亭台楼阁类建筑的文学价值

亭台楼阁作为中国古代的传统建筑,其特殊的体式、功能及其与自然环境所构成的独特意境,成为历代文人登高临远的重要场所,形成了大量诗文,这些作品往往寄寓了游子怀乡、壮士悲歌、文士不遇等情感,许多名篇对后人产生了强大的精神感召力,成为中华民族精神文化遗产的一部分。     

主动雷达成像导引头几个问题的研究

研究了主动雷达成像导引头的工作模式、成像方法和系统控制方式。通过对雷达导引头子孔径数据进行聚束处理，在短时间和大前斜视角情况下完成对其天线波束覆盖的地面目标区域的快速成像，利用雷达图像跟踪和单脉冲跟踪两种跟踪模式分别解决对目标的远距离前斜视跟踪和近距离前视跟踪问题。分析设计了一近程主动雷达成像导引头在Ku和Ka波段的指标并给出其主要的技术参数。     

Spray drying of a phenolic‐rich membrane filtration fraction of olive mill wastewater: optimisation and dried product quality

Olive mill wastewater (OMWW) from 3‐ and 2‐phase mills was subjected to a two‐step membrane filtration process. The obtained reverse osmosis retentate (RO‐R) is a phenolic‐rich coproduct stream, and the reverse osmosis permeate is a near‐pure water stream. A pilot‐scale spray dryer was used for the production of RO‐R powder. The optimum temperature/feed pump conditions were obtained for 3‐phase (150°C/4.4 Hz) and for 2‐phase RO‐R (175°C/3.8 Hz). The powders obtained by spray drying under these conditions were analysed for physicochemical properties, including identification and quantification of phenolic compounds. Protocatechuic acid, 3‐hydroxytyrosol, tyrosol, vanillic acid and p‐coumaric acid were quantified in both RO‐R powders, which show the possibility to obtain a phenolic‐rich powder from an OMWW filtration fraction. This will lead towards better usage of by‐products from olive oil production.     

面向数据流结构的指令映射优化方法

在高性能计算领域,数据流是一类重要的计算结构,也在很多实际场景表现出很好的性能和适用性。在数据流计算模式中,程序是以数据流图来表示的,数据流计算中一个关键的问题是如何将数据流图映射到多个执行单元上。通过分析现有数据流结构的指令映射方法及其不足,提出了基于数据流结构的新型指令映射优化方法。主要是根据多地址共享数据包的特性对指令映射方法进行优化,延迟多地址共享数据路由包的拆分,减少网络拥堵。     

The APOA5-rs662799 Polymorphism Is a Determinant of Dyslipidemia in Vietnamese Primary School Children

Apolipoprotein A-V encoded by apolipoprotein 5 (APOA5) gene plays an important role in lipid metabolism, especially in the regulation of plasma triglycerol levels. The study aimed to evaluate the association of the APOA5-rs662799 polymorphism with dyslipidemia in Vietnamese children and the potential modification of obesity-related traits (body mass index, waist circumference, hip circumference, and waist-to-hip ratio) on this association. A case–control study was conducted with a total of 154 dyslipidemia cases and 389 controls at the age of 6 to 10 recruited at 31 primary schools in Hanoi city of Vietnam. Genotype for APOA5-rs662799 polymorphism was determined by the restriction fragment length polymorphism analysis. The association of APOA5-rs662799 polymorphism with dyslipidemia adjusting for age, sex, residence, and obesity-related traits was analyzed by binary logistic regression analysis. The results showed that in comparison with T/T and T/C carriers, the C/C carriers had a higher concentration of serum TAG in cases (p =0.049). Carriers of the C allele (C/C + T/C) had higher risk for developing dyslipidemia and hypertriglyceridemia than subjects with T/T genotype (odds ratio, OR = 1.7, p =0.0062 and OR = 1.6, p = 0.026, respectively). The association remained significant after adjusting for age, gender, residence, and obesity status (OR = 1.75, p = 0.006 and OR = 1.53, p = 0.049, respectively) or other obesity-related traits. The study suggested that the APOA5-rs662799 polymorphism may be a determinant of dyslipidemia and hypertriglyceridemia in Vietnamese children, independent of obesity-related traits.     

