In recent years, with the rapid growth of State Grid digitization, it has become necessary to perform three-dimensional (3D) reconstruction of power elements with high efficiency and precision to ...achieve full coverage when simulating important transmission lines. Limited by the performance of acquisition equipment and the environment, the actual scanned point cloud usually has problems such as noise interference and data loss, presenting a great challenge for 3D reconstruction. This study proposes a model-driven 3D reconstruction method based on Airborne LiDAR point cloud data. Firstly, power pylon redirection is realized based on the Principal Component Analysis (PCA) algorithm. Secondly, the vertical and horizontal distribution characteristics of the power pylon point cloud and the graphical characteristics of the overall two-dimensional (2D) orthographic projection are analyzed to determine segmentation positions and the key segmentation position of the power pylon. The 2D alpha shape algorithm is adopted to obtain the pylon body contour points, and then the pylon feature points are extracted and corrected. Based on feature points, the components of original pylon and model pylon are registered, and the distance between the original point cloud and the model point cloud is calculated at the same time. Finally, the model with the highest matching degree is regarded as the reconstructed model of the pylon. The main advantages of the proposed method include: (1) identifying the key segmentation position according to the graphical characteristics; (2) for some pylons with much missing data, the complete model can be accurately reconstructed. The average RMSE (Root-Mean-Square Error) of all power pylon components in this study was 15.4 cm. The experimental results reveal that the effects of power pylon structure segmentation and reconstruction are satisfactory, which provides method and model support for digital management and security analysis of transmission lines.
Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) provides effective photon-counting light detection and ranging (LiDAR) data for estimating forest height across extensive geographical areas. ...Although prior studies have illustrated canopy conditions during leaf-on and leaf-off phases may influence ICESat-2 derived forest heights, a comprehensive understanding of this effect remains incomplete. This study seeks to comprehensively assess how varying canopy conditions (leaf-on/leaf-off) affect ICESat-2 forest height retrieval and modelling. First, the accuracies of ICESat-2 terrain and canopy heights under leaf-on and leaf-off conditions were validated. Second, random forest algorithm was utilized to model forest height by integrating ICESat-2, Sentinel-2, and other ancillary datasets. Finally, we evaluated the influence of leaf-on and leaf-off conditions on forest height retrieval and modelling. Results reveal higher consistency between ICESat-2 and airborne LiDAR-derived terrain heights compared to the agreement between two canopy height datasets. Accuracies of ICESat-2 terrain and canopy heights are higher under leaf-off conditions in contrast to leaf-on conditions. Notably, the accuracies of ICESat-2 terrain and canopy heights under various conditions are closely linked to canopy cover. Furthermore, the accuracy of forest height modelling can be enhanced by combining ICESat-2 data collected during both leaf-on and leaf-off seasons with further eliminating low-quality samples.
Background
Few studies to date have analyzed the epidemiology of acute kidney injury (AKI) in children with cancer in developing countries. The aim of this study was to assess the incidence, risk ...profile and outcomes of AKI in Chinese children hospitalized with cancer.
Methods
This multi-center study analyzed Chinese children hospitalized with cancer in 2013–2015. Electronic hospital and laboratory databases were screened to select pediatric patients with malignancy who had at least two Scr results within any 7-day window during their first 30 days of hospitalization. AKI events were identified and staged according to Kidney Disease Improving Global Outcomes (KDIGO) criteria. The incidence of and risk factors for AKI were analyzed, as were mortality rate, incidence of kidney recovery, and length of hospital stay.
Results
Of the 9828 children with cancer, 1657 (16.9%) experienced AKI events, including 549 (5.6%) community-acquired (CA-AKI) and 1108 (11.3%) hospital-acquired AKI (HA-AKI) events. The three types of cancer with the highest incidence of AKI were urinary system cancer (25.8%), hepatic cancer (19.4%), and retroperitoneal malignancies (19.1%). The risk factor profiles of CA-AKI and HA-AKI events differed, with many HA-AKI events due to treatment with nephrotoxic agents. In-hospital death rates were 5.4% (90 of 1657) in children with and 0.9% (74 of 8171) in children without AKI events. AKI events were also associated with longer hospitalization and higher daily costs.
