Slope Of Distribution Research Articles

The application value of shear wave dispersion and shear wave elastography combined with serological indicators in the evaluation of liver fibrosis

Objective: To explore the application value of shear wave dispersion (SWD) and shear wave elastography (SWE) combined with serological indicators in the evaluation of liver fibrosis. Methods: A total of 219 patients with liver disorders who underwent liver biopsy were prospectively collected in Huashan Hospital, Fudan University from January 2021 to September 2022, including 130 males and 89 females, aged from 18 to 76 (42±12) years. All patients underwent SWD and SWE examinations before liver biopsy. Serological indicators including alanine aminotransferase(ALT), aspartate aminotransferase(AST), alkaline phosphatase(ALP)) and γ-glutamyl transpeptadase (GGT) were also collected. Based on pathological diagnosis of liver fibrosis stage (from S0 to S4), the distribution of dispersion slope and liver elastic modulus at different fibrosis stages were analyzed in all patients. All patients were divided 7: 3 into training set (156 cases) and validation set (63 cases) in chronological order. In training set, factors influencing liver fibrosis≥S2 stage and S4 stage were analysed using binary logistic regression. The predictive models were established for diagnosing liver fibrosis≥S2 stage and S4 stage by using R language, and the models were evaluated by the area under curve (AUC) and calibrated for validation. Results: The dispersion slope and elastic modulus increased with the severity of fibrosis, with statistically significant differences in different fibrosis stages (both P<0.001). In training set, dispersion slope, elastic modulus, ALT, AST, and GGT were influential factors in liver fibrosis≥S2 stage and S4 stage(both P<0.05), and prediction models were constructed based on these indicators. In training set, the AUCs of the predictive model, SWD and SWE for diagnosingliver fibrosis≥S2 stage were 0.743 (95%CI: 0.665-0.821), 0.709 (95%CI: 0.628-0.790) and 0.725 (95%CI: 0.647-0.804), respectively; for diagnosing liver fibrosis S4 stage, the AUCs were 0.988 (95%CI: 0.968-1.000), 0.908 (95%CI: 0.852-0.963) and 0.974 (95%CI: 0.945-1.000), respectively. In validation set, the AUC of the predictive model, SWD and SWE for diagnosing liver fibrosis≥S2 stage were 08.735 (95%CI: 0.612-0.859), 0.658 (95%CI:0.522-0.793) and 0.699 (95%CI:0.570-0.828), respectively; for diagnosing liver fibrosis S4 stage, the AUC were 0.976 (95%CI: 0.937-1.000), 0.872 (95%CI: 0.757-0.988) and 0.948 (95%CI: 0.889-1.000), respectively. The calibration curves of the prediction models were consistent in the training and validation sets. Conclusion: The predictive model of SWD and SWE combined with serological indicators is helpful in the diagnosis of stage of liver fibrosis non-invasively.

Effects of rainfall pattern and soil surface roughness on surface–subsurface hydrological response and particle size distribution of red soil slope

Water erosion is strongly affected by rainfall pattern and soil surface roughness (SSR), the available information is inadequate to understand the influences of both on erosion processes and mechanisms. Four simulated rainfall patterns as constant (CR), increasing (IR), decreasing (DR), and rising-falling (RFR) with the same total rainfall amount (180 mm) and duration (180 min) were designed and applied to two soil surface conditions (smooth and rough) with the slope gradient of 15°. The response and generation of surface flow were positively correlated with the initial rainfall intensity of different rainfall patterns. The surface flow generation ranked as: DR > CR > RFR > IR, and the subsurface flow was the opposite. The CR pattern produced the lowest sediment yield, which was around 46.7% of the average soil loss for the varying-intensity rainfall patterns. SSR significantly promoted surface flow generation and sediment production under varying-intensity rainfall patterns, the surface flow coefficient and soil loss rate of the rough surface were 0.6%–13.1% and 3.20–11.27 g m−2 min−1 higher than that of the smooth surface. SSR inhibited the transport of sand particles and promoted the enrichment of clay particles. Under constant and variable rainfall patterns, the average content of clay particles of the rough surface was 2.8% and 0.9% more than that of the smooth surface, respectively. SSR could decrease fine particles and increase coarse particles in the eroded sediment, but only functioned under the rainfall patterns with lower initial rainfall intensity. Through comprehensively considering the effects of rainfall pattern and SSR, the stream power was the best hydraulic parameter for predicting the soil loss rate. The results are beneficial to the investigation of soil erosion in agricultural sloping farmland caused by natural rainfall events.

