Search Results (99)

Accurate transfer of implant position is essential for implant-supported prosthodontic workflows. This in vitro study compared the trueness and precision of five intraoral scanners in single crown, three-unit fixed partial denture, and full-arch implant-supported scanning scenarios using root mean square (RMS) deviation analysis. Two maxillary resin models, representing partially dentulous and fully edentulous conditions, were fabricated through a CAD/CAM and 3D-printing workflow with implant analogs and scan bodies. Reference datasets were obtained with an InEos X5 desktop scanner, and each intraoral scanner was used to perform 10 scans per scenario. After standardized scenario-specific trimming, datasets were analyzed in Geomagic Control X. Statistical analysis included two-way analysis of variance and follow-up one-way analysis of variance with Tukey post hoc comparisons using Bonferroni-adjusted thresholds. Trueness was affected by scanner type (p < 0.001) and scenario (p < 0.001), without interaction (p = 0.096). Precision was affected by scanner type (p = 0.012), scenario (p = 0.004), and their interaction (p < 0.001). iTero Lumina and Helios 600 showed lower trueness deviations, whereas Trios 5 showed greater deviations, especially in full-arch scans. Scanner selection and scan extent should therefore be considered when interpreting surface-based RMS accuracy in implant-supported digital scans. Full article

The rapid growth of artificial intelligence (AI) workloads is reshaping semiconductor design across architecture, interconnect, memory hierarchy, packaging, timing, and design automation. Rather than converging on a single hardware solution, the field is expanding into a heterogeneous ecosystem that includes data-center graphics processing units (GPUs), edge neural processing units (NPUs), and application-specific integrated circuits (ASICs), field-programmable gate array (FPGA)-based and hybrid AI system-on-chip (SoC) platforms, chiplet-enabled systems, and emerging beyond-conventional-silicon approaches such as photonic, neuromorphic, and analog in-memory processors. This paper presents a comprehensive review of AI-on-chip systems from a cross-layer perspective. It examines AI chip architectures and hardware platforms, network-on-chip (NoC) designs for AI communication patterns, and algorithm–hardware co-design methods for model acceleration, including compression, quantization, and sparsity-aware optimization. It also reviews clocking, synchronization, and clock-domain-crossing (CDC) challenges in large heterogeneous systems and chiplets, as well as manufacturing, advanced packaging, and reliability issues, including two-and-a-half-dimensional (2.5D) and three-dimensional (3D) integration, thermal and mechanical constraints, assembly quality, and long-term yield considerations. In parallel, the paper surveys the growing role of AI in chip design itself, covering machine-learning-assisted analysis, Bayesian and reinforcement-learning-based optimization, and the emerging use of large language models (LLMs) and AI agents for register-transfer level (RTL) generation, design-space exploration, and autonomous electronic design automation (EDA) workflows. Finally, it discusses beyond-silicon AI chip directions and the broader economic and industry context shaping cloud, on-premises, and edge deployment. By integrating these topics into a unified framework, this review highlights the key technological drivers, system-level tradeoffs, and future research directions that will define next-generation scalable, reliable, and energy-efficient AI-on-chip systems. Full article

