56 research outputs found
Numerical study of the fluid fracturing mechanism of granite at the mineral grain scale
Hydraulic fracturing is an essential technique for reservoir stimulation in the process of deep energy exploitation. Granite is composed of different rock-forming minerals and exhibits obvious heterogeneity at the mesoscale, which affects the strength and deformation characteristics of rocks and controls the damage and failure processes. Therefore, in this paper, based on the discrete element fluid-solid coupling algorithm and multiple parallel bond-grain based model (Multi Pb-GBM), a numerical model of a granite hydraulic fracturing test is established to study the evolution of hydraulic fractures in crystalline granite under different ground stress conditions. The main conclusions are as follows. The crack propagation of hydraulic fractures in granite is determined by the in situ stress state, crystal size, and mineral distribution, and the ground stress is the main controlling factor. The final fracture mode affects the maximum principal stress and shear stress, and the generation of cracks changes the distribution of the stress field. The hydraulic fracturing initiation pressure decreases with decreasing crystal size. The influence of the crystal size on the crack inclination angle is mainly reflected in local areas, and the general trend of the fissure dip angle distribution is along the direction of the maximum in situ stress. This study not only has important theoretical significance for clarifying the propagation mechanism of hydraulic fractures but also provides a theoretical basis for deep reservoir reconstruction and energy extraction
Engineering antimicrobial supramolecular polymer assemblies
Antibacterial resistance against conventional antibiotics has emerged as a global health problem. To address this problem, antimicrobial peptides (AMPs) have been recognized as alternatives due to their fast-killing activity and less propensity to induce resistance. Here, the AMPs are engineered via a supramolecular fashion to control and increase their biological performance. The AMPs are modified with ureido-pyrimidinone (UPy) to obtain UPy-AMP monomers, followed by modular self-assembling to realize antibacterial UPy-AMP supramolecular polymers. These positively charged assemblies are illustrated as stable, short fibrous or rod-like UPy-AMP nanostructures with enhanced antibacterial activity and modulable cytotoxicity. Moreover, these antibacterial UPy-AMP assemblies can be internalized by both THP-1 derived macrophages and human kidney cells, which would be an effective potential therapy to deliver the AMPs into mammalian cells to address intracellular infections. Overall, the results present here demonstrate that supramolecular engineering of AMPs provides a powerful tool to enhance the antibacterial activity, modulate cytotoxicity and accelerate the clinical application of AMPs.</p
Engineering antimicrobial supramolecular polymer assemblies
Antibacterial resistance against conventional antibiotics has emerged as a global health problem. To address this problem, antimicrobial peptides (AMPs) have been recognized as alternatives due to their fast-killing activity and less propensity to induce resistance. Here, the AMPs are engineered via a supramolecular fashion to control and increase their biological performance. The AMPs are modified with ureido-pyrimidinone (UPy) to obtain UPy-AMP monomers, followed by modular self-assembling to realize antibacterial UPy-AMP supramolecular polymers. These positively charged assemblies are illustrated as stable, short fibrous or rod-like UPy-AMP nanostructures with enhanced antibacterial activity and modulable cytotoxicity. Moreover, these antibacterial UPy-AMP assemblies can be internalized by both THP-1 derived macrophages and human kidney cells, which would be an effective potential therapy to deliver the AMPs into mammalian cells to address intracellular infections. Overall, the results present here demonstrate that supramolecular engineering of AMPs provides a powerful tool to enhance the antibacterial activity, modulate cytotoxicity and accelerate the clinical application of AMPs.</p
The effect of charge and albumin on cellular uptake of supramolecular polymer nanostructures
