Search Results (43)

Dopaminergic amacrine cells (DACs) are a subclass of amacrine cells that modulate retinal processing and light adaptation by releasing dopamine. Although the role of dopamine is largely conserved, their retinal distribution across mammals remains incompletely characterized. In mice, rats, thirteen-lined ground squirrels (TLGSs), and macaques, we systematically compared the localization, number, and topography of DACs by their expression of tyrosine hydroxylase (TH), a crucial enzyme in the biosynthesis of dopamine. In all species examined, TH+ cells were primarily located in the inner nuclear layer; however, there was a species-dependent influence on their number and distribution. Mice exhibited the highest density of TH+cells but completely lacked displaced TH+cells (dTH+cells) in the ganglion cell layer. Despite interspecies variation in the total number of TH+cells in the retina, the overall density in rats, TLGSs, and macaques was similar. Most species displayed a higher density of DACs toward central retinal regions. However, rats exhibited a distinctive dorsal concentration, particularly among dTH+cells. Although most species examined exhibited a similar ratio of TH+cells to Brn3a+ retinal ganglion cells, TLGSs showed a marked reduction, indicating a potentially diminished dopaminergic modulatory role. Species-specific DAC topographies aligned with specialized visual regions, such as the visual streak in TLGS and the macula in macaques. These results reveal both conserved and divergent features of retinal dopamine circuitry, reflecting evolutionary adaptations to visual processing demands. Full article

In rice detection tasks, accurate identification of leaf streaks, pest and disease distribution, and spikelet hierarchies relies on high-quality images to distinguish between texture and hierarchy. However, existing images often suffer from texture blurring and contour shifting due to equipment and environment limitations, which affects the detection performance. In view of the fact that pests and diseases affect the whole situation and tiny details are mostly localized, we propose a rice image reconstruction method based on an adaptive two-branch heterogeneous structure. The method consists of a low-frequency branch (LFB) that recovers global features using orientation-aware extended receptive fields to capture streaky global features, such as pests and diseases, and a high-frequency branch (HFB) that enhances detail edges through an adaptive enhancement mechanism to boost the clarity of local detail regions. By introducing the dynamic weight fusion mechanism (CSDW) and lightweight gating network (LFFN), the problem of the unbalanced fusion of frequency information for rice images in traditional methods is solved. Experiments on the 4× downsampled rice test set demonstrate that the proposed method achieves a 62% reduction in parameters compared to EDSR, 41% lower computational cost (30 G) than MambaIR-light, and an average PSNR improvement of 0.68% over other methods in the study while balancing memory usage (227 M) and inference speed. In downstream task validation, rice panicle maturity detection achieves a 61.5% increase in mAP50 (0.480 → 0.775) compared to interpolation methods, and leaf pest detection shows a 2.7% improvement in average mAP50 (0.949 → 0.975). This research provides an effective solution for lightweight rice image enhancement, with its dual-branch collaborative mechanism and dynamic fusion strategy establishing a new paradigm in agricultural rice image processing. Full article

Rain streaks degrade the quality of optical images and seriously affect the effectiveness of subsequent vision-based algorithms. Although the applications of a convolutional neural network (CNN) and self-attention mechanism (SA) in single image deraining have shown great success, there are still unresolved issues regarding the deraining performance and the large computational load. The work in this paper fully coordinates and utilizes the advantages between CNN and SA and proposes a hybrid content-aware deraining network (CAD) to reduce complexity and generate high-quality results. Specifically, we construct the CADBlock, including the content-aware convolution and attention mixer module (CAMM) and the multi-scale double-gated feed-forward module (MDFM). In CAMM, the attention mechanism is used for intricate windows to generate abundant features and simple convolution is used for plain windows to reduce computational costs. In MDFM, multi-scale spatial features are double-gated fused to preserve local detail features and enhance image restoration capabilities. Furthermore, a four-token contextual attention module (FTCA) is introduced to explore the content information among neighbor keys to improve the representation ability. Both qualitative and quantitative validations on synthetic and real-world rain images demonstrate that the proposed CAD can achieve a competitive deraining performance. Full article

