Search Results (30,116)

Support structures in liquid hydrogen tanks act as localized thermal bridges between the ambient temperature outer vessel and the cryogenic inner vessel. However, the difference between support thermal bridge-induced localized heat input and equivalent uniform heat input remains insufficiently clarified, especially regarding their effects on local thermal behavior and support position-dependent thermodynamic response. In this study, a gas–liquid two-phase CFD model was developed for a 37.4 m³ liquid hydrogen tank at a 50% filling ratio. Localized heat flux regions were used to represent support thermal bridges, and an equivalent uniform heat input case with the same total heat input was introduced for comparison. The results show that localized support heat input concentrates the high-temperature region near the support-corresponding wall area and induces stronger local natural convection with a maximum velocity of approximately 0.27 m/s, compared to approximately 0.14 m/s in the uniform heat input case. The uniform heat input case produces a slightly higher overall gas-phase pressure, but it cannot capture the local heat accumulation and flow field reconstruction caused by support thermal bridges. Circumferential support position variation mainly affects the relative position between the localized heat source, gas region, liquid region, and gas–liquid interface. Upper support position variation has a more pronounced influence on local peak temperature and flow intensity than lower support variation. Axial support position variation mainly shifts the local high-temperature and high-velocity regions along the tank length, while its influence on overall pressure response is limited. These results indicate that equivalent uniform heat input can approximate the overall pressurization trend, but localized support heat input boundaries should be retained when local temperature fields, flow structures, and support layout effects are of concern. Full article

Aging disrupts sleep, but how these changes are structured across circadian time, vigilance states, and sex remains poorly understood, because most prior studies used single-sex cohorts and few days of recordings. We continuously recorded 14 days of EEG/EMG in 24 C57BL/6J mice using a balanced 2 × 2 design (young vs. old; male vs. female; n = 6/group). A comprehensive multiscale analysis of the extended dataset enabled detailed reconstruction of 24 h sleep–wake architecture, better characterization of natural day-to-day variability including across multiple estrous cycles, and detection of rare bouts and transition events. Across seven levels of analysis, from circadian profiles to EEG spectral parameterization, the strongest aging effect was a dark-phase-specific 17–18% loss of theta-dominant active wake (TDW) in both sexes, with reciprocal increases in quiet wake (nTDW) and NREM sleep. We also identified a recurring N-shaped structural motif at the dark-to-light transition, where age-related and several sex-associated differences were most apparent. Broadly, old mice exhibited (i) shorter TDW bouts; (ii) a shift in NREM exit kinetics toward wakefulness; (iii) more brief and poorly consolidated “out-block” NREM episodes; and (iv) a slowing of waking theta and higher low-frequency TDW power. Variance decomposition indicated that statistical power depends more on sample size than on recording length. Together, aging reflects a coordinated, circadian-phase-specific reorganization of sleep–wake architecture. Sex-related and interaction findings should be interpreted as hypothesis-generating pending larger cohorts. Full article

This report describes a unique constellation of accessory ossicles, highlighting their anatomical, clinical, and radiological significance. A 43-year-old female undergoing imaging for suspected fracture was evaluated using multi-detector computed tomography (MDCT) with 1.25 mm slice thickness. Multiplanar reconstructions (axial, coronal, sagittal) and three-dimensional volume-rendered images were analyzed. CT imaging revealed the coexistence of an os subfibulare and a tripartite os naviculare. Multiplanar and three-dimensional reconstructions confirmed the presence and configuration of variants. The combination of supernumerary bones and a multipartite ossicle represents an exceedingly uncommon anatomical presentation. This case illustrates an exceptional coexistence of multiple accessory ossicles, including an exceedingly rare tripartite os naviculare. Thorough radiological evaluation using MDCT and multiplanar reconstructions is essential for accurate identification and differentiation from fractures or other pathology. Full article

