Search Results (95)

The extensive distribution of quaternary sediments and the extraction of underground resources in the Yellow River Delta (YRD) have resulted in significant land subsidence, which accelerates relative sea level (RSL) rise and heightens the risk of coastal inundation. This study uses Sentinel-1A (S1A) imagery and the time-series synthetic aperture radar interferometry (TS-InSAR) method to obtain subsidence information for the YRD. By integrating data from groundwater level monitoring wells, hydrogeological conditions, extensometer monitoring, and drilling wells, we analyze the causes of subsidence and the deformation response to the groundwater level changes in the corresponding aquifers. For the first time in the YRD, this study introduces the high accuracy CoastalDEM v2.1 digital elevation model, combined with absolute sea level (ASL) data, to construct a coastal inundation simulation. This simulation maps the land inundation caused by RSL rise along the YRD in different scenarios. The results indicate significant subsidence bowls in coastal and inland regions, primarily attributed to shallow brine and deep groundwater extraction, respectively. The main subsidence layers in inland towns have been identified, and residual deformation has been observed. Currently, land subsidence has caused a maximum elevation loss of 141 mm/yr in coastal YRD areas, significantly contributing to RSL rise. Seawater inundation simulations suggest that if subsidence continues unabated, 12.84% of the YRD region will be inundated by 2100, with 8.74% of the built-up areas expected to be inundated. Compared to global warming-induced ASL rise, ongoing subsidence is the primary driver of inundation in the YRD coastal areas. Full article

The compressive capacity of helical anchors constitutes a pivotal performance parameter in geotechnical design. To precisely predict the compressive bearing behavior of helical anchors in aeolian sand, this study integrates in situ testing with finite element numerical analysis to systematically elucidate the non-linear evolution of its load-bearing mechanisms. The XGBoost algorithm enabled the rigorous quantification of the governing geometric features of compressive capacity, culminating in a computational framework for the bearing capacity factor (N_q) and lateral earth pressure coefficient (K_u). The research findings demonstrate the following: (1) Compressive capacity exhibits significant enhancement with increasing helix diameter yet displays limited sensitivity to helix number. (2) Load–displacement curves progress through three distinct phases—initial quasi-linear, intermediate non-linear, and terminal quasi-linear stages—under escalating pressure. (3) At embedment depths of H < 5D, tensile capacity diminishes by approximately 80% relative to compressive capacity, manifesting as characteristic shallow anchor failure patterns. (4) When H ≥ 5D, stress redistribution transitions from bowl-shaped to elliptical contours, with ≤10% divergence between uplift/compressive capacities, establishing 5D as the critical threshold defining shallow versus deep anchor behavior. (5) The helix spacing ratio (S/D) governs the failure mode transition, where cylindrical shear (CS) dominates at S/D ≤ 4, while individual bearing (IB) prevails at S/D > 4. (6) XGBoost feature importance analysis confirms internal friction angle, helix diameter, and embedment depth as the three parameters exerting the most pronounced influence on capacity. (7) The proposed computational models for N_q and K_u demonstrate exceptional concordance with numerical simulations (mean deviation = 1.03, variance = 0.012). These outcomes provide both theoretical foundations and practical methodologies for helical anchor engineering in aeolian sand environments. Full article

This paper proposes a drug classification system using convolutional neural network (CNN) training and rotational pill dropping technology. Images of 40 pills for each of 102 types (total 4080 images) were captured, achieving a CNN classification accuracy of 88.8%. The system uses a bowl feeder with optimized operating parameters—voltage, torque, PWM, tilt angle, vibration amplitude (0.2–1.5 mm), and frequency (4–40 Hz)—to ensure stable, sequential pill movement without loss or clumping. Performance tests were conducted at 5 V, 20 rpm, 20% PWM (@40 Hz), and 1.5 mm vibration amplitude. The bowl feeder structure tolerates oblique angles up to 75°, enabling precise pill alignment and classification. The CNN model plays a key role in accurate pill detection and classification. Full article

