Cumulative Slope Research Articles

JWST sighting of decametre main-belt asteroids and view on meteorite sources.

Asteroid discoveries are essential for planetary-defence efforts aiming to prevent impacts with Earth1, including the more frequent2 megaton explosions from decametre impactors3-6. Although large asteroids (≥100 kilometres) have remained in the main belt since their formation7, small asteroids are commonly transported to the near-Earth object (NEO) population8,9. However, owing to the lack of direct observational constraints, their size-frequency distribution (SFD)-which informs our understanding of the NEOs and the delivery of meteorite samples to Earth-varies substantially among models10-14. Here we report 138 detections of some ofthe smallest asteroids (≳10 metres) ever observed in the main belt, which were enabled by JWST's infrared capabilities covering the emission peaks of the asteroids15 and synthetic tracking techniques16-18. Despite small orbital arcs, we constrain the distances and phase angles of the objects using known asteroids as proxies, allowing us to derive sizes through radiometric techniques. Their SFD shows a break at about100 metres (debiased cumulative slopes of q = -2.66 ± 0.60 and-0.97 ± 0.14 for diameters smaller and larger than roughly100 metres, respectively), suggestive of a population driven by collisional cascade. These asteroids were sampled from several asteroid families-most probably Nysa, Polana and Massalia-according to the geometry of pointings considered here. Through further long-stare infrared observations, JWST is poised to serendipitously detect thousands of decametre-scale asteroids across the sky, examining individual asteroid families19 and the source regions of meteorites13,14 'in situ'.

Analysis of driving forces on ecohydrological regime and environmental flow changes in Hongze Lake, China

Environmental flow refers to the fundamental hydrological process that sustains the ecosystem of rivers and lakes. Safeguarding environmental flow is crucial for optimal water resource utilization and lake ecosystem preservation. The study delivers a comprehensive exploration of ecohydrology, focusing on the common analysis of runoff and water level (RWL) to evaluate ecohydrological conditions in Hongze Lake (HZL) over five decades (1970–2020). Techniques such as the change point test and wavelet analysis were employed to discern trends and periodicity in hydrological elements. A series of ecologically pertinent indicators was applied to measure the changes in RWL, assessing their impacts on the lake's ecosystem. The Budyko hypothesis and cumulative slope rate of change (CSRC) were integrated for a quantitative analysis that shed light on the ecological response to RWL variations. Differential effects of human activities and climate change on runoff were discerned through subsurface parameter analysis across different decades. The study's results indicate that human activities, particularly gate dam operations and agricultural irrigation, have precipitated a significant reduction in environmental flow components (EFCs). The gate dam manipulation during the dry season has notably influenced the lake's hydrological regime, with a substantial alteration of RWL by 37% and 41%, respectively. This hydrological modification aligns with observed ecological trends such as species population reduction, habitat fragmentation, and organism miniaturization within HZL. Analysis of subsurface parameters also reflected an increasing influence of climatic factors on runoff over time. Human activities, evapotranspiration, and precipitation were found to contribute 75.5%, 10.3%, and 14.2% to runoff alterations, and 70.1%, 11.4%, and 18.5% to water level (WL) changes, respectively.

Three-level evaluation method of cumulative slope deformation hybrid machine learning models and interpretability analysis

The study aims to address the issues of limited evaluation metrics and low visualization for Machine Learning (ML) models in Cumulative Slope Deformation (CSD) prediction. Firstly, to establish a representative and balanced CSD dataset, the Grey Relational Analysis (GRA) and Mutual Information (MI) were used to determine the main controlling features influencing CSD. Secondly, combining four typical ML algorithms Support Vector Regression (SVR), Extreme Learning Machine (ELM), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) with an Improved Particle Swarm Optimization (IPSO) algorithm to develop hybrid ML models. Moreover, a three-level evaluation method is proposed considering prediction accuracy and error, prediction uncertainty, and prediction robustness to determine the optimal hybrid ML model. Then, the effectiveness of the proposed method is validated using data from a diatomaceous earth slope on the site. Finally, the SHapley Additive exPlanations (SHAP) method was used to perform interpretability analysis on the optimal hybrid ML model in three steps: Moment-specific and global interpretation, Overall importance analysis and contribution analysis, and Dependency analysis. The results indicate that: 1) Based on the combined feature analysis algorithm of GRA and MI, the main controlling features affecting CSD were the three-day cumulative rainfall, daily rainfall, daily moisture content, daily deformation increment, and daily moisture content change. 2) The IPSO algorithm has a significant advantage in improving the prediction accuracy of the ML models. 3) The calculated Comprehensive Evaluation Index (CEI) values for each hybrid ML model are as follows: IPSO-GRU (1.980) < IPSO-SVR (2.380) < IPSO-LSTM (2.564) < IPSO-ELM (2.793), which indicated that the IPSO-GRU was the optimal hybrid ML model. 4) In the IPSO-GRU model, the top three features in order of overall importance are Previous CSD, three-day cumulative rainfall, and daily rainfall, and the feature most closely interacting with three-day cumulative rainfall and daily rainfall is the Previous CSD. The research findings can provide a reference method for selecting the optimal ML model and offer a precise, interpretable, and reliable predictive model for CSD.

