Search Results (14,950)

The inherently high-voltage-length product (V_πL) of thin-film lithium niobate (TFLN) modulators in the O-, C-, and L-telecom bands restricts further scaling of photonic integrated circuits’ bandwidth density, driving their migration toward shorter operating wavelengths. Nevertheless, the corresponding grating couplers, as critical optical input/outputs (optical I/Os) interfaces, remain largely undeveloped. Here, we demonstrate an 850 nm TFLN grating coupler designed based on topological unidirectional guided resonance (UGR). By breaking C₂ symmetry of the unit cell and precisely tailoring its geometry, we achieve unidirectional upward radiation with a 63.7 dB up/down intensity ratio. Subsequent apodization of groove widths and periods enables precise control of the electrical field distribution in both real and momentum spaces. This yields a vertical-cavity surface-emitting laser (VCSEL)-matched, highly fabrication-tolerant TFLN grating coupler that attains, to the best of our knowledge, the highest simulated coupling efficiency of −0.6 dB without mirrors or hybrid materials. This work delivers a high-efficiency, layout-flexible, and complementary metal oxide semiconductor (CMOS)-compatible optical I/Os solution for short-wavelength TFLN modulators with low V_πL. It offers substantial engineering value and broad applicability for on-chip light source integration and high-bandwidth-density short-reach optical interconnects. Full article

Accurate field-scale meteorological information is required for precision agriculture, but operational numerical weather prediction products remain spatially coarse and cannot resolve local microclimate variability. This study proposes a data fusion superresolution workflow that combines global GFS predictors (0.25°), regional station observations from Southern Moravia (Czech Republic), and static physiographic descriptors (elevation and terrain gradients) to predict the 2 m air temperature 24 h ahead and to generate spatially continuous high-resolution temperature fields. Several model families (LightGBM, TabPFN, Transformer, and Bayesian neural fields) are evaluated under spatiotemporal splits designed to test generalization to unseen time periods and unseen stations; spatial mapping is implemented via a KNN interpolation layer in the physiographic feature space. All learned configurations reduce the mean absolute error relative to raw GFS across splits. In the most operationally relevant regime (unseen stations and unseen future period), TabPFN-KNN achieves the lowest MAE (1.26 °C), corresponding to an ≈24% reduction versus GFS (1.66 °C). The results support the feasibility of an operational, sensor-infrastructure-compatible pipeline for high-resolution temperature superresolution in agricultural landscapes. Full article

The objective of this in vitro study was to investigate the effects of dentin pretreatment protocols and thermocycling on the shear bond strength (SBS) of a self-adhesive resin cement (Maxcem elite chroma) on dentin. A total of 168 extracted human third molars were randomly divided into four main groups according to dentin pretreatment: no treatment, 10% polyacrylic acid, Optibond universal, and Scotchbond universal plus. Half of these were subjected to thermocycling (5000 cycles; 5–55 °C). Composite resin rods were bonded using the self-adhesive resin cement, and SBS was measured with a universal testing machine. Two-way ANOVA showed that dentin pretreatment and thermocycling significantly affected SBS, with significant interaction between factors (p < 0.001). The highest SBS was observed in the Optibond universal group (18.71 ± 0.43 MPa), while the lowest SBS occurred in the 10% polyacrylic acid-treated group after thermocycling (2.69 ± 0.39 MPa). Thermocycling significantly reduced SBS in all groups. These results indicate that pretreatment with a compatible universal adhesive improves bond durability, whereas 10% polyacrylic acid pretreatment adversely affects bonding performance. Full article

