Engineering Nanorobots for Tumor-Targeting Drug Delivery: From Dynamic Control to Stimuli-Responsive Strategy

Nanotechnology has been widely applied to the fabrication of drug delivery systems in the past decades. Recently, with the progress made in microfabrication approaches, nanorobots are steadily becoming a promising means for tumor-targeting drug delivery. In general, nanorobots can be divided into two categories: nanomotors and stimuli-responsive nanorobots. Nanomotors are nanoscale systems with the ability to convert surrounding energies into mechanical motion, whereas stimuli-responsive nanorobots are featured with activatable capacity in response to various endogenous and exogenous stimulations. In this minireview, the dynamic control of nanomotors and the rational design of stimuli-responsive nanorobots are overviewed, with particular emphasis on their contribution to tumor-targeting therapy. Moreover, challenges and perspectives associated with the future development of nanorobots are presented.     

ZnO Nanoplatelets with Controlled Thickness: Atomic Insight into Facet-Specific Bimodal Ligand Binding Using DNP NMR

Colloidal nanoplatelets (NPLs) and nanosheets with controlled thickness have recently emerged as an exciting new class of quantum-sized nanomaterials with substantially distinct optical properties compared to 0D quantum dots. Zn-based NPLs are an attractive heavy-metal-free alternative to the so far most widespread cadmium chalcogenide colloidal 2D semiconductor nanostructures, but their synthesis remains challenging to achieve. The authors describe herein, to the best of their knowledge, the first synthesis of highly stable ZnO NPLs with the atomically precise thickness, which for the smallest NPLs is 3.2 nm (corresponding to 12 ZnO layers). Furthermore, by means of dynamic nuclear polarization-enhanced solid-state ¹⁵N NMR, the original role of the benzamidine ligands in stabilizing the surface of these nanomaterials is revealed, which can bind to both the polar and non-polar ZnO facets, acting either as X- or L-type ligands, respectively. This bimodal stabilization allows obtaining hexagonal NPLs for which the surface energy of the facets is modulated by the presence of the ligands. Thus, in-depth study of the interactions at the organic–inorganic interfaces provides a deeper understanding of the ligand–surface interface and should facilitate the future chemistry of stable-by-design nano-objects.     

煤矿冲击地压与冒顶复合灾害研究

随着煤矿向深部发展,矿井动力灾害既表现出冲击地压的部分特征,又表现出冒顶的部分特征。2种典型的灾害打破以往冒顶与冲击地压的发生具有一种互为逆向性的认知规律,在深部高应力煤巷,特别是留顶煤巷道中出现了相互诱导、复合发生的新灾害类型。在总结山东、山西和新疆矿区典型巷道冲击致顶板(顶煤)动力灾害特征的基础上,提出了深部巷道冲击地压与冒顶复合灾害的概念、机理与分类,指出复合灾害机理关键点在于揭示巷道整体系统和破碎区子系统的稳定原理及其2者间的相互影响。建立了巷道发生复合灾害的力学模型,根据扰动响应失稳判据,提出并得到了巷道发生复合灾害的临界应力Pcr、临界软化区半径ρ_cr和最大容许采扰应力增量σ_max,厘清了灾害发生的主控因素,分析了煤岩冲击倾向指数K、支护强度ps、巷道半径ρ₀、煤岩强度σ_c等对灾害发生的影响规律,同时阐明了围岩塑性软化、破碎深度随地应力增加的发育规律。研究结果表明,破碎发育巷道的动力失稳主体为弹性区、软化区与破碎区构成的不稳定系统,垮落主体为破碎区;稳定的破碎区提升了巷道冲击启动临界值,使其启动难度增大,但破碎区的发育又易引起顶煤垮落;巷道稳定支护是解决复合灾害的关键,科学合理支护既能有效调控围岩破碎防冒,又能提升冲击启动临界值。通过理论研究,揭示了巷道冲击地压与冒顶复合灾害的发生机理,阐明了巷道软化与破碎区及其稳控支护对深部破碎发育巷道动力灾害防治的重要性。     

微型土压平衡盾构机液压系统故障分析

以微型土压平衡(Earth Pressure Balance,EPB)盾构机推进液压系统作为研究对象,介绍了推进系统的工作原理,对混入空气后的油液黏度和有效体积弹性模量进行分析,建立了推进系统数学模型,并对混入不同百分比空气的系统进行仿真运算,得到了液压缸位移响应和速度响应随系统含气量变化的关系。研究表明:随着液压系统空气含量的增加,液压缸位移响应发生迟滞,速度响应变慢,液压缸在运动时产生振动。结合各液压元件工作原理,依次对实际盾构机推进系统元件进行排气,最终排除了液压系统中混入的空气,为实现盾构机平稳推进提供了理论依据。     