Automated astronaut traverses with minimum metabolic workload: Accessing permanently shadowed regions near the lunar south pole

The Artemis exploration zone is a topographically complex impact-cratered terrain. Steep undulating slopes pose a challenge for walking extravehicular activities (EVAs) anticipated for the Artemis III and subsequent missions. Using 5 m/pixel Lunar Orbiter Laser Altimeter (LOLA) measurements of the surface, an automated Python pipeline was developed to calculate traverse paths that minimize metabolic workload. The tool combines a Monte Carlo method with a minimum-cost path algorithm that assesses cumulative slope over distances between a lander and stations, as well as between stations. To illustrate the functionality of the tool, optimized paths to permanently shadowed regions (PSRs) are calculated around potential landing sites 001, nearby location 001(6), and 004, all within the Artemis III ‘Connecting Ridge’ candidate landing region. We identified 521 PSRs and computed (1) traverse paths to accessible PSRs within 2 km of the landing sites, and (2) optimized descents from host crater rims into each PSR. Slopes are limited to 15° and previously identified boulders are avoided. Surface temperature, astronaut body illumination, regolith bearing capacity, and astronaut-to-lander direct view are simultaneously evaluated. Travel times are estimated using Apollo 12 and 14 walking EVA data. A total of 20 and 19 PSRs are accessible from sites 001 and 001(6), respectively, four of which maintain slopes <10°. Site 004 provides access to 11 PSRs, albeit with higher EVA workloads. From the crater rims, 94 % of PSRs can be accessed. All round-trip traverses from potential landing sites can be performed in under 2 h with a constant walk. Traverses and descents to PSRs are compiled in an atlas to support Artemis mission planning.

The interpretability of the activity signal detection model for wood-boring pests Semanotus bifasciatus in the larval stage.

The acoustic detection model of activity signals based on deep learning could detect wood-boring pests accurately and reliably. However, the black-box characteristics of the deep learning model have limited the credibility of the results and hindered its application. Aiming to address the reliability and interpretability of the model, this paper designed an active interpretable model called Dynamic Acoustic Larvae Prototype Network (DalPNet), which used the prototype to assist model decisions and achieve more flexible model explanation through dynamic feature patch computation. In the experiments, the average recognition accuracy of the DalPNet on the simple test set and anti-noise test set for Semanotus bifasciatus larval activity signals reached 99.3% and 98.5%, respectively. The quantitative evaluation of interpretability was measured by the relative area under the curve (RAUC) and the cumulative slope (CS) of the accuracy change curve in this paper. In the experiments, the RAUC and the CS of DalPNet were 0.2923 and -2.0105, respectively. Additionally, according to the visualization results, the explanation results of DalPNet were more accurate in locating the bite pulses of the larvae and could better focus on multiple bite pulses in one signal, which showed better performance compared to the baseline model. The experimental results demonstrated that the proposed DalPNet had better explanation while ensuring recognition accuracy. In view of that, it could improve the trust of forestry custodians in the activity signals detection model and aid in the practical application of the model in the forestry field. © 2023 Society of Chemical Industry.

