Search Results (164)

Automated precision drilling is essential for aircraft skin manufacturing, yet current robotic systems face dual challenges: chatter-induced inaccuracies in hole quality and limited access to confined spaces such as air inlets. To overcome these limitations, this paper develops a compact drilling robot for drilling large-curvature skins of aircraft air inlets. Targeting the precision drilling requirements for complex-curvature aircraft air inlets, we present the robot’s overall design scheme, detailing each module’s composition to ensure precision drilling. In-depth analysis of the robot’s large-curvature adaptability precisely calculates the wheel assembly dimensions. To ensure high-precision drilling bit entry into guide mechanisms, a flexible drilling spindle mechanism is designed, with calculated and verified elastic ranges. An integrated intelligent control system is developed, combining vision recognition, real-time pose adjustment, and automated drilling workflow planning. Finally, traversability and drilling capabilities are validated using a simplified air inlet model. Test results confirm successful traversal on R200 mm curvature skins and automated drilling of Carbon Fiber-Reinforced Polymer (CFRP)/7075 aluminum stacks with a diameter of Φ4–Φ6 mm, achieving dimensional errors of less than 0.05 mm and normal direction errors of less than 0.65°. Full article

Background: Optical coherence tomography (OCT) can quantify the morphology and dimensions of a macular hole for diagnosis and treatment planning. Objective: The aim of this study was to perform automatic segmentation of macular holes (MHs) and cysts from OCT macular volumes using a deep learning-based model and to quantitatively evaluate decision reliability using the model’s focus regions and GradientSHAP-based explainability. Methods: In this study, we automatically segmented MHs and cysts in OCT images from the open-access OIMHS dataset. The dataset comprises 125 eyes from 119 patients and 3859 OCT B-scans. OCT B-scan slices were input to a UNet-48-based model with a 2.5D stacking strategy. Performance was evaluated using Dice and intersection-over-union (IoU), boundary accuracy was evaluated using the 95th-percentile Hausdorff distance (HD95), and calibration was evaluated using the expected calibration error (ECE). Explainability was quantified from GradientSHAP maps using lesion coverage and spatial focus metrics: Attribution Precision in Lesion (APILτ), which is the proportion of attributions (SHAP contributions) falling inside the lesion; Attribution Recall in Lesion (ARILτ), which is the proportion of the true lesion covered by the attributions; and leakage (Leakτ = 1 − APILτ), which is the proportion of attributions falling outside the lesion. Spatial focus was monitored using the center-of-mass distance (COM-dist), which is the Euclidean distance between the attribution center and the segmentation center. All metrics were calculated using the top τ% of the pixels with the highest SHAP values. SHAP features were clustered using PCA and k-means. Explanations were calculated using the clinical mask in ground truth (GT) mode and the model segmentation in prediction (Pred) mode. Results: The Dice/IoU values for holes and cysts were 0.94/0.91 and 0.87/0.81, respectively. Across lesion classes, HD95 = 6 px and ECE = 0.008, indicating good boundary accuracy and calibration. In GT mode (τ = 20), three regimes were observed: (i) retina-dominant: high ARIL (hole: 0.659; cyst: 0.654), high Leak (hole: 0.983; cyst: 0.988), and low COM-dist (hole: 7.84 px; cyst: 6.91 px), with the focus lying within the retina and largely confined to the retinal tissue; (ii) peri-lesional: highest ARIL (hole: 0.684; cyst: 0.719), relatively lower Leak (hole: 0.917; cyst: 0.940), and medium/high COM-dist (hole: 16.22 px; cyst: 10.17 px), with the focus located around the lesion; (iii) narrow-coverage: primarily seen for cysts in GT mode (ARIL: 0.494; Leak: 1.000; COM-dist: 52.02 px), with markedly reduced coverage. In Pred mode, the ARIL20 for holes increased in the retina-dominant cluster (0.758) and COM-dist decreased (6.24 px), indicating better agreement with the model segmentation. Conclusions: The model exhibited high accuracy and good calibration for MH and cyst segmentation in OCT images. Quantitative characterization of SHAP validated the model results. In the clinic, peri-lesion and narrow-coverage conditions are the key situations that require careful interpretation. Full article