Conclusions
AKI events are common among Chinese children hospitalized for cancer and are associated with adverse in-hospital outcomes.
The ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) can collect earth surface elevation data with high precision on a global scale. However, the collected photon data contains a large amount of ...background noise due to the influence of sunlight, cloud reflection, and other factors. For photon data of different scenes, how to effectively denoise and achieve accurate classification of photon point clouds is crucial for subsequent applications. This study proposes a random forest based method for denoising and classifying ICESat-2 photon data in urban areas by fusing spectral features from Sentinel-2 images and spatial distribution features from photon data. The experimental results show that the method can effectively identify various types of photons. Compared with the reference data, the overall accuracy of photon denoising and classification is 95.97% on average, and the average kappa coefficient is 94.18%. Further analysis demonstrates that the addition of sentinel-2 spectral information can effectively improve the classification accuracy of photon point clouds in urban areas, and the photon classification method of combining photon lidar data and optical images can be a promising solution to improve classification accuracy.
Martensitic transformations, mechanical properties, shape memory effect and superelasticity of Ti–
x
Zr–(30–
x
)Nb–4Ta (
x
= 15, 16, 17 and 18; at%) alloys were investigated. X-ray diffraction ...(XRD), optical microscopy (OM) and transmission electron microscopy (TEM) results indicated that the Ti–16Zr–14Nb–4Ta, Ti–17Zr–13Nb–4Ta and Ti–18Zr–12Nb–4Ta alloys were mainly composed of α″-martensite, while the Ti–15Zr–15Nb–4Ta alloy was characterized by predominant β phase. The reverse martensitic transformation temperatures increased when Nb was replaced by Zr, indicating stronger β-stabilizing effect for the former. The Ti–15Zr–15Nb–4Ta alloy displayed superelasticity during tensile deformation with a recovery strain of 3.51%. For the other three alloys with higher Zr content, the martensitic reorientation occurred during tensile deformation, resulting in shape memory recovery upon subsequent heating. The maximum shape memory effect was 3.46% in the Ti–18Zr–12Nb–4Ta alloy.
Background
Forest canopy height is a key forest structure parameter. Precisely estimating forest canopy height is vital to improve forest management and ecological modelling. Compared with ...discrete-return LiDAR (Light Detection and Ranging), small-footprint full-waveform airborne LiDAR (FWL) techniques have the capability to acquire precise forest structural information. This research mainly focused on the influence of voxel size on forest canopy height estimates.
Methods
A range of voxel sizes (from 10.0 m to 40.0 m interval of 2 m) were tested to obtain estimation accuracies of forest canopy height with different voxel sizes. In this study, all the waveforms within a voxel size were aggregated into a voxel-based LiDAR waveform, and a range of waveform metrics were calculated using the voxel-based LiDAR waveforms. Then, we established estimation model of forest canopy height using the voxel-based waveform metrics through Random Forest (RF) regression method.
Results and conclusions
The results showed the voxel-based method could reliably estimate forest canopy height using FWL data. In addition, the voxel sizes had an important influence on the estimation accuracies (
R
2
ranged from 0.625 to 0.832) of forest canopy height. However, the
R
2
values did not monotonically increase or decrease with the increase of voxel size in this study. The best estimation accuracy produced when the voxel size was 18 m (
R
2
= 0.832, RMSE = 2.57 m, RMSE% = 20.6%). Compared with the lowest estimation accuracy, the
R
2
value had a significant improvement (33.1%) when using the optimal voxel size. Finally, through the optimal voxel size, we produced the forest canopy height distribution map for this study area using RF regression model. Our findings demonstrate that the optimal voxel size need to be determined for improving estimation accuracy of forest parameter using small-footprint FWL data.
