Search Results (5,395)

Electrochemiluminescence immunoassay (ECLIA) is widely used in clinical diagnostics owing to its high sensitivity, broad dynamic range, and excellent analytical stability. However, the influence of magnetic bead deposition behavior on electrochemiluminescence (ECL) signal performance remains insufficiently characterized. In this study, a quantitative evaluation method for magnetic bead distribution uniformity on the electrode surface was established and applied to optimize fluidic parameters in an ECLIA measurement system. By combining microscopic imaging with image analysis, magnetic bead spreading behavior under different flow conditions was systematically characterized and correlated with luminescence signal intensity. Optimization of the flow rate (18.46 µL·s⁻¹) improved bead distribution uniformity and resulted in a 26.32% increase in luminescence intensity without altering bead coverage or assay chemistry. The optimized system was further validated using thyroid-stimulating hormone (TSH) detection, showing a linear response over 0.016–120 µIU·mL⁻¹ (R² > 0.996) and high consistency with a commercial analyzer (R² = 0.998) from Roche. These results demonstrate that quantitative control of magnetic bead distribution provides an effective strategy for improving ECLIA performance and offers a general optimization framework for bead-based electrochemiluminescence systems. Full article

Laser trackers (LTs) are essential instruments for large-scale equipment assembly and in situ measurement. However, their cooperative targets, Spherically Mounted Retroreflectors (SMRs), are often small, highly reflective, and prone to interference in complex industrial environments, making accurate detection difficult. Compared with generic small-object detection, SMR detection during LT beam reacquisition is further challenged by specular highlights, halo-like blooming, and reflective background clutter, where SMRs may appear as minute bright spots with ambiguous boundaries. In this paper, we propose RBD-YOLOv10n, a lightweight detector tailored for SMRs based on the YOLOv10 framework. To improve robustness while keeping deployment efficient, we introduce three lightweight enhancements across the backbone, neck, and head, including RepNMSC, W-BiFPN, and DEHead. Validated on a custom SMR dataset, our method achieves an mAP@0.5 of 93.24% and an mAP@0.5:0.95 of 78.45%. Notably, the model is extremely lightweight, with 1.98M parameters and a 4.30 MB weight file (stored in FP16). These results show that the proposed method outperforms representative baseline detectors in balancing accuracy and efficiency, supporting practical high-precision LT vision-based SMR reacquisition under industrial conditions. Full article

A high-resolution flat-field grating spectrometer has been employed at the Livermore EBIT-I electron beam ion trap for observations of extreme-uv spectra of Ni-like ions Xe${}^{26+}$ and Co-like ions Xe${}^{27+}$. Multistep ionisation involving the long-lived 3d${}^9$ 4s ${}^3$D${}_3$ level in the Ni-like ion as a stepping stone has a significant influence on the charge state distribution at a given electron beam energy, as has been reported elsewhere. Complementing those observations of 3d-4s $E2$ and $M3$ transitions from long-lived levels, the present report shows spectra of 3d-4p and 3d-4f $E1$ transitions that arise from the decays of short-lived levels in both ions and their neighbouring ions of higher charge states and provide bright reference signals for the changes in the charge state distribution. Their observation is serendipitously furthered by the visual absence of 3d-4d transitions from the observed spectra, although $M1$ and $E2$ transitions between these configurations are permitted. Full article

This paper reports initial experimental results related to the preparation of colored anodic titania thin layers using various deep eutectic solvent (DES)-based formulations. Electrolytes based on choline dihydrogen citrate–oxalic acid–ethylene glycol (1:1:1 molar ratio), choline chloride–oxalic acid (1:1 molar ratio) and choline chloride–lactic acid (1:2 molar ratio) eutectic mixtures were investigated. The anodization has been performed at constant voltage in a range of 10–100 V for various periods of time between 1 and 5 min at room temperature under mild stirring. A brief description of anodization procedures, as well as of some characteristics, from appearance and morphological viewpoints, is presented. A quantitative analysis of color characteristics in relation to the DES-based electrolyte and applied voltage using the CIELAB system is also discussed. The achieved chromatic scale follows this order of colors: golden—blue—light blue—light blue/green—pink—violet. This depends on the applied potential and the DES-based electrolyte. The films present a relatively high brightness and color saturation. The hue vs. anodization voltage diagrams suggest an almost linear dependence of the oxide growth measured against the applied voltage. The corrosion performance has been assessed through continuous immersion tests in (i) 0.5 M NaCl for 240 h and (ii) Hank’s biological solution for 96 h with intermediate visual examinations and recording corrosion potential, as well as potentiodynamic polarization curves and impedance spectra at open circuit potential. Different corrosion performances are discussed considering the aggressive medium involved and the used DES-based systems. Full article

