Search

Secondary hydrocarbon migration is an important aspect of oil-gas accumulation research. While previous studies have relied on geological and fluid geochemical characteristics to predict migration direction, these results are often limited by the number of samples. In recent years, basin simulation has emerged as a valuable tool in hydrocarbon migration research due to its extensive algorithms and adaptable modeling capabilities. It has obvious technical advantages especially for resource evaluation in areas with a lower exploration degree and scarce data. The deep oil and gas in the Cambrian petroleum system in the Tarim Basin is a deep hydrocarbon challenging area in China. There has been no breakthrough in exploration due to the large burial depth ( generally > 6000 m ) and the long accumulation and transformation processes. Therefore, predicting the secondary migration of Cambrian oil and gas has become the key to solving this problem. In this study, first, the thermal evolution of the Lower Cambrian source rocks in the Tarim Basin was recovered, and the three thermal evolution models were developed. The secondary migration process of the Cambrian petroleum system was restored using the geologic model of the source rocks and paleotectonic evolution and the latest fluid potential information. By comparing the simulation results, four secondary migration models of the ultradeep oil-gas migration and accumulation were developed: multisource, multiphase, multidirectional accumulation; multisource, multiphase, single-directional accumulation; single-source, multiphase, multidirectional accumulation; and single-source, multiphase, single-directional accumulation. The fluid potential simulation results indicate that the Cambrian oil and gas have salient inheritance characteristics. The dominant migration channels in the uplift and slope are beneficial to oil-gas migration and accumulation, and the Katake uplift and the west Bachu uplift have multisource charging accumulation. The east Bachu uplift and the Tabei uplift are oil-gas accumulation zones that are beneficial to the lower petroleum system due to the continuous charging of a single petroleum system. This fluid potential simulation provides a new solution for studying the secondary migration of deep oil and gas. It provides an important reference for studying hydrocarbon accumulation in deep and ultradeep areas.

For buildings with shallow foundations embedded in natural soil sediments, the underexcavation method is often used to correct building inclination. Relying on engineering experience and close field monitoring, rectification has been conducted successfully. However, theoretical studies are relatively scarce, resulting in an inadequately informed rectification design and procedure. Assuming the soil is an ideal elastic-plastic body, a simplified analysis was adopted to study the issue theoretically. First, the redistribution of the base contact pressure after building inclination was deduced. Second, according to the force balance between the total contact pressure of the base and the total stress on the horizontal plane at the excavation hole, the limit hole spacing at the critical state of building back tilt was obtained, which was also the preferable hole spacing for soil strip collapse. Third, because the amount of anticipated forced settlement at a certain section of soil excavation is equal to the volume of soil hole collapse, an accurate formula for the hole diameter was obtained. Combined with engineering experience, suggestions for the design procedure were proposed. Finally, two case histories were introduced to verify the correctness and practicability of the theoretical formula for hole spacing and diameter. These two key parameters provide a strong theoretical basis for building rectification in future engineering practice.

Hepatocellular carcinoma (HCC) is a disease with high morbidity, high mortality, and low cure rate. Hyaluronic acid (HA) is widely adopted in tissue engineering and drug delivery. 5-(4-Hydroxyphenyl)-3H-1, 2-dithiol-3-thione (ADT-OH) is one of commonly used H2S donors. In our previous study, HA-ADT was designed and synthesized via coupling of HA and ADT-OH. In this study, compared with sodium hydrosulfide (NaHS, a fast H2S-releasing donor) and morpholin-4-ium (4-methoxyphenyl)-morpholin-4-ylsulfanylidenesulfido-λ5-phosphane (GYY4137, a slow H2S-releasing donor), HA-ADT showed stronger inhibitory effect on the proliferation, migration, invasion, and cell cycle of human HCC cells. HA-ADT promoted apoptosis by suppressing the expressions of phospho (p)-protein kinase B (PKB/AKT), p‐glycogen synthase kinase‐3β (GSK-3β), p‐β‐catenin, and also inhibited autophagy via the downregulation of the protein levels of p‐Smad2, p‐Smad3, and transforming growth factor‐β (TGF‐β) in human HCC cells. Moreover, HA-ADT inhibited HCC xenograft tumor growth more effectively than both NaHS and GYY4137. Therefore, HA-ADT can suppress the growth of HCC cells by blocking the AKT/GSK-3β/β-catenin and TGF‐β/Smad2/3 signaling pathways. HA-ADT and its derivatives may be developed as promising antitumor drugs.

Background. LHON is a progressive disease with early disease onset and male predominance, usually causing devastating visual loss to patients. These systematic review and meta-analysis are aimed at summarizing epidemiology, disease onset and progression, visual recovery, risk factors, and treatment options of Leber’s hereditary optic neuropathy (LHON) with mitochondrial DNA mutation G11778A from current evidence. Methods. The PubMed database was examined from its inception date to November 2021. Data from included studies were pooled with either a fixed-effects model or a random-effects model, depending on the results of heterogeneity tests. Sensitivity analysis was conducted to test the robustness of results. Results. A total of 41 articles were included in the systematic review for qualitative analysis, and 34 articles were included for quantitative meta-analysis. The pooled estimate of proportion of G11778A mutation among the three primary mutations of mitochondrial DNA (G11778A, G3460A, and T14484C) for LHON was 73% (95% CI: 67% and 79%), and the LHON patients with G11778A mutation included the pooled male ratio estimate of 77% (76% and 79%), the pooled age estimate of 35.3 years (33.2 years and 37.3 years), the pooled onset age estimate of 22.1 years (19.7 years and 24.6 years), the pooled visual acuity estimate of 1.4 LogMAR (1.2 LogMAR and 1.6 LogMAR), and the pooled estimate of spontaneous visual recovery rate (in either 1 eye) of 20% (15% and 27%). Conclusions. The G11778A mutation is a prevalent mitochondrial DNA mutation accounting for over half of LHON cases with three primary mutations. Spontaneous visual recovery is rare, and no effective treatment is currently available.