Cricket is a dynamic sport, making the selection of key performance indicators (KPIs) challenging. Objective: The study aims to identify KPIs in Twenty-20 (T20) cricket affecting match outcomes. Methods: Cricket performance data was analysed from three seasons of male T20 matches, identifying 136 performance indicators (PIs). The random forest algorithm and lasso logistic regression were used to develop a model to predict match outcomes. Results: The hybrid model achieved 85.9% accuracy with leave-one-out cross-validation statistical analyses. Sixteen KPIs were identified and ranked by importance including wickets lost in the last six overs, two or more wickets in the second innings, run rate in the last six overs, wickets by seam and spin bowling, batting strike rate, singles percentage in the second innings, sixes in the first innings, overs bowled by seam, runs in last six overs, sixes in middle overs, total catches in second innings, dot ball percentage, opening partnership runs, dot balls in the opening six, and singles in the last six. Conclusions: Cricket match performance in the final overs, especially bowling strike rate and scoring runs, were crucial for successful match outcomes. These KPIs offer insights into team strategy, player selection, and match performance evaluation in T20 cricket. Full article

This study examines rural walking tourism as a sustainable strategy for revitalizing regional economies and preserving natural environments, focusing on the DMZ Punch Bowl in South Korea. Although rural walking tourism has been widely promoted for sustainability, little is known about its operation in geopolitically sensitive and militarized ecological zones, such as the Korean DMZ. Adopting the qualitative case study method, we explored three essential conditions for sustainable rural walking tourism: environmental friendliness, experiential immersion and sense of place, and local economic revitalization through stakeholder cooperation. We employed a hybrid thematic analysis using inductive and deductive coding to analyze the triangulated data collected from interviews, field observations, and policy documents. In-depth interviews with ten walking tourism experts revealed that storytelling that emphasizes local history, ecological conservation, and unique cultural identity enhances tourists’ emotional attachment and sense of place immersion. The DMZ Punch Bowl case was selected due to its effective integration of these elements, achieved through a collaborative governance structure involving government agencies, military units, and local communities. The findings highlight that coordinated management and stakeholder cooperation are crucial for balancing land use policies, ecological preservation, and tourism safety. Additionally, walking tourism significantly contributes to local economic growth through direct spending, job creation, increased resident incomes, the sale of local specialties, and participation in experiential activities. This study provides valuable insights and a replicable model for sustainably developing walking tourism in similarly sensitive or ecologically significant rural areas. Full article

Background/Objectives: Accurate and efficient segmentation of cell nuclei in biomedical images is critical for a wide range of clinical and research applications, including cancer diagnostics, histopathological analysis, and therapeutic monitoring. Although U-Net and its variants have achieved notable success in medical image segmentation, challenges persist in balancing segmentation accuracy with computational efficiency, especially when dealing with large-scale datasets and resource-limited clinical settings. This study aims to develop a lightweight and scalable U-Net-based architecture that enhances segmentation performance while substantially reducing computational overhead. Methods: We propose a novel evolving U-Net architecture that integrates multi-scale feature extraction, depthwise separable convolutions, residual connections, and attention mechanisms to improve segmentation robustness across diverse imaging conditions. Additionally, we incorporate channel reduction and expansion strategies inspired by ShuffleNet to minimize model parameters without sacrificing precision. The model performance was extensively validated using the 2018 Data Science Bowl dataset. Results: Experimental evaluation demonstrates that the proposed model achieves a Dice Similarity Coefficient (DSC) of 0.95 and an accuracy of 0.94, surpassing state-of-the-art benchmarks. The model effectively delineates complex and overlapping nuclei structures with high fidelity, while maintaining computational efficiency suitable for real-time applications. Conclusions: The proposed lightweight U-Net variant offers a scalable and adaptable solution for biomedical image segmentation tasks. Its strong performance in both accuracy and efficiency highlights its potential for deployment in clinical diagnostics and large-scale biological research, paving the way for real-time and resource-conscious imaging solutions. Full article

