Excellent UV-absorbing cotton fabric with high durability and hydrophobicity based on surface-initiated ATRP of polymerizable organic UV-absorber

Cellulose - Ultraviolet (UV) protective cotton fabric is a convenient and reliable way to protect human body from sunlight. Herein, a polymerizable UV-absorber,...     

Facile fabrication of fast recyclable and multiple self‐healing epoxy materials through diels‐alder adduct cross‐linker

A reversibly cross‐linked epoxy resin with efficient reprocessing and intrinsic self‐healing was prepared from a diamine Diels‐Alder (DA) adduct cross‐linker and a commercial epoxy oligomer. The newly synthesized diamine cross‐linker, comprising a DA adduct of furan and maleimide moieties, can cure epoxy monomer/oligomer with thermal reversibility. The reversible transition between cross‐linked state and linear architecture endows the cured epoxy with rapid recyclability and repeated healability. The reversibly cross‐linked epoxy fundamentally behaves as typical thermosets at ambient conditions yet can be fast reprocessed at elevated temperature like thermoplastics. As a potential reversible adhesive, the epoxy polymer with adhesive strength values about 3 MPa showed full recovery after repeated fracture‐thermal healing processes. The methodology explored in this contribution provides new insights in modification of conventional engineering plastics as functional materials. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 2094–2103     

Existence of multi-bump solutions for a system with critical exponent in RN

We consider the following system with critical exponent in ${\mathbb{R}}^N$:$\{\begin{array}{c}?\mathrm{\Delta }u=K_1(y)u^{2^{?}?1}+\frac{p}{2^{?}}V(y)u^{p?1}{v}^q\text{in}{\mathbb{R}}^N,\hfill \\ ?\mathrm{\Delta }v=K_2(y)v^{2^{?}?1}+\frac{q}{2^{?}}V(y)u^p{v}^{q?1}\text{in}{\mathbb{R}}^N,\hfill \\ u,v>0,y\in {\mathbb{R}}^N,\hfill \end{array}$ where $N\ge 5$, $p,q>1$ and $p+q=2^{?}=\frac{2N}{N?2}$. Using finite dimensional reduction method, we prove the existence of multi-bump solutions. Their bumps can be placed on arbitrarily many or even infinitely many lattice points in ${\mathbb{R}}^N$. Since $p<2$ or $q<2$, we introduce two new norms to avoid singularity.     

A Kriging-based constrained global optimization algorithm for expensive black-box functions with infeasible initial points

In many engineering optimization problems, the objective and the constraints which come from complex analytical models are often black-box functions with extensive computational effort. In this case, it is necessary for optimization process to use sampling data to fit surrogate models so as to reduce the number of objective and constraint evaluations as soon as possible. In addition, it is sometimes difficult for the constrained optimization problems based on surrogate models to find a feasible point, which is the premise of further searching for a global optimal feasible solution. For this purpose, a new Kriging-based Constrained Global Optimization (KCGO) algorithm is proposed. Unlike previous Kriging-based methods, this algorithm can dispose black-box constrained optimization problem even if all initial sampling points are infeasible. There are two pivotal phases in KCGO algorithm. The main task of the first phase is to find a feasible point when there is no feasible data in the initial sample. And the aim of the second phase is to obtain a better feasible point under the circumstances of fewer expensive function evaluations. Several numerical problems and three design problems are tested to illustrate the feasibility, stability and effectiveness of the proposed method.     

An efficient multi-objective PSO algorithm assisted by Kriging metamodel for expensive black-box problems

The huge computational overhead is the main challenge in the application of community based optimization methods, such as multi-objective particle swarm optimization and multi-objective genetic algorithm, to deal with the multi-objective optimization involving costly simulations. This paper proposes a Kriging metamodel assisted multi-objective particle swarm optimization method to solve this kind of expensively black-box multi-objective optimization problems. On the basis of crowding distance based multi-objective particle swarm optimization algorithm, the new proposed method constructs Kriging metamodel for each expensive objective function adaptively, and then the non-dominated solutions of the metamodels are utilized to guide the update of particle population. To reduce the computational cost, the generalized expected improvements of each particle predicted by metamodels are presented to determine which particles need to perform actual function evaluations. The suggested method is tested on 12 benchmark functions and compared with the original crowding distance based multi-objective particle swarm optimization algorithm and non-dominated sorting genetic algorithm-II algorithm. The test results show that the application of Kriging metamodel improves the search ability and reduces the number of evaluations. Additionally, the new proposed method is applied to the optimal design of a cycloid gear pump and achieves desirable results.     

