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2022 ◽  
Vol 8 ◽  
Author(s):  
Agnieszka Ruszkowska ◽  
Ya Ying Zheng ◽  
Song Mao ◽  
Milosz Ruszkowski ◽  
Jia Sheng

G•U wobble base pair frequently occurs in RNA structures. The unique chemical, thermodynamic, and structural properties of the G•U pair are widely exploited in RNA biology. In several RNA molecules, the G•U pair plays key roles in folding, ribozyme catalysis, and interactions with proteins. G•U may occur as a single pair or in tandem motifs with different geometries, electrostatics, and thermodynamics, further extending its biological functions. The metal binding affinity, which is essential for RNA folding, catalysis, and other interactions, differs with respect to the tandem motif type due to the different electrostatic potentials of the major grooves. In this work, we present the crystal structure of an RNA 8-mer duplex r[UCGUGCGA]2, providing detailed structural insights into the tandem motif I (5′UG/3′GU) complexed with Ba2+ cation. We compare the electrostatic potential of the presented motif I major groove with previously published structures of tandem motifs I, II (5′GU/3′UG), and III (5′GG/3′UU). A local patch of a strongly negative electrostatic potential in the major groove of the presented structure forms the metal binding site with the contributions of three oxygen atoms from the tandem. These results give us a better understanding of the G•U tandem motif I as a divalent metal binder, a feature essential for RNA functions.


2021 ◽  
Author(s):  
Nadège Popoff ◽  
Renaud Jaunatre ◽  
Caroline Le Bouteiller ◽  
Margot Trinquier ◽  
Yoan Paillet ◽  
...  

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1942
Author(s):  
Cheng Chen ◽  
Jiancang Zhou ◽  
Kangneng Zhou ◽  
Zhiliang Wang ◽  
Ruoxiu Xiao

(1) Background: COVID-19 has been global epidemic. This work aims to extract 3D infection from COVID-19 CT images; (2) Methods: Firstly, COVID-19 CT images are processed with lung region extraction and data enhancement. In this strategy, gradient changes of voxels in different directions respond to geometric characteristics. Due to the complexity of tubular tissues in lung region, they are clustered to the lung parenchyma center based on their filtered possibility. Thus, infection is improved after data enhancement. Then, deep weighted UNet is established to refining 3D infection texture, and weighted loss function is introduced. It changes cost calculation of different samples, causing target samples to dominate convergence direction. Finally, the trained network effectively extracts 3D infection from CT images by adjusting driving strategy of different samples. (3) Results: Using Accuracy, Precision, Recall and Coincidence rate, 20 subjects from a private dataset and eight subjects from Kaggle Competition COVID-19 CT dataset tested this method in hold-out validation framework. This work achieved good performance both in the private dataset (99.94–00.02%, 60.42–11.25%, 70.79–09.35% and 63.15–08.35%) and public dataset (99.73–00.12%, 77.02–06.06%, 41.23–08.61% and 52.50–08.18%). We also applied some extra indicators to test data augmentation and different models. The statistical tests have verified the significant difference of different models. (4) Conclusions: This study provides a COVID-19 infection segmentation technology, which provides an important prerequisite for the quantitative analysis of COVID-19 CT images.


Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1266
Author(s):  
Jing Qin ◽  
Liang Chen ◽  
Jian Xu ◽  
Wenqi Ren

In this paper, we propose a novel method to remove haze from a single hazy input image based on the sparse representation. In our method, the sparse representation is proposed to be used as a contextual regularization tool, which can reduce the block artifacts and halos produced by only using dark channel prior without soft matting as the transmission is not always constant in a local patch. A novel way to use dictionary is proposed to smooth an image and generate the sharp dehazed result. Experimental results demonstrate that our proposed method performs favorably against the state-of-the-art dehazing methods and produces high-quality dehazed and vivid color results.


