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Dynamic infrared emissivity (DIE) regulators, which can efficiently modulate infrared radiation beyond vision, have emerged as an attractive technology in energy and information fields. However, current DIE regulators are usually visibly opaque, which limits their applications involving broad-spectrum requirements or multispectral compatibility. Therefore, it is necessary to propose new DIE mechanism and develop the desirable fully transparent DIE regulators for dynamically regulating infrared emissivity and solar spectral properties independently, although highly challenging. Here, we demonstrate DIE regulators based on a novel DIE mechanism with high visible transparency (84.7%), large emissivity regulation (0.51 in 3–5 µm, 0.42 in 7.5–13 µm), fast response ( 104 cycles). This excellent performance is achieved by the reversible injection/extraction of electrons into/from aluminum-doped zinc oxide (AZO) nanocrystals to modulate infrared plasmonic in a capacitive-type device, and the DIE regulation is attributed to variation of carrier concentration in the depletion layer near the surface of AZO nanocrystals. This novel DIE regulation method and fully transparent DIE regulators provide great opportunities for the on-demand smart thermal management of buildings and spacecrafts, multispectral display and adaptive camouflage, and may in other infrared radiation related technologies.

At present, based on the transfer coefficient method, most of the anti-slide pile design thrusts are calculated by the overload method and the strength reserve method respectively. Many algorithms only consider the remaining sliding force behind the pile and the safety factor that meets the requirements of the design conditions. Generally, the safety factor is the safety factor of the sliding slope behind the pile after the anti slide pile is reinforced. For the entire landslide, there are two safety factors before and after the pile, which is not the design safety factor target value, and there is a big difference between the safety factor and the treatment goal required by the specification. Through the study of the pile-soil interaction of anti-slide piles, it is believed that in addition to the active residual sliding force transmitted by the blocks behind the pile, the anti-slide piles are simultaneously subjected to the passive residual anti-sliding force transmitted upwards by the blocks in front of the pile. The stress analysis shows that: Firstly, according to the different active and passive properties of anti-sliding force transmission and sliding force transmission, the mechanical model of anti-sliding force transmission is studied, and the calculation formula of anti-sliding force transmission coefficient is derived; Secondly, It is believed that the anti-slide pile provides horizontal thrust to the landslide, and two components of the sliding surface direction and the vertical sliding surface direction are generated. The balance equation is established and the overload method and the strength reserve method of anti-slide pile thrust calculation formula are derived; Thirdly, according to the principle of setting piles in the anti-slip section, the optimal location of anti-slide piles are proposed; Fourthly, after verification of cases, the safety factors before and after the piles calculated by the overload method are basically equal, and consistent with the design safety factors. Calculation result shows that the strength reserve method to calculate the safety factor before the pile is accurate and reliable, and the result of the safety factor behind the pile is relatively small.

In recent years, online advertising sales have been the main economic sources of Internet companies such as Google, Facebook, Snap, Pinterest, and Baidu. Advertising click-through rate measures the ratio of users who click an advertisement to the total users who view the advertisement. The click-through rate is very important for Internet companies' online advertisements quality. The click-through rate of online advertising is related to many factors, including gender, age, type of advertisement, and the timely and effective prediction of the click-through rate of online advertising as well as advertisement text. In recent years, the click-through rate of online advertising has become one of the hot areas of research in industry and academia. Advertising prediction models are generally divided into two categories: shallow learning models and deep learning models [1]. This paper surveys Click-Through Rate (CTR) prediction models, discusses the problems in the current advertising click rate prediction models, and points out future research trends.

Fundamental understandings of the pavement-tire friction are vital to improve the design of asphalt pavements. Most of the current research on pavement-tire friction is based on Finite Element Meth...