Seismicity parameters of Nepal by cumulative slope point change method

Nepal is one of the most seismically active countries with several seismic sources that are capable of generating moderate to high magnitude earthquakes. In this study, earthquake catalogue was developed by considering six major source zones. The completeness time period was determined by performing sensitivity analysis for various magnitude bin widths and time intervals. The seismicity parameters were computed by the least square method (LSM) and maximum likelihood method (MLM). LSM was based on Gutenberg Richter’s scale relationship, whereas for the maximum likelihood method, it was performed by a new method called cumulative slope point change method (CSPCM). The CSPCM was introduced to account the drawbacks of maximum curvature method (MCM), especially for bulk number of data. Furthermore, paper compares the LSM and the MLM for the calculation of seismicity parameters. The comparison shows that the proposed CSPCM based on MLM is reliable in terms of theoretical and analytical way as compared to LSM and MCM.

Characterization of the evolution of runoff‐sediment relationship in Min River based on coupling coordination theory

AbstractGlobal climate change and human activities have profoundly affected the hydrological processes in the basin. The study of the characteristics of runoff and sediment variations in the basin and their driving factors is of great significance in promoting the efficient use of water resources and high‐quality development in the basin. The determination of the abrupt change point of the runoff‐sediment relationship is the key to delineate the base period, and is important to assess the contribution of climate change and human activities to the change of the runoff‐sediment relationship. Therefore, this study constructs a binary coupled coordination model of runoff and sediment load to describe the coupled runoff‐sediment coordination relationship, and uses the Pettitt method and the double cumulative curve method to test for mutations. The effects of climate change and human activities on changes in runoff and sediment load were assessed using the Budyko framework‐based elasticity factor method and the cumulative slope rate of change method. The results show that the annual runoff and annual sediment load in the Min River basin show a decreasing trend between 1970 and 2019, with monthly sediment load changing more significantly than monthly runoff. Annual runoff and annual sediment load were significantly coherent throughout the study period, and there were significant resonant cycles of positive phase on 2‐, 3‐, 5‐ and 6‐year time scales. The coupling coordination degree of runoff and sediment load is generally at a coordinated developmental stage and is moving from low to high levels of coordination. Relative to the base period, changes in runoff and sediment load during the change period are mainly attributed to human activities. The contribution of human activities to the change in runoff ranged from 78.92% to 66.71%, and the contribution to the change in sediment load reached 93.40% to 94.15%. In contrast, precipitation in climate change has a greater impact on changes in runoff and sediment load than potential evapotranspiration. Land use changes and reservoir construction in the Min River basin have both contributed positively to the reduction of runoff and sediment load. The results of the study will help us to gain a deeper understanding of the processes and driving mechanisms of the runoff‐sediment relationship in the Min River basin, and provide a scientific basis for water resources management and sustainable development in the basin.

Implications for the Collisional Strength of Jupiter Trojans from the Eurybates Family

In this work, we model the collisional evolution of the Jupiter Trojans and determine under which conditions the Eurybates-Queta system survives. We show that the collisional strength of the Jupiter Trojans and the age of the Eurybates family and by extension Queta are correlated. The collisional grinding of the Jupiter Trojan population over 4.5 Gy results in a size–frequency distribution (SFD) that remains largely unaltered at large sizes (>10 km) but is depleted at small sizes (10 m to 1 km). This results in a turnover in the SFD, the location of which depends on the collisional strength of the material. It is to be expected that the Trojan SFD bends between 1 and 10 km. Based on the SFD of the Eurybates family, we find that the family was likely the result of a catastrophic impact onto a 100 km rubble pile target. This corresponds to objects with a rather low collisional strength (10 times weaker than that of basaltic material studied in Benz & Asphaug). Assuming this weak strength, and an initial cumulative slope of the size–frequency distribution of 2.1 between diameters of 2 m and 100 km when the Trojans were captured, the existence of Queta, the satellite of Eurybates, implies an upper limit for the family age of 3.7 Gy. Alternatively, we demonstrate that an unconventional collisional strength with a minimum at 20 m is a plausible candidate to ensure the survival of Queta over the age of the solar system. Finally, we show how different collisional histories change the expected number of craters on the targets of the Lucy mission and that Lucy will be able to differentiate between them.

