Search Results (464)

Fibrate pharmaceuticals (fibrates), as a widespread class of emerging contaminants, pose potential risks to both ecological systems and human health. The photocatalytic system based on nitrogen (N) and fluorine (F) co-doped TiO₂ nanotube arrays (NF-TNAs) provides a renewable solution for fibrate pharmaceutical removal from water, powered by inexhaustible sunlight. In this study, the degradation of two typical fibrates, i.e., bezafibrate (BZF) and ciprofibrate (CPF), under simulated sunlight irradiation through NF-TNAs were investigated. The photocatalytic degradation of BZF/CPF was achieved through combined radical and non-radical oxidation processes, while the generation and reaction mechanisms of associated reactive oxygen species (ROS) were examined. Electron paramagnetic resonance detection and quenching tests confirmed the existence of h⁺, •OH, O₂^•−, and ¹O₂, with O₂^•− playing the predominant role. The transformation products (TPs) of BZF/CPF were identified through high-resolution mass spectrometry analysis combined with quantum chemical calculations to elucidate the degradation pathways. The influence of co-existing ions and typical natural organic matters (NOM) on BZF/CPF degradation were also tested. Eventually, the ecological risk of BZF/CPF transformation products was assessed through quantitative structure–activity relationship (QSAR) modeling, and the results showed that the proposed photocatalytic system can largely alleviate fibrate toxicity. Full article

Accurately estimating leaves’ relative chlorophyll contents (widely represented by Soil and Plant Analysis Development (SPAD) values) across growth stages is crucial for assessing crop health, particularly in regions characterized by varying sowing dates. Unlike previous studies focusing on high-resolution UAV imagery or specific growth stages, this research incorporates satellite-derived texture indices (TIs) into a SPAD value estimation model applicable across multiple growth stages (from tillering to grain-filling). Field experiments were conducted in Jiangsu Province, China, where winter wheat sowing dates varied significantly from field to field. Sentinel-2 imagery was employed to extract vegetation indices (VIs) and TIs. Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. The newly developed model (SVR-RBF_VIs+TIs) exhibited robust estimation performance (R² = 0.8131, RMSE = 3.2333, RRMSE = 0.0710, and RPD = 2.3424) when validated against independent SPAD value datasets collected from fields with varying sowing dates. Moreover, this optimal model also exhibited a notable level of transferability at another location with different sowing times, wheat varieties, and soil types from the modeling area. In addition, this research revealed that despite the lower resolution of satellite imagery compared to UAV imagery, the incorporation of TIs significantly improved estimation accuracies compared to the sole use of VIs typical in previous studies. Full article

Complex oxides with the general formula Gd₂(Ti_1−xZr_x)₂O₇ are promising candidates for radioactive waste immobilization due to their capacity to withstand radiation by dissipating part of the free energy driving defect creation and phase transitions. In this study, samples with varying zirconium content (xZr = 0.00, 0.15, 0.25, 0.375, 0.56, 0.75, 0.85, 1.00) were synthesized via the sol–gel method and thermally treated at 500 °C to obtain nanosized powders mimicking the defective structure of irradiated materials. Synchrotron-based techniques were employed to investigate their structural properties: High-Resolution X-ray Powder Diffraction (HR-XRPD) was used to assess long-range structure, while Pair Distribution Function (PDF) analysis and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy provided insights into the local structure. HR-XRPD data revealed that samples with low Zr content (xZr ≤ 0.25) are amorphous. Increasing Zr concentration led to the emergence of a crystalline phase identified as defective fluorite (xZr = 0.375, 0.56). Samples with the highest Zr content (xZr ≥ 0.75) were fully crystalline and exhibited only the fluorite phase. The experimental G(r) functions of the fully crystalline samples in the low r range are suitably fitted by the Weberite structure, mapping the relaxations induced by structural disorder in defective fluorite. These structural insights informed the subsequent EXAFS analysis at the Zr-K and Gd-L₃ edges, confirming the splitting of the cation–cation distances associated with different metal species. Moreover, EXAFS provided a local structural description of the amorphous phases, identifying a consistent Gd-O distance across all compositions. Full article

