Search Results (3,254)

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

The rapid proliferation of low-altitude unmanned aerial vehicle (UAV) applications has made autonomous identification technology critical for flight safety and collaborative operations. In this paper, we propose and systematically analyze an autonomous identification scheme based on Bluetooth Low Energy (BLE) technology. We formulate a comprehensive system model that integrates link budget, packet collision, identification success probability, and power consumption. By incorporating safety interval constraints and a three-channel integrated reception probability, we employ an exhaustive search algorithm to optimize monitoring strategy parameters, thereby achieving an optimal trade-off between the Recognition Success Rate (RSR) and power consumption. Simulation results indicate that, at a PHY 1 Mbps rate, the optimal monitoring strategy theoretically approaches the Target Level of Safety (TLS) requirements for civil UAVs under the defined model assumptions, with a power consumption of 19.24 mW and an Average First Identification Delay (AFID) of 105 ms. Furthermore, simulation analysis verifies the scheme’s feasibility under dynamic topology, interference, and multi-UAV scenarios, providing a solid theoretical and technical reference for the practical implementation of autonomous UAV identification. 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 extraction of speech emotion features—particularly at the utterance level—constitutes a critical yet challenging aspect of Speech Emotion Recognition (SER). Emotion represents high-level paralinguistic information, and not all segments within a speech signal carry emotionally salient cues, especially in longer utterances. Conventional methods that process entire utterances may thus waste computational resources and introduce irrelevant acoustic interference. To address this, we propose AdaPre-Selection, an adaptive pre-selection mechanism designed to identify and extract emotion-rich segments from speech signals. Acting as a flexible front-end compression module, AdaPre-Selection consists of two complementary components: an Active Emotion Positioning (AEP) module and a Passive Emotion Constraint (PEC) module. Within AEP, Temporal Length Selection (TLS) and Start Time Point Selection (STPS) operate jointly to adaptively locate the optimal emotional segment in each utterance. Evaluated on two benchmark datasets (IEMOCAP and MSP-IMPROV) using four state-of-the-art SER models, AdaPre-Selection consistently outperforms common preprocessing baselines and delivers the most substantial improvement in recognition performance. Full article

Constant current/voltage (CC/CV) output of wireless power transfer (WPT) systems deviates due to increased load resistance during charging and mutual inductance variations caused by misalignment. Dynamically regulating the DC input voltage can maintain a stable output at the preset value, and predicting the mutual inductance and load resistance can help monitor charging status. However, joint prediction of characteristics and regulation degree can be nonlinear and complicated. This work proposes a data-driven method for characteristic prediction and output optimization for WPT systems based on the current waveform from only the transmitter side. A Multi-Scale Parallel Convolutional (MSPC) neural network is applied to simultaneously predict the load resistance, mutual inductance, output deviation factor and regulation coefficient. By leveraging its multi-scale feature extraction capabilities, it can accurately estimate the aforementioned parameters based on only the AC current waveform at the transmitter side. To improve the model’s generalizability under practical conditions, transfer learning (TL) is utilized to minimize the discrepancy between simulated and physical data. Finally, a 140 W prototype of the series-series (SS)-compensated WPT system is built to validate the effectiveness of the proposed method. Full article

The development of sustainable and efficient plant growth substrates is crucial for modern agriculture. This study assessed the potential of plant pellets formulated from various lignocellulosic residues, either with or without bamboo biochar (BB-char) and arbuscular mycorrhizal fungi (AMF), to support seed germination and early seedling growth. Four types of residues, including coconut coir (CO), corn cob (CC), leaves from the genus Dipterocarpus (DL), and teak leaves (TL), were combined with soil and paper waste to produce eight pellet formulations, with commercial peat pellets serving as a control. Chemical analyses revealed significant variation among the pellet types, with pH values ranging from 6.40 to 7.65, electrical conductivity (EC) from 3.64 to 11.62 mS cm⁻¹, and differences in organic matter, carbon, and nutrient contents [nitrogen (N), phosphorus (P), potassium (K)], reflecting the influence of residue type and the addition of BB-char and AMF. Phytotoxicity screening using aqueous extracts demonstrated species-specific responses, with cucumber exhibiting high tolerance across treatments, whereas chili seeds were more sensitive. Final germination percentage (FGP) and seedling growth assays in greenhouse conditions showed that pellets derived from CC and CO, particularly when combined with BB-char and AMF (T6 and T7), enhanced shoot and root development in carrot, chili, cucumber, and tomato, approaching the performance of commercial peat pellets. In contrast, DL- and TL-based pellets resulted in lower germination and growth. These findings indicate that both the physicochemical properties of lignocellulosic wastes and the combination of BB-char and AMF are important factors influencing pellet efficacy, highlighting the potential of CC- and CO-based pellets as sustainable peat alternatives for early-stage plant cultivation. Full article

