Magnetic Resonance Signal Amplification by Reversible Exchange of Selective PyFALGEA Oligopeptide Ligands Towards Epidermal Growth Factor Receptors

The biorelevant PyFALGEA oligopeptide ligand, which is selective towards the epidermal growth factor receptor (EGFR), has been successfully employed as a substrate in magnetic resonance signal amplification by reversible exchange (SABRE) experiments. It is demonstrated that PyFALGEA and the iridium catalyst IMes form a PyFALGEA:IMes molecular complex. The interaction between PyFALGEA:IMes and H₂ results in a ternary SABRE complex. Selective 1D EXSY experiments reveal that this complex is labile, which is an essential condition for successful hyperpolarization by SABRE. Polarization transfer from parahydrogen to PyFALGEA is observed leading to significant enhancement of the ¹H NMR signals of PyFALGEA. Different iridium catalysts and peptides are inspected to discuss the influence of their molecular structures on the efficiency of hyperpolarization. It is observed that PyFALGEA oligopeptide hyperpolarization is more efficient when an iridium catalyst with a sterically less demanding NHC ligand system such as IMesBn is employed. Experiments with shorter analogues of PyFALGEA, that is, PyLGEA and PyEA, show that the bulky phenylalanine from the PyFALGEA oligopeptide causes steric hindrance in the SABRE complex, which hampers hyperpolarization with IMes. Finally, a single-scan ¹H NMR SABRE experiment of PyFALGEA with IMesBn revealed a unique pattern of NMR lines in the hydride region, which can be treated as a fingerprint of this important oligopeptide.     

Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

探讨加强质量监督管理提高电网安全水平

电网的安全水平主要取决于其使用产品的质量是否过关。如果产品的质量较好，则能建造出优质的电网，电网的安全水平便会随之提高。因此，应加强对产品质量的监督管理，从而提高电网的安全水平。我们可建立质量监督管理系统，及时抽检出质量不过关的产品，从而消除电网运行过程中潜在的安全隐患。     

Quantitative risk assessment using a Japanese hydrogen refueling station model

Although hydrogen refueling stations (HRSs) are becoming widespread across Japan and are essential for the operation of fuel cell vehicles, they present potential hazards. A large number of accidents such as explosions or fires have been reported, rendering it necessary to conduct a number of qualitative and quantitative risk assessments for HRSs. Current safety codes and technical standards related to Japanese HRSs have been established based on the results of a qualitative risk assessment and quantitative effectiveness validation of safety measures over ten years ago. In the last decade, there has been much development in the technologies of the components or facilities used in domestic HRSs and much operational experience as well as knowledge to use hydrogen in HRSs safely have been gained through years of commercial operation. The purpose of the present study is to conduct a quantitative risk assessment (QRA) of the latest HRS model representing Japanese HRSs with the most current information and to identify the most significant scenarios that pose the greatest risks to the physical surroundings in the HRS model. The results of the QRA show that the risk contours of 10^?3 and 10^?4 per year were confined within the HRS boundaries, whereas the risk contours of 10^?5 and 10^?6 per year are still present outside the HRS. Comparing the breakdown of the individual risks (IRs) at the risk ranking points, we conclude that the risk of jet fire demonstrates the highest contribution to the risks at all of the risk ranking points and outside the station. To reduce these risks and confine the risk contour of 10^?6 per year within the HRS boundaries, it is necessary to consider risk mitigation measures for jet fires.     

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering, the studies related to risk analysis methodology, design, and operational management, physical phenomena, and emergency preparedness and nuclear security, have been progressed. Especially, ‘risk analysis methodology’ and ‘design and operational management’ are the main categories of the field, in which more than half of published articles on Journal of Nuclear Science and Technology are related to these categories.     

碳酸盐岩岩溶储层多井评价方法及地质应用

多井评价是建立在单井精细解释对比分析基础上的预测储层及含油气性平面分布规律的技术方法,而常规测井资料无法区分碳酸盐岩岩溶储层,因而利用多井评价结果确定岩溶发育程度在平面上的分布规律就显得十分重要。为此,在岩心标定成像测井的基础上,对四川盆地高石梯—磨溪地区15口井的成像测井岩溶发育特征进行分析,建立了中二叠统茅口组岩溶发育各分带的标准成像图版,利用交会图及直方图分析各分带的常规测井响应特征,在此基础上形成了电成像测井刻度常规测井识别岩溶发育带的新方法。研究结果表明:①高石梯—磨溪地区茅口组岩溶带自上而下可划分为风化壳残积带、垂直渗流岩溶带、水平潜流岩溶带以及受岩溶作用较弱的基岩;②风化壳残积带在成像测井图像显示为"暗—亮—暗"条带状模式,垂直渗流岩溶带为垂直线状与暗色斑状组合模式,水平潜流岩溶带为水平线状—层状与斑状组合模式,基岩整体显示为亮色块状模式偶见线状或斑状特征;③有效储层主要发育在垂直渗流带和水平潜流带的顶部;④该区茅口组岩溶发育主要受裂缝发育控制,而裂缝发育又与断层关系密切。结论认为,该新方法对碳酸盐岩岩溶储层的多井评价具有普遍适用性,为四川盆地中二叠统风险探井的部署提供了技术支撑。