Background/Objectives: Computer-aided surgical planning (CASP) technologies, including virtual surgical planning (VSP), 3D printed cutting guides, and patient-specific implants, have been increasingly applied to deep circumflex iliac artery (DCIA) free flap reconstruction of maxillofacial defects. Despite growing adoption, no systematic review has specifically evaluated their accuracy and clinical outcomes. This study aimed to comprehensively assess the impact of CASP on reconstruction accuracy, operative efficiency, flap survival, and implant rehabilitation in DCIA flap surgery. Methods: A systematic search of PubMed, Web of Science, and Google Scholar was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Studies reporting CASP-assisted DCIA free flap reconstruction with three or more patients were included. Methodological quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) checklist and the Cochrane Risk of Bias 2.0 tool for the randomized controlled trial (RCT). Results: Thirty studies (1 RCT, 13 comparative, and 16 non-comparative) involving 844 patients were included. VSP with 3D-printed cutting guides was the most frequently used technology (n = 22). Mean linear deviations between planned and actual outcomes ranged from 0.40 to 4.4 mm, with most studies reporting 0.7–2.7 mm. The sole RCT demonstrated significantly better accuracy (1.3 vs. 5.5 mm, p < 0.001) and shorter reconstruction time (16 vs. 39 min, p < 0.001) with CASP. Flap survival ranged from 90% to 100%. Conclusions: CASP technologies, particularly VSP with 3D-printed cutting guides, appear to improve the accuracy and predictability of DCIA flap reconstruction. However, the evidence base is predominantly retrospective and heterogeneous; prospective multicenter studies with standardized outcome measures are needed before definitive clinical guidelines can be established. Full article

The digital preservation of built cultural heritage requires precise documentation techniques capable of capturing complex architectural geometries often affected by occlusions and data voids. This study presents a robust multi-sensor fusion workflow integrating Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) photogrammetry for the 3D reconstruction of the Hasaköy (Sasima) Church in Niğde, Türkiye. To address the limitations of traditional registration methods, specifically the susceptibility of the Iterative Closest Point (ICP) algorithm to local minima in datasets with partial overlaps, this study proposes a fine-tuning approach based on the Multi-population Based Differential Evolution (MDE) algorithm. The methodology employs a coarse-to-fine strategy, initiating with Fast Point Feature Histogram (FPFH) extraction and RANSAC (Random Sample Consensus) for global alignment, followed by TR-ICP, MDE, PSO, and Aquila Optimizer (AO) evaluation, computational-time analysis, FPFH-radius sensitivity testing, and 6-DoF transformation decomposition to characterize both accuracy and operational cost. In the 30-run fine-tuning evaluation, MDE reduced the mean bidirectional trimmed RMSE from 0.4152 m for TR-ICP to 0.3726 m. With a population parameter of 10, MDE retained a low median RMSE of 0.3718 m, while PSO exhibited a wider stochastic tail under the same bounded 6-DoF search budget. AO produced a higher mean bidirectional trimmed RMSE of 0.5233 m. The decimeter-scale bidirectional RMSE should be interpreted as a cross-source, partial-overlap distance metric rather than sensor precision; the overlapping facade objective was approximately 2.4–2.8 cm, and the UAV block was independently controlled with a 1.34 cm GCP RMSE. This study establishes a transparent and reproducible framework for heritage documentation, supporting the faithful digital preservation of endangered monuments with complex typologies. Full article

To solve the low-precision prediction problem of noisy non-stationary goaf subsidence sequences, this study aims to establish a high-accuracy hybrid prediction model for mining surface deformation monitoring. The Global Navigation Satellite System (GNSS) monitoring data of surface subsidence in goaf areas exhibits non-stationary and noisy characteristics, which limits the accuracy of traditional prediction models. In this paper, a hybrid prediction model, namely the Improved Radial Movement Optimization–Variational Mode Decomposition–Gated Recurrent Unit (IRMO-VMD-GRU) model, is proposed. The IRMO algorithm is employed to globally optimize the key parameters of VMD, achieving adaptive and stable decomposition of the settlement sequences. The obtained Intrinsic Mode Function (IMF) sub-sequences are input into the GRU network for independent training and prediction, followed by superposition and reconstruction. The model is validated using the GNSS monitoring data from three monitoring points at a coal mine in Shaanxi Province, China. The results show that the proposed model outperforms the comparison models in all four evaluation indicators, namely Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R²), with all R² values exceeding 0.8. The model demonstrates superior fitting performance, correlation, and generalization ability, which provides important practical technical support for goaf subsidence early warning, geological disaster prevention and engineering safety management in mining areas. Full article

