Search Results (2,209)

We present a novel high-resolution complex field extraction technique utilizing U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization cameras with micro-polarized arrays. Our method extracts high-resolution complex field information, achieving a resolution comparable to that of the original polarization camera. Utilizing the parallel phase-shifting digital holography technique, we extracted high-resolution complex field information from four high-resolution phase-shifted interference patterns predicted by our network directly at the hologram plane. Extracting the object’s complex field directly at the hologram plane rather than the object’s plane, our method eliminates the dependency on numerical propagation during dataset acquisition, enabling reconstruction of objects at various depths without DC and conjugate noise. By training the network with real-valued interference patterns and using only a single pair of low- and high-resolution input and ground truth interference patterns, we simplify computational complexity and improve efficiency. Our simulations demonstrate the network’s robustness to variations in random phase distributions and transverse shifts in the input patterns. The effectiveness of the proposed method is demonstrated through numerical simulations, showing an average improvement of over 4 dB in peak-signal-to-noise ratio and 25% in intensity normalized cross-correlation metrics for object reconstruction quality. Full article

An ultra-thin spiral diffractive lens (SDL) was fabricated by using focused ion beam milling on a fiber end-facet coated with a 100 nm thick Au film. Focusing vortex beams (FVBs) were successfully excited by the SDLs due to the coherent superposition of diffracted waves and their azimuth dependence of the phase accumulated from the spiral aperture to the beam axis. The polarization and phase characteristics of the FVBs were experimentally investigated. Results show that the input beams with various polarization states were converted to FVBs, whose polarization states were the same as those of the input beams. Furthermore, the focal length of the SDL and the in-tensity and phase distribution at the focus spot of the FVBs were numerically simulated by the FDTD method in the ultra-wide near-infrared waveband from 1300 nm to 1800 nm. The focal length was tuned from 21.8 μm to 14.7 μm, the intensity profiles exhibited a doughnut-like shape, and the vortex phase was converted throughout the broadband range. The devices are expected to be candidates for widespread applications including optical communications, optical imaging, and optical tweezers. Full article

Structured light is essential in various fields such as imaging, communications, computing, laser microprocessing, and ultrafast and nonlinear optics. The structuring of light can occur in terms of space, amplitude, phase, polarization, time, frequency, and duration. One of the intriguing properties that can be obtained is resistance to the diffractive spread and dispersive broadening of the pulsed beams. This happens when temporal properties such as frequency are coupled with spatial properties like angles of propagation of plane-wave components. In this case, pulsed light beams exhibit characteristics similar to optical bullets, resisting both diffraction and material dispersion. This study questions whether free-space optical bullets that possess nondiffracting and nondispersive properties are possible with subcycle durations. We report on the possibility to create nondiffracting and nondispersing localized subcycle pulsed beams and their complex polarization topologies when controlling the group velocity of these light structures. Full article

The Joint Polar Satellite System 3 (JPSS-3) and 4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) are the fourth and fifth in its series of instruments designed to provide high-quality data products for environmental and climate data records. The VIIRS instrument must be calibrated and characterized prior to launch to meet the data product needs. A comprehensive test program was conducted at the Raytheon Technologies facility in 2020 (JPSS-3) and 2023 (JPSS-4) that included extensive functional and environmental testing. The thermal band radiometric pre-launch performance and stability are the focus of this article, which also compares several instrument performance metrics to the design requirements. Brief comparisons with the JPSS-1 and -2 VIIRS instrument performance will also be discussed. Full article

In this paper, a simple design of a polarization-selective tunable triple terahertz absorber based on a graphene rectangular ring resonator was proposed and studied. The absorber structure consists of a graphene rectangular ring resonant array on the top, SiO₂ dielectric layer in the middle and gold at the bottom. The calculated results show that the absorber can achieve high-efficiency triple-band absorption under both x and y polarization incident light. When x-polarized light is incident, three distinctive absorption peaks at 2.73, 5.70 and 11.19 THz with absorption rates of 96.7%, 98.5% and 96.5% are achieved. When y-polarized light is incident, three additional absorption peaks at 2.29, 7.55 and 9.98 THz can be obtained with absorption rates of 96.3%, 90.3% and 97.4%, respectively. Moreover, the absorption wavelength of the absorber can be tuned by adjusting the chemical potential of the graphene. Owing to the high efficiency of triple-band absorption in different polarization states, the absorber has broad application prospects in terahertz polarization imaging, sensing and detection. Full article

