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Abstract The array of wildfire activities instigated by human endeavors has emerged as a significant source of atmospheric pollution, posing considerable risks to both public health and property safety. This study harnesses Sentinel-2 satellite data, employing a variety of methods including spectral index methods, thresholding, and the Random Forest (RF) model for active fire spot detection. The research encompasses a wide range of land cover types across various Chinese regions. Utilizing the Gini coefficient, the study assesses the importance of spectral and texture features in the RF, culminating in the selection of an optimal feature combination for the construction of a bespoke RF model tailored for active fire detection. The research utilized texture features based on the Grey Level Co-occurrence Matrix (GLCM), demonstrating their significant contribution to enhancing the accuracy of fire detection using the RF model. Our analysis reveals that GLCM-based texture features, which form 40% of the model’s final feature set, are crucial for improving detection accuracy. The optimized RF model demonstrates a marked superiority in identifying active fires, achieving an overall accuracy of 86.1%. The study results demonstrate that the bespoke RF model is suitable for detecting active fire across various land cover environments in China.

The study provides an overview of the development status of sleep disorder monitoring devices. Currently, polysomnography (PSG) is the gold standard for diagnosing sleep disorders, necessitating multiple leads and requiring overnight monitoring in a sleep laboratory, which can be cumbersome for patients. Nevertheless, the performance of PSG has been enhanced through research on sleep disorder monitoring and sleep staging optimization. An alternative device is the home sleep apnea testing (HSAT), which enables patients to monitor their sleep at home. However, HSAT does not attain the same level of accuracy in sleep staging as PSG, rendering it inappropriate for screening individuals with asymptomatic or mild obstructive sleep apnea-hypopnea syndrome (OSAHS). The study suggests that establishing a Chinese sleep staging database and developing home sleep disorder monitoring devices that can serve as alternatives to PSG will represent a future development direction.

At present, the rapid development of big data technology and the Internet of Things has led to the generation of spatiotemporal data streams on a substantial scale. In this context, data holders often opt for cloud storage of their data to mitigate the pressure of local storage and computing overhead. However, this centralized storage mode renders the data susceptible to risks of tampering and leakage due to the absence of physical control over spatiotemporal big data. Therefore, this paper devises a blockchain-based spatiotemporal big data privacy protection scheme. Initially, to ensure data privacy, the scheme adopts a storage mode where the public and side chains are coordinated. Subsequently, the irreversible SHA256 algorithm is utilized to authenticate the access nodes. Finally, AES and RSA hybrid encryption are applied to encrypt the collected spatiotemporal big data, further enhancing the security of private data. The security performance of the system was evaluated by comparing the success rate of attacks on the blockchain under various circumstances. Additionally, the system throughput of this scheme was analyzed through simulation, revealing that the service life of this system extends to a minimum of 13.79 years when 100 nodes are used. In this context, the system throughput achieves 1607 transactions/s, each node hosts 1.2107 blocks, and querying specific spatiotemporal data takes less than 2 seconds.

Objective The Shaxiongdong carbonatite-alkaline related Nb-REE deposit is located in the Wudang area of the south Qinling Belt, but the studies on Nb mineralization in this deposit are scarce. Methods Detailed petrographic observations were made by using polarizing microscope, optical cathodoluminescence and backscattered electron testing. The structure, composition and symbiotic relationship of the minerals were identified. The composition of two types of pyrochlore was analyzed by electron probe and the mechanism of niobium enrichment was discussed. Results The Shaxiongdong complex consists of three types of rocks that are spatially closely related: Meta-pyroxenite, syenite and carbonatite, of which the carbonatites are the major hosts of Nb mineralization characterized by main pyrochlore. This implies that Nb was concentrated to economic values in the carbonatite stage after extensive fractionation of the parental carbonated silicate magma. The pyrochlore in the deposit can be classified into two types on the basis of micro-textures: ① The primary ones (Pcl1) are euhedral to subhedral and display oscillatory zoning, implying their direct crystallization from carbonatite melts; ② The altered grains (Pcl2) exhibit patchy zonation under BSE images due to hydrothermal alteration. EPMA analytical results indicate that both types are rich in Nb and F at the B and Y sites, respectively, and at the A site, they are similarly mostly rich in Ca, thus named F-Ca-pyrochlore, with minor Na, thus named F-Na-pyrochlore. Conclusion The good positive correlations between F and Nb in both types of pyrochlore indicate that F plays a key role in the enrichment of niobium during magma differentiation. On the other hand, compared to the primary pyrochlore, the altered ones have relatively low Nb2O5, CaO, Na2O and F but high UO2, Ta2O5, SrO and SiO2, indicating that the fluids responsible for pyrochlore alteration are rich in Sr, Si and U, and the alteration tends to mobilize Nb in early pyrochlore, a process that is able to lower the Nb budgets of the deposit.