Flexible strain sensors have attracted considerable attention in gait recognition owing to their ability to adhere directly to the skin near joints and transduce local deformation. In existing work, however, sensor placement and orientation are largely determined by anatomical experience, while multi-channel classification still relies on back-end digital processors, whose power consumption and latency constrain system practicality in wearable scenarios. This paper presents an integrated design path that proceeds from skin-mechanics theory through sensor-layout optimization to analog-domain front-end inference. On the layout side, the lines-of-non-extension (LoNE) theory is employed to convert the selection of sensor attachment angles from empirical judgment into a calculable mechanics problem; guided by the spatial course of LoNE in the ankle and knee regions, the positions and angles of the nine sensors are determined individually—channels perpendicular to the LoNE capture maximum strain, channels offset by 45 degrees supplement non-sagittal-plane information, and a channel aligned along the LoNE provides a near-zero-strain reference. On the circuit side, the mathematical equivalence between the weighted summation of a linear classifier and Kirchhoff’s current law (KCL) nodal current superposition is exploited to map the classification operation onto current aggregation in an analog circuit, yielding an in-sensor computing (ISC) front end in which the nine-channel weighted summation is completed in a single analog step. The sensors are fabricated by screen-printing a liquid-metal–polymer composite conductive ink onto a TPU film substrate, with a gauge factor RSD of $6.8\%$ and a tensile linearity $R^2>0.99$. Using walking, running, and stair descent as verification targets, the analog classifier reaches 99% accuracy at the circuit-level functional-verification stage. On real multi-subject data, it achieves $87.0\%\pm 8.4\%$ accuracy under intra-subject cross-session validation, with an analog-domain inference response faster than $100\mathsf{\mu }\mathrm{s}$. This design path is not bound to a specific joint or sensor material; when the layout methodology is extended to additional joint regions and the circuit architecture incorporates multiple outputs to cover more classification categories, the same workflow remains applicable, offering a promising low-power, lightweight technical solution for wearable motion monitoring. Full article

EMAT technology for Non Destructive testing is an important method for materials testing in several industries. In EMAT tools, a key issue is the EMAT coils design and implementation. Depending on the type of inspection, the coil type should be selected, and then, its dimensions should be calculated. This paper describes a methodology to select, design and implement EMAT coils based on Lorentz Force for applications such as thickness measurement and crack detection. Unlike previous works that focus on a single coil topology, this study integrates coil selection, dimensional design, COMSOL-based radiation-pattern simulation and experimental validation within a single workflow. Four Lorentz-force coil designs are covered: PCB spiral (CSPCB), 3D-printed spiral (CS3D), PCB meander-line (CMPCB) and 3D-printed meander-line (CM3D). Key design parameters are explicitly addressed: number of turns N, outer and inner radii R and $r_0$, track width w and spacing s for spiral coils, and meander length and inter-trace distance for meander-line coils. Simulation verification is performed in COMSOL Multiphysics by evaluating the von Mises stress along a semicircular path around the coil to obtain the angular radiation pattern. Experimentally, polar radiation patterns are measured at 500 kHz, 1.9 MHz and 4 MHz on a steel specimen, matching the simulation frequencies, with maximum amplitudes of 32.2, 46.4, 47.9 and 10.6 mV for CSPCB, CS3D, CMPCB and CM3D, respectively, showing consistent agreement between simulated and measured lobe shape and directivity. This work also uses an analogy with radio frequency antennas to better understand the operation of coils through the concept of radiation patterns, in this case in solid materials such as steel. Full article

Introduction: Neurosurgery has evolved from an anatomy-driven analog discipline into a digitally augmented field supported by multimodal imaging, neuronavigation, intraoperative imaging, neurophysiological monitoring, robotics, augmented reality, and artificial intelligence. Objective: To examine how this transition has altered professional responsibility, informed consent, training, and medico-legal accountability in neurosurgical practice. Methods: We performed a structured narrative review of the literature on digital neurosurgery and its ethical and professional implications, focusing on publications from 1990 onward and supplemented by landmark historical papers. Sources were selected for relevance to cranial, spinal, skull base, stereotactic, and neuro-oncological neurosurgery, and then synthesized into thematic domains including brain shift, eloquent cortex preservation, stereotactic accuracy, intraoperative neurophysiology, workflow integration, equity, and liability. Results: Digital systems improve lesion localization, function-preserving surgery, stereotactic precision, documentation, and training, but they also introduce new vulnerabilities related to registration error, brain shift, platform dependence, data overload, cost, cybersecurity, deskilling, and diffuse accountability. Conclusions: Digital augmentation expands rather than diminishes the neurosurgeon’s responsibility. The neurosurgeon remains accountable for surgical indication, interpretation of technology-generated information, intraoperative override, and communication of technology-specific risks. The central ethical challenge is to integrate digital tools without weakening patient-centered judgment. Full article