Impacts of Climatic Variation and Human Activity on Runoff in Western China

Hydrological cycle is sensitively affected by climatic variation and human activity. Taking the upper- and middle-stream of the Weihe River in western China as an example, using multiple meteorological and hydrological elements, as well as land-use/land-cover change (LUCC) data, we constructed a sensitivity model of runoff to climatic elements and human activities based on the hydro-thermal coupling equilibrium equation, while a cumulative slope was used to establish a comprehensive estimation model for the contributions of climatic variation and human activities to the changes of runoff. The results showed that the above function model established could be well applied to quantitatively study the elasticity of runoff’s response to climatic variation and human activities. It was found that the annual average precipitation, evaporation, wind velocity, sunshine hours, relative humidity and runoff showed decreasing trends and that temperature increased. While in the hydrological cycle, precipitation and relative humidity had a non-linear positive driving effect on runoff, while temperature, evaporation, sunshine hours, wind velocity, and land-use/land-cover change (LUCC) have non-linearly negatively driven the variation of runoff. Moreover, runoff has a strong sensitive response to precipitation, evaporation and LUCC. In areas with strong human activities, the sensitivity of runoff to climatic change was decreasing, and runoff has a greater elastic response to underlying surface parameters. In addition, the analysis showed that the abrupt years of climate and runoff changes in the Weihe River Basin were 1970, 1985 and 1993. Before 1985, the contribution rate of climatic variation to runoff was 68.3%, being greater than that of human activities to runoff, and then the contribution rates of human activities to runoff reached 75.1%. The impact of natural climate on runoff was weakened, and the effect of human activities on runoff reduction increased. Under 30 hypothetical climatic scenarios, the evaluation of runoff in the future showed that the runoff in the Weihe River Basin will be greatly reduced, and the reduction will be more significant during the flood season. Comparing the geographically fragile environments and intense human activities, it was believed that climatic variation had a dramatic effect on driving the water cycle of precipitation and evaporation and affected regional water balance and water distribution, while human activities had driven the hydrological processes of the underlying surface, thus becoming the main factors in the reduction of runoff. This study provided scientific tools for regional climate change and water resources assessment.

Research on Automatic Dodging Method for Road Surface Line Array Images

Line scan cameras are widely used to acquire pavement images due to their imaging characteristics and low price, but the acquired pavement line array images often have uneven brightness. To eliminate the impact of image greyscale unevenness on subsequent processing, an automatic dodging method is proposed based on mask dodging algorithm. The main idea of the method is to chuck the images into sub‐blocks with the approximate greyscale change degree by introducing the cumulative slope conception. The rules to determine the filter size and the parameters required to adjust the sub‐block are self‐adaptive. The contrast stretching method is improved to make it more suitable for pavement images. The method is compared with other classical dodging algorithms, and the results show that the proposed automatic dodging method is better than others intuitively and quantitatively. The image length has no significant influence on it. Moreover, the crack segmentation results indicate that the proposed dodging method is effective for line array images, and a more accuracy crack segmentation could be achieved if the images preprocessed by the proposed dodging methods.

A re-assessment of the Kuiper belt size distribution for sub-kilometer objects, revealing collisional equilibrium at small sizes

In this work we combine several constraints provided by the crater records on Arrokoth and the worlds of the Pluto system to compute the size-frequency distribution (SFD) of the crater production function for craters with diameter D ≲ 10 km. For this purpose, we use a Kuiper belt objects (KBO) population model calibrated on telescopic surveys, that describes also the evolution of the KBO population during the early Solar System. We further calibrate this model using the crater record on Pluto, Charon and Nix. Using this model, we compute the impact probability on Arrokoth, integrated over the age of the Solar System. This probability is then used together with other observational constraints to determine the slope of the crater-production function on Arrokoth. These constraints are: (i) the spatial density of sub-km craters, (ii) the absence of craters with 1 < D < 7 km; (iii) the existence of a single crater with D > 7 km. In addition, we use our Kuiper belt model also to compare the impact rates and velocities of KBOs on Arrokoth with those on Charon, integrated over the crater retention ages of their respective surfaces. This allows us to establish a relationship between the spatial density of sub-km craters on Arrokoth and of D ~ 20 km craters on Charon. Together, all these considerations suggest the crater production function on these worlds has a cumulative power law slope of −1.5 < q < − 1.2. Converted into a projectile SFD slope, we find −1.2 < qKBO < − 1.0. These values are close to the cumulative slope of main belt asteroids in the 0.2–2 km range, a population in collisional equilibrium (Bottke et al., 2020). For KBOs, however, this slope appears to extend from ~2 km down to objects a few tens of meters in diameter, as inferred from sub-km craters on Arrokoth. From the measurement of the dust density in the Kuiper belt made by the New Horizons mission, we predict that the SFD of the KBOs becomes steep again below ~10–30 m. All these considerations strongly indicate that the size distribution of the KBO population is in collisional equilibrium.

