Search Results (1,341)

The sustained interest in efficient, low-cost, and straightforward-to-manufacture lasers has prompted intense research into organic semiconductor laser emitter materials in recent decades. The main focus of this research is determining the optical gains and losses of amplified spontaneous emission (ASE) in order to describe materials by their amplification signature. A method that has been used for decades as the standard technique for determining gain characteristics is the variable-stripe-length (VSL) method. The success of the VSL method has led to the development of further measurement techniques. These techniques provide a detailed insight into the nature of optical amplification. One such method is the scattered emission profile (SEP) method. In this study, we present an extension of the SEP method, the Diffracted Emission Profile (DEP) method. The DEP method is based on the detection of ASE by partial decoupling of waveguide modes diffracted by a one-dimensional grating integrated into a planar waveguide. Diffraction causes a proportion of the intensity to exit the waveguide, transferring the growth and decay process of the waveguide mode to the transverse mode profile of the diffracted mode. In the present article, an approach to determine the amplification signature of an organic copolymer is presented, utilizing partial decoupled radiation. Full article

In this study, the optical gain characteristics of a green laser sample based on a III-Nitride InGaN single-quantum-well structure were investigated. The Green gap phenomenon, caused by bandgap fluctuations due to inhomogeneous indium composition and the quantum-confined Stark effect (QCSE), has been a major obstacle in achieving high efficiency and high output in green-light-emitting devices. To address these issues, a sample grown on a (0001)-oriented GaN substrate with a single-quantum-well active layer was fabricated to suppress In composition non-uniformity and enhance the overlap of electron and hole wavefunctions. The optical gain behavior was analyzed using the Variable Stripe Length Method (VSLM) under various excitation densities and stripe lengths ($L_{cav}$). The results showed that as the stripe length increased, the spectral linewidth decreased and stimulated emission occurred at lower excitation densities. However, excessive cavity length led to gain saturation and a red shift in the peak wavelength due to Joule heating effects. These findings provide essential insights for determining the optimal cavity length in laser diode fabrication and are expected to serve as fundamental guidelines for improving the efficiency and output power of III-Nitride-based green laser diodes. Full article

The imaging quality of uncooled long wave infrared (IR) cameras is always limited by the stripe non-uniformity mainly caused by fixed pattern noise (FPN). In this paper, we propose an adaptive dual-frequency denoising network-based stripe non-uniformity correction (NUC) method, namely ADFDNet, to realize the balance between FPN removal and image detail preservation. Our ADFDNet takes the dual-frequency feature deconstruction module as its core, which decomposes the IR image into high-frequency and low-frequency features, and performs targeted processing through detail enhancement branches and sparse denoising branches. The former enhances the performance of detail preservation through multi-scale convolution and pixel attention mechanism, while the latter combines sparse attention mechanism and dilated convolution design to suppress high-frequency FPN. Furthermore, the dynamic weight fusion of features is realized using the adaptive dual-frequency fusion module, which better integrates detail information. In our study, a 420-pair image dataset covering different noise levels is constructed for better model training and evaluation. Experiments verify that the presented ADFDNet method significantly improves image clarity in both real and simulated noise scenes, and achieves a better balance between FPN suppression and detail preservation than other existing methods. Full article

The photovoltaic (PV) bands on the mid-wave and long-wave infrared (MWIR and LWIR) cold focal plane assemblies of Terra and Aqua MODIS have suffered from gradually increasing electronic crosstalk contamination as both instruments have continued to operate in their extended missions, respectively. This contamination has considerable impact, particularly for the PV LWIR bands, which includes image striping and radiometric bias in the Level-1B (L1B)-calibrated radiance products as well as higher level (and mostly atmospheric but also land and oceanic) products (e.g., cloud phase particle, cloud mask, land and sea surface temperatures). The crosstalk was characterized early in the mission, and test corrections were developed then. Ultimately, the groundwork for a robust electronic crosstalk correction algorithm was developed in 2016 and implemented in MODIS Collection 6.1 (C6.1) back in 2017 for the Terra MODIS PV LWIR bands. It was later introduced in Aqua MODIS C6.1 for the same group of bands in April 2022. Additional improvements were made in MODIS Collection 7 (C7) to better characterize the electronic crosstalk in the PV LWIR bands, and the electronic crosstalk correction algorithm was also extended to select detectors in the MODIS MWIR bands. This work will describe the electronic crosstalk correction algorithm and its application on the MODIS L1B product, the differences in application between C6.1 and C7, as well as additional improvements made to enhance the contamination correction and improve image quality for the Aqua MODIS PV LWIR bands. The electronic crosstalk correction coefficient time series for the MODIS PV bands will be discussed, and some cases will be presented to illustrate how image quality improves on the L1B and Level 2 products after the correction is applied. Lastly, experiences gained regarding the PV bands electronic crosstalk and the strategy used to correct it will be discussed to provide future data users and scientists with an insight as to how to improve on the legacy record that the Terra and Aqua MODIS sensors will leave behind after both spacecrafts are decommissioned. Full article

