Synthesis of fluorine-substituted [2.2]paracyclophane-based carbene precursors for copper-catalyzed enantioselective boration of α,β-unsaturated ketones

Fluorine-substituted [2.2]paracyclophane-based carbene precursors have been successfully synthesized and applied to copper-catalyzed asymmetric β-boration of α,β-unsaturated ketones. Fluorination of the planar chiral carbenes has a beneficial impact on the catalytic performance of the relevant complexes. A variety of chiral β-boryl ketones were obtained in excellent yields (up to 99%) and with high enantioselectivities (up to 99% ee).     

BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Scour monitoring is an important concern for subsea pipeline systems. The active-thermometry-based scour monitoring is based on the difference of heat transfer properties between sediment and sand, recognizes the surrounding media though temperature changing patterns during heating and cooling processes, and hence detects the free spans. Based on the scour monitoring system, a two-layer BP neural network was employed to process the monitoring data and achieved media recognition. The network's inputs were normalized temperature time histories. The network's outputs denoted different media: sediment and water. To validate the method, three experiments were conducted; one was used for training the network and the other two for testing. Also, the effect of noise on the network's performance was studied through simulation. The results demonstrated the feasibility and robustness of the neural network.     

阿尔茨海默病诊断的自适应BP神经网络模型

阿尔茨海默病(AD)和轻度认知功能损伤(MCI)具有患者多、诊断难的特点,改进BP神经网络,提出自适应BP神经网络(ABP)进行100次AD和MCI诊断模拟,ABP神经网络的诊断正确率显著高于BP和RBF神经网络.采用留一法将101例正常人、200例MCI和90例AD患者的样本分为训练集和检测集,用ABP神经网络对其进行诊断模拟,总正确率达到73.91%.     

Formula Optimization of Emulsifiers for Preparation of Multiple Emulsions Based on Artificial Neural Networks

Formulation optimization of emulsifiers for preparing multiple emulsions was performed in respect of stability by using artificial neural network (ANN) technique. Stability of multiple emulsions was expressed by the percentage of reserved emulsion volume of freshly prepared sample after centrifugation. Individual properties of multiple emulsions such as droplet size, δ, viscosity of the primary and the multiple emulsions were also considered. A back‐propagation (BP) network was well trained with experimental data pairs and then used as an interpolating function to estimate the stability of emulsions of different formulations. It is found that using mixtures of Span 80 and Tween 80 with different mass ratio as both lipophilic and hydrophilic emulsifiers, multiple W/O/W emulsions can be prepared and the stability is sensitive to the mixed HLB numbers and concentration of the emulsifiers. By feeding ANN with 39 pairs of experimental data, the ANN is well trained and can predict the influences of several formulation variables to the immediate emulsions stability. The validation examination indicated that the immediate stability of the emulsions predicted by the ANN is in good agreement with measured values. ANN therefore could be a powerful tool for rapid screening emulsifier formulation. However, the long‐term stability of the emulsions is not good, possibly due to the variation of the HLB number of the mixed monolayers by diffusion of emulsifier molecules, but can be greatly improved by using a polymer surfactant Arlacel P135 to replace the lipophilic emulsifier.     

广东省能源需求预测模型构建及实证分析

为了对广东省的能源需求进行准确的预测,首先分析了影响广东省能源需求的各种因素,构建了预测指标体系.在此基础上,针对能源系统非线性等复杂系统特征,结合粒子群算法和BP神经网络的优点,构建了改进的PSO-BP神经网络的预测模型,并通过主成分分析法对指标体系进行数据降维,以降低神经网络的规模和复杂程度.以广东省1985-2013年的能源需求数据进行模拟与仿真,并对2014-2018年的能源需求量进行预测,理论分析和实证研究表明,该方法能够很好的反映广东省能源需求的特征,预测结果较为准确合理.     

