Application of robust machine learning methods to modeling hydrogen solubility in hydrocarbon fuels

Having accurate information about the hydrogen solubility in hydrocarbon fuels and feedstocks is very important in petroleum refineries and coal processing plants. In the present work, extreme gradient boosting (XGBoost), multi-layer perceptron (MLP) trained with Levenberg–Marquardt (LM) algorithm, adaptive boosting support vector regression (AdaBoost?SVR), and a memory-efficient gradient boosting tree system on adaptive compact distributions (LiteMORT) as four novel machine learning methods were used for estimating the hydrogen solubility in hydrocarbon fuels. To achieve this goal, a database containing 445 experimental data of hydrogen solubilities in 17 various hydrocarbon fuels/feedstocks was collected in wide-spread ranges of operating pressures and temperatures. These hydrocarbon fuels include petroleum fractions, refinery products, coal liquids, bitumen, and shale oil. Input parameters of the models are temperature and pressure along with density at 20 °C, molecular weight, and weight percentage of carbon (C) and hydrogen (H) of hydrocarbon fuels. XGBoost showed the highest accuracy compared to the other models with an overall mean absolute percent relative error of 1.41% and coefficient of determination (R²) of 0.9998. Also, seven equations of state (EOSs) were used to predict hydrogen solubilities in hydrocarbon fuels. The 2- and 3-parameter Soave-Redlich-Kwong EOS rendered the best estimates for hydrogen solubilities among the EOSs. Moreover, sensitivity analysis indicated that pressure owns the highest influence on hydrogen solubilities in hydrocarbon fuels and then temperature and hydrogen weight percent of the hydrocarbon fuels are ranked, respectively. Finally, Leverage approach results exhibited that the XGBoost model could be well trusted to estimate the hydrogen solubility in hydrocarbon fuels.     

Electromagnetic transients in the control system of output parameters of a solar power plant in Tajikistan Central Asia region

At present, as the demand for electricity increases in all sectors, there is an urgent need to introduce alternative renewable energy sources into modern energy systems. Renewable energy sources, which consist of solar (photovoltaic, PV), wind and hydro power, are key alternative sources of “green energy’’ energies, but it can also be used to produce “green” hydrogen. Thanks to scientific and technological progress, the cost of photovoltaic solar radiation converters is constantly decreasing at a high rate, which makes it possible to build solar power plants of sufficiently large capacity. In the coming decades, solar energy will become an incentive for the economic development of countries that have the maximum “solar” resource. The Republic of Tajikistan is one of these countries with a high potential for solar energy.The article presents an analysis of the resources and potential of solar energy in the Republic of Tajikistan. The study of electromagnetic transients in networks with photovoltaic solar power plants is performed. The main equations, simulation model and calculations of transients are presented, taking into account changes in voltage on DC buses. An algorithm for controlling the system of automatic control of output parameters is proposed. The analysis of dynamic and static modes in parallel operation of a solar power plant with the grid is carried out. A block diagram and computer model is constructed in the MATLAB package together with Simulink and Power System Blockset.     

Hydrangea like composite catalysts of ultrathin Mo2S3 nanosheets assembled on N,S-dual-doped graphitic biocarbon spheres with highly electrocatalytic activity for HER

Water electrolysis is the most clean and high-efficiency technology for production of hydrogen, an ultimate clean energy in future. Highly efficient non-noble electrocatalysts for hydrogen evolution reaction (HER) are desirable for large scale production of hydrogen by water electrolysis. Especially, exposing as many active sites as possible is a vital way to improve activities of the catalysts. Herein, a series of new hydrangea like composite catalysts of ultrathin Mo₂S₃ nanosheets assembled uprightly and interlacedly on N, S-dual-doped graphitic biocarbon spheres were facilely prepared. The unique structure endowed the catalysts highly exposed edge active sites and prominently high activities for HER. Especially, the optimized catalyst Mo₂S₃/NSCS-50 exhibited as low as 106 mV of overpotential at 10 mA/cm² (denoted as ?₁₀). The catalyst also showed low Tafel slope of 53 mV/dec, low electron transfer resistance of 34 Ω and high stability evidenced by the result that the current density only attenuated 11.7% after 10 h i-t test. The catalyst has shown broad prospect for commercial application in water electrolysis.     

内含实体对H型垂直轴风力机气动性能的影响

以H型垂直轴风力机及其内含圆柱形实体为研究对象,对NACA0018翼型的五叶片H型垂直轴风力机的气动性能进行数值模拟和实验验证。分析8种不同直径的内含圆柱体,在内含实体截面积占风轮迎风面积之比分别为21.2%、50.0%和76.9%时,风力机风能利用率的峰值分别下降8.04%、20.7%及74.3%。结果表明：随着内含实体直径的增大,风能利用率的峰值逐渐减小,开始较为缓慢,达到一定值时快速下降。小直径内含实体主要影响叶片在下风区的转矩,对风能利用率的影响较小,而大直径内含实体还会影响叶片在上风区的转矩,其风能利用率迅速减小。对于内含固定直径的实体,比如在现有建筑物外侧安装风力机时,其风轮半径的选择需综合考虑风能利用率和风力机的建造成本两方面的因素。研究结果可为建筑物与垂直轴风力机进行有效结合以提高风能的利用提供参考。     

