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As for the classification network that is constantly emerging with each passing day, different classification network as the backbone of the semantic segmentation network may show different performance. This paper selected the road extraction data set of CVPR DeepGlobe, and compared the performance differences of VGG-16 as the backbone of Unet, ResNet34, ResNet101 and Xception as the backbone of AD-LinkNet. When VGG-16 is used as the backbone of the semantic segmentation network, it performs better in the face of long and wide road extraction. As the backbone of the semantic segmentation network, ResNet has a higher ability to extract small roads. When Xception is used as the backbone of the semantic segmentation network, it not only retains the characteristics of ResNet34, but also can effectively deal with the complex situation of extracting target covered by occlusions.

Backbone chemical shift assignments for the Toho-1 β-lactamase (263 amino acids, 28.9 kDa) are reported based on triple resonance solution-state NMR experiments performed on a uniformly 2H,13C,15N-labeled sample. These assignments allow for subsequent site-specific characterization at the chemical, structural, and dynamical levels. At the chemical level, titration with the non-β-lactam β-lactamase inhibitor avibactam is found to give chemical shift perturbations indicative of tight covalent binding that allow for mapping of the inhibitor binding site. At the structural level, protein secondary structure is predicted based on the backbone chemical shifts and protein residue sequence using TALOS-N and found to agree well with structural characterization from X-ray crystallography. At the dynamical level, model-free analysis of 15N relaxation data at a single field of 16.4 T reveals well-ordered structures for the ligand-free and avibactam-bound enzymes with generalized order parameters of ~ 0.85. Complementary relaxation dispersion experiments indicate that there is an escalation in motions on the millisecond timescale in the vicinity of the active site upon substrate binding. The combination of high rigidity on short timescales and active site flexibility on longer timescales is consistent with hypotheses for achieving both high catalytic efficiency and broad substrate specificity: the induced active site dynamics allows variously sized substrates to be accommodated and increases the probability that the optimal conformation for catalysis will be sampled.

Spectral submanifolds (SSMs) have recently been shown to provide exact and unique reduced-order models for nonlinear unforced mechanical vibrations. Here, we extend these results to periodically or quasi-periodically forced mechanical systems, obtaining analytic expressions for forced responses and backbone curves on modal (i.e. two dimensional) time-dependent SSMs. A judicious choice of the parametrization of these SSMs allows us to simplify the reduced dynamics considerably. We demonstrate our analytical formulae on three numerical examples and compare them to results obtained from available normal-form methods.

Reticulate speciation caused by interspecific hybridization is now recognized as an important mechanism in the creation of biological diversity. However, depicting the patterns of phylogenetic networks for lineages that have undergone interspecific gene flow is challenging. Here we sequenced 25 taxa representing natural diversity in the genus Actinidia with an average mapping depth of 26× on the reference genome to reconstruct their reticulate history. We found evidence, including significant gene tree discordance, cytonuclear conflicts, and changes in genome-wide heterozygosity across taxa, collectively supporting extensive reticulation in the genus. Furthermore, at least two separate parental species pairs were involved in the repeated origin of the hybrid lineages, in some of which a further phase of syngameon was triggered. On the basis of the elucidated hybridization relationships, we obtained a highly resolved backbone phylogeny consisting of taxa exhibiting no evidence of hybrid origin. The backbone taxa have distinct demographic histories and are the product of recent rounds of rapid radiations via sorting of ancestral variation under variable climatic and ecological conditions. Our results suggest a mode for consecutive plant diversification through two layers of radiations, consisting of the rapid evolution of backbone lineages and the formation of hybrid swarms derived from these lineages.

Nanostructured materials have shown extraordinary promise for electrochemical energy storage but are usually limited to electrodes with rather low mass loading (~1 milligram per square centimeter) because of the increasing ion diffusion limitations in thicker electrodes. We report the design of a three-dimensional (3D) holey-graphene/niobia (Nb₂O₅) composite for ultrahigh-rate energy storage at practical levels of mass loading (>10 milligrams per square centimeter). The highly interconnected graphene network in the 3D architecture provides excellent electron transport properties, and its hierarchical porous structure facilitates rapid ion transport. By systematically tailoring the porosity in the holey graphene backbone, charge transport in the composite architecture is optimized to deliver high areal capacity and high-rate capability at high mass loading, which represents a critical step forward toward practical applications.

Big, time-scaled phylogenies are fundamental to connecting evolutionary processes to modern biodiversity patterns. Yet inferring reliable phylogenetic trees for thousands of species involves numerous trade-offs that have limited their utility to comparative biologists. To establish a robust evolutionary timescale for all approximately 6,000 living species of mammals, we developed credible sets of trees that capture root-to-tip uncertainty in topology and divergence times. Our \"backbone-and-patch\" approach to tree building applies a newly assembled 31-gene supermatrix to two levels of Bayesian inference: (1) backbone relationships and ages among major lineages, using fossil node or tip dating, and (2) species-level \"patch\" phylogenies with nonoverlapping in-groups that each correspond to one representative lineage in the backbone. Species unsampled for DNA are either excluded (\"DNA-only\" trees) or imputed within taxonomic constraints using branch lengths drawn from local birth-death models (\"completed\" trees). Joining time-scaled patches to backbones results in species-level trees of extant Mammalia with all branches estimated under the same modeling framework, thereby facilitating rate comparisons among lineages as disparate as marsupials and placentals. We compare our phylogenetic trees to previous estimates of mammal-wide phylogeny and divergence times, finding that (1) node ages are broadly concordant among studies, and (2) recent (tip-level) rates of speciation are estimated more accurately in our study than in previous \"supertree\" approaches, in which unresolved nodes led to branch-length artifacts. Credible sets of mammalian phylogenetic history are now available for download at http://vertlife.org/phylosubsets, enabling investigations of long-standing questions in comparative biology.

