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In order to prevent landslide and collapse in the mining area, it is essential not only to gain a full understanding of the surface deformation information about the open-pit mining area and surrounding dumps, but also to closely monitor the development of surface deformation. Small baseline set (SBAS) technology can be applied to extract the high-resolution spatial-temporal deformation information from the mining areas. Due to decoherence, however, it is difficult to obtain the effective information on deformation from some areas where the results are monitored. This paper proposes a kriging interpolation method that performs better in filling the missing values in the InSAR monitored results by integrating GPS measured data with InSAR monitored data. In the experimental process, 69 Sentinel-1 image data were collected from July 2018 to November 2020. The SBAS-InSAR technology was applied to monitor the surface deformation caused to the Kunyang phosphate mining area and surrounding dumping sites. It was found out that all the mining areas across the Kunyang Phosphorus Mine and the surrounding dumps suffered severe surface deformation, with the maximum line of sight (LOS) deformation rate of −132 mm/yr located in the dump in the north of the second mining area. The verification result shows that InSAR measurement results are consistent with the deformation estimated from GPS measurements. The root mean square error of most points is maintained within ±10 mm. The Kriging interpolation results of fusion GPS data are in good agreement with the GPS results. The root mean square errors at the 4 verification points are ±6.2 mm, ±4.6 mm, ±6.4 mm, ±7.8 mm. The method proposed in this paper is effective in filling in the missing values in the incoherent area, and can be applied to mine surface deformation monitoring with high reliability. The results of this paper serve as a scientific basis for the prevention and control of landslides, collapses and other hidden risks of geological disasters posed by the mining operations conducted in the Kunyang Phosphorus Mine. [ABSTRACT FROM AUTHOR]

Interferometric Synthetic Aperture Radar (InSAR) technology is capable of detecting large areas of potentially unstable slopes. However, traditional time-series InSAR methods yield fewer valid measurement points (MPs) in alpine canyon regions. Distributed Scatterer (DS) Interferometry (DSI) technology serves as a potent tool for monitoring surface deformation in complex land cover areas; nonetheless, it grapples with high computational demands and low efficiency when interpreting deformation across extended time series. This study proposes an image compression–based DSI (ICDSI) method, which, building upon the DSI method, utilizes principal component analysis (PCA) to compress multi-temporal SAR images in the time dimension. It develops a module for compressing long-time sequence SAR images, acquires the compressed image (referred to as a virtual image), and integrates the developed image compression module into the DSI data processing flow to facilitate the inversion of long-time sequence InSAR land surface deformation information. To validate and assess the credibility of the ICDSI method, we processed a total of 78 ascending and 81 descending scenes of Sentinel-1A images spanning the period 2019–2021 using Small Baseline Subset (SBAS), DSI, and the ICDSI method proposed in this paper. Subsequently, these methods were applied to detect landscape displacements on both coasts of the Jinsha River Basin. The investigation reveals that the ICDSI method outperforms SBAS and DSI significantly in monitoring landslide displacements, enabling the detection of more measurement points (MPs) while utilizing less raw data. The accomplishments of this research program carry crucial theoretical implications and practical application value for the detection of surface deformation using long-time series InSAR. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we first analyze the 5 most cited papers with the title containing “Urban ecosystem health” in Chinese academic journals, and 5 newer papers retrieved from the CSSCI (Chinese Social Sciences Citation Index). The results show that the number of indicators to be used together in more than three papers is 28, and then we select 27 of them to assess Beijing and Shanghai's urban ecosystem health from 2000 to 2011. Secondly, when we standardize the original data, the worst value adjustment coefficient is introduced innovatively. Thirdly, using the entropy method, the weights of concrete indicators of Beijing and Shanghai in the different adjustment coefficients are calculated respectively. Fourthly, based on the fuzzy matter-element method, using the Hamming approach degree, the two cities' ecosystem health index and the contribution value to overall health index from each component are calculated. Lastly, using gray prediction model, the evolutionary time response sequence function of Beijing and Shanghai's urban ecosystem health index is identified, and thus both cities' urban ecosystem health is predicted. [Copyright &y& Elsevier]