Recognition method for underwater imitation whistle communication signals by slope distribution

Underwater bionic covert communication has been extensively studied. However, there are little researches on bionic communication signals recognition. We propose a recognition method for bionic binary orthogonal keying modulated signals (BBOKMSs) coded by time frequency (TF) contour. The BBOKMSs realize the covert communication by mimicking the real dolphin whistles with a series of segmented chirp rate modulated signals. We first put forward a TF contours extraction method by the dynamic adaptive threshold calculated by the cross sampling. Next, the slope of TF curve is modeled based on Gaussian kernel probability density estimation (PDE) for the slope distribution. Based on the characteristics of BBOKMSs, the characteristic parameters of PDE curve are calculated and used to recognize the BBOKMSs by support vector machine (SVM). Finally, the numerical simulations are carried out to measure the effectiveness of the recognition method proposed under different SNRs, coding parameters, and channels in this paper. It is shown that when the modulation slope is higher than 20 kHz/s and the code length is longer than 20 ms, the recognition accuracy can reach more than 90% at a SNR of −5 dB in the constructed underwater aquatic channel.

InSAR-based method for monitoring the long-time evolutions and spatial-temporal distributions of unstable slopes with the impact of water-level fluctuation: A case study in the Xiluodu reservoir

Slope instability in reservoir areas is one of the greatest concerns for public and governments worldwide. The long-time evolution of the unstable slopes in reservoir areas after the impoundments remain poorly understood. Among the technologies applied to detecting and monitoring unstable slopes, interferometry synthetic aperture radar (InSAR) technology is one of the most effective. However, owing to the slopes in a reservoir suffering from periodic water-level fluctuations, InSAR technology has shortcomings for monitoring unstable slopes with large displacement for a long time. In this study, a post-processing method of InSAR and a practical strategy were proposed to monitor the long-time evolution of the unstable slopes in reservoir areas both spatially and temporally. The strategy can capture the evolution trends of the unstable slopes based on the variations in their deformation areas with reservoir water-level fluctuations for a long time. The case study was carried out in the Xiluodu reservoir area of China. The monitoring data of the unstable slopes before and after reservoir impoundment were extracted from multi-source SAR data, including those from ALOS-1, ENVISAT ASAR, and Sentinel-1. It was found that there were 40 unstable slopes before the reservoir impoundment and 152 unstable slopes after the reservoir impoundment. Of the 152 slopes, 142 slopes (94%) began deforming in the first 3 years after reservoir impoundment, 15 slopes have been experiencing continuous deformation, and 137 slopes underwent intermittent deformation. The areas of 79 slopes (52%) increased during the water-level drawdown periods and decreased during the rising periods. The areas of 22 slopes (14%) demonstrated the opposite trend, and the areas of 51 slopes (34%) increased independently of the water-level fluctuations. In terms of evolution trends in the deformation area, 30% of slopes experienced a decreasing trend, 15% were under a constant deformation trend, and 55% showed an increasing trend. The distribution of the unstable slopes varied from the dam site to the end of the reservoir, and most of them favorited the areas where slope angle and height were 20–35° and 30–300 m, respectively. The soil slopes composed of the previous landslide deposits were prone to deformation, followed by the dip to overdip layered rock slopes.