A (0001) α-Ga₂O₃ film was grown by the mist chemical vapor deposition method on a (0001) α-Cr₂O₃ template (100 μm thick α-Cr₂O₃ layer formed on an α-Al₂O₃ substrate). Benefiting from the small a-axis lattice mismatch between α-Ga₂O₃ and α-Cr₂O₃, a high-quality α-Ga₂O₃ film with a small twist distribution, and consequently a low edge dislocation density, was coherently grown on an α-Cr₂O₃ template. The edge dislocation density of 7 × 10⁷ cm⁻², estimated from the full-width at half-maximum value of the X-ray rocking curve (XRC) in X-ray diffraction (XRD), was more than two orders of magnitude lower than that of the film grown on an α-Al₂O₃ substrate, and was almost consistent with that of the α-Cr₂O₃ template. The bright-field transmission electron microscopy (TEM) image supports the dislocation density estimated from the XRD measurements. The high-angle annular dark-field scanning TEM and inverse fast Fourier transform images indicate coherent growth, with almost no misfit dislocations generated at the α-Ga₂O₃/α-Cr₂O₃ interface. Full article

Port areas are core hubs for national logistics and high-risk security zones that require constant vehicle access control. However, ensuring the reliability of automatic license plate recognition (ALPR) systems in port environments is severely challenged by complex image degradations, such as dense haze, low light, and motion blur. In this study, we propose a stage-wise degradation-aware restoration network (SDR-Net), which effectively addresses harsh port conditions by sequentially restoring photometric and structural degradations. Particularly, SDR-Net first secures visual cues lost to haze and low light through a photometric restoration module involving a dark-channel-prior-based dehazing and adaptive brightness adjustment. Next, a structural restoration module based on a generative adversarial network featuring edge-guided structural feature blocks and edge-aware refinement blocks is employed to precisely reconstruct character strokes and outlines damaged by motion blur, stably restoring license plate legibility even under complex degradation conditions. Experiments across various intensities of complex degradation demonstrate that SDR-Net maintains high character recognition accuracies of over 97.35% under mild motion blur and low-concentration haze conditions, indicating its superiority over state-of-the-art models. Notably, the performance gap between SDR-Net and comparison models widened as the degradation intensity increased, and SDR-Net achieved the highest multiscale structural similarity index scores across all intervals. Full article

This paper addresses the problem of multi-class classification of bacterial microscopic images using a rigorous experimental protocol designed to prevent information leakage and improve performance. The dataset consists of 2034 images representing 33 taxa, organized by class. Data integrity checks confirmed the absence of corrupted or unreadable files. To formalize image characteristics and ensure quality control, indirect geometric and textural features were calculated, including minimum frame size, brightness statistics (mean and standard deviation), Shannon entropy, Laplace variance, and Sobel gradient energy. Quality checks revealed a small proportion of images with extreme brightness (2.5074%), while no samples with critically low sharpness according to the selected criteria were detected. Statistical analysis of interclass differences using the Kruskal–Wallis test with multiple comparison correction demonstrated the high discriminatory power of texture features, specifically gradient energy (ε² = 0.819987) and Laplace variance (ε² = 0.709904). Feature correlations were consistent with their physical interpretation, revealing a strong positive relationship between sharpness and gradient energy. Principal component analysis confirmed a strong structural pattern, with the first two components explaining 75.5766% of the total variance. For a unified comparison, classical machine learning, transfer learning, and modern deep architectures were evaluated within a single protocol. Full article

Light is the primary zeitgeber for circadian rhythms, and also through these mechanisms, is closely related to mood regulation. Bright light therapy (BLT) is a therapeutic intervention that specifically exploits this physiological mechanism. This review summarizes the clinical procedures of BLT, the mechanisms through which light influences circadian rhythms and mood, and the evidence supporting BLT in psychiatric disorders. BLT is administered by considering device distance, treatment duration, and light intensity. Through pathways originating in the retina and projecting to the Suprachiasmatic Nucleus (SCN), light might generate signals within the central nervous system that influence not only circadian regulation but also mood, via connections involving the limbic system, the lateral habenula, and interactions with the hormonal system. At the clinical level, the strongest evidence for BLT concerns seasonal affective disorder, but data also indicate antidepressant efficacy in major depressive disorder and bipolar disorder, with an excellent tolerability profile. Emerging evidence further suggests benefits for insomnia, and sporadic and heterogeneous findings have explored its potential role in other conditions. Future studies are needed to better define the role of BLT in additional psychiatric disorders and in specific symptom domains that may not adequately respond to standard treatments, such as sexual dysfunction. Full article