Tropospheric delay error must be reduced during interferometric synthetic aperture radar (InSAR) measurement. Depending on different geographical environments, an appropriate correction method should be selected to improve the accuracy of InSAR deformation monitoring. In this study, surface deformation monitoring was conducted in a high mountain gorge region in Yunnan Province, China, using Sentinel-1A images of ascending and descending tracks. The tropospheric delay in the InSAR interferogram was corrected using the Linear, Generic Atmospheric Correction Online Service for InSAR (GACOS) and ERA-5 meteorological reanalysis data (ERA5) methods. The correction effect was evaluated by combining phase standard deviation, semi-variance function, elevation correlation, and global navigation satellite system (GNSS) deformation monitoring results. The mean value of the phase standard deviation (Aver) of the linear correction interferogram and the threshold value (sill) of the semi-variogram were reduced by –20.98% and –41%, respectively, while the accuracy of the InSAR deformation points near the GNSS site was increased by 58%. The results showed that the three methods reduced the tropospheric delay error of InSAR deformation monitoring by different degrees in low-latitude mountains and valleys. Linear correction was the best at alleviating the tropospheric delay, followed by GACOS, while ERA5 had poor correction stability. [ABSTRACT FROM AUTHOR]

The widespread use of Light Detection and Ranging (LiDAR) technology has led to a surge in three-dimensional point cloud data; although, it also poses challenges in terms of data storage and indexing. Efficient storage and management of LiDAR data are prerequisites for data processing and analysis for various LiDAR-based scientific applications. Traditional relational database management systems and centralized file storage struggle to meet the storage, scaling, and specific query requirements of massive point cloud data. However, NoSQL databases, known for their scalability, speed, and cost-effectiveness, provide a viable solution. In this study, a 3D point cloud indexing strategy for mobile LiDAR point cloud data that integrates Hilbert curves, R*-trees, and B+-trees was proposed to support MongoDB-based point cloud storage and querying from the following aspects: (1) partitioning the point cloud using an adaptive space partitioning strategy to improve the I/O efficiency and ensure data locality; (2) encoding partitions using Hilbert curves to construct global indices; (3) constructing local indexes (R*-trees) for each point cloud partition so that MongoDB can natively support indexing of point cloud data; and (4) a MongoDB-oriented storage structure design based on a hierarchical indexing structure. We evaluated the efficacy of chunked point cloud data storage with MongoDB for spatial querying and found that the proposed storage strategy provides higher data encoding, index construction and retrieval speeds, and more scalable storage structures to support efficient point cloud spatial query processing compared to many mainstream point cloud indexing strategies and database systems. [ABSTRACT FROM AUTHOR]

Objective. A case-control study was conducted to determine the effectiveness of laparoscopic surgery and traditional open surgery on stone clearance, laboratory indexes, and life quality in patients with renal calculi. Methods. During March 2017 to March 2022, 272 patients with complex renal calculi (CRC) cured in our hospital were assigned into control group (n = 136) and research group (n = 136) arbitrarily. The former accepted traditional open surgery, while the latter accepted laparoscopic surgery. The operation time, intraoperative blood loss, hospital stay, and time of getting out of bed were compared. The degree of postoperative incision pain was assessed by visual analogue scale (VAS). The life quality was assessed by the Comprehensive Assessment Questionnaire-74 (GQOL-74). The indexes of renal function and urine metabolism were measured. Then, the postoperative stone clearance rate and complications were calculated. Results. Operation time, blood loss intraoperatively, time out of bed, and hospitalization were all remarkably reduced in the research group, and the difference was statistically significant (P < 0.05). The complete stone clearance rates in study and control cohorts were 75.73% and 63.24%, respectively. The VAS scores were lessened after the operation. Compared with the two groups, the VAS scores of the research group were remarkably lower at 1 to 2 weeks and 1 and 3 months after the operation, and the difference was statistically significant (P < 0.05). One week after operation, the levels of β 2-microglobulin (β 2-MG), N-acetyl-β-glucosaminidase (NAG), and renal injury molecule-1 (kidney injury molecule-1, Kim-1) in the research group were remarkably lower. The levels of urinary β 2-MG, NAG, and KIM-1 in the research group were remarkably lower, and the difference was statistically significant (P < 0.05). One week after operation, the levels of urinary oxalic acid, uric acid, and urinary calcium lessened averagely. The levels of urinary oxalic acid, uric acid, and urinary calcium in the research group were lower, and the difference was statistically significant (P < 0.05). The quality-of-life scores were compared. One week after the operation, the scores of physical function, psychological function, social function, and material function were all augmented, and the difference was statistically significant (P < 0.05). The incidence of complications was 9.56% and 2.21%, respectively. The incidence of complications in the research group was lower, and the difference was statistically significant (P < 0.05). Conclusion. Laparoscopic surgery is successful when treating CRC, which is superior to invasive surgery in postoperative complications, stone clearance rate, improvement of postoperative renal function, and life quality. It is one of the ideal treatment methods for CRC. However, the role of open surgery when treating CRC cannot be ignored. This needs to be further confirmed by large samples of randomized controlled trials. [ABSTRACT FROM AUTHOR]

