Search Results (4,028)

Solar energy plays a crucial role in mitigating greenhouse gas emissions in the context of global climate change. However, its deployment for green electricity generation can significantly influence regional climate and vegetation dynamics. While prior studies have examined the impacts of solar power plants on vegetation, the accuracy of these assessments has often been constrained by the availability of publicly accessible multispectral, high-resolution remotely sensed imagery. Given the abundant solar energy resources and the ecological significance of the Tibetan Plateau, a thorough evaluation of the vegetation effects associated with solar power installations is warranted. In this study, we utilize sub-meter resolution imagery from the GF-2 satellite to reconstruct the fractional vegetation cover (FVC) at the Gonghe solar thermal power plant through image classification, in situ sampling, and sliding window techniques. We then quantify the plant’s impact on FVC by comparing data from the pre-installation and post-installation periods. Our findings indicate that the Gonghe solar thermal power plant is associated with a 0.02 increase in FVC compared to a surrounding control region (p < 0.05), representing a 12.5% increase relative to the pre-installation period. Notably, the enhancement in FVC is more pronounced in the outer ring areas than near the central tower. The observed enhancement in vegetation growth at the Gonghe plant suggests potential ecological and carbon storage benefits resulting from solar power plant establishment on the Tibetan Plateau. These findings underscore the necessity of evaluating the climate and ecological impacts of renewable energy facilities during the planning and design phases to ensure a harmonious balance between clean energy development and local ecological integrity. Full article

In a sealed electromagnetic relay, the change in the surface roughness mainly depends on the collision wear between the contact and the moving reed and the ablation effect of the arc on the contact surface based on the strong correlation between the contact resistance and the surface roughness of the Ag-Mg-Ni contact. With a change in contact resistance, the contact temperature increase in a hermetically sealed electromagnetic relay (HSER) is greatly affected. Under extreme overload conditions, the contact surface is severely ablated by the arc, and the roughness increases rapidly with the number of cycles, which greatly affects the contact resistance of the contact surface and the reliability of the relay. A thermal model of a relay contact system based on the surface roughness of Ag-Mg-Ni contacts was established in this paper by analyzing the effect of an arc on the surface roughness of Ag-Mg-Ni contacts under heavy overload conditions. The arc image of the Ag-Mg-Ni contact was recorded using a double-axis arc photographing platform, and the moving track of the arc center under overload conditions was drawn. This paper explored the patterns of arc center movement on the contact surface and the effects of the arc on the surface roughness of the contacts by analyzing the probabilities of the arc center appearing in various locations. A mathematical model correlating the number of contact cycles with contact resistance was established. Subsequently, a finite element simulation model for the equivalent heat source of the contact was developed. The theoretical model error was less than 10%. The accuracy of the equivalent heat source model was verified by comparing the measured data with the simulation results. Full article

Urban tree canopy (UTC) coverage, or area, is an important metric for monitoring changes in UTC over large areas within a municipality. Several methods have been used to obtain these data, but remote sensing image classification is one of the fastest and most reliable over large areas. However, most studies have tested only one or two classification methods to accomplish this while using costly satellite imagery or LiDAR data. This study seeks to compare three urban tree canopy cover classifiers by testing a deep learning U-Net convolutional neural network (CNN), support vector machine learning classifier (SVM) and a random forests machine learning classifier (RF) on cost-free 2012 aerial imagery over a small southern USA city and midsize, growing southern USA city. The results of the experiment are then used to decide the best classifier and apply it to more recent aerial imagery to determine canopy changes over a 10-year period. The changes are subsequently compared visually and statistically with recent urban heat maps derived from thermal Landsat 9 satellite data to compare the means of temperatures within areas of UTC loss and no change. The U-Net CNN classifier proved to provide the best overall accuracy for both cities (89.8% and 91.4%), while also requiring the most training and classification time. When compared spatially with city heat maps, city periphery regions were most impacted by substantial changes in UTC area as cities grow and the outer regions get warmer. Furthermore, areas of UTC loss had higher temperatures than those areas with no canopy change. The broader impacts of this study reach the urban forestry managers at the local, state/province, and national levels as they seek to provide data-driven decisions for policy makers. Full article

