Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

Spatial and Temporal Distribution of Different Grades of Short-time Precipitation in Xining City

Based on the hourly precipitation data from 4 observation stations of Xining City from June to September during 2005-2011,the temporal and spatial distribution characteristics of short-time precipitation were analyzed.The results show that the precipitation distribution in Xining region exhibited the less-more-less trend from southwest to northeast,while the torrential rain gradually increased from the northwest and southwest to the middle.The hourly general precipitation in Xining region had obviously seasonal characteristics,and its annual distribution showed wavy changes,but the annual variation of short-time heavy precipitation and rainstorm was very obvious.Furthermore,short-time heavy precipitation was concentrated from 18:00 to 24:00,followed by 03:00-07:00 on the following day.The occurrence time of short-time rainstorm accorded with short-time heavy precipitation.It offers a useful reference for the accurate and timely short-term forecast.

Dynamically triggered seismicity on a tectonic scale:A review

Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments.In the past several decades,earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering,earthquake prediction,and the desire to use the mechanism of earthquake triggering to reduce,prevent,or trigger earthquakes.Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes.In the past several decades,some models have been developed,including static,dynamic,quasi‐static,and other models.Some reviews have been published,but explosiontriggered seismicity was not included.In recent years,some new results on earthquake triggering have emerged.Therefore,this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area.Instead of a complete review of the relevant literature,this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.

Trigger转座子衍生蛋白1对肝癌细胞生长的影响

细胞周期失调是肿瘤重要的标志之一,生物信息学分析结果表明,Trigger转座子衍生蛋白1(TIGD1)在临床肝癌组织中高表达且与细胞周期相关,但相关机制未知。为了探究TIGD1调控肝癌细胞生长的具体机制,首先,利用shRNA质粒构建靶向敲低TIGD1的肝癌细胞系Hep3B,并分析TIGD1敲低对肝癌细胞生长的影响,结果表明细胞生长受阻;接着,通过细胞流式技术分析TIGD1敲低对肝癌细胞周期进程的影响,结果显示,TIGD1敲低的Hep3B细胞系的细胞周期进程主要阻滞于G2/M期;然后,通过免疫沉淀(IP)实验验证TIGD1可能发生相互结合的蛋白分子,结果表明,TIGD1可能与Aurora激酶相互作用蛋白1(AURKAIP1)存在相互结合,进一步的Co-IP实验证实了TIGD1和AURKAIP1之间的相互作用。已知AURKAIP1可调控Aurora激酶A(AURKA)的蛋白酶体降解途径,AURKA是一种有丝分裂调控蛋白,与细胞周期进程密切相关。文中进一步探究TIGD1对AURKA蛋白水平的影响,实验结果表明,在TIGD1敲低的情况下,AURKA在Hep3B细胞系中的蛋白水平明显下调,mRNA水平没有明显变化。综上所述,TIGD1可能通过调控AURKA在肝癌细胞中的转录后水平来影响细胞周期进程,从而影响肝癌的发生发展。

Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

Stress triggering effect on the 2022 Honghe M_(S)5.0 earthquake with historical strong earthquakes

The 2022 Honghe M_(S)5.0 seismic event is intriguing due to its occurrence in the south of the Red River Fault,an area historically lacking seismic activities greater than M_(S)5.0.To elucidate the seismogenic mechanism and scrutinize stress-triggered interactions,we calculated co-seismic and post-seismic Coulomb stress alterations induced by nine historical seismic events(M≥6.0).The analysis reveals that these substantial seismic events provoked co-seismic stress augmentations of 1.409 bar and postseismic stress increments of 0.159 bar.Noteworthy seismic events,such as the 1833 Songming,1877Shiping,1913 Eshan,and 1970 Tonghai earthquakes,catalyzed the occurrence of the Honghe earthquake.Areas of heightened future seismic risk include the southern region of the Red River Fault and the eastern segments of the Shiping-Jianshui and Qujiang faults.Additionally,we assessed the correlation between the spatial distribution of aftershocks and the Coulomb stress shift triggered by the mainshock,taking into account the influence of calculation parameter settings.

