Explore the vast range of titles available.

Fine classification of urban nighttime lighting is a key prerequisite step for small-scale nighttime urban research. In order to fill the gap of high-resolution urban nighttime light image classification and recognition research, this paper is based on a small rotary-wing UAV platform, taking the nighttime static monocular tilted light images of communities near Meixi Lake in Changsha City as research data. Using an object-oriented classification method to fully extract the spectral, textural and geometric features of urban nighttime lights, we build four types of classification models based on random forest (RF), support vector machine (SVM), K-nearest neighbor (KNN) and decision tree (DT), respectively, to finely extract five types of nighttime lights: window light, neon light, road reflective light, building reflective light and background. The main conclusions are as follows: (i) The equal division of the image into three regions according to the visual direction can alleviate the variable scale problem of monocular tilted images, and the multiresolution segmentation results combined with Canny edge detection are more suitable for urban nighttime lighting images; (ii) RF has the highest classification accuracy among the four classification algorithms, with an overall classification accuracy of 95.36% and a kappa coefficient of 0.9381 in the far view region, followed by SVM, KNN and DT as the worst; (iii) Among the fine classification results of urban light types, window light and background have the highest classification accuracy, with both UA and PA above 93% in the RF classification model, while road reflective light has the lowest accuracy; (iv) Among the selected classification features, the spectral features have the highest contribution rates, which are above 59% in all three regions, followed by the textural features and the geometric features with the smallest contribution rates. This paper demonstrates the feasibility of nighttime UAV static monocular tilt image data for fine classification of urban light types based on an object-oriented classification approach, provides data and technical support for small-scale urban nighttime research such as community building identification and nighttime human activity perception.

Sensing transparent objects has many applications in human daily life, including robot navigation and grasping. However, this task presents significant challenges due to the unpredictable nature of scenes that extend beyond/behind transparent objects, particularly the lack of fixed visual patterns and strong background interference. This paper aims to solve the transparent object segmentation problem by leveraging the intrinsic global modeling capabilities of transformer architectures. We design a Query Parsing Module (QPM) that innovatively formulates segmentation as a dictionary lookup problem, differing fundamentally from conventional pixel-wise mechanisms, e.g., via attention-based prototype matching, and a set of learnable class prototypes as query inputs. Based on QPM, we propose a high-performance transformer-based end-to-end segmentation model, Transparent Object Segmentation through Query (TOSQ). TOSQ’s encoder is based on the Segformer’s backbone, and its decoder consists of a series of QPM modules, which progressively refine segmentation masks by the proposed QPMs. TOSQ achieves state-of-the-art performance on the Trans10K-V2 dataset (76.63% mIoU, 95.34% Acc), with particularly significant gains in challenging categories like windows (+23.59%) and glass doors (+11.22%), demonstrating its superior capability in transparent object segmentation.

HighlightsA novel amide-based nonflammable electrolyte is proposed. The formation mechanism and solvation chemistry are investigated by molecular dynamics simulations and density functional theory.An inorganic/organic-rich solid electrolyte interphase with an abundance of LiF, Li3N and Li–N–C is in situ formed, leading to spherical lithium deposition.The amide-based electrolyte can enable stable cycling performance at room temperature and 60 ℃.The formation of lithium dendrites and the safety hazards arising from flammable liquid electrolytes have seriously hindered the development of high-energy-density lithium metal batteries. Herein, an emerging amide-based electrolyte is proposed, containing LiTFSI and butyrolactam in different molar ratios. 1,1,2,2-Tetrafluoroethyl-2,2,3,3-tetrafluoropropylether and fluoroethylene carbonate are introduced into the amide-based electrolyte as counter solvent and additives. The well-designed amide-based electrolyte possesses nonflammability, high ionic conductivity, high thermal stability and electrochemical stability (> 4.7 V). Besides, an inorganic/organic-rich solid electrolyte interphase with an abundance of LiF, Li3N and Li–N–C is in situ formed, leading to spherical lithium deposition. The formation mechanism and solvation chemistry of amide-based electrolyte are further investigated by molecular dynamics simulations and density functional theory. When applied in Li metal batteries with LiFePO4 and LiMn2O4 cathode, the amide-based electrolyte can enable stable cycling performance at room temperature and 60 ℃. This study provides a new insight into the development of amide-based electrolytes for lithium metal batteries.

Dense mapping is an important part of mobile robot navigation and environmental understanding. Aiming to address the problem that Dense Surfel Mapping relies on the input of a common-view relationship, we propose a local map extraction strategy based on spatiotemporal consistency. The local map is extracted through the inter-frame pose observability and temporal continuity. To reduce the blurring of map fusion caused by the different viewing angles, a normal constraint is added to the map fusion and weight initialization. To achieve continuous and stable time efficiency, we dynamically adjust the parameters of superpixel extraction. The experimental results on the ICL-NUIM and KITTI datasets show that the partial reconstruction accuracy is improved by approximately 27–43%. In addition, the system achieves a greater than 15 Hz real-time performance using only CPU computation, which is improved by approximately 13%.