In this study, we performed microtextural, major/minor element, and Sr-isotope analyses on hornblende and plagioclase (as phenocrysts, groundmass, or inclusions) from the Early Cretaceous Jiagou pluton (eastern North China Craton), to elucidate the magma source, possible magma mixing process, and the transition from low-Mg to high-Mg adakitic magmas. Petrographic study and electron microprobe (EMP) analyses reveal well-defined compositional zoning in hornblende and plagioclase phenocrysts. Outward from the core (first zone), the second and third zones show pronounced oscillatory zoning and significant variations in Mg# and An%, while the fourth zone is relatively homogeneous. A corroded albitic plagioclase core with sieve texture is enclosed in the first zone and locally intergrows with worm-like quartz streaks and fine hornblende inclusions, featuring Mg# = 81 (core) and 62 (rim). The new plagioclase infill has An% = 14–41. The corroded plagioclase has an initial ⁸⁷Sr/⁸⁶Sr = 0.7074, while that of zoned phenocrystic plagioclase ranges from 0.7068 to 0.7079, suggesting EMI and EMII mantle input. Inclusion hornblende is low in Ti and Cr, while phenocrystic hornblende shows higher Cr in the first zone and lower Cr in the outer zones. The newly discovered mafic microgranular enclaves (MMEs) and regional geochemical data suggest three major magma mixing events. The felsic parental magma was likely originated from a mixed EMI–EMII mantle source before mixing with a mafic magma derived from the partial melting of, successively, a low-Cr and a high-Cr peridotite. Our findings support a petrogenetic model of lower crustal delamination and highlight the critical role of repeated mafic injections in generating high-Mg adakitic magmas. Full article

Zoharite (IMA 2017-049), (Ba,K)₆ (Fe,Cu,Ni)₂₅S₂₇, and gmalimite (IMA 2019-007), ideally K₆□Fe²⁺₂₄S₂₇, are two new sulfides of the djerfisherite group. They were discovered in an unusual gehlenite–wollastonite paralava with pyrrhotite nodules located in the Hatrurim pyrometamorphic complex, Negev Desert, Israel. Zoharite and gmalimite build grained aggregates confined to the peripheric parts of pyrrhotite nodules, where they associate with pentlandite, chalcopyrite, chalcocite, digenite, covellite, millerite, heazlewoodite, pyrite and rudashevskyite. The occurrence and associated minerals indicate that zoharite and gmalimite were formed at temperatures below 800 °C, when sulfides formed on external zones of the nodules have been reacting with residual silicate melt (paralava) locally enriched in Ba and K. Macroscopically, both minerals are bronze in color and have a dark-gray streak and metallic luster. They are brittle and have a conchoidal fracture. In reflected light, both minerals are optically isotropic and exhibit gray color with an olive tinge. The reflectance values for zoharite and gmalimite, respectively, at the standard COM wavelengths are: 22.2% and 21.5% at 470 nm, 25.1% and 24.6% at 546 nm, 26.3% and 25.9% at 589 nm, as well as 27.7% and 26.3% at 650 nm. The average hardness for zoharite and for gmalimite is approximately 3.5 of the Mohs hardness. Both minerals are isostructural with owensite, (Ba,Pb)₆(Cu,Fe,Ni)₂₅S₂₇. They crystallize in cubic space group Pm$\overline{3}$m with the unit-cell parameters a = 10.3137(1) Å for zoharite and a = 10.3486(1) Å for gmalimite. The calculated densities are 4.49 g·cm⁻³ for the zoharite and 3.79 g·cm⁻³ for the gmalimite. The primary structural units of these minerals are M₈S₁₄ clusters, composed of MS₄ tetrahedra surrounding a central MS₆ octahedron. The M site is occupied by transition metals such as Fe, Cu, and Ni. These clusters are further connected via the edges of the MS₄ tetrahedra, forming a close-packed cubic framework. The channels within this framework are filled by anion-centered polyhedra: SBa₉ in zoharite and SK₉ in gmalimite, respectively. In the M₈S₁₄ clusters, the M atoms are positioned so closely that their d orbitals can overlap, allowing the formation of metal–metal bonds. As a result, the transition metals in these clusters often adopt electron configurations that reflect additional electron density from their local bonding environment, similar to what is observed in pentlandite. Due to the presence of shared electrons in these metal–metal bonds, assigning fixed oxidation states—such as Fe²⁺/Fe³⁺ or Cu⁺/Cu²⁺—becomes challenging. Moreover, modeling the distribution of mixed-valence cations (Fe²⁺/³⁺, Cu⁺/²⁺, and Ni²⁺) across the two distinct M sites—one located in the MS₆ octahedron and the other in the MS₄ tetrahedra—often results in ambiguous outcomes. Consequently, it is difficult to define an idealized end-member formula for these minerals. Full article

