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Global geological conditions are complex and variable, characterized by frequent plate movements, earthquakes, and volcanic eruptions. Coupled with significant climate differences, various factors interact to trigger frequent landslide disasters, resulting in substantial losses of life and property. Therefore, landslide monitoring is crucial. Traditional monitoring technologies face limitations when dealing with complex terrains and meeting the demands for high timeliness, while unmanned aerial vehicles (UAVs), with their maneuverability, high resolution, and ability to operate in hazardous environments, have been widely applied in landslide monitoring. This paper provides a comprehensive review of UAV-based 3D reconstruction for landslides, detailing the characteristics and application cases of UAVs, explaining the functions and limitations of sensors such as optical sensors and light detection and ranging (LiDAR), and exploring 3D reconstruction methods based on UAV imagery, LiDAR, and hybrid approaches. It analyzes the applications of UAV 3D reconstruction in landslide emergency investigation, monitoring, and disaster assessment. The paper identifies the technical challenges faced in these applications and proposes corresponding solutions. In addition, UAV-based 3D reconstruction technology—with its centimeter-level spatial resolution—enables the precise delineation of landslide extent and hazard potential, thereby enhancing monitoring accuracy and improving the efficiency of emergency investigations. This technology provides strong technical support for landslide research and prevention, with significant implications for reducing landslide disaster losses. Full article

In the era of artificial intelligence, neuromorphic devices that simulate brain functions have received increasingly widespread attention. In this paper, an artificial neural synapse device based on ZnAlSnO thin-film transistors was fabricated, and its electrical properties were tested: the current-switching ratio was 1.18 × 10⁷, the subthreshold oscillation was 1.48 V/decade, the mobility was 2.51 cm²V⁻¹s⁻¹, and the threshold voltage was −9.40 V. Stimulating artificial synaptic devices with optical signals has the advantages of fast response speed and good anti-interference ability. The basic biological synaptic characteristics of the devices were tested under 365 nm light stimulation, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term plasticity (STP), and long-term plasticity (LTP). This device shows good synaptic plasticity. In addition, by changing the gate voltage, the excitatory postsynaptic current of the device at different gate voltages was tested, two different logical operations of “AND” and “OR” were achieved, and the influence of different synaptic states on memory was simulated. This work verifies the application potential of the device in the integrated memory and computing architecture, which is of great significance for promoting the high-quality development of neuromorphic computing hardware. Full article

Multi-core fiber (MCF) has drawn increasing attention for its potential application in distributed acoustic sensing (DAS) due to the compact optical structure of integrating several fiber cores in the same cladding, which indicates an intrinsic space-division-multiplexed (SDM) capability in a single piece of fiber. In this paper, a dual-channel DAS integrated with MCF is presented, of which the equivalent self-noise characteristic is analyzed. The equivalent self-noise of the system can be effectively suppressed by signal superposition with the phase matching method. Considering that the noise correlation among the cores is not zero, the signal-to-noise (SNR) gain after signal superposition is less than the theoretical value. The dual-channel DAS system is set up by a piece of 2 km long seven-core MCF, in which the dual-sensing channels are constructed by a four-core series and three-core series, respectively. The total noise correlation coefficient of the seven cores is 11.28, while the equivalent self-noise of the system can be suppressed by 6.32 dB with signal superposition. An equivalent self-noise suppression method based on a linear delay phase matching scheme is proposed for noise decorrelation in the DAS MCF system. After noise decorrelation, the suppression of the equivalent self-noise of the system can reach the theoretical value of 8.45 dB with a time delay of 1 ms, indicating a noise correlation among the seven cores of almost zero. The feasibility of the equivalent self-noise suppression method for the DAS system is verified for both single-frequency and broadband signals, which is of great significance for the detection of weak vibration signals based on a DAS system. Full article

