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Various applications have been achieved by Gaofen-3 images, while the time series interferometric synthetic aperture radar (TS-InSAR) analysis was rare due to the issues with baseline instability. In this study, we revealed that the primary artefacts degrading the quality of Gaofen-3 interferograms are the long spatial baselines and inaccuracy of orbit information induced by the lack of consideration of satellite orbital tube manoeuvres. To address these challenges, we have proposed an enhanced interferometry processing method aimed at isolating the main artefacts from wrapped interferograms and enhancing the interferometry capabilities of Gaofen-3 images. It mainly includes tips on estimating precise baselines based on orbital information and fringe frequency in the wrapped interferogram and refining the residual phase further by a quadratic polynomial regression model. Subsequently, the TS-InSAR analysis is successfully implemented to acquire high-accuracy land subsidence in Beijing during 2020–2021 based on these refined interferograms. This case study demonstrates the achievement of the land subsidence analysis through TS-InSAR with Gaofen-3 images, highlighting that our proposed method could enhance the quality of Gaofen-3 interferograms. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar interferometry (InSAR) has emerged as an effective technique for monitoring potentially unstable landslides and has found widespread application. Nevertheless, in mountainous reservoir regions, the precision of time-series InSAR outcomes is often constrained by topography-dependent atmospheric delay (TDAD) effects. To address this limitation, we propose a novel InSAR time-series method that integrates TDAD correction. This approach employs advanced deep learning algorithms to individually model and mitigate TDAD for each interferogram, thereby enhancing the accuracy of small baseline subset InSAR (SBAS-InSAR) and stacking InSAR time-series analyses. Utilizing Sentinel-1 data, we apply this method to identify potential landslides in the Baihetan reservoir area, located in southwestern China, where we successfully identified 26 potential landslide sites. Comparative experimental results demonstrate a significant reduction (averaging 70% and reaching up to 90%) in phase standard deviation (StdDev) in the corrected interferograms, indicating a marked decrease in phase–topography correlation. Furthermore, the corrected time-series InSAR results effectively remove TDAD signals, leading to clearer displacement boundaries and a remarkable reduction in other spurious displacement signals. Overall, this method efficiently addresses TDAD in time-series InSAR, enabling precise identification of potentially unstable landslides influenced by TDAD, and providing essential technical support for early landslide hazard detection using time-series InSAR. [ABSTRACT FROM AUTHOR]

Landslides frequently occur in the mountainous area of southwest China, resulting in infrastructure damage, as well as a loss of life and property. The use of interferometric synthetic aperture radar (InSAR) technology has become increasingly popular due to its wide coverage, high precision, and efficiency in identifying potential landslides in steep mountainous regions to mitigate risks. This study focused on the Mao County region in China and utilized a small baseline subset of InSAR (SBAS−InSAR) technology with Sentinel-1 and ALOS-2 data to identify the potential landslides and analyze their applicability. To ensure accuracy, the findings were verified using optical image and field surveys. Additionally, a comparative analysis was performed on C-band and L-band SAR data to examine differences in the coherence, geometric distortion, and displacement results, revealing that the L-band has clear advantages in the coherence, suitable observation coverage, and displacement results, while C-band can detect relatively slight displacements. This study aimed to determine the applicability of different SAR satellites for early landslide identification in steep mountainous areas, which can serve as a technical reference for selecting appropriate SAR data and enhancing InSAR identification abilities for potential landslides in the future. [ABSTRACT FROM AUTHOR]

Aiming at the problem of distributed state estimation in sensor networks, a novel optimal distributed finite-time fusion filtering method based on dynamic communication weights has been developed. To tackle the fusion errors caused by incomplete node information in distributed sensor networks, the concept of limited iterations of global information aggregation was introduced, namely, fast finite-time convergence techniques. Firstly, a local filtering algorithm architecture was constructed to achieve fusion error convergence within a limited number of iterations. The maximum number of iterations was derived to be the diameter of the communication topology graph in the sensor network. Based on this, the matrix weight fusion was used to combine the local filtering results, thereby achieving optimal estimation in terms of minimum variance. Next, by introducing the generalized information quality (GIQ) calculation method and associating it with the local fusion result bias, the relative communication weights were obtained and embedded in the fusion algorithm. Finally, the effectiveness and feasibility of the proposed algorithm were validated through numerical simulations and experimental tests. [ABSTRACT FROM AUTHOR]

This paper considers the problem of multiple missiles to attack a maneuvering target simultaneously. Based on a fixed-time fast nonsingular terminal sliding mode surface (FNTSMS), fixed-time distributed cooperative guidance laws are developed. By designing guidance laws along and perpendicular to line of sight (LOS) direction, both relative velocity and range-to-go are consistent. In addition, a saturation function is introduced to avoid the chattering problem caused by the commonly used sign function. Furthermore, a distributed cooperative guidance law with communication failure is considered and proved theoretically, which shows that the proposed guidance law has excellent performance. Finally, the simulation results not only explain the performance of the distributed guidance law,but also verify the robustness against communication topology switching. [ABSTRACT FROM AUTHOR]

Landslides are a major concern in the mountainous regions of southwest China, leading to significant loss of life and property damage. Therefore, it is crucial to identify potential landslides for early warning and mitigation. stacking-InSAR, a technique used for landslide identification in a wide area, has been found to be faster than conventional time-series InSAR. However, the dense vegetation in southwest China mountains has an adverse impact on the coherence of stacking-InSAR, resulting in more noise and inaccuracies in landslide identification. To address this problem, this paper proposes an improved seasonal interferometry stacking-InSAR method. It uses Sentinel-1 satellite data from 2017 to 2022. The study area is the river valley section of the G213 road from Wenchuan County to Mao County. The study reveals the characteristics of seasonal decoherence in the steep mountainous region, and identifies a total of 21 potential landslides using the improved method. Additionally, optical satellite imagery and LiDAR data were used to assist in the identification of potential landslides. The results of the conventional stacking-InSAR method and the improved seasonal interferometry stacking-InSAR method are compared, showing that the latter is more effective in noise suppression caused by low coherence. Their standard deviations were reduced by 46%, 22%, 10%, and 14%, respectively, using the quantitative statistics for the four tested areas. The proposed method provides an efficient and effective approach for detecting potential landslides in the mountainous regions of southwest China. It can serve as a valuable technical reference for future landslide identification studies in this area. [ABSTRACT FROM AUTHOR]

