ICP-MS法测定黔产枳椇果梗、枳椇子中22种金属元素

建立微波消解-电感耦合等离子体质谱(ICP-MS)法同时分析枳椇果梗、枳椇子中Be、Mg、Al、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Sr、Mo、Ag、Cd、Sn、Sb、Ba、Tl、Pb等22种元素的含量。样品经微波消解后,利用ICP-MS测定上述22种元素,通过标准曲线计算其含量。实验结果表明,22种元素在其线性范围内线性关系良好,r值0.995;检出限为0.0007～1.0713μg/L;重复性的相对标准偏差(RSD)3%;精密度的相对标准偏差(RSD)7%;回收率为81.14%～112.91%。该方法灵敏度高,重复性好,分析速度快,适用于枳椇果梗、枳椇子中22种元素的含量测定。     

中立型分数阶微分控制系统能控性

研究一类分数阶中立型微分控制系统的能控性问题,对系统状态方程的分析,利用拉普拉斯变换通过基本控制系统的基础解给出了控制系统通解的表达式,并且通过构造格拉姆矩阵,研究了控制系统能控性的充分必要条件;最后通过举出一个格拉姆矩阵的计算举例来进行验证。     

基于改进Faster R-CNN的农田残膜识别方法

为了实现农田残膜的精准捡拾,提高残膜回收机的回收率.将改进Faster R-CNN卷积神经网络运用到农田残膜的识别检测中,提出了一种农田残膜的识别方法.以11MS-1850残膜回收机工作后遗留在农田表面的残膜为研究对象,分别在晴天、阴天不同时间段采集图像共计1648幅.通过更改图像亮度、旋转等方式扩充数据集,最终得到4950幅残膜样本图像,按照7:2:1划分为训练集(3465幅)、验证集(990幅)、测试集(495幅);采用双阈值算法替代传统的单阈值算法,降低了阈值对模型性能的影响;通过对比试验,选取具有残差网络结构的ResNet50作为主干特征提取网络,准确率可达88.84％,召回率为87.70％,总体精度为88.27％;为了使检测模型对小目标更加灵敏,根据数据集中残膜尺寸大小,在原有锚点基础上增加322和642的尺度参数,准确率、召回率、总体精度分别提升了1.29％、0.67％、0.97％,单幅检测时间为284.13 ms,基本满足了识别残膜的要求.可为残膜回收机加装补收装置提供参考,为研制人工智能残膜回收机提供理论基础.     

Modeling eBay price using stochastic differential equations

Online auctions have become increasingly popular in recent years. There is a growing body of research on this topic, whereas modeling online auction price curves constitutes one of the most interesting problems. Most research treats price curves as deterministic functions, which ignores the random effects of external and internal factors. To account for the randomness, a more realistic model using stochastic differential equations is proposed in this paper. The online auction price is modeled by a stochastic differential equation in which the deterministic part is equivalent to the second‐order differential equation model proposed in Wang et al. (Journal of the American Statistical Association, 2008, 103, 1100–1118). The model also includes a component representing the measurement errors. Explicit expressions for the likelihood function are also obtained, from which statistical inference can be conducted. Forecast accuracy of the proposed model is compared with the ODE (ordinary differential equation) approach. Simulation results show that the proposed model performs better.     

激光冲击强化对Ti2AlNb合金微观组织及残余应力的影响

Ti2AlNb(O-Ti2AlNb)具有优异的力学性能,在航空发动机方面有远大应用前景.激光冲击强化(Laser Shock Peening,LSP)是一种先进的表面改性技术,能够在材料表面诱导产生高幅值、大深度的残余压应力,改善材料微观组织,提高材料抗疲劳、高温氧化等性能.本文采用激光冲击强化对Ti2AlNb合金进行表面改性,并研究其组织演变、残余应力以及高温环境对性能的影响.结果表明:激光冲击强化能够显著减小Ti2AlNb合金近表面的晶粒尺寸.显微硬度由冲击前的350 HV提升到395 HV;在冲击区域近表面产生了约-377 MPa的残余压应力;而在高温环境中,由激光冲击强化所诱导的材料近表面残余应力随时间逐渐释放,在600℃条件下,残余应力释放较为缓慢;而在720℃条件下,残余应力迅速释放.     

改进蚱蜢算法在电动汽车充换电站调度中的应用

电动汽车充换电站调度优化问题一般采用群智能优化算法求解，但现有算法存在陷入局部最优、早熟收敛等缺陷，因此提出一种改进的蚱蜢算法:采用边界反弹机制，提高算法效率;引入正余弦搜索机制，加强算法的全局搜索能力;采用Lévy飞行对粒子进行随机扰动，防止种群陷入局部最优;采用非线性收敛策略加快算法后期的收敛速度.实验结果表明，该算法在电动汽车充换电站调度优化问题上，性能优于原始蚱蜢算法以及其他现有群智能算法.     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.     

水溶性La_(0.88)Sr_(0.12)MnO_3纳米粒子的非水相合成

采用纳米微乳液法,以三嵌段共聚物聚氧乙烯-聚氧丙烯-聚氧乙烯(PEO-PPO-PEO)为表面活性剂,乙酰丙酮镧(III),乙酰丙酮锰(III)和乙酰丙酮锶(II)为前驱体,1,2-十六烷二醇为还原剂成功合成了水溶性La0.88Sr0.12MnO3纳米粒子.FT-IR分析证实该纳米粒子表面存在PEO-PPO-PEO分子,XRD和TEM分析表明该纳米粒子基本上呈球形、粒径分布窄、结晶度高,VSM测试表明该纳米粒子室温下显示软铁磁性.纳米粒子在水中快速和高效的分散收集过程,表明该纳米粒子具有良好的水溶性和磁操控性.     

Early SIV and HIV infection promotes the LILRB2/MHC-I inhibitory axis in cDCs

Classical dendritic cells (cDCs) play a pivotal role in the early events that tip the immune response toward persistence or viral control. In vitro studies indicate that HIV infection induces the dysregulation of cDCs through binding of the LILRB2 inhibitory receptor to its MHC-I ligands and the strength of this interaction was proposed to drive disease progression. However, the dynamics of the LILRB2/MHC-I inhibitory axis in cDCs during early immune responses against HIV are yet unknown. Here, we show that early HIV-1 infection induces a strong and simultaneous increase of LILRB2 and MHC-I expression on the surface of blood cDCs. We further characterized the early dynamics of LILRB2 and MHC-I expression by showing that SIVmac251 infection of macaques promotes coordinated up-regulation of LILRB2 and MHC-I on cDCs and monocytes/macrophages, from blood and lymph nodes. Orientation towards the LILRB2/MHC-I inhibitory axis starts from the first days of infection and is transiently induced in the entire cDC population in acute phase. Analysis of the factors involved indicates that HIV-1 replication, TLR7/8 triggering, and treatment by IL-10 or type I IFNs increase LILRB2 expression. Finally, enhancement of the LILRB2/MHC-I inhibitory axis is specific to HIV-1 and SIVmac251 infections, as expression of LILRB2 on cDCs decreased in naturally controlled chikungunya virus infection of macaques. Altogether, our data reveal a unique up-regulation of LILRB2 and its MHC-I ligands on cDCs in the early phase of SIV/HIV infection, which may account for immune dysregulation at a critical stage of the anti-viral response.     

EVOKE: A Value-Driven Concept Selection Method for Early System Design

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization. Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for value-driven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the ‘design intent’ of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of value-related information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE’s ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.