To investigate the bearing mechanism and efficiency of group anchors in sand, upward pulling tests of model group anchors were carried out for different conditions of the sand density, anchor burial depth ratio, and anchor spacing. The results show that the load-displacement relationships for group anchors is similar to that for single anchors, both being nonlinear for the same relative density and embedment ratio. The load-carrying capacity of group anchors is not a simple superposition of the capacities of two single anchors, but has a clear superposition effect, depending on the relative density, embedment ratio, and anchor spacing. The load carrying capacity increases with the anchor spacing up to a limiting critical value. The bearing mechanism of group anchors was qualitatively analyzed and quantitatively characterized using the strain field and shear stress field obtained through the digital image correlation. Adopting the test data and theoretical derivation, a critical anchor spacing equation is proposed and the relationship between critical anchor spacing, embedment ratio, and relative density is quantitatively characterized. Theory is proposed for predicting the group efficiency of group anchors with different configurations. Comparisons between the results of the developed model and experimental results reported in the literature show good agreement.

Aiming at the problems such as slow traceability efficiency, poor sharing, and the difficulty of matching the throughput of a blockchain single chain structure due to the complexity of the grain food supply chain links, the large number of participants, and the large amount of data information, this paper proposes a grain food blockchain traceability information management model based on the master-slave multichain structure by analyzing the processes and data characteristics of each link in the grain food supply chain; on this basis, the PLEW consensus algorithm based on Raft + improved PoW algorithm is designed for the master chain, and the CI-PBFT consensus algorithm based on trusted information degree is designed for the slave chain. The master chain and slave chain are anchored to each other through hash locking, and the data is uploaded and queried through smart contracts. In order to verify the effectiveness of the model, the blockchain traceability system is designed and implemented based on Hyperledger Fabric2.2. At the same time, it is compared with the transaction throughput and traceability efficiency of the blockchain single chain structure. Through the safety analysis of the data information of a company in Hubei, the results show that the grain traceability system designed and implemented in this study has certain advantages over the blockchain single chain structure in all aspects. It can also solve the grain food security problems that consumers worry about, and provide reference for the research of grain blockchain traceability information management.

Objectives. The characteristic pathophysiological feature of acute respiratory distress syndrome (ARDS) is a dysregulated inflammatory response. T helper 17 (Th17) cells in the lung are inflammatory cells that contribute to pulmonary inflammatory cascades. In addition, Th17/regulatory T cells (Treg cells) also play an important role in the inflammatory process. Dendritic cells (DCs) can regulate the differentiation of CD4+ T cells, including Th17 and Treg cells. Recent evidence revealed that interleukin-33 (IL-33) signaling could activate and mature DCs. Therefore, the aim of this study was to investigate the effects of IL-33 on inflammation and immunoregulation by inducing the Th17 response and influencing the Th17/Treg balance in LPS-induced ARDS. Methods. IL-33 gene knockout mice and the administration of recombinant mouse IL-33 (rmIL-33) were used to investigate the role of IL-33 and the underlying mechanisms in an LPS-induced ARDS model. Hematoxylin and eosin (H&E) staining, wet/dry (W/D) weight ratios, cell counts, and the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-17 (IL-17), and interleukin-10 (IL-10) in bronchoalveolar lavage fluid (BALF) were investigated. The levels of IL-33, orphan nuclear receptor gamma t (RORγt), and forkhead transcription factor protein 3 (FOXP3) protein in lung tissue were evaluated by Western blotting. The mRNA expression levels of IL-33 and RORγt were measured by quantitative real-time polymerase chain reaction (qRT-PCR). Th17 and Treg cell frequencies were determined by flow cytometry. The levels of IL-6 in the supernatant in a dendritic cell culture system were examined by ELISA. Results. Increased expression of IL-33 was observed in mice with LPS-induced ARDS. IL-33 deficiency significantly inhibited inflammation and attenuated LPS-induced ARDS, whereas pretreatment with rmIL-33 aggravated pulmonary inflammatory response. Furthermore, depletion of IL-33 inhibited Th17 cells, significantly decreased RORγt mRNA and protein expression and IL-17 levels in BALF, and led to less differentiation of T cells into Th17 cells than Treg cells. Moreover, IL-33-/- DCs secreted less IL-6 and IL-23 than normal control DCs. Conclusion. IL-33 deficiency alleviated lung injury in the LPS-induced ARDS model, which was closely related to suppressing Th17 responses and regulating the Th17/Treg balance. The expansion of Th17 cells and imbalance in Th17/Treg cells may be associated with IL-6 and IL-23 secreted from IL-33-activated DCs.

Background. The present study aimed to investigate the prognostic value of serum ferritin in critically ill patients with sepsis by using the MIMIC-IV database. Methods. Data were extracted from the MIMIC-IV database. Adult patients who met the sepsis-3 criteria and had the test of ferritin were included. Patients were divided into subgroups according to the initial serum ferritin. The association between initial serum ferritin and in-hospital mortality was performed by using Lowessregression, logistic regression, and ROC analysis. Subgroup analysis was used to search for the interacting factors and verify the robustness of the results. Results. Analysis of the 2,451 patients revealed a positive linear relationship between serum ferritin and in-hospital mortality. Patients with high-ferritin had a higher risk of in-hospital mortality, but no significant association was found in the low-ferritin subgroup compared with those whose ferritin was in the normal reference range. Serum ferritin had moderate predictive power for in-hospital mortality (AUC = 0.651), with an optimal cut-off value of 591.5 ng/ml. Ferritin ≥591.5 ng/ml acted as an independent prognostic predictor of in-hospital mortality, which increased the risk of in-hospital mortality by 119%. Our findings were still robust in subgroup analysis, and acute kidney injury and anemia were considered interactive factors. Conclusion. High-level serum ferritin was an independent prognostic marker for the prediction of mortality in patients with sepsis. Further high-quality research is needed to confirm the relationship between ferritin and the prognosis of septic patients.

