Effects of Bacillus velezensis zk1 on the physiology and metabolism of peaches

Bacillus velezensis zk1 is the dominant bacterium that causing rot in peaches. However, the mechanisms through that this bacterium causes rot have not been elucidated. Here, we explored the mechanisms of peach decay caused by B. velezensis zk1. The invasion of B. velezensis zk1 in peaches resulted in an increase in glucose and arabinose contents in fruit tissues. Moreover, the relative conductivity of the fruit reached 84% after 4 days of culture with bacterial invasion. With the destruction of cells, the malondialdehyde content increased, whereas the vitamin C, dialdehyde, flavonoid and total phenol contents decreased. Polyphenol oxidase, superoxide dismutase, catalase, peroxidase, ascorbate peroxidase and ammonia lyase activities also decreased. Overall, these findings demonstrated that B. velezensis zk1 infection damaged peach chloroplasts, mitochondria, respiratory chain activity and related free radical scavenging enzyme systems, thereby disrupting the normal physiological metabolism of peaches and causing rot.     

基于软件校准的短波发射机功率控制系统设计

短波发射机功率稳定一直是通信领域致力改善的重点问题,短波发射机功率不稳定会直接影响无线电通信质量,造成通信失真、表达不清晰等问题。针对上述问题,基于软件校准设计短波发射机功率控制系统。该系统借鉴MVC设计模式搭建系统数据库层、业务逻辑层、控制层以及界面显示层基础框架；将功率计与短波发射机相连,实时采集工作状态下的短波发射机功率数据,通过信号处理器实施处理后并存储,借鉴传输元件,将数据发送到控制器,通过控制器校准短波发射机功率与预期之间的偏差,以偏差量为输入,利用改进PID运算得出控制量,生成控制命令,通过输入输出信号接口板输出命令,控制驱动装置调节短波发射机运行参数,实现功率控制。结果表明：与 控制系统、自动调谐系统应用相比较,在所设计系统应用控制下,100s内短波发射机的功率变化曲线与预期曲线之间的拟合优度指数更大,更接近1,优于对比系统,说明相比于对比系统。本系统控制表现更好,更能维持短波发射机功率稳定,达到了研究目标。     

控制爆破法处理卡钻事故

介绍了在包头市某工程实施管道穿越黄河施工中,采用爆破法处理卡钻的经验。针对深水环境条件及钻杆内径小不宜采用集团装药的条件,确定采用"小直径爆破筒,钻杆内部装药"的爆破方案,阐述了爆破设计及施工注意事项。可供类似工程参考。     

Dynamic simulation of hydrogen-based off-grid zero energy buildings with hydrogen storage considering Fanger model thermal comfort

In this study, some locations with different climates, off-grid zero energy buildings with hydrogen energy storage systems are designed, and transient analysis is conducted. These considered buildings supply their electricity consumption without using the electrical grid and PV panels or wind turbines. Also, they supply thermal comfort to occupants by using a vapor compression chiller and humidifier. Domestic hot water of occupants is supplied using solar collectors. For analyzing building's performance and objectives achievement, TRNSYS software is used. Also, for evaluating occupant thermal comfort, the Fanger model is used. The considered building is a one-story building with a 150 m² area. Four occupants are considered. Both of them are seated at rest, and another is seated with light working such as typing. Using the Fanger model equation and MATLAB software, the thermal comfort of occupants is determined. For domestic hot water consumption, verified profiles that vary during 24 h of the day are considered. Achieved results show that for humid and cold cities, PV panels with an area of 73 and 76 m² can be supplied the required electricity of considered building with four occupants and battery state of charge is higher than 50% and 10%, respectively. Moreover, with a suitable air conditioner system, the predicted percentage of dissatisfied (PPD) can be lower than 12% and 8% for humid and cold cities. Therefore, the building can be converted to a zero-energy building using its rooftop area.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.     