#5770 PROPOSING A NEW RENAL OUTCOME WHEN REACHING ESTIMATED GFR OF 30—SIMULATION STUDY USING REAL-WORLD STRATIFIED DATA

Abstract Background and Aims Patients with renal diseases often have progressive decline in eGFR, with many clinical researches having outcomes of reaching renal death/renal replacement therapy. In the real life, however, patients with eGFR under 15 mL/min/1.73m2 (the same unit hereafter) lose their lives more often by cardiovascular diseases before reaching endstage renal disease. Moreover, patients with eGFR below 30 are known to have miscellaneous metabolic derangements including phosphate retention, parathyroid hormone excess, metabolic acidosis, hyperkalaemia and renal anaemia. It appears to be extremely important to recognize that, in order to avoid enfacing plethora of metabolic alterations and cardiovascular disorders that progress after renal function falls below 30, we physicians need to take a step to find ways how to keep patients' eGFR above 30 for as long time as possible. At the same time, renal clinics are fully booked already; we need to prioritize the patients who have the highest risks in reaching eGFR below 30. This simulation study was performed to draw a trajectory to clarify who are the most eligible patients for nephrologists to intervene. Method Before performing the simulations using an inverse transform sampling, a priori statistical distributions were retrieved from the real-world data, i.e., a whole-hospital-wide survey over 4 years; (a) distribution of eGFR: obtained from patients with at least 3 measurements of eGFR over 366 days or more, where a median of eGFR values was used to represent the patient's renal function, (b) distribution of eGFR slopes: similarly retrieved, which were then stratified in 6 strata with each eGFR range of [30,35)/[35,40)/[40,45)/[45,50)/[50,55)/[55,60). The simulation was performed in 4 steps. In the first step (“random number generating step”), 65,000 pairs of random numbers (U1, U2) were generated using a continuous uniform distribution, U[0,1]. In the second step (“eGFR generating step”), eGFR was generated using the clinically-retrieved distribution (a, above) from a random number U1. In the third step (“slope generating step”), a slope in eGFR decline was generated using the a priori stratified distribution (b, above) from a random number U2. In the final step (“estimation step”), renal prognosis, especially an eGFR value 10 years later, was estimated in each of the “65,000 simulated patients”, with or without an effect of nephrology consults. The primary outcome was defined as reaching the eGFR below 30 within 10 years. If this occurred, time until the eGFR 30 was also calculated. Results In the strata of simulated patients with eGFR’s [50,55) and [55,60), 35.3% and 34.9% reached their eGFR below 30, over the periods of 4.78 and 4.95 years in average. In these strata, there were marked differences in renal prognosis based on the eGFR slope, where all the patients with the fastest quartile (annual rate of decline faster than 3.09) reached the outcome, while only 4–11% of the patients with slower decline (the remaining 3/4) reached eGFR &amp;lt;30. The number of patients was the largest in the stratum of [55, 60). In the stratum of eGFR [45,50), 45.3% patients, including 100% of faster quartile and 24.5% of slower 3 quartiles, reached eGFR of &amp;lt;30. Assuming the effect of nephrology consultation as attenuating the slope by 1/3, nephrologist intervention most prominently influenced the prognosis of the patients in strata [40,45) and [45,50) in terms of proportion of patients reaching outcomes (decreases by 10.5% and 12.5%). Conclusion 1) Reaching an eGFR of &amp;lt;30 mL/min/1.73m2 is a newly proposed outcome in clinical research with substantial significance such as avoiding cardiovascular events and metabolic derangements that occur frequently at eGFR below 30. 2) Patients in the fastest quartile in eGFR slope, even those whose baseline eGFR 50–60, are the candidates who merit nephrology consultation.

Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall

Landslides and flooding are two of the most common hazards associated with heavy rainfall. Most studies, however, tackle the occurrence of these hazards separately or independently. Therefore, this study introduces a catchment-scale, multihazard approach that unifies the assessment of both phenomena through a combination of hydrological and geotechnical principles. By incorporating surface flow, infiltration, and slope stability analyses, the spatio-temporal response of both landslides and flooding during intense or heavy rainfall is characterized. To improve computational efficiency, a hybrid approach, consisting of the zero- and local-inertia flow models, is introduced to approximate the surface flow. Additionally, rainfall infiltration is estimated using the one-dimensional Green-Ampt model, and the results are incorporated in a deterministic slope stability analysis whose failure mechanism is generated from the forces arising from the effects of surface flow and the downward propagation of water along the assumed failure surface. The model is applied in the catchment of Marumori Town, Japan which suffered numerous landslide and flooding disasters during Typhoon Hagibis in 2019. The results indicate that the proposed model successfully simulates the hydrologic and geotechnical response of the catchment showing the distribution of both unstable slopes and inundated areas indicative of landslide and flooding hazards. The model’s capability to identify the timing and location of potential landslide and flood-prone areas could provide a practical framework for a unified early warning system, enhancing emergency planning and response efforts during heavy rainfall.

