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Context: Understanding the scale-specific effects of different landscape variables on the COVID-19 epidemics is critical for developing the precise and effective prevention and control strategies within urban areas. Objective: Based on the landscape epidemiology framework, we analyzed the scale-specific effects of urban landscape pattern on COVID-19 epidemics in Hangzhou, China. Methods: We collected COVID-19 cases in Hangzhou from 2020‒2022 and combined the datasets of land use and land cover (LULC) and social gathering point (SGP) to quantify the urban landscape pattern. Optimal general linear model with stepwise regression was applied to explore the dominant landscape factors driving the COVID-19 transmission in the city. Furthermore, multi-scale geographically weighted regression illustrated the spatial heterogeneity and scale specificity of these landscape variables’ effects to COVID-19 epidemic. Results: Eight landscape variables of LULC and SGP patterns were identified which explained 68.5% of the variance in spatial risk of COVID-19. Different optimal bandwidths across these variables in MGWR indicated their scale-specific effects. LSI of green space enhanced the spatial risk across the entire region. The effects of landscape contagion, the number of water bodies, LSI of cropland and built-up areas, and the density of commercial houses were detected to vary between urban and suburban areas. The effects of LSI of water bodies and the density of shopping malls were found to vary among different districts. Conclusions: In this study, we firstly discriminated the scale-specific effects of different landscape variables on the COVID-19 epidemic in the urban region. These findings can help to optimize the differentiated zoning prevention and control strategies for COVID-19 in cities and guide policy-making and urban planning at a multi-scale hierarchical perspective to improve public health and urban sustainability. [ABSTRACT FROM AUTHOR]

Context: Understanding the scale-specific effects of different landscape variables on the COVID-19 epidemics is critical for developing the precise and effective prevention and control strategies within urban areas. Objective: Based on the landscape epidemiology framework, we analyzed the scale-specific effects of urban landscape pattern on COVID-19 epidemics in Hangzhou, China. Methods: We collected COVID-19 cases in Hangzhou from 2020‒2022 and combined the datasets of land use and land cover (LULC) and social gathering point (SGP) to quantify the urban landscape pattern. Optimal general linear model with stepwise regression was applied to explore the dominant landscape factors driving the COVID-19 transmission in the city. Furthermore, multi-scale geographically weighted regression illustrated the spatial heterogeneity and scale specificity of these landscape variables’ effects to COVID-19 epidemic. Results: Eight landscape variables of LULC and SGP patterns were identified which explained 68.5% of the variance in spatial risk of COVID-19. Different optimal bandwidths across these variables in MGWR indicated their scale-specific effects. LSI of green space enhanced the spatial risk across the entire region. The effects of landscape contagion, the number of water bodies, LSI of cropland and built-up areas, and the density of commercial houses were detected to vary between urban and suburban areas. The effects of LSI of water bodies and the density of shopping malls were found to vary among different districts. Conclusions: In this study, we firstly discriminated the scale-specific effects of different landscape variables on the COVID-19 epidemic in the urban region. These findings can help to optimize the differentiated zoning prevention and control strategies for COVID-19 in cities and guide policy-making and urban planning at a multi-scale hierarchical perspective to improve public health and urban sustainability. [ABSTRACT FROM AUTHOR]

Maize (Zea mays) is one of the most important crops in the world, but its yield and quality are seriously affected by diverse diseases. Identifying broad-spectrum resistance genes is crucial for developing effective strategies to control the disease in maize. In a genome-wide study in maize, we identified a G-type lectin receptor kinase ZmLecRK1, as a new resistance protein against Pythium aphanidermatum , one of the causal pathogens of stalk rot in maize. Genetic analysis showed that the specific ZmLecRK1 allele can confer resistance to multiple pathogens in maize. The cell death and disease resistance phenotype mediated by the resistant variant of ZmLecRK1 requires the co-receptor ZmBAK1. A naturally occurring A404S variant in the extracellular domain of ZmLecRK1 determines the ZmLecRK1-ZmBAK1 interaction and the formation of ZmLecRK1-related protein complexes. Interestingly, the ZmLecRK1 susceptible variant was found to possess the amino acid S404 that is present in the ancestral variants of ZmLecRK1 and conserved among the majority of grass species, while the resistance variant of ZmLecRK1 with A404 is only present in a few maize inbred lines. Substitution of S by A at position 404 in ZmLecRK1-like proteins of sorghum and rice greatly enhances their ability to induce cell death. Further transcriptomic analysis reveals that ZmLecRK1 likely regulates gene expression related to the pathways in cell wall organization or biogenesis in response to pathogen infection. Taken together, these results suggest that the ZmLecRK1 resistance variant enhances its binding affinity to the co-receptor ZmBAK1, thereby enhancing the formation of active complexes for defense in maize. Our work highlights the biotechnological potential for generating disease-resistant crops by precisely modulating the activity of ZmLecRK1 and its homologs through targeted base editing. The G-type lectin receptor kinase ZmLecRK1 confers multiple disease resistance in maize. A naturally occurring A404S variant in ZmLecRK1 determines the ZmLecRK1-ZmBAK1 interaction for defense. The susceptible variant of ZmLecRK1 with S404 that is conserved among the majority of grass species constitutes the ancestral variants of ZmLecRK1, while the resistance variant with A404 is only present in a few maize inbred lines. [ABSTRACT FROM AUTHOR]