Under the influence of air temperature change, shallow permafrost landslide is a complex thermal-hydro-mechanical coupling process, which involves the transformation of water between solid state and liquid state. To reveal the influence of air temperature change on the shallow permafrost landslide, based on the coupled thermal-hydro-mechanical model for frozen soil, the thermal-hydro-mechanical evolution process of slope in permafrost region from 2020 to 2024 is simulated. The results are as follows: the rate of water migration presents periodic variation. The thawing degree of the active layer from May to October is high, causing the variation trend of total water content significantly. In summer, the thawing of the high ice content layer below the permafrost table forms a water-rich layer of 15 cm thickness approximately, causing excess pore water pressure difficult to dissipate. The permafrost table will decline by 10.4 cm in 4 years, and the thickness of the active layer and water-rich layer increased. As a result, the sliding force of the overlying thawed soil increases, the sliding resistance decreases, and the shear strength of the soil further decreases. Several centimeters displacement of frost heave and thaw settlement occurs in the active layer per year, shear strength deteriorates continuously, and the weak zone is easiest formed at slope toe.

Accurate and efficient detection for target crops is crucial to develop intelligent agriculture. A great deal of studies have been devoted to improving the accuracy and efficiency of detection algorithms, but the increasing requirement of computing power makes them particularly difficult to implement on embedded devices. Although some methods have been proposed to accelerate inference by lightening the weights of the algorithms after training, the huge computing power requirements of the algorithms are still a problem. In this paper, an improved lightweight parameters network with lightweight designed backbone and neck by grouped convolution is proposed, which also integrates convolutional (Conv) layers and Batch Normalization (BN) layers to accelerate inference. The experiments in this paper utilize the Strawberry Flower Detection dataset, Tomato dataset, Wind Turbine Detection dataset, and VOC2007 dataset to verify performances of the proposed network. And the results show that the computational cost, the number of parameters, memory footprint and inference time of the improved model are all reduced, while the mean Average Precision(mAP) is increased comparing with the baseline algorithm. Furthermore, the detection performances of the proposed algorithm implemented on Jetson Nano platform indicate it is suitable to be deployed in practical scenarios, especially for embedded platforms with limited computing power.

Taking the Wapo collapse area in Yuan’an County as an example, a three-dimensional model was established by drone aerial photography, geological survey and field mapping. Based on Rockfall Analyst (RA) analysis software, a large number of three-dimensional rockfalls in the Wapo collapse area were studied. The motion path, height, energy and other factors in the space were simulated to explore the three-dimensional motion characteristics of rockfalls. The risk assessment of rockfalls in the collapsed area was carried out to guide the prevention and control of the rockfalls. The research results showed that the main failure form of the dangerous rock was the toppling, and it was in an under-stable state at present; the three-dimensional motion trajectory of the simulated rockfall basically coincided with the existing rockfall point which indicating the simulation results were in good agreement with the actual situation; The mode of motion of the rocks were collision, bounce and free fall. Rockfalls were mainly concentrated in the gullies and roads but a few rocks reached residential areas. Therefore, the roads, gullies and the right side of the collapse area were in high risk area; Dangerous rock mass and boulders removal and passive protective nets were adopt as the prevention engineering,two passive protection nets which were 5 m high and 3 m high respectively were set on the inner side of the road and below the slope, and a net with an impact resistance of 2 000 kJ could effectively intercept falling rocks.