Influence of applied voltage and conductive material in DIET promotion for methane generation

The utilization of biological-, electrode- and conductive material-mediated direct interspecies electron transfer (DIET) between exoelectrogenic bacteria and methanogenic archaea for enhancing methane productivity is widely reported in the literature. However, two cardinal questions are still controversial, i.e., which applied voltage value would be more recommended to enhance methane generation? and how the DIET over IIET has the upper hand in enhancing methane productivity? Herein, the influence of different applied voltages to promote biological-, conductive- and electrode-mediated DIET was investigated in MEC-AD reactors with conductive material. Polarized bioelectrodes induced electrode-mediated DIET (eDIET) and biological DIET (bDIET), in addition to cDIET (conductive material-mediated DIET), improved the methane yield to 315.40 mL/g COD_r with an applied voltage of 0.9 V. Whereas further increase of applied voltage 1.2 V, lessened methane production efficiency due to high-voltage inhibition and adverse effect on DIET promotion. The anaerobic digestion coupled microbial electrolysis cells with optimal electric potential selectively promotes the DIET through polarized electrodes were confirmed through microbial analysis. As the contribution of DIET increased to 80%, the methane yield increased, and the substrate residue decreased, resulting in a significant improvement in methane production.     

Locating wind farm for power and hydrogen production based on Geographic information system and multi-criteria decision making method: An application

Hydrogen generation from renewable energy resources is considered as a suitable solution to solve the problems related to the energy sector and the reduction of greenhouse gases. The aim of this study is to provide an integrated framework for identifying suitable areas for the construction of wind farms to produce hydrogen. For this purpose, a combined method of Geographic Information System (GIS) and multi-criteria decision making (MCDM) has been used to locate the power plant in Yazd province. The GIS method in the present study consisted of two parts: constraints and criteria. The constraint section included areas that were unsuitable for the construction of wind farms to produce power and hydrogen. In the present study, various aspects such as physical, economic and environmental had been considered as constraints. In the criteria section, eight different criteria from technical aspects (including average wind speed, hydrogen production potential, land slope) and economic aspects (including distance to electricity grid, distance to urban areas, distance to road, distance to railway and distance to centers of High hydrogen consumption) had been investigated. The MCDM tool had been used to weigh the criteria and identify suitable areas. Analytic Hierarchy Process (AHP) technique was used for weighting the criteria. The results of AHP weighting method showed that economic criteria had the highest importance with a value of 0.681. The most significant sub-criterion was the distance to urban areas and the least significant sub-criterion was the distance to power transmission lines. The results of GIS-MCDM analysis had shown that the most proper areas were in the southern and central sectors of Yazd province. In addition, the feasibility of hydrogen production from wind energy had shown that this province had the capacity to generate hydrogen at the rate of 53.6–128.6 tons per year.     

Optimization and efficiency analysis of methanol SOFC-PEMFC hybrid system

In order to improve the power generation efficiency of fuel cell systems employing liquid fuels, a hybrid system consisting of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) is proposed. Utilize the high temperature heat generated by SOFC to reform as much methanol as possible to improve the overall energy efficiency of the system. When SOFC has a stable output of 100 kW, the amount of hydrogen after reforming is changed by changing the methanol flow rate. Three hybrid systems are proposed to compare and select the best system process suitable for different situations. The results show that the combined combustion system has the highest power generation, which can reach 350 kW and the total electrical efficiency is 57%. When the power of the tail gas preheating system is 160 kW, the electrical efficiency can reach 75%. The PEM water preheating system has the most balanced performance, with the electric power of 300 kW and the efficiency of 66%.     

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.     

Inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products formation in a bovine serum albumin–fructose model

This study investigated the inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products (fAGEs) formation in a bovine serum albumin (BSA)–fructose model. Model systems of BSA and fructose were prepared, and curcumin or piperine was added. fAGEs and BSA oxidation product (dityrosine, kynurenine and N'-formylkynurenine) contents were determined. The results showed that fAGEs content decreased with increasing concentration of curcumin and piperine (P < 0.05). Addition of curcumin and piperine at 160 µg mL⁻¹ could inhibit fluorescent AGEs by 100% and 93% respectively. Dityrosine and N'-formylkynurenine contents decreased as curcumin and piperine concentration increased (P < 0.05). Furthermore, the result of principal component analysis indicated that curcumin and piperine markedly impeded BSA oxidation, resulting in a lower level of fAGEs in model systems. Therefore, adding curcumin and piperine may facilitate reduced fAGEs levels in BSA–fructose model.