Search Results (118)

This study presents a multi-methodological approach combining subsurface characterization with dynamic structural assessment to evaluate Soil–Structure Interaction (SSI) mechanisms at the Palazzo Centrale. The 3D Electrical Resistivity Tomography (ERT) and active Multichannel Analysis of Surface Waves (MASW) results were compared with a lithostratigraphic core log to outline the subsurface framework. The stratigraphic framework mapped geotechnical heterogeneities within the upper 6.0 m, where a low-resistivity anomaly (≤1 log(Ω·m)) outlines a mechanically weakened, water-saturated cover deposit overlaying the basaltic lava. This characterization provides the physical baseline useful for interpreting the site response. In this framework, the ambient vibration recordings performed at the free-field sites exhibit a flat Horizontal-to-Vertical Spectral Ratio (HVSR) response within the 1.0–10.0 Hz range, whereas a localized stratigraphic peak emerges at higher frequencies near 15.0 Hz, particularly evident in the building’s courtyard. The building resonance frequency peaks, derived from the Horizontal-to-Horizontal Spectral Ratio (HHSR) analysis at 3.74 ± 0.09 Hz (NS) and 3.58 ± 0.22 Hz (EW), do not overlap with the site resonance frequencies, demonstrating a dynamic decoupling between the soil and the building within the low-to-medium frequency domain. Conversely, the secondary stratigraphic peak near 15.0 Hz overlaps with higher-order structural frequencies tracked in the HHSR datasets. Given the localized nature of this stratigraphic peak and the involvement of higher-order structural modes, this overlap suggests a limited, localized high-frequency amplification confined to specific architectural components, rather than a global site-structure hazard. Furthermore, torsional analysis reveals significant effects within the 3.8–4.0 Hz frequency band, targeting the North-East corner (peak value of 2.85 at station A4), indicating a localized dynamic anomaly due to structural heterogeneities. Overall, this multi-method approach proves highly effective for non-invasive structural diagnostics, establishing a rigorous physical reference that could be successfully integrated into future preventive conservation frameworks and routine monitoring protocols for ancient architectural heritage. Full article

Field tests were conducted at a heterogeneous industrial site using one circulation well and six monitoring wells. Groundwater circulation well (GCW) extraction–injection (30 d), multi-component tracing (6 h), and circulation–oxidation (20 h) tests were performed to investigate the flow-field characteristics and their influence on multi-component solute transport. The results suggested that the extraction–injection circulation mode increased the flow rate of the single well from 0.5 m³/h to 3.5 m³/h, establishing a composite flow field with near-field circulation and far-field outward expansion. Short-term circulation achieved limited concentration attenuation primarily near the well with rebound. Long-term circulation elevated the average concentration attenuation rates of benzene from 13% in the short-term test to 61%, and chemical oxygen demand (COD) from 16% to 47%, expanding the remediation scope of the circulation well. Bromide tracer tests and an advection–dispersion equation characterized the heterogeneous flow field with preferential flow channels and slow migration zones. Furthermore, sulfate tracer transport was governed by adsorptive retardation and advective delivery. Circulation–oxidation tests showed that benzene and COD showed higher concentration attenuation than naphthalene. After cessation, benzene and COD concentration attenuation rates increased by 39% and 29% compared to the short-term test without oxidation. Electrical resistivity tomography (ERT) revealed the downward diffusion of the oxidant, suggesting that the circulation well system enhances oxidant transport and expands the oxidant-affected zone. This research provides field-scale diagnostic evidence and in situ diagnostic methodologies for GCW remediation at complex contaminated sites. Full article

This study presents and evaluates a system-level optimization of an electrical resistance tomography (ERT) measurement platform based on a ZYNQ-7020 all-programmable system-on-chip (APS-SoC). The design combines deterministic programmable-logic (PL) acquisition, processing-system (PS) configuration and communication scheduling, AXI/DMA data movement, Gigabit Ethernet transmission, and a seventh-order Butterworth excitation filter. FFT-based amplitude extraction and Tikhonov reconstruction remain on the host computer so that the reconstruction algorithm and regularization settings remain identical for the baseline and proposed systems; the present prototype is therefore not claimed as a fully standalone smart sensor. Under the same 16-electrode tap-water testing configuration, the average frame rate increased from 58.23 ± 1.88 FPS to 123.02 ± 1.62 FPS (mean ± sample standard deviation, n = 10), end-to-end latency decreased from 5.2 ms to 2.1 ms, SFDR increased from 68 dB to 95 dB, and SSIM increased from 0.72 to 0.94. In one representative static hardware record at 160 kHz, the calculated amplitude-stability SNR values were 65 dB and 100 dB for the baseline and proposed excitation paths, respectively, while total harmonic distortion decreased from 15.2% to 7.5%. These single-condition signal quality values are descriptive rather than uncertainty-bounded performance specifications. The image-quality differences are attributed primarily to cleaner boundary-voltage measurements with an unchanged reconstruction method, whereas the frame-rate gain reflects the combined PL/PS data path and Gigabit Ethernet upgrade. Full article