Chemosensors ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 268
Author(s):  
Le Zhang ◽  
Lixian Liu ◽  
Huiting Huan ◽  
Xukun Yin ◽  
Xueshi Zhang ◽  
...  

A non-local patch regression (NLPR) denoising-enhanced differential broadband photoacoustic (PA) sensor was developed for the high-sensitive detection of multiple trace gases. Using the edge preservation index (EPI) and signal-to-noise ratio (SNR) as a dual-criterion, the fluctuation was dramatically suppressed while the spectral absorption peaks were maintained by the introduction of a NLPR algorithm. The feasibility of the broadband framework was verified by measuring the C2H2 in the background of ambient air. A normalized noise equivalent absorption (NNEA) coefficient of 6.13 × 10−11 cm−1·W·Hz−1/2 was obtained with a 30-mW globar source and a SNR improvement factor of 23. Furthermore, the simultaneous multiple-trace-gas detection capability was determined by measuring C2H2, H2O, and CO2. Following the guidance of single-component processing, the NLPR processed results showed higher EPI and SNR compared to the spectra denoised by the wavelet method and the non-local means algorithm. The experimentally determined SNRs of the C2H2, H2O, and CO2 spectra were improved by a factor of 20. The NNEA coefficient reached a value of 7.02 × 10−11 cm−1·W·Hz−1/2 for C2H2. The NLPR algorithm presented good performance in noise suppression and absorption peak fidelity, which offered a higher dynamic range and was demonstrated to be an effective approach for trace gas analysis.


Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2430
Author(s):  
Jordi Colomer ◽  
Teresa Serra

This review describes the world of edges in submerged vegetated marine canopies (seagrasses, saltmarshes, and seaweeds) where an edge is a boundary with a frontal area separating the vegetation from the adjacent non-vegetated zones. Plants within the vegetation are made of flexible elements pronating in the direction of the flow and oscillating back and forth in response to wave forcing. Some of them also occupy the full height within the water body. The analysis focuses on both the canopy- and local-patch scales to acquire knowledge about the hydrodynamics and the biophysical interactions in the structural shallows and deep limits of the canopies as well as on the structural edges of vegetation patches and the edges in the gaps within the canopies. The spatial arrangements of both canopy and patch edges are not only well imposed through the modification of hydrodynamics, but so too through small-scale interactions from internal structural causes and modifications. The continuous fragmentation of coastal marine habitats has reduced their structural complexity, thus making habitat edges a prevalent seascape feature, including in the shallow (or upper) and deep (or lower) limits of the canopies, the patch edges, and the edges in the gaps within the canopies. Canopy patches represent a region of high flow resistance where flow deflects and accelerates above and/or next to the canopy, resulting in an increase in water velocity and turbulence, especially at the edges of the patch. At the edges, energy transfer is found in spectral wave velocities from the longer to shorter wave period components. Likewise, at the edges, the net deposition of sediments decreases over a distance to a certain length, relative to the bare bed, which is associated with a region of vertical updraft and elevated turbulent kinetic energy. The edge effects also relate to the influence that a patch edge can have on determining species composition and predation risk, which is additionally mediated by the effect the edges have on habitat complexity within the vegetated patch. Organism feedback within the edges does not simply follow the canopy and local features and, in fact, the intricate interaction between biogeophysical processes is key in explaining the complexity of coastal submerged canopy landscapes. For example, proximity to patch edges has a greater influence on epifaunal density and community structure than structural complexity or predation do. The extent to which edges reduce predation risk depends on the extent to which they support higher structural complexities compared to patch interiors. The canopies’ shallow limits and their position in the underwater beach profile are mostly limited by light availability, the intensity of the wave action, and the local nearshore hydrodynamics, but they also depend on the local structural conditions at the vegetated side. The deep limits of the canopies, however, mainly depend on the availability of light and research findings support migration both to the deeper and shallower layers. All structural edges face changes caused by increasing nutrient inputs, development of coastal zones and the increasing impact of climate change. A considerable challenge to managing, restoring, and conserving coastal marine ecosystems stems from understanding how the canopies are able to cope with these natural and anthropogenic disturbances.


