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This paper presents a non-uniform curved grid-stiffened shell design method aiming to enhance structural performance using various stiffener patterns, allowing simultaneous optimization of stiffener thickness and stiffener layout. Firstly, the grid-stiffened cell description function is defined using quadratic polynomial functions, comprising the orthogrid, the triangle grid, the rotated triangle grid, and the Kagome grid. Then, the non-uniform stiffener layout description function is established using the sawtooth function, while a filter function is employed to ensure the smooth and continuous of the stiffeners. Moreover, the analytical sensitivity is thoroughly derived, and the optimization problem is formulated. Finally, the effectiveness of the proposed method is demonstrated through three representative optimization examples: the cantilever beam, the special-shaped plate, and the S-shape shell. The study concludes that the proposed method can optimize arbitrary flat plates by embedding the design domain into the background domain. Additionally, the proposed method can be extended to perform stiffener design on complex surfaces by establishing projection relationship between the flat surface and the curved surface. Optimization results indicate that the non-uniform curved grid-stiffened shell design exhibits superior structural performance compared to the uniform grid-stiffened shell design. [ABSTRACT FROM AUTHOR]

The grid-stiffened shell is a promising aerospace structure configuration with high load-carrying capacity. However, it is challenging to fully exploit its optimal load-carrying efficiency. In this paper, an isogeometric analysis-based optimization framework in which the size and layout of stiffeners can be optimized simultaneously is provided to maximize the buckling load of the grid-stiffened shell. Firstly, the grid-stiffened cell is established by the beam-shell coupling model. The high-order continuous isogeometric degenerated shell elements and Timoshenko beam elements are used to simulate the skin and the stiffener, respectively. Owing to the high-order continuous property of isogeometric degenerated shell elements, the sensitivity required for the gradient-based optimization solver can be obtained analytically. Then, the equivalent stiffness coefficients of the grid-stiffened cell are obtained by the asymptotic homogenization method, and the buckling analysis efficiency of the equivalent model is improved by the Rayleigh–Ritz method. Typical illustrative examples are carried out to verify the effectiveness and efficiency of the proposed framework, and the effects of initial stiffener layouts and stiffener heights on the optimization results are discussed in detail. The optimization results indicate that the proposed framework can obtain novel grid-stiffened shells, which significantly outperforms traditional orthogonal grid-stiffened shells in terms of load-carrying capacity. [ABSTRACT FROM AUTHOR]

Much efforts have been made to probe the mechanism underlying ischemic stroke (IS). This study was proposed to uncover the role of long non-coding RNA rhabdomyosarcoma 2 related transcript (RMST) in IS through microRNA-221-3p (miR-221-3p)/phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1)/transforming growth factor-β (TGF-β) axis. Neurological behavioral function, pathological changes in brain tissue, oxidative stress, and inflammation responses in middle cerebral artery occlusion (MCAO) mice were tested. RMST, miR-221-3p, PIK3R1, and TGF-β signaling-related protein expression in brain tissues of MCAO mice were detected. RMST and PIK3R1 were elevated, miR-221-3p was downregulated, and TGF-β pathway was activated in mice after MCAO. Restored miR-221-3p or depleted RMST improved neurological behavioral functions, relieved pathological injury in brain tissue, and repressed oxidative stress and inflammation in mice after MCAO. Depleted PIK3R1 or restored miR-221-3p offsets the negative effects of overexpressed RMST on mice with MCAO. The present work highlights that RMST augments IS through reducing miR-221-3p-mediated regulation of PIK3R1 and activating TGF-β pathway. [ABSTRACT FROM AUTHOR]

Introduction: Cerebral ischemic injury is associated with long-term disability. Dexmedetomidine (Dex) can exert neuroprotective effects on cerebral ischemic/reperfusion injury. The present study explored the mechanism of Dex in cerebral ischemic injury. Materials and methods: To this end, the permanent middle cerebral artery occlusion (p-MCAO) mouse model was established and treated with Dex or/and Nrf2 inhibitor ML385. Subsequently, microglia were subjected to oxygen–glucose deprivation (OGD) in sugar-free environment and thereafter treated with Dex, Nrf2 inhibitor, and NLRP3 lentiviral overexpression vector, respectively. Results: Dex alleviated the neurobehavioral deficit of p-MCAO mice, reduced brain water content, relieved pathological changes, and reduced cerebral infarction size. Dex promoted the polarization of microglia from M1 to M2, thus ameliorating oxidative stress and inflammatory responses. Our results showed that Dex promoted M2-polarization of microglia in vivo and in vitro by promoting HO-1 expression via Nrf2 nuclear import. Moreover, the Nrf2/HO-1 axis inhibited the activation of NLRP2 inflammasome and NLRP3 overexpression reversed the effect of Dex. Conclusion: In conclusion, Dex promoted M2-polarization of microglia and attenuated oxidative stress and inflammation, and thus protected against cerebral ischemic injury by activating the Nrf2/HO-1 pathway and inhibiting NLRP3 inflammasome. [ABSTRACT FROM AUTHOR]

