and local reconstruction quality in high-gradient flow regions. Full article

To investigate the thermal environments of three large-span plastic tunnels with different orientations and shapes (two east–west-oriented asymmetrical tunnels, WE15-5 and WE13-7, and one north–south-oriented symmetrical tunnel, NS10-10) under summer high-temperature and winter low-temperature conditions, we continuously monitored the air and soil temperature and conducted a comparative analysis of both under typical weather conditions. Computational fluid dynamics (CFD) simulations were used to further analyze the temperature and airflow fields. The results showed that, in summer, NS10-10 exhibited a superior ventilation and cooling performance with the most uniform temperature distribution, making it more suitable for summer crop cultivation. In winter, WE13-7 demonstrated optimal insulation and heat retention, with the highest minimum air temperatures and best daylighting capacity. CFD model validation showed a good agreement with the measured data (RMSE: 0.73–0.85 °C). These findings provide structural optimization recommendations for large-span plastic tunnels in different seasons. Full article

Trans-anethole oxygenase (TAO) exhibits broad arylpropene substrate specificity but has low activity in converting isoeugenol to high-value vanillin. Herein, we employed computer-aided rational design to engineer TAO from Pseudomonas putida (PpTAO) for enhanced catalytic efficiency toward isoeugenol. Structural modeling and AlphaFold 3 docking identified two key catalytic residues, Arg86 and His118. Through substrate channel engineering and computation-guided mutagenesis, a series of targeted variants were constructed. Three variants, H93A, Q207R/G249C, and I59T/F62T, showed significant improvements in whole-cell performance, with activity increases of 1.8-, 2.13-, and 4.83-fold over the wild type (WT), respectively. Purified enzyme kinetics corroborated these findings, as reflected in k_cat/K_m values that reached 1.6, 2.1, and 4.7 times that of the WT. Mechanistic molecular dynamics simulations revealed that H93A enhances activity by widening the access tunnel, whereas Q207R/G249C exerts beneficial distal effects. Notably, the I59T/F62T variant significantly increases substrate affinity by optimizing hydrophobic interactions within the binding pocket. These results validate the efficacy of computational modeling in enzyme redesign and provide a robust biocatalyst for the sustainable biosynthesis of vanillin. Full article

During the excavation of tunnels in deeply buried underground hydropower stations, complex geological and construction conditions significantly increase the risk of sudden groundwater inflow, and the accuracy of groundwater inflow calculations remains low. This study takes the deeply buried underground powerhouse of a hydropower station as the engineering background and meticulously characterizes the underground powerhouse chamber group and its associated drainage facilities. On this basis, the study couples the geological model with the water flow model to systematically simulate the seepage field characteristics under complex conditions, including the pre-excavation, excavation, and operational phases. The water inflow at different parts of the powerhouse during the excavation phase is predicted. The results show that different rainfall conditions significantly affect the water inflow, with the inflow increasing as rainfall intensity rises. The maximum water inflow occurs in the storage reservoir area under heavy rainfall conditions, reaching 13,043.7 m³/d. During the operation phase, the external water pressure is greatly influenced by rainfall conditions, with the maximum pressure head of the water delivery pipeline from the underground powerhouse area to the reservoir section reaching 882.78 m under heavy rainfall. These findings provide a reference for future engineering construction. The results of this study offer theoretical and engineering references for groundwater inflow prediction and comprehensive control in deeply buried underground powerhouses under complex conditions. Full article