Silicon is considered an exceptionally promising alternative to the most commonly used material, graphite, as an anode for next-generation lithium-ion batteries, as it has high energy density owing to its high theoretical capacity and abundant storage. Here, microsized walnut-like porous silicon/reduced graphene oxide （P-Si/rGO） core-shell composites are successfully prepared via in situ reduction followed by a dealloying process. The composites show specific capacities of more than 2,100 mAh-g-1 at a current density of 1,000 mA-g-1, 1,600 mAh.g-1 at 2,000 mA-g-1, 1,500 mAh-g 1 at 3,000 mA-g-1, 1,200 mAh-g-1 at 4,000 mA.g-1, and 950 mAh.g~ at 5,000 mA.g-~, and maintain a value of 1,258 mAh.g-~ after 300 cycles at a current density of 1,000 mA-g 1. Their excellent rate performance and cycling stability can be attributed to the unique structural design： 1） The graphene shell dramatically improves the conductivity and stabilizes the solid- electrolyte interface layers; 2） the inner porous structure supplies sufficient space for silicon expansion; 3） the nanostructure of silicon can prevent the pulverization resulting from volume expansion stress. Notably, this in situ reduction method can be applied as a universal formula to coat graphene on almost all types of metals and alloys of various sizes, shapes, and compositions without adding any reagents to afford energy storage materials, graphene-based catalytic materials, graphene-enhanced composites, etc.

We investigated the long-term variations in primary production in Lake Taihu using Moderate Resolution Imaging Spectroradiometer (MODIS) data, based on the Vertically Generalized Production Model (VGPM). We firstly test the applicability of VGPM in Lake Taihu by comparing the results between the model-derived and the in situ results, and the results showed that a strong significant correlation (R2 = 0.753, p < 0.001, n = 63). Then, VGPM was used to map temporal-spatial distributions of primary production in Lake Taihu. The annual mean daily primary production of Lake Taihu from 2003 to 2013 was 1094.06 ± 720.74 mg·C·m−2·d−1. Long-term primary production maps estimated from the MODIS data demonstrated marked temporal and spatial variations. Spatially, the primary production in bays, especially in Zhushan Bay and Meiliang Bay, was consistently higher than that in the open area of Lake Taihu, which was caused by chlorophyll-a concentrations resulting from high nutrient concentrations. Temporally, the seasonal variation of primary production from 2003 to 2013 was: summer > autumn > spring > winter, with significantly higher primary production found in summer and autumn than in winter (p < 0.005, t-test), primarily caused by seasonal variations in water temperature. On a monthly scale, the primary production exerts a clear character of bimodality, increasing from January to May, decreasing in June or July, and finally reaching its highest value during August or September. Wind is another important factor that could affect the spatial variations of primary production in the large, eutrophic and shallow Lake Taihu.

Dramatic growth of lithium dendrite, structural deterioration of LiCoO2 (LCO) cathode at high voltages, and unstable electrode/electrolyte interfaces pose significant obstacles to the practical application of high‐energy‐density LCO||Li batteries. In this work, a novel eutectogel electrolyte is developed by confining the nonflammable eutectic electrolyte in a polymer matrix. The eutectogel electrolyte can construct a robust solid electrolyte interphase (SEI) with inorganic‐rich LiF and Li3N, contributing to a uniform Li deposition. Besides, the severe interface side reactions between LCO cathode and electrolyte can be retarded with an in situ formed protective layer. Correspondingly, Li||Li symmetrical cells achieve highly reversible Li plating/stripping over 1000 h. The LCO||Li full cell can maintain 72.5% capacity after 1500 cycles with a decay rate of only 0.018% per cycle at a high charging voltage of 4.45 V. Moreover, the well‐designed eutectogel electrolyte can even enable the stable operation of LCO at an extremely high cutoff voltage of 4.6 V. This work introduces a promising avenue for the advancement of eutectogel electrolytes, the nonflammable nature and well‐regulated interphase significantly push forward the future application of lithium metal batteries and high‐voltage utilization of LCO cathode. A well‐designed eutectogel electrolyte constructs a robust solid electrolyte interphase with inorganic‐rich LiF and Li3N, contributing to a uniform Li deposition. The severe interface side reactions between LiCoO2 cathode and electrolyte can be retarded with an in situ formed protective layer. The well‐regulated interphases ensure the long cycling performance of high energy density LCO||Li cells at high voltage.

