Gluten–starch interface characteristics and wheat dough rheology—Insights from hybrid artificial systems

Referring to the total surface existing in wheat dough, gluten–starch interfaces are a major component. However, their impact on dough rheology is largely unclear. Common viewpoints, based on starch surface modifications or reconstitution experiments, failed to show unambiguous relations of interface characteristics and dough rheology. Observing hybrid artificial dough systems with defined particle surface functionalization gives a new perspective. Since surface functionalization standardizes particle–polymer interfaces, the impact on rheology becomes clearly transferable and thus, contributes to a better understanding of gluten–starch interfaces. Based on this perspective, the effect of particle/starch surface functionality is discussed in relation to the rheological properties of natural wheat dough and modified gluten–starch systems. A competitive relation of starch and gluten for intermolecular interactions with the network-forming polymer becomes apparent during network development by adsorption phenomena. This gluten–starch adhesiveness delays the beginning of non-linearity under large deformations, thus contributing to a high deformability of dough. Consequently, starch surface functionality affects the mechanical properties, starting from network formation and ending with the thermal fixation of structure.     

优化GD-模糊规则的滑坡预报模型研究

为了提高滑坡灾害预报准确率，改善传统的滑坡监测和预报中存在的参数选取困难及模糊控制系统作为预报模型精确度不高的问题，首先采用山体结构稳定性分析法进行滑坡灾害参数的选取，得出降雨量、含水率、土压力及岩土表面位移增量作为预报参数的结论；其次将选取的参数作为模糊系统的输入，建立滑坡灾害发生概率模型，并引入优化的GD算法修正预报模型中的动态参数，使模糊控制模型具有自适应性；同时与未优化的模糊控制模型以及单独模糊控制模型进行仿真对比，仿真结果表明，该控制算法收敛速度快，具有很好的收敛性；最后将该模型在某滑坡重点灾区实验区进行实验测试，实验结果显示该模型具有较好的收敛性，且预报精度达到90%。     

Full Eulerian deformable solid-fluid interaction scheme based on building-cube method for large-scale parallel computing

We propose a full Eulerian incompressible solid-fluid interaction scheme capable of achieving high parallel efficiency and easily generating meshes for complex solid geometries. While good scalability of a full Eulerian solid-fluid interaction formulation has been reported by Sugiyama et al, their analysis was carried out using uniform Cartesian mesh and an artificial compressibility method. Typically, it is more challenging to achieve good scalability for hierarchical Cartesian meshes and a fully incompressible formulation. In addition, the conventional full Eulerian methods require a large computational cost to resolve complex solid geometries due to the usage of uniform Cartesian meshes. In an attempt to overcome the aforementioned issues, we employ the building-cube method, where the computational domain is divided into cubic regions called cubes. Each cube is divided at equal intervals, the same number of cubes is assigned to each core, and the spatial loop processing is executed for each cube. The numerical method is verified by computing five numerical examples. In the weak scaling test, the parallel efficiency at 32768 cores with 32 cores as a reference is 93.6%. In the strong scaling test, the parallel efficiency at 32768 cores with 128 cores as a reference is 70.2%.     

大规模生物网络马尔可夫聚类的并行化算法

马尔可夫聚类算法（MCL）是在大规模生物网络中寻找模块的一个有效方法，能够挖掘网络结构和功能影响力较大的模块。算法涉及到大规模矩阵计算，因此复杂度可达立方阶次。针对复杂度高的问题，提出了基于消息传递接口（MPI）的并行化马尔可夫聚类算法以提高算法的计算性能。首先，生物网络转化成邻接矩阵；然后，根据算法的特性，按照矩阵的规模判断并重新生成新矩阵以处理非平方倍数矩阵的计算；其次，并行计算通过按块分配的方式能够有效地实现任意规模矩阵的运算；最后，循环并行计算直至收敛，得到网络聚类结果。通过模拟网络和真实生物网络数据集的实验结果表明，与全块集体式通信（FCC）并行方法相比，平均并行效率提升了10个百分点以上，因此可以将该优化算法应用在不同类型的大规模生物网络中。     

水电站大型竖井施工安全风险控制措施研究

竖井是大型水电工程中广泛采用的重要建筑物,但竖井的传统施工方法存在施工程序复杂、人工劳动强度大、施工效率不高等特点,同时还存在较大的安全风险。通过对杨房沟水电站大型竖井施工过程的研究,总结出精细化控制爆破、小溜渣井施工方式,同时也设计了一套用于运输的综合提升系统。采用上述创新方法不仅减少了繁琐的施工程序,降低了安全施工风险,而且大量采用机械化手段进一步提高了施工效率,确保了该工程竖井施工的安全风险可控。相关措施可为类似工程的竖井施工提供较好的借鉴作用。     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Performance analysis of large-scale MIMO system for wireless backhaul network

In this paper, we present a performance analysis of large-scale multi-input multi-output (MIMO) systems for wireless backhaul networks. We focus on fully connected N nodes in a wireless meshed and multi-hop network topology. We also consider a large number of antennas at both the receiver and transmitter. We investigate the transmission schemes to support fully connected N nodes for half-duplex and full-duplex transmission, analyze the achievable ergodic sum rate among N nodes, and propose a closed-form expression of the achievable ergodic sum rate for each scheme. Furthermore, we present numerical evaluation results and compare the resuts with closed-form expressions.     

某水电站古滑坡体滑速涌浪分析

某水电站古滑坡体位于库首右岸的峡谷进口段,总方量约1 327×10~4 m~3,历史上该滑坡体曾多次发生滑动,目前处于临界稳定状态。古滑坡体下游侧边缘距离水电站建筑物较近,水电站扩建过程中施工因素及扩建后水库水位上升对古滑坡体的稳定影响较大,一旦滑坡体再次启动滑入水库,激起的涌浪对该工程威胁较大。基于潘家铮滑速计算方法,对计算式进行改进,编写了Fortran计算程序,运用改进后的潘家铮滑速计算方法分析了该古滑坡体的加速度、速度的变化规律;分别采用潘家铮涌浪计算方法和水科院经验公式预测了滑坡体入库激起对岸涌浪高度和坝址处涌浪高度,研究成果对工程建设具有指导意义。     

高可靠重载升降装置技术研究

传统大型升降装置体积大，升降速度低，同步性差、启停冲击大，可靠性低，不满足大型贵重负载的升降需求。通过机械、电子、液压一体化设计，对大型贵重负载重载升降装置的设计方案进行了对比论证，并给出了综合最优解,为某重要产品的设计提供了技术支撑。