On June 17, 2020, Aniangzhai landslide, an ancient landslide located in Danba County, southwest China, was reactivated by Meilonggou debris flow. The front edge of the slope collapsed, mobilizing a soil mass of about 2.35 × 106 m3. Evaluating the stability of the whole slope is of great importance to avoid further landslides and mitigate the damage for Aniangzhai villagers living on this slope. This paper focuses on the inaccessible upper slope of Aniangzhai landslide (no attention paid before) that exhibits a relative elevation difference of more than 1000 m. Multi-source remote sensing, including unmanned aerial vehicle (UAV) photogrammetry, light detection and ranging (LiDAR), and satellite-based interferometric synthetic aperture radar (InSAR) techniques, was used in this research to identify and evaluate this high mountain upper slope potential hazard in Aniangzhai landslide. Considering the huge height difference and the steep slope of Aniangzhai landslide, an iterative route planning method was proposed and adopted to obtain a 3D model with 0.02 m resolution and a DEM with 0.25 m resolution by using UAV and LiDAR close-in flight method, respectively. Meter-level huge cracks were clearly identified by the high-resolution UAV 3D model and LiDAR data, which confirm that the location of these cracks is related to the morphological structure of this ancient landslide. Time series InSAR analysis reveals the activity of this high-altitude area, with a maximum LOS displacement rate of 15 cm/a. The combination of the above remote sensing technologies confirms and reveals the high potential risk and the reactivated condition of the upper slope of Aniangzhai landslide. Through this finding, we show that the evolution of Aniangzhai landslide happened through four stages with a cascading effect. This paper proves the usefulness of an integrated method to successfully identify and evaluate the high-altitude upper slope potential hazard and compares the technical features of them, providing a reference for future works that aimed at mitigating the potential damage of the upper slope. [ABSTRACT FROM AUTHOR]

Owing to their unique advantages, single‐electrode triboelectric nanogenerators (SETENGs) have gained wide attention and have been applied in myriad areas, especially in the burgeoning flexible/wearable electronics. However, there is still a lack of a clear understanding of SETENGs. For example, previous simulation models generally put the reference electrode perpendicularly below the working part, but in practice, the reference electrode is designed in various scenarios and noticeable differences in outputs often occur when the reference electrode changes. With SETENGs developing towards wearability and portability, its reference electrode is often required to be constructed inside the device. Consequently, to achieve optimum performance, it is essential to understand the reference electrode's influence on the outputs. Here, the influence of the reference electrode on the performance of SETENGs is systematically investigated and the targeted optimization strategies are thoroughly revealed. First, theoretical simulations are conducted to investigate the reference electrode's effect on the performance of SETENGs with different structures and in various working modes. Secondly, the theoretical results are certified through corresponding experiments. Based on the results, the targeted optimization strategies for SETENGs are comprehensively demonstrated. This work provides fundamental guidance for the development of TENGs and the design and fabrication of new electronic devices. [ABSTRACT FROM AUTHOR]

A triboelectric nanogenerator (TENG) facilitates the advancement of self‐powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude‐based displacement sensing of conventional TENG‐based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct‐current TENG sensors, this study proposes an environmentally robust character‐based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude‐based TENG sensors, providing a novel route to realize reliable self‐powered displacement sensing in environment‐variable applications. [ABSTRACT FROM AUTHOR]

In this paper, an optimal-damage-effectiveness cooperative-control strategy based on a damage-efficiency model and a virtual-force method is proposed to solve the pursuit–evasion problem with multiple guided missiles. Firstly, different from the overly ideal assumption in the traditional pursuit–evasion problem, an optimization problem that maximizes the damage efficiency is established and solved, making the optimal-damage-effectiveness strategy more meaningful for practical applications. Secondly, a modified virtual-force method is proposed to obtain this optimal-damage-effectiveness control strategy, which solves the numerical solution challenges brought by the high-complexity damage function. Thirdly, adaptive gain is designed in this strategy based on guidance-integrated fuze technology to achieve robust maximum damage efficiency in unpredictable interception conditions. Finally, the effectiveness and robustness of the proposed strategy are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

The integrated device for energy supply and sensing (IDESS) is a potential candidate for relieving the energy and space burdens caused by the rising integration degrees of microsystems. In this article, we propose a force sensor based on an interdigital supercapacitor (IDTSC). The capacitance and internal resistance of the IDTSC change under external loads, resulting in a transient current fluctuation at a constant bias voltage, which can be used to sense external force/acceleration. The IDTSC showed a specific energy and specific power of 4.16 Wh/kg and 22.26 W/kg (at 0.1 A/g), respectively, which could maintain an essential energy supply. According to the simulation analysis, the designed IDTSC's current response exhibited good linearity with the external force. In addition, benefiting from its light weight and the applied gel electrolytes, the IDTSC showed good high-g impact sensing performance (from 9.9 × 103× g to 3.2 × 104× g). This work demonstrated the feasibility of realizing an integrated energy supply and force-sensing device by empowering energy storage devices with sensing capabilities. [ABSTRACT FROM AUTHOR]

Atmospheric effects are among the primary error sources affecting the accuracy of interferometric synthetic aperture radar (InSAR). The topography-dependent atmospheric effect is particularly noteworthy in reservoir areas for landslide monitoring utilizing InSAR, which must be effectively corrected to complete the InSAR high-accuracy measurement. This paper proposed a topography-dependent atmospheric correction method based on the Multi-Layer Perceptron (MLP) neural network model combined with topography and spatial data information. We used this proposed approach for the atmospheric correction of the interferometric pairs of Sentinel-1 images in the Baihetan dam. We contrasted the outcomes with those obtained using the generic atmospheric correction online service for InSAR (GACOS) correction and the traditional linear model correction. The results indicated that the MLP neural network model correction reduced the phase standard deviation of the Sentinel-1 interferogram by an average of 64% and nearly eliminated the phase-elevation correlation. Both comparisons outperformed the GACOS correction and the linear model correction. Through two real-world examples, we demonstrated how slopes with displacements, which were previously obscured by a significant topography-dependent atmospheric delay, could be successfully and clearly identified in the interferograms following the correction by the MLP neural network. The topography-dependent atmosphere can be better corrected using the MLP neural network model suggested in this paper. Unlike the previous model, this proposed approach could be adjusted to fit each interferogram, regardless of how much of the topography-dependent atmosphere was present. In order to improve the effectiveness of DInSAR and time-series InSAR solutions, it can be applied immediately to the interferogram to retrieve the effective displacement information that cannot be identified before the correction. [ABSTRACT FROM AUTHOR]