Gain and bias non-uniformities in infrared line-scanning detectors often result in horizontal streak noise, degrading image quality. This paper introduces a novel non-uniformity correction algorithm combining residual guidance and adaptive weighting, which achieves superior denoising and detail preservation compared to existing methods. The method combines residual and original images in a dual-guidance mechanism and significantly enhances denoising performance and detail preservation through iterative compensation strategies and locally weighted linear regression. Additionally, the algorithm employs local variance to adjust weights dynamically, achieving efficient correction in complex scenes while reducing computational complexity to meet real-time application requirements. Experimental results on both simulated and real infrared datasets demonstrate that the proposed method outperforms mainstream algorithms regarding peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics, achieving an optimal balance between detail preservation and noise suppression. The algorithm demonstrates robust performance in complex scenes, making it suitable for real-time applications in high-resolution infrared imaging systems. Full article

The objective of this study was to elucidate the transmission pathways and spatial distribution of potential source areas for PM_2.5 pollution in Chenzhou City across diverse seasons in southern Hunan. Utilizing Sampling Kriging interpolation analysis, we modeled the temporal and spatial oscillations of PM_2.5 concentrations in Chenzhou City, complemented by HYSPLIT air mass backward trajectories. Furthermore, the model conducted cluster analysis to identify discernible patterns. Our findings unveiled marked seasonal variations in PM_2.5 concentrations within Chenzhou City. The pinnacle is discerned during winter (75.13 μg·m⁻³), whereas the nadir is pronounced in summer (27.64 μg·m⁻³). Notably, the PM_2.5/PM₁₀ ratio surpasses 0.55 during both autumn and winter. Spatially, Chenzhou exhibits an annual average distribution of PM_2.5 pollution characterized by a gradient “from north to south in the western and central sectors, tapering towards the east”. Pollution source analysis suggests that PM_2.5 pollution in Chenzhou City is predominantly ascribed to local emissions. Transmission pathway analysis reveals that the primary transmission corridors, spanning northwest Guangdong, southwestern Henan, Hubei, southern Anhui, and specific zones of southwestern Jiangxi, consistently align with external PM_2.5 pollution sources affecting Chenzhou City throughout the year. Noteworthy seasonal disparities emerge in the spatial distribution and contribution of potential source regions. During spring, autumn, and winter, the predominant contributing regions are primarily located in adjacent provinces. In contrast, during summer, regions with relatively elevated values predominantly streak across the central and western sectors of Jiangxi and the southeastern Hunan region. A comprehensive examination of the seasonal distribution patterns, potential transmission routes, and likely contributing sources of PM_2.5 in Chenzhou City can offer invaluable insights for regional atmospheric environmental governance. Furthermore, it underscores the paramount importance of collaborative regional strategies directed towards the prevention and control of PM_2.5 pollution. Full article

Cassava is an important food crop in western Kenya, yet its production is challenged by pests and diseases that require routine monitoring to guide development and deployment of control strategies. Field surveys were conducted in 2022 and 2023 to determine the prevalence, incidence and severity of cassava mosaic disease (CMD) and cassava brown streak disease (CBSD), whitefly numbers and incidence of cassava green mite (CGM) in six counties of western Kenya. Details of the encountered cassava varieties were carefully recorded to determine the adoption of improved varieties. A total of 29 varieties were recorded, out of which 13 were improved, although the improved varieties were predominant in 60% of fields and the most widely grown variety was MM96/4271. The CMD incidence was higher in 2022 (26.4%) compared to 2023 (10.1%), although the proportion of CMD attributable to whitefly infection was greater (50.6%) in 2023 than in 2022 (18.0%). The CBSD incidence in 2022 was 6.4%, while in 2023 it was 4.1%. The CMD incidence was significantly lower (5.9%) for the improved varieties than it was for the local varieties (35.9%), although the CBSD incidence did not differ significantly between the improved (2.3%) and local varieties (9.7%). Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) were both detected. Most infections were single CBSV infections (82.9%), followed by single UCBSV (34.3%) and coinfection with both viruses (16.7%). Whiteflies were more abundant in 2023, in which 28% of the fields had super-abundant populations of >100/plant, compared to 5% in 2022. KASP SNP genotyping designated 92.8% of the specimens as SSA-ECA for 2022, while it was 94.4% for 2023. The cassava green mite incidence was 65.4% in 2022 compared to 79.9% in 2023. This study demonstrates that cassava viruses, whiteflies and cassava green mites continue to be important constraints to cassava production in western Kenya, although the widespread cultivation of improved varieties is reducing the impact of cassava viruses. The more widespread application of high-quality seed delivery mechanisms could further enhance the management of these pests/diseases, coupled with wider application of IPM measures for whiteflies and mites. Full article