Flash Lamps as Ignition and Initiation Sources of the VS-2 Pyrotechnic Composition

In the present work it is found that the pyrotechnic composition VS-2 can be initiated with flash lamps IFC-500 and EVIS. VS-2 pyrotechnic composition contains 90% of mercury（Ⅱ） 5-hydrazinotetrazolate perchlorate and 10% of optically transparent copolymer of 2-methyl-5-vinyltetrazole and methacrylic acid （PVMT）. We have found that the flash lamps make it possible to initiate combustion of VS-2 composition with its transition to detonation both in cylindrical charges placed in brass caps of 5 mm diameter and 2 mm high， and film charges with 10 mm×80 mm in size and surface weights of 60 mg·cm^-2 and 90 mg·cm^-2， showing ignition delay times 10 μs and 3 μs， respectively. We also measured detonation velocities for VS-2 composition film charges， which were 4375-4505 m·s^-1 （of the charge being surface mass 60 mg·cm^-2） and 4221-4281 m·s^-1 （of the charge being surface mass 90 mg·cm^-2） and their blasting action on the aluminum plate. The depths of the normal shock wave imprints at the charge-barrier interface were 0.6-0.7 mm （for surface mass of the film charges 60 mg·cm^-2） and 1.2-1.3 mm （for surface mass of the film charges 90 mg·cm^-2）.     

Vision-related quality of life with myopia management: A review

The disease of myopia has come into focus as a worldwide public health concern. Myopia has shown increasing prevalence, incidence at earlier age and progression to a higher degree. Progressive increase in degree of myopia is strongly associated with increase in axial length of the eye. Various interventions have been shown to slow axial elongation in children. These interventions have been studied to assess efficacy in slowing axial elongation and correction of vision. In addition, research into quality of vision, risk of adverse events, overall safety and impact on vision-related quality (VR-QoL) of life has been pursued. In contrast, studies have been published to demonstrate the risks of myopia, high myopia and increased axial length. This review will discuss VR-QoL assessment on the most effective and most commonly prescribed interventions to slow axial elongation and myopia progression. The patient attributes considered are VR-QoL scores from validated instruments. The development and use of validated survey instruments to assess the patient-reported outcomes is discussed. The review demonstrates that there are numerous factors that may impact VR-QoL to evaluate in the decision-making process when eye care providers consider when, how and if to prescribe myopia management (MM) for children with myopia.     

雪菊精油对希氏肠球菌产酪胺及相关基因表达的影响

探讨不同质量浓度雪菊精油对希氏肠球菌（Enterococcus hirae）N47产酪胺的影响机制。利用反转录实时定量聚合酶链式反应分析E. hirae在雪菊精油作用下酪氨酸脱羧途径相关基因的表达情况；利用高效液相色谱法检测不同质量浓度雪菊精油对E. hirae产酪胺的影响。并将E. hirae接入到含不同质量浓度雪菊精油的熏马肠中发酵，评估香肠pH值、菌落总数和酪胺积累量。结果表明：在E. hirae纯培养体系和熏马肠体系中，雪菊精油通过抑制微生物的生长和酪氨酸脱羧途径中tyr DC、tyr P基因的表达，降低酪胺的积累量（P＜0.05）。当雪菊精油添加量为1/2最小抑菌浓度（minimal inhibitory concentration，MIC）和MIC时，熏马肠中酪胺的含量分别为78.52 mg/kg和45.83 mg/kg，较对照组分别减少了64.72%和79.41%。     

基于乙酰胆碱酯酶和氧化应激研究海胆酮对阿尔茨海默症的作用机制

海胆酮是一种酮式类胡萝卜素，主要从海胆及藻类等海洋生物中提取。本文研究海胆酮对乙酰胆碱酯酶（acetylcholinesterase，AChE）的抑制作用，应用酶动力学、荧光光谱、圆二色光谱和分子对接技术研究海胆酮对AChE的抑制机理，并用淀粉样β蛋白片段25～35（amyloid beta-peptide 25-35，Aβ25-35）诱导大鼠肾上腺嗜铬细胞瘤细胞（PC12细胞）建立阿尔茨海默症（Alzheimer’s disease，AD）模型，研究海胆酮对AD细胞模型氧化应激损伤的作用。结果表明，海胆酮有很强的AChE抑制活性，其半抑制质量浓度为（16.29±0.97）μg/mL，抑制常数Ki为3.82 μg/mL，表现为竞争性抑制；海胆酮可诱导AChE二级结构改变，更容易与AChE活性中心氨基酸Ser200、His440、Trp84和Tyr121结合，阻碍底物碘代硫代乙酰胆碱（acetylthiocholine iodide，ATCI）与酶结合，从而引起酶活力降低。海胆酮能有效抑制Aβ25-35诱导PC12细胞的AChE活力，降低丙二醛含量，增加超氧化物歧化酶、过氧化氢酶和谷胱甘肽过氧化物酶活力，减轻Aβ25-35诱导的PC12细胞氧化应激损伤。本研究基于AChE和氧化应激阐明了海胆酮对AD的潜在作用机制，为海胆酮在功能食品、生物医药等领域的应用提供了数据支持和理论根据。     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.