Besides the intensity and wavelength, the ability to analyze the optical polarization of detected light can provide a new degree of freedom for numerous applications, such as object recognition, biomedical applications, environmental monitoring, and remote sensing imaging. However, conventional filter-integrated polarimetric sensing systems require complex optical components and a complicated fabrication process, severely limiting their on-chip miniaturization and functionalities. Herein, the reconfigurable polarimetric photodetection with photovoltaic mode is developed based on a few-layer MoS₂/PdSe₂ heterostructure channel and a charge-trap structure composed of Al₂O₃/HfO₂/Al₂O₃ (AHA)-stacked dielectrics. Because of the remarkable charge-trapping ability of carriers in the AHA stack, the MoS₂/PdSe₂ channel exhibits a high program/erase current ratio of 10⁵ and a memory window exceeding 20 V. Moreover, the photovoltaic mode of the MoS₂/PdSe₂ Schottky diode can be operated and manipulable, resulting in high and distinct responsivities in the visible broadband. Interestingly, the linear polarization of the device can be modulated under program/erase states, enabling the reconfigurable capability of linearly polarized photodetection. This study demonstrates a new prototype heterostructure-based photodetector with the capability of both tunable responsivity and linear polarization, demonstrating great potential application toward reconfigurable photosensing and polarization-resolved imaging applications. Full article

Metamaterial absorbers have gained widespread applications in fields such as sensing, imaging, and electromagnetic cloaking due to their unique absorption characteristics. This paper presents the design and fabrication of a novel K-band polarization-sensitive metamaterial absorber, which operates in the frequency range of 20.76 to 24.20 GHz for both TE and TM modes, achieving an absorption rate exceeding 90% and a bandwidth of up to 3.44 GHz. The structure of the metamaterial absorber consists of a rectangular aperture metallic patch, two metallic rings, and two metallic strips, with a metallic patch structure on the back. Both metallic patches are printed on a 1.575 mm-thick FR-4 substrate. In the TE mode, the performance shows diagonal symmetry, with a minimum absorption bandwidth of 1.4 GHz at 45° and a maximum of 3.44 GHz at 0°. The absorption rate exceeds 90% across various polarization angles. In terms of conventional modes, both the TE and TM modes can achieve ultra-wideband absorption. For specific scenarios requiring single-frequency or multi-frequency absorption, the desired functionality can be realized by varying the incident angle. These exceptional characteristics confer strong applicability for high-bandwidth electromagnetic wave absorption and specific frequency point absorption, indicating significant potential and practical value in the field of wireless communication. Full article

Grazing lands are crucial for agricultural productivity, ecological stability, and carbon sequestration, underscoring the importance of monitoring vegetation biomass for the effective management of these ecosystems. Remote sensing data, including optical vegetation indices (VIs) like the Normalized Difference Vegetation Index (NDVI), are widely used to monitor vegetation dynamics due to their simplicity and high sensitivity. In contrast, radar-based VIs, such as the Polarimetric Radar Vegetation Index (PRVI), offer additional advantages, including all-weather imaging capabilities, a wider saturation range, and sensitivity to the vegetation structure information. This study introduces an enhanced form of the PRVI, termed the Normalized PRVI (NPRVI), which is calibrated to a 0 to 1 range, constraining the minimum value to reduce the background effects. The calibration and range factor were derived from statistical analysis of PRVI components across vegetated regions in the Contiguous United States (CONUS), using dual-polarization C-band Sentinel-1 and L-band ALOS-PALSAR data on the Google Earth Engine (GEE) platform. Machine learning models using NPRVI and NDVI demonstrated their complementarity with annual herbaceous biomass data from the Rangeland Analysis Platform. The results showed that the Random Forest Model outperformed the other machine learning models tested, achieving R² ≈ 0.51 and MAE ≈ 498 kg/ha (relative MAE ≈ 32.1%). Integrating NPRVI with NDVI improved biomass estimation accuracy by approximately 10% compared to using NDVI alone, highlighting the added value of incorporating radar-based vegetation indices. NPRVI may enhance the monitoring of grazing lands with relatively low biomass compared to other vegetation types, while also demonstrating applicability across a broad range of biomass levels and in diverse vegetation covers. Full article