Reliable spatial georeferencing of mobile mapping platforms is a fundamental prerequisite for high-fidelity urban remote sensing products such as 3D point clouds and digital twins. However, in deep urban canyons, severe signal occlusion and multipath effects reduce visible GNSS satellites, causing ambiguity resolution (AR) failure and degraded observation geometry for UGV-borne systems. Conventional Vehicle-to-Vehicle (V2V) cooperation offers limited improvement due to symmetric ground-level occlusion. To overcome this, we propose an asymmetric GNSS/UWB fusion method that introduces Unmanned Aerial Vehicles (UAVs) as high-altitude dynamic spatial anchors to reconstruct the 3D observation geometry. Two contributions are presented: (i) an asymmetric heterogeneous stochastic model coupling carrier-to-noise ratio (C/N0) and elevation angle to handle the quality disparity between air and ground sensor links, preventing multipath contamination of high-fidelity UAV observations; and (ii) a dynamic baseline constrained least-squares algorithm integrating Ultra-Wideband (UWB) ranging to stabilize GNSS positioning under high-dynamic relative motion. Validated through high-fidelity simulations and field experiments, the method achieves a 98.2% AR success rate and sub-decimeter 3D accuracy under extreme occlusion (≤3 visible satellites), while urban-canyon tests demonstrate 100% positioning availability across all evaluated epochs and reduce the 95th-percentile 3D error from 7.25 m to 0.19 m under the tested single-UAV/single-UGV configuration. The framework supports smart city modeling, 3D reconstruction, and infrastructure monitoring. Full article

Direction-of-arrival (DOA) estimation of cyclostationary signals is an important problem in array signal processing, especially in sensor-limited and underdetermined scenarios. Sparse arrays and cyclostationary statistics can improve virtual degrees of freedom and target selectivity, but incomplete difference coarray information caused by missing lags may degrade virtual covariance reconstruction and reduce the reliability of DOA estimation in closely spaced, coherent, and interference-contaminated environments. To address this issue, this paper proposes a cyclostationary DOA estimation method based on an augmented extended coprime array (AECA), SVT-based hole recovery, and weighted atomic norm minimization (ANM). The proposed method first constructs the cyclic correlation matrix at the target cyclic frequency and maps it into the AECA-based virtual coarray domain. Redundant lag observations are then aggregated, and an iterative hole recovery procedure is applied to obtain an initial structured virtual covariance matrix. On this basis, a weighted ANM-based covariance refinement model is introduced, where directly observed lags and SVT-recovered hole entries are assigned different confidence levels. The final DOA estimates are obtained using MUSIC on the refined virtual covariance matrix. Simulation results under the considered underdetermined, closely spaced, coherent-source, and interference-contaminated scenarios show that the proposed method achieves lower RMSE and clearer spectral responses than the selected baseline methods. Additional ablation, parameter sensitivity, cyclic frequency mismatch, non-Gaussian noise, and runtime analyses further clarify the contribution, robustness range, and computational cost of the proposed framework. Full article

This paper focuses on the significant potential of specific optical non-invasive methods, such as digital holographic microscopy, digital speckle pattern interferometry, and digital holographic interferometry, as scientific and technological tools for retrieving physical and biomechanical parameters embedded in the optical phase of laser-illuminated biomedical samples. These techniques take advantage of the laser speckle phenomena observed when non-specular surfaces are illuminated, enabling whole-field measurements and reconstruction of 3D images. Their versatility in implementation and application has led to advances in various fields of research and has broadened our understanding in both the basic and applied sciences. In clinical environments, the aforementioned quantitative optical studies are particularly valuable for understanding the behavior of biological samples, as they allow precise characterization of deformations, displacements, stress, strain, refractive index, and morphological features. Applications presented span from soft to hard tissues at both micro- and macro-scales, with results obtained from vocal cords, skin tissues, melanoma cells, and teeth. Furthermore, this overview provides a general perspective of some current speckle-based approaches and their growing relevance in biomedical research. Full article