In recent years, ablation of the buffer layer in high-voltage cables has become a prevalent issue compromising the reliability of power transmission systems. Given the internal location of these faults, direct monitoring and assessment are challenging, resulting in numerous undetected ablation hazards. Previous practice has demonstrated that detecting buffer layer ablation through surface temperature distribution changes is feasible, offering a convenient, efficient, and non-destructive approach. However, the variability in heat generation and the subtle temperature differences in thermal infrared images, compounded by noise interference, can impair the accuracy and timeliness of fault detection. To overcome these challenges, this paper introduces an adaptive enhancement method for the thermal infrared imaging of high-voltage cable buffer layer ablation. The method involves an Average Gradient Weighted Guided Filtering (AGWGF) technique to decompose the image into background and detail layers, preventing noise amplification during enhancement. The background layer, containing the primary information, is enhanced using an improved Contrast Limited Adaptive Histogram Equalization (CLAHE) to accentuate temperature differences. The detail layer, rich in high-frequency content, undergoes improved Adaptive Bilateral Filtering (ABF) for noise reduction. The enhanced background and detail layers are then fused and stretched to produce the final enhanced thermal image. To vividly depict temperature variations in the buffer layer, pseudo-color processing is applied to generate color-infrared thermal images. The results indicate that the proposed method’s enhanced images and pseudo-colored infrared thermal images provide a clearer and more intuitive representation of temperature differences compared to the original images, with an average increase of 2.17 in information entropy and 8.38 in average gradient. This enhancement facilitates the detection and assessment of buffer layer ablation faults, enabling the prompt identification of faults. Full article

Egg freshness is a critical factor that influences the egg’s nutritional value, safety, and overall quality; consequently, it is a priority for both producers and consumers. This review examines the factors that affect egg freshness, and it evaluates both traditional and modern methods for assessing egg freshness. Traditional techniques, such as the Haugh unit test and candling, have long been utilized; however, they have limitations, which are primarily due to their destructive nature. The review also highlights advanced non-destructive methods, including Vis-NIR spectroscopy, ultrasonic testing, machine vision, thermal imaging, hyperspectral imaging, Raman spectroscopy, and NMR/MRI technologies. These techniques offer rapid and accurate assessments while preserving the integrity of the eggs. Despite the current challenges related to calibration and implementation, integrating artificial intelligence (AI) and machine learning with these innovative technologies presents a promising avenue for the improvement of freshness evaluation. This development could revolutionize quality control processes in the egg industry, ensuring consistently high-quality eggs for consumers. Full article

This study presents the development and characterization of medium-chain fatty acid (MCFA)-loaded bigels, using coconut oil as the MCFA source. The bigels exhibited high oil binding capacity, ranging from 87% to 98%, effectively retaining MCFAs within the matrix, with lauric acid (C12) being the main component detected within the bigels at 178.32 ± 0.10 mg/g. Physicochemical analysis, including FTIR and scanning electron microscopy, confirmed stable fatty acid incorporation and a cohesive, smooth structure. The FTIR spectra displayed O-H and C=O stretching vibrations, indicating hydrogen bonding within the matrix, while the SEM images showed uniform lipid droplet distribution with stable phase separation. Thermal stability tests showed that the bigels were stable for 5 days at 50 °C, with oil retention and structural integrity unchanged. Rheological testing indicated a solid-like behavior, with a high elastic modulus (G′) that consistently exceeded the viscous modulus (G″), which is indicative of a strong internal structure. In simulated gastrointestinal digestion, the bigels achieved significantly higher MCFA retention than the pure oil, particularly in the gastric phase, with recovery percentages of 38.1% for the bigels and 1.7% for the oil (p < 0.05), suggesting enhanced bioavailability. Cell-based cytotoxicity assays showed low cytotoxicity, and permeability testing in a co-culture Caco-2/HT29-MTX model revealed a controlled, gradual MCFA release, with approximately 10% reaching the basolateral side over 6 h. These findings highlight MCFA-loaded bigels as a promising platform for nutraceutical applications; they provided stability, safety, and controlled MCFA release, with significant potential for functional foods aimed at enhancing fatty acid bioavailability. Full article

