Search Results (278)

The integration of artificial intelligence (AI) and advanced digital workflows is revolutionising full-arch implant dentistry, particularly for geriatric patients with edentulous and atrophic arches, for whom achieving both prosthetic passivity and optimal aesthetic outcomes is critical. This narrative review evaluates current challenges in intraoral scanning accuracy—such as scan distortion, angular deviation, and cross-arch misalignment—and presents how innovations like the Medit SmartX AI-guided workflow and the Scan Ladder system can significantly enhance precision in implant position registration. These technologies mitigate stitching errors by using real-time scan body recognition and auxiliary geometric references, yielding mean RMS trueness values as low as 11–13 µm, comparable to dedicated photogrammetry systems. AI-driven prosthetic design further aligns implant-supported restorations with facial symmetry and smile aesthetics, prioritising predictable midline and occlusal plane control. Early clinical data indicate that such tools can reduce prosthetic misfits to under 20 µm and lower complication rates related to passive fit, while shortening scan times by up to 30% compared to conventional workflows. This is especially valuable for elderly individuals who may not tolerate multiple lengthy adjustments. Additionally, emerging AI applications in design automation, scan validation, and patient-specific workflow adaptation continue to evolve, supporting more efficient and personalised digital prosthodontics. In summary, AI-enhanced scanning and prosthetic workflows do not merely meet functional demands but also elevate aesthetic standards in complex full-arch rehabilitations. The synergy of AI and digital dentistry presents a transformative opportunity to consistently deliver superior precision, passivity, and facial harmony for edentulous implant patients. Full article

This review presents a comprehensive synthesis of recent advances in the tensile performance of adhesively bonded joints, focusing on applied aspects and modeling developments rather than providing a full theoretical analysis. Although many studies have addressed individual joint types or modeling techniques, an integrated review that compares joint configurations, modeling strategies, and performance optimization methods under tensile loading remains lacking. This work addresses that gap by examining the mechanical behavior of key joint types, namely, single-lap, single-strap, and double-strap joints, and highlighting their differences in stress distribution, failure mechanisms, and structural efficiency. Modeling and simulation approaches, including cohesive zone modeling, extended finite element methods, and virtual crack closure techniques, are assessed for their predictive accuracy and applicability to various joint geometries. This review also covers material and geometric enhancements, such as adherend tapering, fillets, notching, bi-adhesives, functionally graded bondlines, and nano-enhanced adhesives. These strategies are evaluated in terms of their ability to reduce stress concentrations and improve damage tolerance. Failure modes, adhesive and adherend defects, and delamination risks are also discussed. Finally, comparative insights into different joint configurations illustrate how geometry and adhesive selection influence strength, energy absorption, and weight efficiency. This review provides design-oriented guidance for optimizing bonded joints in aerospace, automotive, and structural engineering applications. Full article

In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of $3\times {10}^{16}$ 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach. Full article

In tolerance design for complex mechanical systems, 3D dimension chain analyses are crucial for assembly accuracy. The current methods (e.g., worst-case analysis, statistical tolerance analysis) face limitations from oversimplified assumptions—treating datum features as ideal geometries while ignoring manufacturing-induced spatial distribution of form errors and failing to characterize 3D coupled error constraints. This study proposes a six-dimensional spatial dimension chain (SDC) model based on transfer matrix theory. The key innovations include (1) a six-dimensional model integrating position and orientation vectors, incorporating geometric error propagation constraints for high-fidelity error prediction and tolerance optimization, (2) the characterization of spatially distributed form errors and 3D coupled errors of spatial dimension chain-based multiple mating-surface constraint (SDC-MMSC) using six-degree-of-freedom (6-DoF) geometric error components, reducing the assembly topology complexity while improving the efficiency, and (3) a 6-DoF error characterization method for non-mating-constrained data, providing the theoretical basis for SDC modeling. The experimental validation on an aero-engine casing assembly shows that the SDC model captures multidimensional closed-loop spatial errors, with absolute errors of max–min closed-loop distances below 9.3 μm and coaxiality prediction errors under 8.3%. The SDC-MMSC method demonstrates superiority, yielding normal vector angular errors <0.008° and envelope surface RMSE values <0.006 mm. This method overcomes traditional simplified assumptions, establishing a high-precision, multidimensional distributed-form-error-driven SDC model for complex mechanical systems. Full article