This study proposes an integrated terrestrial laser scanning (TLS)-based workflow for quantitatively and spatially assessing the relative geometric condition of exterior wall surfaces. The workflow consists of point-cloud acquisition, ROI definition, reference-plane estimation, signed-depth computation, grid-based spatial aggregation, specimen-based validation, and real exterior wall application. Rather than introducing a fundamentally new point-cloud processing algorithm, the main contribution lies in integrating established processing steps into a consistent surface-based assessment procedure and extending deviation evaluation from simple numerical summaries to spatial interpretation. A 3D-printed validation specimen with designed defect depths of 1, 3, 5, and 7 mm was used for quantitative validation. Among 136 designed defects, 123 ground-truth-mapped ROIs were evaluated, resulting in an MAE of 0.795 mm, RMSE of 1.168 mm, and P95 error of 2.511 mm. A RANSAC threshold-based sensitivity analysis confirmed that the final refined reference plane and major signed-depth statistics remained stable within the tested threshold range. The workflow was further applied to a real exterior wall dataset with 29,933,332 strict-ROI points, yielding a mean signed depth of 2.448 mm, median of 2.691 mm, RMSE of 9.956 mm, P95 of 17.121 mm, and maximum value of 90.827 mm. High-deviation regions with an absolute centered signed depth of 15 mm or greater occupied 28.218 m², corresponding to 10.62% of the valid analysis area, and were distributed across 57 connected clusters. These results indicate that the proposed workflow can support both quantitative deviation assessment and spatial interpretation of high-deviation regions, while the real exterior wall results should be interpreted as a relative geometric assessment and feasibility demonstration rather than absolute accuracy validation or structural damage assessment. Full article

Background/Objectives: Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is widely used for non-invasive assessment of coronary artery disease under stress and rest conditions. Although deep learning has shown promise for automated SPECT MPI interpretation, most studies focus on single-tracer datasets and do not explicitly account for tracer-dependent variability. This study developed and evaluated a multi-task deep learning framework with tracer-specific prediction heads for patient-level SPECT MPI classification. Methods: A convolutional neural network with a shared feature encoder and tracer-specific heads was implemented using polar map representations from technetium-99m (Tc-99m) and thallium-201 (Tl-201) studies. Transfer learning from ImageNet was applied. Stress-only, rest-only, and dual-input configurations were evaluated using repeated patient-stratified cross-validation and independent testing. Performance was assessed using ROC-AUC and balanced accuracy. Results: For Tc-99m normal versus abnormal perfusion classification, the stress-only model achieved the highest cross-validation AUC (0.88 ± 0.067) and test AUC of 0.88 [0.67–0.99]. For Tl-201 low-risk versus intermediate/high-risk classification, stress-based models achieved the highest cross-validation AUC (0.88 ± 0.051) and test AUC of 0.80 [0.71–0.89], comparable to dual-input models. In both tracer-specific tasks, stress-phase information showed favorable performance, but the endpoints differed and should be interpreted separately. Conclusions: Stress-phase polar maps provided strong discriminative information within this single-center cohort. These findings should be interpreted in a tracer- and task-specific manner supporting stress-phase imaging as an informative input for AI-based SPECT MPI classification while underscoring the need for external validation before broader clinical generalization. Full article

Essential tremor (ET) is a common movement disorder increasingly recognized as a complex syndrome with neurodegenerative features. While mitochondrial dysfunction and cellular aging are implicated in several neurodegenerative diseases, their role in ET remains unexplored. To investigate mitochondrial DNA copy number (mtDNA-CN) and telomere length (TL) in patients with ET and evaluate their potential as biomarkers of mitochondrial dysfunction and biological aging. In this cross-sectional case–control study, 68 ET patients (median age 66 years; 64.7% male) and 62 healthy controls (median age 70 years; 54.8% male) were enrolled. Relative mtDNA-CN and TL were quantified by quantitative PCR, measuring mitochondrial ND1 gene levels and telomere-to-single-copy gene (T/S) ratio, respectively, both normalized to β-actin. Associations with disease status were assessed using age- and sex-adjusted multivariable linear regression on log₂-transformed data, with statistical significance defined as p < 0.05 after false discovery rate (FDR)-corrected Wald tests. Receiver operating characteristic (ROC) and effect size (Cohen’s d) analyses were performed. ET patients showed significantly reduced mtDNA-CN (β = −2.785, 95% CI −3.700 to −1.869; p_FDR = 2.53 × 10⁻⁹) and TL (β = −2.073, 95% CI −2.758 to −1.388; p_FDR = 3.00 × 10⁻⁹), corresponding to ~6.9-fold and ~4.2-fold reductions, respectively. Age- and sex-stratified analyses confirmed consistent reductions, more pronounced in older individuals. Both biomarkers showed good discriminatory performance (mtDNA-CN: AUC = 0.83, 95% CI: 0.75–0.90; TL: AUC = 0.76, 95% CI: 0.68–0.85) and large effect sizes (Cohen’s d = |1.192| and |1.058|), respectively. Reduced mtDNA-CN and TL support the involvement of mitochondrial impairment and accelerated cellular aging in ET and may represent accessible peripheral biomarkers and provide a basis for future longitudinal and mechanistic investigations. Full article