基于布谷鸟算法与BP神经网络的煤灰变形温度预测

以120种煤样为数据基础,采用布谷鸟算法(CS)优化BP(Back Propagation)神经网络,建立了CSBP模型对单煤、煤掺添加剂和配煤等3类样本的煤灰变形温度(DT)样本进行预测。模型以煤灰化学成分及其组合参数等13个变量作为输入量,以变形温度(DT)作为输出量。CSBP模型预测结果与BP神经网络模型预测结果进行对比发现,无论是单煤、煤掺添加剂还是配煤,CSBP模型较BP模型对煤灰变形温度(DT)的预测都更加精准,平均相对误差分别达到了3.11%、4.08%和4.22%。另外,对比3类样本预测结果发现,无论是CSBP模型还是BP模型,相比单煤预测而言,煤掺添加剂及配煤的预测误差都有明显的增加。     

In2BP3O12:Cr3+宽带近红外荧光粉的发光性能及应用研究※

近红外光谱技术在安防监控、食品检测、生物成像、农业等领域具有重要应用价值, 而开发出紧凑高效的近红外光源是其大规模商业应用的前提. 荧光粉转换型近红外发光二极管(light emitting diodes, LED)光源具有结构紧凑、成本低、使用寿命长、发射光谱可调等优点, 因此近些年受到广泛关注, 其关键就在于开发出能被蓝光有效激发的高性能近红外荧光粉. 本工作利用高温固相法制备了一种新型宽带近红外荧光粉In₂BP₃O₁₂:Cr³⁺, 在480 nm激发下, 荧光粉发射峰值位于950 nm, 光谱覆盖了750~1350 nm范围, 半峰宽达到210 nm. 采用该荧光粉与商用蓝光InGaN LED芯片封装, 获得了具有宽带发射的近红外LED光源, 在60 mA的驱动电流下, 近红外光辐射功率为5 mW. 当采用该光源照射人的手掌, 用近红外电感耦合器(charge coupled device, CCD)相机能够对手掌中的血管进行清晰的成像. 上述结果表明该近红外荧光粉可用于制备基于蓝光芯片的宽带近红外LED光源, 并在生物医学等领域具有潜在应用前景.     

基于GA-BP的移动通信设备故障诊断

针对通信设备故障发生随机性强,影响因素多,对应的故障诊断有高度非线性和不确定性的特点,采用BP神经网络算法,优化的GA-BP神经网络算法和POS-BP神经网络算法分别搭建基站设备故障诊断模型,提取设备故障历史数据进行MATLAB仿真,准确预测设备故障类型,帮助提高代维公司调度管理的智能化水平,提高基站设备运维的执行效率。仿真结果表明：本文的BP,GA-BP和POS-BP神经网络算法都能够实现设备故障类别的预测,且GA-BP神经网络算法相比BP和POS-BP神经网络算法对通信设备故障诊断有更好的适应性。     

Experimental and theoretical analyses on the microwave backscattering ability and differential radar reflectivity of non-spherical hydrometeors

This paper experimentally and theoretically examines the scattering properties of simulated non-spherical hydrometeors including water oblates, ice oblates and ice sphere-cone-oblates, in terms of the backscattering cross-section and the differential reflectivity. The experimental measurements of the backscattering cross-sections of non-spherical hydrometeor samples were performed in the Electromagnetic Scattering Laboratory of China National Space Industrial Corporation. Meanwhile, the backscattering cross-sections have been computed with the transition (T) matrix method. The theoretical results are compared with the experimental data, showing that the calculations are consistent with the observations in general. Experimental and theoretical analyses indicate that the backscattering cross-section of non-spherical particles increases as the particle size parameter increases, and fluctuates when the sizes are larger under the effect of resonance scattering. Differential reflectivity Z_DR of water oblates in natural rainfall is always greater than 0 dB whereas Z_DR of hailstones may be negative. There is a good linear relationship between differential reflectivity and aspect ratio of a particle. These derivations agree with the literature and can be used to identify the presence of hail particles and distinguish between plate-type and columnar-type hydrometeors. In this study, the measuring experiment and the T-matrix method calculations for the scattering of simulated raindrop and ice particles are also briefly described.