In this study, we present an adaptive capacitor charging circuit for efficient piezoelectric (PE) energy harvesting (EH), which simplifies the configuration for powering wireless sensor network (WSN) nodes. In the circuit, the PE harvester directly charges the storage capacitor through the rectifier, eliminating the energy loss in the dc–dc converter of conventional EH circuits. An adaptive control circuit is designed to optimize the average charging power. Theoretical analysis shows that the optimal average power of the novel circuit varies from 81.4% to 86.5% of the maximum power of the conventional EH circuit, without considering the power dissipation in the dc–dc converter. Moreover, the power losses of both the proposed and conventional circuits are estimated. When the excitation level is low, the net harvested power of the proposed circuit can be enhanced to as high as 180% of that of the conventional circuit. The experimental results validate that the power transferred to the load is increased by adopting the proposed interface. It is also proved that the circuit is adaptive to different harvesters and excitation conditions. In addition, the area of the proposed circuit is reduced, allowing it to be easily integrated into the WSN nodes. [ABSTRACT FROM AUTHOR]

Electromagnetic rail launch technology is well-known for its short start-up time and high initial velocity, which makes it ideal for material performance testing and aerospace propulsion. However, during the electromagnetic launch, the harsh multiphysics field environment inside the bore imposes higher demands on the rail, armature, and launch load. Previous modeling studies have overlooked the coupling effects between multiphysics fields or simplified the input current model, leading to significant discrepancies between simulated and actual results. In this paper, a field-circuit coupling method is proposed to calculate the impact of coupling effects between multiphysics fields during electromagnetic launches. It takes into account the electromagnetic, mechanical, and thermal fields during launch and characterizes the coupling effects between multiphysics fields in terms of electrical parameters. Based on this method, the high-speed sliding electrical contact problem can be solved, and the distribution of multi-field environments in the armature and rail under coupling effects can be simulated. Furthermore, the distribution characteristics of these fields on the physical properties of the launch load are revealed, and the calculation deviations of acceleration and magnetic flux change rate are compared and analyzed using different methods. Therefore, this method provides a new approach to multiphysics field simulation during electromagnetic launch, which can greatly promote the practical application of electromagnetic rail launch technology and support the design and protection of its projectile-borne systems. • A coupling model is established to characterize the influence of coupling effects. • The magnetic diffusion and heat concentration caused by coupling effects is revealed. • The coupling effects can affect the overload and magnetic field at launch load. [ABSTRACT FROM AUTHOR]

The climate-induced spatio-temporal evolutionary characteristics of glaciers have a strong response in understanding the surface earth system processes, including hydrology, ecology, and topography. With use of multispectral remote sensing, this study explores the long-time glacier shrinkage evolution and their geographical features of Gongga Mountain glaciers (i.e. Gongga Mountain glacier group), in eastern Qinghai-Tibetan Plateau, China. We used a band ratio and decision-tree classification mixed method to automatically delineate Gongga Mountain glaciers shrinking nature. Based on the multispectral Landsat images over nearly 30 years, the long-time spatio-temporal shrinkage evolution of Gongga Mountain glaciers was extracted, in which the glacier shrinkage area changes are consistent with the results from previous works. This study analyzed the nature of shrinking glaciers with topographic derivatives (i.e., different glacier scale, altitude, slope gradient, and slope direction). We noticed that the characteristic of shirking glaciers is associated with the topographic variables. The maximum shrinkage was concentrated at altitudes of 5000–5500 m, and a slope angle of 30° in the south direction. Findings shed light that glaciers in our study area are correlated with temperature changes and precipitation with a correlation coefficient of −0.97 and 0.35, respectively, suggesting that the decreasing glaciers are highly correlated with the temperature increase. This study implies the usefulness of remote sensing in understanding the long-time ecological environment change and helping manage the potential glacial disasters in eastern Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

Wake‐up circuits in smart microsystems make huge contributions to energy conservation of electronic networks in unmanned areas, which still require higher pressure‐triggering sensitivity and lower power consumption. In this work, a bionic triboelectric nanogenerator (bTENG) is developed to serve as a self‐powered motion sensor in the wake‐up circuit, which captures slight mechanical disturbances and overcomes the drawback of conventional self‐powered motion sensors in the wake‐up circuit that the circuit can only be triggered when a considerable pressure is applied on the sensor. The bTENG mimics the structure of plants and the addition of the leaf‐shaped tentacle structures can increase the electrical outputs by four times, which largely extends the detection range of the wake‐up circuit. The bTENG can detect both noncontact and contact mechanical disturbances; and voltages generated from both situations can trigger the wake‐up system. Moreover, the specially designed circuit that is compatible with the bTENG can help more accurately control the wake‐up system and prolong the battery life of the electronic networks to 12.4 times. An intrusion detection system is established in the wake‐up circuit to distinguish human motion and judge the scene. This work opens new horizons for wake‐up technologies, and provides new routes for persistent sensing. [ABSTRACT FROM AUTHOR]

Timely and effective post-disaster assessment is of significance for the design of rescue plan, taking disaster mitigation measures and disaster analysis. Field investigation and remote sensing methods are the common ways to perform post-disaster assessment, which are usually limited by dense cloud coverage, potential risk, and tough transportation etc. in the mountainous area. In this paper, we employ the 2017 catastrophic Xinmo landslide (Sichuan, China) to demonstrate the feasibility of using spaceborne synthetic aperture radar (SAR) data to perform timely and effective post-disaster assessment. With C-band Sentinel-1 data, we propose to combine interferometric coherence to recognize the stable area, which helps us successfully identify landslide source area and boundaries in a space-based remote sensing way. Complementarily, X-band TanDEM-X SAR data allow us to generate a precise pre-failure high-resolution digital elevation model (DEM), which provides us the ability to accurately estimate the depletion volume and accumulation volume of Xinmo landslide. The results prove that spaceborne SAR can provide a quick, valuable, and unique assistance for post-disaster assessment of landslides from a space remote sensing way. At some conditions (bad weather, clouds, etc.), it can provide reliable alternative. [ABSTRACT FROM AUTHOR]

The Daguangbao mega-landslide (China), induced by the 2008 Wenchuan earthquake (M w = 7.9), with an area of approximately 8 km 2 , is one of the largest landslides in the world. Experts predicted that the potential risk and instability of the landslide might remain for many decades, or even longer. Monitoring the activity of such a large landslide is hence critical. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1 satellite provides us with up-to-date high-quality Synthetic Aperture Radar (SAR) images over a wide ground coverage (250 × 250 km), enabling full exploitation of various InSAR applications. However, the TOPS mode introduces azimuth-dependent Doppler variations to radar signals, which requires an additional processing step especially for SAR interferometry. Sentinel-1 TOPS data have been widely applied to earthquakes, but the performance of TOPS data-based time series analysis requires further exploitation. In this study, Sentinel-1 TOPS data were employed to investigate landslide post-seismic activities for the first time. To deal with the azimuth-dependent Doppler variations, a processing chain of TOPS time series interferometry approach was developed. Since the Daguangbao landslide is as a result of the collapse of a whole mountain caused by the 2008 Mw 7.9 Wenchuan earthquake, the existing Digital Elevation Models (DEMs, e.g. SRTM and ASTER) exhibit height differences of up to approximately 500 m. Tandem-X images acquired after the earthquake were used to generate a high resolution post-seismic DEM. The high gradient topographic errors of the SRTM DEM (i.e. the differences between the pre-seismic SRTM and the actual post-seismic elevation), together with low coherence in mountainous areas make it difficult to derive a precise DEM using the traditional InSAR processing procedure. A re-flattening iterative method was hence developed to generate a precise TanDEM-X DEM in this study. The volume of the coseismic Daguangbao landslide was estimated to be of 1.189 ± 0.110 × 10 9 m 3 by comparing the postseismic Tandem-X DEM with the preseismic SRTM DEM, which is consistent with the engineering geological survey result. The time-series results from Sentinel-1 show that some sectors of the Daguangbao landslide are still active (and displaying four sliding zones) and exhibiting a maximum displacement rate of 8 cm/year, even eight years after the Wenchuan earthquake. The good performance of TOPS in this time series analysis indicates that up-to-date high-quality TOPS data with spatiotemporal baselines offer significant potential in terms of future InSAR applications. [ABSTRACT FROM AUTHOR]

