Effects of Different Short-Term UV-B Radiation Intensities on Metabolic Characteristics of Porphyra haitanensis

The effects of ultraviolet (UV) radiation, particularly UV-B on algae, have become an important issue as human-caused depletion of the protecting ozone layer has been reported. In this study, the effects of different short-term UV-B radiation on the growth, physiology, and metabolism of Porphyra haitanensis were examined. The growth of P. haitanensis decreased, and the bleaching phenomenon occurred in the thalli. The contents of total amino acids, soluble sugar, total protein, and mycosporine-like amino acids (MAAs) increased under different UV-B radiation intensities. The metabolic profiles of P. haitanensis differed between the control and UV-B radiation-treated groups. Most of the differential metabolites in P. haitanensis were significantly upregulated under UV-B exposure. Short-term enhanced UV-B irradiation significantly affected amino acid metabolism, carbohydrate metabolism, glutathione metabolism, and phenylpropane biosynthesis. The contents of phenylalanine, tyrosine, threonine, and serine were increased, suggesting that amino acid metabolism can promote the synthesis of UV-absorbing substances (such as phenols and MAAs) by providing precursor substances. The contents of sucrose, D-glucose-6-phosphate, and beta-D-fructose-6-phosphate were increased, suggesting that carbohydrate metabolism contributes to maintain energy supply for metabolic activity in response to UV-B exposure. Meanwhile, dehydroascorbic acid (DHA) was also significantly upregulated, denoting effective activation of the antioxidant system. To some extent, these results provide metabolic insights into the adaptive response mechanism of P. haitanensis to short-term enhanced UV-B radiation.     

象山隧道液压凿岩台车开挖斜孔掏槽施工技术

新建的龙岩至厦门单线铁路象山隧道断面比较小,使用液压凿岩台车开挖,斜孔掏槽方案受到很大限制。本文介绍了使用液压凿岩台车钻爆开挖象山隧道,选择斜孔掏槽方案实现快速开挖,为类似的隧道工程施工提供经验。     

Reasonable construction of proton conducting channel via biomimetic caterpillar-like alumina fiber to improve the properties of its composite proton exchange membrane

In this paper, we prepare a novel biomimetic caterpillar-like alumina fiber with the characteristic of continuous alumina backbone and fine needle whiskers spine. Then the high-performance caterpillar-like alumina fiber composite proton exchange membrane (CAPEM) is obtained by introducing the amino modified biomimetic caterpillar-like alumina fiber into sulfonated polysulfone (SPSF) matrix, which successfully reasonable construction of the proton conducting channels in both vertical and horizontal orientation. The properties of CAPEM, including proton conductivity, methanol permeability, etc. Are systematically studied. The results show that the proton conductivity of CAPEM increases with rising the temperature, which reaches the maximum of 0.263 S/cm at 80 °C and 100% RH, respectively. The excellent proton conductivity of CAPEM is attributed to the long-range continuous proton conducting channel formed by the horizontal continuous alumina skeleton in the in-plane direction and the vertical overlapped fine needle whiskers spine in the through-plane direction. In addition, the interfacial compatibility between amino modified caterpillar-like alumina fiber and SPSF matrix is enhanced through the reasonable construction of proton conducting channels, which effectively inhibits the methanol permeation of the composite membrane with 4.18 × 10^?7 cm² s^?1 and improves the comprehensive performance of the CAPEM.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

火电机组一次调频性能实时监测系统

为了实时监测和评价火电机组一次调频性能，开发了火电机组一次调频性能实测监测系统。该系统具有一次调频参数异动感知、一次调频性能量化预测及自适应校正等关键功能。某机组的实际应用表明，该系统能够实现火电机组一次调频关键参数的实时监测和调频性能的准确预测。     

MHD mixed convection of a Cu–water nanofluid flow through a channel with an open trapezoidal cavity and an elliptical obstacle

In the current work, numerical simulations are achieved to study the properties and the characteristics of fluid flow and heat transfer of (Cu–water) nanofluid under the magnetohydrodynamic effects in a horizontal rectangular canal with an open trapezoidal enclosure and an elliptical obstacle. The cavity lower wall is grooved and represents the heat source while the obstacle represents a stationary cold wall. On the other hand, the rest of the walls are considered adiabatic. The governing equations for this investigation are formulated, nondimensionalized, and then solved by Galerkin finite element approach. The numerical findings were examined across a wide range of Richardson number (0.1 ≤ Ri ≤ 10), Reynolds number (1 ≤ Re ≤ 125), Hartmann number (0 ≤ Ha ≤ 100), and volume fraction of nanofluid (0 ≤ φ ≤ 0.05). The current study's findings demonstrate that the flow strength increases inversely as the Reynolds number rises, which pushes the isotherms down to the lower part of the trapezoidal cavity. The Nu_avg rises as the Ri rise, the maximum Nu_avg = 10.345 at Ri = 10, Re = 50, ϕ = 0.05, and Ha = 0; however, it reduces with increasing Hartmann number. Also, it increase by increasing ϕ, at Ri = 10, the Nu_avg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05).     

基于自适应LS-SVM的柴油机废气再循环冷却控制系统设计

针对当前柴油机废气再循环冷却控制系统受到时滞问题影响,导致系统开度走势与设定走势不一致、废气再循环效果差的问题,提出基于自适应LS-SVM的柴油机废气再循环冷却控制系统;以AT89C51单片机40针作为电控单元核心部件,利用位置传感器向系统发送负载信号,利用温度传感器来传输信号并反馈至D/A转换器;在D/A转换器中,反馈信号以串行或并行方式进入寄存器,并在转换后输出电流电压,控制系统阀门在排气再循环时的开启;伺服泵采用冷却系统,为系统提供液压动力源;利用自适应LS-SVM原理计算柴油机废气再循环冷却控制目标边界值,在最小二乘支持向量机基础上,利用求解线性方程组进行优化,消除了控制误差;根据控制差的大小,调整控制系统的输出值;由试验结果可知,该系统开度走势与设定开度走势一致,且与设定开度误差为1开度,说明使用该系统具有良好稳态特性,有效克服了系统中时滞问题,废气再循环效果较好。     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

Squeezed MHD tangent hyperbolic fluid flow across a sensor surface

In the present numerical study, the combined effect of temperature-dependent thermal conductivity, linear thermal radiation, and magnetic effect on shear-thinning tangent hyperbolic fluid past a sensor surface has been studied. After converting the modelled partial differential equations into ordinary differential equations by using similarity transformation, the system of equations is tackled with the aid of the shooting method. The influence of important parameters on the fluid motion and energy distribution is displayed graphically and analyzed in detail. The presented simulations depict that a significant rise in fluid velocity is noticed for an enhancement in the magnetic parameter while an opposite trend is observed for the temperature distribution. Moreover, the skin friction coefficient decreases as the squeezed flow index is increased.     

基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。