Image deraining aims to mitigate the adverse effects of rain streaks on image quality. Recently, the advent of convolutional neural networks (CNNs) and Vision Transformers (ViTs) has catalyzed substantial advancements in this field. However, these methods fail to effectively balance model efficiency and image deraining performance. In this paper, we propose an effective, locally enhanced visual state space model for image deraining, called DerainMamba. Specifically, we introduce a global-aware state space model to better capture long-range dependencies with linear complexity. In contrast to existing methods that utilize fixed unidirectional scan mechanisms, we propose a direction-aware symmetrical scanning module to enhance the feature capture of rain streak direction. Furthermore, we integrate a local-aware mixture of experts into our framework to mitigate local pixel forgetting, thereby enhancing the overall quality of high-resolution image reconstruction. Experimental results validate that the proposed method surpasses state-of-the-art approaches on six benchmark datasets. Full article

Gold nanoparticles with sizes in the range of 5–15 nm are a standard method of providing fiducial markers to assist with alignment during reconstruction in cryogenic electron tomography. However, due to their high electron density and resulting contrast when compared to standard cellular or biological samples, they introduce artifacts such as streaking in the reconstructed tomograms. Here, we demonstrate a tool that automatically detects these nanoparticles and suppresses them by replacing them with a local background as a post-processing step, providing a cleaner tomogram without removing any sample relevant information or introducing new artifacts or edge effects from uniform density replacements. Full article

Infrared (IR) small target detection in sky scenes is crucial for aerospace, border security, and atmospheric monitoring. Most current works are typically designed for generalized IR scenes, which may not be optimal for the specific scenario of sky backgrounds, particularly for detecting small and dim targets at long ranges. In these scenarios, the presence of heavy clouds usually causes significant false alarms due to factors such as strong edges, streaks, large undulations, and isolated floating clouds. To address these challenges, we propose an infrared dim and small target detection algorithm based on morphological filtering with dual-structure elements. First, we design directional dual-structure element morphological filters, which enhance the grayscale difference between the target and the background in various directions, thus highlighting the region of interest. The grayscale difference is then normalized in each direction to mitigate the interference of false alarms in complex cloud backgrounds. Second, we employ a dynamic scale awareness strategy, effectively preventing the loss of small targets near cloud edges. We enhance the target features by multiplying and fusing the local response values in all directions, which is followed by threshold segmentation to achieve target detection results. Experimental results demonstrate that our method achieves strong detection performance across various complex cloud backgrounds. Notably, it outperforms other state-of-the-art methods in detecting targets with a low signal-to-clutter ratio (MSCR ≤ 2). Furthermore, the algorithm does not rely on specific parameter settings and is suitable for parallel processing in real-time systems. Full article

Background/Objectives: To assess the frequency, extent, localization and potential progression of optic disc drusen (ODD) and the correlation with the angioid streak (AS) length and retinal atrophy in patients with pseudoxanthoma elasticum (PXE). Methods: This retrospective study included patient data from a dedicated PXE clinic at the Department of Ophthalmology, University of Bonn, Germany (observation period from February 2008 to July 2023). Two readers evaluated the presence, localization, and the extent of the ODD on fundus autofluorescence (FAF) imaging at baseline and the follow-up assessments. Additionally, we measured the length of the longest AS visible at baseline and follow-up and the area of atrophy at baseline, both on FAF. Results: A total of 150 eyes of 75 PXE patients (median age at baseline 51.8 years, IRQ 46.3; 57.5 years, 49 female) underwent retrospective analysis. At baseline, 23 of 75 patients exhibited ODD in a minimum of one eye, resulting in an ODD prevalence of 30.7% in our cohort of PXE patients. Among these, 14 patients showed monocular and 9 binocular ODD that were localized predominantly nasally (46.9%). During the observational period (mean 97.5 ± 44.7 months), only one patient developed de novo ODD in one eye and one other patient showed a progression in the size of the existing ODD. The group of patients with ODD had significantly longer ASs (median 7020 µm, IQR 4604; 9183, vs. AS length without ODD: median 4404 µm, IQR 3512; 5965, p < 0.001). No association with the size of the atrophy was found at baseline (p = 0.27). Conclusions: This study demonstrates a prevalence of ODD of 30.7%. ODD presence is associated with longer ASs (an indicator of the severity and extent of ocular Bruch’s membrane calcification), suggesting that ODD formation is tightly related to ectopic calcification—possibly secondary to calcification of the lamina cribrosa. Prospective studies investigating the impact of ODD (in conjunction with intraocular pressure) on visual function in PXE warrant consideration. Full article