Multiple visual objects are represented differently in the human brain and convolutional neural networks

Objects in the real world usually appear with other objects. To form object representations independent of whether or not other objects are encoded concurrently, in the primate brain, responses to an object pair are well approximated by the average responses to each constituent object shown alone. This is found at the single unit level in the slope of response amplitudes of macaque IT neurons to paired and single objects, and at the population level in fMRI voxel response patterns in human ventral object processing regions (e.g., LO). Here, we compare how the human brain and convolutional neural networks (CNNs) represent paired objects. In human LO, we show that averaging exists in both single fMRI voxels and voxel population responses. However, in the higher layers of five CNNs pretrained for object classification varying in architecture, depth and recurrent processing, slope distribution across units and, consequently, averaging at the population level both deviated significantly from the brain data. Object representations thus interact with each other in CNNs when objects are shown together and differ from when objects are shown individually. Such distortions could significantly limit CNNs’ ability to generalize object representations formed in different contexts.

Coupling covariance matrix adaptation with continuum modeling for determination of kinetic parameters associated with electrochemical CO2 reduction

Coupling covariance matrix adaptation with continuum modeling for determination of kinetic parameters associated with electrochemical CO2 reduction

Development Pattern of Toppling Deformation Slopes in Western China

Controlled by regional geological background, and affected by human activity and weathering, toppling deformation slopes occur in different regions in China. Based on statistics about domestic toppling deformation slopes and their distribution, the regional geological susceptibility zonation area of toppling deformation slopes was determined. Firstly, a regional geological susceptibility evaluation was conducted according to these toppling deformation slopes, choosing landform, stratigraphic age, seismic intensity and tectonic stress distribution, and the study area was divided into very low, low, medium, high and very high susceptibility areas. Secondly, a geographic position susceptibility evaluation was conducted aimed at different sections of typical rivers in western China and the toppling deformation slopes related to them, and the study area was divided into upstream, midstream and downstream of 11 rivers that were respectively classified into very low, low, high and very high susceptibility areas. Thirdly, based on the results, associations between the toppling deformation factors (lithology, slope height, elevation, horizontal depth and vertical depth) and the distribution of deformation slopes were revealed. Finally, the development regularity was analyzed comprehensively. The results show that the toppling deformation slopes of hydropower projects are more developed in Sichuan, Qinghai and Yunnan provinces of China. With regard to regional geography, besides the Yellow River, both the Lancang River and the Yalong River flow through areas with toppling deformation that are classified as highly susceptible geological zones in all levels. The results of this study can be used as references for site selection plans in hydropower projects.

One-shot reflectance direction field imaging for measuring the surface slope distribution of a capillary wave.

A method for measuring a surface slope distribution of a capillary wave is proposed. The method uses an optical imaging system that can capture a one-shot image of a light-reflectance direction field in a two-dimensional image plane. A dispersion relation between the wavelength and frequency of the capillary wave is shown to be obtainable by the imaging system, which agrees well with the theoretical prediction.

Revealing the relation between spatial patterns of rainfall return levels and landslide density

Abstract. It is known that the spatial rainfall pattern can mark landslide distribution across the landscape during extreme triggering events. However, the current knowledge of rainfall controls on this distribution remains limited. Here, to reveal what rainfall characteristics control landslide spatial distribution, we explore the spatiotemporal pattern of a rainfall event that triggered over 7500 landslides (area ≈ 100–104 m2) at a regional scale with an area of ≈400 km2 in Japan. Using a 5 km resolution radar-driven and gauge-adjusted hourly precipitation dataset with 32 years of records, we compared rainfall return levels for various time ranges from 1 to 72 h and landslide density in each grid cell of the precipitation dataset (≈25 km2). The results show that, even if local slope distributions within the grid cells are comparable, the number of landslides in a ≈25 km2 grid cell was substantially high when rainfall return levels exceeded the 100-year return period in all examined timespans (i.e., 1–72 h). In contrast, when only specific-duration rainfall intensities (e.g., 6–48 h) exceeded the 100-year return level, the landslide density in corresponding grid cells tended to be low. Consequently, the landslide density increased with the increase in rainfall return levels of various timespans rather than a specific rainfall intensity, such as downpours for a few hours or long-term cumulative rainfall for several days. Moreover, with the increase in the landslide density, the number of relatively large landslides exceeding ≈400 m2 increased. Therefore, the spatial differences in rainfall return levels potentially constrain the density of total landsliding and relatively large landslides. In this sense, whether rainfall intensities reach high return levels rarely experienced in a wide timespan ranging from a few hours to several days is one of the key determinants of the spatial distribution of landslides and the extent of related hazards.