天然气稳态运行优化的混合整数模型及其算法

天然气稳态运行优化问题的难点在于网络结构复杂、规模大、目标函数及约束高度非线性.针对其混合整数非线性规划模型,基于网络约简和线性化技术,建立了线性近似模型,并提出一种新的求解算法.将新算法用于优化我国西部天然气管网系统,结果表明所提算法是有效的.     

A generalized elastic net regularization with smoothed $$\ell _{q}$$ penalty for sparse vector recovery

In this paper, we propose an iterative algorithm for solving the generalized elastic net regularization problem with smoothed \(\ell _{q} (0<q \le 1)\) penalty for recovering sparse vectors. We prove the convergence result of the algorithm based on the algebraic method. Under certain conditions, we show that the iterative solutions converge to a local minimizer of the generalized elastic net regularization problem and we also present an error bound. Theoretical analysis and numerical results show that the proposed algorithm is promising.     

Strong Inhibition of Ice Growth by Biomimetic Crowding Coacervates

The freezing of biological fluids is intensively studied but remains elusive as it is affected not only by the various components but also by the crowding nature of the biological fluids. Herein, we constructed spherical crowders, fibrous crowders, and coacervates by various components ranging from surfactants to polymers and proteins, to mimic three typical crowders in biological fluids, i.e., globular proteins, fibrous networks, and condensates of biomolecules. It is elucidated that the three crowders exhibit low, moderate, and strong ice growth inhibition activity, respectively, resulting from their different abilities in slowing down water dynamics. Intriguingly, the coacervate consisting of molecules without obvious ice growth inhibition activity strongly inhibits ice growth, which is firstly employed as a highly-potent cryoprotectant. This work provides new insights into the survival of freezing-tolerant organisms and opens an avenue for the design of ice-controlling materials.     

A Cyanine-based Liposomal Nanophotosensitizer for Enhanced Cancer Chemo-Photodynamic Therapy

Currently, chemotherapy is one of the most important treatment modalities for malignant tumors in the clinic, however, it exhibits some shortcomings, such as poor selectivity, limited efficacy and serious adverse effects. Therefore, synergistic therapy and accurate drug delivery at tumor sites become a promising strategy for achieving tumor eradication. Herein, a smart NIR fluorescence imaging-guided nanoliposome was fabricated by encapsulating a chemotherapeutic drug(doxorubicin, DOX), liposomes(L) and a near-infrared(NIR) photosensitizer(CY) to form L@CY@DOX, which could realize enhanced therapeutic efficacy of chemo-PDT in cancer therapy(PDT=photodynamic therapy). L@CY@DOX can induce mitochondrial apoptosis and produce severe toxicity at the cellular level, and L@CY@DOX can enrich in the tumor site, which significantly induces tumor death. In vitro and in vivo studies demonstrated that L@CY@DOX exhibited great antitumor efficacy compared with each one of these monotherapies, indicating that the combination of chemotherapy and PDT possessed potential development prospects and is anticipated in clinical application.     

SCN掺杂提高CsPbI3胶体量子点的稳定性和光探测性能

无机卤化物钙钛矿CsPbI₃胶体量子点因其优越的光电性能在光伏和发光器件领域中表现出极大的发展前景。然而,CsPbI₃较差的稳定性阻碍了实际应用。为此,我们采用SCN?离子掺杂CsPbI₃(SCN-CsPbI₃)量子点用于提高量子点的光学性能和稳定性。研究表明,SCN?离子掺杂不仅减少了量子点缺陷、改善了光学性能,还提高了Pb-X键能、量子点结晶质量以及钙钛矿结构稳定性。结果表明,SCN-CsPbI₃量子点的荧光量子产率(PLQY)超过90%,远高于未掺杂原始样品(PLQY为68%)。高的荧光量子产率表明量子点具有较低的缺陷态密度,这归咎于缺陷的减少。空间限制电荷和时间分辨荧光光谱等研究也证实SCN?离子掺杂减少了量子点的缺陷。此外,SCN-CsPbI₃量子点展现出很好的抗水性能,其荧光强度在水中浸泡4 h后依然保持85%的初始值。而未掺杂原始样品的荧光性能很快消失,这是因为水诱导其相变。基于SCN-CsPbI₃量子点的光电探测器表现出宽波域响应(400–700 nm),高的响应率(90 mA·W^?1)和超过1011 Jones的探测度,远高于未掺杂原始量子点探测器的性能(响应率为60 mA·W^?1和探测度为1010 Jones)。