Experimental study on mitigating wind erosion of calcareous desert sand using spray method for microbially induced calcium carbonate precipitation

Wind erosion is one of the significant natural calamities worldwide, which degrades around one-third of global land. The eroded and suspended soil particles in the environment may cause health hazards, i.e. allergies and respiratory diseases, due to the presence of harmful contaminants, bacteria, and pollens. The present study evaluates the feasibility of microbially induced calcium carbonate precipitation (MICP) technique to mitigate wind-induced erosion of calcareous desert sand (Thar desert of Rajasthan province in India). The temperature during biotreatment was kept at 36 °C to stimulate the average temperature of the Thar desert. The spray method was used for bioaugmentation of Sporosarcina (S.) pasteurii and further treatment using chemical solutions. The chemical solution of 0.25 pore volume was sprayed continuously up to 5 d, 10 d, 15 d, and 20 d, using two different concentration ratios of urea and calcium chloride dihydrate viz 2:1 and 1:1. The biotreated samples were subjected to erosion testing (in the wind tunnel) at different wind speeds of 10 m/s, 20 m/s, and 30 m/s. The unconfined compressive strength of the biocemented crust was measured using a pocket penetrometer. The variation in calcite precipitation and microstructure (including the presence of crystalline minerals) of untreated as well as biotreated sand samples were determined through calcimeter, scanning electron microscope (SEM), and energy-dispersive X-ray spectroscope (EDX). The results demonstrated that the erosion of untreated sand increases with an increase in wind speeds. When compared to untreated sand, a lower erosion was observed in all biocemented sand samples, irrespective of treatment condition and wind speed. It was observed that the sample treated with 1:1 cementation solution for up to 5 d, was found to effectively resist erosion at a wind speed of 10 m/s. Moreover, a significant erosion resistance was ascertained in 15 d and 20 d treated samples at higher wind speeds. The calcite content percentage, thickness of crust, bulk density, and surface strength of biocemented sand were enhanced with the increase in treatment duration. The 1:1 concentration ratio of cementation solution was found effective in improving crust thickness and surface strength as compared to 2:1 concentration ratio of cementation solution. The calcite crystals formation was observed in SEM analysis and calcium peaks were observed in EDX analysis for biotreated sand.     

Performance assessment of a direct steam solar power plant with hydrogen energy storage: An exergoeconomic study

Power generation and its storage using solar energy and hydrogen energy systems is a promising approach to overcome serious challenges associated with fossil fuel-based power plants. In this study, an exergoeconomic model is developed to analyze a direct steam solar tower-hydrogen gas turbine power plant under different operating conditions. An on-grid solar power plant integrated with a hydrogen storage system composed of an electrolyser, hydrogen gas turbine and fuel cell is considered. When solar energy is not available, electrical power is generated by the gas turbine and the fuel cell utilizing the hydrogen produced by the electrolyser. The effects of different working parameters on the cycle performance during charging and discharging processes are investigated using thermodynamic analysis. The results indicate that increasing the solar irradiation by 36%, leads to 13% increase in the exergy efficiency of the cycle. Moreover, the mass flow rate of the heat transfer fluid in solar system has a considerable effect on the exergy cost of output power. Solar tower has the highest exergy destruction and capital investment cost. The highest exergoeconomic factor for the integrated cycle is 60.94%. The steam turbine and PEM electrolyser have the highest share of exergoeconomic factor i.e., 80.4% and 50%, respectively.     

Assessment of offshore liquid hydrogen production from wind power for ship refueling