The Raša Fault is a prominent seismically active strike-slip fault within the Dinaric Fault System in SW Slovenia, seismotectonically estimated to be capable of producing earthquakes up to Mw = 7.4. Since the surface exposure of fault-related markers is discontinuous, and the near-surface expression of deformation is poorly constrained, there is a need to improve the detection of fault-related features in complex sedimentary environments. In such settings, signal attenuation, complex stratigraphy, and irregular fault-zone geometries often obscure subtle deformation features, limiting the interpretability of standard 2-D geophysical profiles. A pseudo 3-D Ground-Penetrating Radar (GPR) survey, along with complementary Electrical Resistivity Tomography (ERT) surveys and reprocessing of LiDAR (light detection and ranging) data to obtain high-resolution Digital Elevation Models (DEMs), was conducted in selected environments dominated by low-resistivity karstic deposits and highly heterogeneous fluvial sediments to assess and improve the capability to detect and characterize subtle shallow deformations associated with the Raša Fault. Tectonic geomorphological mapping facilitated the recognition of potentially active fault traces and the identification of Quaternary sedimentary and erosional features, where recent deformations are usually preserved and can be dated in further paleoseismological investigations. The analysis of dense GPR data and complementary ERT profiles enabled us to clearly image the fault deformation pattern and obtain quantitative information about the subsurface, showing details of faulting and related deformation structures not evident at the surface. Furthermore, it enabled the detection of fault zone complexity, revealing it as an irregular and laterally changing area with sediment infillings, rather than a single vertical discontinuity. The complexity of faulting in the near surface depends on many factors, including the competence and age of the faulted material, as well as the local geomorphology. This study has demonstrated the applicability of pseudo 3-D GPR surveying, combined with ERT profiles, for subsurface mapping of active strike-slip faults in karstic and fluvial sedimentary environments. The methodology can be recommended in particular for rapid and cost-effective investigation of sites with subtle surface evidence of active faulting in order to determine near-surface fault splaying. Full article

The rapid expansion of make-on-demand and public chemical libraries has made exhaustive docking-based structure-based virtual screening increasingly difficult. This study introduces SurroDock, a lightweight deep-learning surrogate designed to approximate AutoDock Vina docking scores from low-cost two-dimensional molecular features, serving as a practical pre-filter for docking. SurroDock was evaluated for estrogen receptor alpha using two distinct conformations: an agonist-bound (PDB ID: 1GWR) and an antagonist/SERM-bound (PDB ID: 3ERT). The dataset comprised approximately 334,000 unique compounds curated from the NCI Open Database, PubChem, and BindingDB, all docked using a standardized AutoDock Vina workflow. The model was trained on concatenated 2D molecular representations comprising Morgan fingerprints, MACCS keys, RDKit physicochemical descriptors, Vina-inspired ligand descriptors, atom-pair fingerprints, and 2D pharmacophore fingerprints. The docking-score distributions differed substantially between receptor states, with 3ERT exhibiting more favorable scores than 1GWR and weak inter-state score correlation supporting state-specific modeling. Using the integrated Unified-200k training set (200,000 compounds randomly sampled per receptor from the three docked sources), SurroDock achieved strong held-out validation performance, with R² values of approximately 0.88 for 1GWR and 0.93 for 3ERT. In retrospective screening-style evaluation, SurroDock recovered substantial fractions of Vina’s top-ranked compounds at the top-1% recall (Recall@1%) of approximately 0.57 and 0.61 for 1GWR and 3ERT, respectively, yielding corresponding enrichment factors (EF@1%) of approximately 57-fold and 61-fold relative to random selection. Overall, the results indicate that 2D-based docking-score surrogate modeling can provide a reproducible and retrainable strategy for large-scale structure-based virtual screening by concentrating docking resources on a smaller, enriched subset of compounds. Because SurroDock emulates a docking scoring function rather than experimental binding affinity, its predictions should be used as prioritization aids and complemented by confirmatory docking, pose inspection, and experimental validation. Full article

