Cracks are the most significant pre-disaster of a road, and are also important indicators for evaluating the damage level of a road. At present, road crack detection mainly depends on manual ...detection and road detection vehicles, with which the safety of detection workers is not guaranteed and the detection efficiency is low. A road detection vehicle can speed up the efficiency to a certain extent, but the automation level is low and it is easy to block the traffic. Unmanned Aerial Vehicles (UAV) have the characteristics of low energy consumption and easy control. If UAV technology can be applied to road crack detection, it will greatly improve the detection efficiency and produce huge economic benefits. In order to find a way to apply UAV to road crack detection, we developed a new technique for road crack detection based on UAV pictures, called DenxiDeepCrack, which is a trainable deep convolutional neural network for automatic crack detection which utilises learning high-level features for crack representation. In addition, we create a new dataset based on drone images called UCrack 11 to enrich the crack database of drone images for future crack detection research.
Energy harvesting and power delivery are key technologies for self‐powered systems toward the internet of things, and integration of the two should be prioritized. The dominant mechanism of a ...triboelectric nanogenerator (TENG) is Maxwell's displacement current, which exists both inside the media/device and in the space surrounding the device. The displacement current transmitted in media inside the device can be collected by wired transmission using two electrodes, while the component that is leaked in to the space surrounding the device can be partially collected wirelessly. Herein, simultaneous collection of power transmitted through wires and wirelessly by a rotating TENG, is demonstrated. The wired component gives an output of ≈2 mA and ≈110 V, and the wireless component using the finite size of the collector gives an output current and voltage of ≈3 µA and ≈17.5 V (power density of 21.8 mW m−2). Small mobile electronics and a digital camera can be charged. The study extends the application of TENGs for practical applications.
An integrated rotating triboelectric nanogenerator (TENG) is designed by conjunction of wired and wireless transmissions to collect rotational energy. The integrated rotating TENG with the wireless energy delivery is demonstrated for the electric power supply of smart homes. The hybrid TENG develops the application of Maxwell's displacement current in self‐powered system.
One of the most important tasks in remote sensing image analysis is remote sensing image Change Detection (CD), and CD is the key to helping people obtain more accurate information about changes on ...the Earth's surface. A Multi-Attention Guided Feature Fusion Network (MAFF-Net) for CD tasks has been designed. The network enhances feature extraction and feature fusion by building different blocks. First, a Feature Enhancement Module (FEM) is proposed. The FEM introduces Coordinate Attention (CA). The CA block embeds the position information into the channel attention to obtain the accurate position information and channel relationships of the remote sensing images. An updated feature map is obtained by using an element-wise summation of the input of the FEM and the output of the CA. The FEM enhances the feature representation in the network. Then, an attention-based Feature Fusion Module (FFM) is designed. It changes the previous idea of layer-by-layer fusion and chooses cross-layer aggregation. The FFM is to compensate for some semantic information missing as the number of layers increases. FFM plays an important role in the communication of feature maps at different scales. To further refine the feature representation, a Refinement Residual Block (RRB) is proposed. The RRB changes the number of channels of the aggregated features and uses convolutional blocks to further refine the feature representation. Compared with all compared methods, MAFF-Net improves the
1-Score scores by 4.9%, 3.2%, and 1.7% on three publicly available benchmark datasets, the CDD, LEVIR-CD, and WHU-CD datasets, respectively. The experimental results show that MAFF-Net achieves state-of-the-art (SOTA) CD performance on these three challenging datasets.
Three-dimensional object detection in the point cloud can provide more accurate object data for autonomous driving. In this paper, we propose a method named MA-MFFC that uses an attention mechanism ...and a multi-scale feature fusion network with ConvNeXt module to improve the accuracy of object detection. The multi-attention (MA) module contains point-channel attention and voxel attention, which are used in voxelization and 3D backbone. By considering the point-wise and channel-wise, the attention mechanism enhances the information of key points in voxels, suppresses background point clouds in voxelization, and improves the robustness of the network. The voxel attention module is used in the 3D backbone to obtain more robust and discriminative voxel features. The MFFC module contains the multi-scale feature fusion network and the ConvNeXt module; the multi-scale feature fusion network can extract rich feature information and improve the detection accuracy, and the convolutional layer is replaced with the ConvNeXt module to enhance the feature extraction capability of the network. The experimental results show that the average accuracy is 64.60% for pedestrians and 80.92% for cyclists on the KITTI dataset, which is 1.33% and 2.1% higher, respectively, compared with the baseline network, enabling more accurate detection and localization of more difficult objects.
Recent advances in understanding intracellular amino acid transport and mechanistic target of rapamycin complex 1 (mTORC1) signaling shed light on solute carrier 38, family A member 9 (SLC38A9), a ...lysosomal transporter responsible for the binding and translocation of several essential amino acids. Here we present the first crystal structure of SLC38A9 from Danio rerio in complex with arginine. As captured in the cytosol-open state, the bound arginine was locked in a transitional state stabilized by transmembrane helix 1 (TM1) of drSLC38A9, which was anchored at the groove between TM5 and TM7. These anchoring interactions were mediated by the highly conserved WNTMM motif in TM1, and mutations in this motif abolished arginine transport by drSLC38A9. The underlying mechanism of substrate binding is critical for sensitizing the mTORC1 signaling pathway to amino acids and for maintenance of lysosomal amino acid homeostasis. This study offers a first glimpse into a prototypical model for SLC38 transporters.
