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As immovable stone cultural heritage is kept in the open air, they are more susceptible to damage, and damage detection is very important for the protection and restoration of cultural heritage. This is especially true for gold-overlaid stone cultural heritage, which is usually more complicated than ordinary stone carvings. However, the detection of cultural heritage damages is mainly based on expert visual inspection, which is often subjective, time-consuming, and laborious. This paper uses the Mask R-CNN algorithm to rapidly and accurately detect the gold foil shedding of stone cultural heritage through two-dimensional images. The research data are from the high-precision images of the Dazu Thousand-Hand Bodhisattva Statue (World Heritage, UNESCO) in Chongqing, China. After cleaning and augmentation, 1900 images are input into Mask R-CNN model for training. Finally, the average precision value (AP) for detecting gold foil shedding is found to be 0.967. In order to test the performance of the model, the new images that do not participate in the training period are used, and it is found that the model can still accurately detect the gold foil shedding even if there are interference factors. This is the first attempt to detect the damages of gold-overlaid stone cultural heritage based on a deep learning algorithm, and it has achieved good results. [ABSTRACT FROM AUTHOR]

In the midsummer of 2022, a rare regional high-temperature event occurred in the Yangtze River Basin. Chongqing, as the center of this event, also experienced its strongest high temperature since 1961. In this paper, the characteristics of this event in Chongqing are reviewed in detail and compared with those of 2006. We have confirmed the following conclusions with detailed data: (1) In the midsummer of 2022, the number of days that the daily maximum temperature is exceeding 35 ℃ in Chongqing was the most since 1961, with the number of days that the daily maximum temperature above 40 ℃ increasing significantly compared with 2006. (2) The impact range of this event in Chongqing was quite extensive, especially the range with the daily maximum temperature exceeding 40 ℃ was the widest since 1961. (3) The high-temperature event was more extreme in 2022 than that in 2006. The maximum of daily maximum temperature was 45 ℃, and this is the first time that China has recorded a high temperature of 45 ℃ outside Turpan. There were 5 stations with daily maximum temperature exceeding 44 ℃, accounting for 1/3 of the number of stations with such temperature (15 stations) in China. (4) In the midsummer of 2022, Chongqing was dominated by the compound high-temperature day. Compared with 2006, the daytime high-temperature day decreased significantly, while the compound one increased obviously. [ABSTRACT FROM AUTHOR]

Using the CRITIC method, comprehensive index evaluation method, VAR model, coupling coordination model and other methods, this paper evaluates the comprehensive development of the population economy and eco-geological environment composite system in the twin-city economic circle of Chengdu–Chongqing region from 2000 to 2020, verifies the dynamic coupling relationship between subsystems and measures the coupling coordination degree of complex system. Meanwhile, the differences in the development process of each subsystem are discussed and the spatial–temporal evolution characteristics and laws of coupling coordination of the composite system during the research period are analyzed. The results reveal the following: (1) There is a long-term coordinated relationship between population, economy and eco-geological environment in Chengdu–Chongqing region, which have the conditions for emergence and generation. (2) The subsystems of population, economy and eco-geological environment in Chengdu–Chongqing region show an overall upward trend, among which the Sichuan part obviously outperforms the Chongqing part. Besides, the growth rate of the economy subsystem is significantly higher than that of the population, eco-geological environment subsystem. (3) The coupling coordinated development of the composite system has shown a benign upward development trend, gradually changing from "composite spiral structure" to "two cores outstanding, peripheral collapse, the west superior to the east", while the main coordination state has developed from "Basic synergy—Economic lag" in 2000 to "Basic synergy—Population lag" in 2022. In addition, Cheng-De-Mian and Yuzhong districts with the better level of economic development have shown "Advanced synergy—Ecological lag". [ABSTRACT FROM AUTHOR]

Based on the upper limit theorem of limit analysis and the Hoek-Brown failure criterion and considering the adverse influence of the seepage force, we established a stability analysis method of analyzing the water-resistant rock mass of a karst tunnel face, developed a critical safety thickness criterion for water inrush caused by the instability of the tunnel face, and conducted a sensitivity analysis of the main influencing parameters. We defined the safety coefficient (k) of the tunnel face's resistance to water-inrush instability during the tunnel excavation process and analyzed the dynamic evolution characteristics of the tunnel face's stability during the tunnel construction according to the safety coefficient. We used the method introduced in this paper to calculate the safe thickness of the water-resistant rock mass of the Xiema tunnel face in the first horizontal line of the Chongqing Expressway where it is adjacent to karst cavity 268. We compared these results with the calculation results of a method that did not consider the adverse influence of the karst water seepage force. The results showed that the safety thickness of the water-resistant rock mass calculated using the method proposed in this paper more accurately conformed to the actual situation of the project, which can more effectively ensure the construction safety of the tunnel segment adjacent to the anterior, concealed, high-pressure, water-rich karst cavity. The results of this study hold great significance for improving the predictability and targeted prevention of water-inrush disasters in karst tunnels. [ABSTRACT FROM AUTHOR]

It is of great significance and practical application value to extract land-cover type accurately. However, the input data usually used in classification such as reflectance data or vegetation index are very simple and quantitative remote sensing products are rarely used. In this paper, a multi-spectral land-cover classification method based on deep learning is proposed. Using the excellent detail capture ability of contourlet transform to obtain the potential information to supplement the spectral feature space, combined with deep learning for feature selection and feature extraction, a spectral–texture classification model is constructed. The multi-spectral sensing remote data and field measurement data in Dadukou District of Chongqing, northern Negev, and Changping region of Beijing were used for evaluation. Experiment results show the proposed method can outperform principal component analysis, linear discriminant analysis and neural network, and effectively improve the classification accuracy of multi-spectral images; this method provides a new perspective for land-use classification. [ABSTRACT FROM AUTHOR]

This paper describes a new method using water-silt composite blasting for tunneling and the field tests conducted in the Tieshanping tunnel, Chongqing City, China. In this method, water-silt composite is substituted for the traditional pure silt stemming of the blast holes. Because of the incompressibility of water, the attenuation of the blasting wave is postponed and the effect of the blast air extended. The water-silt blasting method resulted in a larger crack zone, improved the breakage of rock, reduced the rock heap, lowered the dust and saved explosive. The stability of the surrounding rock was studied using theoretical analysis, in situ measurements and numerical modeling. The measured displacement at the tunnel crown was in good agreement with the theoretical and numerical results. [ABSTRACT FROM AUTHOR]