For computational fluid dynamic (CFD) modeling of advanced combustion engines, the cylinder is usually considered a closed system in which the initial conditions are estimated based on the experimental data. Most of these approximations hinder observing the effect of design parameters on engine performance and emissions accurately, and most studies are limited to a few design parameters. An approach is proposed based on the combination of a 1D gas dynamic and a 3D CFD model to simulate the whole engine with as few simplifications as possible. The impact of changing the in-cylinder initial conditions, injection strategy (dual direct injection or multiple pulse injections), and piston bowl geometry on a reactivity controlled compression ignition (RCCI) engine’s performance, emissions, and fuel stratification levels was investigated. It was found that applying the dual direct injection (DDI) strategy to the engine can be promising to reach higher load operations by reducing the pressure rise rate and causing stronger stratification levels. Increasing the number of injection pulses leads to lower Soot/NOx emissions. The best reduction in the pressure rise rate was found by the dual direct strategy (38.36% compared to the base experimental case) and higher exhaust gas recirculation (EGR) levels (41.83% reduction in comparison with the base experimental case). With the help of a novel piston bowl design, HC and CO emissions were reduced significantly. This resulted in a reduction of 54.58% in HC emissions and 80.22% in CO emissions. Full article

Double-layer pipelines are widely used in deep-sea energy transport because of their strong thermal insulation and enhanced structural safety. The stress distribution and the interaction mechanism between inter-pipes of double-layer pipelines are elucidated. A mechanical model is developed to characterize the thermal deformation difference between the two layers. The mechanical response of the pipeline can be divided into two distinct modes based on the initial deformation stages: (1) an inner-pipe-dominated elongation that creates compressive stress in the inner pipe and tensile stress in the outer pipe, and (2) an outer-pipe-dominated elongation that reverses this stress distribution. Sagging deformation (bowl-shaped deformation), primarily caused by the self-weight of the inner pipe, is identified as the critical factor that drives the stress concentration and bending moment at the inner–outer pipe connection. Engineering approaches, such as inserting spacers or additional supports in the annular cavity, effectively reduce peak stresses in both layers under extreme conditions. Full article

Background: Limited research has examined how older adults’ lifestyles intersect with multimorbidity to influence mortality risk. Methods: In this community-dwelling prospective cohort, the Sydney Memory and Ageing Study, principal component analysis was used to identify lifestyle patterns using baseline self-reported data on nutrition, lifestyle factors, and social engagement activities. Multimorbidity was defined by self-reported physician diagnoses. Multivariable logistic regression was used to estimate odds ratios (ORs) for multimorbidity cross-sectionally, and Cox proportional hazards models were used to assess hazard ratios (HRs) for mortality risk longitudinally. Results: Of 895 participants (mean age: 78.2 years; 56.3% female) with complete lifestyle data, 597 had multimorbidity. Two distinct lifestyle patterns emerged: (i) a nutrition pattern characterised by higher intakes of protein, fibre, iron, zinc, magnesium, potassium, and folate, and (ii) an exercise-sleep-social pattern marked by weekly physical activities like bowling, bicycling, sleep quality (low snoring/sleepiness), and high social engagement. Neither pattern was associated with multimorbidity cross-sectionally. Over a median 5.8-year follow-up (n = 869; 140 deaths), participants in the upper tertiles for combined lifestyle pattern scores had a 20% lower mortality risk than those in the lowest tertile [adjusted HR: 0.80 (95% CI: 0.65–0.97); p-trend = 0.02]. This association was stronger in participants with multimorbidity, with a 29% lower risk [0.71 (0.56–0.89); p-trend = 0.01], likely due to multimorbidity modifying the relationship between nutrition and mortality risk (p-interaction < 0.05). While multimorbidity did not modify the relationship between the exercise-sleep-social pattern and risk of mortality, it was consistently associated with a 19–20% lower risk (p-trend < 0.03), regardless of the multimorbidity status. Conclusions: Older adults with multimorbidity may particularly benefit from adopting healthy lifestyles focusing on nutrition, physical activity, sleep quality, and social engagement to reduce their mortality risk. Full article

