Electrorheological Elastomers

Electrorheological elastomers (EREs) are smart elastomers with tunable dynamic properties by applying electric field. They are composed by polarizable particles dispersing within elastomers matrix. In comparison with electrorheological fluids, the particles in EREs do not undergo aggregation and sedimentation. Without the requirement of large-sized electromagnetic coils, the smart devices based on EREs have simpler structures than those based on magnetorheological (MR) elastomers. The unique properties and merits of EREs give rise to their bright future in various fields. During the past decades, great progress has been made by scholars around the world. In this chapter, the conception, preparation, physical mechanisms, classification, development, influence factors, and applications of electrorheological elastomers is reviewed

OPTIMIZING PREPARATION CONDITIONS OF ULTRA-LOW-DENSITY FIBERBOARD BY RESPONSE SURFACE METHODOLOGY

Preparation conditions of ultra-low-density fiberboard (ULDF) were optimized using the Box–Behnken design and response surface methodology. The effect and interactions of Si-Al molar ratio, additive amount of Si sol, and additive amount of Si-Al compounds on internal bond strength of ULDF were investigated. The regression model for ULDF preparation was significant ( p < 0.0001), and the Si-Al molar ratio and the additive amount of Si sol had a significant effect on internal bond strength, whereas the additive amount of Si-Al compounds did not. Optimum internal bond strength (12.68 ± 0.35 KPa) was achieved at 500 mL Si-Al compounds with Si-Al molar ratio of 2:1 and 20 mL Si sol. Fourier transform infrared spectra of the ULDF confirmed that some covalent bonds between Si-Al additives and fibers might be formed, and the thermal conductivity, noise reduction coefficient, and contact angle analysis of ULDF further confirmed the validity of the optimal preparation conditions

Phenylboronic acid-diol crosslinked 6-<i>O</i>-vinylazeloyl-d-galactose nanocarriers for insulin delivery

A new block polymer named poly 3-acrylamidophenylboronic acid-b-6-O–vinylazeloyl-d-galactose (p(AAPBA-b-OVZG)) was prepared using 3-acrylamidophenylboronic acid (AAPBA) and 6-O-vinylazeloyl-D-galactose (OVZG) via a two-step procedure involving S-1-dodecyl-S-(α', α'-dimethyl-α″-acetic acid) trithiocarbonate (DDATC) as chain transfer agent, 2,2-azobisisobutyronitrile (AIBN) as initiator and dimethyl formamide (DMF) as solvent. The structures of the polymer were examined by Fourier transform infrared spectroscopy (FT-IR) and 1H NMR and the thermal stability was determined by thermal gravimetric analysis (TG/DTG). Transmission electron microscopy (TEM) and dynamic light scattering (DLS) were utilized to evaluate the morphology and properties of the p(AAPBA-b-OVZG) nanoparticles. The cell toxicity, animal toxicity and therapeutic efficacy were also investigated. The results indicate the p(AAPBA-b-OVZG) was successfully synthesized and had excellent thermal stability. Moreover, the p(AAPBA-b-OVZG) nanoparticles were submicron in size and glucose-sensitive in phosphate-buffered saline (PBS). In addition, insulin as a model drug had a high encapsulation efficiency and loading capacity and the release of insulin was increased at higher glucose levels. Furthermore, the nanoparticles showed a low-toxicity in cell and animal studies and they were effective at decreasing blood glucose levels of mice over 96 h. These p(AAPBA-b-OVZG) nanoparticles show promise for applications in diabetes treatment using insulin or other hypoglycemic proteins

Cost Forecasting Model of Transmission Project based on the PSO-BP Method

In order to solve being sensitive to the initial weights, slow convergence, being easy to fall into local minimum and other problems of the BP neural network, this paper introduces the Particle Swarm Optimization (PSO) algorithm into the Artificial Neural Network training, and construct a BP neural network model optimized by the particle swarm optimization. This method can speed up the convergence and improve the prediction accuracy. Through the analysis of the main factors on the cost of transmission line project, dig out the path and lead factors, topography and meteorological factors, the tower and the tower base materials and other factors. Use the PSO-BP model for the cost forecasting of transmission line project based on historical project data. The result shows that the method can predict the cost effectively. Compared with the traditional BP neural network, the method can predict with higher accuracy, and can be generalized and applied in cost forecasting of actual projects