Objective. A case-control study was conducted to compare the efficacy and prognostic factors of flexible ureteroscopic lithotripsy (FURL) and percutaneous nephrolithotomy (PCNL) when treating complex upper urinary tract renal calculi based on a retrospective cohort study. Methods. The study period was from October 2019 to December 2021. A retrospective study was carried out on 100 patients with complicated upper urinary tract nephrolithiasis who underwent surgery in the Urology Department of our hospital. They were assigned into two groups: FURL and PCNL groups. The intraoperative blood loss, operation time, hematuria duration, hospital stay, primary stone removal rate, incidence of intraoperative and postoperative complications, VAS score, level of inflammatory factors, and micturition function were compared. According to the postoperative prognosis, the patients were reassigned into two groups: good prognosis group (n = 38) and poor prognosis group (n = 106). The factors related to poor prognosis after FURL and PCNL were screened, and multivariate loglistic regression analysis was adopted to determine the risk factors. Results. The primary stone clearance rate in the PCNL group was significantly higher than that in the FURL group, and there was no significant difference in the incidence of intraoperative and postoperative complications between the two groups (P > 0.05). The intraoperative blood loss and the duration of hematuria in the PCNL group were significantly shorter than those in the FURL group, and the operation time and postoperative hospital stay in the FURL group were longer than those in the FURL group. The postoperative VAS score in the study group was significantly lower than that in the control group (P < 0.05). The levels of CRP, IL-1, TNF-α, and NF-κB in both groups decreased after operation, and the level of inflammatory factors in the PCNL group was significantly lower than that in the FURL group (P < 0.05). The indexes of IPSS and Q max in the PCNL group were significantly lower than those in the control group 3 months after operation. The index of micturition function in the PCNL group was significantly lower than that in the FURL group. Preoperative use of immunosuppressant, preoperative stone fever, positive preoperative urine culture, preoperative urinary leukocyte count ≥ 544 × L , intraoperative urinary opacity, and pus fur were significantly correlated with poor prognosis of ureteral patients (P < 0.05). Preoperative stone fever, high preoperative urinary leukocyte count, intraoperative urinary turbidity, and suppurative fur were independent risk factors for postoperative SIRS in patients with ureteral calculi. Conclusion. PCNL is effective when treating complex upper urinary tract renal calculi. Compared with FURL, PCNL can remarkably reduce intraoperative blood loss and hematuria duration, can enhance micturition function, and will not remarkably increase the incidence of intraoperative and postoperative complications, high safety. High white blood cell count in urine before operation, fever due to stone before operation, turbid urine, and purulent fur during operation are independent risk factors for postoperative adverse outcome in patients with complex upper urinary tract renal calculi. Patients should be fully treated before surgery. [ABSTRACT FROM AUTHOR]

The presence of abundant spatio-temporal information based on the location of mobile objects in publicly accessible GPS mobile devices makes it crucial to collect, analyze, and mine such information. Therefore, it is necessary to index a large volume of trajectory data to facilitate efficient trajectory retrieval and access. It is difficult for existing indexing methods that primarily rely on data-driven indexing structures (such as R-Tree) or space-driven indexing structures (such as Quadtree) to support efficient analysis and computation of data based on spatio-temporal range queries as a service basis, especially when applied to massive trajectory data. In this study, we propose a massive GPS data storage and indexing method based on uneven spatial segmentation and trajectory optimization segmentation. Primarily, the method divides GPS trajectories in a large spatio-temporal data space into multiple MBR sequences by greedy algorithm. Then, a hybrid indexing model for segmented trajectories is constructed to form a global spatio-temporal segmentation scheme, called HHBITS index, to achieve hierarchical organization of trajectory data. Eventually, a spatio-temporal range query processing method is proposed based on this index. This paper implements and evaluates the index in MongoDB and compares it with two other spatio-temporal composite indexes for performing spatio-temporal range queries efficiently. The experimental results show that the method in this paper has high performance in responding to spatio-temporal queries on large-scale trajectory data. [ABSTRACT FROM AUTHOR]