The MAGPI Survey: impact of environment on the total internal mass distribution of galaxies in the last 5 Gyr

ABSTRACT We investigate the impact of environment on the internal mass distribution of galaxies using the Middle Ages Galaxy Properties with Integral field spectroscopy (MAGPI) survey. We use 2D resolved stellar kinematics to construct Jeans dynamical models for galaxies at mean redshift z ∼ 0.3, corresponding to a lookback time of 3–4 Gyr. The internal mass distribution for each galaxy is parametrized by the combined mass density slope γ (baryons + dark matter), which is the logarithmic change of density with radius. We use a MAGPI sample of 28 galaxies from low-to-mid density environments and compare to density slopes derived from galaxies in the high density Frontier Fields clusters in the redshift range 0.29 &amp;lt; z &amp;lt; 0.55, corresponding to a lookback time of ∼5 Gyr. We find a median density slope of γ = −2.22 ± 0.05 for the MAGPI sample, which is significantly steeper than the Frontier Fields median slope (γ = −2.00 ± 0.04), implying the cluster galaxies are less centrally concentrated in their mass distribution than MAGPI galaxies. We also compare to the distribution of density slopes from galaxies in ATLAS3D at z ∼ 0, because the sample probes a similar environmental range as MAGPI. The ATLAS3D median total slope is γ = −2.25 ± 0.02, consistent with the MAGPI median. Our results indicate environment plays a role in the internal mass distribution of galaxies, with no evolution of the slope in the last 3–4 Gyr. These results are in agreement with the predictions of cosmological simulations.

Spatial Dependence of Log-Transformed Electromyography-Force Relation: Model-Based Sensitivity Analysis and Experimental Study of Biceps Brachii.

This study investigated electromyography (EMG)-force relations using both simulated and experimental approaches. A motor neuron pool model was first implemented to simulate EMG-force signals, focusing on three different conditions that test the effects of small or large motor units located more or less superficially in the muscle. It was found that the patterns of the EMG-force relations varied significantly across the simulated conditions, quantified by the slope (b) of the log-transformed EMG-force relation. b was significantly higher for large motor units, which were preferentially located superficially rather than for random depth or deep depth conditions (p < 0.001). The log-transformed EMG-force relations in the biceps brachii muscles of nine healthy subjects were examined using a high-density surface EMG. The slope (b) distribution of the relation across the electrode array showed a spatial dependence; b in the proximal region was significantly larger than the distal region, whereas b was not different between the lateral and medial regions. The findings of this study provide evidence that the log-transformed EMG-force relations are sensitive to different motor unit spatial distributions. The slope (b) of this relation may prove to be a useful adjunct measure in the investigation of muscle or motor unit changes associated with disease, injury, or aging.

Study of Human Activity Intensity from 2015 to 2020 Based on Remote Sensing in Anhui Province, China

The interactions between human activities and land cover have a significant impact on ecosystems. Therefore, studying human activity intensity based on land use or land cover is crucial for understanding the sustainable development of ecosystems. In this study, we selected Anhui Province as the study area and estimated the human activity intensity of land surface (HAILS) in 2015 and 2020 based on the ChinaCover datasets. We further analyzed the spatial, slope, and hydrological distribution characteristics of HAILS and explored the drivers of HAILS changes. The results show that the areas with higher HAILS were mainly located in the central part of Hefei, as well as along the Yangtze and the Huaihe rivers. The largest changes from 2015 to 2020 happened in the gentle slopes with the HAILS of 20–30%, and the percentage of HAILS &gt; 20% decreased over the slope of 15°. In the riparian zone, the HAILS showed a clear decreasing trend after 2 km, while the HAILS in 2020 were higher than in 2015 in each flow-path distance belt, except for the Huaihe river. The HAILS index was strongly correlated with population density, rural population density, urban population density, average land GDP of primary industry, and nighttime light data. The rapid growth of the urban population and economy, as well as ecological protection policies, were identified as drivers of the above changes. Therefore, the HAILS in 2015 and 2020 of Anhui Province provide effective data support to address regional ecological conservation issues.