Background: The striped hyena (Hyaena hyaena) occurs in a wide range from north and east Africa, through southwest Asia to India, but its distribution is increasingly patchy and many of its populations are in decline due to intense human pressure. Its genetic diversity and structure, phylogeography, and evolutionary history, remain poorly understood. Methods: In this study, we investigated mitochondrial DNA variation in Algerian striped hyenas. Moreover, with the aim of contributing to our understanding of the evolutionary history of the species, we also examined samples from other geographic regions and compared our results with those of the only previous study in which individuals from across the range of the species were analyzed. In particular, we performed a wide range of analyses of demographic history and estimation of the age of the extant mitochondrial DNA variation. Results and Conclusions: The Algerian population sample was monomorphic. Overall, the global patterns of genetic diversity and the results of some demographic history analyses support a scenario of population growth in the species, estimated to have occurred in the Late Pleistocene, but many of the analyses did not detect a significant signal of growth, most likely a result of the limited power provided by a small number of segregating sites. The estimates, from three different methods, for the time to the most recent common ancestor (TMRCA) of the mitochondrial DNA variation hovered around 400 ka, coinciding with one of the longest and warmest interglacials of the last 800,000 years, with environmental conditions similar to the Holocene. Full article

The radial sand-ridge field off the Jiangsu coast is a distinctive landform in a strongly tide-dominated environment, where sediment supply and geomorphic patterns have been profoundly altered by Yellow River course changes, reduced Yangtze-derived sediment, and large-scale reclamation. Focusing on a typical nearshore sector off Dongtai, this study integrates multi-source data from 1979 to 2025, including historical nautical charts, high-precision engineering bathymetry, full-tide hydro-sediment observations, and surficial sediment samples, to quantify seabed erosion–deposition over 46 years and clarify linkages among tidal currents, suspended-sediment transport, and surface grain-size patterns. Surficial sediments from Maozhusha to Jiangjiasha channel systematically fine from north to south: sand-ridge crests are dominated by sandy silt, whereas tidal channels and transition zones are characterized by silty sand and clayey silt. From 1979 to 2025, Zhugensha and its outer flank underwent multi-meter accretion and a marked accretion belt formed between Gaoni and Tiaozini, while the Jiangjiasha channel and adjacent deep troughs experienced persistent scour (local mean rates up to ~0.25 m/a), forming a striped “ridge accretion–trough erosion” pattern. Residual and potential maximum currents in the main channels enhance scour and offshore export of fines, whereas relatively strong depth-averaged flow and near-bed shear on inner sand-ridge flanks favor frequent mobilization and short-range trapping of coarser particles. Suspended-sediment concentration and median grain size are generally positively correlated, with suspension coarsening in high-energy channels but dominated by fine grains on nearshore flats and in deep troughs. These findings refine understanding of muddy-coast geomorphology under strong tides and may inform offshore wind-farm foundation design, navigation-channel maintenance, and coastal-zone management. Full article

This study investigates the influence of solar flare events on the time–frequency characteristics of very low frequency (VLF) signals based on observations from the China Seismo–Electromagnetic Satellite (CSES) satellite. By analyzing the VLF electromagnetic wave HDF5 data downloaded on the day of the solar flare, the data were converted into a sequence of spectrograms, and linear structures within them were identified using image processing techniques and the K-means clustering algorithm. In this work, we detect more than twenty candidate transient near-vertical stripe elements (image-domain linear features) in the VLF spectrograms on solar-flare event days and use them as an operational texture fingerprint for large-scale screening. This finding suggests that solar flare events may trigger pulse sequence phenomena in VLF signals, providing new observational evidence for understanding the impact of solar activity on the ionosphere and offering a new perspective for investigating solar-flare effects using VLF signals. Full article

Addressing the difficulty of intuitively identifying and effectively correcting induced heave error in multibeam measurements, this paper proposes a two-stage methodology comprising error identification and correction. This scheme includes an error discrimination method based on regression diagnostics and an error correction method based on Partial Least Squares Regression (PLSR). By establishing a mathematical model between bathymetric discrepancies and attitude parameters, statistical diagnosis and effective identification of the error are achieved. To further mitigate the impact of induced heave error on bathymetric data, an elimination model based on PLSR is developed, enabling high-precision prediction and compensation of the induced heave error. Validation using field survey data demonstrates that this method can effectively estimate the installation offset parameters of the attitude sensor. After correction, the root mean square of bathymetric discrepancies between adjacent survey lines is reduced by approximately 78.8%, periodic stripe-shaped distortions along the track direction are essentially eliminated, and the quality of terrain mosaicking is significantly improved. This provides an effective solution for controlling induced heave error under complex topographic conditions. Full article