Background: Menopause is characterised by a decline in oestrogen levels, leading to physical and psychological symptoms that significantly affect quality of life. Current parenteral oestradiol ester therapies, while effective, are often associated with side effects due to their oil-based formulations, including injection-site reactions and immune responses. Methods: In this study, we developed a water-soluble, polyethylene glycol cross-linked β-cyclodextrin (PEG–β-CD) polymer-based system for parenteral oestradiol delivery and evaluated its biocompatibility, solubility enhancement, immune compatibility, and pharmacokinetics. Results: Cytotoxicity assays using NIH-3T3 fibroblasts and RAW 264.7 macrophages showed minimal toxicity up to 10% (w/w). Phase-solubility studies demonstrated a significant increase in oestradiol solubility with the PEG–β-CD polymer, surpassing that of β-cyclodextrin or PEG alone. Dynamic light scattering and FTIR analyses confirmed successful complex formation, with submicron particles averaging 271 nm and physical incorporation of oestradiol into the polymer matrix. Macrophage activation assays and RT-qPCR analyses indicated an absence of immunogenic responses or pro-inflammatory cytokine induction. In vivo toxicity testing in Galleria mellonella larvae confirmed safety, while pharmacokinetic studies in Wistar rats revealed rapid initial absorption followed by stable, low-level serum concentrations comparable to those of commercially used oestradiol esters. Conclusions: These findings indicate that the PEG–β-CD polymer–oestradiol complex provides a safe, water-based alternative to traditional oil-based injections, with the potential to reduce side effects and improve patient compliance in postmenopausal hormone therapy. Full article

The growing demand for marine resource development and in-depth exploration of the marine environment has positioned soft biomimetic underwater vehicles (SBUVs) as a research hotspot in the fields of underwater equipment and soft robotics. SBUVs are characterized by bodies made of flexible and extensible materials, integrating the dual advantages of softness and biomimetics. They can achieve muscle-like continuous deformation to efficiently absorb collision energy, while mimicking the propulsion mechanisms of marine organisms—such as fish and jellyfish—through undulating body movements or cavity contraction and relaxation. Such biomimetic propulsion is highly compatible with the flexible actuation of soft materials, enabling excellent environmental adaptability while maintaining favorable propulsion efficiency. Compared with traditional rigid underwater vehicles, SBUVs offer higher degrees of freedom, superior environmental adaptability, enhanced impact resistance and greater motion flexibility. This review systematically summarizes typical actuation methods for SBUVs—including fluid-powered actuation, shape memory alloy actuation, and electroactive polymer actuation—elaborating on their working principles, key technological advances, and representative application cases on SBUVs. These actuation mechanisms each offer distinct advantages. Fluid-powered systems are valued for high power density and precise motion control through direct fluidic force transmission. Shape memory alloys provide high force output and accurate positional recovery via controlled thermal phase changes. Meanwhile, electroactive polymers stand out for their rapid (often millisecond-scale) dynamic response, low hysteresis, and fine, muscle-like deformation under electrical stimuli. Current challenges are also analyzed, such as limited actuation efficiency, material durability issues, and system integration difficulties. Despite these constraints, SBUVs show broad application prospects in marine resource exploration, ecological monitoring, and underwater engineering operations. Future research should prioritize the development of novel materials, coordinated optimization of actuation and control systems, and breakthroughs in core technologies to accelerate the practical implementation and industrialization of SBUVs. Full article

The degradation of building foundations, underground structures, and historical fabrics in sulfate-laden environments poses a persistent threat to the durability and safety of the built environment. Developing effective, sustainable repair materials is of paramount importance. This study presents the development, systematic optimization, and performance validation of a novel micro-expansive grout designed for high durability in aggressive sulfate conditions. The grout formulation utilizes industrial by-product fly ash, quicklime, and site-compatible soils, emphasizing sustainability. Nine chemical admixtures were screened for sulfate resistance enhancement. Laboratory experiments rigorously characterized the effects of water-to-solid ratio and admixture dosage on fresh-state properties (fluidity, setting time) and hardened-state performance (volumetric stability). To resolve a multi-objective optimization problem balancing injectability, dimensional compatibility, and cost-effectiveness, an integrated multi-criteria decision-making (MCDM) framework combining FAHP, MII, CRITIC, and TOPSIS was employed. This data-driven methodology identified an optimal formulation incorporating 3% disodium hydrogen phosphate (DSP) at a 0.58 water-to-solid ratio. The optimized grout exhibited a flow value of 75 mm, ensuring excellent injectability within the target range (40–120 mm), and an expansion rate of 7.67%, which falls within the safe range (0–10%) to ensure dimensional compatibility. Accelerated durability tests via cyclic immersion in sodium sulfate solution demonstrated the optimized grout’s exceptional resistance to sulfate attack, retaining approximately 88% of its compressive strength after 15 aggressive cycles. The balanced properties and validated durability indicate strong potential for this grout in demanding repair scenarios. One key example is the repair of fissures in earthen heritage structures, which requires extreme material compatibility and long-term performance. Full article