The brittleness index, as the most important parameter for brittleness evaluation, directly affects the compressibility of unconventional reservoirs. Currently, there is no unified calculation method for the brittleness index. This article uses a three-axis rock mechanics servo testing system to test the rock mechanics parameters of shale oil reservoirs in Block Y of the Ordos Basin and uses an X'Pert PRO X-ray diffractometer to test the rock mineral composition. The average volume fraction of quartz minerals, feldspar, and clay minerals in 36 samples of Block Y was tested to be 22.6%, 51.6%, and 18%, respectively. Calcite, dolomite, and pyrite are only present in a few samples. When the confining pressure is 30 MPa, the elastic modulus of the Chang 7 shale in this block is 14.72–34.58 GPa, with an average value of 23.77 GPa; The Poisson's ratio ranges from 0.106 to 0.288, with an average of 0.182; The differential stress ranges from 100.8 to 260.1 MPa, with an average of 164.36 MPa; The peak strain ranges from 0.57 to 1.21, with an average of 0.91. This article compares several mainstream brittle index evaluation methods and identifies the most suitable brittle index evaluation method for Block Y. Using the Jarvie mineral composition method to calculate the brittleness index 1 (MBI), the average value of 36 experimental results is 0.5393. Using the Rickman normalized Young's modulus and Poisson's ratio average value to calculate the brittleness index 2 (EBI), the average value of 36 experimental results is 0.5204. Based on the stress-strain curve and energy method, a model for brittleness index 3 (DBI) is established, and the average value of 36 experimental results is 0.5306. The trend of the brittleness index calculated by the three methods is consistent, indicating the feasibility of the newly established brittleness evaluation method. From the perspectives of mineral composition, rock mechanics parameters, and energy, establishing a brittleness evaluation method for shale oil reservoirs and studying its evaluation method is of great significance for sweet spot prediction in reservoir engineering, providing theoretical support for the selection of fractured intervals in the Chang 7 shale oil reservoir in Block Y of the Ordos Basin. [ABSTRACT FROM AUTHOR]

The evaluation of gas content plays a key role in determining the efficient development of shale reservoirs. To better understand the gas–water miscible competitive adsorption mechanism in the pore-fracture system of water-bearing shale, the water vapor adsorption experiment of dry shale and the methane gas adsorption experiment of water-bearing shale were carried out to compare and analyze the competitive adsorption laws of formation water and methane gas on the shale surface under different temperatures, pressures, and water saturation conditions. Moreover, based on the molecular layer adsorption theory, the gas–liquid–solid interface competitive adsorption model considering the coupling of temperature, pressure, and water saturation was established to predict the actual gas content of water-bearing shale reservoirs. The results show that the main controlling factors affecting the adsorbed gas content of water-bearing shale are specific surface area, temperature, and water content in turn according to weight coefficients; Compared with the gas–solid adsorption model, the gas–liquid–solid competitive adsorption model has higher accuracy in calculation results, which are much closer to the desorption data of shale cores in Jiaoshiba area, Fuling, China. Hence, the competitive adsorption model provides a theoretical foundation for reasonably evaluating the exploitation potential of shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Cancer immunotherapies, which train the natural immune system to specifically kill tumor cells while sparing the healthy cells, have helped revolutionize cancer treatments and demonstrated promising clinical therapeutic benefits for decades. However, the therapeutic outcome of immunotherapies, even for the most successful immune checkpoint blockade (ICB) therapy, remains unsatisfactory in the clinical practice, mainly due to the low immunogenicity of solid tumors and its immunosuppressive tumor microenvironment (TME). Notably, several cancer treatment modalities, including chemotherapy, radiotherapy, and phototherapy, have been revealed to evoke tumor immunogenicity and reverse immunosuppressive TME via inducing immunogenic cell death (ICD) of tumor cells, which synergistically sensitized tumors to ICB therapy. Nanomedicines have been extensively applied to augment ICD-inducing treatment modalities and potentiate ICB therapeutic efficacy therapy due to the opportune convergence of immunotherapy and nanotechnology. Here, we discuss the recent advances in nanomedicine-mediated ICD and its combination with ICB therapy. [ABSTRACT FROM AUTHOR]

Summary: Maize is one of the most important crops for food, cattle feed and energy production. However, maize is frequently attacked by various pathogens and pests, which pose a significant threat to maize yield and quality. Identification of quantitative trait loci and genes for resistance to pests will provide the basis for resistance breeding in maize. Here, a β‐glucosidase ZmBGLU17 was identified as a resistance gene against Pythium aphanidermatum, one of the causal agents of corn stalk rot, by genome‐wide association analysis. Genetic analysis showed that both structural variations at the promoter and a single nucleotide polymorphism at the fifth intron distinguish the two ZmBGLU17 alleles. The causative polymorphism near the GT‐AG splice site activates cryptic alternative splicing and intron retention of ZmBGLU17 mRNA, leading to the downregulation of functional ZmBGLU17 transcripts. ZmBGLU17 localizes in both the extracellular matrix and vacuole and contribute to the accumulation of two defence metabolites lignin and DIMBOA. Silencing of ZmBGLU17 reduces maize resistance against P. aphanidermatum, while overexpression significantly enhances resistance of maize against both the oomycete pathogen P. aphanidermatum and the Asian corn borer Ostrinia furnacalis. Notably, ZmBGLU17 overexpression lines exhibited normal growth and yield phenotype in the field. Taken together, our findings reveal that the apoplastic and vacuolar localized ZmBGLU17 confers resistance to both pathogens and insect pests in maize without a yield penalty, by fine‐tuning the accumulation of lignin and DIMBOA. [ABSTRACT FROM AUTHOR]