Using pre-failure and post-failure remote sensing data to constrain the three-dimensional numerical model of a large rock slope failure

Factors governing rock slope stability include lithology, geological structures, hydrogeological conditions, and landform evolution. When certain conditions are met, rock slopes may become unstable, inducing deformation and failure. In the present study, an integrated remote sensing-numerical modeling approach investigates the deformation mechanisms leading to the 1965 Hope Slide, BC, Canada and the effect of slope kinematics on the long-term evolution of the slope. Pre- and post-failure datasets were used to perform a large-scale geomorphic and structural characterization, including kinematic and block-theory analyses. Extensive data collection was also undertaken using state-of-the-art remote sensing techniques, including digital photogrammetry (Structure-from-Motion), laser scanning (aerial and terrestrial), and infrared thermography. New evidence is provided that one or more prehistoric failures caused the removal of a key-block, and the initiation of long-term slope deformation and cumulative slope damage ultimately resulting in the catastrophic 1965 event. Detailed characterization of the rock slope has allowed the first three-dimensional, distinct element numerical model of the Hope Slide to be conducted. The results of the numerical simulations involving gradual reduction of the rupture surface shear strength indicate that 1965 slope failure may represent the outcome of a long-term, progressive failure mechanism that initiated after a prehistoric landslide. This combined field mapping–remote sensing–numerical modeling study clearly highlights the role of 3D slope kinematics on the geomorphic evolution of the slope, along with the associated failure mechanisms.

Effects of 120 vs. 60 and 90 g/h Carbohydrate Intake during a Trail Marathon on Neuromuscular Function and High Intensity Run Capacity Recovery.

Background: Current carbohydrate (CHO) intake recommendations for ultra-trail activities lasting more than 2.5 h is 90 g/h. However, the benefits of ingesting 120 g/h during a mountain marathon in terms of post-exercise muscle damage have been recently demonstrated. Therefore, the aim of this study was to analyze and compare the effects of 120 g/h CHO intake with the recommendations (90 g/h) and the usual intake for ultra-endurance athletes (60 g/h) during a mountain marathon on internal exercise load, and post-exercise neuromuscular function and recovery of high intensity run capacity. Methods: Twenty-six elite trail-runners were randomly distributed into three groups: LOW (60 g/h), MED (90 g/h) and HIGH (120 g/h), according to CHO intake during a 4000-m cumulative slope mountain marathon. Runners were measured using the Abalakov Jump test, a maximum a half-squat test and an aerobic power-capacity test at baseline (T1) and 24 h after completing the race (T2). Results: Changes in Abalakov jump time (ABKJT), Abalakov jump height (ABKH), half-squat test 1 repetition maximum (HST1RM) between T1 and T2 showed significant differences by Wilcoxon signed rank test only in LOW and MED (p < 0.05), but not in the HIGH group (p > 0.05). Internal load was significantly lower in the HIGH group (p = 0.017) regarding LOW and MED by Mann Whitney u test. A significantly lower change during the study in ABKJT (p = 0.038), ABKH (p = 0.038) HST1RM (p = 0.041) and in terms of fatigue (p = 0.018) and lactate (p = 0.012) within the aerobic power-capacity test was presented in HIGH relative to LOW and MED. Conclusions: 120 g/h CHO intake during a mountain marathon might limit neuromuscular fatigue and improve recovery of high intensity run capacity 24 h after a physiologically challenging event when compared to 90 g/h and 60 g/h.