Characteristics and triggering mechanisms of early negative Indian Ocean Dipole

Negative Indian Ocean Dipole(nIOD)can exert great impacts on global climate and can also strongly influence the climate in China.Early nIOD is a major type of nIOD,which can induce more pronounced climate anomalies in summer than La Niña-related nIOD.However,the characteristics and triggering mechanisms of early nIOD are unclear.Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD,and the former accounts for over one third of all the nIOD events in the past six decades.These two types of nIODs are similar in their intensities,but are different in their spatial patterns and seasonal cycles.The early nIOD,which develops in spring and peaks in summer,is one season earlier than the La Niña-related nIOD.The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern,with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean.Opposite to the triggering mechanism of early positve IOD,the early nIOD is induced by delayed Indian summer monsoon onset.The results of this study are helpful for improving the prediction skill of IOD and its climate impacts.

A study of pulsed high voltage driven hollow-cathode electron beam sources through synchronous optical trigger

In this study,a pulsed,high voltage driven hollow-cathode electron beam sources through an optical trigger is designed with characteristics of simple structure,low cost,and easy triggering.To validate the new design,the characteristics of hollow-cathode discharge and electron beam characterization under pulsed high voltage drive are studied experimentally and discussed by discharge characteristics and analyses of waveform details,respectively.The validation experiments indicate that the pulsed high voltage supply significantly improves the frequency and stability of the discharge,which provides a new solution for the realization of a high-frequency,high-energy electron beam source.The peak current amplitude in the high-energy electron beam increases from 6.2 A to 79.6 A,which indicates the pulsed power mode significantly improves the electron beam performance.Besides,increasing the capacitance significantly affects the highcurrent,lower-energy electron beam more than the high-energy electron beam.

Mechanisms to explain soil liquefaction triggering,development,and persistence during an earthquake

Mechanisms have been proposed to explain the triggering,development,and persistence of soil liquefaction.The mechanism explaining the horizontal failure plane(triggering)and its depth below the phreatic surface is governed by the flux properties and effective stress at that plane.At the failure plane,the pore water pressure was higher than the effective stress,and the volume change was the highest.The pore water pressure is a function of the soil profile features(particularly the phreatic zone width)and bedrock motion(horizontal acceleration).The volume change at the failure plane is a function of the intrinsic permeability of the soil and bedrock displacement.The failure plane was predicted to occur during the oscillation with the highest amplitude,disregarding further bedrock motion,which was consistent with low seismic energy densities.Two mechanisms were proposed to explain the persistence of soil liquefaction.The first is the existence of low-permeability layers in the depth range in which the failure planes are predicted to occur.The other allows for the persistence and development of soil liquefaction;it is consistent with homogeneous soils and requires water inflow from bedrock water springs.The latter explains many of the features of soil liquefaction observed during earthquakes,namely,surficial effects,“instant”liquefaction,and the occurrence of short-and long-term changes in the level of the phreatic surfaces.This model(hypothesis),the relationship between the flux characteristics and loss of soil shear strength,provides self-consistent constraints on the depth below the phreatic surfaces where the failure planes are observed(expected to occur).It requires further experimental and observational evidence.Similar reasoning can be used to explain other saturated soil phenomena.

Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network

With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.

Microstructural evolution in Al–Zn–Mg–Cu–Sc–Zr alloys during short-time homogenization

Abstract： Microstructural evolution in a new kind of aluminum （A1） alloy with the chemical composition of AI-8.82Zn-2.08Mg- 0.80Cu-3.31Sc-0.3Zr was investigated. It is found that the secondary phase MgZn2 is completely dissolved into the matrix during a short homogenization treatment （470℃, 1 h）, while the primary phase A13（Sc,Zr） remains stable. This is due to Sc and Zr additions into the A1 al- loy, high Zn/Mg mass ratio, and low Cu content. The experimental findings fit well with the results calculated by the homogenization diffusion kinetics equation. The alloy shows an excellent mechanical performance after the short homogenization process followed by hot-extrusion and T6 treatment. Consequently, a good combination of low energy consumotion and favorable mechanical properties is obtained.

