Search Results (2,282)

The ice surface temperature (IST) derived from thermal infrared remote sensing is crucial for accurately monitoring ice or snow surface temperatures in the polar region. Generally, the remote sensing IST needs to be validated by the in situ IST to ensure its accuracy. However, due to the limited availability of in situ IST measurements, previous studies in the validation of remote sensing ISTs are scarce in the Antarctic ice sheet. This study utilizes ISTs from eight broadband radiation stations to assess the accuracy of the latest-released Moderate Resolution Imaging Spectroradiometer (MODIS) IST and Visible Infrared Imager Radiometer Suite (VIIRS) IST products, which were derived from two different algorithms, the Split-Window (SW-based) algorithm and the Temperature–Emissivity Separation (TES-based) algorithm, respectively. This study also explores the sources of uncertainty in the validation process. The results reveal prominent errors when directly validating remote sensing ISTs with the in situ ISTs, which can be attributed to incorrect cloud detection due to the similar spectral characteristics of cloud and snow. Hence, cloud pixels are misclassified as clear pixels in the satellite cloud mask during IST validation, which emphasizes the severe cloud contamination of remote sensing IST products. By using a cloud index (n) to remove the cloud contamination pixels in the remote sensing IST products, the overall uncertainties for the four products are about 2 to 3 K, with the maximum uncertainty (RMSE) reduced by 3.51 K and the bias decreased by 1.26 K. Furthermore, a progressive cold bias in the validation process was observed with decreasing temperature, likely due to atmospheric radiation between the radiometer and the snow surface being neglected in previous studies. Lastly, this study found that the cloud mask errors of satellites are more pronounced during the winter compared to that in summer, highlighting the need for caution when directly using remote sensing IST products, particularly during the polar night. Full article

The rapid identification of bacteria is extremely important for controlling infections and enabling swift and effective action. Light scattering has proven to be a highly versatile technique for identifying bacteria, as it does not require long colony growth times. In this article, we present a study on the use of cross-polarized optical scattering (CPS). Despite a relatively low scattering efficiency (10⁻⁵ to 10⁻⁶), working with cross-polarization enhances contrast by eliminating a highly intense background of scattered light. CPS has been applied to four bacteria, with three similar in shape. Moreover, two of them are Gram+ and two Gram-. The obtained images have been reduced in size down to a 16-bit images and camera noise has been added. Although bacteria are symmetrical in principle, in reality rotations of their orientation generate asymmetries in the CPS patterns that were exploited precisely to recognize and classify the different species. The classification of bacteria by a t-SNE algorithm in a reduced-dimension space shows that their features are grouped into specific clusters. However, such classification is not completely decisive due to partial cluster overlapping. Full article

This paper introduces an image processing method, used to achieve uniform sensitivity across the imaging plane in a high-frequency electric field imaging system, that employs an electro-optical crystal and a polarization image sensor. The polarization pixels have two polarization directions, 0° and 90°, in pairs, and, conventionally, their difference is computed first. In contrast, this study proposes a method to separate each polarization image, perform pixel completion, and subsequently perform intensity correction. The proposed method was demonstrated to improve field distribution images acquired using 36 GHz and 30 GHz input signals for a microstrip line and patch antenna, respectively. From the measurement results of the microstrip line, the application of the proposed method reduced the electric field fluctuations on the line from 3.1 dB to 1.5 dB. This image-processing method can be applied sequentially during image acquisition, making it suitable for the real-time imaging of electric fields. Full article

When collecting data using ERT2D (2D electrical resistivity tomography) and TDIPT2D (2D time domain-induced polarization), different phenomena can occur, which can cause natural or anthropogenic noise, contaminating the data and making its processing, analysis, and interpretation difficult. Different techniques have been developed to eliminate or reduce these effects on the data, such as noise filtering or the development of new techniques to improve data collection in the field. In the present work, an iterative, weighted, least-squares filter was employed after voltage normalization using current and geometrical factor correction on data collected in rough topographic terrains. The selected filter basis function should be able to represent the natural behavior of the function to be filtered. Stationary or variable voltages in electrical prospecting decay with the inverse of the distance, which can be represented by an expansion in Legendre polynomials. On the other hand, uneven spacing of the electrodes leads to using the incorrect geometric factor, resulting in an error in the calculation of the electrical anomaly. The efficiency of the proposed technique was analyzed and tested with field examples using different filters and by comparing applying and not applying the proposed correction factor. The results indicated low RMS and L2-Norm errors, and better definition of the inverted resistivity image was obtained. For the TDIP data, a better correspondence between the inverted images of resistivity and chargeability was obtained. Full article