A global evaluation of daily to seasonal aerosol and water vapor relationships using a combination of AERONET and NAAPS reanalysis data

Abstract. The co-transport of aerosol particles and water vapor has long been noted in the literature, with a myriad of implications such as air mass characterization, radiative transfer, and data assimilation. Here, the relationship between aerosol optical depth (AOD) and precipitable water vapor (PW) is evaluated to our knowledge for the first time globally, at daily to seasonal levels using approximately 20 years of NASA Aerosol Robotic Network (AERONET) observational data and the 16-year Navy Aerosol Analysis Prediction System (NAAPS) reanalysis v1.0 (NAAPS-RA) model fields. The combination of AERONET observations with small uncertainties and the reanalysis fields with global coverage is used to provide a best estimate of the seasonal AOD and PW relationships, including an evaluation of correlations, slope, and PW probability distributions for identification of statistically significant differences in PW for high-AOD events. The relationships produced from the AERONET and NAAPS-RA datasets were compared against each other and showed consistency, indicating that the NAAPS-RA provides a realistic representation of the AOD and PW relationship. The analysis includes layer AOD and PW relationships for proxies of the planetary boundary layer and the lower, middle, and upper free troposphere. The dominant AOD and PW relationship is positive, supported by both AERONET and model evaluation, which varies in strength by season and location. These relationships were found to be statistically significant and present across the globe, observed on an event-by-event level. Evaluations at individual AERONET sites implicate synoptic-scale transport as a contributing factor in these relationships at daily levels. Negative AOD and PW relationships were identified and predominantly associated with regional dry-season timescales in which biomass burning is the predominant aerosol type. This is not an indication of dry-air association with smoke for an individual event but is a reflection of the overall dry conditions leading to more biomass burning and higher associated AOD values. Stronger correlations between AOD and PW are found when evaluating the data by vertical layers, including the boundary layer and the lower, middle, and upper free troposphere (corresponding to typical water vapor channels), with the largest correlations observed in the free troposphere – indicative of aerosol and water vapor transport events. By evaluating the variability between PW and relative humidity in the NAAPS-RA, hygroscopic growth was found to be a dominant term to (1) amplify positive AOD–PW relationships, particularly in the midlatitudes; (2) diminish negative relationships in dominant biomass burning regions; and (3) lead to statistically insignificant changes in PW for high-AOD events for maritime regions. The importance of hygroscopic growth in these relationships indicates that PW is a useful tracer for AOD or light extinction but not necessarily as strongly for aerosol mass. Synoptic-scale African dust events are an exception where PW is a strong tracer for aerosol transport shown by strong relationships even with hygroscopic effects. Given these results, PW can be exploited in coupled aerosol and meteorology data assimilation for AOD, and the collocation of aerosol and water vapor should be carefully taken into account when conducting particulate matter (PM) retrievals from space and in evaluating radiative impacts of aerosol, with the season and location in mind.

Improving the standard protocol for above-water reflectance measurements: 1. Estimating effective wind speed from angular variation of sunglint.

The standard above-water protocol for measurement of water reflectance uses a measurement of wind speed to estimate the air-water interface reflectance factor and, thus, remove reflected skylight from upwelling radiance. This aerodynamic wind speed measurement may be a poor proxy for the local wave slope distribution in cases such as fetch-limited coastal and inland waters and/or where there are spatial or temporal differences between the wind speed measurement and the location of reflectance measurements. Here, an improved method is proposed, with a focus on sensors mounted on autonomous pan-tilt units and deployed on fixed platforms, replacing the aerodynamic wind speed measurement by optical measurements of angular variation of upwelling radiance. Using radiative transfer simulations, it is shown that the difference between two upwelling (i.e.,water plus air-water interface) reflectances acquired at least 10° apart from each other in the solar principal plane is strongly and monotonically related to effective wind speed. The approach shows good performance in twin experiments using radiative transfer simulations. Limitations of the approach are identified, including difficulties for a very high Sun zenith angle (>60∘), very low wind speed (<2m s -1), and, potentially, cases in which nadir-pointing angles are limited by optical perturbations from the viewing platform.