Reliable high-precision positioning in railway tunnels is essential for intelligent train operation and safety monitoring, yet GNSS signals are severely degraded by blockage and multipath. This paper proposes a deployment-oriented numerical framework to optimize pseudolite layouts in tunnels by explicitly modeling visibility obstruction and controlling worst-case geometry along the train trajectory. A high-fidelity 3D tunnel–train model is established, in which line-of-sight (LoS) availability is screened under vehicle occlusion and trajectory-level geometric quality is evaluated accordingly. Instead of optimizing only the average PDOP, the proposed framework minimizes the trajectory 90th-percentile PDOP (qPDOP) to suppress tail-risk geometric degradation, while interpreting PDOP as an error amplification factor that directly affects positioning reliability under measurement noise and local multipath. The core contribution is a Voronoi-partition-constrained improved genetic algorithm (IGA) for tunnel pseudolite deployment. Voronoi partitioning enforces segment-wise coverage by requiring at least one pseudolite in each partition cell and avoids clustering-induced blind zones. Meanwhile, the IGA incorporates improved search and constraint-handling mechanisms to satisfy practical engineering requirements, including feasible installation regions, minimum spacing, mounting-face balance (ceiling/side walls), communication range, and continuous satellite visibility. Comparative simulations and ablation studies demonstrate that the proposed method achieves more uniform coverage and significantly improves full-trajectory geometric stability, reducing high-quantile PDOP and mitigating local spikes in occlusion-sensitive sections under cost-constrained sparse deployments. The proposed framework provides a practical and flexible toolchain for designing positioning-oriented pseudolite infrastructures in underground transportation environments. Full article

Background and Objectives: Tunneled hemodialysis catheters (TDCs) are essential for vascular access in patients with end-stage renal disease (ESRD). This study retrospectively evaluated the clinical outcomes of permanent TDCs placed at a single center, comparing heparin-coated versus non-heparin-coated catheters. Materials and Methods: A total of 189 patients who underwent permanent TDC placement between January 2021 and January 2022 were included. Patients were categorized by catheter type (heparin-coated, n = 80; non-heparin-coated, n = 109). Catheter failure-free survival was analyzed using the Kaplan–Meier method, with arteriovenous fistula creation treated strictly as a censoring event. Multivariable Cox proportional hazards regression was used to identify independent predictors of catheter failure. Results: Complications were significantly more frequent in the non-heparin-coated group (p = 0.004). Catheter exchange was required exclusively in the non-heparin-coated group (p < 0.001). Kaplan–Meier analysis demonstrated significantly longer failure-free catheter survival in the heparin-coated group (restricted mean 49.0 vs. 41.7 months; Log-Rank p < 0.001). On multivariable Cox regression, the complete absence of events in the heparin-coated group yielded a strong protective point estimate (HR = 0.087, 95% CI: 0.004–1.710), rendering individual patient covariates such as INR and age non-significant. Conclusions: Heparin-coated TDCs were associated with significantly longer failure-free survival and lower complication rates compared with non-heparin-coated catheters. Due to the low overall event rate, individual patient-level covariates including INR did not reach statistical significance in the multivariable model. Full article

This work presents an experimental aerodynamic study of a Mars rover model, aimed at characterizing its flow behavior under Martian environmental conditions. Due to the extremely low Reynolds numbers associated with Mars’ thin atmosphere, the experiments were conducted using a scaled model of the rover manufactured via additive techniques. The study first focuses on understanding how the geometry of the rover influences the overall flow field, identifying key aerodynamic features such as separation zones, vortical structures, and flow reattachment regions driven by the complexity of the vehicle. A comprehensive investigation of the flow around the model was performed using both a hydrodynamic towing tank with dye injection for qualitative visualization, and particle image velocimetry (PIV) for quantitative flow field analysis in wind tunnel tests. After the general flow characterization, a more detailed local analysis was conducted using laser Doppler anemometry (LDA). This phase of the study targeted precise velocity measurements at specific locations corresponding to the MEDA (Mars Environmental Dynamics Analyzer) wind sensors onboard the rover. Quantitative results indicate that the central body induces a local flow acceleration of 20% to 40% relative to the free stream while severe turbulence was recorded in specific angular sectors, with velocity fluctuations reaching up to 120% for Sensor 1 and 90% for Sensor 2. Full article