Green hydrogen from electrolysis has become the most attractive energy carrier for making the transition from fossil fuels to carbon-free energy sources possible. Especially in the naval sector, hydrogen has the potential to address environmental targets due to the lack of low-carbon fuel options. This study aims at investigating an offshore liquefied green hydrogen production plant for ship refueling. The plant comprises a wind farm for renewable electricity generation, an electrolyzer stack for hydrogen production, a water treatment unit for demineralized water production, and a hydrogen liquefaction plant for hydrogen storage and distribution to ships. A pre-feasibility study is addressed to find the optimal capacities of the plant that minimize the payback time. The model results show that the electrolyzer capacity shall be set equal to a value between 80% and 90% of the wind farm capacity to achieve the minimum payback times. Additionally, the wind farm capacity shall be higher than about 150 MW to limit the payback time to values lower than 11 years for a fixed hydrogen price of 6 €/kg. The Levelized Cost of Hydrogen results to be below 4 €/kg for a wide range of plant capacities for a lifetime of the plant of 25 years. Thus, the model shows that this plant is economically feasible and can be reproduced similarly for different locations by rescaling the different selected technologies. In this way, the naval sector can be decarbonized thanks to a new infrastructure for the production and refueling of liquified green hydrogen directly provided on the sea.     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

浅谈电子电工技术在电力系统中的应用

本文针对电子电工技术在电力系统中的作用进行了分析,同时为该技术的推广提出了相应的建议。     

基于阶段注意力机制的电力线提取算法

电力系统维护是电力系统稳定运行的重要保障，应用智能算法的无人机电力巡检则为电力系统维护提供便捷。电力线提取是自主电力巡检以及保障飞行器低空飞行安全的关键技术，结合深度学习理论进行电力线提取是电力巡检的重要突破点。本文将深度学习方法用于电力线提取任务，结合电力线图像特点嵌入改进的图像输入策略和注意力模块，提出一种基于阶段注意力机制的电力线提取模型（SA-Unet）。本文提出的SA-Unet模型编码阶段采用阶段输入融合策略（Stage input fusion strategy， SIFS），充分利用图像的多尺度信息减少空间位置信息丢失。解码阶段通过嵌入阶段注意力模块（Stage attention module，SAM）聚焦电力线特征，从大量信息中快速筛选出高价值信息。实验结果表明，该方法在复杂背景的多场景中具有良好的性能。     

Use of Fourier-Transform Infrared Spectroscopy (FT-IR) for Monitoring Experimental Helicobacter pylori Infection and Related Inflammatory Response in Guinea Pig Model

Infections due to Gram-negative bacteria Helicobacter pylori may result in humans having gastritis, gastric or duodenal ulcer, and even gastric cancer. Investigation of quantitative changes of soluble biomarkers, correlating with H. pylori infection, is a promising tool for monitoring the course of infection and inflammatory response. The aim of this study was to determine, using an experimental model of H. pylori infection in guinea pigs, the specific characteristics of infrared spectra (IR) of sera from H. pylori infected (40) vs. uninfected (20) guinea pigs. The H. pylori status was confirmed by histological, molecular, and serological examination. The IR spectra were measured using a Fourier-transform (FT)-IR spectrometer Spectrum 400 (PerkinElmer) within the range of wavenumbers 3000–750 cm⁻¹ and converted to first derivative spectra. Ten wavenumbers correlated with H. pylori infection, based on the chi-square test, were selected for a K-nearest neighbors (k-NN) algorithm. The wavenumbers correlating with infection were identified in the W2 and W3 windows associated mainly with proteins and in the W4 window related to nucleic acids and hydrocarbons. The k-NN for detection of H. pylori infection has been developed based on chemometric data. Using this model, animals were classified as infected with H. pylori with 100% specificity and 97% sensitivity. To summarize, the IR spectroscopy and k-NN algorithm are useful for monitoring experimental H. pylori infection and related inflammatory response in guinea pig model and may be considered for application in humans.     

A robust model-free controller for a three-phase grid-connected photovoltaic system based on ultra-local model

In this paper, a robust model-free controller for a grid-connected photovoltaic (PV) system is designed. The system consists of a PV generator connected to a three-phase grid by a DC/AC converter. The control objectives of the overall system are to extract maximum power from the PV source, to control reactive power exchange and to improve the quality of the current injected into the grid. The model-free control technique is based on the use of an ultra-local model instead of the dynamic model of the overall system. The local model is continuously updated based on a numerical differentiator using only the input–output behavior of the controlled system. The model-free controller consists of a classical feedback controller and a compensator for the effects of internal parameter changes and external disturbances. Simulation results illustrate the efficiency of the controller for grid-connected PV systems.     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.