Optical scattering techniques often lead to simplified assumptions about secondary factors, such as neglecting the absorption effect of particles or the residual particle size micro-distribution after homogenization; these are made to enhance measurement efficiency. However, such simplifications can introduce systematic errors in precise detection. This study uses the scattering–transmission ratio composition determination method as an example, revises the basic scattering–transmission ratio model to incorporate absorption effects, and demonstrates the coefficient calculation process. Furthermore, Mie key coefficients, including the particle size micro-distribution—which are core parameters of this method—are derived. Based on these models, effective particles from image processing are analyzed to assess the impact of these two factors. The results demonstrate the joint influence of the micro-distribution and absorption characteristics of milk fat particles on Mie key coefficients and composition determination, exhibiting non-uniform enhancement and reduction effects. Specifically, at a wavelength of 800 nm, the scattering–transmission ratio of the modified model increases by a factor of 1.56 compared to the traditional model at a volume concentration of 0.5%, while at 3.3% concentration, the scattering–transmission ratio of the modified model is approximately one-third of the traditional model. These findings provide a theoretical basis for developing dairy product quality assessment technologies. Full article

This study aimed to evaluate how acidic and alkaline staining solutions affect the optical properties (mean color change, ΔE*), geometric characteristics (surface roughness, Ra), and bacterial adhesion of zirconia Ceramill Zolid PS computer-aided design/computer-aided manufacture (CAD/CAM) material after 21 days of immersion. Ninety-six zirconia CAD/CAM Ceramill Zolid multilayer PS specimens were prepared and allocated to eight groups based on the pH values of the immersion solutions; the acidic solutions included Mirinda Citrus, CodeRed, yerba mate tea, Saudi coffee, and Nescafe (A–E), and the alkaline solutions included artificial saliva, DZRT (tobacco-free nicotine pouches), and smokeless tobacco (F–H). The specimens were immersed for 21 days at 37 °C, with the solutions replaced every 12 h to ensure consistency. Color changes were measured using a VITA Easyshade V spectrophotometer, and Ra was evaluated via white-light interferometric microscopy. The bacterial adhesion of Streptococcus mutans was quantified by counting colony-forming units (CFUs, CFU/mm²). Statistical analyses included the Shapiro–Wilk test for normality, one-way ANOVA with Tukey’s HSD post hoc test for group comparisons, and paired t-tests, with significance set at <0.05. The recorded pH values of the staining materials ranged from acidic (Mirinda Citrus: 3.23) to alkaline (smokeless tobacco: 8.54). Smokeless tobacco caused the most unacceptable mean color change (ΔE* = 6.84), followed by DZRT (ΔE* = 6.46), whereas artificial saliva produced the least discoloration (ΔE* = 2.15), with statistically significant differences among the solutions (p < 0.001). The Ra measurements varied significantly (p < 0.001), with Nescafe demonstrating the lowest value (0.486 µm) and DZRT the highest (0.748 µm). S. mutans adhesion was the highest for CodeRed (546.75 CFU) and the lowest for smokeless tobacco (283.92 CFU), demonstrating significant variation across groups (ANOVA, p < 0.001). The acidic and alkaline solutions significantly altered the optical properties, Ra, and bacterial adhesion of zirconia Ceramill Zolid PS CAD/CAM, with acidic solutions leading to higher bacterial adhesion. Full article