Prostaglandin E2 (PGE2) enhances Staphylococcus aureus infection but its mechanism is not well understood. Here, we examined the effect of PGE2 on Staphylococcal Protein A (SPA) expression in bovine endometrium and determined the role of select PGE2 receptors (i.e., EP2 and EP4) in adhesion and internalization of S. aureus. S. aureus isolate SA113 was used for in vitro infection of bovine endometrial tissues and epithelial cells, with treatment conditions consisting of untreated control, SA113 treatment, SA113 + PGE2, SA113 + PGE2 + EP2 receptor antagonist (AH-6809), and SA113 + PGE2 + EP4 receptor antagonist (AH-23848). Immunofluorescence assay revealed that PGE2 could promote SPA expression in S. aureus-infected bovine endometrial tissues. PGE2 also enhanced the adhesion and internalization of S. aureus in bovine endometrial cells. The addition of EP4 antagonist, but not the EP2 antagonist, abrogated the ability of PGE2 to promote S. aureus SPA expression, adhesion, and internalization in endometrial cells. Our findings suggest that S. aureus infection in the endometrium is enhanced by PGE2 through the EP4 receptor. This result is essential for the development of new approach to treating S. aureus infection, such as the application of EP4 antagonist as an adjunct drug treatment.

A methodology to account for the interface effect on the viscoelastic behavior of asphalt-based multi-phase particle-reinforced composites is presented. A Kelvin–Voigt type viscoelastic interface is introduced first to simulate the imperfect interface between asphalt mastic and particles. The concept of “effective” particle properties is used to take into account the viscoelastic characteristic of the interface in an averaged manner. Then, the micromechanical creep model is developed based on the Mori–Tanaka method, and further solved analytically by incorporating the elastic–viscoelastic correspondence principle. Tests are conducted on the three types of asphalt concrete with different microstructures, and then compared with the predicted results. The results indicate that the developed micromechanical model has the capability to predict the creep behavior observed from the asphalt concrete. Finally, the effects of particle size, viscoelastic characteristic of asphalt mastic, the different rheological models for simulating asphalt mastic, elastic properties of particles, volume fraction of particles, and particularly interface imperfection on the creep behavior of asphalt concrete are further investigated.

As long as extended producer responsibility comes to effect, appliance producers should take the responsibility to recover and reuse the products. Thus, how to disassemble and reuse the discarded appliances scientifically and work out the optimal recovery and disposal strategies are now the key problems the appliance producers confront with. This paper adopts theories related to products regeneration management and disassembly and recovery assessment. It firstly deals with the disassembly stage of discarded appliances recovered and the principle of disassembly evaluation. It then takes the recovery of discarded computers as an example, setting up the disassembly tree, comparing the different strategies between reusing and recovering discarded appliances and waste disposal. What's more, it analyzes the feasibility of the recovery and disposal plan from the prospects of economy, environmental protection, technology and law, establishes the feasibility criteria and eventually sets up 0–1 goal programming mathematical models, carrying out the quantitative calculation toward the economic and environment load of the plan, which deals with the recovery and disposal plan for discarded appliance, in order to provide better help for the appliance producers to determine and choose an optimal plan for recovery and disposal.

Based on matrix analysis method, this paper analyzes the strengths and weaknesses within and without Hebei Province, the opportunities and threats of Hebei Province in the coordinated development of region. It puts forward eight feasible strategic projects. And the paper adopted quantitative methods, selected some strategic projects fitting in with the development of Hebei Province. In this process, the paper mostly applies external factors evaluation (EFE) matrix, internal factors evaluation (IFE) matrix, SWOT analysis and quantitative strategic planning matrix (QSPM), and concludes Hebei Province should make more contributions to the adjustment of the economic structure, cooperation within Beijing, Tianjin and Hebei Region, and appropriate importing of foreign capital.

The issue of pre-splitting blasting design is investigated in this paper. According to the principle of expert system and neural networks, Visual C++ 6.0 and SQL Sever 2000 are employed to develop hybrid expert system of pre-splitting blasting design based on BP neural networks. The proposed expert system is a coupling system of engineering database and three-layered BP neural networks, which can be applied into cutting excavation of the expressway. The experiments show that the system can enhance the reliability of in-site pre-splitting blasting design scheme, efficiency and quality of construction.

Rockburst is a main engineering geological problems in deep-buried long tunnels. Rockburst phenomena have been analyzed, assumptions and criteria have been presented from the perspectives of strength, stiffness, energy, steadiness, fracture, damage, fractal and catastrophe, etc. Considering individual factors only among some assumptions and criteria will cause unilateral and limited results. Based on the assumptions and criteria of rockburst and real examples of tunnel engineering, a neural network model is proposed to predict rockburst. The prediction results show that it is feasible and valid to use artificial neural network for predicting rockburst.