Human Metapneumovirus Inhibits IFN-β Signaling by Downregulating Jak1 and Tyk2 Cellular Levels

Human metapneumovirus (hMPV), a leading cause of respiratory tract infections in infants, inhibits type I interferon (IFN) signaling by an unidentified mechanism. In this study, we showed that infection of airway epithelial cells with hMPV decreased cellular level of Janus tyrosine kinase (Jak1) and tyrosine kinase 2 (Tyk2), due to enhanced proteosomal degradation and reduced gene transcription. In addition, hMPV infection also reduced the surface expression of type I IFN receptor (IFNAR). These inhibitory mechanisms are different from the ones employed by respiratory syncytial virus (RSV), which does not affect Jak1, Tyk2 or IFNAR expression, but degrades downstream signal transducer and activator of transcription proteins 2 (STAT2), although both viruses are pneumoviruses belonging to the Paramyxoviridae family. Our study identifies a novel mechanism by which hMPV inhibits STAT1 and 2 activation, ultimately leading to viral evasion of host IFN responses

An Efficient Hybrid Algorithm for Multiobjective Optimization Problems with Upper and Lower Bounds in Engineering

Generally, the inconvenience of establishing the mathematical optimization models directly and the conflicts of preventing simultaneous optimization among several objectives lead to the difficulty of obtaining the optimal solution of a practical engineering problem with several objectives. So in this paper, a generate-first-choose-later method is proposed to solve the multiobjective engineering optimization problems, which can set the number of Pareto solutions and optimize repeatedly until the satisfactory results are obtained. Based on Frisch’s method, Newton method, and weighed sum method, an efficient hybrid algorithm for multiobjective optimization models with upper and lower bounds and inequality constraints has been proposed, which is especially suitable for the practical engineering problems based on surrogate models. The generate-first-choose-later method with this hybrid algorithm can calculate the Pareto optimal set, show the Pareto front, and provide multiple designs for multiobjective engineering problems fast and accurately. Numerical examples demonstrate the effectiveness and high efficiency of the hybrid algorithm. In order to prove that the generate-first-choose-later method is rapid and suitable for solving practical engineering problems, an optimization problem for crash box of vehicle has been handled well

Crashworthiness Design for Bionic Bumper Structures Inspired by Cattail and Bamboo

Many materials in nature exhibit excellent mechanical properties. In this study, we evaluated the bionic bumper structure models by using nonlinear finite element (FE) simulations for their crashworthiness under full-size impact loading. The structure contained the structural characteristics of cattail and bamboo. The results indicated that the bionic design enhances the specific energy absorption (SEA) of the bumper. The numerical results showed that the bionic cross-beam and bionic box of the bionic bumper have a significant effect on the crashworthiness of the structure. The crush deformation of bionic cross-beam and box bumper model was reduced by 33.33%, and the total weight was reduced by 44.44%. As the energy absorption capacity under lateral impact, the bionic design can be used in the future bumper body

Crashworthiness optimization of bionic bumper structure under low-speed impact

By considering the crashworthiness design of bionic bumper structure during frontal impact, the thicknesses are chosen to analysis and optimal design to obtain the lightweight demand. The orthogonal experiment design and radial basis function are employed to construct the response surface for the performances of thin-xwalled components. The multi-objective cuckoo search (MOCS) is applied to perform the optimal design. The results demonstrate that the optimal method and process proposed have high accuracy and validity

Biobjective Optimization Algorithms Using Neumann Series Expansion for Engineering Design

In this paper, two novel algorithms are designed for solving biobjective optimization engineering problems. In order to obtain the optimal solutions of the biobjective optimization problems in a fast and accurate manner, the algorithms, which have combined Newton’s method with Neumann series expansion as well as the weighted sum method, are applied to deal with two objectives, and the Pareto optimal front is achieved through adjusting weighted factors. Theoretical analysis and numerical examples demonstrate the validity and effectiveness of the proposed algorithms. Moreover, an effective biobjective optimization strategy, which is based upon the two algorithms and the surrogate model method, is developed for engineering problems. The effectiveness of the optimization strategy is proved by its application to the optimal design of the dummy head structure in the car crash experiments

Crashworthiness optimization of bionic bumper structure under low-speed impact

By considering the crashworthiness design of bionic bumper structure during frontal impact, the thicknesses are chosen to analysis and optimal design to obtain the lightweight demand. The orthogonal experiment design and radial basis function are employed to construct the response surface for the performances of thin-xwalled components. The multi-objective cuckoo search (MOCS) is applied to perform the optimal design. The results demonstrate that the optimal method and process proposed have high accuracy and validity

Multifunctional Flexible Ionic Skin with Dual-Modal Output Based on Fibrous Structure

Flexible wearable electronic devices with multiple sensing functions that simulate human skin in all aspects have become a popular research topic. However, the current expensive and time-consuming means of integration and the complex decoupling process are hampering the further development of multifunctional sensors. Here, an ultraflexible ionic fiber membrane (IFM) prepared by a simple electrospinning technique is reported, which exhibits pressure and humidity sensing properties. With the help of different electrode structures, the IFM-based multifunctional sensor achieved pressure and humidity detection with different sensing mechanisms. Pressure sensing with high sensitivity (49.7 kPa–1 at 0–30 kPa) and wide detection range (0–220 kPa) was indicated by the capacitive signal. Humidity sensing with high linearity (1.086% per percent relative humidity (RH)) in the range 15%–90% RH was indicated by the resistance signal. In particular, the multimodal output of capacitance/resistance corresponding to pressure/humidity in this study directly addresses the problem of accurately distinguishing the two stimuli. Furthermore, we have demonstrated that the impact between pressure and humidity is negligible when measured simultaneously and independently. Because of the excellent pressure/humidity sensing performance, we have fabricated a smart bracelet and mask for pulse, skin moisture, and breathe monitoring, which indicates the promising future of multifunctional flexible sensors based on IFM in the healthcare field