Search Results (1,126)

Underwater image enhancement (UIE) serves as a fundamental preprocessing step in ocean remote sensing applications, encompassing marine life detection, archaeological surveying, and subsea resource exploration. However, UIE encounters substantial technical challenges due to the intricate physics of underwater light propagation and the inherent homogeneity of aquatic environments. Images captured underwater are significantly degraded through wavelength-dependent absorption and scattering processes, resulting in color distortion, contrast degradation, and illumination irregularities. To address these challenges, we propose a contrastive feature disentanglement network (CFD-Net) that systematically addresses underwater image degradation. Our framework employs a multi-stream decomposition architecture with three specialized decoders to disentangle the latent feature space into components associated with degradation and those representing high-quality features. We incorporate hierarchical contrastive learning mechanisms to establish clear relationships between standard and degraded feature spaces, emphasizing intra-layer similarity and inter-layer exclusivity. Through the synergistic utilization of internal feature consistency and cross-component distinctiveness, our framework achieves robust feature extraction without explicit supervision. Compared to existing methods, our approach achieves a 12% higher UIQM score on the EUVP dataset and outperforms other state-of-the-art techniques on various evaluation metrics such as UCIQE, MUSIQ, and NIQE, both quantitatively and qualitatively. Full article

Defining groups of ceramic objects from archaeological excavations is a crucial and primary practice in the study of settlements, providing information related to ceramic technology, provenance, and interactions, among others. This process begins with a macroscopic analysis of each fragment, identifying common features to define ceramic fabrics. Regularly, this procedure requires further analytical techniques to refine the attribution of each ceramic object to the corresponding fabric. The Early Neolithic site of Vale Pincel I in Sines, Portugal, dates to the second and third quarters of the sixth millennium BC. The earliest examples of ceramica impressa, described by patterned impressions on the surface (impresso pottery), in Portugal were found here. These artifacts are indicative of the Western Mediterranean Basin cycle pre-Cardial ceramic tradition. From the numerous Neolithic ceramic fragments discovered at Vale Pincel I, archaeologists identified 42 fragments, categorizing them into 2 main groups (A and B) through visual analysis, while a third group (C) remained unclassified. Group A, thick ceramic body with reddish hues and very friable surfaces; Group B, thin ceramic body with greyish to black shades and a cohesive appearance. With the aim to resolve the classification of group C ceramics, this study uses a multi-analytical methodology, combining Optical Microscopy (OM), Wavelength Dispersive X-Ray Fluorescence Spectroscopy (WD-XRF), and X‑Ray Diffraction (XRD). Integrating the analytical data with previously obtained archaeological information, Group C fragments were attributed to Groups A and B, demonstrating the absence of a distinct third group in Vale Pincel I, highlighting the effectiveness of analytical techniques in ceramic studies, and contributing to a deeper understanding of Neolithic ceramic technology in the Western Mediterranean Basin. Full article

Small targets with low radar cross-section (RCS) and high velocities are very hard to track by radar as long as the frequent variations in speed and location demand shorten the integration temporal window. In this paper, we propose a technique for tracking evasive targets using a continuous wave (CW) radar array of multiple transmitters operating in the millimeter wavelength (MMW). The scheme is demonstrated to detect supersonic moving objects, such as rifle projectiles, with extremely short integration times while utilizing an adaptive processing algorithm of the received signal. Operation at extremely high frequencies qualifies spatial discrimination, leading to resolution improvement over radars operating in commonly used lower frequencies. CW transmissions result in efficient average power utilization and consumption of narrow bandwidths. It is shown that although CW radars are not naturally designed to estimate distances, the array arrangement can track the instantaneous location and velocity of even supersonic targets. Since a CW radar measures the target velocity via the Doppler frequency shift, it is resistant to the detection of undesired immovable objects in multi-scattering scenarios; thus, the tracking ability is not impaired in a stationary, cluttered environment. Using the presented radar scheme is shown to enable the processing of extremely weak signals that are reflected from objects with a low RCS. In the presented approach, the significant improvement in resolution is beneficial for the reduction in the required detection time. In addition, in relation to reducing the target recording time for processing, the presented scheme stimulates the detection and tracking of objects that make frequent changes in their velocity and position. Full article