Analog, paper-based workflows remain the norm in the condition assessment of reinforced concrete infrastructure, limiting the efficiency with which diagnostic data can be used in maintenance planning. In this research, a pre-processing procedure and BIM implementation workflow for half-cell potential measurement data are proposed, implemented in open-source software, to enable data-efficient integration of diagnostic information into a BIM model. By interpreting the potential mappings as point clouds, areas relevant for maintenance planning are automatically identified through the analysis of geometric features. These identified areas are subsequently transformed into BIM objects that carry the relevant diagnostic information. The results demonstrate that the pre-processing procedure and BIM implementation workflow reduce the number of required BIM objects by over 98% (from 27,040 to 434 elements) and the IFC file size by 97% (from 77.8 MB to 2.3 MB), enabling a lightweight BIM implementation with substantially improved rendering performance. Full article

Offshore pipeline landfall sections in tropical coastal zones are often exposed to dynamic hydrodynamic forcing, which may induce seabed erosion and wave-driven liquefaction and thereby affect burial stability. This study presents an integrated assessment of seabed stability for an offshore gas pipeline along the Sarawak coast of the South China Sea, aiming to support burial-depth design in the nearshore surf zone. A multi-model framework was applied to simulate regional hydrodynamics, sediment transport, storm-induced seabed morphodynamics, and wave-induced liquefaction. Model performance was evaluated using field observations, bathymetric survey data, and laboratory experimental results. The results indicate that the seabed remains generally stable under normal environmental conditions, whereas extreme storm-wave forcing may induce localized surf-zone erosion and shallow seabed weakening. Under the 100-year storm-wave scenarios, the maximum simulated erosion depth reaches approximately 0.82 m, and the potential liquefaction response is mainly confined to the upper approximately 1.0 m of the seabed. These results suggest that storm-induced morphodynamic cover loss and wave-induced degradation of near-surface soil support should be evaluated jointly. Based on this integrated process envelope, a minimum burial depth of 2 m is recommended as a conservative engineering requirement for the examined landfall conditions. This process-integrated assessment workflow offers an applicable reference for the design and risk mitigation of analogous offshore pipeline projects in tropical coastal zones. Full article

Background: Effective topical anesthesia is essential to patient comfort and adherence during minimally invasive esthetic procedures. We retrospectively reviewed pain scores recorded after microneedling in a single private clinic where two topical anesthetic formulations—lidocaine 7%/tetracaine 7% (Pliaglis) and lidocaine 2.5%/prilocaine 2.5% (Anesderm)—were used as part of standard clinical practice on different anatomical sites and under different application protocols. Methods: Records were reviewed from 26 healthy female patients (mean age 42 ± 4 years; range 34–48) who underwent microneedling on the face and neck during 2024 in a single private clinic. According to the established clinic protocol, which was not modified for research purposes, Pliaglis was applied to the face without additional occlusion (self-occlusive peel-off film, in accordance with the manufacturer’s recommendation) and Anesderm was applied to the neck under plastic-film occlusion (also in accordance with the manufacturer’s recommendation), both for 45 min prior to microneedling at a fixed depth of 1.25 mm. Treatment allocation was determined by clinic workflow; patients and the operator were not blinded, and the order of the two products within each session was not randomized. Post-procedural pain was recorded using a Visual Analog Scale (VAS, 0–10), with one decimal precision, separately for each anatomical site. Within-patient differences were analyzed using a paired-sample t-test, with a Wilcoxon signed-rank test as a non-parametric sensitivity analysis. Results: Pain scores were lower at the facial site (Pliaglis, no occlusion) than at the cervical site (Anesderm, occlusion): mean VAS 3.00 ± 0.63 vs. 5.38 ± 0.75; mean within-patient difference 2.38 points, 95% CI 1.97–2.80; paired t(25) = 11.87, p < 0.0001; Cohen’s d = 2.33. The Wilcoxon signed-rank test produced a concordant result (p < 0.0001). A within-patient pain reduction of at least 30% on the facial site relative to the cervical site was observed in 81% of patients (21/26). Both products were well tolerated, with only mild transient erythema reported. Conclusions: In this retrospective, non-randomized, non-blinded single-center analysis, lower pain scores were observed at the facial site (treated with lidocaine-tetracaine 7%/7% without additional occlusion, per manufacturer instructions) than at the cervical site (treated with lidocaine-prilocaine 2.5%/2.5% under occlusion, per manufacturer instructions) within the same patients. Because formulation, active-drug concentration, anatomical site, and the manufacturer-mandated occlusion technique co-varied between the two conditions, the observed difference cannot be attributed to formulation alone. These findings should be regarded as hypothesis-generating and require confirmation in prospective, randomized, split-region or split-face studies that disentangle formulation effects from site- and protocol-related factors. Full article