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images. [ABSTRACT FROM AUTHOR]

This paper mainly addresses the simultaneous attack of multiple missiles against a maneuvering target in three-dimensional (3-D) space. Here, we show that a novel fixed-time fast nonsingular terminal slide mode surface (FNTSMS), which has the characteristics of nonsingularity, converges in fixed time. With the help of the fixed-time FNTSMS, fixed-time adaptive distributed guidance laws along and perpendicular to the line of sight (LOS) direction are proposed. This realizes the dynamic adjustment of the target parameters in guidance laws, reduces the energy consumption of the guidance process, and realizes the constraints of the impact time and angle simultaneously. Additionally, considering that the communication topology will cause topology switching failure, this paper proves through graph theory that the proposed adaptive guidance laws will not be affected by topology switching. Moreover, through relevant auxiliary transformations, guidance laws with control input delay are demonstrated. To close to the actual action process of the missile, the air resistance item is added to guidance laws and analyzed. In addition, the control input amplitude is restricted to meet the actual working conditions of the missile. Finally, simulations are conducted to demonstrate the performance of the guidance law and its robustness against the mutation of communication topology. [ABSTRACT FROM AUTHOR]

Electricity is the basic and essential need for every single person and guarantees the development of society, industry, and the economy. The limited conventional fossil fuel meets the challenge of the sharply increasing demand, while may lead to severe pollution. Emerging green energy harvesting systems can convert ambient kinetic, thermal, and solar energy to electricity effectivity. In this review paper, the authors provide an overview of the new and emerging methods, droplet‐based electricity generators, that convert energy from the ubiquitously existing water droplets. The authors begin with a brief introduction of the working principle for droplet‐based power generators. Existing configurations of the droplet‐based power generator are also summarized, including 1) single electrode, 2) transistor‐based, and 3) direct current generator. Then, a detailed discussion of the design and operation factors that may impact the energy harvesting efficiency of droplet‐based power generators is provided. Hybrid energy harvester that integrates droplet‐based power generators with other triboelectric, pyroelectric, and photovoltaic‐based devices are summarized. Finally, challenges and perspectives regarding the future development of droplet‐based power generators are described. The reviews demonstrate a highly efficient method for energy harvesting from water droplets to meet the vital needs of the energy crisis. [ABSTRACT FROM AUTHOR]

Landslide disasters occur frequently in the mountainous areas in southwest China, which pose serious threats to the local residents. Interferometry Synthetic Aperture Radar (InSAR) provides us the ability to identify active slopes as potential landslides in vast mountainous areas, to help prevent and mitigate the disasters. Quickly and accurately identifying potential landslides based on massive SAR data is of great significance. Taking the national highway near Wenchuan County, China, as study area, this paper used a Stacking-InSAR method to quickly and qualitatively identify potential landslides based on a total of 40 Sentinel SAR images acquired from November 2017 to March 2019. As a result, 72 active slopes were successfully detected as potential landslides. By comparing the results from Stacking-InSAR with the results from the traditional SBAS-InSAR (Small Baselines Subset) time series method, it was found that the two methods had a high consistency, with 81.7% potential landslides identified by both of the two methods. A detailed comparison on the detection differences was performed, revealing that Stacking-InSAR, compared to SBAS-InSAR may miss a few active slopes with small spatial scales, small displacement levels and the ones affected by the atmosphere, while it has good performance on poor-coherence regions, with the advantages of low technical requirements and low computation labor. The Stacking-InSAR method would be a fast and powerful method to qualitatively and effectively identify potential landslides in vast mountainous areas, with a comprehensive understanding of its specialty and limitations. [ABSTRACT FROM AUTHOR]

Multiple dynamic impact signals are widely used in a variety of engineering scenarios and are difficult to identify accurately and quickly due to the signal adhesion phenomenon caused by nonlinear interference. To address this problem, an intelligent algorithm combining wavelet transforms with lightweight neural networks is proposed. First, the features of multiple impact signals are analyzed by establishing a transfer model for multiple impacts in multibody dynamical systems, and interference is suppressed using wavelet transformation. Second, a lightweight neural network, i.e., fast-activated minimal gated unit (FMGU), is elaborated for multiple impact signals, which can reduce computational complexity and improve real-time performance. Third, the experimental results show that the proposed method maintains excellent feature recognition results compared to gate recurrent unit (GRU) and long short-term memory (LSTM) networks under all test datasets with varying impact speeds, while its metrics for computational complexity are 50% lower than those of the GRU and LSTM. Therefore, the proposed method is of great practical value for weak hardware application platforms that require the accurate identification of multiple dynamic impact signals in real time. [ABSTRACT FROM AUTHOR]

The Ms 7.0 Jiuzhaigou earthquake that occurred on 8 August 2017 triggered hundreds of landslides in the Jiuzhaigou valley scenic and historic-interest area in Sichuan, China, causing heavy casualties and serious property losses. Quick and accurate mapping of post-disaster landslide distribution is of paramount importance for earthquake emergency rescue and the analysis of post-seismic landslides distribution characteristics. The automatic identification of landslides is mostly based on medium- and low-resolution satellite-borne optical remote-sensing imageries, and the high-accuracy interpretation of earthquake-triggered landslides still relies on time-consuming manual interpretation. This paper describes a methodology based on the use of 1 m high-resolution unmanned aerial vehicle (UAV) imagery acquired after the earthquake, and proposes a support vector machine (SVM) classification method combining the roads and villages mask from pre-seismic remote sensing imagery to accurately and automatically map the landslide inventory. Compared with the results of manual visual interpretation, the automatic recognition accuracy could reach 99.89%, and the Kappa coefficient was higher than 0.9, suggesting that the proposed method and 1 m high-resolution UAV imagery greatly improved the mapping accuracy of the landslide area. We also analyzed the spatial-distribution characteristics of earthquake-triggered landslides with the influenced factors of altitude, slope gradient, slope aspect, and the nearest faults, which provided important support for the further study of post-disaster landslide distribution characteristics, susceptibility prediction, and risk assessment. [ABSTRACT FROM AUTHOR]

