Search Results (57,383)

Background/Objectives: Toxic optic neuropathy (TON) represents a spectrum of optic nerve damage caused by exposure to toxins, including drugs, alcohol, and industrial chemicals. It is characterized by progressive vision loss, dyschromatopsia, and optic nerve pallor and poses a clinical challenge in diagnosis and management due to overlapping features with other optic neuropathies. Non-arteritic anterior ischemic optic neuropathy (NAION), although distinct, shares common pathophysiological mechanisms such as oxidative stress and mitochondrial dysfunction. This review aims to evaluate therapeutic strategies applied in TON and discuss the potential role of NAION-targeted treatments in TON management. Methods: We reviewed medical therapies previously used in NAION patients, including corticosteroids and neuroprotective substances, and analyzed their relevance in the context of TON. Particular focus was given to emerging interventions targeting oxidative stress and mitochondrial health, including experimental drugs. Results: Evidence indicates that early diagnosis and toxin removal are essential in preventing irreversible vision impairment in TON. Therapies for methanol-induced and drug-related ocular neuropathies have demonstrated inconsistent efficacy, especially when integrated with antioxidant and neuroprotective approaches. However, the search for potential synergy between detoxification protocols and NAION-targeted treatments offers a promising direction for comprehensive management strategies. Conclusions: While current therapeutic options remain controversial and often unsatisfactory, integrating detoxification with interventions aimed at oxidative stress and mitochondrial function may improve outcomes. Further research is needed to develop targeted therapies for TON and bridge gaps in clinical decision-making. Full article

Over the past two decades, the meat industry has faced increasing pressure to prevent foodborne outbreaks and reduce economic losses associated with delayed detection of spoilage. This demand has accelerated the development of on-site, real-time sensing tools capable of identifying early signs of contamination. Electrospun nanofiber (NF) platforms have emerged as particularly promising due to their large surface area, tunable porosity, and versatile chemistry, which make them ideal scaffolds for immobilizing enzymes, antibodies, or aptamers while preserving bioactivity under field conditions. These NFs have been integrated into optical, electrochemical, and resistive devices, each enhancing response time and sensitivity for key targets ranging from volatile organic compounds indicating early decay to specific bacterial markers and antibiotic residues. In practical applications, NF matrices enhance signal generation (SERS hotspots), facilitate analyte diffusion through three-dimensional networks, and stabilize delicate biorecognition elements for repeated use. This review summarizes major NF fabrication strategies, representative sensor designs for meat quality monitoring, and performance considerations relevant to industrial deployment, including reproducibility, shelf life, and regulatory compliance. The integration of such platforms with data networks and Internet of Things (IoT) nodes offers a path toward continuous, automated surveillance throughout processing and cold-chain logistics. By addressing current technical and regulatory challenges, NF-based biosensors have the potential to significantly reduce waste and safeguard public health through early detection of contamination before it escalates into costly recalls. Full article

Underwater object detection is critical for marine resource utilization, ecological monitoring, and maritime security, yet it remains constrained by optical degradation, high energy consumption, and vulnerability to adversarial perturbations. To address these challenges, this study proposes an Adaptive Vision Transformer (A-ViT)-based detection framework. At the hardware level, a systematic power-modeling and endurance-estimation scheme ensures feasibility across shallow- and deep-water missions. Through the super-resolution reconstruction based on the Hybrid Attention Transformer (HAT) and the staged enhancement with the Deep Initialization and Deep Inception and Channel-wise Attention Module (DICAM), the image quality was significantly improved. Specifically, the Peak Signal-to-Noise Ratio (PSNR) increased by 74.8%, and the Structural Similarity Index (SSIM) improved by 375.8%. Furthermore, the Underwater Image Quality Measure (UIQM) rose from 3.00 to 3.85, while the Underwater Color Image Quality Evaluation (UCIQE) increased from 0.550 to 0.673, demonstrating substantial enhancement in both visual fidelity and color consistency. Detection accuracy is further enhanced by an improved YOLOv11-Coordinate Attention–High-order Spatial Feature Pyramid Network (YOLOv11-CA_HSFPN), which attains a mean Average Precision at Intersection over Union 0.5 (mAP@0.5) of 56.2%, exceeding the baseline YOLOv11 by 1.5 percentage points while maintaining 10.5 ms latency. The proposed A-ViT + ROI reduces inference latency by 27.3% and memory usage by 74.6% when integrated with YOLOv11-CA_HSFPN and achieves up to 48.9% latency reduction and 80.0% VRAM savings in other detectors. An additional Image-stage Attack QuickCheck (IAQ) defense module reduces adversarial-attack-induced latency growth by 33–40%, effectively preventing computational overload. Full article