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There are still some major issues in the study of fracture network evolution during multi-cluster fracturing in shale reservoirs, such as the simplistic assumption that reservoir rocks are homogeneous and completely brittle, without considering that real rocks are often aggregates of different minerals and may present ductility and heterogeneity. It is important to study the evolution of the multi-cluster fracture network in quasi-brittle shale reservoirs to improve the stimulated reservoir volume (SRV). For this purpose, a 2D, coupled stress-seepage-damage field multi-cluster fracturing numerical model with global cohesive zone was developed in this paper. We conducted triaxial compression acoustic emission experiments using real shale samples and developed a generic trapezoidal TSL softening model that includes triaxial effects. The globally embedded 0-thickness cohesive elements ensures that hydraulic fractures can propagate randomly and thus reflect stress interference among multiple clusters. At the same time, the X-ray diffraction (XRD) experiment was used to determine the mineral content of rock, and the finite element mesh was then processed using the Weibull distribution probability density function to simulate the mineral heterogeneity of rock. In addition, the dynamic distribution of injection fluid flow during multi-cluster fracturing is implemented based on the Bernoulli equation. The cohesive parameters were validated by Brazilian splitting test, and the model was then used to parametrically study the evolution law of the fracture network and the variation characteristics of the flow rate into each cluster. The results show that using conventional bilinear TSL will result in a larger SRV than trapezoidal TSL, and reservoir heterogeneity may further exaggerate the drainage area when using bilinear TSL model. In addition, compared with a homogeneous isotropic reservoir, a highly heterogeneous reservoir has a more balanced flow rate into each cluster during multi-cluster fracturing, and this can significantly increase the complexity of fracture network. By increasing the number of clusters, it is possible to alleviate the stress interference on some internal clusters, which may also promote frequent fracture merging around the wellbore. Compared with increasing the number of clusters, reducing the perforation diameter can better compensate for the stress interference suffered by internal clusters, and make the flow rate into each cluster more balanced, thus improving the SRV. Highlights: The trapezoidal traction separation law can describe the damage softening behavior of quasi-brittle reservoirs. The fracture network formed using the bilinear traction separation law is more complex than the trapezoidal traction separation law. Heterogeneous reservoirs may form a more complex fracture network than homogeneous reservoirs during multi-cluster hydraulic fracturing. Uniformly increasing the number of clusters with small spacing has a limited effect on the uniformity of the flow rate into each cluster. Reducing the perforation diameter is an effective method to balance the flow rate into each cluster by weakening the effect of stress interference. [ABSTRACT FROM AUTHOR]

Face reenactment aims to transfer the upper body motions from a driving actor to a target actor. Current methods either cannot transfer motion adequately or cannot synthesize high-quality video. This paper proposes a novel face reenactment method via unsupervised motion transfer and deep learning-based correction. Firstly, the motion of the driving actor is largely transferred to the target via an unsupervised motion model and a rough synthetic target video can be obtained. Then, a generative neural network with spatial-temporal structure is designed to correct the rough video to a realistic and smooth video. To synthesize smooth and detailed video, 3D convolution and attention mechanism are introduced into the network to process temporal information and guide the video correction. To avoid synthesizing background with artifacts, the background information is embedded into the network as fixed parameters. To improve the realism of the teeth, a mouth enhancement loss is designed. The network is trained in an adversarial manner, ensuring the realism of the generated images. Experiments show that this method can synthesize high-quality target videos and the performance is better than the current state-of-the-art face reenactment methods. [ABSTRACT FROM AUTHOR]

The overexpressed glutathione peroxidase4 (GPX4) and insufficient H2O2 in tumor cells weaken ferroptosis therapy and the elicited anticancer immune response. Herein, a rigid metal‐polyphenol shell decorated nanodevice ssPPELap@Fe‐TA is constructed to successfully overcome the drawbacks of ferroptosis therapy. The ssPPELap@Fe‐TA consists of a rigid Fe‐TA network‐based shell and disulfide‐containing polyphosphoester (ssPPE) core with β‐lapachone loading. The rigid Fe‐TA network‐based shell of ssPPELap@Fe‐TA enables its efficient internalization by tumor cell and then disintegrates in the acidic endosome/lysosome to initiate Fe3+/Fe2+ conversion‐driven ferroptosis. The ssPPE core will deplete glutathione (GSH) via the disulfide‐thiol exchange reaction to inactivate GPX4, and also trigger the release of β‐lapachone to significantly increase intracellular H2O2 and then promote Fe3+‐mediated Fenton reaction, eventually achieving strong inhibition of tumor progression. Moreover, ssPPELap@Fe‐TA elicites a robust systemic antitumor immune response by promoting dendritic cells (DCs) maturation and T cell infiltration, and synergizes with anti‐PD‐L1 antibody (a‐PD‐L1) to strikingly suppress 4T1 tumor growth and lung metastasis. [ABSTRACT FROM AUTHOR]

A radial well has a unique wellbore configuration. Fracture propagation in radial well deflagration fracturing is studied rarely. The mechanism of interaction between deflagration fractures, natural fractures, and micro-fractures is still unknown. Based on continuum mechanics, damage mechanics, and variational principles, a numerical model of fracture propagation in deflagration fracturing is established with the Hamilton principle and phase-field fracture theory. The effects of horizontal principal stress difference, natural fracture distribution, and micro-fractures around the wellbore on fracture propagation in deflagration fracturing are studied. First, when no natural fractures are developed around the radial well, fractures are initiated at both ends of the radial well. Second, when there are three natural fractures around the radial well, the created fractures have the morphology of shorter fractures in the middle and longer fractures on both sides under stress interference mechanisms. Third, a larger density of natural fractures causes obvious stress superposition, changes the initiation points of radial wells and fracture morphology, and increases fracture width and reservoir stimulation volume. Fourth, as the micro-fractures increase, their interference and induction effects on deflagration fractures are enhanced gradually, and the deflection angle of fractures increases by 38.7%. The study provides a reference for optimizing deflagration fracturing in a radial well. [ABSTRACT FROM AUTHOR]

