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This article presents a vibration model of neighboring rolling parts that takes into account non-smooth symmetric collisions. This model was used to examine the motion state of the rolling element and the collision force between nearby rolling elements. It also determined the motion posture and overall collision form of the rolling element after setting the functional slot. Afterwards, the level of disorderly movement and the structure of the moving object were examined and confirmed through the use of a phase diagram of the motion system in relation to zero symmetry, the Lyapunov exponent, and a platform for measuring irregular vibrations in the bearing. This work aims to clarify the factors that contribute to the persistent chaotic state of rolling elements in bearing vibration. [ABSTRACT FROM AUTHOR]

Geothermal resources have been recognized as important sources of clean renewable energy. The exploration, development, and utilization of geothermal resources, especially hot dry rock (HDR) resources, are highly important for achieving peak carbon and carbon neutrality. However, there is no comprehensive evaluation method for determining HDR target areas, and the evaluation scale and application disciplines are relatively simplistic. In this paper, we sought to optimize the identification of HDR target areas through a multiscale and multidisciplinary method and formed a set of generalized and demonstrative processes to guide the exploration of HDR resources. Through practical application to the Gonghe Basin and the Zhangzhou Basin, it was found that the comprehensive geothermal conditions of the Gonghe Basin are superior to those of the Zhangzhou Basin, and the geothermal reservoir depth, geothermal reservoir temperature, geothermal gradient, and heat flow are the four most important factors affecting hot dry rock geothermal resources. Using this method, the prioritization of target areas changes from a qualitative study to a quantitative and semiquantitative study, increasing the specificity and reliability of the decision-making process. [ABSTRACT FROM AUTHOR]

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. [ABSTRACT FROM AUTHOR]

Large-scale wind farms incorporating doubly-fed induction generators (DFIGs) are considered a promising direction for modern energy supply systems due to their role in reducing dependence on fossil energy sources. However, the dynamic interactions between DFIGs and AC grids sometimes lead to sub-synchronous oscillation (SSO) that threatens the safe and stable operation of wind power systems. Therefore, it is essential to develop a mathematical model and design an algorithm to quantitatively design the control parameters. Such algorithms are helpful in preventing or mitigating system stability problems coming from wind power connected to the grid and reducing damage to power equipment. The traditional state-space model is mainly established to determine the stable operating point and analyze the influence of parameters on the system operating mode. However, this method does not provide the selection area for the system parameters. To address this shortcoming, this paper introduces a modular state-space model for DFIGs containing series compensation lines and proposes an algorithm for calculating the parameter selection area based on the Guardian map method. First, a detailed modular state-space model based on the virtual synchronous generator (VSG) control is established. The modular model helps to reflect the relationship between state variables and focuses on describing the operating state of DFIGs in wind farms. Second, this paper focuses on the influence of VSG control parameters and compensation capacitance on SSO. It aims to clarify the role of the series compensation level and control parameters on SSO based on VSG control. Then, an algorithm for the parameter selection area based on the Guardian map is proposed and the area of the VSG-controlled DFIG is obtained. Finally, the accuracy and validity of the algorithm are verified by time domain simulation in MATLAB/Simulink and HIL experiment. [ABSTRACT FROM AUTHOR]

The thermal structure of the lithosphere is key to understanding its thickness, properties, evolution, and geothermal resources. Cratons are known for their low heat flow and deep lithospheric roots. However, present-day cratons in East China have geothermal characteristics that are highly complex, with variable heat flow values, diverging from the typical thermal state of cratons. In this study, we conducted a detailed analysis of the geothermal geological background of the cratons in East China, summarizing the thermal state and tectono-thermal processes of different tectonic units, calculating the temperature at various depths, and discussing differences in temperature and thermal reservoirs at different depths. The observed lithospheric thermal thickness within the North Jiangsu Basin and the Bohai Bay Basin is notably reduced in comparison to that of the Jianghan Basin and the Southern North China Basin. The phenomenon of craton destruction during the Late Mesozoic emerges as a pivotal determinant, enhancing the geothermal resource prospects of both the Bohai Bay Basin and the North Jiangsu Basin. Our findings contribute significantly to the augmentation of theoretical frameworks concerning the origins of heat sources in global cratons. Furthermore, they offer invaluable insights for the methodical exploration, evaluation, advancement, and exploitation of geothermal resources. [ABSTRACT FROM AUTHOR]

With the promotion of the dual carbon target, the scale of the wind power grid connection will significantly increase. However, wind power has characteristics such as randomness and volatility, and its grid connection challenges the pressure of system peak shaving, making it increasingly difficult to regulate the power system. To solve the problem of wind power abandonment, the positive and negative peak shaving characteristics of wind power were first analyzed. Based on this, it is proposed that demand response resources and energy storage with adjustable characteristics are used as the new means of wind power consumption. Together with the thermal power units, they participate in the optimization and scheduling of the power grid, forming a coordinated and optimized operation mode of source load storage. With the goal of minimizing system operating costs, a two-stage economic scheduling model was formed for the day-ahead and intra-day periods. Finally, optimization software was used to solve the problem, and the simulation results showed the effectiveness of the proposed economic scheduling model, which can improve the system's new energy consumption and reduce the system's operating costs. [ABSTRACT FROM AUTHOR]

The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pressure monitoring and early warning. In this paper, the wavelet coefficient threshold denoising method in the time–frequency domain, STA/LTA method, AIC method, and skew and kurtosis method are studied, and the automatic P-phase-onset-time-picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized, the reliability of the P-phase-onset-time-picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity in the underground mine, which is of great significance to the data processing and analysis of microseismic monitoring. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) has been extensively utilized in deep-space exploration. However, GPR modeling commonly employs simplified antenna models and carrier-free impulse signals, resulting in reduced accuracy and interpretability. In this paper, we addressed these limitations by combining a tilted monopole antenna and linear frequency modulation continuous wave (LFMCW) to simulate real conditions. Additionally, a radiation-pattern-compensation back-propagation (RPC-BP) algorithm was developed to improve the illumination of the right-inclined structure. We first introduced the LFMCW used by the Mars Rover Penetrating Radar (RoPeR) onboard the Zhurong rover, where frequencies range from 15 to 95 MHz. Although the LFMCW signal improves radiation efficiency, it increases data processing complexity. Then, the radiation patterns and response of the tilted monopole antenna were analyzed, where the radiated signal amplitude varies with frequency. Finally, a series of numerical and laboratory experiments were conducted to interpret the real RoPeR data. The results indicate that hyperbolic echoes tilt in the opposite direction of the survey direction. This study demonstrates that forward modeling considering real transmit signals and complex antenna models can improve modeling accuracy and prevent misleading interpretations on deep-space exploration missions. Moreover, the migration process can improve imaging quality by considering radiation pattern compensation. [ABSTRACT FROM AUTHOR]