SAR imagery plays a crucial role in geological and environmental monitoring, particularly in highland mountainous regions. However, inherent geometric distortions in SAR images often undermine the precision of remote sensing analyses. Accurately identifying and classifying these distortions is key to analyzing their origins and enhancing the quality and accuracy of monitoring efforts. While the layover and shadow map (LSM) approach is commonly utilized to identify distortions, it falls short in classifying subtle ones. This study introduces a novel LSM ground-range slope (LG) method, tailored for the refined identification of minor distortions to augment the LSM approach. We implemented the LG method on Sentinel-1 SAR imagery from the tri-junction area where the Xiaojiang, Pudu, and Jinsha rivers converge at the Yunnan-Sichuan border. By comparing effective monitoring-point densities, we evaluated and validated traditional methods—LSM, R-Index, and P-NG—against the LG method. The LG method demonstrates superior performance in discriminating subtle distortions within complex terrains through its secondary classification process, which allows for precise and comprehensive recognition of geometric distortions. Furthermore, our research examines the impact of varying slope parameters during the classification process on the accuracy of distortion identification. This study addresses significant gaps in recognizing geometric distortions and lays a foundation for more precise SAR imagery analysis in complex geographic settings. [ABSTRACT FROM AUTHOR]

Based on the fractional variational theory and Hamilton principle, this paper extends a semi-analytic solution and further develops a fractional-order dynamical model of pipe flow. This model facilitates the dynamical coupling of hydraulic and mechanical systems, and ensures easily have the solution for both the physical characteristics by state space equation or the damped vibration characteristics by fractional Bagley–Torvik equation. Subsequent application in an actual hydropower system reveals the potential periodic vibration of pipe flow and the effect of fractional order memory on the dashpot time constant. The comparison of these findings with the smaller alignment index (SALI) detection results reaffirms the soundness of this study. • A semi-analytical solution is extended based on the fractional variational theory. • The fractional dynamical model of pipe flow in hydraulic system is developed. • Physical analysis of dynamic system is analyzed by the fractional dynamical model. • Potential periodic vibration and fractional order memory effect are revealed. [ABSTRACT FROM AUTHOR]

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) is a new remote sensing technology that uses GNSS signals reflected from the Earth's surface to estimate geophysical parameters. Because of its unique advantages such as high temporal and spatial resolutions, low observation cost, wide coverage and all-weather operation, it has been widely used in land and ocean remote sensing fields. Ocean wind monitoring is the main objective of the recently launched Cyclone GNSS (CYGNSS). In previous studies, wind speed was usually retrieved using features extracted from delay-Doppler maps (DDMs) and empirical geophysical model functions (GMFs). However, it is a challenge to employ the GMF method if using multiple sea state parameters as model input. Therefore, in this article, we propose an improved deep learning network framework to retrieve global sea surface wind speed using spaceborne GNSS-R data, named GloWS-Net. GloWS-Net considers the fusion of auxiliary information including ocean swell significant wave height (SWH), sea surface rainfall and wave direction to build an end-to-end wind speed retrieval model. In order to verify the improvement of the proposed model, ERA5 and Cross-Calibrated Multi-Platform (CCMP) wind data were used as reference for extensive testing to evaluate the wind speed retrieval performance of the GloWS-Net model and previous models (i.e., GMF, fully connected network (FCN) and convolutional neural network (CNN)). The results show that, when using ERA5 winds as ground truth, the root mean square error (RMSE) of the proposed GloWS-Net model is 23.98% better than that of the MVE method. Although the GloWS-Net model and the FCN model have similar RMSE (1.92 m/s), the mean absolute percentage error (MAPE) of the former is improved by 16.56%; when using CCMP winds as ground truth, the RMSE of the proposed GloWS-Net model is 2.16 m/s, which is 20.27% better than the MVE method. Compared with the FCN model, the MAPE is improved by 17.75%. Meanwhile, the GloWS-Net outperforms the FCN, traditional CNN, modified CNN (MCNN) and CyGNSSnet models in global wind speed retrieval especially at high wind speeds. [ABSTRACT FROM AUTHOR]

Time-series interferometric synthetic aperture radar (TS-InSAR) is often affected by tropospheric artifacts caused by temporal and spatial variability in the atmospheric refractive index. Conventional temporal and spatial filtering cannot effectively distinguish topography-related stratified delays, leading to biased estimates of the deformation phases. Here, we propose a TS-InSAR atmospheric delay correction method based on ERA-5; the robustness and accuracy of ERA-5 data under the influence of different atmospheric delays were explored. Notably, (1) wet delay was the main factor affecting tropospheric delay within the interferogram; the higher spatial and temporal resolution of ERA-5 can capture the wet delay signal better than MERRA-2. (2) The proposed method can mitigate the atmospheric delay component in the interferogram; the average standard deviation (STD) reduction for the Radarsat-2 and Sentinel-1A interferograms were 19.68 and 14.75%, respectively. (3) Compared to the empirical linear model, the correlation between the stratified delays estimated by the two methods reached 0.73. We applied this method for the first time to a ground subsidence study in the Yuxi Basin and successfully detected three subsidence centers. We analyzed and discussed ground deformation causes based on rainfall and fault zones. Finally, we verified the accuracy of the proposed method by using leveling monitoring data. [ABSTRACT FROM AUTHOR]