After multi-stage volume hydraulic fracturing in a shale oil reservoir, massive amounts of water can be imbibed into the matrix pores. One of the key imbibition characteristics of a shale reservoir is the imbibition water and its height distribution. Based on high pressure mercury injection (HPMI) experiments and nuclear magnetic resonance (NMR) analyses, this study quantitatively evaluated the pore-size distribution of Chang 7 continental shale oil reservoirs in Yanchang Formation, Ordos Basin. The pores could be divided into three types as micropores (≤0.1 μm), mesopores (0.1–1.0 μm), and macropores (>1.0 μm), while the volume of micropores and mesopores accounted for more than 90%. This demonstrated that there were strong heterogeneity and micro–nano characteristics. According to the spontaneous imbibition (SI) experiments, the cumulative proportion of imbibition water content was the largest in micropores, exceeding 43%, followed by mesopores around 30%, and that of macropores was the lowest, and basically less than 20%. The negative values of stage water content in the macropore or mesopore indicated that these pores became a water supply channel for other dominant imbibition pores. Additionally, combining the fractal theory with the NMR T2 spectrum, the relative imbibition water and actual height were calculated in different pores, while the height distribution varied with cores and shale oil. The shorter the core, the higher was the relative height, while the radius of macropores filled with imbibition water was reduced. This indicates that the height distribution was affected by the pore structure, oil viscosity, and core length. [ABSTRACT FROM AUTHOR]

There are still some problems in the study of hydraulic fracture (HF) network evolution in cemented naturally fractured reservoirs, such as microseismic mapping showing exaggerated stimulated reservoir volume in some cases. In addition, the dominant role of natural fracture (NF) cementation strength, injection rate, in situ stress difference, NF distribution, and fracture initiation sequence of perforations in synthetically influencing fracture network formation needs to be further studied. For this purpose, a three‐dimensional matrix hexahedral element global coupled 0‐thickness cohesive element hydraulic fracturing model was developed. Results show that each interaction between HF and NF causes HF diameter shrinkage, which increases the propagation pressure of HF. When the cementation strength of the NF is low, the HF tends to deviate toward the tip of the NF to form a complex fracture network. Increasing the injection rate and the number of NFs can significantly enhance the complexity of the HF network, but does not change the HF and NF interaction pattern. The in situ stress differences dominate the morphology of the HF network when the cementation strength of NFs is constant. The stress interference of multiple fractures under segmented fracturing may form "S"‐shaped HFs, and the HFs are difficult to maintain a symmetrical morphology in the direction of the well axis. In addition, some NFs in inactivated damaged zones have developed a certain width geometrically due to the induced effect of HF, but they are still isolated by the low permeability matrix and might only generate some microseismic events. [ABSTRACT FROM AUTHOR]

The technology of radial-well-assisted hydraulic fracturing is applied in the stimulation of low-permeability hydrocarbon reservoirs where commercial production cannot be achieved by the conventional fracturing method. Here, a study on the reservoir stimulation effect and the fracture propagation pattern of radial-well-assisted deflagration fracturing was carried out. Based on smooth particle hydrodynamics (SPH), rock mechanics theory, and finite element theory, a numerical model of radial-well-assisted deflagration fracturing was established by integrating the JWL state equation. Research on the effects of the deflagration position, radial well azimuth and horizontal principal stress difference on the fracture propagation was carried out. The results show that the deflagration position, radial well azimuth and horizontal principal stress difference have significant effects on the fracture area in deflagration fracturing. The closer distance from the deflagration position is, the larger the radial well azimuth and the smaller the horizontal stress difference are, leading to a larger fracture area, which is conducive to reservoir stimulation. During fracturing, both shear fractures and tensile fractures are formed. The formation and conversion of shear fractures and tensile fractures are related to the deflagration position, radial well azimuth, horizontal principal stress difference, etc. [ABSTRACT FROM AUTHOR]

Atherosclerosis (AS) is a chronic inflammatory disease characterized by hardening and narrowing of arteries. AS leads to a number of arteriosclerotic vascular diseases including cardiovascular diseases, cerebrovascular disease and peripheral artery disease, which pose a big threat to human health. Phytochemicals are a variety of intermediate or terminal low molecular weight secondary metabolites produced during plant energy metabolism. Phytochemicals from plant foods (vegetables, fruits, whole grains) and traditional herb plants have been shown to exhibit multiple bioactivities which are beneficial for prevention and treatment against AS. Many types of phytochemicals including polyphenols, saponins, carotenoids, terpenoids, organic sulfur compounds, phytoestrogens, phytic acids and plant sterols have already been identified, among which saponins are a family of glycosidic compounds consisting of a hydrophobic aglycone (sapogenin) linked to hydrophilic sugar moieties. In recent years, studies have shown that saponins exhibit a number of biological activities such as anti-inflammation, anti-oxidation, cholesterol-lowering, immunomodulation, anti-platelet aggregation, etc., which are helpful in the prevention and treatment of AS. This review aims to summarize the recent advances in the anti-atherosclerotic bioactivities of saponins such as ginsenoside, soyasaponin, astra-galoside, glycyrrhizin, gypenoside, dioscin, saikosaponin, etc. [ABSTRACT FROM AUTHOR]

Bearings, as the key mechanical components of rotary machinery, are widely used in modern aerospace equipment, such as helicopters and aero-engines. Intelligent fault diagnosis, as the main function of prognostic health management systems, plays a critical role in maintaining equipment safety in aerospace applications. Recently, data-driven intelligent diagnosis approaches have achieved great success due to the availability of large-scale, high-quality, and complete labeled data. However, in a real application, labeled data is often scarce because it requires manual labeling, which is time-consuming and labor-intensive. Meanwhile, health monitoring data are usually scattered in different regions or equipment in the form of data islands. Traditional fault diagnosis techniques fail to gather enough data for model training due to data security, economic conflict, relative laws, and other reasons. Therefore, it is a challenge to effectively combine the data advantages of different equipment to develop an intelligent diagnosis model with better performance. To address this issue, a novel clustering federated learning (CFL) method with a self-attention mechanism is proposed for bearing fault diagnosis. Firstly, a deep neural network with a self-attention mechanism is developed in a convolutional pipe for feature extraction, which can capture local and global information from raw input. Then, the CFL is further constructed to gather the data from different equipment with similar data distribution in an unsupervised manner. Finally, the CFL-based diagnosis model can be well trained by fully utilizing the distributed data, while ensuring data privacy safety. Experiments are carried out with three different bearing datasets in aerospace applications. The effectiveness and the superiority of the proposed method have been validated compared with other popular fault diagnosis schemes. [ABSTRACT FROM AUTHOR]