Karst landslides detection and monitoring with multiple SAR data and multi-dimensional SBAS technique in Shuicheng, Guizhou, China

Shuicheng District is a karst mountain area, located in Guizhou Province, China. Its fragile stratum and frequent underground mining activities makes it prone to landslides. Owning to its wide coverage and frequent revisit, the InSAR technology has advantages in potential landslide identification and deformation monitor. However, affected by dense vegetation and atmospheric delay, it is much difficult to get sufficient effective targets to derive the deformation in this area. Besides, deformation derived from single orbit SAR data can result in the missing identification of some potential landslides and the misinterpreting of the real kinematics process of landslides. In this study, the multi-source SAR data, atmospheric error correction by quadratic tree image segmentation method, and phase-stacking method were selected to derive the surface deformation of this area. Besides, DS-InSAR and MSBAS method were combined to derive the deformation of Pingdi landslide. First, the potential landslides in this area were identified, surface deformation result, optical remote sensing images and geomorphological features were jointly considered. Then, the landslide distribution characteristics was analyzed in terms of slope, elevation and stratum. After that, the deformation along the LOS direction was acquired using the DS-InSAR method. The MSBAS method was used to retrieve the two-dimensional deformation of Pingdi landslide. Finally, the comprehensive analysis of triggering factors and failure process were conducted according to the spatial-temporal deformation characteristics and field investigation. The results indicated that landslides in Shuicheng district were mostly located in the junction of T1 and P3 stratum and mining related. Mining activity was the main cause of the Pingdi landslide deformation, the precipitation was the driving factor of the landslide instability. The research provides an insight into the explore the unstable slope distribution characteristic and the failure process of the landslides.

Quantum Chaos and Level Dynamics

We review the application of level dynamics to spectra of quantally chaotic systems. We show that the statistical mechanics approach gives us predictions about level statistics intermediate between integrable and chaotic dynamics. Then we discuss in detail different statistical measures involving level dynamics, such as level avoided-crossing distributions, level slope distributions, or level curvature distributions. We show both the aspects of universality in these distributions and their limitations. We concentrate in some detail on measures imported from the quantum information approach such as the fidelity susceptibility, and more generally, geometric tensor matrix elements. The possible open problems are suggested.

Landslide susceptibility mapping using automatically constructed CNN architectures with pre-slide topographic DEM of deep-seated catastrophic landslides caused by Typhoon Talas

There has been an increasing demand for detailed and accurate landslide maps and inventories in disaster-prone areas of subtropical and temperate zones, particularly in Asia as they can mitigate the impacts of landslides on social infrastructure and economic losses. Hence, in this study, models using automatically constructed high-performing convolutional neural network (CNN) architectures for landslide detection were applied and their outcomes were compared for landslide susceptibility mapping at the Kii peninsula, Japan. First, a total of 38 landslide and 63 non-landslide points were identified and divided into 70% and 30% of training and validation datasets, respectively. Eight landslide influence factors were used: slope angle, eigenvalue ratio, curvature, underground openness, overground openness, topographic witness index, wavelet, and elevation. These factors were selected using a 1-m DEM, which is easy to acquire and process data. Experimental results of model evaluation using receiver operating characteristics (ROC), area under the curve (AUC), and accuracy showed that the optimal models (ROC = 96.0%, accuracy = 88.7%) were more accurate than initial models (ROC = 91.1%, accuracy = 80.7%) in predicting landslides spatially. Furthermore, the landslide susceptibility mapping is consistent with the trends in the distribution of gentle slopes and knick lines unique to the study area and can be used as a powerful method for predicting landslides in future.

Plan‐Form Evolution of Drainage Basins in Response to Tectonic Changes: Insights From Experimental and Numerical Landscapes

AbstractSpatial gradients in rock uplift control the relief and slope distribution in uplifted terrains. Relief and slopes, in turn, promote channelization and fluvial incision. Consequently, the geometry of drainage basins is linked to the spatial pattern of uplift. When the uplift pattern changes, basin geometry is expected to change by migrating water divides. However, the relations between drainage pattern and changing uplift patterns remain elusive. The current study investigates the plan‐view evolution of drainage basins and the reorganization of drainage networks in response to changes in the spatial pattern of uplift, focusing on basin interactions that produce globally observed geometrical scaling relations. We combine landscape evolution experiments and simulations to explore a double‐stage scenario: the emergence of a fluvial network under block uplift conditions followed by tilting that forces drainage reorganization. We find that the globally observed basin spacing ratio and Hack's parameters emerge early in the basin formation and are maintained by differential basin growth. In response to the tilting, main divide migration induces basin size changes. However, basins' scaling relations are mostly preserved within a narrow range of values, assisted by incorporation and disconnection of basins to and from the migrating main divide. Lastly, owing to similarities in landscape dynamics and response rate to uplift pattern changes between experiments and simulations, we conclude that the stream power incision model can represent fluvial erosion processes operating in experimental settings.