Computational clearing (CC) enhances widefield (WF) fluorescence microscopy by suppressing out-of-focus haze and autofluorescence, yielding semi-confocal quality images suitable for segmentation and image-based phenotyping. Here, we propose an “image tracing” workflow for inflammatory mouse intestinal organoids (mIOs) using paired CC and WF images to generate a differential signal (CC − WF). mIOs were derived from intestinal crypts of Lgr5-EGFP stem cell reporter mice and expanded under epidermal growth factor, Noggin, and R-spondin (ENR) conditions. Inflammation was induced by dextran sulfate sodium (DSS) treatment. CC processing enhanced phalloidin-stained apical F-actin and improved EGFP signals by reducing background noise, enabling robust segmentation and quantitative extraction of image morphometrics including area, circularity, and perimeter. CC-WF vectors derived from three-dimensional area–perimeter–circularity plots sensitively captured DSS-induced epithelial disruption analogous to a leaky-epithelium phenotype. Transcriptomic analysis by RNA-seq of DSS-treated mIOs revealed upregulation of inflammatory pathways including TNF-α signaling via NF-κB and IL-6/JAK/STAT3, aligning with microscopy findings. In a proof-of-concept demonstration using phalloidin-stained fluorescence images, ROC analysis of the CC-WF workflow achieved an AUC = 0.95 with 87.5% sensitivity and 92.9% specificity in distinguishing intact from injured mIOs. Full article

Coal roadway support design still relies heavily on engineering analogy and simplified analytical rules, which limits transferability across sites with different geological and geometric conditions. This study develops a theory-constrained machine learning workflow for roof bolt-cable support design and evaluates the generated scheme through FLAC3D simulation. A hybrid dataset containing 80 samples, including 30 real engineering cases and 50 constrained augmented samples, was established. Twelve geological and roadway descriptors were used to predict eight roof-support parameters with weighted single-target models based on random forest, XGBoost, support vector regression, and Gaussian process regression. The optimal regressor differed among targets, confirming strong parameter heterogeneity. The 11104 return-air roadway of Jingu Mine was selected as the main validation case, and the Sanxia 1008 material roadway of Fucun Mine was used as an external consistency case. For the 11104 return-air roadway, the workflow predominantly recommended increasing the roof bolt length from 2.00 m to 2.64 m. FLAC3D results showed reduced roof subsidence and slightly lower local stress peaks, but no improvement in rib convergence. The proposed workflow is therefore better interpreted as a roof-priority optimization tool that integrates data-driven prediction, theoretical correction, and numerical verification. Full article