Background/Objectives: Age-related macular degeneration (AMD) is the leading cause of visual impairment among the elderly. Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality that enables detailed visualisation of retinal vascular layers. However, clinical assessment of OCTA images is often challenging due to high data volume, pattern variability, and subtle abnormalities. This study aimed to develop automated algorithms to detect and quantify AMD in OCTA images, thereby reducing ophthalmologists’ workload and enhancing diagnostic accuracy. Methods: Two texture-based algorithms were developed to classify OCTA images without relying on segmentation. The first algorithm used whole local texture features, while the second applied principal component analysis ($PCA$) to decorrelate and reduce texture features. Local texture descriptors, including rotation-invariant uniform local binary patterns ($LB{P}^{2riu}$), local binary patterns ($LBP$), and binary robust independent elementary features ($BRIEF$), were combined with machine learning classifiers such as support vector machine (SVM) and K-nearest neighbour (KNN). OCTA datasets from Manchester Royal Eye Hospital and Moorfields Eye Hospital, covering healthy, dry AMD, and wet AMD eyes, were used for evaluation. Results: The first algorithm achieved a mean area under the receiver operating characteristic curve (AUC) of $1.00\pm 0.00$ for distinguishing healthy eyes from wet AMD. The second algorithm showed superior performance in differentiating dry AMD from wet AMD (AUC $0.85\pm 0.02$). Conclusions: The proposed algorithms demonstrate strong potential for rapid and accurate AMD diagnosis in OCTA workflows. By reducing manual image evaluation and associated variability, they may support improved clinical decision-making and patient care. Full article

This paper investigates the effects of Ti and Nb addition with varying Mn content on the solidification macrostructure and microstructure in the continuous casting slab of Q355 steel using optical microscopy, scanning electron microscopy, transmission electron microscopy, and electron probe microanalysis. The evolution of central segregation and MnS inclusions during thermal simulation compress deformation has been clearly established using Gleeble-1500 thermal simulation tester. The results indicate that by reducing the Mn content and adding a small amount of Ti and Nb, it is possible to refine the grain and mitigate the center segregation of Q355 steel. Mn steel with 1.25% Mn and without Ti and Nb addition exhibits the most severe center segregation. The TiNb steel with 0.52% Mn and a small amount of Ti and Nb addition showed a marked improvement in the center segregation of the slab. The Nb steel with 0.56% Mn and 0.009% Nb shows the presence of thin film ferrite along prior grain boundaries surrounded by Widmanstätten ferrite, and the central segregation has not shown significant improvement. The thermal simulation samples of the three steel types inherit the characteristics of their respective casting structures. Full article

The search for more sustainable alternatives to traditional organic solvents, in the frame of the green chemistry approach, is leading to an increasing interest toward the exploration of deep eutectic solvents (DESs), especially natural-based ones (NADESs). The great ferment in the use of DESs as innovative media for many applications and in the research of novel types of DESs is not matched by an equal rigor in their characterization and in the study of their physico-chemical characteristics. Nevertheless, it is evident how comparative studies encompassing the investigation of a wide range of properties in relationship with the DESs structures would be beneficial for a rational development of the field. In this work a panel of DESs featuring choline acetate, L-carnitine and L-proline as hydrogen bond acceptor constituents (HBAs) and ethylene glycol, glycerol and levulinic acid as hydrogen bond donor constituents (HBDs) in 1:2 and 1:3 molar ratios have been prepared and characterized. Their density, viscosity and optical properties have been thoroughly investigated at various temperatures, analyzing the influence of their composition in terms of type of HBA, type of HBD and molar ratio on their properties. All the proposed DESs have also been thermally characterized by TGA and DSC, providing a description of their thermal behavior in a wide range of temperature and determining their thermal stability and thermal degradation profile. Full article

Narrow-linewidth broadband tunable external cavity diode lasers (NBTECDLs), with their broadband tuning range, narrow linewidth, high side-mode suppression ratio (SMSR), and high output power, have become important laser sources in many fields such as optical communication, spectral analysis, wavelength division multiplexing systems, coherent detection, and ultra-high-speed optical interconnection. This paper briefly describes the basic theory of NBTECDLs, introduces NBTECDLs with diffraction grating type, fiber Bragg grating (FBG) type, and waveguide type, and conducts an in-depth analysis on the working principles and performance characteristics of NBTECDLs based on different NBTECDL types. Then, it reviews the latest research progress on Littrow-type, Littman-type, FBG-type, and waveguide-type NBTECDLs in detail and compares and summarizes the characteristics of Littrow-type NBTECDLs, Littman-type NBTECDLs, FBG-type NBTECDLs, and waveguide-type NBTECDLs. Finally, it looks at the structural features, key technologies, optical performance, and application fields of the most cutting-edge research in recent years and summarizes the challenges and future development directions of NBTECDLs. Full article