Ion-adsorption rare earth deposits (IADs) constitute the primary global source of medium-to-heavy rare earth elements. The sustainable exploitation of these resources hinges on the precise characterization of the weathered crust architecture and its hydrogeological properties. Conventional drilling often fails to resolve the complex vertical heterogeneity of regolith profiles, thereby limiting orebody delineation and the optimization of in situ leaching (ISL). To address this, this study integrates Electrical Resistivity Tomography (ERT) with Archie’s Law and the Kozeny–Carman equation. Focusing on the YZK1 and YZK2 survey lines in the Dabu mining area, southern Jiangxi, we derived 2D distributions of porosity and permeability from resistivity inversions. Our results delineate the weathered crust into four distinct vertical strata: a surface accumulation layer, a completely-to-highly weathered granite layer, a moderately-to-slightly weathered layer, and fresh bedrock. Quantitatively, the completely-to-highly weathered layer exhibits a “low resistivity (10–700 Ω·m)–high porosity (8.7%–17%)–high permeability (0.04–1.2 mD)” mode, serving as the primary leachable reservoir. In contrast, the surface and moderately weathered layers display “high resistivity (>800 Ω·m)–low porosity (3.4%–6.4%)–low permeability (0.01–0.04 mD)” characteristics. Crucially, although the fractured bedrock zones on both YZK1 and YZK2 profiles exhibit similar absolute permeability values (~0.016 mD), they represent two distinct hydraulic architectures. On the YZK1 profile, the fractured zone acts as a relatively homogeneous potential leakage pathway. Conversely, the YZK2 profile displays significant vertical segmentation: the upper and lower margins function as permeable pathways, while the central core, likely infilled with fault gouge, acts as a sealing zone that impedes fluid flow. Consequently, resistivity data alone are insufficient to accurately assess hydraulic conductivity; joint interpretation incorporating both permeability and porosity is essential to definitively determine whether a fault zone acts as a “conduit” or a “barrier.” By transitioning from qualitative imaging to quantitative parameter evaluation, this study provides a robust technical paradigm for fine-scale exploration and ISL optimization in IADs. Full article

Ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) are physically complementary non-destructive evaluation methods for reinforced concrete, yet their integrated diagnostic use has been limited by the absence of controlled, ground-truth-validated calibration of the joint-signature space. This paper presents a laboratory calibration programme in which a single C30/37 reinforced concrete beam (3000 mm × 300 mm × 200 mm, three T12 bars at 35 mm cover, CEM I 42.5N, w/c = 0.50) was sequentially conditioned through four controlled deterioration states—intact reference (Model A), water-filled saw-cut crack (Model B), full saturation by seven-day top-surface ponding (Model C), and chloride-induced active corrosion (Model D). Seven RES2DINV inverted ERT sections at three electrode spacings (a = 7, 15, and 30 mm) and three 800 MHz GPR profiles were acquired across the four known ground-truth conditions. The intact-reference resistivity ρ₀ = 558 Ω·m (full-section median of the mlab dataset at a = 7 mm) and GPR-calibrated velocity v = 0.095 ± 0.008 m/ns (from hyperbola fitting at 35 mm rebar cover) establish the absolute baselines. The four conditions produce systematically distinct joint signatures: Model A exhibits uniform high resistivity with clean rebar hyperbolae and no anomalous reflections; Model B produces a localised ERT low-ρ anomaly (ρ_min = 1.46 Ω·m) co-located with a negative-polarity (R = −0.68) GPR crack-mouth reflection confirming water-fill; Model C produces pervasive low-ρ with a smooth depth gradient and 50–65% GPR amplitude attenuation (−6.0 to −9.1 dB); Model D produces the same bulk GPR signatures as Model C but with a critically different ERT spatial texture—a heterogeneous near-surface layer above a sharp boundary at z ≈ 40 mm with depth-preferential low-ρ concentrated at rebar level. This depth-preferential signature, quantified here by a reproducible Depth-Preferential Index (DPI), is the primary ERT-only diagnostic criterion distinguishing active corrosion from pervasive saturation. For the Model C versus Model D distinction, the GPR response is non-discriminating; this high-risk distinction is resolved exclusively by the ERT depth-preferential criterion. The calibration demonstrates that GPR and ERT are physically non-redundant in the strict sense: neither method alone can unambiguously discriminate all four states, but their combination yields correct classification within the controlled laboratory conditions and subject to the stated qualification conditions. The corrosion state was confirmed at the regime level (chloride above the depassivation threshold, under accelerated polarisation) but was not quantified electrochemically, so the depth-preferential signature is interpreted as an indirect spatial proxy for active corrosion rather than a measurement of corrosion rate. Seven failure modes are quantitatively characterised and embedded in the framework as a priori qualification conditions. The calibrated reference values (ρ₀, A₀, Stage 2 thresholds, depth-preferential criterion) are specific to the laboratory mix and curing history and require local Stage 1 recalibration for field application. Full article