The chemistry literature contains more than a century's worth of instructions for making molecules, all written by and for humans. Steiner et al. developed an autonomous compiler and robotic laboratory platform to synthesize organic compounds on the basis of standardized methods descriptions (see the Perspective by Milo). The platform comprises conventional equipment such as round-bottom flasks, separatory funnels, and a rotary evaporator to maximize its compatibility with extant literature. The authors showcase the system with short syntheses of three common pharmaceuticals that proceeded comparably to manual synthesis. Science , this issue p. eaav2211 ; see also p. 122 A compiler directs a robotic platform to conduct short organic syntheses using standard protocols and laboratory equipment. The synthesis of complex organic compounds is largely a manual process that is often incompletely documented. To address these shortcomings, we developed an abstraction that maps commonly reported methodological instructions into discrete steps amenable to automation. These unit operations were implemented in a modular robotic platform by using a chemical programming language that formalizes and controls the assembly of the molecules. We validated the concept by directing the automated system to synthesize three pharmaceutical compounds, diphenhydramine hydrochloride, rufinamide, and sildenafil, without any human intervention. Yields and purities of products and intermediates were comparable to or better than those achieved manually. The syntheses are captured as digital code that can be published, versioned, and transferred flexibly between platforms with no modification, thereby greatly enhancing reproducibility and reliable access to complex molecules.

While originally designed for natural language processing tasks, the self-attention mechanism has recently taken various computer vision areas by storm. However, the 2D nature of images brings three challenges for applying self-attention in computer vision: (1) treating images as 1D sequences neglects their 2D structures; (2) the quadratic complexity is too expensive for high-resolution images; (3) it only captures spatial adaptability but ignores channel adaptability. In this paper, we propose a novel linear attention named large kernel attention (LKA) to enable self-adaptive and long-range correlations in self-attention while avoiding its shortcomings. Furthermore, we present a neural network based on LKA, namely Visual Attention Network (VAN). While extremely simple, VAN achieves comparable results with similar size convolutional neural networks (CNNs) and vision transformers (ViTs) in various tasks, including image classification, object detection, semantic segmentation, panoptic segmentation, pose estimation, etc. For example, VAN-B6 achieves 87.8% accuracy on ImageNet benchmark, and sets new state-of-the-art performance (58.2 PQ) for panoptic segmentation. Besides, VAN-B2 surpasses Swin-T 4 mIoU (50.1 vs. 46.1) for semantic segmentation on ADE20K benchmark, 2.6 AP (48.8 vs. 46.2) for object detection on COCO dataset. It provides a novel method and a simple yet strong baseline for the community. The code is available at https://github.com/Visual-Attention-Network .

Peptides have a three-dimensional configuration that can adopt particular conformations for binding to proteins, which are well suited to interact with larger contact surface areas on target proteins. However, low cell permeability is a major challenge in the development of peptide-related drugs. In recent years, backbone N-methylation has been a useful tool for manipulating the permeability of cyclic peptides/peptidomimetics. Backbone N-methylation permits the adjustment of molecule’s conformational space. Several pathways are involved in the drug absorption pathway; the relative importance of each N-methylation to total permeation is likely to differ with intrinsic properties of cyclic peptide/peptidomimetic. Recent studies on the permeability of cyclic peptides/peptidomimetics using the backbone N-methylation strategy and synthetic methodologies will be presented in this review.

Single-mode fibres with low loss and a large transmission bandwidth are a key enabler for long-haul high-speed optical communication and form the backbone of our information-driven society. However, we are on the verge of reaching the fundamental limit of single-mode fibre transmission capacity. Therefore, a new means to increase the transmission capacity of optical fibre is essential to avoid a capacity crunch. Here, by employing few-mode multicore fibre, compact three-dimensional waveguide multiplexers and energy-efficient frequency-domain multiple-input multiple-output equalization, we demonstrate the viability of spatial multiplexing to reach a data rate of 5.1 Tbit s −1  carrier −1 (net 4 Tbit s −1  carrier −1 ) on a single wavelength over a single fibre. Furthermore, by combining this approach with wavelength division multiplexing with 50 wavelength carriers on a dense 50 GHz grid, a gross transmission throughput of 255 Tbit s −1 (net 200 Tbit s −1 ) over a 1 km fibre link is achieved. A few-mode, multicore fibre allows ultra-high-speed data transmission on a single wavelength of light.