A liquid-sealed single-mode–no-core–single-mode (SNS) structure fiber temperature sensor based on polyvinyl alcohol (PVA) partial replacement coating is proposed. Using a liquid-sealed glass capillary structure, the PVA solution is introduced into the SNS structure and avoids its influence by environmental humidity. Temperature can be obtained by measuring the shift of the multimode interference spectrum, which is affected by the thermal optical effect of the PVA solution. Through theoretical simulation of the sensor, the optimal NCF fiber length and coating stripped length are obtained by comprehensively considering the transmitted loss and output spectrum signal-to-noise ratio (SNR). The optimal PVA solution concentration is selected by measuring the thermo-optic coefficient (TOC) and refractive index (RI). Based on the theoretical optimization results, a PVA solution-coated SNS fiber optic temperature sensor is experimentally fabricated, and temperature-sensing characteristics are measured within −3.6 to 73.2 °C. The experimental results show that the sensor has a high sensitivity (nm/°C, maximum is 21.713 nm/°C) and has a resolution of 10⁻³ °C. ${\lambda }_{dip}$ has a stable negative linear relationship with temperature, and the correlation coefficient of the fitting curve exceeds 95%. The temperature cycling experiment and long-term stability test show that the temperature sensor has good repeatability and stability. The experimental results also show the nonlinear relationship between the temperature measurement range and sensitivity, clarify the important factors affecting the response performance of fiber temperature sensors, and provide important reference values for optical fiber temperature sensors. Full article

This study aimed to develop a novel biomaterial for neural tissue regeneration by combining chitosan (CS), a natural polymer, with graphene oxide (GO) at concentrations of 3%, 6%, and 9%. The homogeneity, conductivity, three-dimensional characteristics, and ability to support cell viability of the composite materials were systematically evaluated. Fourier-Transform Infrared (FTIR) spectroscopy confirmed the successful incorporation of GO into the CS matrix, while UV-Vis and photoluminescence (PL) spectrometry revealed modifications in the optical properties with increasing GO content. Thermogravimetric analysis (TG-DSC) demonstrated improved thermal stability of the composites, and swelling tests indicated enhanced water absorption capacity. Although some agglomerates were observed, the homogeneity was reasonable at both macroscopic and microscopic level (optical visualization–FTIR and electron microscopy). The composite films exhibited promising physical and electrochemical properties, highlighting their potential for neural tissue engineering applications. Their biological activity was assessed by culturing neuronal cells on the CS-GO scaffolds. Results from MTT, LDH, and LIVE/DEAD assays demonstrated excellent cell viability, moderate-to-good cell attachment, and the promotion of intercellular network formation. Among the tested formulations, the CS-GO 6% scaffold showed the most favorable biological response, with a significant increase in SH-SY5Y cell viability after 7 days (p < 0.05) compared to the CS control. LIVE/DEAD imaging confirmed enhanced cell attachment and elongated morphology, while the LDH assay indicated minimal cytotoxicity. Notably, a critical threshold was identified between 6% and 9% GO, where conductivity increased by approximately 52-fold. Future studies should focus on optimizing the composite parameters, loading them with specific biologically active agents and thus targeting specific neuronal applications. Full article

Distributed Acoustic Sensing (DAS) is an emerging technology in the maritime domain, enabling the use of existing fiber optic cables to detect acoustic signals in the marine environment. In this study, we present an automated signal detection and classification framework for DAS data that supports near-real-time processing. Using data from the SHEFA-2 cable between the Faroe and Shetland Islands, we develop a method to identify acoustic signals and generate both labeled and unlabeled datasets based on their spectral characteristics. Principal component analysis (PCA) is used to explore separability in the labeled data, and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) is applied to classify unlabeled data. Experimental validation using clustering metrics shows that with the full dataset, we can achieve a Davies–Bouldin Index of 0.828, a Silhouette Score of 0.124, and a Calinski–Harabasz Index of 189.8. The clustering quality degrades significantly when more than 20% of the labeled data is excluded, highlighting the importance of maintaining sufficient labeled samples for robust classification. Our results demonstrate the potential to distinguish between signal sources such as ships, vehicles, earthquakes, and possible cable damage, offering valuable insights for maritime monitoring and security. Full article