This study proposes a novel low-light image enhancement network that incorporates a frequency cross-attention mechanism in the wavelet domain. The proposed network enhances brightness through the low-frequency wavelet subband while simultaneously restoring fine details in the high-frequency subbands. Color degradation during the brightening process is prevented by applying a color-preserving block based on the saturation component before the illumination adjustment. Furthermore, U-shaped lightening and multiscale sharpening blocks are designed to enhance the image brightness and detail, respectively. The disruption of intrinsic symmetry in coefficient correlations poses a major challenge in independently processing wavelet subbands. To address this issue, we propose a frequency cross-attention block that enables effective information exchange between subbands, thereby preserving their inherent correlations. The proposed network produces visually consistent and refined outputs by balancing the enhanced wavelet subbands. Experimental evaluations demonstrate that the proposed network achieves competitive performance in both subjective quality and objective metrics, confirming its effectiveness for low-light image enhancement. Full article

Accurate color property measurements are critical for advancing artificial vision in real-time industrial applications. RGB imaging remains highly applicable and widely used due to its practicality, accessibility, and high spatial resolution. However, significant uncertainties in extracting chromatic information highlight the need to define when conventional digital images can reliably provide accurate color data. This work simultaneously compares six chromatic properties across 700 Pantone^® TCX fabric samples, using optical data acquired simultaneously from both hyperspectral (HSI) and digital (RGB) cameras. The results indicate that the accurate interpretation of optical information from RGB (sRGB and REC2020) images is significantly influenced by lightness ($L^{*}$) values. Samples with bright and unsaturated colors ($L^{*}>$ 50) reach ratio-to-performance-deviation (RPD) values above 2.5 for four properties ($L^{*}, a^{*}, b^{*}$ $h_{ab}$), indicating a good correlation between HSI and RGB information. Absolute color difference comparisons (${∆E}_a$) between HSI and RGB images yield values exceeding 5.5 units for red-yellow-green samples and up to 9.0 units for blue and purple tones. In contrast, relative color differences (${∆E}_r$) comparisons show a significant decrease, with values falling below 3.0 for all lightness values, indicating the practical equivalence of both methodologies according to the Two One-Sided Test (TOST) statistical analysis. These results confirm that RGB imagery achieves reliable color consistency when evaluated against a practical reference. Full article

This study addresses the challenge of through-hole defects in ZM6 cast magnesium alloy components by proposing an innovative repair strategy using ultrasonic-assisted Tungsten Inert Gas (U-TIG) welding. The microstructure and mechanical properties of the repaired joint were systematically characterized through optical microscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), and room-temperature tensile testing. The results indicate that, assisted by the ultrasonic energy field, the repair zone successfully reconstitutes a typical and optimized triple-phase microstructure: (1) the matrix: α-Mg solid solution (dark gray), supersaturated with Nd and Zr; (2) the strengthening phase: a eutectic Mg₁₂Nd phase (light gray), rich in Nd, distributed along grain boundaries acting as the primary strengthening component; (3) the grain refiner: dispersed Zr-rich particles (bright white spots), which effectively pin grain boundaries. Crucially, the application of ultrasound significantly refined the α-Mg grains and transformed the continuous network of the Mg₁₂Nd phase into a more fragmented and uniform dispersion. This refined microstructure synergistically integrates the strengthening mechanisms of solid solution, precipitation hardening, and grain refinement. Consequently, the repaired joint exhibits excellent mechanical properties, achieving over 90% of the base metal’s tensile strength and elongation at room temperature. This work not only validates the feasibility of U-TIG welding for repairing ZM6 alloys but also provides a solid theoretical foundation and a promising technical pathway for the in-service repair and remanufacturing of high-performance magnesium alloy components. Full article