Artificial intelligence (AI) technology has huge scope in developing models to predict the survival rate of critically ill patients in the intensive care unit (ICU). The availability of electronic clinical data has led to the widespread use of various machine learning approaches in this field. Innovative algorithms play a crucial role in boosting the performance of models. This study uses a stacked ensemble model to predict mortality in ICU by incorporating the clinical severity scoring results, in which several machine learning algorithms are employed to compare the performance. The experimental results show that the stacked ensemble model achieves good performance compared with the model without integrating the severity scoring results, which has the area under curve (AUC) of 0.879 and 0.862, respectively. To improve the performance of prediction, two feature subsets are obtained based on different feature selection techniques, labeled as SetS and SetT. Evaluation performances show that the SEM based on the SetS achieves a higher AUC value (0.879 and 0.860). Finally, the SHapley Additive exPlanations (SHAP) analysis is employed to interpret the correlation between the risk features and the outcome.

As a crucial part of the urban system, road networks play a key role in the evolution of the urban structure. Therefore, studying the structural characteristics of urban road networks is pivotal for improving the efficiency of traffic network nodes and for relieving traffic pressure. This paper applies an urban road network analysis method to measure the centrality of the multiscale road network in Shenzhen, China. Taxi GPS data from October 17 to October 23, 2017, were selected for analysis of spatial distribution characteristics. This paper also established a regression model of taxi pick-up and drop-off frequency and road network centrality for further analysis. Several interesting observations were made. With respect to the increasing search radius, the closeness centrality indicator shifts from a multicentered distribution to a single-centered distribution, while the betweenness centrality indicator shifts from a patchy distribution to a distribution along the main roads. In addition, the straightness centrality indicator turns from a dispersed distribution to a point-axis distribution, concentrated in the southern part of the city. Second, there were variations between the centrality of the road network and the location of taxi pick-up and drop-off points. The regression model gets the highest value of R2, indicating a significant correlation in cases where the search radius is 3 km. Finally, the relationship exhibits a clear positive correlation between the betweenness centrality and taxi pick-up and drop-off points. On the other hand, closeness centrality is not correlated with these points. The straightness centrality has a negative correlation with the frequency of taxi pick-up and drop-off at 3 km and 8 km scale.

Hidden Markov models (HMMs) have been recently used for fault detection and prediction in continuous industrial processes; however, the expected maximum (EM) algorithm in the HMM has local optimality problems and cannot accurately find the fault root cause variables in complex industrial processes with high-dimensional data and strong variable coupling. To alleviate this problem, a hidden Markov model-Bayesian network (HMM-BN) hybrid model is proposed to alleviate the local optimum problem in the EM algorithm and diagnose the fault root cause variable. Firstly, the model introduces expert empirical knowledge for constructing BN to accurately diagnose the fault root cause variable. Then, the EM algorithm is improved by sequential and parallel learning to alleviate the initial sensitivity and local optimum problems. Finally, the log-likelihood estimates (LL) calculated by the improved hidden Markov model provide empirical evidence for the BN and give fault detection, prediction, and root cause variable detection results based on information about the similar increasing and decreasing patterns of LL for the training data and the online data. Combining the Tennessee Eastman (TE) process and the continuously stirred tank reactor (CSTR) process, the feasibility and effectiveness of the model are verified. The results show that the model can not only find the fault in time but also find the cause of the fault accurately.

Background. Hepatic encephalopathy (HE) is a neurological and psychiatric syndrome. Recent evidence suggests that HE is not only a disease of the liver and brain but is also related to the gut. Small intestinal bacterial overgrowth (SIBO) is well known to be associated with cirrhosis, but the relationship between SIBO and HE is unclear. We conducted this comprehensive systematic review and meta-analysis to determine the association between SIBO and HE in cirrhotic patients. Methods. We conducted a comprehensive literature search of all studies on the association of SIBO and HE in cirrhotic patients using the PubMed and Embase electronic databases. Studies were screened, and relevant data were extracted and analysed. We calculated the number of cases of SIBO in patients with HE and controls. We then compared the prevalence of SIBO between the two groups to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). Funnel plots were constructed to identify potential publication bias. Results. Six studies with 414 participants (219 HE patients and 195 controls) met the inclusion criteria. The prevalence of SIBO in cirrhotic patients with HE was significantly higher than that in those without HE. The combined OR was 4.43 (95% CI 1.73-11.32, P = 0.002 ). The heterogeneity was moderate ( I 2 = 66 %), and the funnel plot suggested no significant publication bias. Subgroup analysis showed that the OR was 1.95 (95% CI 0.63–6.09) in studies using the lactulose breath test (LBT) and 7.60 (95% CI 3.50–16.50) in studies using the glucose breath test (GBT). The prevalence of SIBO in cirrhotic patients was also related to the severity of liver disease. Conclusions. Our meta-analysis identified a strong association between SIBO and HE, and the risk of SIBO was 4.43 times higher among cirrhotic patients with HE than among those without HE. SIBO could be a predisposing factor for the development of HE in cirrhotic patients. Therefore, the importance of SIBO should be emphasized in patients with HE.