Near-surface structure investigation plays an important role in studying shallow active faults and has various engineering applications. Therefore, we developed a near-surface structure investigation method using ambient noise in a water environment. This newly developed seismic acquisition technology, fiber-optic distributed acoustic sensing (DAS), was used to acquire ambient noise from the Yangtze River. The recorded data were processed to reconstruct surface waves based on the theory of seismic interferometry. The fundamental-mode dispersion curves were extracted and inverted to obtain a shear-wave velocity model below the DAS line. We compared the inverted velocity model with the subsurface geological information from near the study area. The results from the inverted model were consistent with the prior geological information. Therefore, ambient noise in the water environment can be combined with DAS technology to effectively investigate near-surface structures. [ABSTRACT FROM AUTHOR]

Satellite hyperspectral imagery is an important data source for large-scale refined land cover classification and mapping, but the high spatial heterogeneity and spectral variability at low spatial resolution and the high computation cost for massive data remain challenges in the research community. In recent years, convolutional neural network (CNN) models with the capability for feature extraction have been widely used in hyperspectral image classification. However, incomplete feature extraction, inappropriate feature fusion, and high time consumption are still the major problems for CNN applications in large-scale fine land cover mapping. In this study, a Spatial-Convolution Spectral-Transformer Interactive Network (SCSTIN) was proposed to integrate 2D-CNN and Transformer into a dual-branch network to enhance feature extraction capabilities by exploring spatial context information and spectral sequence signatures in a targeted manner. In addition, spatial-spectral interactive fusion (SSIF) units and category-adaptive weighting (CAW) as two feature fusion modules were also adopted between and after the two feature extraction branches to improve efficiency in feature fusion. The ZY1-02D hyperspectral imagery was collected to conduct the experiments in the study area of the eastern foothills of the Helan Mountains (EFHLM), covering an area of about 8800 km2, which is the largest hyperspectral dataset as far as we know. To explore the potential of the proposed network in terms of accuracy and efficiency, SCSTIN models with different depths (SCSTIN-4 and SCSTIN-2) were performed. The results suggest that compared with the previous eight advanced hyperspectral image classifiers, both SCSTIN models achieved satisfactory performance in accuracy and efficiency aspects with low complexity, where SCSTIN-4 achieved the highest accuracy and SCSTIN-2 obtained higher efficiency. Accordingly, the SCSTIN models are reliable for large-scale fast refined land cover classification and mapping. In addition, the spatial distribution pattern of diverse ground objects in EFHLM is also analyzed. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of state estimation for nonlinear multi-sensor systems with cross-correlated noise and packet loss compensation. In this case, the cross-correlated noise is modeled by the synchronous correlation of the observation noise of each sensor, and the observation noise of each sensor is correlated with the process noise at the previous moment. Meanwhile, in the process of state estimation, since the measurement data may be transmitted in an unreliable network, data packet dropout will inevitably occur, leading to a reduction in estimation accuracy. To address this undesirable situation, this paper proposes a state estimation method for nonlinear multi-sensor systems with cross-correlated noise and packet dropout compensation based on a sequential fusion framework. Firstly, a prediction compensation mechanism and a strategy based on observation noise estimation are used to update the measurement data while avoiding the noise decorrelation step. Secondly, a design step for a sequential fusion state estimation filter is derived based on an innovation analysis method. Then, a numerical implementation of the sequential fusion state estimator is given based on the third-degree spherical-radial cubature rule. Finally, the univariate nonstationary growth model (UNGM) is combined with simulation to verify the effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Aiming at the problems of power flow fluctuation and voltage exceeding standard caused by high permeability distributed power supply access, this paper proposes a load state perception early warning method for distribution networks. Firstly, the random behavior characteristics and voltage early warning mechanisms of power supply and load in distribution networks are analyzed, the dynamic model of distribution networks based on complex network theory is established, and the risk index of voltage exceeding limits under the conditions of high permeability distributed power supply access is put forward. Secondly, the random power flow of distribution networks based on the Monte Carlo method is studied by sampling and analyzing the dynamic model of distribution networks. Then, the risk calculation and safety assessment of voltage exceeding limits are carried out on the currently extracted model, and the risk control strategy of distribution network operation is put forward. Finally, an improved IEEE30-node distribution network topology is proposed. Through simulation analysis, it is proven that the load situation awareness early warning method of distribution networks can effectively predict, improve the security of distribution networks, and provide timely early warning information for maintenance personnel. [ABSTRACT FROM AUTHOR]

Ordered porous polyimide films were fabricated from (AB)m type of diblock copolymer polyimide-b-polystyrene (PI-b-PS). An increase in PS volume fraction (f VPS) is beneficial to decrease the relative dielectric constants and water contact angles of the obtained porous PI films: the relative dielectric constant decreases to 1.89 and water contact angle decreases to 43° when f VPS is 0.36, indicating porous PI films can be used as low-κ material and have good wettability. The solvent uptake of the porous PI films increases with increasing f VPS. A net-like morphology appears when f VPS reaches 0.36. The net-like porous PI film reaches equilibrium uptake of water within approximately 2.5 h, with a final equilibrium uptake ratio of 17.5%, and reaches equilibrium uptake of toluene within approximately 8 h, with a final equilibrium uptake ratio of 15.4%, displaying the highest and fastest solvent uptake compared with other microstructured porous PI films, which is ascribed to the specific characteristic of the interconnecting porous channels derived from the self-assembly of PI-b-PS with f VPS 0.36. Introducing thermally degradable segments to PI-based block copolymer is an effective method to prepare porous PI films and can enhance some of their properties. [ABSTRACT FROM AUTHOR]