Recently, multiple studies have shown that chronic inflammation disturbs cholesterol homeostasis and promotes its accumulation in the liver. The underlying molecular mechanism remains to be revealed. The relationship between the toll-like receptor 4 (TLR4) inflammatory signaling pathway and cholesterol accumulation was investigated in HepG2 cells treated with lipopolysaccharide (LPS) or palmitic acid (PA) for different lengths of time. In addition, the effects of pretreatment with 20μmol/L ST2825 (MyD88 inhibitor) were also studied in LPS- or PA-treated HepG2 cells and myeloid differentiation factor 88 (MyD88)-overexpressing HEK293T cells. The intracellular total and free cholesterol levels were measured using a commercial kit and filipin staining, respectively. The expression levels of sterol regulatory element-binding protein-2 (SREBP-2) and components in the TLR4 signaling pathway were determined using Western blotting. The treatments with LPS for 12 h and with PA for 24 h significantly increased the contents of intracellular total and free cholesterol, as well as the expression levels of SREBP-2 and components in the TLR4 signaling pathway. The inhibition of MyD88 by ST2825 significantly decreased the cholesterol content and the expression levels of SREBP-2 and components of the TLR4/MyD88/NF-κB pathway in HepG2 cells, as well as MyD88-overexpressing HEK293T cells. These results indicated that LPS and PA treatments increase SREBP-2-mediated cholesterol accumulation via the activation of the TLR4/MyD88/NF-κB signaling pathway in HepG2 cells. [ABSTRACT FROM AUTHOR]

The injection of high‐pressure fluid and the propagation of hydraulic fractures (HF) can impact the stress state of natural fractures (NF) in shale reservoirs, which will lead to shear slip in NF that are in a critical stress state. However, the NF mechanics response mechanism during hydraulic fracture (HF) approximation has not been well investigated, especially under triaxial stress and injection conditions. This work focuses on the NF shear‐slip characteristics during HF through experimental investigation. Each shale sample contains a single rough NF in the tests, and high‐pressure fluid is injected through a pre‐drilled hole at the top of the sample. Meanwhile, the deformation (axial deformation and radial deformation), axial stress, and injection pressure of the sample during the experiment were recorded in real‐time. The experimental results show that the NF will initiate in tension or shear mode during the HF approaching process, and the fracture will produce shear slip in both initiation modes. In addition, the deviator stress, confining pressure, hydraulic fracture approach angle, and fracture surface roughness all affect the degree of shear slip in natural fractures (NF). The results further reveal the mechanical response mechanism of NF during hydraulic fracturing and provide a reference for optimizing hydraulic fracturing process measures. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) classification is a small-sample-size problem due to the expensive cost of labeling. As a novel approach to this problem, cross-scene HSI classification has become a hot research topic in recent years. In cross-scene HSI classification, the scene containing enough labeled samples (called source scene) is used to benefit the classification in another scene containing a small number of training samples (called target scene). Transfer learning is a typical solution for cross-scene classification. However, many transfer learning algorithms assume an identical feature space for source and target scenes, which violates the fact that source and target scenes often lie in different feature spaces with various dimensions due to different HSI sensors. Aiming at the different feature spaces between the two scenes, we propose an end-to-end heterogeneous deep transfer learning algorithm, namely, cross-domain variational autoencoder (CDVAE). This algorithm is mainly composed of two key parts: 1) the features of the two scenes are embedded into the shared feature subspace through the two-stream variational autoencoder (VAE) to ensure that the output feature dimensions of the two scenes are identical and 2) graph regularization is used to establish the manifold constraints between source and target scenes in the shared subspace, so as to align the feature spaces. Experiments on two different cross-scene HSI datasets have proved the superior performance of the proposed CDVAE algorithm. [ABSTRACT FROM AUTHOR]

Coordination of networked microgrids (MGs) offers a promising solution to utilize distributed resources flexibilities and accommodate renewable energy. This paper studies real-time coordination of distribution system operation (DSO) and MGs considering multivariate uncertainty. Current researches suffer from inadaptability to dynamic system uncertainty, extensive iterations, and dependence on prediction. To fill these gaps, A novel multi-agent learning based stochastic dynamic programming (MASDP) is proposed to obtain the optimal policy for entities. Specifically, transactive energy control (TEC) mechanism, which requires only market-based information interactions, is employed to facilitate coordination between MG and DSO. A data-driven offline self-learning is proposed for entities to learn how to manage resources in response to system uncertainty. After sufficient offline learning, online operation of MASDP can be run in both non-iterative and iterative manners, by which near-optimal/optimal real-time solutions of DSO and MGs can be given sequentially and distributedly. Numerical comparisons with state-of-art policies and TEC algorithms verify the optimality, efficiency, adaptability, and scalability of MASDP. [ABSTRACT FROM AUTHOR]

The injection production ratio of reservoir is influenced by formation pressure, water cut, accumulated water oil ratio, and other factors, and the traditional calculation process is complex, the application scope of traditional methods is different, and the formula conditions are also different, so these methods have their own limitations. To solve the problem, a new injection production ratio calculation model is proposed by using the new water drive type curve, which is widely used in reservoir engineering. Compared with the traditional calculation methods, the new model requires less production data, has a wide range of application and simple calculation process, and only the water cut value is needed at a certain time in the future to estimate the reasonable injection production ratio. Two examples show that the estimated injection production ratios are close to the actual values; the average errors are 7.07% and 4.9%, respectively, which meet the requirements of engineering calculation; and the injection production ratio decreases with the increment of water cut. The new model is useful to determine the injection allocation for different water cut in the future, and provides guidance for the future development of the oilfield. [ABSTRACT FROM AUTHOR]