Accurate spatial mapping of Tailing Impoundments (TIs) is vital for environmental sustainability in mining ecosystems. While remote sensing enables large-scale monitoring, conventional methods relying on single-sensor data and traditional machine learning-based algorithm suffer from reduced accuracy in cluttered environments. This research proposes a deep learning framework leveraging multi-source high-resolution imagery to address these limitations. An upgraded You Only Look Once (YOLO) model is introduced, integrating three key innovations: a multi-scale feature aggregation layer, a lightweight hierarchical fusion mechanism, and a modified loss metric. These components enhance the model’s ability to capture spatial dependencies, optimize inference speed, and ensure stable training dynamics. A comprehensive dataset of TIs across varied terrains was constructed, expanded through affine transformations, spectral perturbations, and adversarial sample synthesis. Evaluations confirm the framework’s superior performance in complex scenarios, achieving higher precision and computational efficiency than state-of-the-art detectors. Full article

Understanding spatial variations in land surface temperature (LST) is critical for analyzing urban climate dynamics, especially within the framework of two-dimensional (2D) turbulence theory. This study assesses the spatial sampling behavior of urban thermal fields across eight metropolitan areas, encompassing diverse morphologies, surface materials, and Köppen–Geiger climate zones. We analyzed thermal infrared (TIR) imagery from two remote sensing platforms—MODIS (1 km) and Landsat (30 m)—to evaluate resolution-dependent turbulence indicators such as spectral slopes and breakpoints. Power spectral analysis revealed systematic divergences across spatial scales. Landsat exhibited more negative breakpoint values, indicating a greater ability to capture fine-scale thermal heterogeneity tied to vegetation, buildings, and surface cover. MODIS, in contrast, emphasized broader thermal gradients, suitable for regional-scale assessments. Seasonal differences reinforced the turbulence framework: summer spectra displayed steeper, more variable slopes, reflecting increased thermal activity and surface–atmosphere decoupling. Despite occasional agreement between sensors, spectral metrics remain inherently resolution-dependent. MODIS is better suited for macro-scale thermal structures, while Landsat provides detailed insights into intra-urban processes. Our findings confirm that 2D turbulence indicators are not fully scale-invariant and vary with sensor resolution, season, and urban form. This multi-sensor comparison offers a framework for interpreting LST data in support of climate adaptation, urban design, and remote sensing integration. Full article

This study investigates the spatial distribution of transition metals—iron (Fe), titanium (Ti), and chromium (Cr)—within the Dryden crater on the Moon using hyperspectral data from the Moon Mineralogy Mapper (M³). By applying spectral parameters and false color composite techniques, geospatial maps of chromite distribution and FeO, TiO₂ wt.% distribution were generated at a resolution of ~140 m. The findings reveal distinct elemental enrichments along geomorphologically active regions such as crater walls, terraces, and central peaks, highlighting impact-driven material differentiation, the influence of morphology, degradation, and space weathering. These results enhance our understanding of lunar crustal evolution and support future exploration and resource utilization efforts. Full article

In this study, we delve into the intricate microstructural features of Ti-6Al-4V alloy additively manufactured and heat-treated at 800 °C for 4 h. Our in-depth analysis will enable us to gain a better understanding of the β-Ti precipitation process, its dependence on temperature, and its ultimate effect on the overall mechanical properties. As well as α-Ti martensite grains and β-Ti particles interspersed in the α-Ti grain boundaries, there is a third microstructural feature, overlooked by many researchers. This feature is observed as nano-sized particles homogeneously embedded inside the α-Ti laths. Using high-resolution transmission electron microscopy, we reveal that these nano-sized features do not constitute a different phase. Instead, they define isolated regions of α-Ti in its relaxed form, surrounded by the heavily strained form of the α-Ti phase. This phenomenon is a result of the “incomplete” precipitation of the β-Ti phase following the heat treatment stage. The straining of the α-Ti phase appears as a shift in the equilibrium atomic position. Full article