Division-of-focal-plane (DoFP) polarization imaging systems have demonstrated considerable promise in target detection and tracking in complex backgrounds. However, existing methods face challenges, including dependence on complex image preprocessing procedures and limited real-time performance. To address these issues, this study presents a novel histogram of polarization gradient (HPG) feature descriptor that enables efficient feature representation of polarization mosaic images. First, a polarization distance calculation model based on normalized cross-correlation (NCC) and local variance is constructed, which enhances the robustness of gradient feature extraction through dynamic weight adjustment. Second, a sparse Laplacian filter is introduced to achieve refined gradient feature representation. Subsequently, adaptive polarization channel correlation weights and the second-order gradient are utilized to reconstruct the degree of linear polarization (DoLP). Finally, the gradient and DoLP sign information are ingeniously integrated to enhance the capability of directional expression, thus providing a new theoretical perspective for polarization mosaic image structure analysis. The experimental results obtained using a self-developed long-wave infrared DoFP polarization thermal imaging system demonstrate that, within the same FBACF tracking framework, the proposed HPG feature descriptor significantly outperforms traditional grayscale {8.22%, 2.93%}, histogram of oriented gradient (HOG) {5.86%, 2.41%}, and mosaic gradient histogram (MGH) {27.19%, 18.11%} feature descriptors in terms of precision and success rate. The processing speed of approximately 20 fps meets the requirements for real-time tracking applications, providing a novel technical solution for polarization imaging applications. Full article

The Chinese HuanjingJianzai-2 (HJ-2) A/B satellites are equipped with advanced sensors, including a Multispectral Camera (MSC) and a Polarized Scanning Atmospheric Corrector (PSAC). To address the challenges of atmospheric correction (AC) for the MSC’s wide-swath, wide-field images, this study proposes a pixel-by-pixel method incorporating Bidirectional Reflectance Distribution Function (BRDF) effects. The approach uses synchronous atmospheric parameters from the PSAC, an atmospheric correction lookup table, and a semi-empirical BRDF model to produce surface reflectance (SR) products through radiative, adjacency effect, and BRDF corrections. The corrected images showed significant improvements in clarity and contrast compared to pre-correction images, with minimum increases of 55.91% and 35.63%, respectively. Validation experiments in Dunhuang and Hefei, China, demonstrated high consistency between the corrected SR and ground-truth data, with maximum deviations below 0.03. For surface types not covered by ground measurements, comparisons with Sentinel-2 SR products yielded maximum deviations below 0.04. These results highlight the effectiveness of the proposed method in improving image quality and accuracy, providing reliable data support for applications such as disaster monitoring, water resource management, and crop monitoring. Full article

In this study, we present a novel ultra-wideband passive polarization conversion metasurface (PCM) that integrates double V-shaped patterns with circular split-ring resonators. Operating without any external power supply or active components, this design effectively manipulates the polarization state of incident electromagnetic waves. Numerical and experimental results demonstrate that the proposed PCM can convert incident linear polarization into orthogonal states across a wide frequency range of 7.1–22.3 GHz, encompassing the C-, X-, Ku-, and K-bands. A fabricated prototype confirms that the polarization conversion ratio (PCR) exceeds 90% throughout the specified band. Furthermore, we explore an additional application of this passive metasurface for electromagnetic stealth, wherein it achieves over 10 dB of monostatic radar cross-section (RCS) reduction from 7.6 to 21.5 GHz. This broad effectiveness is attributed to strong electromagnetic resonances between the top and bottom layers, as well as the Fabry–Pérot cavity effect, as evidenced by detailed analyses of the underlying physical mechanisms and induced surface currents. These findings confirm the effectiveness of the proposed design and highlight its potential for future technological applications, including 6G communications, radar imaging, anti-interference measures, and electromagnetic stealth. Full article