This study presents an integrated diabatic compressed air energy storage (D-CAES)–cascade organic Rankine cycle (ORC)–liquefied natural gas (LNG) polygeneration system that simultaneously delivers electricity, district cooling, and pipeline-grade natural gas. The D-CAES turbine exhaust serves as the primary heat source for a cascade ORC employing a zeotropic working-fluid mixture, while the LNG warming curve provides a cryogenic condensation sink uniquely suited to glide-matched condensation of the zeotropic condenser. A four-criterion (4E) framework is applied at the component level, yielding four global performance metrics: exergy round-trip efficiency (ERTE), total annualized cost rate (Ż_tot), CO₂ emission factor (ζ_CO2), and net discharge power. A surrogate-assisted multi-objective optimization is developed in which 1000 Latin-hypercube-sampled high-fidelity simulations train three independent artificial neural network (ANN) surrogate models, which are then coupled with the optimization algorithm. The TOPSIS-selected compromise solution achieves an ERTE of 47.55%, a total cost rate of 293.75 USD h⁻¹, and a CO₂ emission factor of 166.98 kg MWh⁻¹. Sensitivity analysis demonstrates that turbine inlet temperature and charging pressure are the dominant thermoeconomic drivers. Full article

Concealed shallow karst along long-distance pipeline corridors can trigger subsidence, uneven settlement, and leakage, creating environmental and infrastructure hazards. In the Huyuanxi area (Fuyang District, Hangzhou, Zhejiang, China), strong electromagnetic interference and limited site access motivated an integrated electrical resistivity tomography (ERT) plus ambient-noise microtremor (SPAC) workflow for shallow-karst screening. Three ERT lines (900 m each) were deployed along the pipeline axis and at ±15 m offsets with 10 m spacing using a WDJD-4 system (100 V constant-voltage; Wenner array, 30 layers), followed by resistivity inversion; Res2Dinv v3.65 was adopted as the inversion software. The L2 norm was selected for the objective function, and the error model was set to the default error floor plus 5%. The regularization parameter was set as λ = 0.01, and adaptive gridding was used for the mesh with a minimum cell size of 0.5 m × 0.5 m. The number of iterations was set to 15, with a final root mean square (RMS) misfit of 3.2%. The depth of investigation (DOI) was calculated via the built-in algorithm of the software, yielding a maximum value of 30 m. Low-resistivity anomalies were used to focus eight perpendicular microtremor profiles (3 m spacing) acquired with SmartSolo IGU-16HR 1C and 10 geophones (5 Hz; 1 ms sampling interval) in a nested SPAC array (0.5/1/2 m radii); processing removed segments with SNR < 3 and inverted 2-D Vs structure by damped least-squares. Resistivity sections show 50–8600 Ω·m near surface, including a <100 Ω·m fracture-zone anomaly (28–30 m wide; 8–18 m depth) and a cavity-zone anomaly (55–70 m wide; 10–20 m depth). Joint interpretation places karst development mainly at 10–25 m depth near the bedrock–cover interface (~16 m). At HYXK3, microtremor versus shear-wave logging yielded a void-layer bottom depth of 21.28 m versus 20.12 m (5.76% error) and Vs of 457 versus 446 m/s (2.40% error). Example profiles show microtremor-derived depths (18.3/14.5/18.7 m) consistent with ERT (16.8/15.1/19.5 m; 4.1–8.1% errors). Drilling verification accuracy was approximately 81.7%, precision approximately 90%, recall approximately 74.0%, and the F1-score 81.1% supporting practical corridor risk screening under complex field constraints. Full article