Current research suggests that chronic high-fat dietary intake can lead to bone loss in adults; however, the mechanism by which high-fat diets affect the development of osteoporosis in individuals is unclear. As high-fat diets are strongly associated with ferroptosis, whether ferroptosis mediates high-fat diet-induced bone loss was the focus of our current study. By dividing the mice into a high-fat diet group, a high-fat diet + ferroptosis inhibitor group and a normal chow group, mice in the high-fat group were given a high-fat diet for 12 weeks. The mice in the high-fat diet + ferroptosis inhibitor group were given 1 mg/kg Fer-1 per day intraperitoneally at the start of the high-fat diet. Microscopic CT scans, histological tests, and biochemical indicators of ferroptosis were performed on bone tissue from all three groups at the end of the modelling period. Mc3t3-E1 cells were also used in vitro and divided into three groups: high-fat medium group, high-fat medium+ferroptosis inhibitor group, and control group. After 24 hours of incubation in high-fat medium, Mc3t3-E1 cells were assayed for ferroptosis marker proteins and biochemical parameters, and osteogenesis induction was performed simultaneously. Cellular alkaline phosphatase content and expression of osteogenesis-related proteins were measured at day 7 of osteogenesis induction. The results showed that a high-fat diet led to the development of femoral bone loss in mice and that this process could be inhibited by ferroptosis inhibitors. The high-fat diet mainly affected the number of osteoblasts produced in the bone marrow cavity. The high-fat environment in vitro inhibited osteoblast proliferation and osteogenic differentiation, and significant changes in ferroptosis-related biochemical parameters were observed. These findings have implications for the future clinical treatment of bone loss caused by high-fat diets.

We investigated the frequency dependence of Poisson’s ratio ν in partially/fully fluid-saturated rocks. Based on one dominant fluid flow mechanism at each condition, we theoretically summarized that (1) when a rock is partially saturated or transits from drained state to undrained state at full saturation, ν increases monotonously with frequency, and the associated attenuation 1 / Q ν is positive with one peak. (2) When the rock transits from undrained state to unrelaxed state at full saturation, there are three cases: 1) ν increases monotonously with frequency and has positive 1 / Q ν with one peak, 2) ν keeps constant with frequency and has no attenuation, 3) and ν decreases monotonously with frequency and has negative 1 / Q ν with one peak. In this condition, the dependence is influenced by the concentrations of stiff and soft pores, the aspect ratio of soft pores, and the pore fluid bulk modulus. (3) When it comes to the transition from drained state to unrelaxed state at full saturation, ν can exhibit two shapes with frequency: 1) step shape with two positive attenuation peaks and 2) bell shape with one positive attenuation peak and one negative attenuation peak. Then, we conducted a numerical example to indicate the effect of influence factors (the concentrations of stiff and soft pores, the aspect ratio of soft pores, and the pore fluid bulk modulus) on Poisson’s ratio from undrained state to unrelaxed state, and validated the theoretical analysis by the published experimental data. In addition, based on 1 / Q ν , we reanalyzed and validated the relationship between different attenuation modes (i.e., bulk attenuation 1 / Q K , P-wave attenuation 1 / Q P , extensional attenuation 1 / Q E , and S-wave attenuation 1 / Q S ): (1) when 1 / Q ν is positive, the relationship between them is 1 / Q K > 1 / Q P > 1 / Q E > 1 / Q S ; when 1 / Q ν is 0, the relationship between them is 1 / Q K = 1 / Q P = 1 / Q E = 1 / Q S ; and when 1 / Q ν is negative, the relationship between them is 1 / Q K < 1 / Q P < 1 / Q E < 1 / Q S . The relationship between different attenuation modes does not depend on saturation state (partial or full saturation) or ν but on 1 / Q ν . This research provides the frequency dependence of Poisson’s ratio in partially/fully saturated rocks, which helps better understand Poisson’s ratio at different frequencies and saturation states and can be used to improve the accuracy of geophysical data interpretation, such as lithology identification, hydrocarbon characterization in conventional reservoir, and brittleness evaluation of shale/tight sandstones in unconventional reservoir.

While facing complex surroundings, robots need to identify the same intention which is expressed in different ways. In order to solve the problem of assisting robots to get a better intention understanding, a self-tuning multimodal fusion algorithm is put forward in this paper, which is not restricted by the expressions of interacting participants and environment. The multimodal fusion algorithm can be transferred to different application platforms. Robots can own the understanding competence and adapt new tasks by changing the content of the robot knowledge base. Compared with other multimodal fusion algorithms, this paper attempts to transfer the basic structure of feed-forward neural networks on discrete sets, which has strengthened the consistency and perfect the complementary relations between multiple mode, and has realized the simultaneous operation of fusion operator’s self-tuning and intention search. There are three kinds of modes selected in the paper: speech, gesture, and scene objects, where the single modal classifiers are trained separately. This method conducted a human-computer interaction experiment on the bionic robot Pepper platform, which proved that the method can effectively improve the accuracy and robustness of robots in aspects of understanding human intentions, and reduce the uncertainty about intention judgment in a single modal interaction.

Traditional onefold data-driven methods for fault detection in complex process industrial systems with high-dimensional, linear, nonlinear, Gaussian, and non-Gaussian coexistence often have less than satisfactory monitoring performance because only a single distribution of process variables is considered. To address this problem, a hybrid fault detection model based on PCA-KPCA-ICA-KICA-BI (Bayesian inference) is proposed, taking into account the advantages of principal component analysis (PCA), kernel principal component analysis (KPCA), independent component analysis (ICA), and kernel independent component analysis (KICA) in terms of dimensionality reduction and feature extraction. Foremost, this paper proposed a nonlinear evaluation method and divided the feature variables into Gaussian linear blocks, Gaussian nonlinear blocks, non-Gaussian linear blocks, and non-Gaussian nonlinear blocks by using the Jarque–Bera (JB) test and nonlinear discrimination method. Each division was monitored by the PCA-KPCA-ICA-KICA model, and finally the Bayesian fusion strategy proposed in this study is used to synthesize the detection results for each block. The hybrid model helps in evaluating variable features and bettering detection performance. Ultimately, the superiority of this hybrid model was verified through the Tennessee Eastman (TE) process and the Continuous Stirred Tank Reactor (CSTR) process, and the fault monitoring results showed an average accuracy of 85.91% for this hybrid model.