Hyperspectral imaging and laser technology both rely on different wavelengths of light to analyze the characteristics of materials, revealing their composition, state, or structure through precise spectral data. In hyperspectral image (HSI) classification tasks, the limited number of labeled samples and the lack of feature extraction diversity often lead to suboptimal classification performance. Furthermore, traditional convolutional neural networks (CNNs) primarily focus on local features in hyperspectral data, neglecting long-range dependencies and global context. To address these challenges, this paper proposes a novel model that combines CNNs with an average pooling Vision Transformer (ViT) for hyperspectral image classification. The model utilizes three-dimensional dilated convolution and two-dimensional convolution to extract multi-scale spatial–spectral features, while ViT was employed to capture global features and long-range dependencies in the hyperspectral data. Unlike the traditional ViT encoder, which uses linear projection, our model replaces it with average pooling projection. This change enhances the extraction of local features and compensates for the ViT encoder’s limitations in local feature extraction. This hybrid approach effectively combines the local feature extraction strengths of CNNs with the long-range dependency handling capabilities of Transformers, significantly improving overall performance in hyperspectral image classification tasks. Additionally, the proposed method holds promise for the classification of fiber laser spectra, where high precision and spectral analysis are crucial for distinguishing between different fiber laser characteristics. Experimental results demonstrate that the CNN-Transformer model substantially improves classification accuracy on three benchmark hyperspectral datasets. The overall accuracies achieved on the three public datasets—IP, PU, and SV—were 99.35%, 99.31%, and 99.66%, respectively. These advancements offer potential benefits for a wide range of applications, including high-performance optical fiber sensing, laser medicine, and environmental monitoring, where accurate spectral classification is essential for the development of advanced systems in fields such as laser medicine and optical fiber technology. Full article

Retinal degenerations, such as age-related macular degeneration and retinitis pigmentosa, present significant challenges due to genetic heterogeneity, limited therapeutic options, and the progressive loss of photoreceptors in advanced stages. These challenges are compounded by difficulties in precisely targeting residual retinal neurons and ensuring the sustained efficacy of interventions. Optogenetics offers a novel approach to vision restoration by inducing light sensitivity in residual retinal neurons through gene delivery of light-sensitive opsins. This review traces the evolution of opsins in optogenetic therapies, highlighting advancements from early research on channelrhodopsin-2 (ChR2) to engineered variants addressing key limitations. Red-shifted opsins, including ReaChR and ChrimsonR, reduced phototoxicity by enabling activation under longer wavelengths, while Chronos introduced superior temporal kinetics for dynamic visual tracking. Further innovations, such as Multi-Characteristic Opsin 1 (MCO1), optimized opsin performance under ambient light, bridging the gap to real-world applications. Key milestones include the first partial vision restoration in a human patient using ChrimsonR with light-amplifying goggles and ongoing clinical trials exploring the efficacy of opsin-based therapies for advanced retinal degeneration. While significant progress has been made, challenges remain in achieving sufficient light sensitivity for functional vision under normal ambient lighting conditions in a manner that is both effective and safe, eliminating the need for external light-enhancing devices. As research progresses, optogenetic therapies are positioned to redefine the management of retinal degenerative diseases, offering new hope for millions affected by vision loss. Full article

The multi-configurational Dirac–Hartree–Fock method has been used to examine the electron correlation effect on wavelengths and transition rates for $L\to K$ transitions occurring in He- and Li-like nickel ions. The collisional-radiative modelling approach has been used to simulate the X-ray spectra, in a 1.585–1.620 Å wavelength range, originating from the He-like nickel ions and their dielectronic Li-, Be-, and B-like satellites for various electron temperature values in the 2 keV to 8 keV range. The presented results may be useful in improving the plasma electron temperature diagnostics based on nickel spectra. Full article