Gaofen-3 is the first Chinese spaceborne C-band SAR satellite with multiple polarizations. The Gaofen-3 satellite's data has few applications for monitoring landslides at present, and its potential for use requires further investigation. Consequently, we must evaluate and analyze the landslide interference quality and displacement monitoring derived from the Gaofen-3 SAR satellite's data, particularly in high and steep, mountainous regions. Based on the nine Gaofen-3 SAR datasets gathered in 2020–2021, this study used DInSAR technology to track landslide displacement in Mao County, Sichuan Province, utilizing data from Gaofen-3. Our findings were compared to SENTINEL-1 and ALOS-2 data for the same region. This study revealed that due to its large spatial baseline, Gaofen-3's SAR data have a smaller interference effect and weaker coherence than the SENTINEL-1 and ALOS-2 SAR data. In addition, the displacement sensitivity of the Gaofen-3 and SENTINEL-1 data (C-band) is higher than that of the ALOS-2 data (L-band). Further, we conducted a study of observation applicability based on the geometric distortion distribution of the three forms of SAR data. Gaofen-3's SAR data are very simple to make layover and have fewer shadow areas in hilly regions, and it theoretically has more suitable observation areas (71.3%). For its practical application in mountainous areas, we introduced the passive geometric distortion analysis method. Due to its short incidence angle (i.e., 25.8°), which is less than the other two satellites' SAR data, only 39.6% of the Gaofen-3 SAR data in the study area is acceptable for suitable observation areas. This study evaluated and analyzed the ability of using Gaofen-3's data to monitor landslides in mountainous regions based on the interference effect and observation applicability analysis, thereby providing a significant reference for the future use and design of Gaofen-3's data for landslide monitoring. [ABSTRACT FROM AUTHOR]

Dalian Jinzhou Bay International Airport (DJBIA) is an offshore artificial island airport, where the reclaimed land is prone to uneven land subsidence due to filling consolidation and construction. Monitoring and predicting the subsidence are essential to assist the subsequent subsidence control and ensure the operational safety of DJBIA. However, the accurate monitoring and prediction of reclaimed subsidence for such a wide area under construction are hard and challenging. This paper utilized the Small Baseline Subset Synthetic Aperture Radar (SBAS-InSAR) technology based on Sentinel-1 images from 2017 to 2021 to obtain the subsidence over the land reclamation area of the DJBIA, in which the results from ascending and descending orbit data were compared to verify the reliability of the results. The SBAS-InSAR results reveal that uneven subsidence is continuously occurring, especially on the runway, terminal, and building area of the airport, with the maximum subsidence rate exceeding 100 mm/year. It was found that there is a strong correlation between the subsidence rate and backfilling time. This study provides important information on the reclaimed subsidence for DJBIA and demonstrates a novel method for reclaimed subsidence monitoring and prediction by integrating the advanced InSAR technology and Terzaghi Consolidation Theory modeling. Moreover, based on the Terzaghi consolidation theory and the corresponding geological parameters of the airport, predicted subsidence curves in this area are derived. The comparison between predicted curves and the actual subsidence revealed by InSAR in 2017–2021 is highly consistent, with a similar trend and falling in a range of ±25 mm/year, which verifies that the subsidence in this area conforms to Terzaghi Consolidation Theory. Therefore, it can be predicted that in the future, the subsidence rate of the new reclamation area in this region will reach about 80 mm/year ± 25 mm/year, and the subsidence rate will gradually slow down with the accumulation of reclamation time. The subsidence rate will slow down to about 30 mm/year ± 25 mm/year after 10 years. [ABSTRACT FROM AUTHOR]

• Investigate subsidence in Beijing with Sentinel-1 TOPS SAR data. • Demonstrates subsidence in Beijing (2015–2017) is still severe up to 14 cm/year. • Investigates detailed active geological faults information in Beijing. • Reveals subsidence is spatially controlled by geological faults to some degree. Beijing, the capital city of China, has been affected by land subsidence due to intensive groundwater extraction since 1935. Recent studies reported that the maximum subsidence occurred in the east of Beijing, reaching more than 11 cm/year till 2017. To investigate the subsidence (2015˜2017) in Beijing, in this paper, time series interferometric synthetic aperture radar (TS-InSAR) analysis was performed with 22 Sentinel-1 Terrain Observation by Progressive Scans (TOPS) mode SAR data. Results show that wide areas in the east of Beijing are subsiding with a maximum rate of 14 cm/year, which is consistent with GPS data. Detailed analysis of the obtained subsidence map reveals the existence of several characteristic near-linear boundaries within the subsiding areas. As a result of our previous three-year project, we generated the exact location, direction, and late Quaternary activity of the main potential active faults in the Beijing area. The relationship between the trace of these existing geological faults and the mentioned subsidence boundaries was investigated in detail. It is suggested that land subsidence in Beijing was mainly caused by the over-extraction of groundwater, with its spatial pattern being controlled by geological faults. [ABSTRACT FROM AUTHOR]

The Baihetan reservoir region is characterized by complex geomorphology, significant altitude differences, and rugged terrain. Geological hazards in such areas are often characterized by high concealment, wide distribution, and difficulty in field investigation. Traditional identification techniques are unable to detect and monitor geological hazards on a large scale with high efficiency and accuracy. In recent decades, interferometric synthetic aperture radar (InSAR) techniques, such as small baseline subset InSAR (SBAS-InSAR), have been widely applied to landslide identification. However, due to factors such as vegetation and the degree of landslide deformation, single-band synthetic aperture radar (SAR) still has certain limitations in detecting landslides. In this study, SBAS-InSAR was conducted based on ALOS-2 and Sentinel-1 ascending-descending images covering the Baihetan reservoir region. Deformation identification results were utilized to conduct a statistical analysis of the SAR detection performance and landslide characteristics, and the effect of vegetation on the detection effectiveness of different SAR bands was discussed. The study revealed that when surface vegetation coverage reaches a high degree, the percentage of areas with coverage greater than 0.6 is greater than 95%, the SAR coherence is mainly affected by vegetation thickness; the comparison of the difference change in the average coherence of the C/L bands among the four vegetation types shows that the ratio of the average coherence of the L-bands to the C-bands increases by a factor of three with the increase in thickness and the transition from crops to shrubs and trees. The results showed that the L-band has better detectability than the C-band in alpine-canyon terrain with vegetation coverage and complex vegetation composition. However, considering the high temporal resolution and accessibility of Sentinel-1 SAR data, it is still the main data choice for wide-area identification of landslides in the reservoir area, while other satellite-borne SAR data with different wavelengths and resolutions, such as ALOS, can be used to assist in the identification and monitoring of landslide hazards with significant magnitude of deformations and dense vegetation coverage. Therefore, the combined utilization of multi-band SAR data has the potential to enhance the dependability of landslide identification and monitoring, resulting in more accurate detection results. [ABSTRACT FROM AUTHOR]

