Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.     

Selective Binding of Cyclodextrins with Leflunomide and Its Pharmacologically Active Metabolite Teriflunomide

The selectivity of encapsulation of leflunomide and teriflunomide by native α-, β- and γ-cyclodextrins was investigated through ¹H NMR and molecular modeling. Thermodynamic analysis revealed the main driving forces involved in the binding. For α-cyclodextrin, the partial encapsulation was obtained while deep penetration was characterized for the other two cyclodextrins, where the remaining polar fragment of the molecule is located outside the macrocyclic cavity. The interactions via hydrogen bonding are responsible for high negative enthalpy and entropy changes accompanying the complexation of cyclodextrins with teriflunomide. These results were in agreement with the molecular modeling calculations, which provide a clearer picture of the involved interactions at the atomic level.     

复杂应力区段煤柱合理留设宽度仿真研究

针对南关煤矿3205运输巷道工作面掘进与支护困难、巷道变形严重且维修频繁的现状,为破解复杂应力情况下煤柱合理留设宽度这一关键性问题,借助FLAC 3D软件进行了应力场与位移场仿真分析。研究结果表明:显著的水平应力场、邻近的采动应力场与劣化的围岩稳定性三重因素的综合作用是制约3205运输巷正常掘进作业的瓶颈。在不同煤柱宽度方案比选过程中,窄煤柱在应对较强水平应力与剪切应力作用时处于劣势。煤柱宽度越大,采动应力场对煤柱及工作面的影响越小,采掘活动更为安全。经过方案比选,最终确立留设煤柱在复杂应力区段的合理宽度为30 m。     

一种大型复杂构件加工新模式及新装备探讨

大型复杂构件是航空航天、能源、船舶等领域装备的核心结构件，此类构件通常具有尺寸大、形状复杂、刚性弱等特点。传统“分体离线加工-在线检测”模式存在工艺不稳定、过程复杂、柔性差、周期长等问题，以龙门式多轴数控机床加工为代表的“包容式”加工模式，难以适应大型复杂构件的高效高质量加工制造需求。提出一种基于移动式和吸附式机器人的多机协同原位加工新模式，通过多机器人系统自主寻位、精确定位加工与加工质量原位检测，实现大型复杂构件多安装面并行铣削、制孔与打磨等作业。多机器人系统包括移动式混联机器人、吸附式并联机器人、移动式串联铣削机器人、移动式双臂加工机器人和移动式打磨机器人。构建多机协同原位加工模式，需要揭示多机器人协同原位加工行为与大型弱刚性结构件质量控制的交互机理，面临着本体、测量、工艺和集成四个方面的挑战，需要设计高灵活、高刚度的移动式和吸附式加工机器人，解决移动机器人自主准确寻位和超大结构件原位高精检测难题，攻克加工变形误差在线补偿和振动抑制技术，通过集成实现多机协同高效高精加工，为大型复杂构件的高效高质量制造提供创新技术及装备，并实现此类构件制造核心技术及装备自主可控。     

慢刀伺服车削刀具半径定向补偿的分段逼近求解

复杂曲面的慢刀伺服车削加工过程中，采用刀具法向补偿算法会在各个直线轴产生补偿量，加工法向矢量突变的曲面时，这种算法并非最优，将补偿量只应用于负载较低的直线轴却是更优的选择。提出一种基于线段逼近的刀具半径定向补偿数值求解算法来求解定向刀位点，通过半径细分的策略使法向误差收敛。算法实例验证及与相关算法的对比结果显示，该算法适用于点云构成的曲面或分段曲面的刀具半径补偿。     

Comprehensive reliability evaluation of multistate complex electromechanical systems based on similarity of cloud models

High reliability and security have become the hallmarks of complex electromechanical systems. Owing to the difficulties in fault data collection, ambiguity and uncertainty have been inevitably associated with complex electromechanical systems. Thus, the ability to perform reliability evaluation using scarce fault data is of immense significance to these machines and is the focus of this study. A similarity based cloud model is proposed to evaluate the running state of complex electromechanical systems. By combining objective and subjective factors, the reliability of complex electromechanical systems is evaluated by calculating the similarity between the cloud models of actual and standardised states. Next, the inverter of an offshore wind turbine is used to verify the accuracy and effectiveness of the proposed approach. The cloud model based framework for reliability evaluation inherits the preponderance of the uncertainty problem, overcomes the drawbacks of the current reliability approaches, and provides a theoretical basis, as well as a practical approach for the maintenance and repair of complex electromechanical systems with missing fault data. Additionally, it also provides a new methodology for solving the uncertainty problems caused by paucity of data.     