Noninteractive Verifiable Outsourcing Algorithm for Bilinear Pairing with Improved Checkability

It is well known that the computation of bilinear pairing is the most expensive operation in pairing-based cryptography. In this paper, we propose a noninteractive verifiable outsourcing algorithm of bilinear pairing based on two servers in the one-malicious model. The outsourcer need not execute any expensive operation, such as scalar multiplication and modular exponentiation. Moreover, the outsourcer could detect any failure with a probability close to 1 if one of the servers misbehaves. Therefore, the proposed algorithm improves checkability and decreases communication cost compared with the previous ones. Finally, we utilize the proposed algorithm as a subroutine to achieve an anonymous identity-based encryption (AIBE) scheme with outsourced decryption and an identity-based signature (IBS) scheme with outsourced verification

Brown adipocytes can display a mammary basal myoepithelial cell phenotype in vivo

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13030000) and the CAS-Novonordisk Foundation, as well as grants from the ‘1000 talents’ recruitment program, and a ‘Great-wall professorship’ from the CAS-Novonordisk Foundation all to JRS. We are grateful to all the members of Molecular Energetics Group for their support and discussion of the results. We would like to thank the Center for Biological Imaging from Institute of Biophysics Chinese Academy of Sciences and Professor Zhaohui Wang's Lab from Institute of Genetics and Developmental Biology Chinese Academy of Sciences for confocal microscopy and the Center for Developmental Biology from Institute of Genetics and Developmental Biology Chinese Academy of Sciences and Dr. Jai from Core Facility for Protein Research from Institute of Biophysics Chinese Academy of Sciences for flow cytometry. We are grateful to Dr. Kuang from Purdue University and Dr. Zhu from Chinese Academy of Medical Sciences Peking Union Medical College for the kind donation of Myf5-Cre mice and Dr. Wolfrum from the Institute of Food Nutrition and Health at the ETH Zurich for the kind donation of the Ucp1-DTR mice. Xun Huang provided valuable comments on previous versions of the manuscript.Peer reviewedPublisher PD

Functionalized MoS2 nanosheet-capped periodic mesoporous organosilicas as a multifunctional platform for synergistic targeted chemo-photothermal therapy

The combination of different therapies into a single platform has attracted increasing attention as a potential synergistic tumor treatment. Herein, the fabrication of a novel folate targeted system for chemo-photothermal therapy by using thioether-bridged periodic mesoporous organosilica nanoparticles (PMOs) as a drug-loading vehicle is described. The novel targeted molecular bovine serum albumin-folic acid-modified MoS2 sheets (MoS2-PEI-BSA-FA) were successfully synthesized and characterized, and then utilized as a capping agent to block PMOs to control the drug release and to investigate their potential in near-infrared photothermal therapy. The resulting PMOs–DOX@MoS2–PEI-BSA-FA complexes had a uniform diameter (196 nm); high DOX loading capacity (185 mg/g PMOs-SH); excellent photothermal transformation ability; and good biocompatibility in physiological conditions. The PMOs–DOX@MoS2–PEI-BSA-FA exhibited pH-dependence and near infrared (NIR) laser irradiation-triggered DOX release. In vitro experimental results confirmed that the material exhibits excellent photothermal transfer ability, outstanding tumor killing efficiency and specificity to target tumor cells via an FA-receptor-mediated endocytosis process. The in vivo experiments further demonstrated that the platform for synergistic chemo-photothermal therapy could significantly inhibit tumor growth, which is superior to any monotherapy. Meanwhile, cytotoxicity assays and histological assessments show that the engineered PMOs@MoS2–PEI-BSA-FA have good biocompatibility, further inspiring potential biomedical applications. Overall, this work describes an excellent drug delivery system for chemo-photothermal synergistic targeted therapy having good drug release properties, which have great potential in cancer therapy