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Stiffened plates are widely used in aerospace structures as load-bearing components. In order to obtain a novel design of stiffened structures with excellent performance, a generative design method of stiffened plates (GDMSP) based on the homogenization method is proposed in this paper, which optimizes the stiffener layout based on an equivalent model. Then, the detailed model can then be obtained by extracting the stiffener path from the discrete distribution of stiffener angles. Moreover, the optimized design can be obtained by size optimization based on the detailed model. Two examples are used to illustrate the proposed framework, including the stiffness maximization of a rectangle stiffener plate and the buckling load maximization of a square stiffener plate. The optimized stiffener configurations are characterized by streamlines and uniform lines, respectively. For the first example, the stiffness of the stiffener design has an improvement of 17%. For the second example, the optimized design improves the buckling load by 35%. Results indicate that the proposed method can effectively provide a novel generative design for stiffened plates. Moreover, the obtained results have a clear stiffener path and have a noticeable improvement in performance, which can be directly used to establish a detailed model. [ABSTRACT FROM AUTHOR]

The accurate result of heuristic models combined by social inspired optimization methods is interesting issue for optimizations of hierarchical stiffened shells (HSS). In this paper, six heuristic combined by social-inspired optimization is compared for both ability and accuracy in optimization of load-carrying capacities of HSS. A three level optimization method is employed as (1) explicit dynamic method to provide the train database of optimization model, (2) six heuristic models including response surface method (RSM), multivariate adaptive regression splines (MARS), Kriging, artificial neural network, radial basis function neural network (RBFNN), and support vector regression (SVR) for approximating load-carrying capacity of HSS and (3) an improved partial swarm optimization (IPSO) to search for the optimum results of HSS. In IPSO as optimizer operator, a random adjusting process is presented to update the positions of particles using best particle by a dynamical bandwidth generated by normal standard distribution. Optimization performances for accuracy and ability of six heuristic models coupled by IPSO are compared for optimum model as maximum load-carrying capacity under mass constraint of HSS. The SVR, Kriging and RSM combined by IPSO can be introduced as efficient and accurate modeling-based optimization method to evaluate the optimum design of HSS. The best optimal result is obtained by RBFNN while the worst optimum result is given using MARS among other models. [ABSTRACT FROM AUTHOR]

Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF–miRNA–gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF–miRNA, miRNA–gene, TF–gene, miRNA–TF, gene–gene and miRNA–miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MG. In addition, the genes, TFs and miRNAs in the CFMSN were also utilized to identify potential drugs. Five related genes, 3 TFs and 13 miRNAs, were extracted from the CFMSN. As the most important TF in the CFMSN, MYC was inferred to play a critical role in MG. Pathway enrichment analysis showed that the genes and miRNAs in the CFMSN were mainly enriched in pathways related to cancer and infections. Furthermore, 21 drugs were identified through the CFMSN, of which estradiol, estramustine, raloxifene and tamoxifen have the potential to be novel drugs to treat MG. The present study provides MG-related TFs by constructing the CFMSN for further experimental studies and provides a novel perspective for new biomarkers and potential drugs for MG. [ABSTRACT FROM AUTHOR]