With the deployment of mega-constellations, the proliferation of on-orbit Resident Space Objects (RSOs) poses a severe challenge to Space Situational Awareness (SSA). RSOs produce elongated and stripe-like signatures in long-exposure imagery as a result of their relative orbital motion. The accurate detection of these signatures is essential for critical applications like satellite navigation and space debris monitoring. However, on-orbit detection faces two challenges: the obscuration of dim RSOs by complex stray light interference, and their dense overlapping trajectories. To address these challenges, we propose the Shape-Aware Attention Network (SAANet), establishing a unified Shape-Aware Paradigm. The network features a streamlined Shape-Aware Feature Pyramid Network (SA-FPN) with structurally integrated Two-way Orthogonal Attention (TTOA) to explicitly model linear topologies, preserving dim signals under intense stray light conditions. Concurrently, we propose an Adaptive Linear Oriented Bounding Box (AL-OBB) detection head that leverages a Joint Geometric Constraint Mechanism to resolve the ambiguity of regressing targets amid dense, overlapping trajectories. Experiments on the AstroStripeSet and StarTrails datasets demonstrate that SAANet achieves state-of-the-art (SOTA) performance, achieving Recalls of 0.930 and 0.850, and Average Precisions (APs) of 0.864 and 0.815, respectively. Full article

The extraction of the light stripe center is a pivotal step in line-structured light vision measurement. This paper addresses a key challenge in the online measurement of train wheel treads, where the diverse and complex profile characteristics of the tread surface lead to uneven gray-level distribution and varying width features in the stripe image, ultimately degrading the accuracy of center extraction. To solve this problem, a region-adaptive multiscale method for light stripe center extraction is proposed. First, potential light stripe regions are identified and enhanced based on the gray-gradient features of the image, enabling precise segmentation. Subsequently, by normalizing the feature responses under Gaussian kernels with different scales, the locally optimal scale parameter (σ) is determined adaptively for each stripe region. Sub-pixel center extraction is then performed using the Hessian matrix corresponding to this optimal σ. Experimental results demonstrate that under on-site conditions featuring uneven wheel surface reflectivity, the proposed method can reliably extract light stripe centers with high stability. It achieves a repeatability of 0.10 mm, with mean measurement errors of 0.12 mm for flange height and 0.10 mm for flange thickness, thereby enhancing both stability and accuracy in industrial measurement environments. The repeatability and reproducibility of the method were further validated through repeated testing of multiple wheels. Full article

Leaves are the primary photosynthetic organs, and alterations in leaf color can affect photosynthesis and plant biomass. In an EMS-mutagenized SN9816 population, we identified two white-striped mutants, ws21-1 and ws21-2. Both mutants showed severely reduced pigment content, defective chloroplasts, and elevated reactive oxygen species. The ws21-2 allele caused a near-complete albino phenotype, while ws21-1 resulted in milder striping. Genetic mapping and cloning identified causal mutations in OsRNRS1, encoding the small subunit of ribonucleotide reductase. The G583R (ws21-1) and Y365F (ws21-2) mutations likely impair enzyme activity, disrupting the dNTP pool for plastid genome replication and causing aberrant chloroplast development. Correspondingly, the expression of genes for chlorophyll synthesis, photosynthesis, and ROS metabolism was altered. Our findings directly link nuclear-encoded nucleotide metabolism to chloroplast biogenesis and demonstrate that dNTP homeostasis is critical for maintaining photosynthetic capacity and redox balance in plants. Full article