Intracellular delivery of functional biomolecules by using supramolecular polymer nanostructures has gained significant interest. Here, various charged supramolecular ureido-pyrimidinone (UPy)-aggregates were designed and formulated via a simple “mix-and-match” method. The cellular internalization of these UPy-aggregates in the presence or absence of serum proteins by phagocytic and non-phagocytic cells, i.e., THP-1 derived macrophages and immortalized human kidney cells (HK-2 cells), was systematically investigated. In the presence of serum proteins the UPy-aggregates were taken up by both types of cells irrespective of the charge properties of the UPy-aggregates, and the UPy-aggregates co-localized with mitochondria of the cells. In the absence of serum proteins only cationic UPy-aggregates could be effectively internalized by THP-1 derived macrophages, and the internalized UPy-aggregates either co-localized with mitochondria or displayed as vesicular structures. While the cationic UPy-aggregates were hardly internalized by HK-2 cells and could only bind to the membrane of HK-2 cells. With adding and increasing the amount of serum albumin in the cell culture medium, the cationic UPy-aggregates were gradually taken up by HK-2 cells without anchoring on the cell membranes. It is proposed that the serum albumin regulates the cellular internalization of UPy-aggregates. These results provide fundamental insights for the fabrication of supramolecular polymer nanostructures for intracellular delivery of therapeutics.</p
Comprehensive analysis of the association between inflammation indexes and complications in patients undergoing pancreaticoduodenectomy
BackgroundDuring clinical practice, routine blood tests are commonly performed following pancreaticoduodenectomy (PD). However, the relationship between blood cell counts, inflammation-related indices, and postoperative complications remains unclear.MethodWe conducted a retrospective study, including patients who underwent PD from October 2018 to July 2023 at the First Hospital of Chongqing Medical University, and compared baseline characteristics and clinical outcomes among different groups. Neutrophil count (NC), platelet count (PLT), lymphocyte count (LC), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and the product of platelet count and neutrophil count (PPN) were derived from postoperative blood test results. We investigated the association between these indicators and outcomes using multivariable logistic regression and restricted cubic spline analysis. The predictive performance of these indicators was assessed by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and decision curve analysis (DCA).ResultA total of 232 patients were included in this study. Multivariate logistic regression and restricted cubic spline analysis showed that all indicators, except for PLT, were associated with clinical postoperative pancreatic fistula (POPF). SII, NLR, and NC were linked to surgical site infection (SSI), while SII, NLR, and PLR were correlated with CD3 complication. PLT levels were related to postoperative hemorrhage. SII (AUC: 0.729), NLR (AUC: 0.713), and NC (AUC: 0.706) effectively predicted clinical POPF.ConclusionIn patients undergoing PD, postoperative inflammation-related indices and blood cell counts are associated with various complications. NLR and PLT can serve as primary indicators post-surgery for monitoring complications
Experimental Study on Mechanical Properties and Failure Laws of Granite with Artificial Flaws under Coupled Static and Dynamic Loads
Rock is the main construction material of rock engineering, such as the engineering of mines and tunnels; in addition, its mechanical properties and failure laws are of great significance to the stability evaluation of rock engineering, especially under the conditions of coupled static–static stresses. In this study, granite specimens were manufactured with artificial flaws. Coupled static and dynamic loads tests were carried out with a modified split Hopkinson pressure bar (SHPB) apparatus; and six typical levels of axial pre-stresses and three crack inclination angles were designed. Three-dimensional digital image correlation (3D-DIC) was also applied to record and analyze the fracturing process and damage evolution of the specimens. The test results show that there was no compaction stage in the stress–strain curve under combined dynamic and static loading. The dynamic strength of the specimens increased first and then decreased with the increase in the static pressure; moreover, the specimens reached the maximum dynamic strength when the static pressure was 10% UCS. The dynamic strength decreased first and then increased with the increase in the crack inclination angle; and the lowest strength appeared when the inclination angle was 45°. The change in axial compression had a significant influence on the failure mode, and the failure mode gradually transformed from shear–tensile failure to shear failure with the increase in the pre-stress. The tensile strain was usually generated at the end of the fractures or near the rock bridge. When the axial pressure was small, the tensile strain zone parallel to the loading direction was easily generated; and when the axial pressure was large, a shear strain zone developed, extending along the diagonal direction. The research results can provide a theoretical reference for the correct understanding of the failure mechanisms of granite and its engineering stability under actual conditions