The ideal wind turbine power curve provided by the manufacturer cannot monitor the practical performance of wind turbines accurately in the engineering stage; in this paper, a modified approach of the wind turbine power curve is proposed based on improved Bins and K-means++ clustering. By analyzing the wind speed-power data collected by the supervisory control and data acquisition system (SCADA), the relationship between wind speed and output is compared and elaborated on. On the basis of data preprocessing, an improved Bins method for equal frequency division of data is proposed, and the results are clustered through K-means++. Then, the wind turbine power curve correction is realized by data weighting and regression analysis. Finally, an example is given to show that the power curve of the same type of wind turbines, which, installed in different locations, are discrepant and different from the MPC, and the wind turbine power curve obtained by using this method can reflect the output characteristics of the wind turbine operating more effectively in a complex environment. [ABSTRACT FROM AUTHOR]

The high-resolution seismic characterization of gas hydrate reservoirs plays an important role in the detection and exploration of gas hydrate. The conventional AVO (amplitude variation with offset) method is based on a linearized Zoeppritz equation and utilizes only the reflected wave for inversion. This reduces the accuracy and resolution of the inversion properties and results in incorrect reservoir interpretation. We have studied a high-resolution wave-equation-based inversion method for gas hydrate reservoirs. The inversion depends on the scattering integral wave equation that describes a nonlinear relationship between the seismic wavefield and the elastic properties of the subsurface medium. In addition to the reflected wave, it considers more wavefields including the multiple scattering and transmission during inversion to improve the subsurface illumination, so as to enhance the accuracy and resolution of the inversion properties. The results of synthetic data from Pearl River Mouth Basin, South China Sea, demonstrate the validity and advantages of the wave-equation-based inversion method. It can effectively improve the resolution of inversion results compared to the conventional AVO method. In addition, it has good performance in the presence of noise, which makes it a promising method for field data. [ABSTRACT FROM AUTHOR]

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy–economy–environment–security (3E–S) evaluation method, in which principal component analysis (PCA) was adopted for multi-criterion decision making. According to the analysis results of the case city in Guangdong, this evaluation method was proved to be an effective way to identify the factors that may influence coordinated development. By adjusting the relevant parameters and factors in the model, the optimal decarbonization pathway can be found to promote sustainable and coordinated development, thus helping government decision makers to quantitatively evaluate planning paths. [ABSTRACT FROM AUTHOR]

For large-scale and sustainable water electrolysis, it is of great significance to develop cheap and efficient electrocatalysts that can replace platinum. Currently, it is difficult for most catalysts to combine high activity and stability. To solve this problem, we use cobalt to regulate the electronic structure of ruthenium to achieve high activity, and use carbon matrix to protect alloy nanoparticles to achieve high stability. Herein, based on the zeolitic imidazolate frameworks (ZIFs), a novel hybrid composed of RuCo alloy nano-particles and N-doped carbon was prepared via a facile pyrolysis-displacement-sintering strategy. Due to the unique porous structure and multi-component synergy, the optimal RuCo500@NC750 material in both acidic and alkaline media exhibited eminent HER catalytic activity. Notably, the 3-RuCo500@NC750 obtained a current density of 10 mA cm−2 at 22 mV and 31 mV in 0.5 M H2SO4 and 1.0 M KOH, respectively, comparable to that of the reference Pt/C catalyst. Furthermore, the Tafel slopes of the catalyst are 52 mV Dec−1 and 47 mV Dec−1, respectively, under acid and alkali conditions, and the catalyst has good stability, indicating that it has broad application prospects in practical electrolytic systems. This work contributes to understanding the role of carbon-supported polymetallic alloy in the electrocatalytic hydrogen evolution process, and provides some inspiration for the development of a high efficiency hydrogen evolution catalyst. [ABSTRACT FROM AUTHOR]

In shale gas hydraulic fracture monitoring or rock acoustic emission experiments, fracture plane identification is always a complex task. Conventional approaches typically use the source locating results derived from the micro-seismic event and then interpret the fracture plane using manual qualitative analysis. Large errors typically occur due to manual operations. On the other hand, the density-based clustering algorithm with spatial constraints is widely used in geographic information science, biological cells science and astronomy. It is an automated algorithm and can achieve good classification results. In this paper, we introduced the above-mentioned clustering algorithm with spatial constraints to fracture identification applications. Moreover, because micro-seismic events are 4D in nature, every micro-seismic event has both time and space information. Hence, we improve the conventional clustering algorithm by incorporating a time constraint. We test the proposed method using rock acoustic emissions data and compare our fracture identification results with CT scan images; the comparison clearly shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The study of thermal conductivity anisotropy is of great importance for more accurate heat flow calculations, geodynamic studies, development and utilization of hot dry rock, and simulation of heat transfer in geological reservoirs of nuclear waste, and so on. To study the thermal conductivity anisotropy of rocks, 1158 cores from 60 boreholes in East China were tested for thermal conductivity, including thermal conductivity values parallel to (λ∥) and perpendicular to (λ⊥) structural planes of basalt, mudstones, gneisses, sandstones, carbonates, evaporites, and metamorphic rocks. The thermal conductivity anisotropy is not obvious for sand, clay, and evaporate, and the average anisotropic factors of 1.19 ± 0.22, 1.18 ± 0.17, and 1.18 ± 0.17 for tuff/breccia, granitoid and contact metamorphic rocks, respectively, indicate that these three rocks have strong anisotropy characteristics. Finally, the effect of thermal conductivity anisotropy on heat flow is studied and discussed in detail, showing that the results of thermal conductivity tests have a significant effect on the calculation of heat flow and thermal structure, and the data show that a deviation of about 10% in thermal conductivity causes a deviation of about 11% in heat flow, which may lead to a misperception of deep thermal structure studies. The regular and anisotropic characteristics of thermal conductivity of various rocks in Eastern China obtained in this paper can provide parameter support for projects such as heat flow calculations, thermal structure studies, and geothermal resource development and utilization. [ABSTRACT FROM AUTHOR]

