Explore the vast range of titles available.

An improved Dijkstra algorithm based on adaptive resolution grid (ARG) is proposed to assist manual transmission line planning, shorten the construction period and achieve lower cost and higher efficiency of line selection. Firstly, the semantic segmentation network is used to change the remote sensing image into a ground object-identification image and the grayscale image of the ground object-identification image is rasterized. The ARG map model is introduced to greatly reduce the number of redundant grids, which can effectively reduce the time required to traverse the grids. Then, the Dijkstra algorithm is combined with the ARG and the neighborhood structure of the grid is a multi-center neighborhood. An improved method of bidirectional search mechanism based on ARG and inflection point-correction is adopted to greatly increase the running speed. The inflection point-correction reduces the number of inflection points and reduces the cost. Finally, according to the results of the search, the lowest-cost transmission line is determined. The experimental results show that this method aids manual planning by providing a route for reference, improving planning efficiency while shortening the duration, and reducing the time spent on algorithm debugging. Compared with the comparison algorithm, this method is faster in running speed and better in cost saving and has a broader application prospect.

In this paper, a finite-time controller is proposed for the quadrotor aircraft to achieve hovering control in a finite time. The design of controller is mainly divided into two steps. Firstly, a saturated finite-time position controller is designed such that the position of quadrotor aircraft can reach any desired position in a finite time. Secondly, a finite-time attitude tracking controller is designed, which can guarantee that the attitude of quadrotor aircraft converges to the desired attitude in a finite time. By homogenous system theory and Lyapunov theory, the finite-time stability of the closed-loop systems is given through rigorous mathematical proofs. Finally, numerical simulations are given to show that the proposed algorithm has a faster convergence performance and a stronger disturbance rejection performance by comparing to the PD control algorithm.

The planning of power transmission line projects encompasses vast and complex geographical terrains. To address the complexity of transmission line planning and achieve lower line costs, this study proposes a novel intelligent line planning method. For the first time, it combines the Dueling Double Deep Q Network (D3QN) with the prioritized experience replay (PER) mechanism. First, correlate the reward function with metrics such as line length, number of corner points, and geographical environmental data, which are pertinent to the construction costs of power transmission line. Second, the D3QN algorithm is formulated by integrating Double DQN and Dueling DQN. The network's input information is divided into two components during training, aligning with the characteristics of power transmission line planning projects. Finally, the convergence efficiency of the algorithm is improved by using the PER mechanism for the problem of cost difference due to the different number of corner points in the planning path. In order to test the feasibility of the algorithm, we conducted experiments using real maps. Compared with the traditional ant colony optimization (ACO) algorithm, the D3QN‐PER deep reinforcement learning algorithm reduces the line length by more than 4% and the number of corner points by more than 60%. This paper describes the theoretical basis and practical effect of establishing an intelligent route selection model for power transmission line planning based on deep reinforcement learning algorithm. The planning results of this deep reinforcement learning algorithm are compared with those of the traditional ant colony algorithm in real maps, and this deep reinforcement learning algorithm reduces the length of the line by more than 4%, and the number of inflection points by more than 60%, which can effectively reduce the cost of power transmission line planning.

In order to achieve the automatic planning of power transmission lines, a key step is to precisely recognize the feature information of remote sensing images. Considering that the feature information has different depths and the feature distribution is not uniform, a semantic segmentation method based on a new AS-Unet++ is proposed in this paper. First, the atrous spatial pyramid pooling (ASPP) and the squeeze-and-excitation (SE) module are added to traditional Unet, such that the sensing field can be expanded and the important features can be enhanced, which is called AS-Unet. Second, an AS-Unet++ structure is built by using different layers of AS-Unet, such that the feature extraction parts of each layer of AS-Unet are stacked together. Compared with Unet, the proposed AS-Unet++ automatically learns features at different depths and determines a depth with optimal performance. Once the optimal number of network layers is determined, the excess layers can be pruned, which will greatly reduce the number of trained parameters. The experimental results show that the overall recognition accuracy of AS-Unet++ is significantly improved compared to Unet.

Extreme precipitation occurring on consecutive days may substantially increase the risk of related impacts, but changes in such events have not been studied at a global scale. Here we use a unique global dataset based on in situ observations and multimodel historical and future simulations to analyze the changes in the frequency of extreme precipitation on consecutive days (EPCD). We further disentangle the relative contributions of variations in precipitation intensity and temporal correlation of extreme precipitation to understand the processes that drive the changes in EPCD. Observations and climate model simulations show that the frequency of EPCD is increasing in most land regions, in particular, in North America, Europe, and the Northern Hemisphere high latitudes. These increases are primarily a consequence of increasing precipitation intensity, but changes in the temporal correlation of extreme precipitation regionally amplify or reduce the effects of intensity changes. Changes are larger in simulations with a stronger warming signal, suggesting that further increases in EPCD are expected for the future under continued climate warming.

