A New Map Symbol Design Method for Real-Time Visualization of Geo-Sensor Data (Short Paper)

Maps are an excellent way to present data with spatial components. For the large-scale geo-sensors being utilized in recent years, the map-based management and visualization of geo-senor data have become ubiquitous. Without a doubt, managing and visualizing geo-sensor data on maps will have vastly more future applications. However, current maps typically do not support real-time communication in the Internet of Things (IoT), and it is difficult to implement real-time visualization of sensor data on a map. Map symbols are the language of maps. In this paper, we describe a new map symbol design method for geo-sensor data acquisition and visualization on maps. We refer to the sensor data visual method in supervisory control and data acquisition system (SCADA) and apply it to the design process of map symbols. Based on the traditional vector map symbol, the mapping relationship between the sensor data and the graphic element is defined in the map symbol design process. When the map symbol is rendered in the map, the map symbol is integrated into the map layer. The communication module in the map that communicates with the sensor device receives real-time sensor data and triggers a refresh of the map layer according to the mapping profile. All the methods and processes shown herein have been verified in GeoTools

Real-Time Visualization of Geo-Sensor Data Based on the Protocol-Coupling Symbol Construction Method

Obtaining and visualizing the internal state and position information of the remote device using sensors are important aspects of industrial manufacturing. For large-scale geo-sensors that have been recently used, map-based management and visualization of the geo-sensor devices have become ubiquitous. Users often build multiple map symbols to represent the multiple states of a device based on traditional map symbols. Visualizing multiple geo-sensor data in real time with one map symbol is difficult. In this paper, a protocol-coupling map symbol and a construction method for real-time data visualization is introduced where different sensor states of the geo-sensor are expressed with one symbol. The sensor data visualization method in supervisory control and data acquisition systems (SCADA) was introduced and applied to the construction and visualization process of map symbols. First, based on the traditional vector map symbols and the communication protocol parsing interface, the mapping relationship between the sensor data item and the graphic element is defined in the map symbol construction process. Second, by referring to the streaming services method in ArcGIS GeoEvent, geo-sensor data acquisition and a transfer broker in a GIS server is built, through which the real-time sensor data can be transferred from the remote side to the map client and used for map symbol rendering. Finally, the new map symbols are used for real-time geo-sensor data visualization in applications. In the application of the real-time monitoring of geo-sensor devices, remote device information was acquired by sensor and transmitted to the broker then cached on the server side. If the cached sensor data has changed compared to the previous, the changed data will be pushed to map client by broker. The communication module in the map client that communicates with the broker receives changed geo-sensor data and triggers a refresh of the map. Then the protocol-coupling map symbol is rendered according to the mapping profile and the status of the geo-sensor device will be displayed on the map in real time. All the methods and processes were verified in client-server and browser-server GIS architecture

Super-resolution reconstruction of a digital elevation model based on a deep residual network

The digital elevation model (DEM) is an important basic data tool applied in geoscience applications. Because of its high cost and long development cycle of enhancing hardware performance, designing the related models and algorithms to improve the resolution of DEM is of considerable significance. At present, there is little research on DEM super-resolution based on deep learning, and the results of the reconstructed DEMs obtained by existing methods are inaccurate. Therefore, deepening of the network layers is utilized to improve the accuracy of a reconstructed DEM. This paper designs a neutral network model with 30 convolutional layers to learn the feature mapping relationship between a low- and high-resolution DEM. To avoid the problem of network degradation caused by increasing the number of convolutional layers, residual learning is introduced to accelerate the convergence speed of the model, thereby preferably realizing the DEM super-resolution process. The results show that DEM super-resolution based on a deep residual network is better than that obtained using a neural network with fewer convolutional layers, and the reconstructed result of the DEM based on a deep residual network is remarkably improved in terms of the peak signal to noise ratio and visual effect

Bump feature detection of the road surface based on the Bi-LSTM

The road network is the basic facility for transportation systems in the city. Every day, a large number of vehicles move on the road and exert different pressure on the ground, which leads to various problems for the road surface, such as the bump features of the road surface (BFRS). However, traditional methods, such as detecting BFRS manually or with professional equipment, require a lot of professional management and devices. Based on the mobile sensor and the bidirectional long short-term memory (Bi-LSTM), a detection method for BFRS is proposed. The BFRS detection method proposed in this article solves the problem that other BFRS detection methods cannot detect large area road surface efficiently and provides an algorithm idea for efficient detection of large area road surface BFRS. The mobile phone with multi-sensors is carried on vehicles, and the BFRS information is logged during the movements. The orientation of the mobile is computed according to the gyroscope. The actual posture of the acceleration sensor is adjusted with the reference coordinate system, whose z-axis is vertical to the ground. This article uses the adjusted acceleration data as the training dataset and labels it according to time stamps and videos recorded by the driving recorder. Finally, the Bi-LSTM is constructed and trained, followed by the BFRS detection. The results show that it can detect BFRS in different regions. The detection accuracy of the campus section and the extended experiment was 92.85 and 87.99%, respectively

Evaluation of MODIS DT, DB, and MAIAC Aerosol Products over Different Land Cover Types in the Yangtze River Delta of China