In recent years, deep learning methods, especially convolutional neural network (CNN), have received extensive attentions and applications in fault diagnosis. However, recent studies have shown that the shift-invariance of CNN is not good enough, resulting in fragile feature extraction and sharp reduction in model performance when the shift occurs in the input. To improve the shift-invariance of CNN, considering the periodic characteristics of vibration signals, a multiscale CNN with feature alignment (MSCNN-FA) is proposed for bearing fault diagnosis under different working conditions. First, by analyzing the operating principles of the convolutional layer and pooling layer, a feature alignment module including single-stride convolution layer, adaptive max-pooling layer, and global average pooling layer is designed to obtain aligned features. Next, to extract shift-invariant robust features from vibration signals, a multiscale convolution strategy is utilized, and a feature-aligned multiscale feature extractor is constructed. Finally, a classifier composed of fully connected (FC) layers is constructed for bearing fault diagnosis. The effectiveness of the method is verified by a rolling bearing experiment, which outperforms other related existing CNN-based methods in terms of diagnosis accuracy and feature robustness. [ABSTRACT FROM AUTHOR]

According to the relationship between permeability and porosity of geotechnical materials, a finite element model representing pore and solid particles is generated randomly according to the porosity of a given finite element calculation model. According to Darcy's law of flow distribution and steady seepage in the finite element random simulation section, the equivalent permeability coefficients at different porosities are calculated, and the relationship between the equivalent permeability coefficient and the porosity of rock and soil is studied. The results show that the equivalent permeability coefficient is proportional to the porosity with the same pore size. In order to study the seepage characteristics of structural planes of nonmaterial geotechnical materials in different strata contact zones, the formulas for calculating the deformation parameters and permeability coefficients of heterogeneous rock masses with single nonmaterial geotechnical materials are deduced theoretically, and the correctness and applicability of the formulas are verified by experiments. The rock mass sample selected in this paper is granite, which is simulated and analyzed by sandstone in the experiment. The results show that the permeability coefficients of coarse sandstone, fine sandstone, and heterogeneous rock mass are different under the same water pressure and confining pressure. This shows that the lithology on both sides of the nonmaterial geotechnical material surface has a significant influence on the permeability of the nonmaterial geotechnical material rock mass; the permeability coefficient of the nonmaterial geotechnical material rock mass decreases with the increase of confining pressure, the numerical change is limited to a certain confining pressure range, and the permeability coefficient tends to be stable when the confining pressure reaches a certain value. Comparing the theoretical calculation value of permeability coefficient of rock mass with the experimental result, it is found that the two values are in good agreement, which indicates the correctness and applicability of the theoretical calculation formula of permeability coefficient of rock mass of single intangible geotechnical material. [ABSTRACT FROM AUTHOR]

Viscosity is an important index to evaluate gas flowability. In this paper, a double-porosity model considering the effect of pressure on gas viscosity was established to study shale gas percolation through reservoir pressure, gas velocity, and bottom hole flowing pressure. The experimental results show that when pressure affects gas viscosity, shale gas viscosity decreases, which increases the percolation velocity and pressure drop velocity of the free state shale gas in matrix and fracture systems. And it is conducive to the desorption of adsorbed shale gas and effectively supplemented the bottom hole flowing pressure with the pressure wave propagation range and velocity increasing, so that the rate of pressure drop at the bottom of the well slows down, which makes the time that bottom hole flowing pressure reaches stability shortened. Therefore, the gas viscosity should be fully considered when studying the reservoir gas percolation. [ABSTRACT FROM AUTHOR]

This article introduces a novel method for asset and option trading in a binomial scenario. This method uses nonparametric predictive inference (NPI), a statistical methodology within imprecise probability theory. Instead of inducing a single probability distribution from the existing observations, the imprecise method used here induces a set of probability distributions. Based on the induced imprecise probability, one could form a set of conservative trading strategies for assets and options. By integrating NPI imprecise probability and expectation with the classical financial binomial tree model, two rational decision routes for asset trading and for European option trading are suggested. The performances of these trading routes are investigated by computer simulations. The simulation results indicate that the NPI based trading routes presented in this article have good predictive properties. [ABSTRACT FROM AUTHOR]

This paper proposes a novel multi-searcher optimization (MSO) algorithm for the optimal energy dispatch (OED) of combined heat and power-thermal-wind-photovoltaic systems. The available power of wind turbine (WT) units and photovoltaic (PV) units is approximated with the probability density functions of wind speed and solar irradiance, respectively. The chaos theory is used to implement a wide global search, which can effectively avoid a low-quality local optimum for OED. Besides, a double-layer searcher is designed to guarantee fast convergence to a high-quality optimal solution. Finally, three benchmark functions and an energy system with 27 units are used for testing the performance of the MSO compared with nine other frequently used heuristic algorithms. The simulation results demonstrate that the proposed technique not only can solve the highly nonlinear, non-smooth, and non-convex OED problem of an energy system, but can also achieve a superior performance for the convergence speed and the optimum quality. [ABSTRACT FROM AUTHOR]

