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The Šine-Usu Inscription is the most voluminous one with 50 lines among the Uighur inscriptions. Although most parts of this inscription can be well understood, many words and sentences in the south and west sides are not so. These sides are now severely damaged. W..GšNG in the 4th line of the west side has been differently interpreted by researchers. The author regards xNùx±±v W..GšNG as a misreading for xNùx±±N N..GšNG, and amends it as xNùx[vL]N N[LW]GšNG an[lu]γšanïγ, suggesting that the letter groups TKGWYILKA …… N[LW]GšNGYWwKïKILms in this line should be read as taqïγu yïlqa …… an[lu]γšanïγ yoq q͜ ïlmïš “In the Fowl year (= 757), …… allegedly he (or they) eliminated Anluγšan (= An Lushan)”.

In the last thirty years, there have been fierce debates over how civilizations develop and why the West became so powerful.The Measure of Civilizationpresents a brand-new way of investigating these questions and provides new tools for assessing the long-term growth of societies. Using a groundbreaking numerical index of social development that compares societies in different times and places, award-winning author Ian Morris sets forth a sweeping examination of Eastern and Western development across 15,000 years since the end of the last ice age. He offers surprising conclusions about when and why the West came to dominate the world and fresh perspectives for thinking about the twenty-first century. Adapting the United Nations' approach for measuring human development, Morris's index breaks social development into four traits--energy capture per capita, organization, information technology, and war-making capacity--and he uses archaeological, historical, and current government data to quantify patterns. Morris reveals that for 90 percent of the time since the last ice age, the world's most advanced region has been at the western end of Eurasia, but contrary to what many historians once believed, there were roughly 1,200 years--from about 550 to 1750 CE--when an East Asian region was more advanced. Only in the late eighteenth century CE, when northwest Europeans tapped into the energy trapped in fossil fuels, did the West leap ahead. Resolving some of the biggest debates in global history,The Measure of Civilizationputs forth innovative tools for determining past, present, and future economic and social trends.

Established in 221 BCE, the Chinese empire lasted for 2,132 years before being replaced by the Republic of China in 1912. During its two millennia, the empire endured internal wars, foreign incursions, alien occupations, and devastating rebellions--yet fundamental institutional, sociopolitical, and cultural features of the empire remained intact.The Everlasting Empiretraces the roots of the Chinese empire's exceptional longevity and unparalleled political durability, and shows how lessons from the imperial past are relevant for China today. Yuri Pines demonstrates that the empire survived and adjusted to a variety of domestic and external challenges through a peculiar combination of rigid ideological premises and their flexible implementation. The empire's major political actors and neighbors shared its fundamental ideological principles, such as unity under a single monarch--hence, even the empire's strongest domestic and foreign foes adopted the system of imperial rule. Yet details of this rule were constantly negotiated and adjusted. Pines shows how deep tensions between political actors including the emperor, the literati, local elites, and rebellious commoners actually enabled the empire's basic institutional framework to remain critically vital and adaptable to ever-changing sociopolitical circumstances. As contemporary China moves toward a new period of prosperity and power in the twenty-first century, Pines argues that the legacy of the empire may become an increasingly important force in shaping the nation's future trajectory.

With the increasing frequency of all kinds of natural disasters, strengthening the resilience and disaster prevention capacity of communities, and improving residents' preparedness for disasters, have gradually become effective means of dealing with disaster risks and improving residents' well-being. However, few studies have explored the correlation between community resilience and disaster preparedness. This study uses survey data from 327 households in four districts and counties affected by the Wenchuan earthquake and the Lushan County, Sichuan earthquake in Sichuan Province, China. The study deeply analyzed the characteristics of community resilience and residents' disaster preparedness. We constructed a Tobit regression model to explore the correlations between community resilience and residents' disaster preparedness. The results show that (1) the community resilience and disaster prevention capability reached the general level of disaster risk reduction paradigm, and the overall disaster preparedness of residents was moderate. (2) The higher the score of community connection care, the better the residents' knowledge and skills preparation and overall disaster preparedness. The higher the score of community resource endowment, the weaker the residents' emergency preparedness. The higher the score of community change potential, the stronger the residents' emergency preparedness. The higher the score of community disaster management, the stronger the residents' emergency preparedness, knowledge and skills preparation, and overall preparedness. The higher the community information communication score, the weaker the knowledge and skills preparation of residents. This study deepens the understanding of the relationship between community resilience and residents’ disaster preparedness. Furthermore, it provides information for the establishment of resilient disaster prevention systems in communities threatened by disasters and for the formulation of policies to improve residents' ability to avoid disasters.

The Lushan shale, located in the Upper Sinian Formation of China, is a promising zone for commercial shale gas development. Understanding the crack evolution and fractal failure mechanisms of anisotropic Lushan shale under compression is critical for ensuring safe drilling and optimizing reservoir reconstruction. In this study, uniaxial compression tests were conducted on Lushan shale samples with varying bedding angles ( θ ) ranging from 0° to 90°, using acoustic emission (AE) techniques to monitor crack propagation and failure processes. The results reveal that both uniaxial compressive strength (UCS) and cumulative AE counts initially decrease and then increase with increasing bedding angle, reaching a minimum at θ  = 60°. During the initial loading phase, microcracking activity predominates, as indicated by a rising AE amplitude ( b -value); however, as the stress nears 70–80% of the UCS, the b -value undergoes a sharp decline, signaling a corresponding surge in large-magnitude cracking events and the onset of rock instability. Regardless of varying bedding angles, the failure of Lushan shale under compression is primarily dominated by tensile fractures, accounting for over 70% of the total fracture events. Three failure modes of anisotropic shale were mainly identified: through-layer failure, layer-slip failure, and tensile splitting failure. Fractal statistical analysis reveals that the fractal dimensions of AE signals correlate with shale fragment distribution, indicating that microcracking evolution directly influences macroscopic failure patterns, providing a potential framework for assessing rock stability.