The task of nucleus segmentation plays an important role in medical image analysis. However, due to the challenge of detecting small targets and complex boundaries in datasets, traditional methods often fail to achieve satisfactory results. Therefore, a novel nucleus segmentation method based on the U-Net architecture is proposed to overcome this issue. Firstly, we introduce a Weighted Feature Enhancement Unit (WFEU) in the encoder decoder fusion stage of U-Net. By assigning learnable weights to different feature maps, the network can adaptively enhance key features and suppress irrelevant or secondary features, thus maintaining high-precision segmentation performance in complex backgrounds. In addition, to further improve the performance of the network under different resolution features, we designed a Double-Stage Channel Optimization Module (DSCOM) in the first two layers of the model. This DSCOM effectively preserves high-resolution information and improves the segmentation accuracy of small targets and boundary regions through multi-level convolution operations and channel optimization. Finally, we proposed an Adaptive Fusion Loss Module (AFLM) that effectively balances different lossy targets by dynamically adjusting weights, thereby further improving the model’s performance in segmentation region consistency and boundary accuracy while maintaining classification accuracy. The experimental results on 2018 Data Science Bowl demonstrate that, compared to state-of-the-art segmentation models, our method shows significant advantages in multiple key metrics. Specifically, our model achieved an IOU score of 0.8660 and a Dice score of 0.9216, with a model parameter size of only 7.81 M. These results illustrate that the method proposed in this paper not only excels in the segmentation of complex shapes and small targets but also significantly enhances overall performance at lower computational costs. This research offers new insights and references for model design in future medical image segmentation tasks. Full article

During mine excavation, rock wall collapse can pose a safety risk to miners. Reasonably designed support equipment can prevent collapse and ensure a safe working environment. In this paper, a new half-bowl spherical rubber structure is introduced and modeled using Abaqus to study its damping ability under different impact energies. By comparing the support reaction forces and pressures of the A-S, R-S, and C-S structures, we find that the R-S structure, with a smaller number of half-bowl spheres, has superior energy absorption abilities and impact resistance. These findings support the designing and manufacturing of mining support equipment. Full article

Background: The effectiveness of paclitaxel (PTX) in treating non-small-cell lung carcinoma (NSCLC) is restricted by its poor pharmacokinetic profile and side effects. This limitation stems from the lack of a suitable delivery vector to efficiently target cancer cells. Therefore, there is a critical need to develop an efficient carrier for the optimised delivery of PTX in NSCLC therapy. Methods: The present study describes the fabrication of mesoporous polydopamine (mPDA) nano-bowls via an emulsion-induced interfacial anisotropic assembly method, designed for efficient entrapment of PTX and pH-responsive release behaviour. Results: The nano-bowls depicted a typical bowl-like shape, with connecting mesoporous channels and a central hollow cavity, allowing optimal loading of PTX. The fabricated nanocarrier system, mPDA-PTX-nb, had a mean hydrodynamic bowl diameter of 200.4 ± 5.2 nm and a surface charge of −39.2 ± 1.3 mV. The entrapment efficiency of PTX within the nano-bowls was found to be 95.7%, with a corresponding release of 85.1% achieved at the acidic pH 5.9 (simulated tumour microenvironment) at 48 h. Drug release was best fitted to the Peppas–Sahlin model, indicating the involvement of both diffusion and relaxation mechanisms. Treatment with mPDA-PTX-nb significantly suppressed A549 lung cancer cell proliferation at 48 and 72 h, resulting in cell viability of 14.0% and 9.3%, respectively, at the highest concentration (100 µg/mL). Conclusions: These results highlight the potential of mPDA-PTX-nb as an effective nanocarrier for PTX, promoting enhanced anti-proliferative effects in NSCLC therapy. Full article