With the development of robot technology and the extensive application of robots, the research on special robots for some complex working environments has gradually become a hot topic. As a special robot applied to transmission towers, the climbing robot can replace humans to work at high altitudes to complete bolt tightening, detection, and other tasks, which improves the efficiency of transmission tower maintenance and ensures personal safety. However, it is mostly the ability to autonomously locate in the complex environment of the transmission tower that limits the industrial applications of the transmission tower climbing robot. This paper proposes an intelligent positioning method that integrates the three-dimensional information model of transmission tower and visual sensor data, which can assist the robot in climbing and adjusting to the designated working area to guarantee the working accuracy of the climbing robots. The experimental results show that the positioning accuracy of the method is within 1 cm.

Calcium and integrin-binding protein 2 (CIB2) belongs to a protein family with four known members, CIB1 through CIB4, which are characterized by multiple calcium-binding EF-hand domains. Among the family members, the and genes are expressed in mouse cochlear hair cells, and mutations in the human gene have been associated with nonsyndromic deafness DFNB48 and syndromic deafness USH1J. To further explore the function of CIB1 and CIB2 in hearing, we established and knockout mice using the clustered regularly interspaced short palindromic repeat (CRISPR)-associated Cas9 nuclease (CRISPR/Cas9) genome editing technique. We found that loss of CIB1 protein does not affect auditory function, whereas loss of CIB2 protein causes profound hearing loss in mice. Further investigation revealed that hair cell stereocilia development is affected in knockout mice. Noticeably, loss of CIB2 abolishes mechanoelectrical transduction (MET) currents in auditory hair cells. In conclusion, we show here that although both CIB1 and CIB2 are readily detected in the cochlea, only loss of CIB2 results in profound hearing loss, and that CIB2 is essential for auditory hair cell MET.

The merging of environmental maps constructed by individual UAVs alone and the sharing of information are key to improving the efficiency of distributed multi-UAVexploration. This paper investigates the raster map-merging problem in the absence of a common reference coordinate system and the relative position information of UAVs, and proposes a raster map-merging method with a directed crossover multidimensional perturbation variational genetic algorithm (DCPGA). The algorithm uses an optimization function reflecting the degree of dissimilarity between the overlapping regions of two raster maps as the fitness function, with each possible rotation translation transformation corresponding to a chromosome, and the binary encoding of the coordinates as the gene string. The experimental results show that the algorithm could converge quickly and had a strong global search capability to search for the optimal overlap area of the two raster maps, thus achieving map merging.

Stereocilia are actin-based cell protrusions of inner ear hair cells and are indispensable for mechanotransduction. Ankle links connect the ankle region of developing stereocilia, playing an essential role in stereocilia development. WHRN, PDZD7, ADGRV1 and USH2A have been identified to form the so-called ankle link complex (ALC); however, the detailed mechanism underlying the temporal emergence and degeneration of ankle links remains elusive. Here we show that WHRN and PDZD7 orchestrate ADGRV1 and USH2A to assemble the ALC through liquid-liquid phase separation (LLPS). Disruption of the ALC multivalency for LLPS largely abolishes the distribution of WHRN at the ankle region of stereocilia. Interestingly, high concentration of ADGRV1 inhibits LLPS, providing a potential mechanism for ALC disassembly. Moreover, certain deafness mutations of ALC genes weaken the multivalent interactions of ALC and impair LLPS. In conclusion, our study demonstrates that LLPS mediates ALC formation, providing essential clues for understanding the pathogenesis of deafness. In this work, the authors demonstrate that LLPS of the quaternary USH2 protein complex initiates the formation of stereociliary ankle link condensates, providing insights into the pathogenesis of deafness.

● Wetlands have been fragmented over the last century by environmental changes. ● The relative importance of human activities and climate change varies geographically. ● Human activities are more important than climate change at the century scale. ● Climate change is more important at the decadal scale. ● Geographic factors are most important in all periods of the past century. Mid and high latitude wetlands are becoming fragmented and losing ecosystem functions at a much faster rate than many other ecosystems. This is due in part to increasing human activities and climate change. In this study, we analyzed wetland distribution and spatial pattern changes for the Heilongjiang River Basin over the past 100 yr. We identified the driving factors and quantified the relative importance of each factor based on landscape pattern metrics and machine learning algorithms. Our results show that wetlands have been fragmented into smaller and regular patches with dominant factors that varied at different periods. Geographic features play the most important role in patterns of wetland change for the entire basin (with 50%-60% of relative importance). Human activities are more important than climate change at the century scale, but less important when magnified at the decadal scale. In the early 1900s, human activities were relatively low and localized and remained that way in the subsequent decades. Thus, the effect of human activities on wetland area of the entire basin is weaker when examined at the magnified decadal scale. The results also show that human activities are more important on the Chinese side of the Heilongjiang River Basin, in the Zeya-Bureya Plain on the Russian side, and at lower altitudes (0-100 m). Revealing the spatial and temporal processes and driving factors over the past 100 yr helps researchers and policymakers understand and anticipate wetland change and design effective conservation and restoration policies.