In recent years, image segmentation based on deep learning has been widely used in medical imaging, automatic driving, monitoring and security. In the fields of monitoring and security, the specific location of a person is detected by image segmentation, and it is segmented from the background to analyze the specific actions of the person. However, in low-illumination conditions, it is a great challenge to the traditional image-segmentation algorithms. Unfortunately, a scene with low light or even no light at night is often encountered in monitoring and security. Given this background, this paper proposes a multi-modal fusion network based on the encoder and decoder structure. The encoder, which contains a two-branch swin-transformer backbone instead of the traditional convolutional neural network, fuses the RGB and depth features with a multiscale fusion attention block. The decoder is also made up of the swin-transformer backbone and is finally connected via the encoder with several residual connections, which are proven to be beneficial in improving the accuracy of the network. Furthermore, this paper first proposes the low light–human segmentation (LLHS) dataset of portrait segmentation, with aligned depth and RGB images with fine annotation under low illuminance, by combining the traditional monocular camera and a depth camera with active structured light. The network is also tested in different levels of illumination. Experimental results show that the proposed network has good robustness in the scene of human segmentation in a low-light environment with varying illumination. The mean Intersection over Union (mIoU), which is often used to evaluate the performance of image segmentation model, of the Swin-MFA in the LLHS dataset is 81.0, is better than those of ACNet, 3DGNN, ESANet, RedNet and RFNet at the same level of depth in a mixed multi-modal network and is far ahead of the segmentation algorithm that only uses RGB features, so it has important practical significance. [ABSTRACT FROM AUTHOR]

Aquaculture plays a vital role in global food production, with fish pond water quality directly impacting aquatic product quality. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) serves as a key producer of aquatic products in South China. Monitoring environmental changes in fish ponds serves as an indicator of their health. This study employed the extreme gradient boosting tree (BST) model of machine learning, utilizing Landsat imagery data, to assess Chlorophyll-a (Chl-a) concentration in GBA fish ponds from 2013 to 2022. The study also examined the corresponding spatiotemporal variations in Chl-a concentration. Key findings include: (1) clear seasonal fluctuations in Chl-a concentration, peaking in summer (56.7 μg·L−1) and reaching lows in winter (43.5 μg·L−1); (2) a slight overall increase in Chl-a concentration over the study period, notably in regions with rapid economic development, posing a heightened risk of eutrophication; (3) influence from both human activities and natural factors such as water cycle and climate, with water temperature notably impacting summer Chl-a levels; (4) elevated Chl-a levels in fish ponds compared to surrounding natural water bodies, primarily attributed to human activities, indicating an urgent need to revise breeding practices and address eutrophication. These findings offer a quantitative assessment of fish pond water quality and contribute to sustainable aquaculture management in the GBA. [ABSTRACT FROM AUTHOR]

Geothermal energy has been recognized as an important clean renewable energy. Accurate assessment of geothermal resources is an essential foundation for their development and utilization. The North Jiangsu Basin (NJB), located in the Lower Yangtze Craton, is shaped like a wedge block of an ancient plate boundary and large-scale carbonate thermal reservoirs are developed in the deep NJB. Moreover, the NJB exhibits a high heat flow background because of its extensive extension since the Late Mesozoic. In this study, we used the Monte Carlo method to evaluate the geothermal resources of the main reservoir shallower than 10 km in the NJB. Compared with the volumetric method, the Monte Carlo method takes into account the variation mode and uncertainties of the input parameters. The simulation results show that the geothermal resources of the sandstone thermal reservoir in the shallow NJB are very rich, with capacities of (6.6–12) × 1020 J (mean 8.6 × 1020 J), (5.1–16) × 1020 J (mean 9.1 × 1020 J), and (3.2–11) × 1020 J (mean 6.6 × 1020 J) for the Yancheng, Sanduo and Dai'nan sandstone reservoir, respectively. In addition, the capacity of the geothermal resource of the carbonate thermal reservoir in the deep NJB is far greater than the former, reaching (9.9–15) × 1021 J (mean 12 × 1021 J). The results indicate capacities of a range value of (1.2–1.7) × 1021 J (mean 1.4 × 1022 J) for the whole NJB (<10 km). [ABSTRACT FROM AUTHOR]

Human-caused nitrogen (N) deposition is a global environmental issue that can change community composition, functions, and ecosystem services. N deposition affects plants, soil, and microorganisms regionally and is linked to ecosystem, soil, and climate factors. We examined the effects of six N addition levels (0, 2.34 g, 4.67, 9.34,18.68, and 37.35 g N m−2 yr−1) on aboveground vegetation, surface soil properties, and microbial community. Alterations in microbial communities in response to N addition were monitored using 16S rRNA (16S ribosomal ribonucleic acid, where S donates a sedimentation coefficient) and ITS (internal transcribed spacer) regions for bacterial and fungal communities, respectively. N addition positively affected aboveground vegetation traits, such as biomass and community weighted mean of leaf nitrogen. N addition also limited phosphorus (P) availability and altered the microbial community assembly process from random processes to deterministic processes. The microbial community diversity and composition, however, were not sensitive to N addition. Partial least squares structural equation models showed that the composition of bacterial communities was mainly driven by the composition of plant communities and total nitrogen, while the composition of fungal communities was driven by soil pH and community weighted mean of leaf nitrogen. Taken together, the results of this research improved our understanding of the response of grassland ecosystems to N deposition and provided a theoretical basis for grassland utilization and management under N deposition. [ABSTRACT FROM AUTHOR]