Blockchain technology is widely used in various fields according to its programmable advantages. Such technology has several typical characteristics, such as openness, automation, independence, security, sharing, and modularity. The logistics system is greatly beneficial from such characteristics. Therefore, blockchain technology can provide core technical support for the construction of logistics supply chain system. In this paper, we focus on the current demands of “blockchain + logistics” business system and reduce half risks in the supply chain through decentralization and detrusting of blockchain technology. Finally, experimental results show that it has a certain practical significance for the adjustment of the strategic layout and sound development of supply chain logistics.

With the development of the intelligent and interactive power system, the elements of distribution network planning continue to increase. The distribution network connects the transmission system and individuals, directly affects the individual’s power consumption experience, and is a key link in the power system. A reasonable planning scheme can not only improve the power supply capacity and reliability of the distribution network but also fully apply the data of each system in the distribution network to realize the optimal planning of the medium-voltage distribution network driven by data. Firstly, this paper constructs the CIM model and the distribution network topology model and establishes the wiring pattern recognition feature library. The network reconstruction and planning method research was carried out for the target line, and a typical operation scenario of the distribution network was generated. At the same time, based on the time period network loss index, the distribution network reconfiguration optimization model and distribution network expansion planning model are established, and the solution method of the distribution network reconstruction and expansion planning model is expounded. A reconstruction optimization scheme with the best overall network loss performance is in the network operation scenario. The experimental results of the final example show that based on the proposed time period network loss index, the overall operation loss of the distribution network in a period can be calculated more accurately, and the optimized planning scheme is more suitable for the load power consumption characteristics of the region, and the method has certain feasibility.

To address the problems with deep-hole presplit blasting intended to fracture and improve the permeability of deeply buried, soft, high-gas-content coal seams, a method using a blasthole and a relief hole drilled into the underlying rock stratum was proposed. By establishing a theoretical model for this purpose, the stress wave propagation characteristics during the blasting process were analyzed, and the working mechanisms of the relief hole and the stress transmission characteristics were investigated. The blasting of the C13-1 coal seam in the Huainan mining area under different in situ stress conditions using different blasthole–relief hole distances was simulated using an implicit–explicit coupled method and the ANSYS/LS-DYNA software. The results showed that the blasting-induced stress wave was reflected from the coal–rock interface and transformed into a tensile wave owing to the different wave impedances of coal and rock, thereby fracturing the rock and coal masses better and achieving the intended permeability improvement effect. A free surface effect was produced near the relief hole during the blasting process, which directed the stress wave to propagate in the direction of the relief hole, thereby promoting fracturing in that direction. The in situ stress inhibited the blasting-induced fracturing in the coal mass. Thus, for blasting intended to improve the permeability of deeply buried coal masses, the blasthole–relief hole distance should be reduced to achieve better fracturing. Our results have a certain reference value for directional blasting intended to fracture and improve the permeability of deeply buried, soft, high-gas-content coal seams.

Chemokine C-C motif chemokine ligand 3 (CCL3) plays an important role in the invasion and metastasis of malignant tumors. For developing new therapeutic targets and antitumor drugs, the effect of chemokine CCL3 and the related cytokine network on colorectal cancer should be investigated. This study used cell, tissue, and animal experiments to prove that CCL3 is highly expressed in colorectal cancer and confirmed that CCL3 can promote the proliferation of cancer cells, and its expression is closely related to TRAF6/NF-κB molecular pathway. In addition, protein chip technology was used to examine colorectal cancer tissue samples and identify the key factors of chemokine CCL3 and the toll-like receptors/nuclear factor-κB (TLR/NF-κB) pathway in cancer and metastatic lymph nodes. Furthermore, the lentiviral vector technology was employed for transfection to construct interference and overexpression cell lines. The experimental results reveal the mechanism of CCL3 and TNF receptor-associated factor 6 (TRAF6)/NF-κB pathway-related factors and their effects on the proliferation of colon cancer cells. Finally, the expression and significance of CCL3 in colorectal cancer tissues and its correlation with clinical pathology were studied by immunohistochemistry. Also, the results confirmed that CCL3 and C-C motif chemokine receptor 5 (CCR5) were expressed in adjacent tissues, colorectal cancer tissues, and metastatic cancer. The expression level was correlated with the clinical stage and nerve invasion. The expression of chemokine CCL3 and receptor CCR5 was positively correlated with the expression of TRAF6 and NF-κB and could promote the proliferation, invasion, and migration of colorectal cancer cells through TRAF6 and NF-κB.

Background. Lung cancer is a malignant cancer which results in the most cancer incidence and mortality worldwide. There is increasing evidence that the pattern of DNA methylation affects tumorigenesis and progression. However, the molecules and mechanisms regulating DNA methylation remain unclear. Methods. The expression of miR-26a-5p in NSCLC cell lines was detected by qPCR and verified in NSCLC tissues from TCGA using Limma R package. CCK-8 assay, plate clone formation assay, flow cytometry, and sphere formation assay were used to detect the cell proliferation, colony formation, cell cycle, and cancer stem cell- (CSC-) like property in NSCLC cell lines. The immunoblotting was used to detect the protein levels of DNMT3A, SFRP1, and Ki67. Global DNA methylation levels and DNA methylation levels of SFRP1 promoter were examined using ELISA and MSP-PCR assay, respectively. The distribution of β-catenin was examined using immunofluorescence (IF). Besides, xenograft mouse model was used to investigate the antitumor effects of miR-26a-5p in vivo. The pathology and protein levels were, respectively, detected by hematoxylin and eosin (H&E) and immunocytochemistry (IHC). Results. The expression of miR-26a-5p was downregulated in the tumor tissues comparted to adjacent normal tissues as well as NSCLC cell lines compared to normal lung epithelial cell (BEAS2B). The overexpression of miR-26a-5p inhibited cell proliferation, colony formation, CSC-like property, and arrested cell cycle at G1 phase. DNMT3A was a target of miR-26a-5p and upregulated DNA methylation on SFRP1 promoter. Mechanistically, miR-26a-5p repressed cell proliferation, colony formation, CSC-like property, and arrested cell cycle at G1 phase by binding DNMT3A to reduce DNA methylation levels of SFRP1 then upregulated SFRP1 expression. Moreover, miR-26a-5p exerted antitumor effects in vivo. Conclusion. Our results revealed that miR-26a-5p acted as a tumor suppressor through targeting DNMT3A to upregulate SFRP1 via reducing DNMT3A-dependent DNA methylation.