This manuscript continues a series of papers devoted to the study of bio-optical characteristics of the Volga River waters in the context of development of regional bio-optical models. A particularly weak point in this effort is the limited knowledge of dissolved organic matter (DOM): its component composition, spectral absorption characteristics, and the lack of satellite-based assessment algorithms. Using excitation–emission matrix fluorescence spectroscopy, we examined the fluorescent fraction of DOM of surface water layer of the Volga River and its tributaries in the area from the Gorky Reservoir to the Volgograd Reservoir, a stretch spanning over 1500 km, in the period from May to September 2022–2024. Four fluorescent components were validated in parallel factor analysis. The ratio of fluorescent components was mostly stable, while their fluorescence intensities varied a lot. For example, the fluorescence intensity of the DOM of the Gorky Reservoir and the Kama River differed by more than 2.5-fold. The highest FDOM fluorescence was found in the Gorky Reservoir. Downstream, it decreased due to the inflow of the Oka and Kama rivers. The influence of small rivers such as Kerzhenets, Sundovik, Sura, and Vetluga was insignificant. It is demonstrated that neither conventional remote sensing techniques (LiDAR) plus in situ measurements of DOM with a probe nor DOM absorption at 440 nm allows probing all the fluorescent components, so their efficiency is determined by the correlation of fluorophore group content. Full article

Optical frequency domain reflectometry (OFDR) is one of the key diagnostic tools for fiber optic components and circuits built on them. A low signal-to-noise ratio, resulting from the low intensity of backscattered signals, prevents the correct quantitative description of the medium parameters. Known methods of signal denoising, such as empirical mode decomposition, frequency filtering, and activation function dynamic averaging, make the signal smoother but introduce errors into its dynamic characteristics, changing the intensity of reflection peaks and distorting the backscattering level. We propose a method to reduce OFDR trace noise using elliptical arc fitting (EAF). The obtained results indicate that this algorithm efficiently processes both areas with and without contrasting back reflections, with zero distortion of Fresnel reflection peaks, and with zero attenuation error in regions without Fresnel reflections. At the same time, other methods distort reflection peaks by 14.2–42.6% and shift the correct level of Rayleigh scattering by 27.2–67.3%. Further work will be aimed at increasing the accuracy of the method and testing it with other types of data. Full article

Highly efficient shielding materials, transparent in the visible and IR ranges are becoming important in practice. This stimulates the development of cheap methods for creating transparent conductors with low sheet resistance and high optical transparency. This work presents a complex approach based on preliminary modeling of the shielding characteristics of two-layer sandwich structures based on irregular aluminum mesh (IAM) formed by the cracked template method. Experimentally measured spectral dependences of the transmission coefficient of single-layer IAM are used as a reference point for modeling. According to the simulation results, two types of sandwich structures were designed using IAM, with varying filling factors and a fixed PMMA layer thickness of 4 mm. The experimentally measured shielding characteristics of the sandwich structures in the range of 0.01–7 GHz are in good agreement with the calculated data. The obtained structures demonstrate a shielding efficiency of 55.96 dB and 65.55 dB at a frequency of 3.5 GHz (the average range of 5G communications). At the same time, their optical transparency at a wavelength of 550 nm are 84.07% and 75.78%, respectively. Our sandwich structures show electromagnetic shielding performance and uniform diffraction pattern. It gives them an advantage over structures based on regular meshes. The obtained results highlight the prospect of the proposed comprehensive approach for obtaining highly efficient, low-cost optically transparent shielding structures. Such materials are needed for modern wireless communication systems and metrology applications. Full article