Geothermal energy is an eco-friendly, renewable source of underground thermal energy that exists in the interior of the earth. By tapping into these formations, fluids can be channeled to heat the rock formations above, resulting in a significantly higher land surface temperature (LST). However, LST readings are influenced by various factors such as sun radiation, cyclical variations, and precipitation, which can mask the temperature anomalies caused by geothermal heat. To address these issues and highlight the LST anomalies caused by geothermal heat, this paper proposes a methodology to efficiently and quickly calculate the multi-temporal LST leveraging of the Google Earth Engine (GEE) in the Damxung–Yangbajain basin, Qinghai–Tibet Plateau. This method incorporates terrain correction, altitude correction, and multi-temporal series comparison to extract thermal anomaly signals. The existing geothermal manifestations are used as a benchmark to further refine the methodology. The results indicate that the annual mean winter LST is a sensitive indicator of geothermal anomaly signals. The annual mean winter LST between 2015 and 2020 varied from −14.7 °C to 26.7 °C, with an average of 8.6 °C in the study area. After altitude correction and water body removal, the annual mean winter LST varied from −22.1 °C to 23.3 °C, with an average of 6.2 °C. When combining the distribution of faults with the results of the annual mean winter LST, this study delineated the geothermal potential areas that are located predominantly around the fault zone at the southern foot of the Nyainqentanglha Mountains. Geothermal potential areas exhibited a higher LST, ranging from 12.6 °C to 23.3 °C. These potential areas extend to the northeast, and the thermal anomaly range reaches as high as 19.6%. The geothermal potential area makes up 8.2% of the entire study area. The results demonstrate that the approach successfully identified parts of known geothermal fields and indicates sweet spots for future research. This study highlights that utilizing the multi-temporal winter LST is an efficient and cost-effective method for prospecting geothermal resources in plateau environments. [ABSTRACT FROM AUTHOR]

Photocatalytic degradation technology has developed rapidly in the treatment of organic pollutants due to its high efficiency, mild reaction conditions and easy control. In this paper, a series of heterogeneous photocatalysts, BWZ-en-R (BWZ = [BW11Z(H2O)O39]7−, Z = Zn, Cd, Mn, en = ethylenediamine, R = Merrifield resin), were prepared by using ethanediamine as a linker to immobilize Keggin-type transition elements substituting tungstoborates on Merrifield resin and characterized by Fourier transform infrared spectroscopy, X-ray powder diffraction, scanning electron microscopy and energy-dispersive X-ray spectroscopy. The photocatalytic properties of BWZ-en-R (Z = Zn, Cd, Mn) for the degradation of methyl red (MR) were investigated. The results show that the BWZ-en-R (Z = Zn, Cd, Mn) photocatalysts exhibited high photodegradation ability for MR under the irradiation of ultraviolet light, and were easily separated from the reaction media. The maximum degradation rate (%) of MR (40 mL, 25 μM, pH = 2) reached 96.4% for the BWMn-en-R photocatalyst (40 mg) after being irradiated for 30 min, making this a promising photocatalyst candidate for dye degradation. Moreover, the influences of some factors, such as the Z-substituted elements in the BWZ, the BWZ-en-R dosage and the MR initial concentration, on the photocatalytic degradation rate of MR were also examined. [ABSTRACT FROM AUTHOR]

The photosensitive resins for 3D printing technology have been widely applied throughout the advanced communication field due to their merits of high molding accuracy and fast processing speed. Regardless, they, in particular, should have better mechanical properties, heat resistance, and dielectric properties. Herein, photocurable fluorinated poly (phthalazinone ether) (FSt-FPPE) was utilized as a prepolymer to improve the performance of photosensitive resin. A series of UV-curable inks named FST/DPGs were prepared with FSt-FPPE and acrylic diluents of different mass fractions. The FST/DPGs were cured into films by UV curing and post-treatment. After curing, their properties were characterized in detail. In terms of heat resistance, glass transition temperature (Tg) could reach 233 °C and the 5% thermal decomposition temperature (Td5%) was 371 °C. The tensile strength surprisingly reached 61.5 MPa, and the dielectric constant (Dk) could be significantly reduced to 2.75. Additionally, FST/DPGs were successfully employed in UV-assisted direct writing (DIW) to print 3D objects that benefited from their commendable fluidity and rapid curing speed. A stiff cylinder sample with a smooth surface and distinct pattern was ultimately obtained, indicating their remarkable 3D printing adaptation. Such photosensitive resin for UV-assisted DIW exhibits tremendous potential in the electronic industry. [ABSTRACT FROM AUTHOR]

For the frequent occurrence of harmful algal blooms (HABs) in the Qinhuangdao coastal sea (QCS) of the Bohai Sea in summer, we tested the hypothesis that high-biodiversity HAB species exist in the area, and a series of censuses of HAB species were conducted in the QCS in the summers of 2014–2019. Through morphological identification, we found 100 algae species representing 42 genera in 3 phytoplankton phyla in this study, among which Bacillariophyta was the most dominant phylum. We also found that the population density of Dinoflagellata increased from 2016 to 2019. In total, 59 HAB species were annotated in this study, including 39 of Bacillariophyta, 18 of Dinoflagellata and 2 of Ochrophyta, of which 13 HAB species were reported in the Bohai Sea for the first time, and most HAB species were widely distributed in the QCS in summer. Notably, four dominant HAB species displayed unique temporal and spatial distribution characteristics, while their distribution ranges and population densities increased from 2014 to 2019. The distributions of five environmental factors were different in the QCS, while the temperature, salinity, and dissolved inorganic nitrogen might be the key environmental factors influencing the distribution of dominant HAB species in the summer. In conclusion, this study provides a detailed evaluation of phytoplankton diversity and interannual variation in the QCS. The existence of a high level of biodiversity of algal bloom species suggests the need for long-term monitoring in order to further study and prevent potential HABs. [ABSTRACT FROM AUTHOR]

High oleic acid peanut (HOAP) is extensively embraced in China because of its high nutritional value and enhanced oxidative stability. However, its dissemination has been severely constrained in high altitude and high latitude areas due to chilling stress during sowing, resulting in significant yield loss in these regions. Despite the lack of understanding of the molecular mechanisms underlying low temperature germination (LTG) in HOAP, discovering the quantitative trait loci (QTL) that confer this trait will undoubtedly benefit breeding efforts. In the present study, we identified putative genomic regions and single nucleotide polymorphisms (SNPs) that govern LTG tolerance of HOAP in an F2 population derived from the cross of chilling-tolerant YH65 and chilling-sensitive FL14 using bulk segregant analysis (BSA). Analysis of ΔSNP-index and Euclidean distance (ED) value association pinpointed the overlapped region to a 2.29 Mb interval on chromosome A05. The candidate interval showed that 122 genes were significantly related to response to abiotic stress and plant–pathogen interaction. Furthermore, an SNP site associated with LTG tolerance was discovered. The SNP site was employed as a Kompetitive Allele Specific PCR (KASP) marker and validated in a universal peanut panel. These findings may provide valuable insight into the molecular mechanism underpinning LTG tolerance and facilitate marker-assisted selective breeding in HOAP. [ABSTRACT FROM AUTHOR]