Background/Objectives: Carbonic anhydrase I (CAI) is a zinc-dependent metalloenzyme whose inhibitor discovery requires both effective navigation of chemical space and explicit evaluation of coordination-credible binding hypotheses. We aimed to develop an interpretable and reproducible QSAR-to-structure workflow for CAI inhibitor discovery. The workflow links potency prediction with zinc-site plausibility and early developability to support decision-oriented prioritization of new CAI inhibitor candidates. Methods: CAI inhibitors were retrieved from ChEMBL (CHEMBL261) and modeled as $p{K}_i=9-{\mathrm{l}\mathrm{o}\mathrm{g}}_{10}(K_i [\mathrm{n}\mathrm{M}\left]\right)$. AlvaDesc v3.0.8 generated 4224 2D descriptors, which were reduced using train-only preprocessing, variance filtering, correlation pruning, and bagged-tree ranking to a top-100 panel. Five regressors (elastic net, CART, bagging, GB, and XGB) were benchmarked on a held-out test set. Potent ChEMBL seeds (K_i ≤ 10 nM) were used for a 90% 2D similarity PubChem expansion. Predicted hits were then externally validated using independently available PubChem CAI $K_i$ records. Ten novel candidates lacking CAI $K_i$ data were docked to CAI (PDB: 1AZM) via SwissDock AutoDock Vina in neutral and relevant anionic states, with pose selection constrained by a Zn-donor filter (Zn-N/O $\le 2.6$ Å). SwissADME was used to profile physicochemical space, alerts, and absorption/distribution proxies. Results: The bagging model showed the best test generalization ($R^2=0.646$; RMSE = 0.61; MAE = 0.45). PFI and SHAP converged on sulfur/heteroatom connectivity and polar–lipophilic organization as dominant potency drivers. PubChem expansion yielded 25,315 analogs and 233 candidates at predicted $p{K}_i\ge 8.0$; external validation on 145 CAI-measured hits gave $R^2=0.358$ (RMSE = 0.456; MAE = 0.320). Across 20 ligand/protomer docking runs, 12 produced canonical Zn-anchored poses (10 Zn-N; 2 Zn-O). SwissADME indicated consensus logP values from −0.65 to 3.21, 0/10 PAINS alerts, and predominantly favorable drug-likeness (8/10 with zero Lipinski violations), supporting tiered advancement. Conclusions: Integrating interpretable QSAR, external PubChem validation, coordination-aware docking, and SwissADME yields a practical triage framework for CAI inhibitor discovery. The resulting tiered shortlist identifies two Zn-N-anchored N-alkyl sulfamides (CIDs 103935964 and 112684680) and one Zn-O-anchored carboxylate control (CID 122367674) as highest-priority computational hypotheses for staged biochemical evaluation. Full article

In the northern Norwegian North Sea, the Lower Paleogene post-rift succession constitutes an underexplored interval with considerable potential for stratigraphic petroleum plays. Nevertheless, predicting its subsurface prospectivity remains hindered by persistent uncertainties in facies architecture, depositional heterogeneity, and reservoir quality. To address these uncertainties, the present study integrates relative geologic time (RGT)-based seismic stratigraphic interpretation, spectral decomposition, sedimentary facies analysis, and litho-saturation assessment, primarily constrained by seismic and well-log datasets, to evaluate the Paleocene post-rift Lista Formation in the northern Norwegian North Sea. The results reveal the presence of Paleocene mass-transport deposit (MTD) complexes associated with axial lobe sandstones of submarine fan systems. These MTD complexes exhibit pronounced vertical and lateral facies transitions into low-density turbidites, debrites, and hemipelagic drapes, together forming an effective stratigraphic framework for hydrocarbon entrapment. Although the Lista submarine-fan sandstones are relatively thin, typically ranging from a few centimeters to decimeters in thickness, they display favorable reservoir characteristics. Litho-saturation analysis indicates preserved porosity and low water saturation (<20%), supporting their potential as effective hydrocarbon storage intervals. Distal fan-lobe sandstones, despite their limited thickness, show encouraging reservoir quality, whereas thicker low stand systems tract (LST) accumulations and time-equivalent carbonate mound complexes appear to have developed within more proximal structural domains. This proximal-to-distal facies organization reflects the dynamic interaction between tectonically inherited accommodation space and sediment-routing pathways during the early Paleocene. Overall, the findings highlight the significant petroleum prospectivity of the Paleocene post-rift succession in the northern Norwegian North Sea. The stratigraphic juxtaposition of sand-prone submarine-fan lobes against hemipelagic sealing intervals, combined with heterogeneity imposed by syn-rift structural inheritance, generates a highly favorable architecture for stratigraphic trapping. More broadly, the integrated workflow presented here enhances the predictive mapping of subtle stratigraphic traps within post-rift successions and provides a robust framework for reducing exploration uncertainty in analogous basins. Full article