The dynamic management of sensor nodes and advanced information fusion are necessary technologies to enhance the comprehensive performance of sensor networks. This paper presents a cascaded sensor dynamic activation and information fusion algorithm to simultaneously optimize the energy and sensing performance of wireless sensing networks. The proposed algorithm dynamically activates nodes that are most suitable for the current sensing task through a joint event-driven and state ranking activation algorithm that achieves a better sensing performance with lower energy costs. In addition, it further utilizes the sensing information of all the activated nodes with maximum efficiency, through an improved distributed Kalman information fusion, which achieves an extra improvement in sensing accuracy as measured by the minimum variance. Finally, the superiority of the proposed cascaded algorithm is verified by a simulation comparison, achieving almost zero dead nodes in terms of energy, and a 62.1% decrease in average error in terms of sensing. [ABSTRACT FROM AUTHOR]

Interferograms with short wavelength (e.g., X-band) are usually prone to temporal decorrelation in permafrost regions, leading to the unavailability of sufficient high-coherence interferograms for performing conventional time series InSAR analysis. This paper proposes the utilization of temporary scatterers for the stacking InSAR method, thus enabling extraction of subsidence in a permafrost region with limited SAR images and limited high-coherence interferograms. Such method is termed as the temporary scatterers stacking InSAR (TSS-InSAR). Taking the Gonghe-Yushu highway (about 30 km), part of G214 National Highway in Qinghai province (in a permafrost region), as a case study, this TSS-InSAR approach was demonstrated in detail and implemented. With 10 TerraSAR-X images acquired during the period from May 2015 to August 2015, the subsidence along this highway was extracted. In this case the lack of a consistent number of SAR acquisitions limits the possibility to perform other conventional time series InSAR analysis. The results show that the middle part of this highway is in the thermokarst and seasonal frozen soil area, and its accumulated subsidence reach up to 10 cm in 110 days. The thawing phenomena is still the main reason for the instability of highway. The results demonstrate that the TSS-InSAR method can effectively extract the subsidence information in a challenging scenario with limited X-band SAR images and limited high-coherence interferograms, where other time series InSAR-based techniques cannot be applied in a simple way. [ABSTRACT FROM AUTHOR]

Supercapacitors (SCs) are a type of energy storage device with high power density and long lifecycles. They have widespread applications, such as powering electric vehicles and micro scale devices. Working stability is one of the most important properties of SCs, and it is of significant importance to investigate the operational characteristics of SCs working under extreme conditions, particularly during high-g acceleration. In this paper, the failure mechanism of SCs upon high-g impact is thoroughly studied. Through an analysis of the intrinsic reaction mechanism during the high-g impact, a multi-faceted physics model is established. Additionally, a multi-field coupled kinetics simulation of the SC failure during a high-g impact is presented. Experimental tests are conducted that confirm the validity of the proposed model. The key factors of failure, such as discharge currents and discharging levels, are analyzed and discussed. Finally, a possible design is proposed to avoid the failure of SCs upon high-g impact. [ABSTRACT FROM AUTHOR]

China has a significant portion of land in landslide-prone areas, and remote sensing technologies are becoming a tool of choice to investigate and monitor landslides. Although much progress has been made with remote sensing technologies and their applications in China, there is no systematical summary report. Thus, we summarize Synthetic Aperture Radar (SAR), optical remote sensing, and laser technologies currently being used in China, and their associated platforms (space-borne, air-borne, and ground-based). Multi-temporal optical images and time series SAR are often used to detect active landslides at time scales of years and months. The latest optical images and SAR intensity images are usual adopted to map fresh landslides, especial for coseismic landslides. LiDAR technology has been widely applied to identify ancient landslides. Combining advantages and limitations of every technology, an integrated space-air-ground collaborative investigation strategy has been proposed for early identification and early warning of landslides. Additionally, a comprehensive landslide investigation integrating multidisciplinary approaches, including remote sensing, geology, and geophysical exploration, could be a further developing trend, because remote sensing technologies just provide surface information, while a complete understanding of landslides requires more than surface information – knowledge of geotechnical parameters, geological features, and field conditions is also needed. • SAR, optical remote sensing and laser technologies have been applied for landslide investigations in China. • China has proposed remote sensing strategies for different landslides. • China has carried out successful remote-sensing applications on different scales. • Multidisciplinary integration for landslide investigation should be the further trend. [ABSTRACT FROM AUTHOR]

This paper is concerned with the estimation of correlated noise and packet dropout for information fusion in distributed sensing networks. By studying the problem of the correlation of correlated noise in sensor network information fusion, a matrix weight fusion method with a feedback structure is proposed to deal with the interrelationship between multi-sensor measurement noise and estimation noise, and the method can achieve optimal estimation in the sense of linear minimum variance. Based on this, a method is proposed using a predictor with a feedback structure to compensate for the current state quantity to deal with packet dropout that occurs during multi-sensor information fusion, which can reduce the covariance of the fusion results. Simulation results show that the algorithm can solve the problem of information fusion noise correlation and packet dropout in sensor networks, and effectively reduce the fusion covariance with feedback. [ABSTRACT FROM AUTHOR]