We review some aspects of accretion disks physics, spacetime photon shell and photon orbits, related to retrograde (counter-rotating) motion in Kerr black hole (BH) spacetimes. In this brief review, we examine the counter-rotating components of the Kerr BH shadow boundary, under the influence of counter-rotating accretion tori, accreting flows and proto-jets (open critical funnels of matter, associated with the tori) orbiting around the central BH. We also analyze the redshifted emission arising from counter-rotating structures. Regions of the shadows and photon shell are constrained in their dependence of the BH spin and observational angle. The effects of the counter-rotating structures on these are proven to be typical of the fast-spinning BHs, and accordingly can be observed only in the restricted classes of the Kerr BH spacetimes. This review is intended as a concise guide to the main properties of counter-rotating fluxes and counter-rotating disks in relation to the photon shell and the BH shadow boundary. Our findings may serve as the basis for different theoretical frameworks describing counter-rotating accretion flows with observable imprints manifesting at the BH shadow boundary. The results can eventually enable the distinction of counter-rotating fluxes through their observable imprints, contributing to constraints on both the BH spin and the structure of counter-rotating accretion disks. In particular, photon trajectories and their impact parameters can manifest in the morphology of the BH shadow. Such features, when accessible through high-resolution imaging and spectral or polarization measurements, could provide a direct avenue for testing different theoretical models on accretion disk dynamics and their BH attractors. Full article

Conventional tourism planning in ecologically fragile regions often adopts a reductionist perspective, failing to address the synergistic spatial interactions between ecological conservation, resource utilization, and infrastructure. To bridge this gap, this study develops a multi-constraint synergistic assessment framework for the dry-hot valley of Lujiang Dam (LJD) in China. Grounded in the understanding of rural tourism as a complex adaptive system, the framework innovatively integrates the InVEST model, kernel density estimation, and cumulative cost-distance algorithms to identify Natural Spatial Suitability for Tourism Development (NSSTD). Key findings include (1) pronounced spatial heterogeneity in habitat quality, with high-quality zones in the west/southeast requiring strict conservation; (2) a “barbell-shaped” clustering of natural/cultural resources at the valley’s northern and southern extremities, highly congruent with ethnic settlements; and (3) a “concentric layered” accessibility pattern where 88.08% of resources are within a 90 min drive. Crucially, the spatial overlay analysis revealed that NSSTD (54.74 km²) emerges not from single high-value zones but from areas of synergy, such as those with medium habitat quality coupled with high resource endowment and accessibility. These results provide a scientifically robust, spatially explicit layer for China’s “Multi-plan Integration” territorial spatial planning. They enable differentiated strategies—channeling development to southern corridors, implementing niche tourism in northern “structural hole” villages, and enforcing conservation in western habitats—thereby offering a replicable methodology to balance ecological integrity with sustainable rural development. Full article

This paper presents the design, optimization, and measurement validation of a highly compact and frequency-selective Microstrip Crossover architecture for microwave applications, specifically targeting the 2.4 GHz band. The proposed design features a modified hexagonal structure enhanced with Sierpinski carpets, four loading stubs on the access lines, and Defected Ground Structures (DGS), along with two via holes to excite a new operating mode. This integration achieves an outstanding miniaturization ratio, occupying 62% less surface area compared to conventional crossover designs. Through simulation, the optimized structure demonstrates superior performance with low insertion loss of 1 dB and Isolation/Matching better than 20 dB at 2.4 GHz. A key contribution is the demonstrated response controllability, where the loading stubs and DGS serve as independent tuning elements: the stub length controls the frequency of the lower band transmission zeros for selectivity control, while the DGS dimensions govern the passband width and Fractional Bandwidth (FBW). Full article

Monitoring bottom-hole pressure (BHP) is critical for reservoir management and flow assurance, especially in offshore fields where challenging conditions and production losses are more impactful. However, reliability issues and high installation costs of Permanent Downhole Gauges (PDGs) often limit access to this vital data. Soft sensors offer a cost-effective and reliable alternative, serving as backups or replacements for physical sensors. This study proposes a novel data-driven methodology for estimating flowing BHP using wellhead and topside measurements from plant monitoring systems. The framework employs ensemble methods combined with clustering techniques to partition datasets, enabling tailored supervised training for diverse production conditions. Aggregating results from sub-models enhances performance, even with simpler machine learning algorithms. We evaluated Linear Regression, Neural Networks, and Gradient Boosting (XGBoost and LightGBM) as base models. A case study of a Brazilian Pre-Salt offshore oilfield, using data from 60 wells across nine platforms, demonstrated the methodology’s effectiveness. Error metrics remained consistently below 2% across varying production conditions and reservoir lifecycle stages, confirming its reliability. This solution provides a practical, economical alternative for studies and monitoring in wells lacking PDG data, improving operational efficiency and supporting reservoir management decisions. Full article