Highly accurate rice cultivation distribution and area extraction are essential to food security. Moreover, Inner Mongolia, whose slogan is “from scientific rice to world rice”, is an essential national rice production base. However, high-quality rice mapping products at high resolutions are still scarce around the Inner Mongolia Autonomous Region. This condition is not conducive to rational planning of farmland resources, maintaining food security, and promoting sustainable growth of the local agricultural economy. In this study, the rice backscattering intensity difference index from the vertically polarized backscatter intensity of Sentinel-1 and the phenology differential index from the spectral indices of two critical rice phenological phases of Sentinel-2 images were constructed. Other spectral features, including spectral indices, tasseled cap, and texture features, were computed using simple non-iterative clustering (SNIC) to achieve image segmentation. These variables served as input features for the random forest (RF) algorithm. Results reveal that employing the RF with the SNIC segmentation algorithm and combining it with optical and synthetic aperture radar data is an effective way to extract data on rice in mid-latitude regions. The overall accuracy and kappa coefficient are 0.98 and 0.967, correspondingly. The accuracy for rice is 0.99, as proven by empirical data. These results meet the requirements of regional rice cultivation assessment and area monitoring. Furthermore, owing to its resilience against longitude-associated influences, the model discerns rice across diverse regions and multiple years, achieving an R2 of 0.99. This capability significantly bolsters efforts to improve regional food security and the pursuit of sustainable development. Full article

Oleogels are structured materials formed by immobilizing oil within a polymer network. This study aimed to synthesize bilayer foamed oleogels using Ecogel™ as an emulsifier—a natural gelling and emulsifying agent commonly used to stabilize emulsions. Ecogel™ is multifunctional, particularly in cosmetic formulations, where it aids in creating lightweight cream gels with a cooling effect. However, the specific goal of this study was to investigate the physicochemical properties of oleogels formed with Ecogel™, Tween 80, gelatin, and glycerin. The combination of these ingredients has not been studied before, particularly in the context of bilayer foamed oleogels. The biphasic nature of the resulting materials was explored, consisting of a uniform lower phase and a foamed upper layer. Several analytical techniques were employed, including FT-IR spectrophotometric analysis, moisture content evaluation, surface wettability measurements, microscopic imaging, and rheological studies, in addition to surface energy determination. The results demonstrated that the addition of Tween 80 significantly improved the stability and rigidity of the oleogels. Furthermore, storage at reduced temperatures after synthesis enhanced the material’s stabilizing properties. These materials also showed an affinity for interacting with non-polar compounds, indicating potential applications in skincare, especially for interaction with skin lipids. Full article

Maintaining the integrity of urban road pavements is vital for public safety, transportation efficiency, and economic stability. However, aging infrastructure and limited budgets make it challenging to detect subsurface defects that can lead to pavement collapses. Traditional inspection methods are often inadequate for identifying such underground anomalies. Ground Penetrating Radar (GPR), especially dual-polarized array systems, offers a non-destructive, high-resolution solution for subsurface inspection. Despite its potential, effectively detecting and analyzing areas at risk of collapse in urban pavements remains a challenge. This study employed a dual-polarized array GPR system to inspect road pavements in London. The research involved comprehensive field testing, including data acquisition, signal processing, calibration, background noise removal, and 3D migration for enhanced imaging. Additionally, Short-Fourier Transform Spectrum (SFTS) analysis was applied to detect moisture-related anomalies. The results show that dual-polarized GPR systems effectively detect subsurface issues like voids, cracks, and moisture-induced weaknesses. The ability to capture data in multiple polarizations improves resolution and depth, enabling the identification of collapse-prone areas, particularly in regions with moisture infiltration. This study demonstrates the practical value of dual-polarized GPR technology in urban pavement inspection, offering a reliable tool for early detection of subsurface defects and contributing to the longevity and safety of road infrastructure. Full article