Multimedia recommenders can use behavioral records together with visual and textual item information, but unreliable interactions and sparse histories still make user preference modeling difficult. Most graph-based methods propagate messages over observed user–item edges as if all interactions were equally informative, so incidental or semantically inconsistent behaviors may distort the learned representations. The standard recommendation loss also provides limited context for modeling dependencies within a user’s historical sequence. We propose MGDSL, a MGDSL applies a multimodal-aware topology denoising module to calculate edge reliability weights for historical interactions from collaborative, textual, and visual evidence, and uses these weights for reliability-aware historical aggregation. In parallel, a masked self-supervised auxiliary task reconstructs masked items from sequence context, adding supervision for latent preference learning. Experiments on three benchmark datasets show that MGDSL consistently improves recommendation accuracy over competitive baselines, with particularly clear gains on the sparsest dataset. Full article

Geometric monitoring of slender support structures, particularly steel lattice transmission towers, is a critical component of power infrastructure diagnostics. Such structures are susceptible to environmental influences and long-term deformation processes, which necessitates precise assessment of their geometric axis. The aim of this study was to evaluate the influence of the terrestrial laser scanning (TLS) scanner class and point cloud registration strategy on the determination of the geometric axis of a steel high-voltage lattice transmission tower (hereafter LTT). Unlike previous studies focused primarily on TLS-based axis reconstruction, this work introduces a comparative assessment of registration strategies, an error propagation model, and the proposed Axis Drift Index (ADI) as quantitative indicators of axis stability. The analysis was based on data obtained using a tachymetric method (reference), a compact scanner (Leica BLK360), and a survey-grade scanner (Riegl VZ-400i). The comparison included planimetric axis deviation, consistency of deformation direction, variation in results with height, and the influence of registration quality. The results show that TLS measurements performed using a survey-grade scanner and target-based registration exhibit high agreement with tachymetric results. In contrast, cloud-to-cloud registration without a stable reference framework leads to cumulative errors and instability of the reconstructed axis, particularly in the upper parts of the structure. The observed deviations in the BLK360 dataset were dominated by registration-related geometric instability rather than unequivocal structural deformation signals. The findings indicate that the accuracy of geometric axis determination in slender structures is governed more by the adopted point cloud registration strategy than by the scanner class itself. The proposed ADI parameter and linear error propagation model additionally enabled a quantitative assessment of geometric consistency with height. From an engineering perspective, this highlights the importance of stable reference systems and appropriate survey design in high-precision TLS applications. Although the study was conducted on a single lattice tower, the results provide practical insight into the reliability of TLS workflows for slender structures characterized by discontinuous geometry and high sensitivity to registration errors. Full article

The second-hand Battery Electric Vehicle (BEV) market in Italy is affected by substantial information asymmetry, particularly with regard to battery State of Health (SOH), residual value, and expected maintenance costs. This lack of transparency limits consumer confidence and reduces the potential of used BEVs to support a broader and more inclusive electric mobility transition. In this study, a data-driven decision-support framework is developed to improve the evaluation of second-hand BEVs in the Italian market. The proposed approach combines market data collected from major online platforms with historical price reconstruction and an assessment of the information asymmetries that limit user confidence in the second-hand BEV market. It also incorporates a semi-empirical SOH estimation model based on observable vehicle characteristics. The results reveal a consistent depreciation gap between BEVs and comparable internal combustion engine vehicles across different market segments and indicate that battery-related uncertainty appears to be one of the factors associated with consumer hesitation. The framework shows that combining non-invasive battery-health estimation with maintenance-related information can support a more objective assessment of used electric vehicles. Overall, the study demonstrates the potential of integrated digital and engineering-based tools to reduce uncertainty and enhance transparency in the second-hand BEV market. Full article