With the gradual opening of the market, the overall development of Chinese enterprises is “rapid development, gradual improvement of industry status, and promising prospects.” Not only the development of Chinese local enterprises is getting better and better, but also a large number of foreign-funded enterprises are pouring into the domestic market, and the competition pressure on domestic enterprises is increasing. The purpose of this study is to study the effect of neutral AHP on the establishment of the mathematical model of enterprise marketing economic analysis and to use the method of structural judgment matrix and hierarchical structural model to put forward a concrete practical analysis of enterprise marketing cost and business performance. The experimental results of this study show that the establishment of an enterprise marketing economic mathematical model based on AHP can help group companies maintain an annual revenue growth rate of more than 5.8%, while the annual revenue economic growth rate is less than 5% for companies that establish a mathematical model.

Context. Bruguiera gymnorrhiza (L.) Lam. (BG), as a major species of mangroves, is also a traditional Chinese medicine, which has received attention for its anti-inflammatory and anticancer effects. However, the protective effect of BG on gastric injury is rarely studied. Objective. The present study aimed at the anti-inflammatory and antioxidant effects of the extract of Bruguiera gymnorrhiza (L.) Lam. fruit (BGF) on the gastric injury. Materials and Methods. The chemical components in the extract of BGF were used in UPLC/Q-Orbitrap analysis. 60 SD rats were randomized into six groups: normal group (MC), ethanol-injured control group (EC), omeprazole group, and three groups with different doses (50, 100, and 200 mg/kg) of BGF. After continuous administration for seven days, the stomachs of rats were taken out to observe the pathological gastric tissue changes; inflammatory factors and oxidative stress markers in the stomach tissues were measured. Western blot (WB) analyses were conducted to explore the mechanism of BGF on gastric tissue and RAW 246.7 cells with excessive inflammation. Results. BGF enhanced gastric mucosal protection by improving the mucosal blood flow of the stomach and significantly decreased inflammatory factors and oxidative stress markers. Moreover, BGF significantly reduced the expression of p-NF-κB p65. Consistently, BGF demonstrated similar effects on LPS-induced RAW 264.7 cells as it did in vivo. Conclusion. BGF could accelerate the healing of gastric injury by exerting antioxidant and anti-inflammatory effects and maintaining mucosal integrity.

With the transformation of the supply chain from factor driven to investment driven and to innovation driven, supply chain innovation has attracted more and more attention. This paper obtains the Bayesian prior probability of innovation and studies the supply chain innovation path from the perspective of strategy and behavior. The model divides the overall innovation capability of the supply chain into specific node tasks and assets (Capability Set), and the innovation demand of the supply chain is expressed in the form of the conditional probability of market demand. Under the conditions of minimum risk, minimum cost, and rapid market response, it determines who should lead the supply chain innovation first and what type of supply chain innovation should be carried out first. Finally, taking the supply chain of the professional market in Zhejiang Province as an example, this paper verifies the theoretical model of supply chain innovation decision-making. The innovation of the supply chain of Zhejiang’s specialized market is decomposed into the capability set of each enterprise node of the supply chain. This paper transforms the group innovation ability of the supply chain in the professional market into the individual innovation ability of a single enterprise node and reveals the starting point and intensity of the demand innovation of products/services in the supply chain.

Rain height is crucial for rain attenuation prediction along slant paths, such as Earth-space links. The global digital map of the mean annual rain height is given in Recommendation ITU-R P.839-4. The disadvantage of this model is that heavy rainfall in most regions of the middle and high latitudes of the world is typically concentrated over a few months, such as summer in North China, and the mean rain height during these months and the mean annual rain height are often significantly different. In this study, a new weighted mean annual rain height is proposed by using the ratio of the mean monthly rainfall to the mean annual rainfall as the weight. The analysis shows that the weighted mean annual rain heights have been closer to the statistical rain heights during heavy rainfall in general. On the other hand, the work of this paper helps to improve the accuracy of the rain attenuation prediction model on Earth-space links in China. However, the weighted mean annual rain heights have different characteristics for different rainfall climate zones. This study will contribute to the research of rain attenuation modelling on Earth-space links.

Aim of Study. Myocardial infarction is the number one cause of death worldwide. Existing treatment methods such as drugs and surgery cannot completely restore the structure and function of the ischemic heart. In recent years, therapeutic angiogenesis has received gradually increasing attention due to its fundamental therapeutic advantages of improving microcirculation and restoring blood supply in ischemic areas. This article mainly reviewed the mechanism and effect of angiogenesis-promoting herbs. Methods. We conducted a literature search on the bioactive components of medicinal plants and their effects on angiogenesis after MI. We searched for articles in Web of Science, MEDLINE, PubMed, Scopus, Google Scholar, and China National Knowledge Infrastructure databases before April 2021. Results. In this article, we summarized the mechanisms by which copper ions, microRNA, Akt1, inflammation, oxidative stress, mitochondria, and pericytes are involved in angiogenesis after myocardial infarction. In addition, we reviewed the angiogenic effects of natural herbal medicines such as Salvia miltiorrhiza Bunge Bunge, Carthamus tinctorius L., Pueraria lobata, Astragalus, Panax ginseng C.A. Mey., Panax notoginseng (Burkill) F.H. Chen, Cinnamomum cassia (L.) J. Presl, Rehmannia glutinosa (Gaertn.) DC., Leonurus japonicus Houtt, Scutellaria baicalensis Georgi., and Geum macrophyllum Willd. Conclusions. Some herbs have the effect of promoting angiogenesis. In the future, natural proangiogenic drugs may become candidates for the treatment of cardiovascular diseases.