Soil health is the sustained ability of soil to function as a vital ecosystem that supports plants, animals, and humans. Conventional agricultural practices, such as intensive tillage and monocropping, degrade soils by depleting organic matter, causing erosion, and reducing biodiversity. Agroforestry systems, by contrast, mimic natural ecosystems and offer a viable solution to restore and protect this crucial resource. The purpose of this review was to explore agroforestry’s effects on soil health in the context of sustainable agriculture. By restoring and building soil health, the review revealed that agroforestry provides a solution to combat soil degradation, enhance biodiversity, and increase agricultural sustainability. Benefits to soil are diverse and include improving its physical, chemical, and biological aspects, which boosts ecosystem services and resilience. Despite its clear advantages, agroforestry has not been widely adopted. Challenges to adoption include time lag for trees to mature, insecure land tenure and lack of expertise and institutional support. Overcoming these barriers through supportive policies, financial incentives and farmer participatory approaches offers clear pathways towards more resilient and profitable farming systems. This will require site-specific studies to optimize species selection and system designs compatible with local conditions. Long-term agroforestry success is determined by aligning site-specific conditions (soil, slope, climate) with appropriate species selection, expert management, and farmer knowledge. In conclusion, intentionally combining trees and crops provides a powerful solution for building resilient soil ecosystems and ensuring agricultural sustainability. Full article

Mid-IR flat/integrated optics require low-loss, programmable phase control. We investigate femtosecond laser direct writing (FLDW) in aluminogermanate glass (Corning 9754), first mapping the processing landscape to delineate no modification, Type I index increase, and spatial broadening regimes. We then operate in a non-accumulating regime that provides a broad, stable writing window. Quantitative-phase microscopy yields Δφ and a monotonic Δn with optically limited cross-sections compatible with low loss. Transmission spectroscopy shows high values (about 90% up to 4 µm) and no additional absorptions across the near-IR and mid-IR range. FTIR reveals a redshift of the Ge–O–(Ge/Al) stretching envelope from ≈1 µJ, correlating with the high Δn onset. s-SNOM at 925 cm⁻¹ resolves the written line as reduced near-field amplitude and decreased phase, confirming a local complex permittivity change consistent with densification-driven Type I tracks. Together, these results define practical conditions for on-demand mid-IR flat/GRIN/Fresnel optics by FLDW in this commercial mid-IR transparent glass. Full article

Background: Embryoid bodies (EBs) play a central role in organoid engineering, where their formation fidelity and size critically influence downstream differentiation outcomes. Current EB production workflows primarily rely on retrospective quality assessment, which limits reproducibility in high-throughput culture systems. Objective: This study aimed to develop a prospective, non-invasive framework that integrates early-phase bright-field time-lapse imaging with a three-dimensional convolutional neural network to predict EB formation outcomes and final EB diameter within the microwell platform. Methods: Time-lapse image sequences collected during the first hours after cell seeding on the microwell array were used to train 3D-CNN models for classification (formation vs. non-formation) and regression (final diameter). A balanced dataset was constructed through under-sampling, and five-fold cross-validation with data augmentation was applied to evaluate model performance. Results: The classification model achieved an accuracy of 96.5%, reliably distinguishing between successful and failed EB formation using short-duration image sequences. The regression model predicted the final EB diameter with a mean absolute error of ±7.1 µm, reflecting strong agreement with measured values and capturing seeding-density-dependent size variations. Conclusions: Early aggregation dynamics captured by bright-field time-lapse imaging contain sufficient spatiotemporal information to enable accurate, prospective EB quality prediction. The proposed framework provides a label-free and automation-compatible strategy for improving reproducibility in large-scale EB manufacturing and supports the future development of adaptive and closed-loop organoid culture systems for clinical applications. Full article