Avian wings enable autonomous control over flight trajectory and speed, and their swept-wing geometry inspires the application of sweep modifications to horizontal-axis wind turbine blades, an approach that is critical for improving aerodynamic performance. Hence, wind tunnel experiments were performed to evaluate the output power and wake features of a baseline straight-bladed and a swept-blade wind turbine. The experimental results demonstrate that inflow turbulence intensity (T.I.) affects the peak power coefficient of the swept-bladed turbine, with power coefficient gains being more significant when the tip speed ratio is greater than 3.0 and under yawed conditions. At a yaw angle of 20°, when the T.I. is 0.5%, 10.5%, and 19.0%, respectively, the corresponding increased values are 13.17%, 3.44%, and 4.68%. Cross-stream velocity in the near-wake region of the swept-bladed turbine is markedly higher than that for the baseline condition. The averaged T.I. in the wake velocity region of the swept-blade conditions is greater than that of the baseline condition at most measurement positions. Moreover, power spectral density (PSD) magnitudes behind the blade tip for the swept-blade configuration are higher than those of the baseline, particularly in the medium- and high-frequency domains. This work clarifies the aerodynamic characteristics of swept-blade wind turbines to varying levels of turbulent inflow. Full article

Previous studies and current wind-load standards for low-aspect-ratio circular structures primarily consider external pressure and insufficiently address the combined effects of roof openings, internal–external-pressure interaction, and surface roughness. To overcome these limitations, this study investigates the net-pressure characteristics of such structures through wind-tunnel experiments conducted for two aspect ratios and four levels of surface roughness. The vertical variation in net pressure and its implications for wind-load estimation are systematically examined. For smooth surfaces, the net-pressure distribution exhibits pronounced height dependence due to the free-end effect. This dependence diminishes as surface roughness increases, indicating a significant modification of the flow structure around the cylinder. Neglecting this height-dependent behavior leads to substantial inaccuracies in drag-coefficient estimation. Comparisons with existing standards reveal that the drag coefficients specified in AS/NZS 1170.2 and AIJ-RLB overestimate values for smooth surfaces by up to 38.7% and 21.5%, respectively, whereas the AIJ-RLB provisions underestimate values for rough surfaces by approximately 4.7%. To improve predictive accuracy, a simplified model for the circumferential distribution of mean net-pressure coefficients is developed. The proposed model incorporates height-dependent aerodynamic parameters and demonstrates strong agreement with experimental data, with a maximum relative error below 8.6%. This model provides a practical reference for more reliable wind-load estimation in the structural design of low-aspect-ratio circular structures with roof openings. Full article

Breast cancer brain metastasis (BCBM) affects up to 30% of patients with metastatic disease and carries a median survival of only 4–18 months. Emerging evidence reveals that BCBM cells are not passive survivors, but active participants that hijack core neurotransmitter networks, GABA (gamma-aminobutyric acid) and glutamate, to fuel their growth. BCBM, particularly triple-negative breast cancer (TNBC), frequently switch to a GABAergic mode utilizing brain-derived GABA as an oncometabolite. In parallel, BCBM cells can also form direct synapses with neurons, tapping into excitatory input through glutamatergic receptors to drive tumor cell proliferation and survival. Concurrently, reprogrammed astrocytes establish gap junctions, secrete growth factors, and provide metabolic support. Together, tumor cells, neurons, and astrocytes form a pathological partnership locked in feedback loops sustaining metastatic progression. This review focuses on the unique mechanisms employed by distinct breast cancer subtypes and maps the metastatic progression from pre-metastatic to mature brain metastatic niche formation of BCBM. We highlight opportunities to repurpose neurological drugs to disrupt these communication axes. Full article