The Huanggangliang area in Inner Mongolia is a major fluorite and polymetallic ore district in China. Its skarn-type deposit yields rare color-change fluorite, yet the coloration and photochromic mechanisms remain poorly studied. Five faceted samples were characterized by conventional gemological tests, EDXRF, UV-Vis, Raman, PL, TL, and FTIR to determine their composition, spectral features, and defects. The results indicate two distinct color-forming mechanisms. Group I is dominated by f-f transitions of rare-earth elements with color-center synergy, showing a strong gray-blue to blue-violet color change and a characteristic absorption peak at ~580 nm in the UV-Vis spectrum. Group II is dominated by high-concentration irradiated color centers. Its deep blue-violet color and weak color change are attributed to colloidal induced by long-term endogenous α, β, and γ irradiation from radioactive Th. The lack of additional Raman peaks and a broad UV-Vis absorption peak at ~595 nm, along with multiple UV color-center peaks, weak fluorescence, and thermoluminescence, all confirm the presence of high-concentration electron traps. This study establishes the composition–spectrum–color relationship, reveals the control of ore-fluid evolution on mechanism differentiation, and provides a scientific basis for identifying and analyzing color-change fluorite. Full article

Objectives: To prospectively compare the outcomes of external dacryocystorhinostomy (EX-DCR), endonasal dacryocystorhinostomy (EN-DCR), and laser-assisted transcanalicular dacryocystorhinostomy (TL-DCR) in patients with nasolacrimal duct obstruction (NLDO) and to evaluate the relationship between surgical outcomes and patient quality of life (QoL). Methods: This prospective comparative study included patients presenting with epiphora who were diagnosed with NLDO and scheduled for surgical treatment. Patients underwent EX-DCR, EN-DCR, or TL-DCR according to patient preference and nasal anatomical characteristics. All patients received bicanalicular silicone tube intubation. Follow-up examinations were performed on postoperative day 1, week 1, at month 1, and every three months thereafter. Anatomical success was defined as patency on nasolacrimal irrigation, and functional success was defined as a postoperative Munk score of ≤ 1 (complete or near-complete resolution of epiphora). QoL was assessed using the Lacrimal Symptom Questionnaire (Lac-Q) and the Glasgow Benefit Inventory (GBI). Statistical comparisons were performed between groups. Results: A total of 69 patients (45 women, 24 men; mean age 58.99 ± 14.86 years) were included, with a mean follow-up of 17.19 ± 4.07 months. The highest postoperative pain scores were observed in the EX-DCR group; with no significant intergroup differences. Anatomical success rates were 92% for EX-DCR, 90.5% for EN-DCR, and 91.3% for TL-DCR. Functional success rates were 88%, 90.5%, and 82.7%, respectively, with no statistically significant difference among techniques (p > 0.05). All groups showed postoperative improvement in Lac-Q and GBI scores. Numerically greater improvements were observed in the EN-DCR group, although intergroup differences were not statistically significant. Conclusions: EX-DCR achieved the numerically highest anatomical success rate, whereas EN-DCR demonstrated numerically greater improvement in patient-reported QoL outcomes. However, no statistically significant differences in anatomical success, functional success, or QoL measures were observed among the three techniques. Overall, all three procedures were effective surgical options for the treatment of NLDO. Full article

This study investigates the dyke swarms of the Um Dwiela area in the southern Egyptian Shield through a combined approach of remote sensing, field investigations and laboratory analyses, including mineralization and radioactive prospecting. Radioelements laboratory measurements and optical remote sensing datasets are combined to detect the bostonite rocks and their radioactive mineralization. The processing of Landsat-8, Sentinel-2 and ASTER data effectively delineated the country rocks, bostonite dykes and structural elements. Field observations indicate that the dykes trend NE-SW, extending approximately 12 km with widths ranging from 1 to 13 m. These dykes have experienced multiple alteration phases, pointing to the influence of hydrothermal fluids. Uranium mineralization is structurally controlled, occurring within fractures at the contact between bostonite and metasedimentary rocks. Average measurements obtained using a NaI(Tl) analyzer reveal elevated and variable radionuclide concentrations [²³²Th (442.25 Bq/kg), ²³⁸U (608.43 Bq/kg), and ⁴⁰K (1141.41 Bq/kg)], all exceeding internationally permissible safety limits. Multiple radiological hazard indices further indicate a substantial radiation risk, with all values classified as high according to global standards. Consequently, the associated gamma radiation exposure poses an elevated radiological hazard concern. Full article