With the rapid and ongoing expansion of urban areas, the need for accurate, reliable, and regularly updated topographic maps has become increasingly critical for planning and sustainable development. While traditional aerial photogrammetry—whether analog or digital—has long been the standard for such tasks, it remains costly, time-consuming, and logistically demanding, particularly when large or inaccessible regions are involved. This study proposes an alternative approach based on very-high-resolution satellite imagery, focusing specifically on data acquired from Morocco’s Mohammed VI A and B satellites. The research evaluates the capacity of this satellite imagery to support large-scale topographic mapping, both in terms of geometric accuracy and the ability to identify essential urban features. To validate the results, we conducted a comparative analysis of satellite data with conventional photogrammetric imagery from analog cameras (RMK TOP) and digital sensors (ADS, DMC), using ground control points (GCPs) and differential GPS (DGPS) measurements for calibration and accuracy assessment. The outcomes demonstrate that planimetric accuracy from satellite imagery meets the required standards for mapping at 1:10,000 and 1:5000 scales. However, altimetric accuracy is closer to the upper permissible limits, especially in applications requiring finer detail. While major urban elements such as roads, buildings, and vegetation are well identified, smaller infrastructure components, such as power lines, remain challenging to detect. Despite these limitations, the study highlights the growing potential of satellite imagery as a cost-effective and operationally efficient alternative to traditional methods, particularly in rapidly evolving urban environments where frequent map updates are essential. Integration with GeoAI workflows is identified as a key direction for future research and is not part of the current methodology. Full article

Highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b continues to circulate globally across wild birds, poultry, and an expanding range of mammalian hosts, highlighting the need for antiviral strategies that address the animal–environment–human interface. The influenza A polymerase acidic (PA) endonuclease, a key enzyme in viral transcription, represents a conserved antiviral target across host species. In this study, we present a computational prioritization framework integrating homology modeling, molecular docking, molecular dynamics simulations, and physicochemical filtering to identify candidate PA endonuclease inhibitors relevant to a One Health context. Homology models of contemporary H5N1 clade 2.3.4.4b PA sequences were constructed based on the crystallographic template 6FS8 and used for cross-host docking against a targeted ligand library. Docking analysis identified baloxavir, a reference inhibitor, and entecavir, a nucleoside analog, as compounds of interest, with entecavir demonstrating favorable binding behavior, particularly in the poultry-associated model. Molecular dynamics simulations of the poultry PA–entecavir complex indicated stable interaction over 170 ns, supported by low structural deviation and favorable binding free energy (ΔG ≈ −85 kJ/mol). Physicochemical profiling suggested that entecavir possesses properties such as high polarity and predicted aqueous solubility, which were considered within the translational filtering step of this computational workflow. However, these properties do not establish antiviral efficacy or practical suitability for field use. The study provides a structured framework for integrating cross-host structural analysis with basic translational considerations, supporting the identification of candidate compounds for further biochemical and virological evaluation within the context of H5N1 control. Full article

Synthetic cathinones are among the most frequently encountered classes of new psychoactive substances, and many occur as structural isomers sharing identical molecular formulas and highly similar mass-spectral features. Among them, substituted cathinones with the molecular formula C12H17NO (MW 191 Da) present particular analytical challenges because of their similar chromatographic behavior and overlapping ionization patterns. This study evaluated a combined EI-GC-MS and ESI-LC-MS/MS workflow, incorporating derivatization with trifluoroacetic anhydride (TFAA) and acetic anhydride (AA), for the differentiation of ten MW 191 Da isomers. TFAA-derivatized GC-MS enabled preliminary classification of the isomers, although several EMC and MEC analogs remained only partially resolved. AA derivatization improved the separation of unresolved isomers under slower oven temperature conditions, demonstrating the value of alternative acylation for enhancing chromatographic discrimination. LC-MS/MS provided complementary confirmation for several analytes, but some isomers remained difficult to distinguish because of shared product ions and peak fusion in mixed-standard analysis. Overall, this study establishes a practical analytical workflow for distinguishing MW 191 Da substituted cathinone isomers and highlights both the strengths and limitations of combining derivatization-based GC-MS with LC-MS/MS confirmation in routine forensic or clinical laboratories. Full article