The patch loading resistance of slender steel plate girders is a critical factor in the design of launched steel and composite steel–concrete bridges. Traditional design methods enhance patch loading resistance through various stiffening techniques, with contributions typically estimated via code expressions calibrated on experimental data that do not always reflect the complexities of full-scale bridge applications. Finite Element (FE) modeling offers a more realistic alternative, though its practical application is often hindered by modeling uncertainties and nonlinearities. To bridge this gap, this paper introduces an advanced FE modeling approach. It provides a comprehensive description of an FE model that accurately predicts both the load–displacement behavior and the patch loading resistance. The model is benchmarked against a broad set of experimental tests and systematically investigates the effects of key modeling parameters and their interactions—material stress–strain law, boundary condition representation, stiffness of the load introduction area, initial geometric imperfections, and solving algorithms. Key findings demonstrate that a bilinear elastoplastic material model with hardening is sufficient for estimating ultimate resistance, and kinematic constraints can effectively replace rigid transverse stiffeners. The stiffness of the load application zone significantly influences the response, especially in launched bridge scenarios. Initial imperfections notably affect both stiffness and strength, with standard fabrication tolerances offering suitable input values. The modified Riks algorithm is recommended for its efficiency and stability in nonlinear regimens. The proposed methodology advances the state of practice by providing a simple yet reliable FE modeling approach for predicting patch loading resistance in real-world bridge applications, leading to safer and more reliable structural designs. Full article

A DataMatrix (DM) code is an automatic identification barcode based on a combination of coding and image processing. Traditional DM code sampling methods are mostly based on simple segmentation and sampling of a DM code. However, the obtained DM code images often have problems such as wear, corrosion, geometric distortion, and strong background interference in practical scenarios. To improve decoding ability in complex environments, a DM code recognition method based on coarse positioning of images is proposed. The two-dimensional barcode is first converted into a one-dimensional waveform using a projection algorithm. Then, the spacing between segmentation lines is predicted and corrected using an exponential weighted moving average model for adaptive grid division. Finally, the local outlier factor algorithm and local weighted linear regression algorithm are applied to predict and binarize the gray level values, converting the DM code image into a data matrix. The experimental results show that this method effectively handles problems like blurring, wear, corrosion, distortion, and background interference. Compared to popular DM decoding libraries like libdmtx and zxing, it demonstrates better resolution, noise resistance, and distortion tolerance. Full article

We designed lens systems for a smart-pixel-based optical convolutional neural network (SPOCNN) using optical software to analyze image spread and estimate alignment tolerance for various kernel sizes. The design, based on a three-element lens, was reoptimized to minimize spot size while meeting system constraints. Simulations included root mean square spot and encircled energy diagrams, showing that geometric aberration increases with the scale factor, while diffraction effect remains constant. Alignment tolerance was determined by combining geometric image size with image spread analysis. While the preliminary scaling analysis predicted a limit at a kernel array size of 66 × 66, simulations showed that a size of 61 × 61 maintains sufficient alignment tolerance, well above the critical threshold. The discrepancy is likely due to lower angular aberration in the simulated optical design. This study confirms that an array size of 61 × 61 is feasible for SPOCNN, validating the scaling analysis for predicting image spread trends caused by aberration and diffraction. Full article

Background: Prophylactic human papillomavirus (HPV) vaccination substantially alleviates cervical cancer burden. This study aimed to evaluate the safety, tolerability, and immunogenicity of an Escherichia coli-expressed recombinant nonavalent HPV vaccine. Methods: A dose-escalating phase 1 clinical trial was conducted in Sheyang County, Jiangsu Province, China. Each participant received either the test vaccine or the control vaccine (Gardasil 9) following a 0/2/6-month schedule. Adverse reactions (ARs) within 7 days after vaccination, adverse events (AEs) within 30 days, and serious adverse events (SAEs) throughout the study were recorded. Blood parameters were measured before and 3 days after each dose. Serum immunoglobulin G (IgG) and neutralizing antibodies (nAbs) against nine HPV types were analyzed at months 0, 3, and 7. Results: A total of 160 women aged 18–45 years were enrolled, and 155 participants completed the full vaccination regimen. Within 7 days following vaccination, the incidence of ARs ranged from 56.67% to 90.00%, with the low-dose group showing a significantly higher rate than the control group (p = 0.004). Most AEs were mild or moderate, and no vaccine-related SAEs occurred. No significant differences were observed among the four groups regarding the incidence of abnormal laboratory findings. Seroconversion rates for nAbs and IgG against nine HPV types exceeded 97.92% following three doses. High levels of nAbs and IgG were observed at months 3 and 7, with geometric mean titers (GMTs) showing further increases by month 7. Conclusions: This new recombinant nonavalent HPV vaccine exhibits good tolerability and strong immunogenicity among women aged 18–45 years, supporting further efficacy studies in larger populations. Full article