The geologic sequestration of carbon dioxide by coal beds leads to the swelling deformation of coal. In order to investigate the swelling deformation characteristics at the microscopic scale, X-ray computed tomography (CT) scanning technology was used. X-ray CT scanning technology detects the internal structure, deformation, and porosity of coal at different gas pressures. Results show that swelling deformation is nonuniform, which is caused by the heterogeneity of the coal structure. Through quantitative measurement of the distance between fractures and pseudocolor processing of CT images, we observed that fractures gradually close with the increase of adsorption pressure. As adsorption pressure increases, the porosity of coal decreases, and the density of coal increases. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of acupuncture on Parkinson's disease (PD) patients with tremor and its potential neuromechanism by functional magnetic resonance imaging (fMRI). Methods: Forty-one PD patients with tremor were randomly assigned to true acupuncture group (TAG, n = 14), sham acupuncture group (SAG, n = 14) and waiting group (WG, n = 13). All patients received levodopa for 12 weeks. Patients in TAG were acupunctured on DU20, GB20, and the Chorea-Tremor Controlled Zone, and patients in SAG accepted sham acupuncture, while patients in WG received no acupuncture treatment until 12 weeks after the course was ended. The UPDRS II and III subscales, and fMRI scans of the patients' brains were obtained before and after the treatment course. UPDRS II and III scores were analyzed by SPSS, while the degree centrality (DC), regional homogeneity (ReHo) and amplitude low-frequency fluctuation (ALFF) were determined by REST. Results: Acupuncture improved the UPDRS II and III scores in PD patients with tremor without placebo effect, only in tremor score. Acupuncture had specific effects on the cerebrocerebellar pathways as shown by the decreased DC and ReHo and increased ALFF values, and nonspecific effects on the spinocerebellar pathways as shown by the increased ReHo and ALFF values (P < 0.05, AlphaSim corrected). Increased ReHo values were observed within the thalamus and motor cortex of the PD patients (P < 0.05, AlphaSim corrected). In addition, the default mode network (DMN), visual areas and insula were activated by the acupuncture with increased DC, ReHo and/or ALFF, while the prefrontal cortex (PFC) presented a significant decrease in ReHo and ALFF values after acupuncture (P < 0.05, AlphaSim corrected). Conclusions: The cerebellum, thalamus and motor cortex, which are connected to the cerebello-thalamo-cortical (CTC) circuit, were modulated by the acupuncture stimulation to alleviate the PD tremor. The regulation of neural activity within the cognitive brain regions (the DMN, visual areas, insula and PFC) together with CTC circuit may contributes to enhancing movement and improving patients' daily life activities. [ABSTRACT FROM AUTHOR]

Background: Micro-RNAs (miRNAs) play important roles in the regulation of immune response and inflammation. The purpose of this study was to investigate the association between three single nucleotide polymorphisms (SNPs) ( mir-146a rs2910164, let-7a-2 rs1143770, miR-196a2 rs11614913) and susceptibility to and severity of childhood immunoglobulin A (IgA) nephropathy (IgAN). Methods: We genotyped three miRNA SNPs in two independent Han Chinese populations composed of 158 patients and 265 controls (discovery set), and 246 patients and 446 controls (validation set), respectively. Results: We found that rs2910164 was significantly associated with IgAN in the discovery but not the validation set. Combined analysis revealed that rs2910164 CC and CG genotypes were associated with increased risk of IgAN compared with the GG genotype [adjusted odds ratios (OR) = 1.684, 95 % confidence interval (CI)1.190-2.384, P = 0.003; adjusted OR = 1.472, 95 % CI 1.079-2.007, P = 0.015, respectively). We also found that the frequency of the rs2910164 CC genotype was significantly higher in patients with Haas grade III-V than in those with Haas grade I-II for all study populations ( P < 0.05). The expression of miR-146a in normal renal tissues with CC genotype was lower than in those with a G allele ( P = 0.038). Conclusions: These results indicated that rs2910164 may affect the susceptibility and severity of pediatric IgAN. Further studies are needed to validate these findings. [ABSTRACT FROM AUTHOR]

Rheological properties of wormlike micelle solutions of zwitterionic surfactant were studied as a function of cosurfactant, organic salt, and solvents at high temperature. Addition of cosurfactant and organic salt increases the viscoelasticity at high temperature. Addition of isopropanol as solvent shifts the maximum viscosity of wormlike micelle to lower temperature. Addition of propylene glycol as solvent has less effect on the viscoelasticity of the wormlike micelle solution. An analysis based on the polarity of the solvent and phase behavior in concentrate region explains the effect of solvents on worm-like micelle. [ABSTRACT FROM PUBLISHER]

β-carotene, a member of the carotenoid family, is a provitamin A, and can be converted into vitamin A (retinol), which plays essential roles in the regulation of physiological functions in animal bodies. Microalgae synthesize a variety of carotenoids including β-carotene and are a rich source of natural β-carotene. This has attracted the attention of researchers in academia and the biotech industry. Methods to enrich or purify β-carotene from microalgae have been investigated, and experiments to understand the biological functions of microalgae products containing β-carotene have been conducted. To better understand the use of microalgae to produce β-carotene and other carotenoids, we have searched PubMed in August 2021 for the recent studies that are focused on microalgae carotenoid content, the extraction methods to produce β-carotene from microalgae, and the bioactivities of β-carotene from microalgae. Articles published in peer-reviewed scientific journals were identified, screened, and summarized here. So far, various types and amounts of carotenoids have been identified and extracted in different types of microalgae. Diverse methods have been developed overtime to extract β-carotene efficiently and practically from microalgae for mass production. It appears that methods have been developed to simplify the steps and extract β-carotene directly and efficiently. Multiple studies have shown that extracts or whole organism of microalgae containing β-carotene have activities to promote lifespan in lab animals and reduce oxidative stress in culture cells, etc. Nevertheless, more studies are warranted to study the health benefits and functional mechanisms of β-carotene in these microalgae extracts, which may benefit human and animal health in the future. [ABSTRACT FROM AUTHOR]

The Chang 7 continental shale oil reservoir is tight. The recovery factor is extremely low, the remaining oil is very high, and injecting water to improve oil recovery effectiveness is too hard. Therefore, in this paper, physical simulation experiments of CO2 huff-n-puff shale oil and NMR tests were conducted to study the cycle numbers and permeability on the recovery degree, as well as the characteristics of shale oil mobilization and the remaining oil micro distribution. The results showed that the cumulative oil recovery factors (ORFs) gradually increased in the natural logarithmic form, the single cycle ORFs decreased rapidly in exponential form with the huff-n-puff cycle number, and the biggest economic cycle numbers were between approximately 3 and 5. Furthermore, the higher the permeability, the higher the ORF, but the difference of ORF decreased between the two experimental samples with the cycles. In addition, the gap of production and recovery degree was large between the different scale pores, the ORF of macropores was 6–8 times that of micropores, and the final remaining oil was mainly distributed in the micropores, accounting for 82.29% of the total amount; meanwhile, the macropores comprised less than 0.5%. In the process of huff-n-puff, CO2 flowed into macropores, mesopores, and smallpores under the pressure differential effect, but a small amount of CO2 slowly diffused into micropores, resulting in the ORF of the former with more free oil being higher and the ORF of micropores with more adsorbed oil being lower. Therefore, promoting a better contact and reaction between CO2 and shale oil of micropores is one of the key ways to effectively develop the Chang 7 continental shale oil and enhance oil recovery. [ABSTRACT FROM AUTHOR]