The Lenghu Saishiteng Mountain in Qinghai Province has the international first-class optical astronomy observation conditions. It creates a major opportunity for the development of optical astronomy in China and provides a valuable strategic resource for international optical astronomy development. Closely focusing on the engineering and geological site selection problem facing the construction of the Lenghu Saishiteng Mountain Observatory, the engineering and geological site selection evaluation is carried out on the basis of extensive collection of the geological survey results obtained by previous authors, by using a combination of remote sensing images, unmanned aerial photography, numerical simulation and manual ground survey. At this stage, two constructed platforms and two vacant platforms have been identified in Mount Saishiteng. In order to ensure the stability of engineering geological conditions of the constructed platforms and vacant platforms, firstly, manual ground investigation, rock samples and 3D response of slopes of constructed platforms under simulated seismic effects are conducted to determine the stability of platforms. InSAR monitoring and analysis of terrain deformation is then used in the key working area to determine the engineering geological stability of the key working area, and the BP neural network model algorithm is finally used to evaluate the regional engineering and geological stability of the Saishiteng Mountain area. The evaluation results show that although there are faults in the two constructed platforms, the impact on the construction is relatively small; no fault fragmentation zones and fracture structures are found in and around the two vacant platforms. Suggestions are made for the construction of the observatory to minimize the placement of engineering works and important equipment in the filling area, to ensure that the slope of the filling side slope is less than the natural rest angle, and to carry out appropriate engineering treatment for the rubble soil side slopes formed by manual excavation or filling ensure engineering safety and normal use of equipment. At the same time, two recommended platforms of 4300 m and 4050 m are recommended based on the evaluation results of different levels.

Several local landslides occurred in the Quwajiasa giant landslide in the upper reaches of the Yellow River from 1985 to 2020, which seriously threatened the safety of G227 national highway and the housing security of the villagers below. Taking the H1 landslides at the middle front of the northeast section of Quwajiasa landslide on September 20, 2019 as an example, based on the field investigation, deformation data and stability analysis, this paper intends to research the deformation and failure characteristics of the landslide, further analyze the sliding range as it moves through dynamic simulation, and the back analysis validated that after the movement of the No.1 shallow landslide following the Frictional model, it accumulated in the highway G227 and residential area from the retaining wall to Jungong Road, however, the No.2 shallow landslide in unstable state was predicted to accumulat in the residential area from Jungong road to the Yellow River after its movement, which will not block the frontal. The research content of this paper can provide some reference for the evaluation method for dynamic prediction super large landslides in the upper reaches of the Yellow River.

In arid and semi-arid regions, rainfall takes on a critical significance to both agricultural and engineering construction activities, and the transport process and driving mechanism of soil water under rainfall conditions are in need of further investigation. To clarify the variations in soil moisture, temperature, and liquid and vapor flux under various rainfall scenarios, the Mu Us Sandy Land was selected as the study region, and a water–vapor–heat transport model was established using the Hydrus-1D software with in situ observed soil and meteorological data. The simulated results were in good agreement with the measured data during both the calibration and validation periods, suggesting that the model was accurate and applicable to the study region. The variations in the selected dry and rainy periods proved the significant effect of rainfall events on soil matric potential, temperature, and driving forces. When rainfall occurred, the hydraulic conductivity for liquid water rose by three to five orders of magnitude, driving the liquid water flow downward. In contrast, the vapor flux played a vital role in soil water movement, accounting for about 15% of the total water flux in the shallow layer when the soil was dry, while it became non-significant during rainy periods due to the reduction in hydraulic conductivity for vapor and the temperature gradient. These results clarified the mechanisms of soil liquid water and vapor movement in arid areas, which could provide scientific support for future studies on vegetation restoration and ecosystem sustainability in ecologically fragile areas.

Abstract Most heritage buildings and monuments are constructed out of natural stones which suffer irrevocable degradation when undergoing wet weathering, bowing, and dissolution in outdoor conditions. Self-cleaning treatments are effective for stone protecting. Herein, nano-materials which provide enhanced protectants for Marble, Qingshi and Hedishi were prepared. Inherent microscale interstices and holes exist on polished natural stone surfaces. When treated by a commercial protectant, 101S, the surfaces were hydrophobic but not self-cleaning. Colloidal protectants were prepared by dispersion of Al2O3 and SiO2 nano-powder in 101S, respectively. Self-cleaning stone surfaces were achieved after treated by the protectants, meanwhile, the interstices and holes were reserved as much as possible. The principle of the as- prepared protectants is penetrating and crosslinking on the stone surfaces as well as the inner surfaces of the interstices and holes. The reserving of the micro interstices and holes is important since the breathability of the stones is remained. The self-cleaning surfaces showed good thermal stability below 250 °C. Meanwhile, changes of color and gloss of the treated stone surfaces are in the acceptable range.