[Display omitted] • Magnetic soft robot with three-joint-unit exhibits a high crawling speed up to 1.4 BL/s owing to its inchworm-like locomotion gait. • Bionic antennae based on triboelectric tactile sensors is capable of sensing mechanical collisions, with a sensitivity of 0.13 V KPa−1. • The magnetic arthropod soft robot with five-joints bodies integrated bionic antennae can perceive obstacles and make turns to avoid. Magnetic soft robots exhibit attractive advantages such as nontethered constraints and remote control capabilities, with broad prospects in environmental exploration, minimally invasive surgery and other fields. However, constrained by the magnetic control mode and the high flexibility of the soft materials, achieving rapid movement and perception-feedback of magnetic soft robots are still challenging. Therefore, this paper aims to draw inspiration from biomimetic joint structures to design and fabricate a magnetic arthropod soft robot capable of rapid cyclic extension-contraction deformation under an alternating magnetic field. First, a type A magnetic arthropod soft robot (MASR-A) is developed with a speed up to 1.4 body length per second (BL/s) with three-joint-unit. Next, we designed a type B magnetic arthropod soft robot (MASR-B) that offers higher flexibility and deformation adaptability with bodies owing five-joints structure. Then, inspired by snail's tentacles, we developed bionic antennae based on triboelectric tactile sensors (TTSs), which can convert external mechanical collisions into electrical signals output, with a sensitivity of up to 0.13 V KPa−1. By mounting the bionic antennae on the head of MASR-B to realize the magnetic soft robot's sensing function, enabling MASR-B to detect collisions with obstacles of various materials (PMMA, Resin, PLA and etc.). Particularly, the bionic antennae consists of two completely independent triboelectric sensing units (LTTS and RTTS). The signals from these two TTSs are received and identified by a microcontroller to determine the direction of obstacle relative to the robot. The relay is then controlled to alter the magnetic field generated by the electromagnetic coils to enable MASR-B to avoid obstacle. This paper provides a biomimetic design approach for the rapid movement and flexible sensing of magnetic soft robots. [ABSTRACT FROM AUTHOR]

Extracting facade maps from 3D point clouds is a fast and economical way to describe a building's surface structure. Existing methods lack efficiency, robustness, and accuracy, and depend on many additional features such as point cloud reflectivity and color. This paper proposes a robust and automatic method to extract building facade maps. First, an improved 3D Hough transform is proposed by adding shift vote and 3D convolution of the accumulator to improve computational efficiency and reduce peak fuzziness and dependence on the step selection. These modifications make the extraction of potential planes fast and accurate. Second, the coplane and vertical plane constraints are introduced to eliminate pseudoplanes and nonbuilding facades. Then, we propose a strategy to refine the potential facade and to achieve the accurate calibration and division of the adjacent facade boundaries by clustering the refined point clouds of the facade. This process solves the problem where adjoining surfaces are merged into the same surface in the traditional method. Finally, the extracted facade point clouds are converted into feature images. Doors, windows, and building edges are accurately extracted via deep learning and digital image processing techniques, which combine to achieve accurate extraction of building facades. The proposed method was tested on the MLS and TLS point cloud datasets, which were collected from different cities with different building styles. Experimental results confirm that the proposed method decreases computational burden, improves efficiency, and achieves the accurate differentiation of adjacent facade boundaries with higher accuracy compared with the traditional method, verifying the robustness of the method. Additionally, the proposed method uses only point cloud geometry information, effectively reducing data requirements and acquisition costs. [ABSTRACT FROM AUTHOR]

Hybrid energy storage systems composed of batteries and supercapacitors (SCs) can provide a stable and sustainable power source for wireless sensor network (WSN) nodes, where the energy management strategy (EMS) plays a significant role. However, the design of a traditional EMS is based on empirical rules and cannot fully utilize the SC. In this study, we propose the concept of a sponge SC and design a strategy based on it to prolong the lifetime of solar-powered WSN nodes. This sponge SC EMS is realized by using dynamic programming (DP), which is a global optimization algorithm. Thus, the proposed EMS is significantly improved over other traditional empirical-based strategies. The difference between the lifetime simulated by the proposed strategy and the optimal upper bound given by DP is within 40%, and the novel strategy extends the battery lifetime by 32%–77% compared with the best existing strategies investigated. The robustness of the proposed method is also validated. It can be confirmed that the strategy performs well under different workloads and sunlight conditions. The sponge SC rule-based hybrid EMS provides a theoretical near-optimal solution for the extension of the life of the WSN node, contributing to wider application prospects of the WSN node. • A novel concept of "Sponge Supercapacitor" is proposed. • A sponge SC rule-based EMS for WSN that can be used online is designed accordingly. • The DP algorithm is introduced to optimize EMS. • The WSN model simulation platform is constructed using MATLAB. • The effectiveness and robustness of the proposed EMS are verified. [ABSTRACT FROM AUTHOR]

On 22 December 2018, volcano Anak Krakatau, located in Indonesia, erupted and experienced a major lateral collapse. The triggered tsunami killed at least 437 people by the 13-m-high tide. Traditional optical imagery plays a great role in monitoring volcanic activities, but it is susceptible to cloud and fog interference and has low temporal resolution. Synthetic aperture radar (SAR) imagery can monitor volcanic activities at a high temporal resolution, and it is immune to the influence of clouds. In this paper, we propose an automatic method to accurately extract the volcano boundary from SAR images by combining multi-polarized water enhancement and the Nobuyuki Otsu (OTSU) method. We extract the area change of the volcano in 2018–2019 from Sentinel-1 images and ALOS-2 imagesThe area change and evolution are verified and analyzed by combing the results from SAR and optical data. The results show that the southeastern part of the volcano expanded significantly after the eruption, and the western part experienced collapse and recovery. The volcano morphology change experienced a slow-fast-slow process in the two years. [ABSTRACT FROM AUTHOR]

• A new two-port hybrid diode topology is proposed for solar-powered WSN. • An adaptive supercapacitor buffer energy management strategy is designed. • The system cost, size, control complexity, and energy loss are decreased. • The battery lifetime is increased by at least two times that of the existing HESSs. Solar energy harvesting is promising to provide long-term power autonomy for wireless sensor networks. Energy storage devices like lithium-ion batteries are usually integrated to solar-powered sensor nodes to overcome the intermittency of solar power. However, the cycle life of lithium-ion batteries is short, which limits the lifetime of the nodes. Therefore, supercapacitor-battery hybrid energy storage system has been used to extend the cycle life of battery. The design of hybrid energy storage systems significantly affects the performance of wireless sensor network nodes in many ways. However, hybrid energy storage system optimization is a comprehensive problem because the configuration and power-split strategy need to be considered concurrently, which has not been done in the existing studies of solar-powered sensor nodes. In this study, a two-port hybrid diode topology is proposed, accompanied by an adaptive supercapacitor buffer energy management strategy to achieve integrated optimization. The hybrid diode semi-active topology uses a unidirectional DC/DC converter accompanied by two diodes to replace the bidirectional DC/DC converter in the existing semi-active topology. Accordingly, the energy lose is decreased by 15.5% while the cost, size, and controlling complexity are also decreased. Moreover, an adaptive supercapacitor buffer energy management strategy is designed based on the new topology to decrease the battery degradation. Simulation and experimental results indicate that the proposed hybrid energy storage system increases the battery lifetime to at least 3 times that of existing hybrid energy storage systems. Finally, a long-life solar-powered wireless sensor network node with a relatively small size and cost is achievable. [ABSTRACT FROM AUTHOR]