The dyes and nitroaromatic pollutants from wastewater have attracted much attention due to their huge safety risks to human society. At present, nanomaterials as catalysts of photocatalytic ...degradation have emerged as attractive and effective materials for wastewater treatment. On the one hand, much work has been focused on the search for nanomaterials with high catalytic activity, such as precious metal nanoparticles (NPs) and other advanced functional materials (e.g. graphene oxide (GO), MXenes, metal organic frameworks (MOFs), etc.). On the other hand, modifications of existing photocatalysts to enhance their photocatalytic activity have also been explored. In this paper, photocatalysts in various dimensions (including precious metal nanoparticles, nanofibres, 2D nanosheets such as MXenes, and MOFs) are been described. The deposition of nano photocatalysts by different techniques such as the formation of hydrogel structures to immobilize the catalysts, the treatment of nanocatalysts using electrospinning technique, and the formation of core‐shell structures to enhance catalytic activity are also discussed. These techniques not only solve the aggregation of NPs due to their high surface energy but also impart unique properties to the nano photocatalysts. This review explores the synthesis of nano photocatalysts in different dimensions and their application in the catalytic degradation of dyes and nitro compounds, providing good leads for nano photocatalysts in materials design and environmental remediation.
This review explores the synthesis of nano photocatalysts in different dimensions and their application in the catalytic degradation of dyes and nitro compounds, providing good leads for nano photocatalysts in materials design and environmental remediation.
Nano-sized nickel oxides have been synthesized in a water-in-oil microemulsion. The as-synthesized samples were characterized by powder X-ray diffraction (XRD), transmission electronic microscopy ...(TEM) and nitrogen adsorption/desorption. The particle size of nickel oxide can be controlled from 11.5 to 31.5nm by varying the proportion of water, surfactant and oil in the microemulsion, mixing method, and calcining temperature. Gas sensors based on as-synthesized nickel oxide are fabricated and investigated. They exhibit much higher sensitivities to hydrogen sulfide, ethanol and nitrogen dioxide, compared to those based on the conventional bulk NiO. Furthermore, the response of as-synthesized materials to various kinds of target gases increases with the decreasing of the particle size of gas sensors. It is noted that the NiO sensor with particle size of 11.5nm displays high degree of selectivity, coupled with high response value, making it particularly interesting for H2S-monitoring applications.
► Nano-sized nickel oxides have been synthesized in a microemulsion system. ► The particle size of nickel oxide can be controlled from 11.5 to 31.5nm. ► They exhibit higher sensitivities to H2S, C2H5OH and NO2 in contrast to bulk NiO. ► The response to all target gases increases with the decreasing of the particle size. ► The NiO sensor (11.5nm) displays outstanding sensitivity and selectivity to H2S
Serotonin or 5-hydroxytryptamine (5-HT) regulates a wide spectrum of human physiology through the 5-HT receptor family. We report the crystal structures of the human 5-HT 1B G protein–coupled ...receptor bound to the agonist antimigraine medications ergotamine and dihydroergotamine. The structures reveal similar binding modes for these ligands, which occupy the orthosteric pocket and an extended binding pocket close to the extracellular loops. The orthosteric pocket is formed by residues conserved in the 5-HT receptor family, clarifying the family-wide agonist activity of 5-HT. Compared with the structure of the 5-HT 2B receptor, the 5-HT 1B receptor displays a 3 angstrom outward shift at the extracellular end of helix V, resulting in a more open extended pocket that explains subtype selectivity. Together with docking and mutagenesis studies, these structures provide a comprehensive structural basis for understanding receptor-ligand interactions and designing subtype-selective serotonergic drugs.
Photovoltaic panels exposed to harsh environments such as mountains and deserts (e.g., the Gobi desert) for a long time are prone to hot-spot failures, which can affect power generation efficiency ...and even cause fires. The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is proposed. In this paper, the feature extraction part of YOLOv5 is replaced by the more lightweight Focus structure and the basic unit of ShuffleNetv2, and then the original feature fusion method is simplified. Considering that there is no publicly available infrared photovoltaic panel image dataset, this paper generates an infrared photovoltaic image dataset through frame extraction processing and manual annotation of a publicly available video. Consequently, the number of parameters of the model was 3.71 M, mAP was 98.1%, and detection speed was 49 f/s. A comprehensive comparison of the accuracy, detection speed, and model parameters of each model showed that the indicators of the new model are superior to other detection models; thus, the new model is more suitable to be deployed on the UAV platform for real-time photovoltaic panel hot-spot fault detection.
N-acetyl sugar amidotransferase (NASAT) is involved in the lipopolysaccharide (LPS) biosynthesis pathway that catalyzes the formation of the acetamido moiety (sugar-NC(=NH)CH3) on the O-chain. So ...far, little is known about its structural and functional properties. Here, we report the crystal structure of an N-acetyl sugar amidotransferase from Legionella pneumophila (LpNASAT) at 2.33 Å resolution. LpNASAT folds into a compact basin-shaped architecture with an unusually wide and open putative substrate-binding pocket and a conserved zinc ion-binding tetracysteine motif. The pocket contains a Rossmann-like fold with a PP-loop, suggesting that the NASAT-catalyzed amidotransfer reaction probably requires the conversion of ATP to AMP and PPi. Our data provide structural insights into the NASAT family of proteins, and allow us to possibly identify its functionally important regions.
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