In scenes where there are lighting changes, localization may fail for visual SLAM due to feature point tracking failure. Thus, a feature point tracking method based on multi-condition constraints is proposed for visual SLAM. The proposed method tracks the feature points of optical flow from aspects such as the overall motion position of feature points, descriptor grayscale information, and spatial geometric constraints. First, to solve the problem of feature point mismatch in complex environments, we propose a feature point mismatch removal method that combines optical flow, descriptor, and RANSAC. We eliminate incorrect feature point matches layer by layer through these constraints. The uniformity of feature point distribution in the image can then affect the accuracy of camera pose estimation, and different scenes can also affect the difficulty of feature point extraction. In order to balance the quality and uniformity of the extracted feature points, we propose an adaptive mask homogenization method that adaptively adjusts the mask radius according to the quality of feature points. Experiments conducted on the EuRoC dataset show that the proposed method which integrates the improved feature point mismatch removal method and mask homogenization method into feature point tracking, exhibits robustness and accuracy under various interferences such as lighting changes, image blurring, and unclear textures. Compared to the RANSAC method, we reduce the location error by about 85% using the EuRoC dataset.

This study aimed to investigate the effects of dietary supplementation with methylsulfonylmethane (MSM) and myo-inositol (MI) on hair quality, fecal microbiota, and metabolome in poodles. Thirty-two adult poodles categorized based on initial body weight and sex were randomly assigned to four groups. These groups (designated the CON, MSM, MI, and MSM + MI groups) received a basal diet, the same diet supplemented with 0.2% MSM + 0% MI, the same diet supplemented with 0% MSM + 0.2% MI, or the same diet supplemented with 0.2% MSM + 0.2% MI, respectively. The study lasted for 65 days. During the entire study period, body weight, average daily weight gain, feed intake, energy intake, and fecal output were normal in all the animals and did not differ significantly among the treatment groups. Hair scale thickness was lower in the MI and MSM + MI groups than in the CON group on Day 65 (p < 0.05). An amino acid analysis of the hair revealed higher sulfur content in the MI and MSM + MI groups on Day 65 than on Day 0 (p < 0.05). Moreover, the poodles in the MSM, MI, and MSM + MI groups presented significantly lower levels of Proteobacteria_unclassified and Candidatus Phytoplasma than did those in the CON group. The relative abundance of Gammaproteobacteria_unclassified was greater in the MSM and MI groups than in the CON group (p < 0.05). The MSM group presented a greater abundance of Glucerabacter than the CON group (p < 0.05). Compared with those in the CON and MSM + MI groups, the abundances of Paramuribaculum and Hafnia in the MSM group were greater (p < 0.05). The abundances of Enterobacter and Kineothrix were greater (p < 0.05) in the MI group than in the CON and MSM + MI groups. The poodles in the MI group presented significantly greater abundances of Bacteroidales_unclassified, Halanaerobium, Mycobacterium, and Erysipelotrichaceae_unclassified than did poodles in the CON, MSM, and MSM + MI groups. Fecal metabolomics analysis revealed that MSM, MI, and MSM + MI treatment markedly affected carbohydrate metabolism. MSM + MI treatment also influenced lipid metabolism. These findings suggest that dietary supplementation with MSM and MI can improve the hair quality of poodles.

This paper introduced the calibration of the CE‐318 sunphotometer of the China Aerosol Remote Sensing Network (CARSNET) and the validation of aerosol optical depth (AOD) by AOD module of ASTPWin software compared with the simultaneous measurements of the Aerosol Robotic Network (AERONET)/Photométrie pour le Traitement Opérationnel de Normalization Satellitaire (PHOTONS) and PREDE skyradiometer. The results show that the CARSNET AOD measurements have the same accuracy as the AERONET/PHOTONS. On the basis of a comparison between CARSNET and AERONET, the AODs from CARSNET at 1020, 870, 670, and 440 nm are about 0.03, 0.01, 0.01, and 0.01 larger than those from AERONET, respectively. The aerosol optical properties over Beijing acquired through the CE‐318 sunphotometers of one AERONET/PHOTONS site and two CARSNET sites were analyzed on the basis of 4‐year measurements. It was obvious that the AOD of the Shangdianzi site (rural site) was lower than that of the two urban sites (the Institute of Atmospheric Physics (IAP) site (north urban site) and the Beijing Meteorological Observatory (BJO) site (south urban site)). The AOD of BJO was about 0.05, 0.04, 0.05, and 0.06 larger than that of IAP at 1020, 870, 670, and 440 nm, respectively, indicating that there is more local pollution in the south part of Beijing. The highest AOD was found in summer because of the stagnation planetary boundary layer and transport of pollutants from large pollution centers south of Beijing. The high temperature and relative humidity in summer also favor the production of aerosol precursor and the hygroscopic growth of the existing particles locally, which results in high AOD. In contrast, the lowest AOD at the two urban sites and one rural site in Beijing occurred in winter as the frequent cold air masses help pollutants diffuse easily.