Bronze materials are indispensable across numerous industries for enhancing the durability and performance of components, primarily due to their excellent tribological properties, corrosion resistance, and machinability. This study investigates the impact of different atmospheric conditions on the properties of WAAM (wire arc additive manufacturing) cladded bronze coatings on 09G2S steel substrate. Specifically, the research examines how varying atmospheres—including ambient air (N₂/O₂, no shielding gas), pure argon (Ar), carbon dioxide (CO₂), and 82% Ar + 18% CO₂ (Ar/CO₂) mixture—influence coating defectiveness (porosity, cracks, non-uniformity), wettability (manifested as uniform layer formation and strong adhesion), and the extent of intergranular penetration (IGP), leading to the formation of characteristic infiltrated cracks or “bronze whiskers”. Modern investigative techniques such as optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) were employed for comprehensive material characterization. Microhardness testing was also carried out to evaluate and confirm the homogeneity of the coating structure. The findings revealed that the bronze coatings primarily consisted of a dominant, highly textured FCC α-Cu phase and a minor BCC α-Fe phase, with Rietveld refinement quantifying a α-Fe volume fraction of ~5%, lattice parameters of a = 0.3616 nm for α-Cu and a = 0.2869 nm for α-Fe, and a modest microstrain of 0.001. The bronze coating deposited under a pure Ar atmosphere exhibited superior performance, characterized by excellent wettability, a uniform, near-defect-free structure with minimal porosity and cracks, and significantly suppressed formation of bronze whiskers, both in quantity and size. Conversely, the coating deposited without a protective atmosphere demonstrated the highest degree of defectiveness, including agglomerated pores and cracks, leading to an uneven interface and extensive whisker growth of varied morphologies. Microhardness tests confirmed that while the Ar-atmosphere coating displayed the lowest hardness (~130 HV_0.1), it maintained consistent values across the entire analyzed area, indicating structural homogeneity. These results underscore the critical role of atmosphere selection in WAAM processing for achieving high-quality bronze coatings with enhanced interfacial integrity and functional performance. Full article

Accurate extrinsic calibration between optical sensors, such as camera and LiDAR, is crucial for multimodal perception. Traditional methods based on specific calibration targets exhibit poor robustness in complex optical environments such as glare, reflections, or low light, and they rely on cumbersome manual operations. To address this, we propose a fully unsupervised, end-to-end calibration framework. Our approach adopts a dual-Transformer architecture: a Vision Transformer extracts semantic features from the image stream, while a Point Transformer captures the geometric structure of the 3D LiDAR point cloud. These cross-modal representations are aligned and fused through a neural network, and a regression algorithm is used to obtain the 6-DoF extrinsic transformation matrix. A multi-constraint loss function is designed to enhance structural consistency between modalities, thereby improving calibration stability and accuracy. On the KITTI benchmark, our method achieves a mean rotation error of 0.21° and a translation error of 3.31 cm; on a self-collected dataset, it attains an average reprojection error of 1.52 pixels. These results demonstrate a generalizable and robust solution for optical-sensor extrinsic calibration, enabling precise and self-sufficient perception in real-world applications. Full article

This paper investigates the abnormal combustion behavior—specifically knock and pre-ignition—of a hydrogen direct-injection (H₂-DI) engine operated under stoichiometric conditions. Two different cylinder head configurations with central and lateral injector placement are analyzed using thermodynamic measurements, CFD simulations, and the optical diagnostic system VISIOLution^®. The results show that combustion stability and knock tendency are significantly influenced by injector positioning, injection pressure, and ignition timing. Controlled mixture formation and high turbulence during the compression phase are key to achieving both high power density and thermal efficiency in hydrogen-fueled engines. Full article

Additive manufacturing technologies are no longer limited to rapid prototyping but are increasingly used for low-volume production of functional end-use components. Among advanced AM techniques, HP Multi-Jet Fusion (MJF) stands out for its high precision and efficiency. Polyamides, thanks to their balanced mechanical and thermal properties, are commonly used as building materials in this technology. However, these materials are notoriously difficult to bond with conventional adhesives. This study investigates the shear strength of bonded joints made from two frequently used MJF materials—PA12 and glass-bead-filled PA12—using four different industrial adhesives. Experimental procedures were conducted according to ASTM standards. Specimens for single-lap-shear tests were fabricated on an HP MJF 4200 series printer, bonded using a custom jig, and tested on a Zwick-Roell Z250 electro-mechanical testing machine. Surface roughness of the adherends was measured with a 3D optical microscope to assess its influence on bonding performance. The polyurethane-based adhesive (3M Scotch-Weld DP620NS) demonstrated superior performance with maximum shear strengths of 5.0 ± 0.35 MPa for PA12 and 4.4 ± 0.03 MPa for PA12GB, representing 30% and 17% higher strength, respectively, compared to epoxy-based alternatives. The hybrid cyanoacrylate–epoxy adhesive (Loctite HY4090) was the only system showing improved performance with glass-bead-reinforced substrate (16.5% increase from PA12 to PA12GB). Statistical analysis confirmed significant differences between adhesive types (F_3,24 = 31.37, p < 0.001), with adhesive selection accounting for 65.7% of total performance variance. In addition to the experimental work, a finite element-based numerical simulation was performed to analyze the distribution of shear and peel stresses across the adhesive layer using Siemens Simcenter 3D 2406 software with the NX Nastran solver. The numerical results were compared with analytical predictions from the Volkersen and Goland–Reissner models. Full article