Multi-Objective Robust Optimization of Integrated Energy System with Hydrogen Energy Storage
A novel multi-objective robust optimization model of an integrated energy system with hydrogen storage (HIES) considering source–load uncertainty is proposed to promote the low-carbon economy operation of the integrated energy system of a park. Firstly, the lowest total system cost and carbon emissions are selected as the multi-objective optimization functions. The Pareto front solution set of the objective function is applied by compromise planning, and the optimal solution among them is obtained by the maximum–minimum fuzzy method. Furthermore, the robust optimization (RO) approach is introduced to cope with the source–load uncertainty effectively. Finally, it is demonstrated that the illustrated HIES can significantly reduce the total system cost, carbon emissions, and abandoned wind and solar power. Meanwhile, the effectiveness of the proposed model and solution method is verified by analyzing the influence of multi-objective solutions and a robust coefficient on the Chongli Demonstration Project in Hebei Province
Adaptive transfer learning for PINN
Physics-informed neural networks (PINNs) have shown great potential in solving computa-tional physics problems with sparse, noisy, unstructured, and multi-fidelity data. However, the training of PINN remains a challenge, and PINN is not robust to deal with some com-plex problems, such as the sharp local gradient in broad computational domains, etc. Transfer learning techniques can provide fast and accurate training for PINN through in-telligent initialization, but the previous researches are much less effective when dealing with transfer learning cases with a large range of parameter variation, which also suffers from the same drawbacks. This manuscript develops the concept of the minimum energy path for PINN and proposes an adaptive transfer learning for PINN (AtPINN). The Partial Differential Equations (PDEs) parameters are initialized by the source parameters and up-dated adaptively to the target parameters during the training process, which can guide the optimization of PINN from the source to the target task. This process is essentially per-formed along a designed low-loss path, which is no barrier in the energy landscape of neural networks. Consequently, the stability of the training process is guaranteed. AtPINN is utilized to achieve transfer learning cases with a large range of parameter variation for solving five complex problems. The results demonstrate that AtPINN has promising po-tential for extending the application of PINN. Besides, three transfer learning cases with different ranges of parameter variation are analyzed through visualization. Furthermore, results also show that the idea of adaptive transfer learning can be a particular optimiza-tion strategy to directly solve problems without intelligent initialization. & COPY; 2023 Elsevier Inc. All rights reserved
Numerical Investigation of a Hydrosplitting Fracture and Weak Plane Interaction Using Discrete Element Modeling
Water inrush caused by hydrosplitting is an extremely common disaster in the engineering of underground tunnels. In this study, the propagation of fluid-driven fractures based on an improved discrete element fluid-solid coupling method was modeled. First, the interactions between hydrosplitting fractures (HFs) and preexisting weak planes (WPs) with different angles were simulated considering water pressure in the initial fracture. Second, the influence of the in situ stress ratio and the property of WPs were analyzed, and corresponding critical pressure values of different interactions were calculated. Lastly, the maximum principal stress and maximum shear stress variation inside the pieces were reproduced. The following conclusions can be drawn: (1) Five different types of interaction modes between HFs and natural WPs were obtained, prone to crossing the WPs under inclination of 90°. (2) The initiation pressure value decreased with an increased in situ stress ratio, and the confining stress status had an effect on the internal principal stress. (3) During HFs stretching in WPs with a high elastic modulus, the value of the maximum principal stress was low and rose slowly, and the maximum shear stress value was smaller. Through comprehensive analysis, the diversity of the principal stress curves is fundamentally determined by the interaction mode between HFs and WPs, which are influenced by the variants mentioned in the paper. The analysis provides a better guideline for understanding the failure mechanism of water gushing out of deep buried tunnel construction and cracking seepage of high head tunnels
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