Roof damage caused by hurricanes and other storms needs to be rapidly identified and repaired to help communities recover from catastrophic events and support the well-being of residents. Traditional, ground-based inspections are time-consuming but have recently been expedited via manual interpretation of remote sensing imagery. To potentially accelerate the process, automated methods involving artificial intelligence (i.e., deep learning) can be applied. Here, we present an end-to-end workflow for training and evaluating deep learning image segmentation models that detect and delineate two classes of post-storm roof damage: roof decking and roof holes. Mask2Former models were trained using 2500 roof decking and 2500 roof hole samples from drone RGB orthomosaics (0.02–0.08 m ground sample distance [GSD]) captured in Sint Maarten and Dominica following Hurricanes Irma and Maria in 2017. The trained models were evaluated using 1440 reference samples from 10 test images, including eight drone orthomosaics (0.03–0.08 m GSD) acquired outside of the training areas in Sint Maarten and Dominica, one drone orthomosaic (0.05 m GSD) from the Bahamas, and one orthomosaic (0.15 m GSD) captured in the US Virgin Islands with a crewed aircraft and different sensor. Accuracies increased with a single-class modeling approach (instead of training one dual-class model) and expansion of the training datasets with 500 roof decking and 500 roof hole samples from external areas in the Bahamas and US Virgin Islands. The best-performing models reached overall F1 scores of 0.88 (roof decking) and 0.80 (roof hole). In this study, we provide: our end-to-end deep learning workflow; a detailed accuracy assessment organized by modeling approach, damage class, and test location; discussion of implications, limitations, and future research; and access to all data, tools, and trained models. Full article

We present a quantitative theory of contraction and expansion cycles within the Quantum Memory Matrix (QMM) cosmology. In this framework, spacetime consists of finite-capacity Hilbert cells that store quantum information. Each non-singular bounce adds a fixed increment of imprint entropy, defined as the cumulative quantum information written irreversibly into the matrix and distinct from coarse-grained thermodynamic entropy, thereby providing an intrinsic, monotonic cycle counter. By calibrating the geometry–information duality, inferring today’s cumulative imprint from CMB, BAO, chronometer, and large-scale-structure constraints, and integrating the modified Friedmann equations with imprint back-reaction, we find that the Universe has already completed $N_{\mathrm{past}}=3.6\pm 0.4$ cycles. The finite Hilbert capacity enforces an absolute ceiling: propagating the holographic write rate and accounting for instability channels implies only $N_{\mathrm{future}}=7.8\pm 1.6$ additional cycles before saturation halts further bounces. Integrating Kodama-vector proper time across all completed cycles yields a total cumulative age $t_{\mathrm{QMM}}=62.0\pm 2.5\mathrm{Gyr}$, compared to the $13.8\pm 0.2\mathrm{Gyr}$ of the current expansion usually described by $\mathrm{\Lambda }$CDM. The framework makes concrete, testable predictions: an enhanced faint-end UV luminosity function at $z\gtrsim 12$ observable with JWST, a stochastic gravitational-wave background with $f^{2/3}$ scaling in the LISA band from primordial black-hole mergers, and a nanohertz background with slope $\alpha \simeq 2/3$ accessible to pulsar-timing arrays. These signatures provide near-term opportunities to confirm, refine, or falsify the cyclical QMM chronology. Full article

Electronic quick response (e-QR) codes provide access to real-time sensor data using smartphone readers and internet connectivity. Printed electronics and hybrid integration on flexible substrates is a promising solution for wide-scale and low-cost deployment of sensor systems. This paper presents a 21 × 21-pixel e-QR display implemented on black Kapton using hybrid additive and subtractive microfabrication techniques. The process flow for the double-sided circuit allows for layer alignment using multiple fiducial markers. The steps include inkjet printing of tracks on both sides of the substrate, laser-cut via holes, stencil-aided via filling, solder paste dispensing, and final integration of discrete surface-mount components by semi-automatic pick-and-place. Full article

Significant risk of water and sand inrushes is commonly encountered during coal seam mining when thin bedrock is directly overlain by thick, water-bearing, unconsolidated layers. Achieving effective strata control and establishing reliable water-isolating mechanisms under these conditions represent critical scientific and technological challenges for safe mining operations. Furthermore, this is a vital research direction for advancing the extraction limit (or recovery height) in coal seams. Initially, drawing on key stratum theory, ground pressure behavior patterns, and mining operation characteristics, the weathered zone was identified as the critical grouting horizon. During the initial mining stage, the first two periodic weighting intervals (approximately 60 m) were identified as the key area. Subsequently, a strategy of high-pressure grouting was proposed to modify the weathered stratum. Numerical simulation methods were employed to optimize the grouting parameters, with the core specifications determined as follows: grouting pressure ≥30 MPa, water–cement ratio of 0.7:1, and grouting hole spacing ≤30 m. Ultimately, a grouting system was designed that used directional drilling from the surface to access the weathered zone, followed by branched horizontal boreholes for staged high-pressure grouting. The borehole trajectory was predominantly L-shaped. Field implementation demonstrated that the grouting intervention increased the first weighting span by an average of 17.3%. Critically, no water inflow was observed throughout the initial caving period, and significant roof falls or rib spalling were effectively mitigated. This confirmed a substantial improvement in key stratum stability, ensuring the safe and efficient advancement of the mining face. This study provides essential technical support and a practical model for safely and efficiently extracting coal seams under thin bedrock under similar complex hydrogeological conditions. Full article