Advancing neuromorphic computing technology requires the development of versatile synaptic devices. In this study, we fabricated a high-performance Al/LiNbO₃/Pt memristive synapse and emulated various synaptic functions using its primary key operating mechanism, known as oxygen vacancy-mediated valence charge migration (V_O-VCM). The voltage-controlled V_O-VCM induced space-charge-limited conduction and self-rectifying asymmetric hysteresis behaviors. Moreover, the device exhibited voltage pulse-tunable multi-state memory characteristics because the degree of V_O-VCM was dependent on the applied pulse parameters (e.g., polarity, amplitude, width, and interval). As a result, synaptic functions such as short-term memory, dynamic range-tunable long-term memory, and spike time-dependent synaptic plasticity were successfully demonstrated by modulating those pulse parameters. Additionally, simulation studies on hand-written image pattern recognition confirmed that the present device performed with high accuracy, reaching up to 95.2%. The findings suggest that the V_O-VCM-based Al/LiNbO₃/Pt memristive synapse holds significant promise as a brain-inspired neuromorphic device. Full article

Recent advancements in novel fiber-coupled and portable terahertz (THz) spectroscopic imaging technology have accelerated applications in nondestructive testing (NDT). Although the polarization information of THz waves can play a critical role in material characterization, there are few demonstrations of polarization-resolved THz imaging as an NDT modality due to the deficiency of such polarimetric imaging devices. In this paper, we have inspected industrial carbon fiber composites using a portable and handheld imaging scanner in which the THz polarizations of two orthogonal channels are simultaneously captured by two photoconductive antennas. We observed significant polarimetric differences between the two-channel images of the same sample and the resulting THz Stokes vectors, which are attributed to the anisotropic conductivity of carbon fiber composites. Using both polarimetric channels, we can visualize the superficial and underlying interfaces of the first laminate. These results pave the way for the future applications of THz polarimetry to the assessment of coatings or surface quality on carbon fiber-reinforced substrates. Full article

The integrity of global elections is increasingly under threat from artificial intelligence (AI) technologies. As AI continues to permeate various aspects of society, its influence on political processes and elections has become a critical area of concern. This is because AI language models are far from neutral or objective; they inherit biases from their training data and the individuals who design and utilize them, which can sway voter decisions and affect global elections and democracy. In this research paper, we explore how AI can directly impact election outcomes through various techniques. These include the use of generative AI for disseminating false political information, favoring certain parties over others, and creating fake narratives, content, images, videos, and voice clones to undermine opposition. We highlight how AI threats can influence voter behavior and election outcomes, focusing on critical areas, including political polarization, deepfakes, disinformation, propaganda, and biased campaigns. In response to these challenges, we propose a Blockchain-based Deepfake Authenticity Verification Framework (B-DAVF) designed to detect and authenticate deepfake content in real time. It leverages the transparency of blockchain technology to reinforce electoral integrity. Finally, we also propose comprehensive countermeasures, including enhanced legislation, technological solutions, and public education initiatives, to mitigate the risks associated with AI in electoral contexts, proactively safeguard democracy, and promote fair elections. Full article

Event cameras, as bio-inspired visual sensors, offer significant advantages in their high dynamic range and high temporal resolution for visual tasks. These capabilities enable efficient and reliable motion estimation even in the most complex scenes. However, these advantages come with certain trade-offs. For instance, current event-based vision sensors have low spatial resolution, and the process of event representation can result in varying degrees of data redundancy and incompleteness. Additionally, due to the inherent characteristics of event stream data, they cannot be utilized directly; pre-processing steps such as slicing and frame compression are required. Currently, various pre-processing algorithms exist for slicing and compressing event streams. However, these methods fall short when dealing with multiple subjects moving at different and varying speeds within the event stream, potentially exacerbating the inherent deficiencies of the event information flow. To address this longstanding issue, we propose a novel and efficient Asynchronous Spike Dynamic Metric and Slicing algorithm (ASDMS). ASDMS adaptively segments the event stream into fragments of varying lengths based on the spatiotemporal structure and polarity attributes of the events. Moreover, we introduce a new Adaptive Spatiotemporal Subject Surface Compensation algorithm (ASSSC). ASSSC compensates for missing motion information in the event stream and removes redundant information, thereby achieving better performance and effectiveness in event stream segmentation compared to existing event representation algorithms. Additionally, after compressing the processed results into frame images, the imaging quality is significantly improved. Finally, we propose a new evaluation metric, the Actual Performance Efficiency Discrepancy (APED), which combines actual distortion rate and event information entropy to quantify and compare the effectiveness of our method against other existing event representation methods. The final experimental results demonstrate that our event representation method outperforms existing approaches and addresses the shortcomings of current methods in handling event streams with multiple entities moving at varying speeds simultaneously. Full article