2021 ◽  
Author(s):  
Stephen L. Totterman

ABSTRACTThe reliability of ‘citizen science’ datasets where volunteers are free to choose sampling locations is not clear. This study examined local (‘patch’) scale spatial sampling patterns in the Atlas of Australian Birds and then compared reporting rates, i.e. the proportion of sampling units in which a given species was present, from a sample of atlas points with those from a regular sample. Three sites that have been were surveyed sequentially between January–May 2017: Killawarra Forest, Victoria, Coolah Tops National Park and Pilliga Nature Reserve, New South Wales. Spatial bias in atlas sampling patterns was evident as clusters at tourist areas and special habitat features and linear patterns along roads and creek lines. Atlas samples overestimated reporting rates for species with spatial distributions that were concordant with those sampling patterns and vice versa. At least two-fold differences in atlas/regular sample reporting rate ratios were detected for between 13–15% of non-rare species (with reporting rates ≥ 0.08). Concerns are raised that spatial sampling bias is common in the atlas and affects a variety of species, that popular sites may not be representative of habitat patches and that a large proportion of surveys are being filtered out in data analyses.


Author(s):  
Haoxuan Song ◽  
Jiahui Huang ◽  
Yan-Pei Cao ◽  
Tai-Jiang Mu

AbstractReconstructing dynamic scenes with commodity depth cameras has many applications in computer graphics, computer vision, and robotics. However, due to the presence of noise and erroneous observations from data capturing devices and the inherently ill-posed nature of non-rigid registration with insufficient information, traditional approaches often produce low-quality geometry with holes, bumps, and misalignments. We propose a novel 3D dynamic reconstruction system, named HDR-Net-Fusion, which learns to simultaneously reconstruct and refine the geometry on the fly with a sparse embedded deformation graph of surfels, using a hierarchical deep reinforcement (HDR) network. The latter comprises two parts: a global HDR-Net which rapidly detects local regions with large geometric errors, and a local HDR-Net serving as a local patch refinement operator to promptly complete and enhance such regions. Training the global HDR-Net is formulated as a novel reinforcement learning problem to implicitly learn the region selection strategy with the goal of improving the overall reconstruction quality. The applicability and efficiency of our approach are demonstrated using a large-scale dynamic reconstruction dataset. Our method can reconstruct geometry with higher quality than traditional methods.


2021 ◽  
Author(s):  
Anna Skye Bruce ◽  
Wayne E. Thogmartin ◽  
Chris Trosen ◽  
Karen Oberhauser ◽  
Claudio Gratton

Abstract Context It is estimated that over one billion milkweed stems need to be restored to sustain the eastern North American migratory population of monarch butterflies; where and in what context the stems should be placed on the landscape is key to addressing habitat deficits. Objectives We assessed how the amount of appropriate habitat surrounding a particular patch of monarch habitat affects monarch presence and reproduction. To ensure that habitat restoration efforts are targeted towards areas that maximize monarch population growth, it is important to understand the effects of landscape heterogeneity on monarch occurrence in habitat patches (i.e. grasslands with milkweeds) across the landscape. Methods Over two summers (2018-2019), we surveyed monarch adults, larvae, and eggs at sixty grassland sites in Wisconsin that varied in patch size and landscape context (proportion grassland, forest edge density, and road density). We also estimated milkweed density and floral richness to characterize local patch quality. Results Adult monarch abundance was highest at patches with the lowest proportion of surrounding grassland and lowest road density, and was heavily influenced by patch quality variables. Egg and larva density in a patch increased with milkweed density and floral richness within a patch. Patch size was unrelated to monarch abundance. Conclusions These results suggest that optimal sites for monarch habitat restoration are within landscapes with less surrounding habitat and that high milkweed density and floral richness should be conservation goals.


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