Despite significant progress, fabricating two-dimensional (2D) lithium niobate (LN)-based photonic crystal (PhC) cavities integrated with tapered and PhC waveguides remains challenging, due to structural imperfections. Notable, especially, are variations in hole radius (r) and inclination angle (°), which induce bandgap shifts and degrade quality factors (Q-factor). These fabrication errors underscore the critical need to address nanoscale tolerances. Here, we systematically investigate the impacts of key geometric parameters on optical performance and optimize a 2D LN-based cavity integrated with taper and PhC waveguide system. Using a 3D Finite-Difference Time-Domain (FDTD) and varFDTD simulations, we identify stringent fabrication thresholds. The a must exceed 0.72 µm to sustain Q > ${10}^7$; reducing a to 0.69 µm collapses Q-factors below ${10}^4$, due to under-coupled modes and bandgap misalignment, which necessitates ±0.005 µm precision. When an r < 0.22 µm weakens confinement, Q plummets to 2 × ${10}^4$ at r = 0.20 µm (±0.01 µm etching tolerance). Inclination angles < 70° induce 100× Q-factor losses, requiring ±2° alignment for symmetric modes. Air slot width (s) variations shift resonant wavelengths and require optimization in coordination with the inclination angle. By optimizing s and the inclination angle (at 70°), we achieve a record Q-factor of 6.21 ×${10}^6$, with, in addition, C-band compatibility (1502–1581 nm). This work establishes rigorous design–fabrication guidelines, demonstrating the potential for LN-based photonic devices with high nano-fabrication robustness. Full article

Dual-mode sensors are currently facing difficulties in achieving independent sensing of parameters as well as low sensitivity. In this paper, we propose a dual-mode sensor using the finite element method (FEM) based on a coupled silver–PDMS–gold (SPG) cavity. We coupled a square ring resonant cavity with a double-ring resonant cavity structure, thus identifying a unique resonant cavity structure. The square ring resonator is made of silver and a double-ring resonant cavity filled with PDMS. Our proposed SPG cavity can independently achieve temperature and refractive index sensing. The SPG cavity enables us to obtain the highest biosensing sensitivity of about 1030 nm/RIU and the highest temperature sensitivity of about 216 pm/K. In addition, SPG cavities have excellent tolerances for geometric parameters. Our results provide new methodologies for metasurface design for dual-mode sensing. Full article

Wire electrical discharge machining (WEDM) enables the production of complex parts with tight tolerances, although maintaining dimensional accuracy in corners and tapers remains challenging due to wire deflection and vibration. This study optimizes WEDM parameters for achieving high accuracy in machining complex geometrical parts and taper cuts in 6061 aluminum alloy using an Excetek W350G WEDM machine with a copper wire electrode. Parameters including wire tension, pulse on-time, pulse off-time, wire feed rate, open circuit voltage, and flushing pressure were varied using a L18 Taguchi orthogonal array and the response graph method to identify optimal cutting conditions. Experimental results indicated that feature-specific optimization is crucial, as different geometrical features (rectangular fins, triangular fins, gears) exhibited varying critical parameters. Key findings highlighted the importance of wire tension and pulse on-time in maintaining cutting accuracy, although at varying levels for specific features. Response graphs demonstrated the effects of major WEDM parameters on corner and profile accuracies, whereas Taguchi analysis provided the optimum settings of parameters for each feature and taper cutting. These findings will help enhance precision, efficiency, and versatility of the WEDM process in machining complex profiles and corners, contributing to precision manufacturing. Full article

Objective: To assess changes in disease activity in Multiple Sclerosis (MS) patients on various disease-modifying-drugs, as well as immunogenicity, safety and clinical tolerability following combined tetanus- and diphtheria-vaccination. Methods: We conducted a prospective, multicentre, non-randomised real-world observational study at specialised outpatient MS care centres in Germany. We enrolled multiple sclerosis patients receiving a combined tetanus- and diphtheria-vaccination who had a stable MS-treatment regimen for at least six months and had an indication for this vaccination. Serum samples were obtained before and four weeks after vaccination for specific antibody response. Antibody concentrations against vaccine antigens were measured in duplicate via ELISA. Subjects were followed for one year after immunisation. MS disease activity (EDSS and relapse rates) was evaluated at follow-up visits. Local and systemic adverse events were registered four weeks after vaccination. Results: In total, 72 MS patients received tetanus and diphtheria vaccination. The annualised relapse rates in the year after vaccination were comparable to the year before vaccination (0.39 vs. 0.37). During the study period, the EDSS score did not change significantly. The score was 2.0 and 2.2 in the two years prior to vaccination and 2.5 in the year following vaccination. No subjects experienced severe adverse events. However, 14 (19.4%) had local adverse events, and 10 (13.9%) had systemic reactions. Following vaccination, all subjects had protective antibody titres against tetanus- and diphtheria-toxoid. Geometric mean antibody titres of tetanus toxoid antibodies increased from 0.64 IU/mL to 2.23 IU/mL (p < 0.0001) and of diphtheria toxoid antibodies from 0.1 IU/mL to 0.45 IU/mL (p < 0.0001). Conclusions: Tetanus- and diphtheria vaccination proved to be safe and effective in MS patients in a real-world situation. Full article