This paper describes experiments on finned tube heat exchangers, focusing on reducing the thermal contact resistance at the contact between the pipe and the lamella. Various contact materials, such as solders and adhesives, were investigated. Several methods of establishing contact were tested, including blowtorch soldering, brazing, and furnace soldering. Thermal camera measurements were carried out to assess the performance of the contact materials. Moreover, finite element analysis was performed to evaluate the contact materials and establish guidelines in the fin–tube connection modeling by comparing simplified models with the realistic model. Blowtorch brazing tests were successful while soldering attempts failed. During the thermographic measurements, reflective surfaces could be measured after applying a thin layer of paint with high emissivity. These measurements did not provide valuable results; thus, the contact materials were assessed using a finite element analysis. The results from the finite element analysis showed that all the inspected contact materials provided better heat transfer than not using a contact material. The heat transfer rate of the tight-fit realistic model was found to be 33.65 for air and 34.9 for the Zn-22Al contact material. This finding could be utilized in developing heat exchangers with higher heat transfer with the same size. Full article

The microstructure of aluminum thin films, including the grain morphology and surface roughness, are key parameters for improving the thermal or electrical properties and optical reflectance of films. The first step in optimizing these parameters is a thorough understanding of the grain growth mechanisms and film structure. To investigate these issues, thin aluminum films with thicknesses ranging from 25 to 280 nm were coated on SiO_x/Si substrates at ambient temperature under high-vacuum conditions and a low argon pressure of 3 × 10⁻³ mbar (0.3 Pa) using the radio frequency magnetron sputtering method. Quantitative analyses of the surface roughness and nanograin characteristics were conducted using atomic force microscopy (AFM), transmission electron microscopy (TEM), and X-ray diffraction. Changes in specular reflectance were measured using ultraviolet–visible and near-infrared spectroscopy. The low roughness values obtained from the AFM images resulted in high film reflectivity, even for thicker films. TEM and AFM results indicate monomodal, randomly oriented grain growth without a distinct columnar or spherical morphology. Using TEM cross-sectional images and the dependence of the grain size on the film thickness, we propose a grain growth mechanism based on the diffusion mobility of aluminum atoms through grain boundaries. Full article

Androgenetic alopecia (AGA) is caused by the impact of dihydrotestosterone (DHT) on hair follicles, leading to progressive hair loss in men and women. In this study, we developed caffeine-loaded hollow mesoporous silica nanoparticles coated with ultradeformable liposomes (ULp-Caf@HMSNs) to enhance caffeine delivery to hair follicles. Caffeine, known to inhibit DHT formation, faces challenges in skin penetration due to its hydrophilic nature. We investigated caffeine encapsulated in liposomes, hollow mesoporous silica nanoparticles (HMSNs), and ultradeformable liposome-coated HMSNs to optimize drug delivery and release. For ultradeformable liposomes (ULs), the amount of polysorbate 20 and polysorbate 80 was varied. TEM images confirmed the mesoporous shell and hollow core structure of HMSNs, with a shell thickness of 25–35 nm and a hollow space of 80–100 nm. SEM and TEM analysis showed particle sizes ranging from 140–160 nm. Thermal stability tests showed that HMSNs coated with ULs exhibited a Td₁₀ value of 325 °C and 70% residue ash, indicating good thermal stability. Caffeine release experiments indicated that the highest release occurred in caffeine-loaded HMSNs without a liposome coating. In contrast, systems incorporating ULp-Caf@HMSNs exhibited slower release rates, attributable to the dual encapsulation mechanism. Confocal laser scanning microscopy revealed that ULs-coated particles penetrated deeper into the skin than non-liposome particles. MTT assays confirmed the non-cytotoxicity of all HMSN concentrations to human follicle dermal papilla cells (HFDPCs). ULp-Caf@HMSNs promoted better cell viability than pure caffeine or caffeine-loaded HMSNs, highlighting enhanced biocompatibility without increased toxicity. Additionally, ULp-Caf@HMSNs effectively reduced ROS levels in DHT-damaged HFDPCs, suggesting they are promising alternatives to minoxidil for promoting hair follicle growth and reducing hair loss without increasing oxidative stress. This system shows promise for treating AGA. Full article