Ground reaction forces (GRFs) are known to be high during front foot contact of fast bowling deliveries in cricket. There is a lack of published data on the GRFs during follow through foot contacts. The aim of this study was to quantify and compare peak GRFs and impulse of the delivery stride and the follow through of fast bowling deliveries. Ten trained male fast bowlers (ball release speed mean ± SD; 32.6 ± 2.3 m/s) competing in the Men’s Victorian Premier League participated in the study. Peak GRF and impulse data were collected using in-ground force plates in a laboratory setting. Linear mixed modelling of GRFs and impulse showed a significant effect of foot strike (p < 0.001). Front foot contact had the greatest magnitude of peak vertical GRF (5.569 ± 0.334 BW) but was not significantly greater than back foot recontact (4.471 ± 0.285 BW) (p = 0.07). Front foot impact had the greatest vertical impulse (0.408 ± 0.018 BW·s) but was similar to back foot (0.377 ± 0.012 BW·s) and front foot (0.368 ± 0.006 BW·s) recontacts (p = 0.070 to 0.928). The high GRF and impulse during the follow through highlights the need for further kinetic and kinematic research on this phase of the fast bowling delivery. Full article

Land subsidence is an environmental hazard occurring gradually over time, potentially posing significant threats to the structural stability of civilian buildings and essential infrastructures. This study presented a workflow using the SBAS-PSInSAR approach to analyze surface deformation in the Choushui River Fluvial Plain (CRFP) based on Sentinel-1 SAR images and validated against precise leveling. Integrating the InSAR results with hydrogeological data, such as groundwater levels (GWLS), multilayer compactions, and borehole loggings, a straightforward model was proposed to estimate appropriate groundwater level drops to minimize further subsidence. The results showed a huge subsidence bowl centered in Yunlin, with maximal sinking at an average 60 mm/year rate. High-resolution subsidence maps enable the quantitative analyses of safety issues for Taiwan High-Speed Rail (THSR) across the areas with considerable subsidence. In addition, the analysis of hydrogeological data revealed that half of the major compaction in the study area occurred at shallow depths that mainly included the first and second aquifers. Based on a maximal subsidence control rate of 40 mm/year specified in the CRFP, the model results indicated that the groundwater level drops from wet to dry seasons needed to be maintained from 3 to 5 m for the shallowest aquifer and 4–6 m for Aquifers 3 and 4. The workflow demonstrated the compatibility of InSAR with traditional geodetic methods and the effectiveness of integrating multiple data sources to assess the complex nature of land subsidence in the CRFP. Full article

In dietary assessment using a single-view food image, an object of known size, such as a checkerboard, is often placed manually in the camera’s view as a scale reference to estimate food volume. This traditional scale reference is inconvenient to use because of the manual placement requirement. Consequently, utensils, such as plates and bowls, have been suggested as alternative references. Although these references do not need a manual placement procedure, there is a unique challenge when a dining bowl is used as a reference. Unlike a dining plate, whose shallow shape does not usually block the view of the food, a dining bowl does obscure the food view, and its shape may not be fully observable from the single-view food image. As a result, significant errors may occur in food volume estimation due to the unknown shape of the bowl. To address this challenge, we present a novel method to premeasure both the size and shape of the empty bowl before it is used in a dietary assessment study. In our method, an image is taken with a labeled paper ruler adhered to the interior surface of the bowl, a mathematical model is developed to describe its shape and size, and then an optimization method is used to determine the bowl parameters based on the locations of observed ruler makers from the bowl image. Experimental studies were performed using both simulated and actual bowls to assess the reliability and accuracy of our bowl measurement method. Full article