Metallogels, three-dimensional supramolecular networks formed through metal–ligand coordination, have emerged as a new generation of adaptive soft materials with promising biomedical potential. By integrating the structural stability and tuneable functionality of metal centres with the dynamic self-assembly of organic gelators, these systems exhibit exceptional mechanical strength, responsiveness, and multifunctionality. Recent studies demonstrate their diverse applications in drug delivery, anticancer therapy, antimicrobial and wound healing treatments, biosensing, bioimaging, and tissue engineering. Interestingly, the coordination of metal ions such as Ru(II), Zn(II), Fe(III), and lanthanides enables the creation of self-healing, thixotropic, and stimuli-responsive gels capable of controlled release and therapeutic action. Moreover, the incorporation of luminescent or redox-active metals adds optical and electronic properties suitable for diagnostic and monitoring purposes. This collection summarizes the most recent advances in the field, highlighting how rational molecular design and coordination chemistry contribute to the development of multifunctional, biocompatible, and responsive metallogels that bridge the gap between materials science and medicine. Full article

In free-space optical (FSO) communication systems, on–off keying (OOK) modulation is widely used due to its simplicity. However, systems applying OOK suffer from the BER floor in atmospheric turbulence channels, leading to persistently high BER even at high SNR. To mitigate this limitation in atmospheric turbulence channels, differential modulation and detection (DMD) can be adopted. An in-depth theoretical and experimental investigation of DMD in FSO systems is conducted in this paper, considering the effects of turbulence. A comprehensive derivation of the system performance for DMD under atmospheric turbulence channels is also provided, with the results of research revealing that DMD outperforms OOK in high-SNR regions. To validate the theoretical analysis, an experimental platform is set up to sample the fluctuation of light intensity. Furthermore, the system performance of DMD is analyzed under varying scintillation indices, modulation depths, and transmission rates in this paper. Based on the data acquired from experiments, the results corroborate the analytical findings, confirming the great advantages of DMD in turbulent environments. The insights provided in this study establish a foundation for practical FSO system design, enabling the development of simpler and more reliable communication systems. Full article

Integrating artificial intelligence (AI) with wearable sensor technologies can revolutionize the monitoring and management of various chronic diseases and acute conditions. AI-integrated wearables are categorized by their underlying sensing techniques, such as electrochemical, colorimetric, chemical, optical, and pressure/stain. AI algorithms enhance the efficacy of wearable sensors by offering personalized, continuous supervision and predictive analysis, assisting in time recognition, and optimizing therapeutic modalities. This manuscript explores the recent advances and developments in AI-powered wearable sensing technologies and their use in the management of chronic diseases, including COVID-19, Diabetes, and Cancer. AI-based wearables for heart rate and heart rate variability, oxygen saturation, respiratory rate, and temperature sensors are reviewed for their potential in managing COVID-19. For Diabetes management, AI-based wearables, including continuous glucose monitoring sensors, AI-driven insulin pumps, and closed-loop systems, are reviewed. The role of AI-based wearables in biomarker tracking and analysis, thermal imaging, and ultrasound device-based sensing for cancer management is reviewed. Ultimately, this report also highlights the current challenges and future directions for developing and deploying AI-integrated wearable sensors with accuracy, scalability, and integration into clinical practice for these critical health conditions. Full article

Unidirectional guided resonances (UGRs) in periodic metasurfaces have recently attracted research interest because of their ability to achieve unidirectional radiation in all-dielectric structures without metal reflectors, which offers new possibilities for efficient grating couplers and unidirectional lasers. Here, we propose a hybrid metasurface consisting of silicon and ${\mathrm{Ge}}_2{\mathrm{Sb}}_2{\mathrm{Te}}_5$ (GST) phase change material for controlled UGR generation in the mid-infrared region. Leveraging GST’s phase-change properties to modulate the optical response of the metasurface, we achieve tunable generation of the UGR, which is demonstrated to carry a topological charge of +1. Moreover, by adjusting the degree of GST phase transition, continuous tuning of the radiation asymmetry ratio from ${10}^4$ to 1 is achieved for a specific in-plane momentum and operating wavelength. These findings offer a promising avenue for dynamically controllable UGRs, with potential applications in tunable on-chip optical couplers and light sources. Full article