Background: Lidocaine and prilocaine cream is a compounded topical anesthetic formulation comprising lidocaine and prilocaine. Upon application, the active ingredients are locally released and permeate into the subcutaneous tissue, exerting anesthetic effects by blocking ion channels involved in nerve impulse transmission. Variations in drug permeation may influence the onset time, anesthetic efficacy, and duration of action. Methods: This study investigates the in vitro properties of the innovator formulation Emla^® and five generic formulations through in vitro bioequivalence studies and Q3 Characterization tests. Results: With the exception of TS, the generic formulations exhibited notable differences compared to the innovator product. Specifically, TB and TL demonstrated significantly higher in vitro release than Emla^®, yet exhibited lower in vitro permeation rates. In contrast, TH and TT showed release rates comparable to Emla^®, while their permeation rates were similarly reduced. Conclusions: These findings indicate that in vitro release rate does not directly predict in vitro permeation. Permeation behavior is significantly influenced by emulsion globule size, rheological characteristics (viscosity and elasticity), and pH, collectively underscoring the multifactorial nature of this phenomenon. Full article

Existing accounts of platform-mediated complementor growth rest on two limiting assumptions: that platform enablement constitutes a homogeneous environmental input and that firm growth is a unitary outcome. This double simplification obscures how distinct platform provisions generate qualitatively different forms of firm transformation. This study asks which combinations of mechanistically distinct platform enablement types and internal strategic response capabilities activate which forms of leapfrog growth among complementor firms operating under dual institutional governance. We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) on survey data from 374 complementor firms in China’s autonomous driving platform ecosystem. Five antecedent conditions are examined across two dimensions: platform enablement, comprising rule-based enablement (RE) and business platform enablement (BPE); and strategic response capabilities, comprising network linkage capability (NLC), organizational ambidexterity (OA), and policy responsiveness (PR). Three outcome variables capture three non-reducible leapfrog dimensions: technology-chain (TL), value-chain (VL), and institutional-chain (IL) transitions. A reverse-causality robustness check and a common-method-bias assessment corroborate the validity of findings. The analysis identifies equifinal configurational pathways with distinct dominant logics across the three chains. Technology-chain transitions are predominantly network-linkage-driven; value-chain transitions are policy-responsiveness-anchored; institutional-chain transitions exhibit genuine equifinality between network-linkage and policy-responsiveness pathways, both requiring dual-platform enablement as a universal structural precondition. No single enabling condition or capability suffices; leapfrog growth is irreducibly configurational and causally asymmetric. The study offers a dual-enablement, three-chain configurational framework for understanding platform-mediated firm growth under dual institutional governance. For complementor firms, findings support dimension-selective capability investment over uniform accumulation strategies. For platform orchestrators, differentiated governance design calibrated to specific complementor upgrading trajectories outperforms homogeneous resource provisioning. For policymakers, institutionalized consultative channels linking private platform governance with public regulatory processes are recommended to facilitate coordinated digital industrial transformation. Full article

The Djurkovo and Govedarnika deposits represent hydrothermal Pb-Zn systems spatially associated with the Eocene–Oligocene tectono-magmatic evolution of the Rhodope Metamorphic Complex. This study presents new mineralogical and geochemical data for galena, sphalerite, pyrite, and chalcopyrite obtained by electron probe microanalysis (EPMA) and LA-ICP-MS in order to evaluate the compositional variations of sulphides among the vein and metasomatic mineralization types and between the two deposits. The analysed sulphides exhibit distinct compositional signatures reflecting the different mineralization stages and hydrothermal environments. Sphalerite from the Govedarnika metasomatic ores is enriched in Mn (up to 5200 ppm), Fe (up to 5.13 wt.%) and Co due to interaction with Mn-rich skarn assemblages, whereas Djurkovo sphalerite shows elevated Cd (up to 3000 ppm), In and Hg concentrations. Trace-element systematics indicate coupled Fe-Mn incorporation, competitive Cd-Fe substitution and local re-equilibration processes associated with “chalcopyrite disease” textures. Late pyrite from the quartz-carbonate stage is enriched in As (up to 3.87 wt.%), Au (up to 78 ppm), Ag, Se, Sb and Tl, with positive Au-As and Au-Ag correlations suggesting invisible gold and possible submicroscopic precious-metal inclusions. The obtained data demonstrate prolonged hydrothermal evolution and highlight the potential role of the studied sulphides as concentrators of economically important elements. Full article