In the field of laser circumferential detection and laser imaging, there is demand for a simple and small system. A new kind of small linear laser circumferential laser radar using a single detector is proposed. The effects of surface characteristics of two typical targets (a plane and a cylinder) on echo waves of a linear laser are investigated via modeling, theoretical analysis, and an experiment. The results show that the echo waveform is affected by the detection range, target surface condition, and target size. The rising edge, broadening, and arrival time of the echo are affected by the shape of the target. Furthermore, a simple imaging method is proposed in the last part of our study using this circumferential system based on the echo characteristic studied. [ABSTRACT FROM AUTHOR]

The direct-to-home satellite digital video broadcasting has been fast developed in the past decades, and the continuous phase modulation (CPM) is an alternative modulation scheme with the advantages of constant envelope and high spectral efficiency for the band-limited channel and non-linear amplifiers of the satellite transponder. In this paper, CPM cascaded with irregular low density parity check (LDPC) code is studied. A practical system model with global interleaving is proposed for the optimization of degree distribution of the LDPC codes, and code word design is obtained with a modified progressive edge-growth algorithm. Simulation results combined with theoretical analysis clarify the effect of signal-to-noise ratios and two important CPM parameters (modulation index ${h}$ and correlation length ${L}$ ), providing guidance for system design. Simulation on bit error rate performance show the validity of the proposed algorithm. This paper systematically solves the optimal system design of cascade irregular LDPC-CPM and is of great significance for future satellite broadcasting. [ABSTRACT FROM AUTHOR]

At 5:38 am on the 24th June, 2017, a catastrophic rock avalanche destroyed the whole village of Xinmo, in Maoxian County, Sichuan Province, China. About 4.3 million m of rock detached from the crest of the mountain, gained momentum along a steep hillslope, entrained a large amount of pre-existing deposits, and hit the village at a velocity of 250 km/h. The impact produced a seismic shaking of ML = 2.3 magnitude. The sliding mass dammed the Songping gully with an accumulation body of 13 million m. The avalanche buried 64 houses; 10 people were killed and 73 were reported missing. The event raised great concerns both in China and worldwide. Extensive field investigation, satellite remote sensing, UAV aerial photography, and seismic analysis allowed to identify the main kinematic features, the dynamic process, and the triggering mechanism of the event. With the aid of ground-based synthetic aperture radar monitoring, the hazard deriving from potential further instabilities in the source area has been assessed. The preliminary results suggest that the landslide was triggered by the failure of a rock mass, which had been already weakened by the M 7.5 Diexi earthquake in 1933. Several major earthquakes since then, and the long-term effect of gravity and rainfall, contributed to the mass failure. The high elevation, slope angle, and vegetation cover in the source area hinder geological field investigation and make hazard assessment difficult. Nonetheless, monitoring and prevention of similar collapses in mountainous areas must be carried out to protect human lives and infrastructures. To this aim, the integrated use of modern high-precision observation technologies is strongly encouraged. [ABSTRACT FROM AUTHOR]

The biological effects of low-dose or low-dose-rate ionizing radiation on normal tissues has attracted attention. Based on previous research, we observed the morphology of liver tissues of C57BL/6J mice that received <50, 50–500, and 500–1000 μGy/h of 137Cs radiation for 180 d. We found that the pathological changes in liver tissues were more obvious as the irradiation dose rates increased. Additionally, differential protein expression in liver tissues was analyzed using a proteomics approach. Compared with the matched group in the 2D gel analysis of the irradiated groups, 69 proteins had ≥ 1.5-fold changes in expression. Twenty-three proteins were selected based on ≥2.5-fold change in expression, and 22 of them were meaningful for bioinformatics and protein fingerprinting analysis. These molecules were relevant to cytoskeleton processes, cell metabolism, biological defense, mitochondrial damage, detoxification and tumorigenesis. The results from real-time PCR and western blot (WB) analyses showed that calreticulin (CRT) was up-regulated in the irradiated groups, which indicates that CRT may be relevant to stress reactions when mouse livers are exposed to low-dose irradiation and that low-dose-rate ionizing radiation may pose a cancer risk. The CRT protein can be a potential candidate for low-dose or low-dose-rate ionizing radiation early-warning biomarkers. However, the underlying mechanism requires further investigation. [ABSTRACT FROM AUTHOR]

On April 25, 2015, a destructive M W 7.8 earthquake struck the capital of Nepal, Kathmandu, killing more than 8800 people and destroying numerous historical structures. We analyze six coseismic interferograms from several satellites (ALOS-2, Sentinel-1 A, and RADARSAT-2), as well as three-dimensional displacements at six GPS stations to investigate fault structure and slip distribution of the Gorkha earthquake. Using a layered crustal structure, the best-fit slip model shows that the preferred dip angle of the mainshock fault is 6 ± 3.5° and the major slip is concentrated within depths of 8–15 km. The maximum slip of ~ 6.0 m occurs at a depth of 11 km, 70 km south east of the epicenter. The coseismic rupture extends ~ 150 km eastward of the epicentre with a cumulative geodetic moment of 7.8 × 10 20 Nm, equivalent to an earthquake of M W 7.84. We also investigate the M W 7.2 aftershock on 12 May 2015 using another three postseismic interferograms from ALOS2, RADARSAT-2, and Sentinel-1 A. The InSAR-based best-fit slip model of the largest aftershock implies that its major slip is next to the eastern lower end of the mainshock rupture with a similar maximum slip of ~ 6 m at a depth of ~ 13 km. This study generates various coseismic geodetic measurements to determine the source parameters of the M W 7.8 Gorkha earthquake and 12 May M W 7.2 afershock, providing an additional chance to understand the local fault structure and slip extent. [ABSTRACT FROM AUTHOR]

Assessment of seismic hazard relies on estimates of how large an area of a tectonic fault could potentially rupture in a single earthquake. Vital information for these forecasts includes which areas of a fault are locked and how the fault is segmented. Much research has focused on exploring downdip limits to fault rupture from chemical and thermal boundaries, and along-strike barriers from subducted structural features, yet we regularly see only partial rupture of fully locked fault patches that could have ruptured as a whole in a larger earthquake. Here we draw insight into this conundrum from the 25 April 2015 Mw 7.8 Gorkha (Nepal) earthquake. We invert geodetic data with a structural model of the Main Himalayan thrust in the region of Kathmandu, Nepal, showing that this event was generated by rupture of a décollement bounded on all sides by more steeply dipping ramps. The morphological bounds explain why the event ruptured only a small piece of a large fully locked seismic gap. We then use dynamic earthquake cycle modeling on the same fault geometry to reveal that such events are predicted by the physics. Depending on the earthquake history and the details of rupture dynamics, however, great earthquakes that rupture the entire seismogenic zone are also possible. These insights from Nepal should be applicable to understanding bounds on earthquake size on megathrusts worldwide. [ABSTRACT FROM AUTHOR]