A magic optical dipole trap (ODT) can confine atoms in the ground state and a highly excited state with the same light shifts, resulting in a long-range coherent lifetime between them, which plays an important role in high-fidelity quantum logic gates, multi-body physics and other quantum information. Here, we use a sum-over-states model to calculate the dynamic polarizabilities of the 6S_1/2 ground state and 46S_1/2 Rydberg state of Cs atoms and identify corresponding magic wavelengths and magic detunings for trapping the two states in the range of 900–1950 nm. Then, we analyze the robustness of the magic condition and the feasibility of the experimental operation. Furthermore, we estimate the trapping lifetime of Cs Rydberg atoms by considering different dissipation mechanisms, such as photon scattering and photoionization in the magic ODT. The photoexcitation and photoionization of Cs atoms under the action of three-step laser pulses are calculated by the rate equation. The presented results for magic-wavelength ODTs are of great significance for quantum information and quantum computing based on Rydberg atoms. Full article

The positions of millisecond pulsars (MSPs) can be determined with sub-milliarcsecond (mas) accuracy using both Very Long Baseline Interferometry (VLBI) and timing, referenced to the International Celestial Reference Frame (ICRF) and planetary ephemerides frame, respectively, representing kinematic and dynamical reference frames. The two frames can be connected through observations of common celestial objects, MSPs observed with VLBI and timing. However, previous attempts to establish this connection were unreliable due to the limited number of MSPs observed by both techniques. Currently, 23 MSPs have been precisely measured using both multiple timing and VLBI networks. Among them, 17 MSPs are used to link the two reference frames, marking a significant three-fold increase in the number of common MSPs used for frame linking. Nevertheless, six MSPs located near the ecliptic plane are excluded from frame linkage due to positional differences exceeding 20 mas measured by VLBI and timing. This discrepancy is primarily attributed to errors introduced in fitting positions in timing methods. With astrometric parameters obtained via both VLBI and timing for these MSPs, the precision of linking DE436 and ICRF3 has surpassed 0.4 mas. Furthermore, thanks to the improved timing precision of MeerKAT, even with data from just 13 MSPs observed by both MeerKAT and VLBI, the precision of linking DE440 and ICRF3 can also exceed 0.4 mas. The reliability of this linkage depends on the precision of pulsar astrometric parameters, their spatial distribution, and discrepancies in pulsar positions obtained by the two techniques. Notably, proper motion differences identified by the two techniques are the most critical factors influencing the reference frame linking parameters. The core shift of the calibrators in VLBI pulsar observations is one of the factors causing proper motion discrepancies, and multi-wavelength observations are expected to solve it. With the improvement in timing accuracy and the application of new observation modes like multi-view and multi-band observations in VLBI, the linkage accuracy of the dynamical and kinematic reference frames is expected to reach 0.3 mas. Full article

A switchable enhancement group delay in the terahertz band based on a novel sandwich topology protection structure with graphene is proposed in this paper. The notable phase transition of the reflected beam comes from the topological edge-protected mode excited at the sandwich photonic crystal surface, and the non-trivial topology of the photonic crystal allows the structure to be immune against defects and imperfections, which lays the foundation for the enhancement of group delay in the terahertz band. And the introduction of graphene creates favorable conditions for the reversible switching of positive and negative reflection group delay. Moreover, the reflected group delay can also be flexibly and dynamically controlled by the incident angle. The positive and negative reversible switching reflected group delay proposed in the terahertz band greatly reduces the optical transmission loss and significantly increases the transmission efficiency compared with the traditional metal sandwich structure, which provides a feasible idea for the realization of multi-dimensional manipulation of the wavelength and phase of electromagnetic waves in the terahertz band. The novel scheme is expected to provide potential applications in fields such as optical buffers or ultrafast modulators. Full article