Artificial levees along major rivers are critical for flood-risk mitigation, yet many aging structures have poorly constrained internal composition and material heterogeneity, limiting the reliability of conventional safety assessments. This study develops a quantitative, non-destructive framework for characterizing levee internal structure by integrating electrical resistivity tomography (ERT) with borehole (BH) observations. ERT profiles were combined with borehole measurements of grain size (D50) and water content to investigate subsurface compositional variability and to evaluate relationships between sedimentological and geophysical parameters. Grain-size data from borehole samples were modeled using four predictive approaches—random forest regression (RFR), artificial neural networks (ANN), linear regression (LR), and support vector regression (SVR)—based on ERT-derived resistivity and moisture information. The results reveal pronounced internal heterogeneity within the investigated levees and demonstrate consistent relationships between sediment composition, water content, and electrical resistivity. Among the tested models, the ensemble-based RFR provided the highest predictive performance (R² = 0.81). These findings indicate that D50 characteristics of levee materials can be reliably inferred from ERT data using machine learning, reducing the need for destructive sampling. The proposed approach offers a transferable methodology for levee assessment and supports future applications in non-destructive monitoring, spatially explicit flood-risk analysis, and climate-resilient flood-protection management. Full article

Infantile-onset lysosomal acid lipase deficiency (LAL-D) (Wolman disease, historically) is a rare inherited, rapidly progressive disorder caused by pathogenic variants in the LIPA gene, which encodes the enzyme LAL. LAL is essential for the metabolism of cholesteryl esters and triglycerides. LAL deficiency leads to the accumulation of cholesteryl esters and triglycerides within the lysosomes, macrophages, and parenchymal cells in most tissue types, including those in the liver, gastrointestinal tract, and lymph nodes but excluding the central nervous system. Infants with rapidly progressive LAL-D present with gastrointestinal disturbance, adrenomegaly with calcification, hepatosplenomegaly, growth failure due to malabsorption, and systemic inflammation. If untreated, rapidly progressive LAL-D typically leads to death within the first year of life. Treatment takes the two-pronged approach of sebelipase alfa, a human lysosomal acid lipase enzyme replacement therapy (ERT) that improves lipid metabolism, combined with nutritional management. Dietary substrate (lipid) reduction, known as substrate reduction therapy, is essential for optimal management in LAL-D. Following a nutritional plan and managing gastrointestinal disturbances together reduce systemic inflammation and improve growth, gut function, liver health, quality of life, and survival in patients with infantile-onset LAL-D. A multidisciplinary specialized team is necessary to manage the highly complex, multisystemic conditions in these patients. Nutritional management of LAL-D has evolved with increasing experience with the clinical management of ERT-treated infantile-onset LAL-D. A review of guidance for best practice nutritional management is needed. This narrative review aims to provide updated recommendations and guidance for the optimal nutritional management of infantile-onset LAL-D. Full article

Saline water intrusion poses a major threat to groundwater security in arid and semi-arid regions, reducing freshwater availability and challenging sustainable water resource management. Accurate delineation of the fresh-saline water interface is therefore essential; however, conventional hydrochemical and laboratory-based assessments remain costly, invasive, and spatially limited. Resistivity methods have long been used to infer subsurface salinity, as low resistivity typically reflects clay-rich saline water and higher resistivity reflects freshwater-bearing sand or gravel. Yet, resistivity values for similar lithologies frequently overlap, causing ambiguity in distinguishing fresh and saline aquifers. To overcome this limitation, Dar–Zarrouk (D–Z) parameters are often applied to enhance hydrogeophysical discrimination, but previous studies have relied exclusively on one-dimensional (1D) D–Z derivations using vertical electrical sounding (VES), which cannot resolve the lateral complexity of alluvial aquifers. This study presents the first application of electrical resistivity tomography (ERT) to derive two- and three-dimensional D–Z parameters for detailed mapping of the fresh-saline water interface in the alluvial aquifers of Punjab, Pakistan. ERT provides non-invasive, continuous, and high-resolution subsurface imaging, enabling volumetric assessment of aquifer electrical properties and salinity structure. The resulting 2D/3D models reveal the geometry, depth, and spatial continuity of salinity transitions with far greater clarity than VES-based or purely hydrochemical methods. Physicochemical analyses from boreholes along the ERT profiles independently verify the geophysical interpretations. The findings demonstrate that ERT-derived 2D/3D D–Z modeling offers a cost-effective, scalable, and significantly more accurate framework for assessing fresh-saline water boundaries. This approach provides a transformative pathway for sustainable groundwater monitoring, improved well siting, and long-term aquifer protection in salinity-stressed alluvial regions. Full article