Undevelopable stiffened curved shells have been widely used in engineering fields. The shape of the undevelopable curved surface is generally characterized with the non-straight generatrix and variable cross sections, which makes it challenging to automatically model and optimize stiffeners on the undevelopable curved surface. Therefore, the data-driven modelling and optimization framework are proposed for undevelopable stiffened curved shells in this paper. Firstly, a novel mesh deformation method is developed for the data-driven modelling of undevelopable stiffened curved shells based on RBF neural network machine learning method. Its main idea is to firstly define a developable curved shell (background mesh domain) having similar topological characteristics with the undevelopable curved shell (target mesh domain), and then train the mapping relationship between the background mesh domain and the target mesh domain by RBF neural network, and finally the complicated modelling problem of the undevelopable stiffened curved shell can be transformed into a simple modelling problem of developable stiffened curved shell by means of the mapping relationship. Moreover, based on the efficient global optimization (EGO) surrogate method, a data-driven layout optimization method is established for minimizing the structural weight of undevelopable stiffened curved shells. Finally, three representative optimization examples are carried out, including modelling and optimization of stiffeners on hyperbolic parabolic curved surfaces, blade-shaped curved surfaces and S-shaped variable cross-sectional curved surfaces. Optimal results indicate that the structural weight of undevelopable stiffened curved shells decreases significantly after the optimization, indicating the effectiveness of the proposed modelling and optimization framework. [ABSTRACT FROM AUTHOR]

In practical engineering, the design scheme is generally a compromise solution that meets various requirements. In most cases, the traditional optimization method provides a single optimized solution, which may be prone to fail during the subsequent design stage because some unpredictable requirements may be not considered in the preliminary optimization process. For example, maximizing fundamental frequency is generally regarded as the optimization objective for aerospace structures under the vibration environment in the preliminary design stage. However, the optimized solution may fail for strength, buckling, or other requirements during the subsequent detailed design stage. Therefore, it is crucial to provide multiple alternative solutions for insurance. In this paper, a diverse discrete material optimization (DDMO) framework is proposed for multi-patch laminates. It can optimize the material topology layout and fiber orientations of composite structures simultaneously and provide multiple alternative solutions that have diversity in design space and different potential performance. In this paper, a diversity index for discrete variables is proposed and the discrete material optimization (DMO) method with the diversity index constraint is employed to perform the DDMO. Two illustrative examples are used to verify the effectiveness of the proposed optimization framework, including a simple example of a composite plate and a complex engineering example of an S-shaped curved shell. Results indicate that, the proposed method can provide multiple diverse alternative solutions with similar performance in the optimization objective, which are verified to have better potential performance than the single solution by the traditional single design method. Moreover, multiple design options by the diverse optimization method can contribute to reducing the probability of redesign and shortening the design cycle. [ABSTRACT FROM AUTHOR]

In this paper, a novel implementation of extrusion constraint in topology optimization is proposed based on Helmholtz-type anisotropic filter approach. The main idea is to set a far larger filter feature size along the extrusion direction than other directions, and thus, the density field is kept constant along the extrusion direction. The Helmholtz-type anisotropic filter can be easily implemented by adding a few more parameters to the isotropic one. Three illustrative examples, including 3D cantilever, spherical frame, and S-shape curved shell, are carried out to verify the effectiveness and robustness of the proposed method. Example results corroborate that the proposed method is suitable for both regular and irregular meshes regardless of geometrical complexity. Compared with the traditional variable mapping method, the proposed method needs less manual setup in the preprocessing of the analysis model for implementing extrusion constraint in topology optimization, which can be easily integrated into the solid isotropic materials with penalization (SIMP) topology optimization or commercial topology optimization software. [ABSTRACT FROM AUTHOR]

Since the high-fidelity model (HFM) of hierarchical stiffened shells is time-consuming, the sampling points based on HFM are generally few, which would result in a certain randomness of the sampling process. In some cases, the prediction accuracy of the variable-fidelity surrogate model (VFSM) is prone to be not robust and reliable. In order to improve the robustness of the prediction accuracy of VFSM, a two-step adaptive updating approach is proposed for the robust establishment of VFSM. In the first step, the leave-one-out (LOO) cross validation is carried out for sampling points of the low-fidelity model (LFM), aiming at finding out those with large prediction error. Then, these points are evaluated by HFM and then added into the original HFM set. In the second step, another LOO cross validation is performed on sampling points of the hybrid bridge function linking HFM and LFM. Based on the Voronoi diagram method, new updating points are chosen from where the largest prediction error of the bridge function lies, and then the VFSM is updated. After above two-step updating process, the VFSM is established. Three simple examples of test functions are firstly presented to verify the effectiveness and efficiency of the proposed method. Further, the proposed method is applied to an engineering example of hierarchical stiffened shells. In order to provide evaluation indexes for prediction accuracy and robustness of VFSM, the VFSM is established by multiple times, and the mean value and the standard deviation of the relative root mean square error (RRMSE) values of the multiple sets of VFSM are calculated. Results indicate that, under the similar computational cost, the mean value and the standard deviation of the RRMSE values of the proposed method decrease by 24.1% and 82.0% than those of the traditional VFSM based on the direct sampling method, respectively. Therefore, the high prediction accuracy and robustness of the proposed method is verified. Additionally, the total computational time of the proposed VFSM decreases by 70% than that of the surrogate model based on HFM when achieving the similar prediction accuracy, indicating the high prediction efficiency of the proposed VFSM. [ABSTRACT FROM AUTHOR]

