The deformation process of landslide displacement has complex nonlinear characteristics. In view of the problems of large error, slow convergence and poor stability of the traditional neural network ...prediction model, in order to better realize the accurate and effective prediction of landslide displacement, this research proposes a landslide displacement prediction model based on Genetic Algorithm (GA) optimized Elman neural network. This model combines the GA with the Elman neural network to optimize the weights, thresholds and the number of hidden neurons of the Elman neural network. It gives full play to the dynamic memory function of the Elman neural network, overcomes the problems that a single Elman neural network can easily fall into local minimums and the neuron data is difficult to determine, thereby effectively improving the prediction performance of the neural network prediction model. The displacement monitoring data of a slow-varying landslide in the Guizhou karst mountainous area are selected to predict and verify the landslide displacement, and the results are compared with the traditional Elman neural network prediction results. The results show that the prediction results of GA-Elman model are in good agreement with the actual monitoring data of landslide. The average error of the model is low and the prediction accuracy is high, which proves that the GA-Elman model can play a role in the prediction of landslide displacement and can provide reference for the early warning of landslide displacement deformation.
Lung cancer is a leading cause of cancer mortality worldwide, with a 5-year survival rate of less than 20%. Gambogic acid (GA) is a naturally occurring and potent anticancer agent that destroys tumor ...cells through multiple mechanisms. According to the literature, one of the most potent inhibitors of caspases and apoptosis currently known is the X-linked Inhibitor of Apoptosis Protein (XIAP). It is highly expressed in various malignancies but has little or no expression in normal cells, making it an attractive target for cancer treatment. Here we report the development of a chitosan (CS)-based cationic nanoemulsion-based pulmonary delivery (p.d.) system for the co-delivery of antineoplastic drugs (GA) and anti-XIAP small interfering RNA (siRNA). The results showed that the chitosan-modified cationic nanoemulsions could effectively encapsulate gambogic acid as well as protect siRNA against degradation. The apoptosis analysis confirmed that the cationic nanoemulsions could induce more apoptosis in the A549 cell line. In addition, most drugs and siRNAs have a long residence time in the lungs through pulmonary delivery and show greater therapeutic effects compared to systemic administration. In summary, this work demonstrates the applicability of cationic nanoemulsions for combined cancer therapy and as a promising approach for the treatment of lung cancer.
The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of ...geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.
The injection of carbon dioxide (CO2) into gas reservoirs has become an important way to enhance gas recovery and reduce CO2 emissions. Large discrepancies are observed when predicting natural gas ...compressibility factors with high CO2 content by several well-known empirical correlations. An explicit correlation is proposed to improve the prediction accuracy in the estimation of compressibility factors on condensate gases with variable CO2 contents. The analysis of the results is carried out on the basis of 202 experimental data from 9 various mixtures of natural gases. The results show that relative deviations of compressibility factors predicted by conventional empirical correlations increase with the increase in CO2 mole fraction with an average error of 8%. The average error of the new method is less than 4%. The effect of compressibility factors on the estimations of dynamic reserves is studied and the compressibility factor causes a 3% reduction in dynamic reserves estimation. The proposed correlation has fewer uncertainties and more accurate results than other correlations that involve the iterative process in calculating compressibility factors of natural gases with variable CO2 contents.
The development of heavy oil reservoirs in China is of great significance to safeguard national energy security, but great challenges are faced due to the complex and heterogeneous reservoir ...properties. Inter-well connectivity analysis is critical to enhancing the development performance, as it is a good way to interpret fluid flow and provides a theoretical basis for injection-production optimization. Data-driven deep learning methods have been widely used in reservoir development and can be employed to develop surrogate models of injection and production and to infer inter-well connectivity. In this study, the model performance of a recurrent neural network (RNN) and its four variants were evaluated and compared in a temporal production prediction. The comparison results showed that bidirectional gated recurrent unit (Bi-GRU) is the optimal algorithm with the highest accuracy of 0.94. A surrogate model was established to simulate the inter-well connectivity of steam-assisted gravity drainage (SAGD) in the research area by utilizing the Bi-GRU algorithm. A global sensitivity analysis method, Fourier amplitude sensitivity testing (FAST), was introduced and combined with the surrogate model to explain the influence of the input variables on the output variables by quantitatively calculating the sensitivity of each variable. Quantitative results for the inter-well connectivity of SAGD were derived from the sensitivity analysis of the proposed method, which was effectively applied to typical linear patterns and five-spot patterns. Inter-well connectivity varied from 0.1 to 0.58 in test applications, and mutual corroboration with previous geological knowledge can further determine the distribution of the interlayer in the reservoir. The workflow proposed in this study provides a new direction for analyzing and inferring the inter-well connectivity of SAGD in Northeast China heavy oil reservoirs.