This study focuses on the topographic structure of optical anisotropy maps (theziograms) of dehydrated blood plasma films (facies) to identify and utilize markers for diagnosing self-similarity (multifractality) in the birefringence parameters of supramolecular protein networks. The research is based on the Jones-matrix analytical framework, which describes the formation of polarization-structural speckle fields in polycrystalline blood plasma facies. In the proposed model, algorithms were developed to relate the real and imaginary parts of the complex elements of the Jones matrix to the theziograms of linear and circular birefringence. To experimentally implement these algorithms, a novel optical technology was introduced for polarization-interference registration and phase scanning of the laser speckle field of blood plasma facies. The laser-based Jones-matrix layer-by-layer theziography relies on polarization filtration and the digital recording of interference patterns from microscopic images of blood plasma facies. This process includes digital 2D Fourier reconstruction and phase-by-phase scanning of the object field of complex amplitudes, enabling the acquisition of phase sections of laser polarization-structural speckle field components scattered with varying multiplicities. Jones-matrix images of supramolecular networks, along with their corresponding theziograms of linear and circular birefringence, were obtained for each phase plane. The experimental data derived from laser layer-by-layer Jones-matrix theziography were quantitatively analyzed using two complementary approaches: statistical analysis (central moments of the 1st to 4th orders) and multifractal analysis (spectra of fractal dimension distributions). As a result, the most sensitive markers—namely asymmetry and kurtosis—were identified, highlighting changes in the statistical and scale self-similar structures of the theziograms of linear and circular birefringence in blood plasma facies. The practical aspect of this work is to evaluate the diagnostic potential of the Jones-matrix theziography method for identifying and differentiating changes in the birefringence of supramolecular networks in blood plasma facies caused by the long-term effects of COVID-19. For this purpose, a control group (healthy donors) and three experimental groups of patients, confirmed to have had COVID-19 one-to-three years prior, were formed. Within the framework of evidence-based medicine, the operational characteristics of the method—sensitivity, specificity, and accuracy—were assessed. The method demonstrated excellent accuracy in the differential diagnosis of the long-term effects of COVID-19. This was achieved by statistically analyzing the spectra of fractal dimensions of Jones-matrix theziograms reconstructed in the phase plane of single scattering within the volume of blood plasma facies. Full article

A spherical amide with C₃ symmetry was synthesized by a one-step cyclization reaction using triphenylphosphine and hexachloroethane as coupling reagents. This method enabled synthesis of N-benzyl and N-allyl derivatives, which could not be obtained by the previously reported method. The optical resolution of each compound was measured, and their electronic circular dichroism spectra revealed that they were mirror images. The high structural symmetry resulted in a higher Δε (molar absorption difference against right or left circular polarization: ε_L − ε_R value compared to that of another structural isomer synthesized previously. The absolute structure of the enantiopure crystal of the N-benzyl derivative was determined using the Flack parameter obtained by X-ray crystallographic analysis. Full article

Body temperature is a critical indicator of pig health. This study proposes a non-contact method for detecting body temperature in group-housed pigs by extracting temperature data from thermal images of ear roots. Thermal images in the drinking trough area were captured using a thermal camera, with real-time data transmitted to a monitoring room via optical fibers. The YOLO v11m-OBB model was utilized to detect the ear root areas with oriented bounding boxes, while a novel algorithm, the two-stage left and right ear root pairing algorithm (YOLO TEPA-OBB), paired the ear roots of individual pigs using center distance clustering and angular relationships in a polar coordinate system. The maximum temperature of the ear roots was extracted to represent the body temperature. Experimental results based on 749 ear roots show that the YOLO TEPA-OBB achieves 98.7% precision, 98.4% recall, and 98.7% mean average precision (mAP) in detecting ear roots, with an ear root pairing accuracy of 98.1%. The Pearson correlation coefficient (r) between predicted and reference temperatures is 0.989, with a mean bias of 0.014 °C and a standard deviation of 0.103 °C. This research facilitates real-time body temperature monitoring and precise health management for group-housed pigs. Full article

The long-term impact of stroke on Alzheimer’s disease (AD) progression, particularly regarding sex-specific differences, remains unknown. Using a longitudinal study design, we investigated transient middle cerebral artery occlusion in 3.5-month-old APP_swe/PS1_dE9 (APP/PS1) and wild-type mice. In vivo, we assessed behavior, cerebral blood flow (CBF), and structural integrity by neuroimaging, as well as post-mortem myelin integrity (polarized light imaging, PLI), neuroinflammation, and amyloid beta (Aβ) deposition. APP/PS1 mice exhibited cognitive decline, white matter degeneration (reduced fractional anisotropy (FA) via diffusion tensor imaging (DTI)), and decreased myelin density via PLI. Despite early hypertension, APP/PS1 mice showed only sporadic hypoperfusion. Cortical thickening and hippocampal hypertrophy likely resulted from Aβ accumulation and neuroinflammation. Stroke-operated mice retained cognition despite cortical thinning and hippocampal atrophy due to cerebrovascular adaptation, including increased CBF in the hippocampus and thalamus. Stroke did not worsen AD pathology, nor did AD exacerbate stroke outcomes. Sex differences were found: female APP/PS1 mice had more severe Aβ deposition, hyperactivity, lower body weight, and reduced CBF but less neuroinflammation, suggesting potential neuroprotection. These findings highlight white matter degeneration and Aβ pathology as key drivers of cognitive decline in AD, with stroke-related deficits mitigated by (cerebro)vascular adaptation. Sex-specific therapies are crucial for AD and stroke. Full article