The monitoring of telegraph poles as essential features supporting overhead distribution network lines is the primary subject of this work. This paper proposes a method for locating and extracting ...telegraph poles from an image matching-based point cloud. Firstly, the point cloud of the poles is extracted using the planar grid segmentation clustering algorithm and the connected component analysis algorithm of the region grows according to the isolated features of the poles perpendicular to the ground. Secondly, the candidate telegraph poles are located based on the suspension point of the buffer, considering that the top of the pole is connected to the power suspension line. Thirdly, the horizontal projection method of the backbone area is utilized to eliminate the interference of vegetation in the buffer area. Finally, the point cloud of the telegraph pole is extracted through the density-based spatial clustering of applications with noise (DBSCAN) algorithm. The experimental results demonstrate that the average values of Recall, Precision, and F1-score in telegraph pole detection can reach 91.09%, 90.82%, and 90.90%, respectively. The average RMSE value of location deviation is 0.51m. The average value of the F1-score in the telegraph pole extraction is 91.83%, and the average extraction time of a single pole is 0.27s. Accordingly, this method has strong adaptability to areas with lush vegetation and can automatically locate and extract the telegraph pole point cloud with high accuracy, and it can still achieve very high accuracy even under the holes in the data.
Communication tower (CT) and its accessory equipment (AE) such as radio frequency equipment (RFE) and antenna, are essential in providing highspeed and stable mobile network services. It is necessary ...to routinely monitor the security and stability of CT and AE for seamless communication. There is limited research on fine segmentation of communication base station objects. This paper proposes a method for accurately segmenting the point cloud of the CT and AE from Terrestrial Laser Scanning (TLS) data. At first, the CT point cloud is accurately segmented based on region growing and Random Sample Consensus (RANSAC). Then, the point cloud of pole-shaped apart is extended to a certain distance to obtain the buffer point cloud containing AE. Normal Differential (ND) clustering is employed to obtain several groups of clusters containing planes, and calculate each plane's filling rate and size. Finally, the cluster type (such as antenna, RFE, or other) is distinguished. The experimental results demonstrate that the point-based average F1-score of CTs is 98. 70%, the point-based and object-based average F1-scores of antennas are 96. 09% and 97. 93%, and the corresponding values for the RFE are 89. 89% and 90. 00%, respectively, indicating the optimal performance of the proposed method.
The abnormally hyperphosphorylated tau is thought to be implicated in diabetes-associated cognitive deficits. The role of mammalian target of rapamycin (mTOR) / S6 kinase (S6K) signalling in the ...formation of tau hyperphosphorylation has been previously studied. Caveolin-1 (Cav-1), the essential structure protein of caveolae, promotes neuronal survival and growth, and inhibits glucose metabolism. In this study, we aimed to investigate the role of Cav-1 in the formation of tau hyperphosphorylation under chronic hyperglycemic condition (HGC). Diabetic rats were induced by streptozotocin (STZ). Primary hippocampal neurons with or without molecular intervention such as the transient over-expression or knock-down were subjected to HGC. The obtained experimental samples were analyzed by real time quantitative RT-PCR, Western blot, immunofluorescence or immunohistochemisty. We found: 1) that a chronic HGC directly decreases Cav-1 expression, increases tau phosphorylation and activates mTOR/S6K signalling in the brain neurons of diabetic rats, 2) that overexpression of Cav-1 attenuates tau hyperphosphorylation induced by chronic HGC in primary hippocampal neurons, whereas down-regulation of Cav-1 using Cav-1 siRNA dramatically worsens tau hyperphosphorylation via mTOR/S6K signalling pathway, and 3) that the down-regulation of Cav-1 induced by HGC is independent of mTOR signalling. Our results suggest that tau hyperphosphorylation and the sustained over-activated mTOR signalling under hyperglycemia may be due to the suppression of Cav-1. Therefore, Cav-1 is a potential therapeutic target for diabetes-induced cognitive dysfunction.
The R-Spondin (RSpo) family of secreted proteins act as potent activators of the Wnt/β-catenin signaling pathway. We have previously shown that RSpo proteins can induce proliferative effects on the ...gastrointestinal epithelium in mice. Here we provide a mechanism whereby RSpo1 regulates cellular responsiveness to Wnt ligands by modulating the cell-surface levels of the coreceptor LRP6. We show that RSpo1 activity critically depends on the presence of canonical Wnt ligands and LRP6. Although RSpo1 does not directly activate LRP6, it interferes with DKK1/Kremen-mediated internalization of LRP6 through an interaction with Kremen, resulting in increased LRP6 levels on the cell surface. Our results support a model in which RSpo1 relieves the inhibition DKK1 imposes on the Wnt pathway.
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