Clear aligners have gained popularity in orthodontics due to their aesthetics, comfort, and removability; however, their prolonged intraoral wear and frequent removal–reinsertion cycles create favorable conditions for microbial colonization. This in vitro study evaluated the efficacy of seven commercially available mouthwash formulations in inhibiting biofilms of Streptococcus mutans, Streptococcus oralis, and Candida albicans formed on four different clear aligner materials. Standardized aligner fragments were incubated for 24 h with microbial suspensions to allow biofilm formation, treated for 1 min with one of the mouthwashes, and then assessed for residual viability through spectrophotometric optical density measurements after a further 24 h incubation. Biofilm inhibition varied according to both mouthwash composition and aligner material. The chlorhexidine-based rinse (MW-D) consistently showed the highest inhibition across microorganisms, while the fluoride–cetylpyridinium chloride rinse (MW-B) performed strongly for S. oralis and C. albicans. An essential oil-based formulation with xylitol (MW-G) showed notable antifungal activity against C. albicans. Monolayer polyurethane aligners generally achieved higher inhibition rates than multilayer or copolyester-based materials. These findings indicate that antimicrobial efficacy on aligners depends on both mouthwash type and material, supporting a tailored approach to biofilm management in clear aligner therapy to reduce the risk of caries, periodontal disease, and candidiasis. Full article

In this study, we fabricated Fe-25Ni-15Cr alloy rods via vacuum induction melting, electroslag remelting, forging, hot rolling, and annealing. We systemically investigated the influence of varying cold-drawing deformation levels (10–60%) on microstructure evolution and mechanical properties, which were characterized by a variety of multi-scale characterization techniques, including optical microscopy, scanning electron microscopy, X-ray diffraction, and transmission electron microscopy. The results show that when the cumulative deformation amount is less than 30%, the hardness, tensile strength, and yield strength increase significantly with the increase in deformation amount, while the elongation continues to decline; when the cumulative deformation amount exceeds 30%, the rates of increase in hardness and strength decrease significantly; and when the deformation amount increases to 50%, dislocation density accumulates preferentially at the grain boundaries and forms a cellular substructure, while the texture orientation gradually stabilizes from random distribution to the <111> direction. This alloy rod exhibits three strengthening mechanisms during cold drawing: grain refinement, second-phase precipitation, and work hardening. A predictive model for tensile strength is derived through theoretical calculations. This work has guiding significance for establishing a cold-drawing process window without intermediate annealing. Full article

The silicon photonic optical phased array (OPA) has attracted enormous interest in free-space optical communication (FSO) owing to its high integration and agile beam steering. However, existing studies have only used its ability for fast beam switching to achieve point-to-multipoint communication, which results in link disconnection and time waste during the switching process. To address this problem, we make full use of the light field manipulation capabilities of Si-OPA to generate beams with multiple main lobes pointing to different targets at the same time, and combine code division multiple access (CDMA) to achieve uninterrupted point-to-multipoint communication. Through detailed data analysis, it is experimentally demonstrated that the proposed method has improved the communication efficiency by 24.576% compared with the previous beam-switching solution. This method provides a new application idea for Si-OPA in FSO communication. Full article

This study introduces a physics-based inverse rendering method for determining the reduced scattering and absorption coefficients of turbid materials with arbitrary shapes, using a single image as input. The approach enables fully spectrally-resolved reconstruction of the wavelength-dependent behaviour of the optical properties while also circumventing the specialised sample preparation required by established measurement techniques. Our approach employs a numerical solution of the Radiative Transfer Equation based on an inverse Monte Carlo framework, utilising an improved Levenberg–Marquardt algorithm. By rendering the edge effects accurately, particularly translucency, it becomes possible to differentiate between scattering and absorption from just one image. Importantly, the errors induced by only approximate prior knowledge of the phase function and refractive index of the material were quantified. The method was validated through theoretical studies on three materials spanning a range of optical parameters, initially using a simple cube geometry and later extended to more complex shapes. Evaluated via the CIE $\Delta E_{2000}$ colour difference, forward renderings based on the recovered properties were indistinguishable from those preset, which were obtained from integrating sphere measurements on real materials. The recovered optical properties showed less than 4% difference relative to these measurements. This work demonstrates a versatile approach for optical material characterisation, with significant potential for digital twin creation and soft-proofing in manufacturing. Full article