In order to reduce the infrared emissivity to meet the requirements of modern warfare for infrared stealth materials, we prepared the polymers containing Schiff base moieties using polyetheramine and 2,6-pyridinedicarboxaldehyde by solution polycondensation and coordinated with Ni2+, Cu2+, and Sm3+ ions to prepare organic coatings. The structure and the thermal and mechanical properties of the coatings were studied in detail. Meanwhile, the effect of the conductivity change of coordination polymers on infrared emissivity was studied systematically. The results showed the polymer coordinated with Sm3+ ions had the lowest energy band gap, which was 2.99 eV, and the best electrical conductivity of 3.54 × 10−4 S/cm compared with Ni2+ and Cu2+ coordination polymers. The infrared emissivity was the lowest in the 2–22 μm infrared waveband range, which reached 0.58, suggesting the polymers containing Schiff base moieties and their coordination polymers may have a great potential to be applied as infrared stealth materials in military applications. [ABSTRACT FROM AUTHOR]

Immediately and accurately assessing the risk of coal spontaneous combustion and taking targeted action are crucial steps in coal spontaneous combustion prevention and control. A new model, AEM-AHP-LSTM, was proposed to solve the weight calculation problem of multiobjective evaluation in the process of coal spontaneous combustion. Firstly, the key indicators of coal spontaneous combustion were analyzed and used as risk factors to establish an evaluation system. Next, the objective and subjective weights were calculated using AEM and AHP, respectively. The objective and subjective weights were then combined, and TOPSIS was used to calculate the score of the evaluation sample. Finally, the obtained evaluation samples were trained with the BP, RBF, and LSTM model to resolve the problem of model overdependence on historical data and achieve the auto-adapt adjustment of weight with data change. Additionally, data from 15 typical Chinese coal mines were applied to the model. The results indicate that, compared with the BP and RBF neural networks, the LSTM model has higher prediction accuracy, stronger generalization ability, and stronger practicability. The modeling and application findings show that the AEM-AHP-LSTM model was better appropriate for the risk assessment of coal spontaneous combustion. This method can potentially be further applied as reliable approach for the assessment of mine disaster risk. [ABSTRACT FROM AUTHOR]

Wildland fires dramatically affect forest ecosystems, altering the loss of their biodiversity and their sustainability. In addition, they have a strong impact on the global carbon balance and, ultimately, on climate change. This review attempts to provide a comprehensive meta-analysis of studies on remotely sensed methods and data used for estimation of forest burnt area, burn severity, post-fire effects, and forest recovery patterns at the global level by using the PRISMA framework. In the study, we discuss the results of the analysis based on 329 selected papers on the main aspects of the study area published in 48 journals within the past two decades (2000–2020). In the first part of this review, we analyse characteristics of the papers, including journals, spatial extent, geographic distribution, types of remote sensing sensors, ecological zoning, tree species, spectral indices, and accuracy metrics used in the studies. The second part of this review discusses the main tendencies, challenges, and increasing added value of different remote sensing techniques in forest burnt area, burn severity, and post-fire recovery assessments. Finally, it identifies potential opportunities for future research with the use of the new generation of remote sensing systems, classification and cloud performing techniques, and emerging processes platforms for regional and large-scale applications in the field of study. [ABSTRACT FROM AUTHOR]

A fuzzy soft set is a mathematical tool used to deal with vagueness and uncertainty. Parameter reduction is an important issue when applying a fuzzy soft set to handle decision making. However, existing methods neglect newly added parameters and have higher computational complexities. In this paper, we propose a new S-Score table-based parameter-reduction approach for fuzzy soft sets. Compared with two existing methods of parameter reduction for a fuzzy soft set, our method takes newly added parameters into account, which brings about greater flexibility and is beneficial to the extension of fuzzy soft sets and a combination of multiple fuzzy soft sets. Additionally, our method accesses fewer elements from the dataset, which results in lower computation compared with the two existing approaches. The experimental results from two applications show the availability and feasibility of our approach. [ABSTRACT FROM AUTHOR]

The thermal conductivity of a stratum is a key factor to study the deep temperature distribution and the thermal structure of the basin. A huge expense of core sampling from boreholes, especially in offshore areas, makes it expensive to directly test stratum samples. Therefore, the use of well logging (the gamma-ray, the neutron porosity, and the temperature) to estimate the thermal conductivity of the samples obtained from boreholes could be a good alternative. In this study, we measured the thermal conductivity of 72 samples obtained from an offshore area as references. When the stratum is considered to be a shale–sand–fluid model, the thermal conductivity can be calculated based on the mixing models (the geometric mean and the square root mean). The contents of the shale and the sand were derived from the natural gamma-ray logs, and the content of the fluid (porosity) was derived from the neutron porosity logs. The temperature corrections of the thermal conductivity were performed for the solid component and the fluid component separately. By comparing with the measured data, the thermal conductivity predicted based on the square root model showed good consistency. This technique is low-cost and has great potential to be used as an application method to obtain the thermal conductivity for geothermal research. [ABSTRACT FROM AUTHOR]

Simulation of the seismic wave propagation in natural gas hydrate (NGH) is of great importance. To finely portray the propagation of seismic wave in NGH, attenuation properties of the earth's medium which causes reduced amplitude and dispersion need to be considered. The traditional viscoacoustic wave equations described by integer-order derivatives can only nearly describe the seismic attenuation. Differently, the fractional time derivative seismic wave-equation, which was rigorously derived from the Kjartansson's constant-Q model, could be used to accurately describe the attenuation behavior in realistic media. We propose a new fractional finite-difference method, which is more accurate and faster with the short memory length. Numerical experiments are performed to show the feasibility of the proposed simulation scheme for NGH, which will be useful for next stage of seismic imaging of NGH. [ABSTRACT FROM AUTHOR]