Understanding strain behavior near grain boundaries is critical for controlling structural distortions and oxygen vacancy migration in perovskite oxides. However, conventional techniques often lack the spatial resolution needed to analyze phase and domain evolution at the nanoscale. In this paper, polarization-dependent second-harmonic generation (SHG) imaging is employed as a tool to probe local symmetry breaking and complex domain structures in the vicinity of a low-angle grain boundary of SrTiO₃ (STO) bicrystals. We show that the anisotropic strain introduced by a tilted grain boundary produces strong local distortions, leading to the coexistence of tetragonal and rhombohedral domains. By analyzing SHG intensity and variations in the second-order nonlinear optical susceptibility, we map the distribution of strain fields and domain configurations near the boundary. In pristine samples, the grain boundary acts as a localized source of strain accumulation and symmetry breaking, while in samples subjected to intentional electrical stressing, the SHG response becomes broader and more uniform, suggesting strain relaxation. This work highlights SHG imaging as a powerful technique for visualizing grain-boundary-driven structural changes, with broad implications for the design of strain-engineered functional oxide devices. Full article

Guided mode resonance (GMR) sensors are known for their ultrasensitive and label-free detection, achieved by assessing refractive index (RI) variations on grating surfaces. However, conventional systems often require manual adjustments, which limits their practical applicability. Therefore, this study enhances the practicality of GMR sensors by introducing an optimized detection system based on the Jones matrix method. In addition, finite element method simulations were performed to optimize the GMR sensor structure parameter. The GMR sensor chip consists of three main components: a cyclic olefin copolymer (COC) substrate with a one-dimensional grating structure of a period of ~295 nm, a height of ~100 nm, and a ~130 nm thick TiO₂ waveguide layer that enhances the light confinement; an integrated COC microfluidic module featuring a microchannel; and flexible tubes for efficient sample handling. A GMR sensor in conjunction with a specially designed system was used to perform RI measurements across varying concentrations of sucrose. The results demonstrate its exceptional performance, with a normalized sensitivity (S_n) and RI resolution (R_s) of 0.4 RIU⁻¹ and 8.15 × 10⁻⁵ RIU, respectively. The proposed detection system not only offers improved user-friendliness and cost efficiency but also delivers an enhanced performance, making it ideal for scientific and industrial applications, including biosensing and optical metrology, where precise polarization control is crucial. Full article

Macrophage apoptosis, along with inflammation in the interface membrane, has been demonstrated to be significant in the pathogenesis and development of particle-induced periprosthetic osteolysis and aseptic loosening. Additionally, the apoptosis of macrophages is considered an indicator of the resolution phase of inflammation and the transition to normal tissue healing. Therefore, targeting macrophages presents a promising strategy for both the prevention and therapeutic management of periprosthetic osteolysis. In this study, we explored the therapeutic potential of chemical chaperone 4-phenylbutyrate (4-PBA) as a pharmacological intervention aimed at modulating macrophage behaviors, particularly focusing on the processes of apoptosis, inflammation, and osteoclastogenesis in a murine model of TiAl6V4 nanoparticle (TiNP)-induced osteolysis. The results derived from in vivo studies conducted on the murine model provide compelling evidence that TiNPs could trigger osteolysis, activate inflammatory cell infiltration, and promote the differentiation of osteoclasts, accompanied by a notable rise in apoptosis at the osteolytic interface periosteum. The severity of TiNP-induced osteolysis, chaotic bone morphology, extensive bone erosion and destruction, occurrence of infiltrating inflammatory cells, and quantity of osteoclasts were attenuated following co-intervention with 4-PBA. Furthermore, the levels of apoptosis, in conjunction with apoptosis-regulated proteins Bcl-2 and Bax, were accentuated following 4-PBA co-intervention, indicating that the TiNP-induced osteolytic interface periosteum environment exhibited a greater propensity for apoptosis due to the pharmacological intervention of 4-PBA. Notably, the use of 4-PBA as a standalone treatment demonstrated comparatively low levels of toxicity and was deemed to be experimentally safe in mice. These findings indicated that 4-PBA may ameliorate the severity of particle-induced osteolysis by inhibiting the inflammatory response and promoting macrophage apoptosis in a manner that may be beneficial for therapeutic strategies. Thus, pharmacological intervention with 4-PBA appears to be a viable option for addressing osteolysis and aseptic loosening resulting from exposure to wear particles, combining efficacy in promoting apoptosis with a favorable safety profile. Full article