Ground motions near the source area of the mainshock of the 2013 Lushan earthquake (Mw 6.6) in Sichuan Province in China were reproduced using the characterized source model and the empirical Green’s function method (EGFM). The best-fit characterized source model consisted of one strong motion generation area (SMGA) and a background area. The synthesized ground motions of the characterized source model were in fairly good agreement with the observed ground motions in the frequency range from 0.5 to 30.0 Hz at ten strong motion stations. For the 2013 Lushan earthquake (Mw 6.6), both the relationships between the SMGA and the seismic moment, and those between the flat amplitude of the acceleration source spectrum in the short period and the seismic moment almost followed the empirical scaling relationships of inner fault parameters developed for crustal earthquakes. The reasons for the largest peak ground acceleration (PGA) (> 1 g) in the strong-motion observation history of China recorded at the 51BXD strong motion station were investigated from the source and site effects. We found that the directivity effect did not contribute to the largest record by comparing the effect of different positions of the rupture starting point on the synthesized ground motions. The nonlinear effect of shallow layers was negligible, as indicated by the similarity of the earthquake H/V spectral ratios between the mainshock and EGF events. A large shear-wave velocity contrast might not exist in the shallow layers as the station was situated on the slope of a small rock hill. Finally, we agreed with previous studies that the hanging-wall effect and topographic effect might be the reasons for generating the largest record at Station 51BXD.

As one of the most earthquake-prone regions in the world, China faces extremely serious earthquake threats, especially for those heavily populated urban areas located near large fault zones. To improve the ability to prevent and minimize earthquake disaster risks, and to reduce earthquake disaster losses, China is currently building a nationwide earthquake early warning system (EEWS) with the largest seismic network in the world. In this paper, we present the newest progress of this project through describing the overall architecture of the national EEWS and evaluating the system performance during the 2022 Lushan M6.1 earthquake. The accuracy of the source characterization for the Lushan earthquake is discussed by comparing the continually estimated location and magnitude with the catalogs obtained from the China Earthquake Networks Center. For this earthquake, the EEWS generated a total of five alerts, and an initial alert was created 5.7 s after its occurrence, with excellent epicentral location and origin time estimation. The final alert was issued 16.5 s after origin time with a magnitude estimate of M6.1, the same as the catalog value. However, from the point view of alerting performance, the radius of the real blind zone without warning time was about 30 km and much larger than the theoretical result, mainly caused by the releasing system not considering the epicenter distance of each terminal when issuing the alerts. Although the earthquake exposed some limitations that need to be addressed in future upgrades, the results showed that most aspects of the EEWS presented a robust performance, with continuous, reliable event detections and early-warning information releasing.

The April 20, 2013 Mw6.6 earthquake of Lushan County, Sichuan Province, China, has triggered 4540 landslides (> 1000 m2). Exploring a more effective method to assess landslide hazard in the affected area of this event is of great significance for disaster prevention and mitigation. By applying the Newmark model and two statistical analysis models (logic regression and support vector machine, LR and SVM), this study addressed this issue. In the Newmark model, we used the landslide point density, the average gradient (mean slope) and the mean peak ground acceleration to group the lithology and created a critical acceleration (ac) map. The Newmark displacements and the probability of the slope instability are mapped by combining the ac map and PGA map. In the statistical analysis models of LR and SVM, 7040 samples (4540 landslide sites and 2500 random non-landslide sites) were randomly divided into the training set (5000 samples) and validation set (2040 samples). Based on the relationship between landslide distribution and influence factors, we selected the critical acceleration (ac) value, topographic relief, PGA, and distance to rivers as the independent variables for LR and SVM. Finally, the ROC curves for three landslide hazard models were drawn and the AUC values were calculated. The landslide hazard maps produced by LR are similar to those by applying SVM. The AUC values indicate that these two models combined with ac data perform better than the simplified Newmark model. In this study, a new method of integrating statistical analysis models (LR and SVM) with critical acceleration (ac) for earthquake landslide hazard assessment is presented, which can be used to carry out seismic landslide hazard assessment more effectively than the simplified Newmark model.

At 17:00 (UTC+8) on 1 June 2022, an Ms 6.1 reverse earthquake struck Lushan County, Ya’an City, Sichuan Province. This earthquake event had a focal depth of 10 km and the epicenter was located at 30.37° N and 102.94° E. The purpose of this study is to document a comprehensive coseismic landslide inventory for this event and analyze the distribution pattern and factors controlling the landslides. After careful visual interpretations, this quake event was determined to have in total triggered about 2352 landslides in an area of 3900 km2, including both shallow disrupted landslides and collapses, for which the spatial distribution was statistically related to regional topography, geology, and seismicity. Notably, a vast majority of the landslides were located on the NW plate of the seismogenic fault, and were distributed in the area with a seismic intensity of VII. In addition, coseismic landslides were more likely to appear in areas with high altitude, relief, and large slope. The landslide area density (LAD) increased with an increase in the above factors and is explained by an exponential relationship, indicating that the occurrence of coseismic landslides in this area was more easily affected by topographic factors than seismic factors. Most small-scale landslides were clustered in the ridge area, which shows the seismic amplification effects of mountain slopes. Due to the impact of seismic wave propagation direction, hillslopes facing northeast-east (NE-E) were more prone to collapse than southwest-facing ones. Based on the distribution pattern of the landslides, we suggest that the seismogenic fault of this event was NW dipping. These findings indicate that it is effective to identify the dipping of seismogenic faults using the spatial distribution pattern of coseismic landslides.