Hate speech on social media reproduces norms of inequality and gender stereotypes, disproportionately affecting women. This study proposes a hybrid approach that integrates emotional tone classification with explicit hostility detection to strengthen preventive moderation. We constructed a corpus from three open data sets (1,236,371 records; 1,003,991 after ETL) and represented the text using TF-IDF and contextual RoBERTa embeddings. We trained individual models (RoBERTa fine-tuned, Random Forest, and XGBoost) and a stacking metamodel (Gradient Boosting) that combines their probabilities. On the test set, the ensemble outperformed the base classifiers, achieving accuracy of 0.93 in hate detection and 0.90 in emotion classification, with an AUC of 0.98 for emotion classification. We implemented a RESTful API and a web client to validate the moderation flow before publication, along with an administration panel for auditing. Performance tests in a prototype deployment (Google Colab exposed through an Ngrok tunnel) provided proof-of-concept validation, revealing concurrency limitations from around 300 users due to infrastructure constraints. In general, the results indicate that incorporating emotional tone analysis improves the model’s ability to identify implicit hostility and offers a practical way to promote safer digital environments. The probabilistic outputs produced by the ensemble model were subsequently analyzed using the Bayesian Calibration and Optimal Design under Asymmetric Risk (BACON-AR) framework, which serves as a mathematical post hoc decision layer for evaluating classification behaviour under unequal error costs. Rather than modifying the trained architecture or improving its predictive performance, the framework identifies a cost-sensitive operating threshold that minimizes the total expected risk under the selected asymmetric cost configuration. The experiments were conducted using an English-language data set; therefore, the findings of this study are limited to hate speech detection in English. Full article

In urban subway construction, shield tunneling inevitably passes in close proximity to existing pile foundations, inducing adverse effects on their internal forces and deformations. Taking the twin shield tunnels with small clearance adjacent to the bridge piles as the engineering background, this study establishes a three-dimensional finite element numerical model to investigate the deformation and internal force responses of the adjacent pile foundations under different pile lengths, twin-tunnel construction sequences, and tunnel face pressure conditions. The findings indicate that the primary influence zone affected by twin-tunnel excavation extends approximately twice the tunnel diameter (2D) before and after the pile foundation location. Compared with short piles, longer piles exhibit smaller vertical displacements. Meanwhile, the lateral displacements, additional axial forces and bending moments of medium and long piles increase, with their maximum values occurring near the tunnel centerline. For the near pile, when the right tunnel is excavated first, compared with the condition of the left-tunnel-first excavation, the lateral and vertical displacements slightly increase. In addition, the maximum additional axial force increases by 38.8%, while the maximum additional bending moment decreases by approximately 21%. Tunnel face pressure exerts a moderate influence on the vertical displacement of both the surrounding soil and pile foundation, while its effect on lateral displacement and internal forces is relatively insignificant. The tunnel face pressure within the range of 200 kPa to 300 kPa provides optimal control over pile foundation deformation. Full article

Tunnels, soundproof screens and other vertical roadside traffic facilities play an important role in isolating the driving environment, maintaining driving safety, and reducing driving noise. As the usage time increases, these facade traffic buildings become polluted and cause traffic safety problems. Obstacles on three-dimensional walls of different shapes, colors, and sizes are the most challenging problem in intelligent cleaning environment perception. This paper proposes an obstacle segmentation method based on a visual language model to overcome these problems. Firstly, in the constructed experimental environment, a visual–language obstacle dataset is collected, named the Road-side General Obstacles Dataset (RGOD), and the collected dataset is labeled with both a segmentation mask and a language description. These preprocessing results are used as the training input of the perception model to obtain the foreground and background separation results. Secondly, a VLM-GOS model was proposed to segmentation special-shaped obstacles, which emphasizes the distinction between background and foreground targets. Finally, the general obstacle is segmented by a vision–language model with a similar loss function, and evaluated with different metrics. Experimental results show that compared with models such as MaskFormer, SegFormer, and ASD-Net, this method improves the model’s perceptual ability and increases accuracy by 3%. More importantly, the model is more interpretable. Full article