Aiming at the problems of glare interference, local overexposure and detail loss caused by artificial light sources such as vehicle lamps and street lamps in nighttime road scenes, as well as the challenges of existing glare suppression models with large parameters, high computational complexity and difficulty in deploying on edge devices, this paper proposes a lightweight glare suppression network (LGSNet) based on ghost depthwise separable convolution and Lightweight Parallel Attention. Based on the U-Net architecture, the network introduces ghost depthwise separable convolution blocks (GhostDSC) in the encoder and decoder, which generates ghost features through cheap linear transformations by exploiting feature map redundancy, significantly reducing model parameters and computational costs while maintaining feature representation ability. Meanwhile, a Lightweight Parallel Attention (LPA) module is designed in the decoder stage, which integrates channel attention and pixel attention in parallel, enhancing the network’s attention to glare regions and edge details with extremely low parameter increment to improve detail recovery accuracy. In addition, a joint loss function consisting of background loss, glare loss and reconstruction loss is constructed to collaboratively optimize glare suppression and detail preservation. Experimental results on the public Flare7K++ dataset and the self-built nighttime road glare dataset NRGD show that the proposed method has only 7.45 M parameters, much lower than standard U-Net and Uformer. It achieves competitive results on full-reference metrics such as PSNR, SSIM, LPIPS and no-reference metrics such as NIQE, BRISQUE, PIQE, and can effectively suppress various types of glare interference and restore obscured scene details. It achieves a superior trade-off between model complexity and enhancement performance, significantly reducing the parameter count and computational overhead compared to heavy baselines, thereby offering a highly efficient solution for resource-aware glare suppression tasks. Full article

The white rhinoceros (Ceratotherium simum) offers a unique model for investigating the genomic consequences of extreme demographic bottlenecks. However, the fragmented southern white rhinoceros genome assembly has limited chromosome-scale structural and evolutionary comparisons with the functionally extinct northern subspecies. Here, we report a chromosome-scale genome assembly for the southern white rhinoceros by integrating Oxford Nanopore Technology long-read sequencing, Illumina short-read polishing and high-throughput chromosome conformation capture (Hi-C) scaffolding. The final assembly spans 2.48 Gb and achieves a contig N50 of 42.06 Mb, representing a 452-fold improvement in contiguity over the previous assembly. In total, 2.46 Gb of sequence was anchored to 40 autosomes plus the X and Y chromosomes. Genome annotation identified 1.13 Gb of repetitive elements (45.7% of the assembly), 22,593 protein-coding genes, and 100.68 Mb of segmental duplications. Inspection of the major histocompatibility complex class II gene region further supported the local assembly and annotation reliability, revealing conserved gene composition and order between the southern and northern white rhinoceroses. Whole-genome comparison with the northern white rhinoceros assembly indicated extensive chromosome-scale synteny, along with localized structural variants between the two subspecies, including 111 inversions spanning 33.48 Mb and 497 translocations spanning 36.48 Mb. Furthermore, coalescent demographic reconstruction indicated asynchronous Pleistocene population dynamics for southern and northern white rhinoceroses, reflecting divergent responses to historical climate oscillations. Both subspecies also exhibit lower recent effective population sizes than estimated Pleistocene ancestral levels, underscoring persistent conservation concern. This assembly provides a useful resource for evaluating the genomic consequences of historical bottlenecks, informing future genomic-rescue plans, and strengthening the comparative framework for rhinoceros conservation and evolutionary genomics. Full article

Background: Modern warfare has introduced novel mechanisms of injury, particularly drone-induced blast trauma, resulting in complex craniomaxillofacial injuries. These injuries differ substantially from typical ballistic wounds and require adapted surgical strategies. This study was conducted to evaluate the clinical characteristics, management approaches, and long-term outcomes of midfacial blast injuries. Methods: A retrospective analytical study was conducted on 41 patients with drone-induced midfacial blast injuries treated at a tertiary referral center in Armenia following the 2020 Nagorno-Karabakh War. All patients underwent surgical management after initial stabilization and were followed for 5 years. Clinical outcomes, complications, and reconstructive needs were assessed. Results: All patients presented with comminuted midfacial fractures, which were frequently associated with polytrauma (87.8%). Burns were observed in 82.9% of cases. Surgical management included radical debridement and early definitive osteosynthesis using titanium fixation systems. No cases of postoperative osteomyelitis, bone sequestration, or implant failure were observed during the 5-year follow-up period. Patients with extensive soft tissue defects, particularly nasal and lip amputations, required multiple reconstructive procedures. Long-term follow-up revealed progressive soft tissue thinning over titanium meshes, especially in the zygomatico-orbital region, necessitating secondary interventions such as lipofilling. Conclusions: Drone-induced midfacial blast injuries represent a distinct and severe form of trauma. Early definitive reconstruction following adequate debridement was associated with favorable outcomes. However, soft tissue reconstruction remains challenging and often requires staged procedures. Long-term follow-up is essential to manage delayed complications and optimize aesthetic outcomes. Full article