Topology optimization of flexure hinges with a prescribed compliance matrix based on the adaptive spring model and stress constraint

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.     

Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.     

Blends of Bio-Based Poly(Limonene Carbonate) with Commodity Polymers

In this study, blends of the bio-based poly(limonene carbonate) (PLimC) with different commodity polymers are investigated in order to explore the potential of PLimC toward generating more sustainable polymer materials by reducing the amount of petro- or food-based polymers. PLimC is employed as minority component in the blends. Next to the morphology and thermal properties of the blends the impact of PLimC on the mechanical properties of the matrix polymers is studied. The interplay of incompatibility and zero-shear melt viscosity contrast determines the blend morphology, leading for all blends to a dispersed droplet morphology for PLimC. Blends with polymers of similar structure to PLimC (i.e., aliphatic/aromatic polyester) show the best performance with respect to mechanical properties, whereas blends with polystyrene or poly(methyl methacrylate) are too brittle and polyamide 12 blends show very low elongations at break. In blends with Ecoflex (poly(butylene adipate-co-terephthalate)) and Arnitel EM400 (copoly(ether ester)) with poly(butylene terephthalate) hard and polytetrahydrofuran soft segments) a threefold increase in E-modulus can be achieved, while keeping the elongation at break at reasonable high values of ≈200%, making these blends highly interesting for applications.     

高稳高效海上风电安装平台关键制造技术研究

海上风电作为可再生清洁能源之一,受到世界各国的高度重视与大力发展。我国将海上风电提升至解决能源危机、减缓气候变化、调整能源结构的国家战略高度,到2030年我国单位国内生产总值二氧化碳排放将比2005年下降65%以上,非化石能源占一次能源消费比重将达到25%左右。安装平台不足将是我国海上风电场无法如期建成投产的主要障碍。对自升自航式海上风电安装平台系列高端装备及其设计制造的三大技术难题——腿站立作业易“失稳”、大平台大跨距大倾覆力矩自升易“失控”、高空吊装巨型叶片逾百螺栓精准定位易“失准”,以及焊缝缺陷修复和局部裂纹损伤的激光锻造修复再制造进行了介绍,研制的具有不同规格的系列装备在中国、英国、丹麦、德国等国家的著名海上风电场建设应用情况良好。     

药物相互作用研究在新药研发和审评决策中的应用

药物相互作用改变了剂量效应关系，可能会降低疗效或增加毒性，是临床应用中合并用药治疗时重要的考虑因素。预测具有临床意义的药物相互作用是药物研发过程中获益风险评估的重要环节。本文概述了药物研发过程中药物相互作用研究的目的和意义，体内和体外研究的主要内容；梳理分析了2020年国家药品监督管理局（National Medical Products Administration, NMPA）和美国食品药品监督管理局（Food and Drug Administration, FDA）批准上市的新药药物相互作用研究情况，旨在为我国药物研发过程中药物相互作用研究及其监管审评提供参考。     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Modeling Sialidosis with Neural Precursor Cells Derived from Patient-Derived Induced Pluripotent Stem Cells

Sialidosis, caused by a genetic deficiency of the lysosomal sialidase gene (NEU1), is a systemic disease involving various tissues and organs, including the nervous system. Understanding the neurological dysfunction and pathology associated with sialidosis remains a challenge, partially due to the lack of a human model system. In this study, we have generated two types of induced pluripotent stem cells (iPSCs) with sialidosis-specific NEU1^G227R and NEU1^V275A/R347Q mutations (sialidosis-iPSCs), and further differentiated them into neural precursor cells (iNPCs). Characterization of NEU1^G227R- and NEU1^V275A/R347Q- mutated iNPCs derived from sialidosis-iPSCs (sialidosis-iNPCs) validated that sialidosis-iNPCs faithfully recapitulate key disease-specific phenotypes, including reduced NEU1 activity and impaired lysosomal and autophagic function. In particular, these cells showed defective differentiation into oligodendrocytes and astrocytes, while their neuronal differentiation was not notably affected. Importantly, we found that the phenotypic defects of sialidosis-iNPCs, such as impaired differentiation capacity, could be effectively rescued by the induction of autophagy with rapamycin. Our results demonstrate the first use of a sialidosis-iNPC model with NEU1^G227R- and NEU1^V275A/R347Q- mutation(s) to study the neurological defects of sialidosis, particularly those related to a defective autophagy–lysosome pathway, and may help accelerate the development of new drugs and therapeutics to combat sialidosis and other LSDs.     

Achieving fabrication of highly transparent Y2O3 ceramics via air pre-sintering by deionization treatment of suspension

An easy albeit quite effective deionization suspension treatment was adopted to alleviate the detrimental effects related to the hydrolysis of Y₂O₃ in an aqueous medium. Fabrication of highly transparent Y₂O₃ ceramics with a fine grain size via air pre-sintering and post–hot isostatic pressing (HIP) treatment without using any sintering additive was achieved using the treated suspensions. The hydrolysis issue of Y₂O₃ powder in an aqueous medium was effectively alleviated by using deionization treatment, and a well-dispersed suspension with a low concentration of dissolved Y³⁺ species was obtained. The dispersed suspensions were consolidated by the centrifugal casting method, and the green bodies derived from the suspension of 35.0 vol% solid loading showed an improved homogeneity with a relative density of 52.1%. Fully dense Y₂O₃ transparent ceramic with high transparency was obtained by pre-sintering consolidated green compacts at a low temperature of 1400°C for 16 h in air followed by a post-HIP treatment at 1550°C for 2 h under 200 MPa pressure. The sample had a fine average grain size of 690 nm. The in-line transmittance of the sample reached 83.3% and 81.8% at 1100 nm and 800 nm, respectively, very close to the theoretical values of Y₂O₃.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

Optimization of room-temperature TCR of polycrystalline La0.9-xSrxK0.1MnO3 ceramics by Sr adjustment

High-density La_0.9-xSr_xK_0.1MnO₃ ceramics (LSKMO, A-site = La, Sr and K, 0 ≤ x ≤ 0.25) are successfully fabricated by using facile sol-gel method. Electrical properties are performed by using combination of phenomenological percolation (PP) model, double exchange (DE) mechanism, and Jahn-Teller (JT) effect. Moreover, X-ray diffraction and scanning electron microscopy are employed to analyze the structure and morphology of LSKMO ceramics. Valence states and ionic stoichiometry are assessed by using X-ray photoemission spectrometry. Results reveal that Sr²⁺ ions, substituting La³⁺ ions, significantly influenced DE mechanism and JT effect. In addition, Sr-doping plays essential role in improving electrical properties of LSKMO ceramics. At optimal doping content of x = 0.09, peak temperature coefficient of resistance (TCR) of the resistivity is found to be 11.56% K^?1 at 297.15 K, which is optimal TCR for A-site K-occupied perovskite manganese oxides. These results confirm that polycrystalline LSKMO ceramics render high room-temperature TCR values due to Sr-doping.