“…Human cells, when exposed to both real and simulated microgravity (s-µg), form 3D tissue constructs mirroring in vivo architectures (e.g., cartilage, intima constructs, cancer spheroids and others). …”
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“…CONCLUSIONS: The observed heterogeneity in structure, collagen content, and stiffness highlights that fibroid regions differ in architectural status. These differences might be associated with variations in local pressure, biomechanical signaling, and altered growth. …”
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“…To assess the feature of the expression of KPNA2 in the development of the ductal atypia and islet architectures, we scrutinized the pancreas of Tg mice histopathologically. …”
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“…Backpropagation, while highly effective on von Neumann architectures, becomes inefficient when scaling to large networks. …”
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“…Cancers exhibit spatially heterogeneous, unique vascular architectures across individual samples, cell-lines and patients. …”
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“…Compared to existing asynchronous adders corresponding to various architectures such as the ripple carry adder (RCA), the conventional carry lookahead adder (CCLA), the carry select adder (CSLA), the BCLARC, and the hybrid BCLARC-RCA, the proposed BCLARC is found to be faster and more energy-optimized. …”
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“…The recent advent of Deep Learning has renewed the interest in neural networks, with dozens of methods being developed taking advantage of these new architectures. However, most methods are still heavily based pre-processing of the input data, as well as extraction and integration of multiple hand-picked, and manually designed features. …”
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“…We used atomic force microscopy (AFM) to image the different photosystem I (PSI) membrane architectures of the MED4 (HL) Prochlorococcus ecotype grown under high-light and low-light conditions in addition to the MIT9313 (LL) and SS120 (LL) Prochlorococcus ecotypes grown under low-light conditions. …”
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“…The thus obtained materials were studied by quantitative nanomechanical measurements using atomic force microscopy (QNM-AFM). The different architectures led to different local elastic moduli at the polymer-air interface, where the CL surfaces were much stiffer (Derjaguin-Muller-Toporov (DMT) modulus = 20 ± 0.8 GPa) compared to the structured 3D networks obtained by µCP (DMT modulus = 42 ± 1.1 MPa). …”
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“…On the mammogram of 39 SA cases, the percentage of architectural distortion, calcifications, mass/nodular, asymmetric density, and mass combining with calcifications were 30.8%, 23.1%, 17.9%, 12.8%, and 7.7%, respectively; and 3 cases had no abnormal findings. …”
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“…The results are highly relevant for the stability of porphyrin/IL-based thin film catalyst systems and molecular devices, and more generally, stacked organic multilayer architectures.…”
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“…Neurobiological systems rely on hierarchical and modular architectures to carry out intricate computations using minimal resources. …”
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“…However, these models used simple statistical architectures and the additional inputs were derived from costly and / or invasive procedures. …”
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“…We devised three deep learning architectures for DILI prediction on the challenge data and compared them to random forest and multi-layer perceptron classifiers. …”
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“…[Image: see text] Steroid-degrading bacteria, including Mycobacterium tuberculosis (Mtb), utilize an architecturally distinct subfamily of acyl coenzyme A dehydrogenases (ACADs) for steroid catabolism. …”
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“…Herein, we present a novel method to study the evolution of operons based on phylogenetic clustering of operon-encoded protein families and genomic-proximity network visualizations of operon architectures. We applied this approach to study the evolution of the synthase dependent exopolysaccharide (EPS) biosynthetic systems: cellulose, acetylated cellulose, poly-β-1,6-N-acetyl-D-glucosamine (PNAG), Pel, and alginate. …”
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“…Other imaging features included crazy paving pattern (57.1%), fibrous stripes (50%), subpleural lines (35.7%), architectural distortion (28.6%), air bronchogram sign (26.2%), vascular thickening (23.8%) and nodules (2.4%). …”
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“…Although there are a few deep learning-based techniques for chest anatomy segmentation, most of them only consider single class lung segmentation with deep complex architectures that require a lot of trainable parameters. …”
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“…Despite promising results obtained with chitosan 3D scaffolds, significant challenges persist in fabricating hydrogel structures with ordered architectures and biological properties to mimic native tissues. …”
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“…Many recent developments in machine learning have come from the field of “deep learning,” or the use of advanced neural network architectures and techniques. While these methods have produced state-of-the-art results and dominated research focus in many fields, such as image classification and natural language processing, they have not gained as much ground over standard multivariate pattern analysis (MVPA) techniques in the classification of electroencephalography (EEG) or other human neuroscience datasets. …”
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