With coastal tourism depending on clean beaches and litter surveys remaining manual, sparse, and costly, this study coupled centimeter-resolution UAV imagery with a Grid R-CNN detector to automate debris mapping on five beaches of Wonsan Island, Korea. Thirty-one Phantom 4 flights (0.83 cm GSD) produced 31,841 orthoimages, while 11 debris classes from the AI Hub dataset trained the model. The network reached 74.9% mAP and 78%/84.7% precision–recall while processing 2.87 images s⁻¹ on a single RTX 3060 Ti, enabling a 6 km shoreline to be surveyed in under one hour. Georeferenced detections aggregated to 25 m grids showed that 57% of high-density cells lay within 100 m of the beach entrances or landward edges, and 86% within 200 m. These micro-patterns, which are difficult to detect in meter-scale imagery, suggest that entrance-focused cleanup strategies could reduce annual maintenance costs by approximately one-fifth. This highlights the potential of centimeter-scale GeoAI in supporting sustainable beach management. Full article

Background and Objectives: The goal of this study was to introduce a novel device, the iMPACT implant planer, designed to machine (create a complete smooth surface) contaminated implant surfaces intraorally, promoting peri-implant tissue healing and possible re-osseointegration, and the new Quadrant protocol, evaluating them in vitro and clinically. The null hypothesis was that there would be no improvement in the clinical parameters for the implants with peri-implantitis (PI) treated with the new protocol and tool. Materials and Methods: The Quadrant protocol was used in conjunction with the iMPACT tool, which primarily functions to remove biofilm and microbial contaminants from the exposed implant surface, while simultaneously preparing the surface through standardized implantoplasty, thereby enhancing the potential for re-osseointegration. An in vitro analysis was developed, and three medium/long-term cases were presented, detailing the procedures and outcomes. Results: The in vitro assessment showed smooth surfaces after treatment. Different areas presented minimal particles (<1 μm) on the implant surface, with a high content of titanium (Ti) and tungsten (W). In case 1, severe and advanced peri-implantitis around implants #46 and #47 was found. A combination of resective (Quadrant + iMPACT) and regenerative surgery was used for treatment, along with a buccal single flap (BSF). Significant clinical and radiographic improvements were observed at 14 and 43 months postoperatively, including vertical bone gain with re-osseointegration and stable probing depths (PDs). In the second case, a severe PI and prosthesis instability were observed. Resective (Quadrant + iMPACT) and regenerative procedures were applied. At 3 and 12 months postoperatively, clinical and radiographic evaluations demonstrated significant improvements with re-osseointegration, including PDs reduced to 0–1 mm and a vertical bone gain of approximately 6.5 mm. In case 3, mandibular implants from 42 to 47 exhibited inflammation, suppuration, and moderate-to-severe bone loss. Just resective surgery (Quadrant + iMPACT), without grafting, was performed. At 6- and 12-month follow-ups, clinical and radiographic assessments showed the resolution of inflammation, stable bone levels, and healthy peri-implant gingiva. Conclusions: Favorable outcomes were achieved using the iMPACT and Quadrant protocols in the three clinical cases, resulting in re-osseointegration when combined with regenerative procedures. The favorable medium/long-term outcomes achieved, despite the patient’s complex medical history and, at times, inconsistent oral hygiene, underscore the potential efficacy of such interventions. Full article

Arc scanning synthetic aperture radar (ArcSAR) can achieve high-resolution panoramic imaging and retrieve submillimeter-level deformation information. To monitor buildings in a city scenario, ArcSAR must be lightweight; have a high resolution, a mid-range (around a hundred meters), and low power consumption; and be cost-effective. In this study, a novel high-resolution wide-beam single-chip millimeter-wave (mmwave) ArcSAR system, together with an imaging algorithm, is presented. First, to handle the non-uniform azimuth sampling caused by motor motion, a high-accuracy angular coder is used in the system design. The coder can send the radar a hardware trigger signal when rotated to a specific angle so that uniform angular sampling can be achieved under the unstable rotation of the motor. Second, the ArcSAR’s maximum azimuth sampling angle that can avoid aliasing is deducted based on the Nyquist theorem. The mathematical relation supports the proposed ArcSAR system in acquiring data by setting the sampling angle interval. Third, the range cell migration (RCM) phenomenon is severe because mmwave radar has a wide azimuth beamwidth and a high frequency, and ArcSAR has a curved synthetic aperture. Therefore, the fourth-order RCM model based on the range-Doppler (RD) algorithm is interpreted with a uniform azimuth angle to suit the system and implemented. The proposed system uses the TI 6843 module as the radar sensor, and its azimuth beamwidth is 64°. The performance of the system and the corresponding imaging algorithm are thoroughly analyzed and validated via simulations and real data experiments. The output image covers a 360° and 180 m area at an azimuth resolution of 0.2°. The results show that the proposed system has good application prospects, and the design principles can support the improvement of current ArcSARs. Full article