The use of Artificial Intelligence (AI) algorithms has enhanced WiFi fingerprinting-based indoor localization. However, most existing approaches are limited to 2D coordinate estimation, which leads to significant performance declines in multi-floor environments due to vertical ambiguity and inadequate spatial modeling. This limitation reduces reliability in real-world applications where accurate indoor localization is essential. This study proposes RELoc, a new 3D indoor localization framework that integrates Recursive Feature Elimination with Cross-Validation (RFECV) for optimal Access Point (AP) selection and Extremely Randomized Trees (ERT) for precise 2D and 3D coordinate regression. The ERT hyperparameters are optimized using Bayesian optimization with Optuna’s Tree-structured Parzen Estimator (TPE) to ensure robust, stable, and accurate localization. Extensive evaluation on the SODIndoorLoc and UTSIndoorLoc datasets demonstrates that RELoc delivers superior performance in both 2D and 3D indoor localization. Specifically, RELoc achieves Mean Absolute Errors (MAEs) of 1.84 m and 4.39 m for 2D coordinate prediction on SODIndoorLoc and UTSIndoorLoc, respectively. When floor information is incorporated, RELoc improves by 33.15% and 26.88% over the 2D version on these datasets. Furthermore, RELoc outperforms state-of-the-art methods by 7.52% over Graph Neural Network (GNN) and 12.77% over Deep Neural Network (DNN) on SODIndoorLoc and 40.22% over Extra Tree (ET) on UTSIndoorLoc, showing consistent improvements across various indoor environments. This enhancement emphasizes the critical role of 3D modeling in achieving robust and spatially discriminative indoor localization. Full article

This study investigates the hydraulic connection of surface karst features within the Northern segment of the Edwards Balcones Fault Zone Aquifer, using a combination of 2D and pseudo-3D Electrical Resistivity Tomography (ERT) at an outcrop near Salado, Texas. The study site features several surface fractures whose hydrological functions are not well understood. Nine ERT profiles and two pseudo-3D models were used to evaluate the connection between surface fractures and subsurface karst conduits. Karst features at the study site were physically evaluated using characteristics such as morphology, which resulted in the identification of three surface fractures (F1, F2, and F3). The ERT results showed several high-resistivity anomalies interpreted as a poorly fractured zone and low-resistivity water-filled conduits within the Edwards Formation. Furthermore, the result reveals that slow hydraulic connectivity exists in F1 and F2; however, F3 presents a low-resistivity zone that extends vertically into the subsurface, which suggests that F3 may serve as a potential recharge feature to the Edwards Aquifer. These findings are corroborated by a water percolation test, as water penetrated more at F3 compared to F1 and F2. This study showed that the combined application of 2D and pseudo-3D ERT can successfully delineate potential recharge pathways in an exposed karst system, thereby constituting a supportive approach providing critical insight into recharge and the vulnerability of karst aquifers to contamination. Full article

This study proposes an automated, visual–geometric fusion method for measuring pupillary height (PH) and interpupillary distance (PD), aiming to replace manual measurements while balancing accuracy, efficiency, and cost accessibility. To this end, a two-layer Ensemble of Regression Tree (ERT) is used to coarsely localize facial landmarks and the pupil center, which is then refined via direction-aware ray casting and edge-side-stratified RANSAC followed by least-squares fitting; in parallel, an RC-BlendMask instance-segmentation module extracts the lowest rim point of the spectacle lens. Head pose and lens-plane depth are estimated with the Perspective-n-Point (PnP) algorithm to enable pixel-to-millimeter calibration and pose gating, thereby achieving 3D quantification of PH/PD under a single-camera setup. In a comparative study with 30 participants against the Zeiss i.Terminal2, the proposed method achieved mean absolute errors of 1.13 mm (PD), 0.73 mm (PH-L), and 0.89 mm (PH-R); Pearson correlation coefficients were r = 0.944 (PD), 0.964 (PH-L), and 0.916 (PH-R), and Bland–Altman 95% limits of agreement were −2.00 to 2.70 mm (PD), −0.84 to 1.76 mm (PH-L), and −1.85 to 1.79 mm (PH-R). Lens segmentation performance reached a Precision of 97.5% and a Recall of 93.8%, supporting robust PH extraction. Overall, the proposed approach delivers measurement agreement comparable to high-end commercial devices on low-cost hardware, satisfies ANSI Z80.1/ISO 21987 clinical tolerances for decentration and prism error, and is suitable for both in-store dispensing and tele-dispensing scenarios. Full article