Breast cancer remains a leading cause of cancer-related deaths among women, emphasizing the critical need for early detection and monitoring techniques. Conventional imaging modalities such as mammography, MRI, and ultrasound have face sensitivity, specificity, cost, and patient comfort limitations. This study introduces a handheld Near-Infrared Diffuse Optical Tomography (NIR DOT) probe for breast cancer imaging. The NIRscan probe utilizes multi-wavelength light-emitting diodes (LEDs) and a linear charge-coupled device (CCD) sensor to acquire real-time optical data, reconstructing cross-sectional images of breast tissue based on scattering and absorption coefficients. With wavelengths optimized for the differential optical properties of tissue components, the probe enables functional imaging, distinguishing between healthy and malignant tissues. Clinical evaluations have demonstrated its potential for precise tumor localization and monitoring therapeutic responses, achieving a sensitivity of 94.7% and specificity of 84.2%. By incorporating machine learning algorithms and a modified diffusion equation (MDE), the system enhances the accuracy and speed of image reconstruction, supporting rapid, non-invasive diagnostics. This development represents a significant step forward in portable, cost-effective solutions for breast cancer detection, with potential applications in low-resource settings and diverse clinical environments. Full article

Non-invasive haemoglobin (Hb) testing devices enable large-scale haemoglobin screening, but their accuracy is not comparable to traditional blood tests. To this end, this paper aims to design a non-invasive haemoglobin testing device and propose a classification-regression prediction framework for non-invasive testing of haemoglobin using visibility graphs (VG) with network clustering of multi-sample pulse-wave-weighted undirected graphs as the features to optimize the detection accuracy of non-invasive haemoglobin measurements. Different prediction methods were compared by analyzing 608 segments of multiwavelength fingertip PPG signal data from 152 volunteers and analyzing and comparing the data and methods. The results showed that the classification using NVG with complex network clustering as features in the interval classification model was the best, with its classification accuracy (acc) of 93.35% and model accuracy of 88.28%. Among the regression models, the classification regression stack: SVM-Light Gradient Boosting Machine (LGBM) was the most effective, with a Mean Absolute Error (MAE) of 6.67 g/L, a Root Mean Square Error (RMSE) of 8.21 g/L, and an R-Square (R2) of 0.64. The results of this study indicate that the use of complex network technology in non-invasive haemoglobin detection can effectively improve its accuracy, and the detector designed in this study is promising to carry out a more accurate large-scale haemoglobin screening. Full article

The spatial correlation of wall pressure fluctuations is a crucial parameter that affects the structural vibration caused by a turbulent boundary layer (TBL). Although the phase-array technique is commonly used in industry applications to obtain this correlation, it has proven to be effective only for moderate frequencies. In this study, an artificial neural network (ANN) method was developed to calculate the convective speed, indicating the spatial correlation of wall pressure fluctuations and extending the frequency range of the conventional phase-array technique. The developed ANN system, based on a radial basis function (RBF), has been trained using discrete simulated data that follow the physical essence of wall pressure fluctuations. Moreover, a normalization method and a multi-parameter average (MPA) method have been employed to improve the training of the ANN system. The results of the investigation demonstrate that the MPA method can expand the frequency range of the ANN, enabling the maximum analysis frequency of convective velocity for aircraft wall pressure fluctuations to reach over 10 kHz. Furthermore, the results reveal that the ANN technique is not always effective and can only accurately calculate the wavenumber when the standard wavelength is less than four times the width of the sensor array along the flow direction. Full article