The utilization of waste and renewable oils as asphalt modifiers is a crucial strategy for achieving sustainable development in pavement engineering. However, the different physicochemical effects exerted by oil sources (bio-based versus petroleum-based) on the asphalt–aggregate interface remain insufficiently understood. This study aims to elucidate the influence mechanism of two bio-based oils and two petroleum-based oils on asphalt adhesion and the pavement performance of mixtures. A quantitative evaluation method combining the boiling test with digital image processing (DIP) technology was developed to assess the anti-stripping performance of modified asphalt on different lithological aggregates (acidic granite and alkaline limestone). Additionally, Fourier transform infrared spectroscopy (FTIR) was employed to reveal the chemical evolution of the modified asphalt. The results indicated that, although all oil-based modifiers demonstrated excellent compatibility and storage stability with the base asphalt (segregation ratio < 5%), their adhesion properties were significantly influenced by aggregate lithology. The key finding was that, compared to petroleum-based oils, bio-based oils exhibited superior adhesion performance on acidic granite surfaces, markedly mitigating moisture-induced stripping. FTIR analysis confirmed that this enhancement was attributable to the aromatic and carbonyl functional groups introduced by bio-based oils, which effectively promoted the interfacial bonding. Furthermore, bio-oil-modified mixtures exhibited optimal low-temperature cracking resistance without compromising high-temperature stability. These findings elucidate the mechanism by which bio-oil enhances the water-damage resistance of acidic aggregate systems, providing a theoretical basis for the optimized selection of sustainable asphalt modifiers. Full article

This narrative review aims to highlight and analyze the supervision of precision robotic surgical interventions. These are autonomous, closed-loop procedures, assisted by images and managed by intelligent digital tools. These administered procedures are designed to be safe and reliable, adhering to the principles of minimal invasiveness, precise positioning, and non-toxicity. Thus, a precision intervention uses non-ionizing imaging-assisted robotics, controlled by a precise positioning device, forming an autonomous procedure augmented by artificial intelligence tools and supervised by digital twins. This intelligent digital management procedure allows staff to plan, train, predict, and execute interventions under human supervision. Patient safety and staff efficiency are linked to non-ionizing imaging, minimal invasiveness through image guidance, and strict delimitation of the intervention zone through precise positioning. This study includes, successively, sections covering an introduction, therapeutic and surgical interventions, imaging strategies integrating diagnostic and assistance functions, intelligent digital tools including digital twins and artificial intelligence, image-guided procedures including autonomous and precision robotic surgical interventions increased by machine learning, as well as augmented healthcare monitoring, and a discussion and conclusions of the review. All topics addressed in this analysis are supported by examples from the literature. Full article

We developed an indoor positioning system combining Bluetooth direction-finding antennas with machine learning to improve localization accuracy and stability cost-effectively. It integrates existing indoor positioning and lighting control with a Bluetooth angle of arrival (AoA)-dongle, compatible with current mesh networks, using the message queuing telemetry transport protocol for data transmission to a server. The system, developed with nRF5340 and u-blox AoA antenna boards, was evaluated in an experimental field with 12 positioning points arranged in a grid. Datasets categorized by AoA antenna quantity and data preprocessing were used to train K-nearest neighbors, support vector machine (SVM), random forest, and multilayer perceptron models. Optimal parameters were identified using grid search, and models were validated using confusion matrices and F1-scores. Results indicated significant accuracy improvements of 11.11–30.51% without preprocessing and 1.17–6.32% with preprocessing when incorporating AoA features. Real-time tests revealed SVM as the best-performing model, achieving up to 96.58% accuracy, significantly enhancing positioning stability. The results of this study underscore Bluetooth direction-finding combined with machine learning as a promising solution for the Internet of Things applications. Full article