Differentially Expressed Proteome of Microcystis under Short-time Ultrasonic Stress

This study was conducted to explore the regulation mechanism for key protein expression. The Microcystis treated by short-time ultrasonic wave was select-ed to analyze the total protein based on 2-DE. The results showed that there were 71 up-regulated protein spots, 56 down-regulated protein spots, 54 new protein spots and 21 protein spots disappeared under short-time ultrasonic stress. Eight dif-ferential proteins were chosen for further MALDI-TOFTOF/MS analysis, and the re-sults showed that 2 unknown proteins and 6 functional proteins were detected. These proteins were relevant to some physiological processes, such as antioxidation and anti-inflammatory process, phosphate synthesis and electron transfer, which is beneficial to the metabolic balance and self-protection under short-time ultrasonic stress.

Adaptive Short-Time Fractional Fourier Transform Based on Minimum Information Entropy

Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order to overcome the shortcomings,the STFrFT method with adaptive window function is proposed.In this method,the window function of STFrFT is ad-aptively adjusted by establishing a library containing multiple window functions and taking the minimum information entropy as the criterion,so as to obtain a time-frequency distribution that better matches the desired signal.This method takes into account the time-frequency resolution characteristics of STFrFT and the excellent characteristics of adaptive adjustment to window func-tion,improves the time-frequency aggregation on the basis of eliminating cross term interference,and provides a new tool for improving the time-frequency analysis ability of complex modulated sig-nals.

An HHT-based method to eliminate short-time strong disturbance from measured signals of bridge

According to the characteristic that Hilbert-Huang transform （HHT） can detect abnormity in signals, an HHT-based method to eliminate short-time strong disturbance was proposed. The signal with short-time strong disturbance was decomposed into a series of intrinsic mode functions （IMFs） and a residue by the empirical mode decomposition （EMD）. The instantaneous amplitudes and frequencies of each IMF were calculated. And at abnormal section, instantaneous amplitudes and frequencies were fired according to the data at normal section, replacing the fitted data for the original ones. A new set of IMFs was reconstructed by using the processed instantaneous amplitudes and frequencies. For the residue, abnormal fluctuations could be directly eliminated. And a new signal with the short-time strong disturbance eliminated was reconstructed by superposing all the new IMFs and the residue, The numerical simulation shows that there is a good correlation between the reconstructed signal and the undisturbed signal, The correlation coefficient is equal to 0.999 1. The processing results of the measured strain signal of a bridge with short-time strong disturbance verify the practicability of the method.

Characteristics of Radar Echo Parameters and Microphysical Structure Simulation of a Short-Time Heavy Precipitation Supercell