新工科背景下现代设计方法教学探讨

“现代设计方法”是机电工程专业一门重要的专业必修课程。聚集于新工科中解决复杂工程问题的能力这一重要目标,针对目前教学中存在的一些不足之处,本文从教学内容、教学模式与教学方法等角度提出了相应的教学改革措施,为进一步培养学生解决复杂工程问题能力提供借鉴。     

Microencapsulation of camellia oil to maintain thermal and oxidative stability with focus on protective mechanism

Camellia oil (CO) microcapsules were developed using chitosan–soybean protein isolate (CS-SPI) complexes as wall materials and transglutaminase (TGase) as the cross-linking agent. Results indicated that CO/SPI under the ratio of 1:2 exhibited the highest microencapsulation efficiency and yield, possessing the best encapsulation effect. Morphology observation showed that CO microcapsules were intact, compact and nearly spherical. The microencapsulated CO exhibited the improved thermal resistance and significantly lower peroxide values after 3 days storage, demonstrating that the produced microcapsule was a promising way to maintain the thermal and oxidative stability of camellia oil. It could be found evidence from FTIR, which indicated that covalent cross-linking and hydrogen bonding might be involved among wall materials, and physical interactions between the core and wall materials. Therefore, the produced CO microcapsules could be an effective way to protect camellia oil, which was helpful for improving the processing and storage qualities of camellia oil.     

Predictive economic efficiency of combining nuclear power plants with autonomous hydrogen power complex

Currently, the United Energy System (UEC) of Russia is trending in the deficit of peak and half-peak capacity with a simultaneous increase in the number of nuclear power plants (NPPs), which will require the participation of the NPPs in the variable part of the schedule of electrical loads.In addition to the economic need to maintain the high-level utilization rate, there are technological limitations of maneuverability for NPPs.The authors developed an approach to solving this problem by combining with an environmentally friendly energy source – an autonomous hydrogen power complex, which includes thermal batteries and an additional multifunctional low-power steam turbine installation.The developed energy complex can also provide reliable reservation of electricity supply to consumers of their own needs of the nuclear power plant in case of complete blackout of the plant.The feasibility study of the main equipment of the autonomous hydrogen power complex, which is necessary for combining with a two-unit nuclear power plant with WWER-1000, has been evaluated.On the basis of the assessment of the inflation indicators of the Russian economy over the past 11 years, three variants of fuel cost dynamics and tariff rates for electricity (capacity) as well as the size of operating costs, including depreciation deductions to the main equipment, are defined, taking into account the current principles of price formation.The result is a value for accumulated net present value, depending on the ratio of the cost of the half-peak and off-peak electricity at different inflation rates.The positive economic effect of reducing the risk of the core damage accident, replacing the construction of the gas turbine unit as a maneuverable source of electricity in the power grid and increasing the income of the Russian federal budget from the savings of natural gas has been taken into account.The greatest economic efficiency is achieved with maximum projected inflation, which is associated with the maximum rate of discounting and the high rate of growth of electricity tariffs.Reducing the risk of the core damage accident ensures that the proposed approach is competitive in all the inflation options under consideration and the ratio of electricity tariffs.     

Passivity and synchronisation of complex dynamical networks with multiple derivative couplings

Two network models with multiple derivative couplings and different dimensions of output and input vectors are investigated in this paper. The problem of passivity for the proposed network models is analysed by utilising some inequality techniques and Lyapunov functional method, and several synchronisation conditions for complex dynamical networks with multiple derivative couplings (CDNMDC) are given. Moreover, by employing adaptive state feedback control strategy, some sufficient conditions for guaranteeing passivity and synchronisation of CDNMDC are obtained. In the end, we give two examples to verify the effectiveness of the results.