Detecting near-Earth asteroids (NEAs) is crucial for research in solar system and planetary science. In recent year, deep-learning methods have almost dominated the task. Since NEAs represent only one-thousandth of the pixels in images, we proposed an ICC-BiFormer model that includes an image compression and contrast enhancement block and a BiFormer model to capture local features in input images, which is different from previous models based on Convolutional Neural Network (CNN). Furthermore, we utilize a larger input size of the model, which corresponds to the side length of the input image matrix, and design a cropping algorithm to prevent NEAs from being truncated and better divide NEAs and satellites. We apply our ICC-BiFormer model into a dataset of approximately 20,000 streak and 40,000 non-streak images to train a binary classification model. The ICC-BiFormer achieves 99.88% accuracy, which is superior to existing models. Focusing on local features has been proven effective in detecting NEAs. Full article

Barley yellow dwarf is a threat to cereal crops worldwide. Barley yellow dwarf virus—PAS (BYDV-PAS) was detected for the first time in Poland in 2015, then in 2019. In the spring of 2021, in several locations in Poland, winter wheat and barley plants with dwarfism and leaf yellowing were collected. Reverse transcription—polymerase chain reaction results revealed BYDV presence in 47 samples and excluded wheat streak mosaic virus infections. Next, immuno-captured polymerase chain reactions confirmed only one case of co-infection caused by BYDV and wheat dwarf virus. Moreover, restriction fragment length polymorphism analysis showed that BYDV-PAS was predominant. The preliminary results were confirmed using sequencing. Infected cereal plants originated mainly from northwestern Poland. The complete coding sequence of coat protein (CP) and a fragment of RNA-dependent RNA polymerase (RdRp) genes of 14 Polish isolates were determined and deposited in the GenBank database. The nucleotide and deduced amino acid sequences of local isolates were compared with others reported to date, indicating their high similarity, from 75.4% to 99.5% and from 81.1% to 100% nucleotide sequence identity, in RdRp and CP, respectively. Phylogenetic analysis, based on the CP gene, revealed the presence of 3 main groups. The Polish isolates clustered together within the Ia group. Full article

‘Violetto di Ramacca’ is a local variety of artichoke grown in Sicily (Southern Italy), known for its purple color with green streaks. In this study, the effects of two different preparation and drying methods (method A, fresh sample oven-dried at 40 °C for 48 h then mixed and ground into flour; and B, minced and frozen sample oven-dried at 40 °C for 24 h then blended and ground into flour) for flours from different parts of the artichoke (bracts, stems, and mix), used at different percentages of integration (5, 7.5, and 10%), in combination with re-milled semolina, have been evaluated. The polyphenol contents of the flours produced with the two methods were measured. The results showed significant differences between the methods and samples, with a range from 9.09 mg GAE/g d.m. (bracts 100%, method A) to 2.62 mg/g (mix 100%, method B). The values were then lowered in the flour products with supplements ranging from 0.96 mg GAE/g (bract flour 10%, method A) to 0.11 mg GAE/g (mixed flour 7.5%, method B). As the amounts of polyphenols increased, the antioxidant activity increased, with a range that varied in the pure flour from 8.59 mg trolox eq/g d.m. (bract flour, method A) to 3.83 mg trolox eq/g d.m. (mixed flour, method B). These flours were also analyzed for color, highlighting a clear difference between methods A (greener) and B (browner). The flours thus obtained were used to produce breads, which were evaluated for their physicochemical characteristics during 4 days of storage. The results showed a reduction in volumes and heights, an increase in the percentage of integration of the artichoke flours, a greater quantity of moisture in the integrated breads, and a lower reduction in the structural characteristics during storage compared to the control breads. The TPA was conducted on the breads from T₀ to T₄, highlighting that, although initially more compact, the integrated breads offered less alteration of the values during storage. The a_w ranged from 0.63 (mix flour 5%, method B) to 0.90 (bract flour 5%, method B). The amounts of polyphenols (from 0.57 mg GAE/g in bread with bracts at 10% (method A) to 0.13 mg GAE/g in bread with mix 5% (method B)) and the antioxidant activity (from 0.55 mg trolox eq/g d.m. in bread with bract flour 10% (method A) to 0.14% mg trolox eq/g d.m. in bread with mix flour) were also evaluated, showing a trend similar to the values obtained in the flours. Colorimetric tests highlighted a color more similar to wholemeal bread in the loaves produced with method B. Statistical factor analysis and cluster analysis were conducted for all trials. Full article