Breast cancer (BRCA) is one of the leading causes of death among women worldwide, and drug resistance often leads to a poor prognosis. Necroptosis is a type of programmed cell death (PCD) and exhibits regulatory effects on tumor progression, but few studies have focused on the relationships between necroptosis-associated lncRNAs and BRCA. In this study, we established a signature basis of 7 necroptosis-related lncRNAs associated with prognosis and divided BRCA patients into high- and low-risk groups. Kaplan-Meier curves all showed an adverse prognosis for patients in the high-risk group. Cox assays confirmed that risk score was an independent prognostic factor for BRCA patients. The receiver operating characteristic (ROC) curve proved the predictive accuracy of the signature and the area under the curve (AUC) values of the risk score reached 0.722. The nomogram relatively accurately predicted the prognosis of the patients. GSEA analysis suggested that the related signaling pathways and biological processes enriched in the high- and low-risk groups may influence the tumor microenvironment (TME) of BRCA. ssGSEA showed the difference in immune cell infiltration, immune pathway activation, and immune checkpoint expression between the two risk groups, with the low-risk group more suitable for immunotherapy. According to the significant difference in IC50 between risk groups, patients can be guided for an individualized treatment plan. Overall, the authors established a prognostic signature consisting of 7 necroptosis-associated lncRNAs that can independently predict the clinical outcome of BRCA patients. The difference in the tumor immune microenvironment between the low- and high-risk populations may be the reason for the resistance to immunotherapy in some patients.

Space robot teleoperation is an important technology in the space human-robot interaction and collaboration. Hand-based visual teleoperation can make the operation more natural and convenient. The fast and accuracy hand detection is one of the most difficult and important problem in the hand-based space robot teleoperation. In this work, we propose a fast and accurate hand detection method by using a spatial-channel attention single shot multibox detector (SCA-SSD). The SSD framework is used and improved in our method by introducing spatial-channel attentions with feature fusion. To increase the restricted receptive field in shallow layers, two shallow layers are fused with deep layers by using feature fusion modules. And spatial attention and channel-wise attention are also used to extract more efficient features. This method can not only ease the computational burden but also bring more contextual information. To evaluate the effectiveness of the proposed method, experiments on some public datasets and a custom astronaut hand detection dataset (AHD) are conducted. The results show that our method can improve the hand detection accuracy by 2.7% compared with the original SSD with only 15 fps speed drops. In addition, the space robot teleoperation experiment proves that our hand detection method can be well utilized in the space robot teleoperation system.

With the expansion of the digital business line, the network flow behind the digital power grid is also exploding. To prevent network congestion, this article proposes a novel network flow forecasting model, which is composed of variational mode decomposition (VMD), GRU-xgboost block, and a forecasting adjustment block, to grasp the changing patterns and trends of network flow in advance, and to formulate reasonable and effective flow management strategies and meet the requirements of users for network service quality. The network flow series in power grid enterprise always contain complex patterns and outliers, and VMD is applied to adaptively process complex net flow time series into several subseries with simpler patterns. A GRU-xgboost block is designed to reconstruct the features of historical series. Then, xgboost model is applied to generate predictions for all decomposed subsignals. For the final predictions, we design a forecasting adjustment block to further remove the influence of random noise. Finally, the empirical results show the superior performance of the proposed model on network flow forecasting task.

Clear cell renal carcinoma (ccRCC) is one of the most common renal carcinomas worldwide, which has worse prognosis compared with other subtypes of tumors. We propose a potential RNA regulatory mechanism associated with ccRCC progression. Accordingly, we screened out clinical factors and the expression of RNAs and miRNAs of ccRCC from the TCGA database. 9 lncRNAs (FGF12-AS2, WT1-AS, TRIM36-IT1, AC009093.1, LINC00443, TCL6, COL18A1-AS1, AC110619.1, HOTTIP), 2 miRNAs (mir-155 and mir-21), and 3 mRNAs (COL4A4, ERMP1, PRELID2) were selected from differential expression RNAs and built predictive survival models. The survival models performed very well in predicting prognosis and were found to be highly correlated with tumor stage. In addition, the survival-related lncRNA-miRNA-mRNA (ceRNA) network was constructed by 18 RNAs including 12 mRNAs, 2 miRNAs, and 4 lncRNAs. It is found that the “ECM-receptor interaction,” “Pathways in cancer,” and “Chemokine signaling pathway” as the main pathways in KEGG pathway analysis. Overall, we established predictive survival model and ceRNA network based on multivariate Cox regression analysis. It may open a new approach and potential biomarkers for clinical prognosis and treatment of ccRCC patients.

Hydraulic fracturing is a rock structure transformation method that significantly weakens the mechanical properties of the hard roof strata. Considering the poor hydraulic fracturing effect of special structure such as composite layered rock, this paper carries out hydraulic fracturing numerical simulation experiments and compares the hydraulic fracture morphology and bedding plane interaction mode under different injection rate and injection modes. The experimental results show that the bedding plane can change the trajectory and propagation direction of hydraulic fracture. Under the low injection rate, hydraulic fracturing is conducive to open the bedding plane, but the expansion length of the main hydraulic fracture is easy to be limited. Under the high injection rate, the hydraulic fracture can extend for a long distance. But the fracture morphology tends to be slender and single, which is not conducive to the formation of fracture network. Compared with conventional hydraulic fracturing, stepped variable injection rate hydraulic fracturing can activate more bedding planes, so as to improve the effect of rock strata transformation. The experimental results are instructive in achieving effective control of composite layered rock.

