In recent time, as the Chinese consumption level increases, the consumption quantity of high-value fruits, vegetables and seafood products have been increasing year by year. As a consequence, the traffic volume of refrigerated products also increases yearly and the popularization degree of the cold-chain transportation enhances. A low-temperature environment should be guaranteed during transportation, thus there is about 40% of diesel oil should be consumed by the refrigerating system and the cold-chain transportation becomes very costly. This study aimed to explore methods that could reduce the cost of transport packages of refrigerated products. On the basis of the heat transfer theory and the fluid mechanics theory, the heat exchanging process of corrugated cases during the operation of refrigerating system was analyzed, the heat transfer process of corrugated cases and refrigerator van was theoretically analyzed and the heat balance equation of corrugated cases was constructed.
Forecasting yield curves with regime switches is important in academia and financial industry. As the number of interest rate maturities increases, it poses difficulties in estimating parameters due to the curse of dimensionality. To deal with such a feature, factor models have been developed. However, the existing approaches are restrictive and largely based on the stationarity assumption of the factors. This inaccuracy creates non-ignorable financial risks, especially when the market is volatile. In this paper, a new methodology is proposed to adaptively forecast yield curves. Specifically, functional principal component analysis (FPCA) is used to extract factors capable of representing the features of yield curves. The local AR(1) model with time-dependent parameters is used to forecast each factor. Simulation and empirical studies reveal the superiority of this method over its natural competitor, the dynamic Nelson-Siegel (DNS) model. For the yield curves of the U.S. and China, the adaptive method provides more accurate 6- and 12-month ahead forecasts.
Shape optimization on mufflers within a limited space volume is essential for industry, where the equipment layout is occasionally tight and the available space for a muffler is limited for maintenance and operation purposes. To proficiently enhance the acoustical performance within a constrained space, the selection of an appropriate acoustical mechanism and optimizer becomes crucial. A multi-chamber side muffler hybridized with reverse-flow ducts which can visibly increase the acoustical performance is rarely addressed; therefore, the main purpose of this paper is to numerically analyze and maximize the acoustical performance of this muffler within a limited space.
In this paper, the four-pole system matrix for evaluating the acoustic performance - sound transmission loss (STL) - is derived by using a decoupled numerical method. Moreover, a simulated annealing (SA) algorithm, a robust scheme in searching for the global optimum by imitating the softening process of metal, has been used during the optimization process. Before dealing with a broadband noise, the STL's maximization with respect to a one-tone noise is introduced for the reliability check on the SA method. Moreover, the accuracy check of the mathematical models with respect to various acoustical elements is performed.
The optimal result in eliminating broadband noise reveals that the multi-chamber muffler with reverse-flow perforated ducts is excellent for noise reduction. Consequently, the approach used for the optimal design of the noise elimination proposed in this study is easy and effective.
In order to enhance the acoustical performance of a traditional straight-path automobile muffler, a multi-chamber muffler having reverse paths is presented. Here, the muffler is composed of two internally parallel/extended tubes and one internally extended outlet. In addition, to prevent noise transmission from the muffler’s casing, the muffler’s shell is also lined with sound absorbing material. Because the geometry of an automotive muffler is complicated, using an analytic method to predict a muffler’s acoustical performance is difficult; therefore, COMSOL, a finite element analysis software, is adopted to estimate the automotive muffler’s sound transmission loss. However, optimizing the shape of a complicated muffler using an optimizer linked to the Finite Element Method (FEM) is time-consuming. Therefore, in order to facilitate the muffler’s optimization, a simplified mathematical model used as an objective function (or fitness function) during the optimization process is presented. Here, the objective function can be established by using Artificial Neural Networks (ANNs) in conjunction with the muffler’s design parameters and related TLs (simulated by FEM). With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). Consequently, the discharged muffler which is optimally shaped will improve the automotive exhaust noise.
MDAP-2 is a new antibacterial peptide with a unique structure that was isolated from house- flies. However, its biological characteristics and antibacterial mechanisms against bacteria are still poorly understood. To study the biological characteristics, antibacterial activity, hemolytic activi- ty, cytotoxicity to mammalian cells, and the secondary structure of MDAP-2 were detected; the results showed that MDAP-2 displayed high antibacterial activity against all of the tested Gram-negative bacteria. MDAP-2 had lower hemolytic activity to rabbit red blood cells; only 3.4% hemolytic activity was observed at a concentration of 800μg/ml. MDAP-2 also had lower cytotoxicity to mammalian cells; IC50 values for HEK-293 cells, VERO cells, and IPEC-J2 cells were greater than 1000 μg/ml. The circular dichroism (CD) spectra showed that the peptide most- ly has α-helical properties and some β-fold structure in water and in membrane-like conditions. MDAP-2 is therefore a promising antibacterial agent against Gram-negative bacteria. To deter- mine the antibacterial mechanism(s) of action, fluorescent probes, flow cytometry, and transmis- sion electron microscopy (TEM) were used to study the effects of MDAP-2 on membrane perme- ability, polarization ability, and integrity of Gram-negative bacteria. The results indicated that the peptide caused membrane depolarization, increased membrane permeability, and destroyed membrane integrity. In conclusion, MDAP-2 is a broad-spectrum, lower hemolytic activity, and lower cytotoxicity antibacterial peptide, which is mainly effective on Gram-negative bacteria. It exerts its antimicrobial effects by causing bacterial cytoplasm membrane depolarization, increas- ing cell membrane permeability and disturbing the membrane integrity of Gram-negative bacte- ria. MDAP-2 may offer a new strategy to for defense against Gram-negative bacteria.