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将小烛树蜡和日本木蜡分别添加到高油酸葵花籽油中制备凝胶油，分析其在凝胶油形成过程中结晶行为的差异。结果表明：在添加量为5%时，两种蜡均表现出低频率依赖的“强凝胶”行为，小烛树蜡具有更强的热稳定性和表观黏度，日本木蜡则具有更高的触变回复性；热力学性质进一步证实凝胶油性能的差异与天然蜡的成分有关。在微观层面上，小烛树蜡凝胶油和日本木蜡凝胶油分别呈现簇状和针状的晶体形态；小烛树蜡晶型为β′型，而日本木蜡则在形成凝胶油的过程中发生晶体排列堆积方式的改变，晶型由β′型转为β型。日本木蜡具有与高熔点蜡不同的特殊结晶性质，在塑性脂肪开发中具有潜在应用价值。 Candelilla wax(CLW) and Japan lacquer wax(RLW) were added into high-oleic sunflower seed oil to prepare oleogels, and the difference in crystalline behavior during the formation of oleogels was analyzed. The results showed that both the waxes exhibited stable oleogels with low frequency dependence at the dosage of 5%. Candelilla wax had stronger thermal stability and apparent viscosity, while Japan lacquer wax had higher thixotropic recovery. Thermal properties further comfirmed that the difference of oleogels capacity was related to the composition of waxes. At the microscopic level, candelilla wax oleogels and Japan lacquer wax oleogels presented cluster and needle-like crystal morphologies, respectively. The crystal polymorph of candelilla wax was β′, while the crystal arrangement of Japan lacquer wax changed in the process of forming oleogel, and its crystal polymorph turned from β′ to β. Japan lacquer wax had special crystalline properties different from other high-melting point waxes, and had potential application value in the development of plastic fat replacement.

Conventional reinforced concrete shear walls are vulnerable to strong earthquakes with significant residual deformations, which substantially affect structural service and can even lead to structural collapse. Superelastic shape memory alloys (SMAs) are advanced materials that can realize strain recovery upon unloading. If SMAs can be used as reinforcing bars in structures, they can undergo large deformation without permanent deformation. This study presents a complementary and synergistic material system that integrates SMA with damage-tolerant engineered cementitious composites (ECCs) to minimize residual displacement and mitigate concrete damage. This study explored the seismic performance of shear walls using SMA and ECC in the plastic hinge region. Reverse cyclic loading tests were performed on four specimens to demonstrate the feasibility of this method. The specimens included a conventional steel-reinforced concrete shear wall (SW-R-C), steel-reinforced ECC shear wall (SW-R-ECC), SMA-reinforced concrete shear wall (SW-SMA-C), and SMA-reinforced ECC shear wall (SW-SMA-ECC). The results show that the SW-SMA-C specimen exhibited remarkable self-centering capability of more than 85% even after a large deformation, compared to SW-R-C. Furthermore, reduced damage and better ductility were observed in the SW-SMA-ECC specimen in addition to reduced residual displacement. The proposed approach indicated that SMA combined with ECC is more effective in mitigating plastic hinge damage and minimizing residual displacements, which could improve the seismic performance of shear walls. [ABSTRACT FROM AUTHOR]

Romosozumab treatment in women with postmenopausal osteoporosis increases bone formation while decreasing bone resorption, resulting in large BMD gains to reduce fracture risk within 1 yr. DXA-based 3D modeling of the hip was used to assess estimated changes in cortical and trabecular bone parameters and map the distribution of 3D changes in bone parameters over time in patients from 2 randomized controlled clinical trials: FRAME (romosozumab vs placebo followed by denosumab) and ARCH (romosozumab vs alendronate followed by alendronate). For each study, data from a subset of ~200 women per treatment group who had TH DXA scans at baseline and months 12 and 24 and had provided consent for future research were analyzed post hoc. 3D-SHAPER software v2.11 (3D-SHAPER Medical) was used to generate patient-specific 3D models from TH DXA scans. Percentage changes from baseline to months 12 and 24 in areal BMD (aBMD), integral volumetric BMD (vBMD), cortical thickness, cortical vBMD, cortical surface BMD (sBMD), and trabecular vBMD were evaluated. Data from 377 women from FRAME (placebo, 190; romosozumab, 187) and 368 women from ARCH (alendronate, 185; romosozumab, 183) with evaluable 3D assessments at baseline and months 12 and 24 were analyzed. At month 12, treatment with romosozumab vs placebo in FRAME and romosozumab vs alendronate in ARCH resulted in greater increases in aBMD, integral vBMD, cortical thickness, cortical vBMD, cortical sBMD, and trabecular vBMD (P  < .05 for all). At month 24, cumulative gains in all parameters were greater in the romosozumab-to-denosumab vs placebo-to-denosumab sequence and romosozumab-to-alendronate vs alendronate-to-alendronate sequence (P  < .05 for all). 3D-SHAPER analysis provides a novel technique for estimating changes in cortical and trabecular parameters from standard hip DXA images. These data add to the accumulating evidence that romosozumab improves hip bone density and structure, thereby contributing to the antifracture efficacy of the drug. [ABSTRACT FROM AUTHOR]