Serial flow cytometry was recently introduced as a method that can estimate measurement uncertainty (i.e., imprecision, the coefficient of variation of repeated measurements of individual particles) independent from population characteristics. Replication of light sources and detectors at multiple sites along a flow cytometer’s microchannel requires more equipment and can complicate detector synchronization. Here, we introduce amplitude modulation to encode each region of a serial cytometer with a unique carrier frequency, which enables demultiplexing of the combined signal incident on a single photodetector by fast Fourier transform (FFT) peak magnitude. To facilitate validation of detection, matching, and uncertainty quantification of fluorescence signals, we designed a microfluidic amplitude modulation (AM) serial flow cytometer that has ground truth detectors on individual regions (serial cytometry) in parallel with the combined channel detection for AM demultiplexing. With this report, we present metrics for event detection and dynamic range, prevalence and processing of overlapping detections, region-decoding accuracy, process yield, and uncertainty quantification on a brightness ladder of calibration microspheres. Despite being operated with reduced light intensities, the AM cytometer was capable of high-fidelity performance in comparison to conventional serial cytometry. For events above the detection limit, over 97% were analyzed. Both conventional and AM serial cytometers achieved median imprecisions in the range of 0.53% to 2.1% after outlier removal, which was well below the inherent intensity distribution of any of the microsphere subpopulations. Overall, AM cytometry supports uncertainty quantification and temporal analyses of serial cytometry data with a reduced number of photodetectors, which offers simplification of chip design with multiple measurement regions and wide-field detectors. Full article

In this paper, the authors developed a data-driven model to classify radar measurements into precipitation (P) and non-precipitation (NP) echoes using the Random Forest machine learning algorithm. Dual-polarimetric radar variables and their local variability exhibit distinctive characteristics between P and NP echoes. The authors found that using larger search window sizes generally improves classification accuracy, though it involves a trade-off: while it helps eliminate small clusters of NP echoes, it may also suppress weak precipitation signals near storm edges. Incorporating multiscale local variability estimates computed with varying window sizes further enhances classification performance by capturing spatial-scale-dependent features characteristic of P and NP echoes. The main model uses radar variables obtained from a single scan and demonstrates consistent performance across all distances from the radar. This consistency allows reliable use of the model out to 230 km—the maximum range at which dual-polarimetric variables are used for rainfall estimation from NEXRAD radars—without significant degradation in accuracy due to range effects. Supplementing the model with independent information from GOES-16 infrared channel products further improves classification by helping to eliminate localized NP echoes remaining after the main model, particularly those caused by wind turbines that mimic precipitation in dual-polarimetric signatures. This is based on the tendency of water vapor and/or raindrops to absorb terrestrial radiation, thereby lowering brightness temperatures. A practical challenge remains near the radar, where the sampling volume is small and signal processing (e.g., sidelobe impact and ground clutter suppression) can distort radar measurements. The under-detection of precipitation in these regions is likely due to such corrupted data. This issue may be mitigated by adopting a hybrid scan strategy—such as a Constant Altitude Plan Position Indicator (CAPPI)—specifically for regions close to the radar. Full article

Pandemic influenza remains a persistent global threat with the potential to cause widespread morbidity, mortality, and economic disruption. Despite decades of preparedness efforts, current influenza vaccine systems remain constrained by long production timelines, early strain-selection requirements, and limited flexibility once a pandemic is underway. The COVID-19 pandemic fundamentally reshaped expectations for vaccine development and deployment, demonstrating that platform-based technologies, particularly messenger RNA (mRNA) vaccines, can deliver safe and effective vaccines at unprecedented speed when supported by regulatory readiness, manufacturing capacity, and coordinated public–private investment. Drawing on lessons from COVID-19, recent Phase III clinical trial data for seasonal influenza mRNA vaccines, and global preparedness initiatives such as the 100 Days Mission, this expert perspective examines how mRNA and other next-generation vaccine technologies could strengthen preparedness for a future influenza pandemic. It reviews evidence related to platform speed, clinical performance, manufacturing adaptability, regulatory pathways, and global access, while also highlighting emerging scientific frontiers, including artificial intelligence–augmented immunogen design and innovations in vaccine delivery. It argues that sustained investment in adaptable vaccine platforms, coupled with advances in delivery, manufacturing, and data-driven design, will be critical to improving global readiness and reducing the impact of the next influenza pandemic. Full article

This paper focuses on a high-order Korteweg–de Vries wave equation. The extended F-expansion method, a modified form of Kudryashov’s auxiliary equation approach, is employed to construct Jacobi elliptic function solutions for this equation. Three distinct families of solutions are obtained, including solitary waves, breathers, dark/bright solitons, bright–dark interaction solitons, and rogue-like solutions. To better illustrate the complex nonlinear dynamics of the high-order Korteweg–de Vries wave equation, representative solutions are selected, and their moduli are visualized using Maple software through three-dimensional, two-dimensional, and contour plots. Full article