Feline parasitism affects animals’ health and welfare. Faeces from 472 client-owned cats from Greece were examined to provide updated data on the epizootiology of metazoan endo- and ectoparasites (namely, Toxocara cati, Ancylostomatidae, Dipylidium caninum, lungworms, Toxascaris leonina, Otodectes cynotis, fleas, ticks and Notoedres cati). All positive animals received a topical formulation containing esafoxolaner, eprinomectin and praziquantel (NexGard^® Combo, Boehringer Ingelheim), and its efficacy was evaluated. The overall prevalence of parasitism was 22.9%, while that of multiparasitism was 16.3%. Toxocara cati (18.4%) was the most prevalent endoparasite, followed by Ancylostomatidae (10.8%), D. caninum (4.7%), lungworms (2.5%) and T. leonina (0.4%). Regarding ectoparasites, O. cynotis (3.2%), fleas (2.3%), ticks (0.6%) and N. cati (0.4%) were found. To estimate the efficacy of treatment, the geometric means of the number of parasitic elements before the first treatment and post-treatment, (i) 14 days for intestinal helminths, (ii) 28 and 56 days for lungworms and (iii) 28 days for O. cynotis and fleas, were estimated and compared. Following statistical analyses (paired t-test and McNemar’s test), an efficacy of 100% was recorded against the most commonly detected parasites (gastrointestinal helminths and mites) and a notable statistically significant effect against fleas and lungworms after one dose, while 100% efficacy against lungworms was achieved after two doses of the product. No adverse effects were reported. The prevalence of parasitism in owned cats in Greece remains high, highlighting the demand for targeted preventive antiparasitic schemes. This study demonstrated high-level efficacy and tolerance of NexGard^® Combo against common endoparasites and ectoparasites of household cats in Greece. Full article

In an air-conditioned multinational graduate students’ office in Japan during the winter season, we examined indoor environmental conditions, occupants’ perceptions, and their acceptance levels over five consecutive days. Indoor air quality (IAQ) acceptance peaked on the third day, coinciding with the most favourable thermal sensation vote, which was “neutral” at a geometric mean indoor temperature of 25.1 °C. Aural comfort received the lowest acceptance due to ongoing construction work, but did not significantly impact overall IEQ acceptance, thus suggesting that unacceptable aspects of indoor environmental quality (IEQ) can be offset by acceptable aspects. IAQ and thermal comfort compensated for its effects, offering insights into occupants’ environmental tolerance. IAQ sensation votes and visual comfort votes exhibit a strong relationship with overall comfort, as indicated by their respective R² values. However, variations in overall comfort are primarily explained by IAQ, which has the highest R² value of 0.50, suggesting that IAQ accounts for 50% of the changes in overall occupant comfort. Non-Japanese participants had lower IEQ acceptance and a significantly higher number of complaints than Japanese participants more so in visual comfort where acceptable luminance levels were higher in Japan than other participants’ countries of origin. Thermal comfort was mutually highly accepted by both groups. Nose and eye irritation were significantly experienced by the international participants due to low RH levels but experiencing loss of concentration and lethargy was comparable in both groups (p > 0.05, t-test). We recommend global coherence in indoor environmental quality standards as is the case with drinking water standards for public health protection and seamless transitions in new indoor environments. Full article

Additive manufacturing of metals is limited by a fundamental tradeoff between deposition rates and manufacturability of fine-scale features. To overcome this problem, a laser-ablated bound metal deposition (laBMD) process is demonstrated in which 3D-printed green-state bound metal deposition (BMD) parts are post-processed via laser ablation prior to conventional BMD debinding and sintering. The laBMD process is experimentally characterized via a full-factorial design of experiments to determine the effect of five factors—number of laser passes (one pass, three passes), laser power (25%, 75%), scanning speed (50%, 100%), direction of laser travel (perpendicular, parallel), and laser resolution (600 dpi, 1200 dpi)—on as-sintered ablated depth, surface roughness, width, and angle between ablated and non-ablated regions. The as-sintered ablation depth/pass ranged from 3 to 122 µm/pass, the ablated surface roughness ranged from 3 to 79 µm, the angle between ablated and non-ablated regions ranged from 1° to 68°, and ablated bottom widths ranged from 729 to 1254 µm. This study provides novel insights into as-manufactured ablated geometries and surface finishes produced via laser ablation of polymer–metallic composites. The ability to inexpensively and accurately manufacture fine-scale features with tailorable geometric tolerances and surface finishes is important to a variety of applications, such as manufacturing molds for microfluidic devices. Full article