While striped catfish (Pangasianodon hypophthalmus) is an economically important aquaculture species, its genomic resources remain limited. To date, linkage maps, QTL (quantitative trait loci) analyses, and the identification of candidate genes associated with disease resistance traits are very limited. Therefore, the present study aimed to construct a high-density linkage map and identify candidate genes for this species. Our analysis was conducted on a pedigree population consisting of 560 individuals (490 offspring and 70 parents for 40 families), whose genomes were analyzed using a genotyping-by-sequencing platform. After stringent filtering, 9882 high-quality SNPs were retained for linkage analysis. Linkage analysis placed 8786 markers onto 30 linkage groups (LGs), with an average density of 0.43 SNPs per cM. Recombination rates varied across the 30 linkage groups (LGs), averaging of 3.6 cM/Mb in males, 6.7 cM/Mb in females, and 5.1 cM/Mb when sex-averaged. Using the linkage map, our QTL analysis identified three significant QTLs for disease resistance to Edwardsiella ictaluri, the causative agent of Bacillary Necrosis of Pangasius (BNP). The QTLs were located on LG1, LG9 and LG29, and their peak markers explained 17.03% of the phenotypic variance. An LD-based interval of approximately ±25 kb surrounding the QTL peak was identified as the putative candidate region. However, subsequent genome-wide association analysis did not identify significant SNP effects within these regions, suggesting that the QTLs may represent polygenic or small-effect loci that are detectable only in linkage-based analyses. In summary, this study presents the first high-density SNP-based linkage map for striped catfish and reports significant QTL and associated candidate genes related to disease resistance and growth traits. These findings provide valuable insights into the genetic architecture of economically important traits in P. hypophthalmus. Nevertheless, further validation in independent populations is required before incorporating these markers into selective breeding programs. Full article

This study aimed to assess the impact of gradual versus abrupt light–dark transitions on the pectoral muscle, heart, tibia, and eye tissues of broilers, focusing on rearing disorders. A total of 270 male broiler chicks (ROSS-308) were divided into three groups according to the type of light transition: abrupt, 30-min gradual, and 1-h gradual changes in light intensity. The broilers were reared for six weeks, after which samples were collected for gross examination, morphometric and histomorphometric measurements, and histopathological analysis of the pectoral muscle, heart, tibia, and eye. White striping incidence in the pectoral muscle was not significantly affected by light–dark transition type. Results indicated that broilers in the 30-min gradual transition group had a higher relative heart weight than those in the abrupt-transition group (p < 0.05), although the RV/TV ratio did not differ. Tibial measurements, including weight, length, and cortical index, showed no differences across groups. Broilers exposed to a 1-h gradual transition between light and dark periods showed significantly greater eye weights compared to both the birds in the abrupt transition group and the birds in the 30-min transition group (p < 0.01). Overall, gradual light transitions did not substantially affect pectoral muscle or bone health but had minor effects on heart and eye weights in broilers reared under intensive production systems. Full article

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), poses a severe threat to global wheat production. The adaptor protein complex AP-1 plays a crucial role in vesicular trafficking, yet its function in rust fungi remains poorly understood. In this study, a gene encoding an AP-1 σ subunit, designated PsAP1, was identified in Pst. The expression of PsAP1 was highly induced during the early infection stage. Heterologous expression of PsAP1 in a Fusarium graminearum mutant partially restored its pathogenic defects. Subcellular localization analysis revealed that PsAP1 localizes to the plasma membrane, cytoplasm, and nucleus. Silencing PsAP1 in wheat using Barley stripe mosaic virus-mediated host-induced gene silencing (BSMV-HIGS) significantly attenuated Pst pathogenicity, reducing hyphal growth by 6.7% (colony diameter), sporulation by 61.6% (lesion length), and pathogen biomass by 66%, along with enhanced accumulation of host reactive oxygen species. Transcriptomic analysis further demonstrated that silencing PsAP1 disrupted multiple pathways, including MAPK signaling, glutathione metabolism, and carbohydrate metabolism. These findings indicate that PsAP1 facilitates Pst infection by modulating vesicular trafficking, suppressing host immunity, and reprogramming host metabolism. This study provides novel insights into the pathogenic mechanisms of rust fungi and suggests a potential target for disease control. Full article

Striping noise is a common problem in multi-detector scanning radiometers on remote sensing satellites, typically caused by response inconsistency among detector elements. For payloads with a multi-column redundant architecture, this paper proposes a detector-selection framework that jointly considers sensitivity and uniformity from the perspective of detector-element selection to mitigate striping noise. First, the degree of detector consistency is quantified using the Inter-Row Brightness Temperature Difference (IRBTD). Then, a dynamic programming approach based on the Viterbi algorithm is employed to select detector elements row by row with linear time complexity, optimizing the process through a weighted cost function that integrates sensitivity and consistency. Experiments on raw data from the FY-4B Geostationary High-speed Imager (GHI) show that the method reduces inconsistency by 10–40% while increasing the noise-equivalent temperature difference (NEdT) by only 1–4% (≤4 mK). The average IRBTD decreases by approximately 20–100 mK, and high-frequency striping energy is significantly suppressed (reduction of 50–90%). The algorithm exhibits linear time complexity and low computational overhead, making it suitable for real-time on-board processing. Its weighting parameter enables flexible trade-offs between sensitivity and uniformity. By suppressing striping noise directly during the detector-selection stage without introducing data distortion or requiring calibration adjustments, the proposed method can be widely applied to scanning radiometers that employ multi-column long-linear-arrays. Full article