Robust eigenstructure clustering by non-smooth optimisation

We extend classical eigenstructure assignment to more realistic problems, where additional performance and robustness specifications arise. Our aim is to combine time-domain constraints, as reflected by pole location and eigenvector structure, with frequency-domain objectives such as the H₂, H_∞ or Hankel norms. Using pole clustering, we allow poles to move in polydisks of prescribed size around their nominal values, driven by optimisation. Eigenelements, that is poles and eigenvectors, are allowed to move simultaneously and serve as decision variables in a specialised non-smooth optimisation technique. Two aerospace applications illustrate the power of the new method.     

A study of bicycle dynamics via system identification approaches

This study investigates bicycle dynamic properties by using system identification approaches. The non-linear bicycle model with configuration parameters from a previously developed benchmark model is studied. The roll angle of the bicycle is controlled at different speeds to generate input–output data including steering torque, roll, and steering angles. The collected data are then used to identify the one-input two-output linear model by a prediction-error identification method using parameterization in canonical state-space form derived as Whipple's model. Simulations are used to verify the accuracy of the generated linear model. Numerous properties for various speed ranges are discussed from the pole and zero locations of the identified linear model. The system stability, limit-cycle phase portraits of the roll and steering angles, and the non-minimum phase property of the non-linear system are further investigated and compared with the corresponding linearized results from previous studies in the literature.     

Fabrication of platinum nanoparticle counter electrode for highly efficient dye-sensitized solar cells by controlled thermal reduction time

We report the effect of the thermal reduction time during sintering on the electrocatalytic activity and the morphology of platinum nanoparticles (Pt-NPs) fabricated using thermal decomposition method. A uniform and dense distribution of Pt-NPs on fluorine-doped tin oxide glass substrate was achieved by controlling the thermal reduction time higher than 15 min and this morphology of Pt-NPs was responded for high electrocatalytic performance of counter electrode (CE). As expected, the excellent electrocatalytic activity with low charge-transfer resistance of 1.04 Ω cm² and highly conductivity of Pt-NPs CE prepared at the thermal reduction time of 15 min during sintering was obtained, which was desirable for dye-sensitized solar cells. The energy conversion efficiency of 9.43 % was obtained for the thermal reduction time of 15 min with fill factor of 63.05 %, J _sc of 18.82 mA cm^?2 and V _oc of 795 mV.     

An Evaluation of Different Controllers Based on the Network Frequency Maintenance Strategy for a Large and Multi-control-area Interconnected Power System

Abstract—Maintaining the network frequency at its nominal value due to the load changes is one of the most important issues in the control and operation schedule of a large and multi-area interconnected power system. For the effective control solution, two types of tie-line bias control strategy-based controllers have been applied, i.e., classical and improved controllers. The classical controllers using conventional regulators, including integral, proportional–integral and proportional-integral-derivative, have achieved initial control results to bring the steady state back to the network. However, due to the very poor control features (e.g., large overshoots and long settling times), they need to be replaced with improved controllers, such as fuzzy logic and artificial neural network. To obtain an entire evaluation of the application of different load-frequency controllers, a five-control-area interconnected power system was built as a typical case study. Three improved controllers using proportional-plus-integral-based fuzzy logic and artificial neural network-based non-linear autoregressive moving average (NARMA-L2) architectures as well as their hybrid combination will also be investigated in this study. Simulation results obtained reveal that the improved controllers have obtained smaller overshoots (from 13.95 to 84.18%) and shorter settling times (from 19.91 to 65.71%) compared with the classical controllers.