Simulation of the seismic wave propagation in natural gas hydrate (NGH) is of great importance. To finely portray the propagation of seismic wave in NGH, attenuation properties of the earth's medium which causes reduced amplitude and dispersion need to be considered. The traditional viscoacoustic wave equations described by integer-order derivatives can only nearly describe the seismic attenuation. Differently, the fractional time derivative seismic wave-equation, which was rigorously derived from the Kjartansson's constant-Q model, could be used to accurately describe the attenuation behavior in realistic media. We propose a new fractional finite-difference method, which is more accurate and faster with the short memory length. Numerical experiments are performed to show the feasibility of the proposed simulation scheme for NGH, which will be useful for next stage of seismic imaging of NGH. [ABSTRACT FROM AUTHOR]

The environment for practical applications of an energy storage system (ESS) in a microgrid system is very harsh, and therefore actual operating conditions become complex and changeable. In addition, the signal of the ESS sampling process contains a great deal of system and measurement noise, the sampled current fluctuates significantly, and also has high frequency. In this case, under such conditions, it is difficult to accurately estimate the state of charge (SOC) of the batteries in the ESS by common estimation methods. Therefore, this study proposes a compound SOC estimation method based on wavelet transform. This algorithm is very suitable for microgrid systems with large current, frequent fluctuating conditions, and high noise interference. The experimental results and engineering data show that the relative error of the method is 0.5%, which is much lower than the extend Kalman filter (EKF) based on wavelet transform. [ABSTRACT FROM AUTHOR]

Current treatment of rheumatoid arthritis (RA) is limited by relative shortage of treatment targets. HM-3 is a novel anti-RA polypeptide consisting of 18 amino acids with integrin αVβ3 and α5β1 as targets. Previous studies confirmed that HM-3 effectively inhibited the synovial angiogenesis and the inflammatory response. However, due to its short half-life, the anti-RA activity was achieved by frequent administration. To extend the half-life of HM-3, we designed a fusion protein with name HM-3-Fc, by combination of modified Fc segment of immunoglobulin 4 (IgG4) with HM-3 polypeptide. In vitro cell experiments demonstrated that HM-3-Fc inhibited the proliferation of splenic lymphocytes and reduced the release of TNF-α from macrophages. The pharmacodynamics studies on mice paw in Collagen-Induced Arthritis (CIA) model demonstrated that HM-3-Fc administered once in 5 days in the 50 and 25 mg/kg groups, or once in 7 days in the 25 mg/kg group showed a better protective effect within two weeks than the positive control adalimumab and HM-3 group. Preliminary pharmacokinetic studies in cynomolgus confirmed that the in vivo half-life of HM-3-Fc was 15.24 h in comparison with 1.32 min that of HM-3, which demonstrated that an Fc fusion can effectively increase the half-life of HM-3 and make it possible for further reduction of subcutaneous injection frequency. Fc-HM-3 is a long-acting active molecule for RA treatment. [ABSTRACT FROM AUTHOR]

The knowledge of hydraulic fracture morphology is significant for the analysis of fracture mechanisms. This paper utilizes passive Ultrasonic Travel-time Tomography (UTT) to characterize the hydraulic fracture. We constructed a velocity model based on X-ray computerized tomography (X-CT) images scanned on a real hydraulically fractured shale column. Then, ray-paths and travel times corresponding to the source-receiver configuration were calculated by curved ray-tracing schemes. Lastly, we performed tomographic inversions using total variation regularization (TVR). The simulation results showed that 3D passive UTT based on TVR is an accurate, efficient, and stable method to reconstruct the velocity structures with fractures, even in the case of sparse ray-coverage or high noise level. Meanwhile, we also verified that the passive UTT is a valid alternative to X-CT in depicting the hydraulic fracturing rock via a proper interpretation method. [ABSTRACT FROM AUTHOR]

Electroless Ni(P)/electroless Pd/immersion Au (ENEPIG) is a common surface finish in electronic packaging, while the Ni(P) layer increases the impedance of solder joints and leads to signal quality degradation in high-frequency circuits. Reducing the thickness of the Ni(P) layer can balance the high impedance and weldability. In this paper, the interfacial reaction process between ultrathin ENEPIG substrates with different Ni layer thicknesses (0.112 and 0.185 μm) and Sn–3.0Ag–0.5Cu (SAC305) solder during reflow and aging was studied. The bonding ability and reliability of solder joints with different surface finishes were evaluated based on solder ball shear test, drop test and temperature cycle test (TCT), and the failure mechanism was analyzed from the perspective of intermetallic compound (IMC) interface growth. The results showed that the Ni–Sn–P layer generated by ultrathin ENEPIG can inhibit the growth of brittle IMC so that the solder joints maintain high shear strength. Ultrathin ENEPIG with a Ni layer thickness of 0.185 μm had no failure cracks under thermal cycling and drop impact, which can meet actual reliability standards. Therefore, ultrathin ENEPIG has broad prospects and important significance in the field of high-frequency chip substrate design and manufacturing. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of unmanned aerial vehicles (UAVs) autonomous tracking moving target with only an airborne camera sensor. We proposed a novel integrated controller framework for this problem based on multi-neural-network modules (MNNMs). In this framework, two neural networks are designed for target perception and guidance control, respectively. The deep learning method and reinforcement learning method are applied to train the integrated controller. The training result demonstrates that the integrated controller can be trained more quickly and efficiently than the end-to-end controller trained by the deep reinforcement learning method. The flight tests with the integrated controller are implemented in simulated and realistic environments, the results show that the integrated controller trained in simulation can easily be transferred to the realistic environment and achieve the UAV tracking randomly moving target, which has a faster motion velocity. The integrated controller based on the MNNMs structure has a better performance on an autonomous tracking target than the control mode that combines with a perception network and a proportional integral derivative controller. [ABSTRACT FROM AUTHOR]