Thin TiO₂–SnO₂ nanocomposite films with high gas sensitivity to NO₂ were synthesized by oxidative pyrolysis and comprehensively studied. The composite structure and quantitative composition of the obtained film nanomaterials have been confirmed by X-ray photoelectron spectroscopy, high-resolution transmission electron microscopy, and energy dispersive X-ray spectroscopy, which causes the presence of n-n heterojunctions and provides improved gas-sensitive properties. The sensor based on the 3TiO₂–97SnO₂ film has the maximum responses, which is explained by the existence of a strong surface electric field formed by large surface potentials in the region of TiO₂–SnO₂ heterojunctions detected by the Kelvin probe force microscopy method. Exposure to low-intensity radiation (no higher than 0.2 mW/cm², radiation wavelength—400 nm) leads to a 30% increase in the sensor response relative to 7.7 ppm NO₂ at an operating temperature of 200 °C and a humidity of 60% RH. At room temperature (20 °C), under humidity conditions, the response is 1.8 when exposed to 0.2 ppm NO₂ and 85 when exposed to 7.7 ppm. The lower sensitivity limit is 0.2 ppm NO₂. The temporal stability of the proposed sensors has been experimentally confirmed. Full article

The contemporary challenge in remote sensing lies in the precise retrieval of increasingly abundant and high-resolution remotely sensed images (RS image) stored in expansive data warehouses. The heightened spatial and spectral resolutions, coupled with accelerated image acquisition rates, necessitate advanced tools for effective data management, retrieval, and exploitation. The classification of large-sized images at the pixel level generates substantial data, escalating the workload and search space for similarity measurement. Semantic-based image retrieval remains an open problem due to limitations in current artificial intelligence techniques. Furthermore, on-board storage constraints compel the application of numerous compression algorithms to reduce storage space, intensifying the difficulty of retrieving substantial, sensitive, and target-specific data. This research proposes an innovative hybrid approach to enhance the retrieval of remotely sensed images. The approach leverages multilevel classification and multiscale feature extraction strategies to enhance performance. The retrieval system comprises two primary phases: database building and retrieval. Initially, the proposed Multiscale Multiangle Mean-shift with Breaking Ties (MSMA-MSBT) algorithm selects informative unlabeled samples for hyperspectral and synthetic aperture radar images through an active learning strategy. Addressing the scaling and rotation variations in image capture, a flexible and dynamic algorithm, modified Deep Image Registration using Dynamic Inlier (IRDI), is introduced for image registration. Given the complexity of remote sensing images, feature extraction occurs at two levels. Low-level features are extracted using the modified Multiscale Multiangle Completed Local Binary Pattern (MSMA-CLBP) algorithm to capture local contexture features, while high-level features are obtained through a hybrid CNN structure combining pretrained networks (Alexnet, Caffenet, VGG-S, VGG-M, VGG-F, VGG-VDD-16, VGG-VDD-19) and a fully connected dense network. Fusion of low- and high-level features facilitates final class distinction, with soft thresholding mitigating misclassification issues. A region-based similarity measurement enhances matching percentages. Results, evaluated on high-resolution remote sensing datasets, demonstrate the effectiveness of the proposed method, outperforming traditional algorithms with an average accuracy of 86.66%. The hybrid retrieval system exhibits substantial improvements in classification accuracy, similarity measurement, and computational efficiency compared to state-of-the-art scene classification and retrieval methods. Full article