Carbon fiber-reinforced polymer (CFRP), noted for its outstanding properties including high specific strength and superior fatigue resistance, is increasingly employed in aerospace and other demanding applications. This study investigates the interactions between CFRP composites and high-energy lasers (HEL), with continuous wave laser powers reaching up to 120 kW. A novel automated sample exchange system, operated by a robotic arm, minimizes human exposure while enabling a sequence of targeted laser tests. High-speed imaging captures the rapid expansion of a plume consisting of hot gases and dust particles during the experiment. The research significantly advances empirical models by systematically examining the relationship between laser power, perforation times, and ablation rates. It demonstrates scalable predictions for the effects of high-energy laser radiation. A detailed examination of the damaged samples, both visually and via micro-focused computed X-ray tomography, offers insights into heat distribution and ablation dynamics, highlighting the anisotropic thermal properties of CFRP. Compression after impact (CAI) tests further assess the residual strength of the irradiated samples, enhancing the understanding of CFRP’s structural integrity post-irradiation. Collectively, these tests improve the knowledge of the thermal and mechanical behavior of CFRP under extreme irradiation conditions. The findings not only contribute to predictive modeling of CFRP’s response to laser irradiation but enhance the scalability of these models to higher laser powers, providing robust tools for predicting material behavior in high-performance settings. Full article

The phosphors with persistent luminescence in the NIR (near-infrared) region and the NIR-to-NIR Stokes luminescence properties have received considerable attention owing to their inclusive application prospects in the in vivo imaging field. In this paper, Nd³⁺ doped SrSnO₃ phosphors with remarkable NIR emission performance were prepared using a high temperature solid state reaction method; the phase structure, morphology, and luminescence properties were discussed systematically. The SrSnO₃ host exhibits broadband NIR emission (800–1300 nm) with absorptions in the near ultraviolet region. Nd³⁺ ions emerge excellent NIR-to-NIR Stokes luminescence under 808 nm laser excitation, with maximum emission at around ~1068 nm. The concentration-dependent luminescence properties, temperature dependent emission, and the luminescence decay curves of Nd³⁺ in the SrSnO₃ host were also studied. The Nd³⁺ doped SrSnO₃ phosphors exhibit exceptional thermal stability; the integrated emission intensity can retain approximately 66% at 423 K compared to room temperature. Most importantly, NIR persistent luminescence also can be observed for the SrSnO₃:Nd³⁺ samples, which is in the first and second biological windows. A possible mechanism was proposed for the persistent NIR luminescence of Nd³⁺ based on the thermo-luminescence spectra. Consequently, the exciting results indicate that multifunctional NIR luminescence has been successfully realized in the SrSnO₃:Nd³⁺ phosphors. Full article

Femtosecond laser processing combines highly accurate structuring with low residual heating of materials, low thermal damage, and nonlinear absorption processes, making it suitable for the machining of transparent brittle materials. However, with high average powers and laser pulse repetition rates, residual heating becomes relevant. Here, we present a study of the femtosecond laser pulse-on-demand operation regime, combined with regular scanners, aiming to improve throughput and quality of processing regardless of the scanner’s capabilities. We developed two methods to define the needed pulse-on-demand trigger sequences that compensate for the initial accelerating scanner movements. The effects of pulse-on-demand operation were studied in detail using direct process monitoring with a fast thermal camera and indirect process monitoring with optical and topographical surface imaging of final structures, both showing clear advantages of pulse-on-demand operation in precision, thermal effects, and structure shape control. The ability to compensate for irregular scanner movement is the basis for simplified, cheaper, and faster femtosecond laser processing of brittle and heat-susceptible materials. Full article

Iron oxide nanoparticles (IONPs) have garnered significant attention in biomedical applications due to their unique magnetic properties, biocompatibility, and versatility. This review comprehensively examines the synthesis methods, surface functionalization techniques, and diverse biomedical applications of IONPs. Various chemical and physical synthesis techniques, including coprecipitation, sol–gel processes, thermal decomposition, hydrothermal synthesis, and sonochemical routes, are discussed in detail, highlighting their advantages and limitations. Surface functionalization strategies, such as ligand exchange, encapsulation, and silanization, are explored to enhance the biocompatibility and functionality of IONPs. Special emphasis is placed on the role of IONPs in biosensing technologies, where their magnetic and optical properties enable significant advancements, including in surface-enhanced Raman scattering (SERS)-based biosensors, fluorescence biosensors, and field-effect transistor (FET) biosensors. The review explores how IONPs enhance sensitivity and selectivity in detecting biomolecules, demonstrating their potential for point-of-care diagnostics. Additionally, biomedical applications such as magnetic resonance imaging (MRI), targeted drug delivery, tissue engineering, and stem cell tracking are discussed. The challenges and future perspectives in the clinical translation of IONPs are also addressed, emphasizing the need for further research to optimize their properties and ensure safety and efficacy in medical applications. This review aims to provide a comprehensive understanding of the current state and future potential of IONPs in both biosensing and broader biomedical fields. Full article

