Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Statistical Piezotronic Effect in Nanocrystal Bulk by Anisotropic Geometry Control

Utilizing inner-crystal piezoelectric polarization charges to control carrier transport across a metal-semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano-electromechanical system (MEMS/NEMS), human-machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress-induced piezo-potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m⁻¹ MPa⁻¹ and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.     

Synergistic effect of bulk phase doping and layered-spinel structure formation on improving electrochemical performance of Li-Rich cathode material

In this study, La was doped into the lithium layer of Li-rich cathode material and formed a layered-spinel hetero-structure. The morphology, crystal structure, element valence and kinetics of lithium ion migration were studied by field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy (EIS). The La doped lithium-rich cathode material exhibited similar initial discharge capacity of 262.8 mAh g^?1 at 0.1 C compared with the undoped material, but the discharge capacity retention rate can be obviously improved to 90% after 50 cycles at 1.0 C. Besides that, much better rate capability and Li⁺ diffusion coefficient were observed. The results revealed that La doping not only stabilized the material structure and reduced the Li/Ni mixing degree, but also induced the generation of spinel phase to provide three-dimensional diffusion channels for lithium ion migration. Moreover, the porous structure of the doped samples also contributed to the remarkable excellent electrochemical performance. All of these factors combined to significantly improve the electrochemical performance of the material.     

Novel TiC-based composites with enhanced mechanical properties

Novel TiC-based composites were synthesized by reactive hot-pressing at 1800 °C for 1 h with ZrB₂ addition as a sintering aid for the first time. The effects of ZrB₂ contents on the phase composition, microstructure evolution, and mechanical properties were reported. Based on the reaction and solid solution coupling effects between ZrB₂ and TiC, the product ZrC may be partially or completely dissolved into the TiC matrix, and then phase separation within the miscibility gap is observed to form lamellar nanostructured ZrC-rich (Zr, Ti)C. The TiC-10 mol.% ZrB₂ (starting batch composition) exhibits good comprehensive mechanical properties of hardness 27.7 ± 1.3 GPa, flexural strength 659 ± 48 MPa, and fracture toughness of 6.5 ± 0.6 MPa m^1/2, respectively, which reach or exceed most TiC-based composites using ceramics as sintering aids in the previous reports.     

Mechanical Properties of Single-Layer Diamond Reinforced Poly(vinyl alcohol) Nanocomposites through Atomistic Simulation

Low-dimensional carbon nanostructures are ideal nanofillers to reinforce the mechanical performance of polymer nanocomposites due to their excellent mechanical properties. Through molecular dynamics simulations, the mechanical performance of poly(vinyl alchohol) (PVA) nanocomposites reinforced with a single-layer diamond – diamane is investigated. It is found the PVA/diamane exhibits similar interfacial strengths and pull-out characteristics with the PVA/bilayer-graphene counterpart. Specifically, when the nanofiller is fully embedded in the nanocomposite, it is unable to deform simultaneously with the PVA matrix due to the weak interfacial load transfer efficiency, thus the enhancement effect is not significant. In comparison, diamane can effectively promote the tensile properties of the nanocomposite when it has a laminated structure as it deforms simultaneously with the matrix. With this configuration, the interlayer sp³ bonds endows diamane with a much higher resistance under compression and shear tests, thus the nanocomposite can reach very high compressive and shear stress. Overall, enhancement on the mechanical interlocking at the interface as triggered by surface functionalization is only effective for the fully embedded nanofiller. This work provides a fundamental understanding of the mechanical properties of PVA nanocomposites reinforced by diamane, which can shed lights on the design and preparation of next generation high-performance nanocomposites.     

Prevention of breast cancer by dietary polyphenols—role of cancer stem cells

Abstract

Breast cancer is a common malignancy with poor prognosis. Cancer cells are heterogeneous and cancer stem cells (CSCs) are primarily responsible for tumor relapse, treatment-resistance and metastasis, so for breast cancer stem cells (BCSCs). Diets are known to be associated with carcinogenesis. Food-derived polyphenols are able to attenuate the formation and virulence of BCSCs, implying that these compounds and their analogs might be promising agents for preventing breast cancer. In the present review, we summarized the origin and surface markers of BCSCs and possible mechanisms responsible for the inhibitory effects of polyphenols on BCSCs. The suppressive effects of common dietary polyphenols against BCSCs, such as curcumin, epigallocatechin gallate (EGCG) and related polyphenolic compounds were further discussed.     

离子液体体系卤水提锂的洗涤工艺研究

溶剂萃取法是盐湖提锂的重要工艺方法。采用磷酸三丁酯（TBP）/1-丁基-3-甲基咪唑双三氟甲基磺酰亚胺盐（[C₄mim][NTf₂]）离子液体体系对高镁锂比盐湖卤水中的锂进行萃取分离提取实验,对负载有机相的洗涤和反萃过程进行了研究。萃取实验：在TBP与[C₄mim][NTf₂]体积比为9∶1、相比（有机相与水相的体积比）为2∶1条件下,锂离子与其他离子的分离系数分别为β（锂/钠）=94.70、β（锂/钾）=148.85、β（锂/镁）=131.81。洗涤实验：系统考察了洗涤剂种类及浓度、相比、洗涤次数等因素对杂质离子洗脱率的影响,结果发现氯化锂和盐酸的混合溶液是从负载有机相中洗涤除去杂质离子的有效洗涤剂。洗涤过程适宜条件：洗涤剂中氯化锂浓度为4 mol/L、盐酸浓度为0.5 mol/L,相比为5∶1,洗涤次数为2次。反萃实验：用稀盐酸（1.0 mol/L）对负载有机相进行反萃取,在相比为1∶1条件下,单级反萃率达到97.81%。研究表明,离子液体体系作为一种新型萃取体系,在高镁锂比盐湖卤水中提取锂具有较好的应用前景。     

钢渣热焖工艺及其对水泥性能的影响

本文研究了不同的热焖压力和时间对钢渣活性的影响和钢渣的不同掺量对水泥性能的影响.热焖工艺主要改善的是钢渣的膨胀性,熟料的7 d膨胀率为0.034％,未热焖的钢渣掺入15％和35％时膨胀率分别增加155.9％和311.8％,而1 MPa 1 h热焖后,相比于未热焖的情况,钢渣掺入15％和35％时分别降低77.0％、89.3％,钢渣掺量25％时,其3 d、7 d、28 d 抗压强度分别增加8. 0 MPa、3.6 MPa、2.7 Mpa,分别提高21.1％ 、11. 3％ 、6. 1％.     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.