In this work, the deposition of graphene coatings on substrates of an ELI grade Ti-6Al-4V alloy was carried out using the Plasma Enhanced Chemical Vapor Deposition (PECVD) technique. The purpose of this study was to improve the surface properties of the material. The characterization of the material was carried out by non-destructive techniques, such as Raman Spectroscopy and Thermoelectric Potential. A preliminary characterization of Ti substrates was carried out by Raman spectroscopy. Conversely, thermoelectric potential tests were conducted using three distinct tip systems and four different temperature gradients. Lastly, some surface roughness measurements were conducted on all samples, both coated and uncoated. Graphene micro-structured coatings were obtained using a plasma-activated mixture of hydrogen and methane gases with an equimolar feed ratio (1:1 H₂:CH₄) at a temperature of 850 °C and a plasma exposure of 150 Watts and duration of 15 min. Raman spectra verified the presence of uniform micrometric graphene on the surface of Ti substrates. Graphene-coated Ti-6Al-4V ELI substrates exhibited Seebeck coefficient values indicating metallic-like behavior and suitability for thermoelectric sensing. In the eddy current analyses, it was found that low frequencies provided the highest sensitivity for differentiating between samples. An inverse relationship was identified between substrate thickness and phase angle, and a direct relationship with calculated electrical conductivity was also identified. This direct relation is attributed to penetration depth and interactions due to the chemical nature of the substrate and coating. Despite a slight increase in surface roughness after graphene deposition, values remained comparable to the base alloy, preserving compatibility for biomedical integration. Thermoelectric potential measurements revealed enhanced sensitivity to surface morphology and interfacial effects when high-sensitivity probe configurations were employed. These results support potential applications in implantable or wearable temperature sensors, energy harvesting devices, and smart biomedical interfaces. The thickness of the graphene coating was also characterized by SEM, which showed that the films deposited by PECVD are about 1 micron thick. Full article

The NerveRepack project is a European initiative that aims to develop biomimetic exoskeletons/exoprostheses for amputated or paralyzed leg patients that will receive and transmit signals to enable movements and sensations for the patient. To implement the project, it is fundamental to develop implantable neuronal electrodes that will allow bidirectional signaling between the sensors placed on the exoskeletons/exoprostheses and the nervous system. In this direction, two electrodes, plug and cuff, have been designed as integral parts of the final implantable device. The electrodes should comply with strict regulations to ensure their safe implantation in patients. The purpose of this study was to support the compliance of the implant platforms of certain key components with the ISO and ASTM standards that would be required for clinical applications. We have used an indirect method to assess the biocompatibility of the developed electrodes against neuronal cells, fibroblasts, and keratinocytes. Also, we assessed hemocompatibility, i.e., the potential of implantable electrodes to induce hemolysis or complement activation. Finally, the mutagenic/genotoxic potential was tested against the internationally recommended CHO cells. Both representative plug and cuff electrode components were found non-cytotoxic, non-mutagenic, and unable to induce hemolysis. Therefore, from the point of early evaluation of in vitro material and process biocompatibility, the selected implant platforms for the electrodes could be implanted in preclinical models to delineate their potential in vivo applications as neuronal interface with the biomimetic exoskeleton/exoprostheses. Full article

This paper proposes a unified energy management, fault detection, and fault-tolerant control (EMS–FDI–FTC) framework for Hybrid Hydrogen Electric Vehicles (HHEVs) integrating a fuel cell (FC), battery (Bat), and supercapacitor (SC). While such multi-source architectures enable high-efficiency propulsion under dynamic driving conditions, actuator and state faults such as FC voltage sag, Bat internal resistance increase, and SC capacitance degradation can compromise safety, availability, and component lifetime. The proposed framework converts real-world GPS-recorded vehicle speed profiles into route-aware traction power demand and combines interpretable model-based indicators with an AI-based fault detection and classification module. Based on the diagnosis outcome, a fault-tolerant supervisory strategy performs online power reallocation among the FC, Bat, and SC while enforcing operational constraints. Validation is conducted in a MATLAB-based software-in-the-loop (SIL) environment using three urban driving routes collected from on-road measurements in Tunisia with injected ground-truth faults. The results demonstrate reliable fault classification performance and effective service continuity during fault intervals, supplying over 94% of the demanded energy across all routes, with energy-not-served remaining below 0.02 kWh. In addition, processor-in-the-loop (PIL) implementation on an STM32F407VG controller confirms real-time feasibility with a 10 Hz supervisory sampling rate and execution time margins compatible with embedded automotive deployment. Overall, the proposed closed-loop framework provides a practical route-aware diagnosis-to-control solution for robust and fault-resilient HHEV operation under realistic driving variability. All energy and efficiency indicators reported in this study are derived from control-oriented component models and are intended for consistent comparative evaluation across routes and operating scenarios, rather than absolute representation of a specific commercial vehicle. Full article