Over the course of NASA’s Dawn Discovery mission, the onboard framing camera mapped Ceres across a wide wavelength spectrum at varying polar science orbits and altitudes. With increasing resolution, the uniqueness of the 92 km wide, young Occator crater became evident. Its central cryovolcanic dome, Cerealia Tholus, and especially the associated bright carbonate and ammonium chloride deposits—named Cerealia Facula and the thinner, more dispersed Vinalia Faculae—are the surface expressions of a deep brine reservoir beneath Occator. Understandably, this made this crater the target for future sample return mission studies. The planning and preparation for this kind of mission require the characterization of potential landing sites based on the most accurate topography and orthorectified image data. In this work, we demonstrate the capabilities of the freely available and open-source USGS Integrated Software for Imagers and Spectrometers (ISIS 3) and Ames Stereo Pipeline (ASP 2.7) in creating high-quality image data products as well as stereophotogrammetric (SPG) and multi-view shape-from-shading (SfS) digital terrain models (DTMs) of the aforementioned spectroscopically challenging features. The main data products of our work are four new DTMs, including one SPG and one SfS DTM based on High-Altitude Mapping Orbit (HAMO) (CSH/CXJ) and one SPG and one SfS DTM based on Low-Altitude Mapping Orbit (LAMO) (CSL/CXL), along with selected Extended Mission Orbit 7 (XMO7) framing camera (FC) data. The SPG and SfS DTMs were calculated to a GSD of 1 and 0.5 px, corresponding to 136 m (HAMO SPG), 68 m (HAMO SfS), 34 m (LAMO SPG), and 17 m (LAMO SfS). Finally, we show that the SPG and SfS approaches we used yield consistent results even in the presence of high albedo differences and highlight how our new DTMs differ from those previously created and published by the German Aerospace Center (DLR) and the Jet Propulsion Laboratory (JPL). Full article

When radiation from a background source passes through a cloud of cold plasma, diverging lensing occurs if the source and observer are well-aligned. Unlike gravitational lensing, plasma lensing is dispersive, increasing in strength with wavelength. The Drude model is a generalization of cold plasma, including absorbing dielectric dust described by a complex index of refraction. The Drude lens is only dispersive for wavelengths shorter than the dust characteristic scale ($\lambda \ll {\lambda }_d$). At sufficient photon energy, the dust particles act like refractive clouds. For longer wavelengths $\lambda \gg {\lambda }_d$, the optical properties of the Drude lens are constant, unique behavior compared to the predictions of the cold plasma lens. Thus, cold plasma lenses can be distinguished from Drude lenses using multi-band observations. The Drude medium extends the applicability of all previous tools, from gravitational and plasma lensing, to describe scattering phenomena in the X-ray regime. Full article

A novel bacterial cellulose (BC)-based composite hydrogel with graphene quantum dots (BC-GQDs) was developed for photodynamic therapy using blue and green light (BC-GQD_blue and BC-GQD_green) to target pathogenic bacterial biofilms. This approach aims to address complications in treating nosocomial infections and combating multi-drug-resistant organisms. Short-term illumination (30 min) of both BC-GQD samples led to singlet oxygen production and a reduction in pathogenic biofilms. Significant antibiofilm activity (>50% reduction) was achieved against Staphylococcus aureus and Escherichia coli with BC-GQD_green, and against Pseudomonas aeruginosa with BC-GQD_blue. Atomic force microscopy images revealed a substantial decrease in biofilm mass, accompanied by changes in surface roughness and area, further confirming the antibiofilm efficacy of BC-GQDs under blue and green light, without any observed chemical alterations. Additionally, the biocompatibility of BC-GQDs was demonstrated with human gingival fibroblasts (HGFs). For the first time, in vitro studies explored the visible light-induced potential of BC-GQD composites to promote wound healing processes, showing increased migratory potential and the upregulation of eNOS and MMP9 gene expressions in HGFs. Chemical characterization revealed a 70 nm upshift in the photoluminescence emission spectra compared to the excitation wavelength. These novel photoactive BC-GQD hydrogel composites show great promise as effective agents for wound healing regeneration and infection management. Full article