基于Matlab的量子激光雷达稳频通信模拟系统设计

传统通信模拟系统设计较为复杂,导致模拟过程消耗能量较大,不能准确模拟稳频通信质量。因此,提出基于Matlab的量子激光雷达稳频通信模拟系统。由于振荡器是雷达形成初始信号源的基础,通过分析振荡电路与相位噪声,获得相位噪声函数与通信频率存在的关系;为确保通信过程的稳定,将准确性与稳定性作为信号质量的评价指标,并采用锁频环稳频技术计算频率偏移程度,根据PID控制算法控制频率,量子激光雷达稳频通信;利用Matlab确定激光器、探测器等硬件组成结构,通过时序与数字阵列的设置完成模拟系统设计。仿真结果表明所提系统结构简便、性能稳定,能够真实模拟出稳频通信的信号质量。     

对大中型钢结构企业生产管理体系的研究分析

以某大型钢结构制造企业为例,通过对产量分布、质量控制、劳动效率等基本数据的分析,研判外协生产管理体系方面存在的问题,从组织形态、管理模式、职能管理等多个维度提出了可行性建议,可为同类型钢结构制造企业提供经验借鉴。     

马尔可夫跳变线性系统最优控制的研究现状与进展

马尔可夫跳变线性系统（MJLS）是一种具有多个模态的随机系统，系统在各个模态之间的跳变转移由一组马尔可夫链来决定。MJLS模型因其在表示过程中可以产生突变而更能精确的描述实际工程应用中的系统。近年来，MJLS的最优控制问题成为了研究的热点，动态规划、极大值原理以及线性矩阵不等式等成为了解决此类问题的主流方法。本文对MJLS最优控制领域的研究现状进行了综述。分别对一般情况下、带有噪声的情况下、带有时滞的情况下以及某些特定情况下的MLJS最优控制问题的国内外研究现状进行论述。最后进行了总结并提出MJLS最优控制领域未来值得关注的研究方向。     

A numerical model to predict the powder–binder separation during micro-powder injection molding

The micro-powder injection molding (micro-PIM) process has the potential to bridge the gap between the design and manufacturing of micro-components that are often used in small and handy devices. Numerical modeling helps to analyze and overcome various difficulties of micro-PIM. In the present work, a numerical model is developed to predict the powder–binder separation (a common defect in PIM and especially severe in micro-PIM) during the injection of an alumina feedstock. A powder–binder separation criterion is proposed dealing with applied injection pressure and friction force between the powder and binder. An indirect comparison of feedstock travel time between two locations is used to validate the model. The predicted segregation from the simulated result is supported by a qualitative experimental measurement. The developed model can be used to optimize injection parameters to get a defect-free product.     

优化GD-模糊规则的滑坡预报模型研究

为了提高滑坡灾害预报准确率，改善传统的滑坡监测和预报中存在的参数选取困难及模糊控制系统作为预报模型精确度不高的问题，首先采用山体结构稳定性分析法进行滑坡灾害参数的选取，得出降雨量、含水率、土压力及岩土表面位移增量作为预报参数的结论；其次将选取的参数作为模糊系统的输入，建立滑坡灾害发生概率模型，并引入优化的GD算法修正预报模型中的动态参数，使模糊控制模型具有自适应性；同时与未优化的模糊控制模型以及单独模糊控制模型进行仿真对比，仿真结果表明，该控制算法收敛速度快，具有很好的收敛性；最后将该模型在某滑坡重点灾区实验区进行实验测试，实验结果显示该模型具有较好的收敛性，且预报精度达到90%。     

基于多边限定的室内定位方法设计与系统实现

随着基于位置服务（Location Based Services，LBS）的发展与智能移动设备的普及，室内定位算法与系统受到了广泛研究与关注。为提高室内定位精度、增强系统鲁棒性，提出了基于多边限定的fingerprint定位方法。基于Wi-Fi RSSI（Received Signal Strength Indication）信号处理建立离线fingerprint数据库；通过对拟合距离-RSSI函数分析，提出了多边限定的方法确定一个最佳参考点（Reference Point，RP）集合，缩小在线定位阶段的搜索范围。在此基础上，再利用fingerprint定位方法进行定位。此外，实现了基于提出方法的室内定位系统原型用于算法性能评估。通过大量真实场景实验分析、验证了相较于传统fingerprint方法，基于多边限定的fingerprint定位方法能有效提高室内定位精度，增强系统鲁棒性。