TiO₂ photocatalysts exhibit great potential in solar fuel production and environmental remediation, yet their practical applications are often hindered by high electron-hole recombination rates. This study presents a novel strategy for fabricating hollow anatase TiO₂-modified ZnS heterostructures (TiO₂/ZnS) via a simple hydrothermal method. The heterostructure effectively combines the high electron mobility of ZnS, which facilitates rapid photogenerated electron transfer, with the high specific surface area of hollow TiO_2, which enhances pollutant adsorption. As a result, TiO₂/ZnS demonstrates superior tetracycline degradation efficiency due to optimized charge separation and improved accessibility to reactive sites, compared to pristine TiO₂ and ZnS. Furthermore, the enhanced photocatalytic activity is attributed to efficient charge separation facilitated by Type-II heterojunctions between ZnS and anatase TiO₂. Cycling tests reveal that TiO₂/ZnS retains over 94% of its activity after 5 cycles. This work offers a versatile approach for stabilizing metal oxides through heterostructure engineering, with significant implications for scalable environmental catalysis. Full article

Outdoor access, often referred to as pop holes, is widely used to improve the production and welfare of hens. Such cage-free environments present an opportunity for precision flock management via best environmental control practices. However, outdoor access disrupts the integrity of the indoor environment, including properly planned ventilation. Moreover, complaints exist that hens do not use the holes to access the outdoor environment due to the strong incoming airflow through the outdoor access, as they behave as uncontrolled air inlets in a negative pressure ventilation system. As the egg industry transitions to cage-free systems, there is an urgent need for validated computational fluid dynamics (CFD) models to optimize ventilation strategies that balance animal welfare, environmental control, and production efficiency. We developed and validated CFD models of a cage-free hen house with outdoor access by specifying real-world conditions, including two exhaust fans, sidewall ventilation inlets, wire-meshed pens, outdoor access, and plenum inlets. The simulations of four ventilation scenarios predict the measured air flow velocity with an error of less than 50% for three of the scenarios, and the simulations predict temperature with an error of less than 6% for all scenarios. Plenum-based systems outperformed sidewall systems by up to 136.3 air changes per hour, while positive pressure ventilation effectively mitigated disruptions to outdoor access. We expect that knowledge of improved ventilation strategy will help the egg industry improve the welfare of hens cost-effectively. Full article

The modern Chinese architectural heritage combines sturdy Western materials with delicate Chinese styling, mainly adopting brick-timber structural systems that are highly vulnerable to fire damage. The study assesses the fire spread characteristics of the First Faculty House, a 20th-century architectural heritage located at a university in China. The assessment is carried out by analyzing building materials, structural configuration, and fire load. By using FDS (Fire Dynamics Simulator (PyroSim version 2022)) and SketchUp software (version 2023) for architectural reconstruction and fire spread simulation, explores preventive measures to reduce fire risks. The result show that the total fire load of the building amounts to 1,976,246 MJ. After ignition, flashover occurs at 700 s, accompanied by a sharp increase in the heat release rate (HRR). The peak ceiling temperature reaches 750 °C. The roof trusses have critical structural weaknesses when approaching flashover conditions, indicating a high potential for collapse. Three targeted fire protection strategies are proposed in line with the heritage conservation principle of minimal visual and functional intervention: fire sprinkler systems, fire retardant coating, and fire barrier. Simulations of different strategies demonstrate their effectiveness in mitigating fire spread in elongated architectural heritages with enclosed ceiling-level ignition points. The efficacy hierarchy follows: fire sprinkler system > fire retardant coating > fire barrier. Additionally, because of chimney effect, for fire sources located above the ceiling and other hidden locations need to be warned in a timely manner to prevent the thermal plume from invading other sides of the ceiling through the access hole. This research can serve as a reference framework for other Modern Chinese Architectural Heritage to develop appropriate fire mitigation strategies and to provide a methodology for sustainable development of the Chinese architectural heritage. Full article

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Background and Importance: Chronic subdural hematoma (cSDH) is a common and complex neurosurgical problem, particularly in elderly patients. Revision surgery for chronic subdural hematoma can be challenging, particularly in cases with inhomogeneous, firm consistency and extensive adhesions. Clinical Presentation: In this article, we present our endless-loop craniotomy technique, which offers a novel approach to address these challenges by performing the wide, curved exposure of the subdural space utilizing the already-present burr hole. This technique allows for a wide, unobstructed view of the subdural space, enabling the access and evacuation of this chronic and often adhesive subdural hematoma. Conclusion: We believe that endless-loop craniotomy is a valuable addition to the neurosurgeon’s armamentarium for managing complex cases of revision surgery in chronic subdural hematomas. Full article