Paraglacial history and structure of the Moosfluh Landslide (1850–2016), Switzerland

Rock slopes next to the tongue of the Great Aletsch Glacier, Switzerland are characterized by rapid environmental adjustment to non-glacial conditions. This study investigates and describes in detail the historic development of the largest rock slope instability in this area, called Moosfluh Landslide. We study in detail the structure, evolution and stability since the end of the Little Ice Age (LIA) until September 2016 and discuss their relationships with the evolution of the Great Aletsch Glacier since the Lateglacial period. In 2016 around 50 m of glacial ice thickness were left at the Moosfluh Landslide toe, where in 1850 glacial ice was >400 m thick. The changing stability conditions at the interface with the melting valley glacier are studied based on novel balanced cross sections and kinematic model of the Moosfluh Landslide dominated by toppling phenomena in metamorphic rock. The morphology and evolution of this landslide since the LIA are investigated with multi-temporal landslide maps based on aerial digital photogrammetry (ADP) applied to historic images since 1961. Internal deformation at Moosfluh is accommodated by shear slip along uphill-facing foliation and fault planes, and by extensional faulting forming tension cracks and graben-structures at the landslide head. Together with Digital Image Correlation (DIC) and total station monitoring (TPS) the Moosfluh Landslide displacement history was reconstructed, evidencing post-Egesen landslide displacements and an acceleration of movements since the LIA and especially since 2007. The displacement rates increase from few mm per year until the nineties to several meter per day in September 2016. Different kinematic models have been tested and changes in the Moosfluh rock slope stability in response to retreating glacial ice and changing groundwater conditions was explored with limit-equilibrium analysis of the stepped planar block toppling model of Goodman and Bray (1976). For the observed conditions and a toppling joint friction angle of 19° the simulated factor of safety drops non-linearly from the LIA maximum (1.12) to the year 2007 (1.02), when the height of ice above the valley bottom melted down to 100 m.This study illustrates with unprecedented detail the time scales, displacement magnitudes and structural evolutions of a large toppling mode slope instability in a paraglacial setting. The long-term cumulative slope displacements between the Egesen stadial and the LIA are of the same magnitude as the cumulative displacements between the LIA and the year 2016. As large portions of the studied slope underwent multiple retreats and advances of the Great Aletsch Glacier during the Lateglacial and Postglacial period, the observed onset of large slope displacements should be related to incremental damage (slip weakening and weathering) occurring along steeply dipping toppling fractures during the LIA.

Assessment of Topographical Factor (LS-Factor) Estimation Procedures in a Gently Sloping Terrain

The major uncertainty in soil erosion assessment studies is derived from LS-factor constituting slope length and slope steepness factors. Empirical soil erosion models employing different algorithms for estimation of LS-factor using raster-based digital elevation models (DEMs). Different algorithms have been adopted for LS-factor determination in soil erosion studies without proper justification for their selection according to the terrain characteristics; a few among them addressed suitability of the algorithms on hilly terrains. The present study focused on the performance of LS-factor estimation methods involving specific contributing area (SCA) method and cumulative slope length method for slope length factor and USLE, RUSLE and USPED algorithms for slope steepness factor in a gently sloping terrain. The results showed that SCA method is the best performing method in gently sloping terrain since the effect of contour length exponent get minimized since there are less influence from diagonal flow direction. The pixel-to-pixel-based slope length exponent may result in more appropriate estimation of slope length factor in gently sloping terrains. The SCA-based slope length estimation along with USLE S-factor algorithm was found to perform well under different elevation classes and slope classes in both SRTM DEM and ASTER DEM. The results from the study may be helpful in appropriate prediction of soil erosion in gently sloping terrains.

Analysis of runoff characteristics and contribution rate in Xiying River Basin in the Eastern Qilian Mountains

The impact of climate change on the basin is extensive and long-lasting, which will have a profound impact on the natural ecosystems, water resources, agriculture, and human production and life throughout the basin. An in-depth understanding of the impacts of climate change on watersheds and quantitative assessments will help to scientifically plan and manage water resources and protect the integrity of natural ecosystems. In this paper, temperature, precipitation and potential evapotranspiration data were used to analyze the response of Xiying River runoff to climatic factors in the Qilian Mountains by sliding correlation and wavelet analysis. M-K test and cumulative anomaly (CA) were used to analyze the climatic factors and runoff in the basin and use the pettitt method to test. Finally, the cumulative rate slope change rate comparison method was used to analyze the change of precipitation, potential evapotranspiration and snow-melt water contribution to runoff in this area. The results showed that temperature, precipitation and potential evapotranspiration had obvious mutations from 1961 to 2012 in this region. Compared with temperature and potential evapotranspiration, the precipitation showed greater impact on runoff. In addition, the contribution rate of ice and snow melt water to runoff was relatively larger in 1990 - 2002 compared to 1961-1989, followed by precipitation and evapotranspiration; the increase of the precipitation contribution rate became the main factor to runoff, followed by ice and snow melting and evapotranspiration compared to 1990-2002 in 2003-2017.