With the popularity of spatiotemporal big data applications, more and more sensitive data are generated by users, and the sharing and secure storage of spatiotemporal big data are faced with many challenges. In response to these challenges, the present paper puts forward a new technology called CSSoB (Classified Secure Storage Technology over Blockchain) that leverages blockchain technology to enable classified secure storage of spatiotemporal big data. This paper introduces a twofold approach to tackle challenges associated with spatiotemporal big data. First, the paper proposes a strategy to fragment and distribute space–time big data while enabling both encryption and nonencryption operations based on different data types. The sharing of sensitive data is enabled via smart contract technology. Second, CSSoB’s single-node storage performance was assessed under local and local area network (LAN) conditions, and results indicate that the read performance of CSSoB surpasses its write performance. In addition, read and write performance were observed to increase significantly as the file size increased. Finally, the transactions per second (TPS) of CSSoB and the Hadoop Distributed File System (HDFS) were compared under varying thread numbers. In particular, when the thread number was set to 100, CSSoB demonstrated a TPS improvement of 7.8% in comparison with HDFS. Given the remarkable performance of CSSoB, its adoption can not only enhance storage performance, but also improve storage security to a great extent. Moreover, the fragmentation processing technology employed in this study enables secure storage and rapid data querying while greatly improving spatiotemporal data processing capabilities.

Spatiotemporal big data are a kind of data that marks time information and geographic location and has been widely applied in various fields. However, there are always security issues with spatiotemporal big data, especially in data collection and authentication. Traditional authentication protocols are less efficient in the face of ultra-large-scale IoT (Internet of Things, IoT) device verification, and the threat of single-point failure is relatively large. Given these complications, a group authentication scheme is proposed in this paper with blockchain spatiotemporal big data. The decentralization of the blockchain is utilized to solve the single point of failure, and the single-point authentication is combined with the group authentication, the authentication efficiency is improved through the group authentication, and the illegal nodes are accurately identified using the single-point authentication. The simulation results demonstrate that using the MHT (Merkel Hash Tree, MHT) algorithm for group authentication can effectively improve the authentication efficiency of the entire system when the number of users exceeds 200. The time overhead is only 4 ms when the number of users is 16,000. It can have a large throughput (400–500 tps) and a low latency (1–2 s) at the same time when the block size is 1500 KB. This study not only verifies the legitimacy of each device and protects the security of spatiotemporal big data, but also significantly reinforces the authentication efficiency compared with similar schemes.

Heritage buildings and monuments are mostly made from natural stone, which undergoes irreversible decay under outdoor conditions. The main reason for the contamination, degradation, and cracking of natural stones is water and oil permeation. Hence, modifications on stones rendering their surface self-cleaning are effective for stone protection. Reported in this paper is the development of a bionic approach to enabling self-cleaning stone surface via growing self-assembled polydopamine (PDA) as the adhesive layer on the stone surface, followed by depositing Al2O3 nanoparticles derivatized by self-assembled monolayers of a fluorophosphonic acid (FPA). This approach ensured a robust surface modification that realized superhydrophobicity, as demonstrated on natural marbles, Hedishi, and Qingshi. The surface modification was thermally stable up to 400 °C.

Cu _2 O has the advantages of low price, stable chemical properties, and high visible light absorption rate. It is a very promising hole transport material in solar cells. However, the pure phase Cu _2 O has a low hole transport rate, which can be improved it by means of doping or something else. In this paper, based on the first-principles, the performance of different amounts of S, Se, and Te doped Cu _2 O are calculated, it is found that the Te-doped Cu _2 O performance is pronounced, with the energy gap reduction (1.871 eV), there appear free electron generating, the valence band maximum enables energy level is matched (−5.463 eV), and the absorption coefficient in the ultraviolet and visible range improved, nearly 103.07% at 3.26 eV, the reflectance increased to, for the point 11.7 eV, 76%, and the loss function value is very small in the visible light region (less than 0.1).

To explore the impact of social distance and information presentation types on self-other risk preferences in monetary tasks. Risk preferences were examined in decision-making tasks and experiential information tasks within different frameworks when participants made decisions for themselves and others. Experiment 1 employed experiential decision tasks and revealed individual differences in decision-making for oneself and others. In gain situations, participants exhibited more risk aversion when deciding for others compared to themselves. Experiment 2 presented both types of information simultaneously to investigate whether risk decisions for oneself and others are influenced by information types. Results indicated that experiential information led participants to make more conservative choices for others, while descriptive information eliminated this effect. This study discovered the influence of social distance on self-other risk decisions and the role of information presentation types in self and other risk decision-making. Future research could further explore self-other decision-making from the perspectives of decision-makers' traits and culture. [ABSTRACT FROM AUTHOR]