Integrating multiple types of sensors into autonomous systems, such as cars and robots, has become a widely adopted approach in modern technology. Among these sensors, RGB cameras, thermal cameras, and LiDAR are particularly valued for their ability to provide comprehensive environmental data. However, despite their advantages, current research primarily focuses on the one or combination of two sensors at a time. The full potential of utilizing all three sensors is often neglected. One key challenge is the ego-motion compensation of data in dynamic situations, which results from the rotational nature of the LiDAR sensor, and the blind spots of standard cameras due to their limited field of view. To resolve this problem, this paper proposes a novel method for the simultaneous registration of LiDAR, panoramic RGB cameras, and panoramic thermal cameras in dynamic environments without the need for calibration targets. Initially, essential features from RGB images, thermal data, and LiDAR point clouds are extracted through a novel method, designed to capture significant raw data characteristics. These extracted features then serve as a foundation for ego-motion compensation, optimizing the initial dataset. Subsequently, the raw features can be further refined to enhance calibration accuracy, achieving more precise alignment results. The results of the paper demonstrate the effectiveness of this approach in enhancing multiple sensor calibration compared to other ways. In the case of a high speed of around 9 m/s, some situations can improve the accuracy about 30 percent higher for LiDAR and Camera calibration. The proposed method has the potential to significantly improve the reliability and accuracy of autonomous systems in real-world scenarios, particularly under challenging environmental conditions. Full article

Serpentine (Mg₃Si₂O₅(OH)₄), like quartz, dolomite and magnesite minerals, is a versatile mineral group characterized by silica and magnesium silicate contents with multiple polymorphic phases. Among the phases composed of antigorite, lizardite, and chrysotile, lizardite and chrysotile are the most prevalent phases in the serpentinites studied here. The formation process of serpentinites, which arise from the hydrothermal alteration of peridotites, influences the ratio of light rare earth elements (LREE) to heavy rare earth elements (HREE). In serpentinites, the ratio of light rare earth elements (LREE)/heavy rare earth elements (HREE) provides insights into formation conditions, geochemical evolution, and magmatic processes. The depletion of REE compositions in serpentinites indicates high melting extraction for fore-arc/mantle wedge serpentinites. The studied serpentinites show a depletion in REE concentrations compared to chondrite values, with HREE exhibiting a lesser degree of depletion compared to LREE. The high ΣLREE/ΣHREE ratios of the samples are between 0.16 and 4 ppm. While Ce shows a strong negative anomaly (0.1–12), Eu shows a weak positive anomaly (0.1–0.3). This indicates that fluid interacts significantly with rock during serpentinization, and highly incompatible elements (HIEs) gradually become involved in the serpentinization process. While high REE concentrations indicate mantle wedge serpentinites, REE levels are lower in mid-ocean ridge serpentinites. The enrichment of LREE in the analyzed samples reflects melt/rock interaction with depleted mantle and is consistent with rock–water interaction during serpentinization. The gradual increase in highly incompatible elements (HIEs) suggests that they result from fluid integration into the system and a subduction process. The large differential thermal analysis (DTA) peak at 810–830 °C is an important sign of dehydration, transformation reactions and thermal decomposition, and is compatible with H₂O phyllosilicates in the mineral structure losing water at this temperature. In SEM images, chrysotile, which has a fibrous structure, and lizardite, which has a flat appearance, transform into talc as a result of dehydration with increasing temperature. Therefore, the sudden temperature drop observed in DTA graphs is an indicator of crystal form transformation and CO₂ loss. In this study, the mineralogical and structural properties and the formation of serpentinites were examined for the first time using thermo-gravimetric analysis methods. In addition, the mineralogical and physical properties of serpentinites can be recommended for industrial use as additives in polymers or in the adsorption of organic pollutants. As a result, the high refractory nature of examined serpentine suggests that it is well-suited for applications involving high temperatures. This includes industries such as metallurgy and steel production, glass manufacturing, ceramic production, and the chemical industry. Full article