Based on the multi-element monitoring of landslide, this paper adopts the GNSS technology to build the three-dimensional space monitoring system to research the landslide multi-element three- ...dimensional space monitoring technology. Through collecting the rainfall, soil moisture content, slope, pore water pressure, stress, single point surface deformation etc, the system has many key technologies such as multi-parameter, information acquisition, data fusion analysis and real-time early warning of landslides and integrate various elements by using the professional technology. This research provides an important reference for the landslide disaster prevention.
Brace root architecture is a critical determinant of maize’s stalk anchorage and nutrition uptake, influencing root lodging resistance, stress tolerance, and plant growth. To identify the key ...microRNAs (miRNAs) in control of maize brace root growth, we performed small RNA sequencing using brace root samples at emergence and growth stages. We focused on the genetic modulation of brace root development in maize through manipulation of miR390 and its downstream regulated auxin response factors (ARFs). In the present study, miR167, miR166, miR172, and miR390 were identified to be involved in maize brace root growth in inbred line B73. Utilizing short tandem target mimic (STTM) technology, we further developed maize lines with reduced miR390 expression and analyzed their root architecture compared to wild-type controls. Our findings show that STTM390 maize lines exhibit enhanced brace root length and increased whorl numbers. Gene expression analyses revealed that the suppression of miR390 leads to upregulation of its downstream regulated ARF genes, specifically ZmARF11 and ZmARF26, which may significantly alter root architecture. Additionally, loss-of-function mutants for ZmARF11 and ZmARF26 were characterized to further confirm the role of these genes in brace root growth. These results demonstrate that miR390, ZmARF11, and ZmARF26 play crucial roles in regulating maize brace root growth; the involved complicated molecular mechanisms need to be further explored. This study provides a genetic basis for breeding maize varieties with improved lodging resistance and adaptability to diverse agricultural environments.
The occurrence of pool fires adjacent to a sidewall poses significant risks. To investigate fire source combustion characteristics and thermal feedback of sidewall-attached fires, experiments ...involving rectangular heptane pool fires with varying aspect ratios and pool orientation relative to sidewall were conducted. The flame tilting behavior, temperature near sidewall, thermal transfer process and air entrainment effects of rectangular pool fires were studied. The findings show that triangular flame shape in parallel arrangements and flame separation of perpendicular setups attribute to the unbalanced air entrainment near sidewall. Perpendicular pools lead to lower temperatures near sidewall surface caused by flame separation. The mass loss rate (MLR) of parallel pool fires initially decreases with n driven by thermal radiation from the flame. It is followed by an increase due to thermal conduction and thermal radiation through the sidewall, with a threshold value at n = 3. The MLR of perpendicular pools decreases continuously owing to the dominance of total thermal radiation. Finally, based on the air entrainment theory, a quantitative correlation between the flame height and n relative to sidewall is proposed. This is also validated by experimental and previous research data.
The TAGAP gene locus has been linked to several infectious diseases or autoimmune diseases, including candidemia and multiple sclerosis. While previous studies have described a role of TAGAP in T ...cells, much less is known about its function in other cell types. Here we report that TAGAP is required for Dectin-induced anti-fungal signaling and proinflammatory cytokine production in myeloid cells. Following stimulation with Dectin ligands, TAGAP is phosphorylated by EPHB2 at tyrosine 310, which bridges proximal Dectin-induced EPHB2 activity to downstream CARD9-mediated signaling pathways. During Candida albicans infection, mice lacking TAGAP mount defective immune responses, impaired Th17 cell differentiation, and higher fungal burden. Similarly, in experimental autoimmune encephalomyelitis model of multiple sclerosis, TAGAP deficient mice develop significantly attenuated disease. In summary, we report that TAGAP plays an important role in linking Dectin-induced signaling to the promotion of effective T helper cell immune responses, during both anti-fungal host defense and autoimmunity.
Software-defined network separates the control plane and the data plane, making the network more flexible. With the expansion of the network scale, one centralized controller cannot meet the latency ...needs of large-scale networks. Therefore, it is necessary to use multicontroller architecture, which has some problems with the controller placement. In this article, we take both the average latency and the worst latency between switch and controller into consideration and make a multi-objective optimization model. An improved label propagation algorithm based on traffic gravitation is proposed to solve the subdomain division problem, and a heuristic method is for subdomain controller placement. The simulation experiments show the effectiveness of the proposed algorithm and the time complexity guarantee for large-scale networks.
PDF
