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1.
Simon Neumann Pin Hu Felix Bretschneider Holger Schmalz Andreas Greiner 《大分子材料与工程》2021,306(7):2100090
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. 相似文献
2.
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。 相似文献
3.
Recently, a number of classification techniques have been introduced. However, processing large dataset in a reasonable time has become a major challenge. This made classification task more complex and expensive in calculation. Thus, the need for solutions to overcome these constraints such as field programmable gate arrays (FPGAs). In this paper, we give an overview of the various classification techniques. Then, we present the existing FPGA based implementation of these classification methods. After that, we investigate the confronted challenges and the optimizations strategies. Finally, we highlight the hardware accelerator architectures and tools for hardware design suggested to improve the FPGA implementation of classification methods. 相似文献
4.
5.
Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness. 相似文献
6.
Corey Andrews Yiting Xu Michael Kirberger Jenny J. Yang 《International journal of molecular sciences》2021,22(1)
Calmodulin (CaM) is an important intracellular protein that binds Ca2+ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca2+ concentration through interactions with CaM. 相似文献
7.
Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels. 相似文献
8.
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. 相似文献
9.
Optimization of room-temperature TCR of polycrystalline La0.9-xSrxK0.1MnO3 ceramics by Sr adjustment
Hongjiang Li Kaili Chu Xingrui Pu Xiaohan Yu Xiaoli Guan Shuaizhao Jin Xiang Liu 《Ceramics International》2021,47(1):94-101
High-density La0.9-xSrxK0.1MnO3 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. 相似文献
10.
《Ceramics International》2021,47(18):25574-25579
Vanadium dioxide (VO2) is known as a typical 3d-orbital transition metal oxide exhibiting the metal-to-insulator-transition (MIT) property near room temperature. However, their electronic applications have been challenged by the quality and uniformity of VO2 thin films. In this work, we demonstrate the high sensitivity in the valence charge of vanadium and the MIT properties of the VO2 thin films to the deposition temperature. This observation indicates the necessity to eliminate the inhomogeneity in the temperature distribution of substrate during the vacuum-deposition process of VO2. In addition, a high thermoelectric power factor (PF, e.g., exceeding 1 μWcm−1K−2) was achieved in the metallic phase of the VO2 thin films and this value is comparable to typical organic or oxide thermoelectric materials. We believe this high PF enriches the potential functionality in thermoelectric energy conversions beyond the existing electronic applications of the current vacuum-grown VO2 thin films. 相似文献