The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) has been widely used in atmospheric environment and climate change research. Based on data of the Aerosol Robotic Network and Sun–Sky Radiometer Observation Network in the Yangtze River Delta, the retrieval accuracies of MODIS C6.1 Dark Target (DT), Deep Blue (DB), and C6.0 Multi-angle Implementation of Atmospheric Correction (MAIAC) products under different land cover types, aerosol types, and observation geometries were analyzed. About 65.64% of MAIAC AOD is within the expected error (Within EE), which is significantly higher than 41.43% for DT and 56.98% for DB. The DT product accuracy varies most obviously with the seasons, and the Within EE in winter is more than three times that in spring. The DB and MAIAC products have low accuracy in summer but high in other seasons. The accuracy of the DT product gradually decreases with the increase in urban and water land-cover proportion. After being corrected by bias and mean relative error, the DT accuracy is significantly improved, and the Within EE increases by 24.12% and 32.33%, respectively. The observation geometries and aerosol types were also examined to investigate their effects on AOD retrieval

Oncoprotein SET-associated transcription factor ZBTB11 triggers lung cancer metastasis

Abstract Metastasis is the major cause of lung cancer-related death, but the mechanisms governing lung tumor metastasis remain incompletely elucidated. SE translocation (SET) is overexpressed in lung tumors and correlates with unfavorable prognosis. Here we uncover SET-associated transcription factor, zinc finger and BTB domain-containing protein 11 (ZBTB11), as a prometastatic regulator in lung tumors. SET interacts and collaborates with ZBTB11 to promote lung cancer cell migration and invasion, primarily through SET-ZBTB11 complex-mediated transcriptional activation of matrix metalloproteinase-9 (MMP9). Additionally, by transcriptional repression of proline-rich Gla protein 2 (PRRG2), ZBTB11 links Yes-associated protein 1 (YAP1) activation to drive lung tumor metastasis independently of SET-ZBTB11 complex. Loss of ZBTB11 suppresses distal metastasis in a lung tumor mouse model. Overexpression of ZBTB11 is recapitulated in human metastatic lung tumors and correlates with diminished survival. Our study demonstrates ZBTB11 as a key metastatic regulator and reveals diverse mechanisms by which ZBTB11 modulates lung tumor metastasis

Noble Metal-Free Ceria-Zirconia Solid Solutions Templated by Tobacco Materials for Catalytic Oxidation of CO

A series of ceria-zirconia solid solutions were synthesized using tobacco leaves, stems and stem-silks as biotemplates. A combination of physicochemical techniques such as powder X-ray diffraction (XRD), N2 adsorption/desorption measurement, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were used to characterize the as-synthesized samples. The results show that the morphologies of the templates were well replicated in the obtained ceria-zirconia solid solutions. Catalytic oxidation activities of CO over the ceria-zirconia solid solutions were then investigated. The catalyst templated by tobacco stem-silk exhibited higher conversion of CO at lower temperature than that of ceria-zirconia solid solutions templated by tobacco leaves and stems or without templates due to its special morphology. The catalyst even showed similar CO conversion when compared to ceria-zirconia solid solutions doped with 1.0 wt % noble metals such as Pt, Ag and Au. The results highlighted the advantages of using tobacco as biotemplate

Coupled deglycosylation-ubiquitination cascade in regulating PD-1 degradation by MDM2

Summary: Posttranslational modifications represent a key step in modulating programmed death-1 (PD-1) functions, but the underlying mechanisms remain incompletely defined. Here, we report crosstalk between deglycosylation and ubiquitination in regulating PD-1 stability. We show that the removal of N-linked glycosylation is a prerequisite for efficient PD-1 ubiquitination and degradation. Murine double minute 2 (MDM2) is identified as an E3 ligase of deglycosylated PD-1. In addition, the presence of MDM2 facilitates glycosylated PD-1 interaction with glycosidase NGLY1 and promotes subsequent NGLY1-catalyzed PD-1 deglycosylation. Functionally, we demonstrate that the absence of T cell-specific MDM2 accelerates tumor growth by primarily upregulating PD-1. By stimulating the p53-MDM2 axis, interferon-α (IFN-α) reduces PD-1 levels in T cells, which, in turn, exhibit a synergistic effect on tumor suppression by sensitizing anti-PD-1 immunotherapy. Our study reveals that MDM2 directs PD-1 degradation via a deglycosylation-ubiquitination coupled mechanism and sheds light on a promising strategy to boost cancer immunotherapy by targeting the T cell-specific MDM2-PD-1 regulatory axis

Expert consensus on the diagnosis and treatment of RET gene fusion non‐small cell lung cancer in China

Abstract The rearranged during transfection (RET) gene is one of the receptor tyrosine kinases and cell‐surface molecules responsible for transmitting signals that regulate cell growth and differentiation. In non‐small cell lung cancer (NSCLC), RET fusion is a rare driver gene alteration associated with a poor prognosis. Fortunately, two selective RET inhibitors (sRETi), namely pralsetinib and selpercatinib, have been approved for treating RET fusion NSCLC due to their remarkable efficacy and safety profiles. These inhibitors have shown the ability to overcome resistance to multikinase inhibitors (MKIs). Furthermore, ongoing clinical trials are investigating several second‐generation sRETis that are specifically designed to target solvent front mutations, which pose a challenge for first‐generation sRETis. The effective screening of patients is the first crucial step in the clinical application of RET‐targeted therapy. Currently, four methods are widely used for detecting gene rearrangements: next‐generation sequencing (NGS), reverse transcription‐polymerase chain reaction (RT‐PCR), fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC). Each of these methods has its advantages and limitations. To streamline the clinical workflow and improve diagnostic and treatment strategies for RET fusion NSCLC, our expert group has reached a consensus. Our objective is to maximize the clinical benefit for patients and promote standardized approaches to RET fusion screening and therapy