To address the difficulty of separating background materials from similar materials associated with the use of "single-spectral information" for hyperspectral anomaly detection, a fast hyperspectral anomaly detection algorithm based on what we term the "greedy bilateral smoothing and extended multi-attribute profile" (GBSAED) method is proposed to improve detection precision and operation efficiency. This method utilizes "greedy bilateral smoothing" to decompose the low-rank part of a hyperspectral image (HSI) dataset and calculate spectral anomalies. This process improves the operational efficiency. Then, the extended multi-attribute profile is used to extract spatial anomalies and restrict the shape of anomalies. Finally, the two components are combined to limit false alarms and obtain appropriate detection results. This new method considers both spectral and spatial information with an improved structure that ensures operational efficiency. Using five real HSI datasets, this study demonstrates that the GBSAED method is more robust than eight representative algorithms under diverse application scenarios and greatly improves detection precision and operational efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a topology of PV MVDC converter with wide output voltage range for a series DC system and its control strategy. In the series DC system, the PV MVDC converters are input-independent, and their outputs are series-connected. A high-level system voltage is achieved for power collection and transmission. This series boost system is flexible and very suitable for decentralized renewable energy application. A modular topology is present for the MVDC converter to improve its applicability. A reconfigurable topology and its modulation method are proposed for the module of the converter. By regulating of duty cycle of switches, the module can be reconfigured to step-up or step-down mode. The operating principles and theoretical derivations of the reconfigurable topology are discussed in detail in this paper. Multimode control strategy for the converter is designed to adapt to complex operation conditions in a series DC system. With the proposed topology and control strategy, the series-connected PV MVDC converter achieves wide input and output voltage range to adapt to the operating characteristics of the series DC system; 3 kV/80 kW DC–DC module and 20 kV/500 kW PV MVDC converter are developed and operating stably in practice. The operation results are presented in the paper. [ABSTRACT FROM AUTHOR]

Most research about Light and elevated Temperature Induced Degradation (LeTID) is focused on multicrystalline silicon (mc-Si). In this work, the degradation kinetics of Czochralski-grown monocrystalline silicon (Cz-Si) induced by light at an elevated temperature were studied in detail. The lifetime evolutions over time during (1) light soaking (LS), (2) dark annealing–light soaking (DA–LS), and (3) DA–LS cycling experiments were analyzed. Ratios of the capture coefficients for the electrons and holes (k-values) were used to characterize the possible defects responsible for degradation. We found that the behavior of degradation and recovery under light soaking with or without a dark annealing treatment was mostly like boron–oxygen (BO)-related degradation but gave k-values from 19 to 25. In the DA–LS cycling experiment, the max degradation amplitudes hardly changed from the second cycle, and the k-values decreased with an increase in the cycling number. We then analyzed the possible reactions in Cz-Si and discuss the relationship between BO defects and LeTID. [ABSTRACT FROM AUTHOR]

Most research about Light and elevated Temperature Induced Degradation (LeTID) is focused on multicrystalline silicon (mc-Si). In this work, the degradation kinetics of Czochralski-grown monocrystalline silicon (Cz-Si) induced by light at an elevated temperature were studied in detail. The lifetime evolutions over time during (1) light soaking (LS), (2) dark annealing–light soaking (DA–LS), and (3) DA–LS cycling experiments were analyzed. Ratios of the capture coefficients for the electrons and holes (k-values) were used to characterize the possible defects responsible for degradation. We found that the behavior of degradation and recovery under light soaking with or without a dark annealing treatment was mostly like boron–oxygen (BO)-related degradation but gave k-values from 19 to 25. In the DA–LS cycling experiment, the max degradation amplitudes hardly changed from the second cycle, and the k-values decreased with an increase in the cycling number. We then analyzed the possible reactions in Cz-Si and discuss the relationship between BO defects and LeTID. [ABSTRACT FROM AUTHOR]

Most acrylonitrile butadiene styrene (ABS) resin is plagued by an unpleasant odor attributed to the high residual volatile organic compound (VOC) content. This paper primarily aimed to solve the odor issue of ABS resin by effectively reducing the VOC content. To that end, a synthesis of ABS resins was optimized through a supercritical extraction process while evaluating multiple novel chain transfer agents (linear dimer of α-methyl-styrene, methyl 3-mercaptopropionate, and dodecyl mercaptan). ABS resin obtained through a α-methyl-styrene chain transfer agent demonstrated the lowest odor. Moreover, it had the least amount of VOC content which was three times lower than when dodecyl mercaptan was employed. To improve the supercritical extraction process, an orthogonal test was designed to optimize four main process parameters: extrusion temperature, residence time, vacuum degree and extractant dosage. The most optimal conditions were found to be 250 °C extrusion temperature, one minute residence time, vacuum degree of minus 99 KPa, and 1.5% CO2 extractant dosage. [ABSTRACT FROM AUTHOR]

Oridonin (ORI) is a natural active ingredient with strong anticancer activity. But its clinical use is restricted due to its poor water solubility, short half-life, and low bioavailability. The aim of this study is to utilize the metal organic framework material MOF-5 to load ORI in order to improve its release characteristics and bioavailability. Herein, MOF-5 was synthesized by the solvothermal method and direct addition method, and characterized by Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), Fourier Transform Infrared Spectrometer (FTIR), Thermogravimetric Analysis (TG), Brunauer–Emmett–Teller (BET), and Dynamic Light Scattering (DLS), respectively. MOF-5 prepared by the optimal synthesis method was selected for drug-loading and in vitro release experiments. HepG2 cells were model cells. MTT assay, 4′,6-diamidino-2-phenylindole (DAPI) staining and Annexin V/PI assay were used to detect the biological safety of blank carriers and the anticancer activity of drug-loaded materials. The results showed that nano-MOF-5 prepared by the direct addition method had complete structure, uniform size and good biocompatibility, and was suitable as an ORI carrier. The drug loading of ORI@MOF-5 was 52.86% ± 0.59%. The sustained release effect was reliable, and the cumulative release rate was about 87% in 60 h. ORI@MOF-5 had significant cytotoxicity (IC50:22.99 μg/mL) and apoptosis effect on HepG2 cells. ORI@MOF-5 is hopeful to become a new anticancer sustained release preparation. MOF-5 has significant potential as a drug carrier material. [ABSTRACT FROM AUTHOR]