Background: Previous studies indicate that soyasaponins may reduce inflammation via modulating toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88) signaling. However, its underlying mechanisms are still not fully understood. Methods: Lipopolysaccharide (LPS)-challenged inflamed male ICR mice were intervened by intragastrical administration with 10 and 20 μmol/kg·BW of soyasaponin A1, A2 or I for 8 weeks. The serum inflammatory markers were determined by commercial kits and the expression of molecules in TLR4/MyD88 signaling pathway in liver by real-time PCR and western blotting. The recruitments of TLR4 and MyD88 into lipid rafts of live tissue lysates were detected by sucrose gradient ultracentrifugation and western blotting. LPS-stimulated RAW264.7 macrophages were treated with 10, 20 and 40 μmol/L of soyasaponin A1, A2 or I for 2 h. MyD88-overexpressed HEK293T cells were treated with 20 and 40 μmol/L of soyasaponins (A1, A2 or I) or 20 μmol/L of ST2825 (a MyD88 inhibitor) for 6 h. The expression of molecules in TLR4/MyD88 signaling pathway were determined by western blotting. Data were analyzed by using one way analysis of variance or t-test by SPSS 20.0 statistical software. Results: Soyasaponins A1, A2 or I significantly reduced the levels of tumor necrosis factor alpha (TNFα), interleukin (IL)-6 and nitric oxide (NO) in serum (p < 0.05), and decreased the mRNA levels of TNFα, IL-6, IL-1β, cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS) (p < 0.05), the protein levels of myeloid differentiation protein 2 (MD-2), TLR4, MyD88, toll-interleukin1 receptor domain containing adaptor protein (TIRAP), phosphorylated interleukin-1 receptor-associated kinase 4 (p-IRAK-4), phosphorylated interleukin-1 receptor-associated kinase 1 (p-IRAK-1) and TNF receptor associated factor 6 (TRAF6) (p < 0.05), and the recruitments of TLR4 and MyD88 into lipid rafts in liver (p < 0.05). In LPS-stimulated macrophages, soyasaponins A2 or I significantly decreased MyD88 (p < 0.05), soyasaponins A1, A2 or I reduced p-IRAK-4 and p-IRAK-1 (p < 0.05), and soyasaponin I decreased TRAF6 (p < 0.05). In MyD88-overexpressed HEK293T cells, soyasaponins (A1, A2 or I) and ST2825 significantly decreased MyD88 and TRAF6 (p < 0.05). Conclusion: Soyasaponins can reduce inflammation by downregulating MyD88 expression and suppressing the recruitments of TLR4 and MyD88 into lipid rafts. This study provides novel understanding about the anti-inflammatory mechanism of soyasaponins. [ABSTRACT FROM AUTHOR]

Polymer microspheres (PMs) are used as a new material to recover residual oil left in unswept oil areas after secondary recovery methods. The fact that the PMs plug the macropores causes the flow direction of the injection fluid to be transferred from macropores to micropores. In order to investigate the plugging and profile control mechanisms of PMs in reservoirs, four kinds of PMs with different particle sizes and four kinds of artificial cores with different permeability were selected for flooding tests, including plugging experiments and profile control experiments. The pore throat size distribution of cores was characterized by nuclear magnetic resonance (NMR) technology. The particle size distribution of PMs used in the experiment was characterized using a laser particle size analyzer. The results showed that there are six matching relationships existing simultaneously between pore throats and PMs based on theoretical analysis, which are completely plugging, single plugging, bridge plugging, smooth passing, deposition, and deformable passing. A key principle for optimizing PMs in profile control is that the particle size of the selected PMs can enter the high permeability layer well, but it is difficult for it to enter the low permeability layer. The results of this paper provide a theoretical basis for the optimal particle size of PMs during the oil field profile control process. [ABSTRACT FROM AUTHOR]

Spontaneous imbibition of water into tight oil reservoirs is considered an effective way to improve tight oil recovery. We have combined testing techniques such as nuclear magnetic resonance, mercury injection capillary pressure, and magnetic resonance imaging to reveal the distribution characteristics of oil and water during the spontaneous imbibition process of tight sandstone reservoir. The experimental results were used to describe the dynamic process of oil–water distribution at the microscopic scale. The water phase is absorbed into the core sample by micropores and mesopores under capillary forces that dry away the original oil phase into the hydraulically connected macropores. The oil phase entering the macropores will drive away the oil in place and expel the original oil from the macropores. The results of magnetic resonance imaging clearly show that the remaining oil accumulates in the central region of the core because a large amount of water is absorbed in the late stage of spontaneous imbibition, and the water in the pores gradually connects to form a "water shield" that blocks the flow of the oil phase. We propose the spontaneous imbibition pathway, which can effectively explain the internal mechanisms controlling the spontaneous imbibition rate. The surface of the core tends to form many spontaneous imbibition pathways, so the rate of spontaneous imbibition is fast. The deep core does not easily form many spontaneous imbibition pathways, so the rate of spontaneous imbibition is slow. This paper reveals the pore characteristics and distribution of oil and water during the spontaneous imbibition process, which is of significance for the efficient development of tight oil. [ABSTRACT FROM AUTHOR]