Although previous studies have made some clear leap in learning latent dynamics from high‐dimensional representations, the performances in terms of accuracy and inference time of long‐term model prediction still need to be improved. In this study, a deep convolutional network based on the Koopman operator (CKNet) is proposed to model non‐linear systems with pixel‐level measurements for long‐term prediction. CKNet adopts an autoencoder network architecture, consisting of an encoder to generate latent states and a linear dynamical model (i.e., the Koopman operator) which evolves in the latent state space spanned by the encoder. The decoder is used to recover images from latent states. According to a multi‐step ahead prediction loss function, the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini‐batch manner. In this manner, gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self‐adaptively tune the latent state space in the training process, and the resulting model is time‐invariant in the latent space. Therefore, the proposed CKNet has the advantages of less inference time and high accuracy for long‐term prediction. Experiments are performed on OpenAI Gym and Mujoco environments, including two and four non‐linear forced dynamical systems with continuous action spaces. The experimental results show that CKNet has strong long‐term prediction capabilities with sufficient precision. [ABSTRACT FROM AUTHOR]

Nanocellulose, as a native renewable material extracted from cellulosic biomass, has gained increased attention in biomedical applications due to its unique physical features, biocompatibility, low toxicity, and modifiable surface chemistry. However, as a candidate for biomedical uses, native nanocellulose still has some limitations, including mechanical properties that are incomparable to those of natural tissues, a lack of biodegradability in vivo, and insufficient cell adhesion support, all of which prevent the widespread use of nanocellulose in the biomedical field. Recently, surface or interface engineering has been advocated as a promising strategy for tailoring the bioactivities and physiochemical properties of native nanocellulose for specific biomedical applications. This review paper focuses on recent advances in nanocellulose surface and/or interface engineering strategies for potential biomedical applications. The features of native nanocellulose that are similar to those of biomaterials have been emphasized. It also proposed a roadmap for the development of nanocellulose-based biomaterials, along with bottlenecks and prospects. This review paper emphasizes a new concept for nanocellulose-based biomaterials development strategies based on nanocellulose surface and interface properties for potential biomedical applications. [ABSTRACT FROM AUTHOR]

To improve the seismic performance of coupled shear walls in high‐rise buildings and to eliminate the problems of large residual deformation and relatively small initial stiffness and damping properties of the traditional viscoelastic coupling beam damper (TVCBD), an innovative shape memory alloy (SMA)‐cable‐controlled self‐centering viscoelastic coupling beam damper (SVCBD) with energy dissipation and self‐centering capabilities was designed and investigated in this study. The construction form and operating principles of the SVCBD were proposed, relevant material performance tests of the cables were performed, and good results were obtained. Finally, the contribution of the SVCBD to seismic mitigation of a 10‐story reinforced concrete coupled shear wall structure was verified by seismic time‐history analyses. The results indicated that compared with TVCBD, SVCBD possesses fuller hysteretic curves, showing stronger energy dissipation capacity, higher initial stiffness, and much smaller residual deformation. The initial strain and cross‐sectional area of the SMA cables and the shear area of the viscoelastic plates affect the energy dissipation and self‐centering performance of SVCBD significantly. The seismic response and post‐earthquake residual deformation of the coupled shear wall structure and the plastic damage of the main components can be effectively controlled by utilizing the proposed SVCBD. [ABSTRACT FROM AUTHOR]

Interest in oleogel as a promising alternative to traditional hydrogenated vegetable oil has increasingly grown in recent years due to its low content of saturated fatty acids and zero trans fatty acids. This study aimed to develop wax-based margarine to replace traditional commercial margarine. The wax-based margarine was prepared and compared with commercial margarine in texture, rheology, and microscopic morphology. The possibility of preparing margarine at room temperature (non-quenched) was also explored. The results showed that the hardness of oleogel-based margarine increased as the BW concentration increased. Denser droplets and crystal network structure were observed with the increase in BW content. XRD patterns of oleogel-based margarine with different content BW were quite similar and structurally to the β′ form. However, the melting temperature of oleogel-based margarine was over 40 °C at each concentration, which represented a poor mouth-melting characteristic. In addition, the unique, improved physical properties of oleogel-based margarine were obtained with binary mixtures of China lacquer wax (ZLW) and Beeswax (BW), due to the interaction of the ZLW and BW crystal network. The rapid cooling process improved the spreadability of oleogel-based margarine. The margarine prepared by 5% BW50:ZLW50 had similar properties to commercial margarine in texture and melting characteristics (37 °C), which had the potential to replace commercial margarine. [ABSTRACT FROM AUTHOR]