High impedance fault detection method based on improved complete ensemble empirical mode decomposition for DC distribution network

Aiming at DC distribution network, we proposed a novel high impedance fault detection method in the paper, it main procedures are as follows: Firstly, used the algorithm of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to extract the first intrinsic mode function (IMF) of the characteristic mode. Secondly, calculated the singular point of mutation and the cumulative slope by the acquisition of the first order difference operation, and then, achieved to distinguish the fault state and the normal state by the comparison between the slope and the starting threshold. Thirdly, identified the first IMF with Prony algorithm to obtain the parameters of characteristic frequency components (CFC) and direct current components (DC), and calculated the energy ratio between them, and then, distinguished small impedance fault (SIF), medium impedance fault (MIF), high impedance fault (HIF) and load switching (LS) by different values of energy ratio. A large number of experiments show that the proposed method is accurate and effective. Compared with other methods, this method shows its merits in feature extraction accuracy, detection accuracy and calculation speed.

Adaptive Optimized Pattern Extracting Algorithm for Forecasting Maximum Electrical Load Duration Using Random Sampling and Cumulative Slope Index

Load forecasting techniques can be an essential method to save energy and shave peak loads in order to improve energy efficiency and maintain the stability of a power grid. To achieve this goal, machine learning-based approaches have been proposed recently. Before moving toward the long-term and ultimate solution such as machine learning, we propose a simple and efficient method to forecast electricity usage patterns and the duration of maximum electrical load using a small data set. The proposed algorithm can forecast maximum electrical load duration using random sampling and a cumulative slope index. To verify the algorithm, we utilized electricity data (from 2015.11 to 2016.12) obtained from a building with a constant lifestyle and electricity pattern. The performance of the algorithm was evaluated using electricity bills, the discharging condition of an energy storage system, and the cumulative slope index. It was found that the proposed algorithm could provide electricity cost savings of 0.62–2.28% compared with other, conventional electricity prediction techniques, such as the moving average method and exponential smoothing. In near future research, it is expected that this algorithm could be applied to electrical big data to handle real-time data processing.

Acoustic correlates of prosodic dimensions in younger and older speakers of Czech

The present study reports phonetic data applicable for diagnostic purposes in voice related pathologies. However, apart from purely physiological concern, linguistic considerations are also acknowledged since the speech material consists of a continuous spoken text. Three age groups of speakers were recorded (young, middle-aged and old adults), each represented by 15 men and 15 women (n = 90). Several measures of fundamental frequency, together with variation in intensity and speech tempo were captured. An appreciably innovative metric, Cumulative Slope Index (CSI), was successfully employed to capture F0 variability in utterances. The results confirm differences between the age groups, but also between men and women, and contribute the normative mapping of the Czech population.

Linking the Depth-to-Water Topographic Index to Soil Moisture on Boreal Forest Sites in Alberta

The depth-to-water (DTW) index is defined as the cumulative slope along the least-cost pathway from any cell in the landscape to the nearest flow channel. The flow channel network is determined by the flow initiation area selected, allowing the representation of various geological and topographical attributes of the landscape. We used data from 125 plots across five locations in the boreal forest of Alberta, Canada, to evaluate the following: the relationships between soil attributes and DTW; the optimal flow initiation area; and models to map the spatial variation of soil properties. Soil moisture regime (SMR), drainage class, and depth-to-mottles were strongly related with DTW, whereas soil nutrient regime, organic matter thickness, soil texture, and coarse fragment content exhibited weak and inconsistent relationships with DTW. A flow initiation area of 2 ha yielded the best representation for SMR, drainage class, and depth-to-mottles. DTW, flow accumulation (FA) and local slope were combined in a linear model to estimate and map SMR, whereas only DTW and FA were used to model drainage and depth-to-mottles. These results suggest that the DTW index can capture soil properties closely influenced by the water table but cannot characterize site and soil factors, which are also determined by parent material, climate, and vegetation.