By using the conventional observations, radar data, NCEP/NCAR FNL 1°×1° reanalysis data and numerical simulation data and with the construction and calculation of radar echo parameters, this paper presents the structural characteristics and physical processes of a short-time heavy precipitation supercell that occurred in the squall line process in Shanxi Province on 24 June 2020. The results show that this squall line event occurred in front of a surface cold front,combined with infiltration of low-level cold air and continuous increase of near-surface humidity in the afternoon. The surface mesoscale convergence line and mesoscale dew point front contributed to the development and systemization of the squall line by a large degree. The short-time extremely heavy precipitation in Pingshun County was caused by the development of a supercell from thunderstorm cells on the front side of the squall line. The characteristics of sharp increase in vertical integral liquid water content, persistent increase in reflectivity factor and continuous rise in the echo top height appeared about 23 min earlier than the severe precipitation, which has qualitative indicating significance for the nowcasting of short-time heavy precipitation. A quantitative analysis of the radar echo parameters suggests that the“sudden drop”of FV40was a precursor signal of cells’ coalescence and rapid development to the mature stage. The areal change of the echo core at the 6 km height was highly subject to the merging and developing of cells, the rapid change of hydrometeor particles in clouds and the precipitation intensity. Changes in the cross-sectional area of convective cells at different heights can indirectly reflect the changes of liquid particles and ice particles in clouds, which is indicatively meaningful for predicting the coalescing and developing-to-maturing of cells and heavy precipitation 30-45 min earlier.A comprehensive echo parameter prediction model constructed by the random forest principle can predict the magnitude of short-time heavy precipitation 40-50 min in advance. Numerical simulation reveals that large amounts of water vapor existed in the near-surface atmosphere, and that the cells rapidly obtained moisture from the ambient atmosphere and developed rapidly through maternal feeding. The cold cloud zone was narrow, upright and had a high stretch height. The upward motion in clouds was strong and deep, and very rich in liquid water content. The graupel particles had a large vertical distribution range, the coexistence area of graupel and snow was large, the height of raindrops was close to the surface with a wide horizontal scale, and the precipitation efficiency was high. These may be the important elements responsible for the occurrence of the short-time heavy precipitation that exceeded historical extreme values. On the basis of the above analyses, a comprehensive parameter(CP) prediction model is worked out, which can estimate the developing trend of supercells and the intensity of short-time heavy precipitation about 1 h in advance.

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20 - 30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23 - 24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16 - 18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

Resilient Event-Triggered Model Predictive Control for Adaptive Cruise Control Under Sensor Attacks

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor attacks.In the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal data.Then,the robust control gains are derived to design the terminal region constraint for MPC.

A review of tidal triggering of global earthquakes

Earthquake prediction remains a challenging and difficult task for scientists all over the world.The tidal triggering of earthquakes is being proven by an increasing number of investigations,most of which have shown that earthquakes are positively correlated with tides,and thus,tides provide a potential tool for earthquake prediction,especially for imminent earthquakes.In this study,publications concerning the tidal triggering of earthquakes were compiled and analyzed with regard to global earthquakes,which were classified into three main types:tectonic,volcanic,and slow earthquakes.The results reveal a high correlation between tectonic earthquakes and tides(mainly for semidiurnal and diurnal tides;14-day tides) before and after the occurrence of significant earthquakes.For volcanic earthquakes,observations of volcanoes on the seafloor and land indicate that volcanic earthquakes in near-shore volcanic areas and mid-ocean ridges have a strong correlation with tidal forces,mostly those with semidiurnal and diurnal periods.For slow earthquakes,the periodicity of the tremor duration is highly correlated with semidiurnal and diurnal tides.In conclusion,the tidal triggering of these three types of earthquakes makes a positive contribution to earthquake preparation and understanding the triggering mechanism,and thus,the prediction of these types of earthquakes should be investigated.However,there are still several inadequacies on this topic that need to be resolved to gain a definitiveanswer regarding the tidal triggering of all earthquakes.The main inadequacies are discussed in this paper from our point of view.

Short-Time Decoherence of Solid-State Qubit at Optimal Operation Points

We investigate the short-time decoherence of a solid-state qubit under Ohmic noise at optimal operation points. The decoherence is analyzed by maximum norm of the deviation density operator. It is shown that at the temperature T = 3 mK, the loss of the fidelity due to decoherence is much smaller than the DiVincenzo low decoherence criterion, which means that the mode/may be an optimal candidate of qubit for quantum computation.

Short-Time Dynamics of the Random n-Vector Model

Short-time critical behavior of the random n-vector model is studied by the theoretic renormalization-group approach.Asymptotic scaling laws are studied in a frame of the expansion in e = 4 - d for n ≠ 1 and for n = 1respectively.In d ＜ 4,the initial slip exponents θ′ for the order parameter and θ for the response function are calculated up to the second order in e ＝ 4 - d for n ≠ 1 and for n ＝ 1 at the random fixed point respectively.Our results show that the random impurities exert a strong influence on the short-time dynamics for d ＜ 4 and n ＜ nc.