Research on deep learning (DL)-based channel estimation for massive multiple-input multiple-output (MIMO) communication systems has attracted considerable interest in recent years. In this paper, we propose a DL-assisted channel estimation algorithm that transforms the original channel estimation problem into an image denoising problem, contrasting it with traditional experience-based channel estimation methods. We establish a new polarized self-attention-aided channel estimation neural network (PACE-Net) to achieve efficient channel estimation. This approach addresses the limitations of the conventional methods, particularly their low accuracy and high computational complexity. In addition, we construct a channel dataset to facilitate the training and testing of PACE-Net. The simulation results show that the proposed DL-assisted channel estimation algorithm has better normalization mean square error (NMSE) performance compared with the traditional algorithms and other DL-assisted algorithms. Furthermore, the computational complexity of the proposed DL-assisted algorithm is significantly lower than that of the traditional minimum mean square error (MMSE) channel estimation algorithm. Full article

Most electromagnetic metasurfaces only control a single property of electromagnetic waves, such as the phase, amplitude, polarization or frequency, leading to a shortage in capacity and security in communication and a decrease in radar imaging efficiency. By switching the states of four PIN diodes soldered between adjacent resonant arms, cross-polarization and co-polarization reflected waves both with a 1-bit phase can be implemented. The simulation results demonstrate that the proposed metasurface operates within a frequency band of 5.7 GHz to 5.88 GHz, covering ISM 5.8 GHz. Within its operational frequency range, in the cross-polarization reflection case, the losses of the 1-bit phase reflected wave are from 1 dB to 1.5 dB, with a high polarization conversion rate exceeding 91% and even reaching 99%. For the co-polarization reflection case, the losses of the 1-bit reflected wave are from 0.3 dB to 2 dB, and the polarization conversion is almost 100%. The phase difference of the reflected wave in both cases can be realized as about 180°, which satisfies the 1-bit phase requirement for building a good property of beam steering. Upon constructing a 10 × 10 small array, the cross-polarized reflection beam can be steered within the range of elevation angle from 0° to 45° and the elevation angle from 0° to 30° in the co-polarized reflection case. Full article

Retrieving LST from infrared spectral observations is challenging because it needs separation from emissivity in surface radiation emission, which is feasible only when the state of the surface–atmosphere system is known. Thanks to its high spectral resolution, the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard Metop polar-orbiting satellites is the only sensor that can simultaneously retrieve LST, the emissivity spectrum, and atmospheric composition. Still, it cannot penetrate thick cloud layers, making observations blind to surface emissions under cloudy conditions, with surface and atmospheric parameters being flagged as voids. The present paper aims to discuss a downscaling–fusion methodology to retrieve LST missing values on a spatial field retrieved from spatially scattered IASI observations to yield level 3, regularly gridded data, using as proxy data LST from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) flying on Meteosat Second Generation (MSG) platform, a geostationary instrument, and from the Advanced Very High-Resolution Radiometer (AVHRR) onboard Metop polar-orbiting satellites. We address this problem by using machine learning techniques, i.e., Gradient Boosting, Random Forest, Gaussian Process Regression, Neural Network, and Stacked Regression. We applied the methodology over the Po Valley region, a very heterogeneous area that allows addressing the trained models’ robustness. Overall, the methods significantly enhanced spatial sampling, keeping errors in terms of Root Mean Square Error (RMSE) and bias (Mean Absolute Error, MAE) very low. Although we demonstrate and assess the results primarily using IASI data, the paper is also intended for applications to the IASI follow-on, that is, IASI Next Generation (IASI-NG), and much more to the Infrared Sounder (IRS), which is planned to fly this year, 2025, on the Meteosat Third Generation platform (MTG). Full article

With the advancement of polarimetric synthetic aperture radar (PolSAR) imaging technology and the growing demand for image interpretation, extracting meaningful land cover information from PolSAR images has become a key research focus. To address the segmentation challenge, we propose an innovative method. First, features from co-polarization and cross-polarization channels are separately used as dual inputs, and a cross-attention mechanism effectively fuses these features to capture correlations between different polarization information. Second, a diffusion framework is employed to jointly model target features and class probabilities, aiming to improve segmentation accuracy by learning and fitting the probabilistic distribution of target labels. Finally, experimental results demonstrate that the proposed method achieves superior performance in PolSAR image segmentation, effectively managing complex polarization relationships while offering robustness and broad application potential. Full article