This article presents a dual circular polarization (CP) microstrip antenna, emitting electromagnetic waves above and below the substrate, which is fed by the double L-probe. Selecting the L-probe feed increases the bandwidth of the antenna, and different probes control the rotation of CP. The antenna could radiate two polarized waves of the same amplitude and vertical through two square radiation patches; meanwhile, adjusting the phase difference between both waves to 90° will produce a CP wave in the far-field. The simulation and measurement results show that the antenna is in 4.3–4.8 GHz band with S11

In the modern petroleum industry system, oil-water two-phase flows exist widely. Among them, the total flow rate of mixture fluid in a horizontal well is difficult to obtain due to the phase segregation caused by gravity. Therefore, it is a difficult and hot issue. To obtain the total flow rate of oil-water two-phase flows in horizontal wells, in this paper, Multiple Array Production Suite (MAPS), which is also called Production Array Logs (PAL), is used to conduct simulation experiments, uses BP neural network (BPNN) algorithm to train the data samples, and establishes the prediction models of the total flow rates of oil-water two-phase flows in horizontal wells. The results showed that the average relative error was less than 10%, which justify that the BPNN has good practicability in using data of MAPS in oil-water two-phase flows horizontal wells to predict the total flow rates, and it provides a new method and theoretical support for obtaining flow rates in horizontal wells.

Rice is a major food crop around the world, and its various quality and safety problems are closely related to human health. As an important area of food safety research, the rice supply chain has attracted increasing attention. Based on blockchain technology, this study investigated problems of data privacy and circulation efficiency caused by complex rice supply networks, long circulation cycles, and various risk factors in each link. First, we deconstructed the quality and safety of each link of the rice supply chain at the information level and established a key information classification table for each link. On that basis, we built a rice supply chain information supervision model based on blockchain. Various encryption algorithms are used to secure the sensitive data of enterprises in the supply chain to meet regulators’ needs for efficient supervision. Moreover, we propose a practical Byzantine fault-tolerant consensus algorithm that scores the credit of enterprise nodes, optimizes the selection strategy of master nodes, and ensures high efficiency and low cost. Then, we built a prototype system based on the open-source framework of hyperledger fabric, analyzed the model’s viability, and implemented the system using cases. The results indicated that the proposed system can optimize the information supervision process of rice supply chain regulators and provide a feasible solution for the quality and safety supervision of grain and oil.

MutS homolog 2 (MSH2) is a crucial participant in human DNA repair, and lots of the studies functionally associated with it were begun with hereditary nonpolyposis colorectal cancer (HNPCC). MSH2 has also been reported to take part in the progresses of various tumors’ formation. With the help of GTEx, CCLE, and TCGA pan-cancer databases, the analysis of MSH2 gene distribution in both tumor tissues and normal control tissues was carried out. Kaplan-Meyer survival plots and COX regression analysis were conducted for the assessment into the MSH2’s impact on tumor patients’ clinical prognosis. In an investigation to the association of MSH2 expression with immune infiltration level of various tumors and a similar study on tumor immune neoantigens, microsatellite instability was subsequently taken. It was found that high expression of MSH2 is prevalent in most cancers. MSH2’s efficacy on clinical prognosis as well as immune infiltration in tumor patients revealed a fact that expression of MSH2 in prostate adenocarcinoma (PRAD), brain lower-grade glioma (LGG), breast-invasive carcinoma (BRCA), and head and neck squamous cell carcinoma (HNSC) posed a significant correlation with the immune cell infiltration level of patients. Likewise as above, MSH2’s expression comes in a similar trend with tumor immune neoantigens and microsatellite instability. MSH2’s expression in the majority of tumors is a direct factor to the activation of tumor-associated pathways as well as immune-associated pathways. MSH2’s early screening or even therapeutic target role for sarcoma (SARC) diagnosis is contributing to the efficiency of early screening and overall survival in SARC patients.

Transcatheter mitral valve implantation (TMVI) is a promising and minimally invasive treatment for high-risk mitral regurgitation. We aimed to investigate the feasibility of a novel self-expanding valved stent for TMVI via apical access.We designed a novel self-expanding mitral valve stent system consisting of an atrial flange and saddle-shaped ventricular body connected by two opposing anchors and two opposing extensions. During valve deployment, each anchor was controlled by a recurrent string. TMVI was performed in 10 pigs using the valve prosthesis through apical access to verify technical feasibility. Echocardiography and ventricular angiography were used to assess hemodynamic data and valve function. Surviving pigs were killed 4 weeks later to confirm stent deployment.Ten animals underwent TMVI using the novel mitral valve stent. Optimal valve deployment and accurate anatomical adjustments were obtained in nine animals. Implantation failed in one case, and the animal died 1 day later due to stent mismatch. After stent implantation, the hemodynamic parameters of the other animals were stable, and valve function was normal. The mean pressure across the mitral valve and left ventricular outflow tract were 2.98 ± 0.91 mmHg and 3.42 ± 0.66 mmHg, respectively. Macroscopic evaluation confirmed the stable and secure positioning of the stents. No obvious valve displacement, embolism, or paravalvular leakage was observed 4 weeks postvalve implantation.This study demonstrated that the novel mitral valve is technically feasible in animals. However, the long-term feasibility and durability of this valved stent must be improved and verified.

Background. Lung metastasis of malignant tumor signifies worse prognosis and immensely deteriorates patients’ life quality. Spatholobi Caulis (SC) has been reported to reduce lung metastasis, but the mechanism remains elusive. Methods. The active components and corresponding targets of SC were obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) database and the SwissTargetPrediction database. The disease targets were acquired from DisGeNET and GeneCards databases. Venn map was composed to figure out intersection targets by using R. The PPI network was constructed through STRING and Cytoscape, and MCODE plug-in was used to sift hub targets. Gene Ontology (GO)-Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out by utilizing clusterProfiler package (R3.6.1) with adjusted P value