Shadow indexes can effectively and easily detect shadows in remote sensing images. Although various shadow indexes are used, there is no consensus regarding the optimal one. The evaluation criteria used to determine the performance of shadow indexes are relatively homogeneous. A multi-criteria evaluation of widely used shadow indexes is necessary to analyse the application performance of each index in different scenarios. The eight most common shadow indexes were selected for this study. In addition to the standard visual inspection and accuracy assessment criteria, the cosine of solar incidence (cosi) was introduced to evaluate the sensitivity of the indexes to illumination intensity. Furthermore, in order to evaluate the separability of shadows and confusable objects, the interquartile range (IQR) of shadows and confusable objects was used to calculate the 1.5IQR separation ratio (1.5IQRSR). The multi-scale evaluation included mountain and urban scenarios, with the sensitivity to illumination intensity used to assess mountain scenarios and the capacity to separate confusable objects used to assess urban scenarios. The results obtained for each evaluation criterion were aggregated to form the multi-criteria evaluation score of the shadow indexes. The results show that the combinational shadow index (CSI), shadow detector index (SDI), and shadow index (SI) perform relatively well for each evaluation criterion. SI and CSI had the highest shadow detection accuracy in mountain and urban areas, respectively. The shadow enhancement index (SEI) and CSI had relatively high sensitivity to illumination intensity, especially CSI. In addition, CSI has the highest water separability but low separability for blue and dark impervious surfaces. SDI and SI have high separability for confusable objects, but they are ineffective in separating water bodies and less sensitive to illumination intensity. In summary, CSI, SDI, and SI excel in many application contexts, whereas the performances of the remaining five indexes were similar in all respects. [ABSTRACT FROM AUTHOR]

At present, in the field of video-based human action recognition, deep neural networks are mainly divided into two branches: the 2D convolutional neural network (CNN) and 3D CNN. However, 2D CNN's temporal and spatial feature extraction processes are independent of each other, which means that it is easy to ignore the internal connection, affecting the performance of recognition. Although 3D CNN can extract the temporal and spatial features of the video sequence at the same time, the parameters of the 3D model increase exponentially, resulting in the model being difficult to train and transfer. To solve this problem, this article is based on 3D CNN combined with a residual structure and attention mechanism to improve the existing 3D CNN model, and we propose two types of human action recognition models (the Residual 3D Network (R3D) and Attention Residual 3D Network (AR3D)). Firstly, in this article, we propose a shallow feature extraction module and improve the ordinary 3D residual structure, which reduces the parameters and strengthens the extraction of temporal features. Secondly, we explore the application of the attention mechanism in human action recognition and design a 3D spatio-temporal attention mechanism module to strengthen the extraction of global features of human action. Finally, in order to make full use of the residual structure and attention mechanism, an Attention Residual 3D Network (AR3D) is proposed, and its two fusion strategies and corresponding model structure (AR3D_V1, AR3D_V2) are introduced in detail. Experiments show that the fused structure shows different degrees of performance improvement compared to a single structure. [ABSTRACT FROM AUTHOR]

A 35-day experiment was carried out to investigate the effect of light intensity on growth of Brachymystax lenok under different light intensities: 10, 70, 240 and 1000 lx. Fish(5.5 ± 0.24 g)used in the experiment were fed to satiation twice a day (08:00 hours, 14:00 hours).The photoperiod was 12L:12D (08:00-20:00 hours). The specific growth rate( SGR) of B. lenok under lower intensities(10 lx,70 lx)was significantly higher than the other groups( P < 0.05).No significant difference in feed intake was observed at different light intensities, but feed efficiency ( FE) in wet weight at lower intensities (1070 lx) was higher than that at higher intensities(240,1000 lx) ( P < 0.05).The final survival rate of juveniles varied from 86.33% to 93.66%,and there was no significant difference between experimental groups. The tested fish under higher light intensities (240 and 1000 lx) spent much more energy in respiration and excretion while depositing less energy for growth than those fish under lower light intensities. It is concluded that light intensity significantly affected growth and optimal light intensity for B. lenok juveniles was about 10-70 lx. [ABSTRACT FROM AUTHOR]