Treatment of antioxidants is necessary to protect ischemic stroke associated neuronal damage. Xanthohumol (XN), a natural flavonoid extracted from hops, has been reported to have potential function as an antioxidant and can be used for neuro protection. However, the role of XN in ischemic stroke remains unclear. Here, we studied the neuroprotective effects of XN through experimental stroke models. Middle cerebral artery occlusion (MCAO) and oxygen–glucose deprivation (OGD) was used as in vivo and in vitro model, respectively. We found that the treatment of XN improved MCAO-induced brain injury by reducing infarct size, improving neurological deficits, reversing neuronal damage, reducing oxidative stress injury and cell apoptosis. Further experimental studies showed that XN could revive neuronal apoptosis induced by OGD by preventing oxidative stress injury. In addition, our study suggested that these effects were related to the inhibition of phosphorylation of p38-MAPK and the mediation of nuclear Nrf2 activation. In conclusion, the neuroprotective effects of XN showed in this study make XN a promising supplement for ischemic stroke protection. [ABSTRACT FROM AUTHOR]

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy. [ABSTRACT FROM AUTHOR]

For tailoring the non-uniform axial compression, each sub-panel of stiffened shells should be designed separately to achieve a high load-carrying efficiency. Motivated by the challenge caused by numerous variables and high computational cost, a fast procedure for the minimum weight design of non-uniform stiffened shells under buckling constraint is proposed, which decomposes a hyper multi-dimensional problem into a hierarchical optimization with two levels. To facilitate the post-buckling optimization, an efficient equivalent analysis model of stiffened shells is developed based on the Numerical Implementation of Asymptotic Homogenization Method. In particular, the effects of non-uniform load, internal pressure and geometric imperfections are taken into account during the optimization. Finally, a typical fuel tank of launch vehicle is utilized to demonstrate the effectiveness of the proposed procedure, and detailed comparison with other optimization methodologies is made. [ABSTRACT FROM AUTHOR]

In this study, a two-stage optimization framework is proposed for cylindrical or flat stiffened panels under uniform or non-uniform axial compression, which are extensively used in the aerospace industry. In the first stage, traditional sizing optimization is performed. Based on the buckling or collapse-like deformed shape evaluated for the optimized design, the panel can be divided in sub-regions each of which shows characteristic deformations along axial and circumferential directions. Layout optimization is then performed using a stiffener spacing distribution function to represent the location of each stiffener. A layout coefficient is assigned to each sub-region and the overall layout of the panel is optimized. Three test problems are solved in order to demonstrate the validity of the proposed optimization framework: remarkably, the load-carrying capacity improves by 17.4 %, 66.2 % and 102.2 % with respect to the initial design. [ABSTRACT FROM AUTHOR]

A concept of hierarchical stiffened shell is proposed in this study, aiming at reducing the imperfection sensitivity without adding additional weight. Hierarchical stiffened shell is composed of major stiffeners and minor stiffeners, and the minor stiffeners are generally distributed between adjacent major stiffeners. For various types of geometric imperfections, e.g., eigenmode-shape imperfections, hierarchical stiffened shell shows significantly low imperfection sensitivity compared to traditional stiffened shell. Furthermore, a surrogate-based optimization framework is proposed to search for the hierarchical optimum design. Then, two optimum designs based on two different optimization objectives (including the critical buckling load and the weighted sum of collapse loads of geometrically imperfect shells with small- and large-amplitude imperfections) are compared and discussed in detail. The illustrative example demonstrates the inherent superiority of hierarchical stiffened shells in resisting imperfections and the effectiveness of the proposed framework. Moreover, the decrease of imperfection sensitivity can finally be converted into a decrease of structural weight, which is particularly important in the development of large-diameter launch vehicles. [ABSTRACT FROM AUTHOR]