Machine learning-based direct solver for one-to-many problems on temporal shaping of relativistic electron beams

To control the temporal profile of a relativistic electron beam to meet requirements of various advanced scientific applications like free-electron-laser and plasma wakefield acceleration, a widely-used technique is to manipulate the dispersion terms which turns out to be one-to-many problems. Due to their intrinsic one-to-many property, current popular stochastic optimization approaches on temporal shaping may face the problems of long computing time or sometimes suggesting only one solution. Here we propose a real-time solver for one-to-many problems of temporal shaping, with the aid of a semi-supervised machine learning method, the conditional generative adversarial network (CGAN). We demonstrate that the CGAN solver can learn the one-to-many dynamics and is able to accurately and quickly predict the required dispersion terms for different custom temporal profiles. This machine learning-based solver is expected to have the potential for wide applications to one-to-many problems in other scientific fields.     

Cluster synchronization in a network of non-identical dynamic systems

Cluster synchronization in a network of non-identical dynamic systems is studied in this paper, using two-cluster synchronization for detailed analysis and discussion. The results show that the common intercluster coupling condition is not always needed for the diffusively coupled network. Several sufficient conditions are obtained by using the Schur unitary triangularization theorem, which extends previous results. Some numerical examples are presented for illustration.     

Interaction between β‐Cyclodextrin and Mixed Cationic‐Anionic Surfactants (2): Aggregation Behavior

The interactions between β‐cyclodextrin (β‐CD) and the mixtures of cationic‐anionic surfactants in the aqueous solution were investigated by surface tension, rheology, and dynamic light scattering measurements. It was shown that the key‐lock interactions between β‐CD and mixed cationic‐anionic surfactants were stronger than the electrostatic/hydrophobic interactions between cationic and anionic surfactants. The inclusion of β‐CD to surfactants could destroy the ion‐pair and aggregates of cationic‐anionic surfactants, and even inhibited the precipitation of the mixed cationic‐anionic surfactants. Furthermore, the inclusion of β‐CD to surfactants could also destroy the hydrogen bond between β‐CD molecules, inducing the disassociation of the aggregation formed by β‐CD themselves.     

含绿色荧光蛋白发色团双自由基分子的非线性光学性质

采用密度泛函理论(DFT)方法研究了系列含绿色荧光蛋白发色团双自由基分子光学异构体的几何结构、极化率(αs)和第一超极化率(βtot).结果表明,引入电子给受体取代基使分子的极化率增大,而对第一超极化率有不同影响.对于光照前的反式结构,引入电子受体βtot值增加,且βtot值随取代基吸电子能力的增强而增大;引入电子给体βtot值降低,且βtot值随取代基给电子能力的增强而减小.当分子变成相应的顺式结构时,其βtot值变化趋势与反式结构的结果正好相反.光异构化前后分子的βtot值变化不同,引入电子受体使顺式结构的βtot值比反式结构的小,其中―NO2使顺式结构的βtot值减小为反式结构的1/6;引入电子给体使反式结构的βtot值比顺式结构的小,其中―NH2使反式结构的βtot值减小为顺式结构的1/6.从而,光异构化起到调节非线性光学(NLO)响应的作用.     

18O同位素标记定量肽段串联体蛋白质结合同位素稀释-多反应监测质谱的蛋白质绝对定量新方法

建立了定量肽段串联体蛋白质(concatamers of Q peptides, QconCATs)结合¹⁸O同位素标记-多反应监测质谱的蛋白质绝对定量新方法。首先对QconCAT重组蛋白质进行了纯度表征,十二烷基硫酸钠-聚丙烯酰胺凝胶电泳(SDS-PAGE)表征结果表明重组蛋白质的纯度在99%以上,相对分子质量约为63.4 kDa。对QconCAT重组蛋白质酶切后的肽段混合物进行质谱分析,并经pFind和pLabel软件处理,验证了目标肽段。还考察了QconCAT重组蛋白质的酶切效率和¹⁸O标记效率,并对QconCAT蛋白质结合¹⁸O标记-同位素稀释-多反应监测质谱方法进行了评价。实验结果表明,采用该方法对腾冲嗜热厌氧菌(Thermoanaerobacter tengcongensis, TTE)中选定蛋白质的肽段进行绝对含量测定时,相对标准偏差小于20%,准确度较高,说明该方法可用于复杂生物样本中蛋白质的绝对定量。更重要的是所建方法不仅解决了细胞培养氨基酸稳定同位素标记(SILAC)技术的重标试剂价格昂贵的问题,也为定量蛋白质组学提供了一种新的方法。     

加速溶剂萃取-气相色谱法测定木材中五氯酚残留量

提出了气相色谱法测定木材中五氯酚残留量的方法。样品用乙醇经加速溶剂萃取仪在100℃静态萃取10 min。采用DB-5毛细管柱分离,电子捕获检测器测定五氯酚含量。五氯酚的质量浓度在0.01～50 mg·L^-1范围内与峰面积呈线性关系,方法的检出限（3S/N）为0.01 mg·kg^-1。以木材样品为基体,进行加标回收试验,回收率在94.2%～98.2%之间,测定值的相对标准偏差（n=6）小于4%。     

分数阶微分方程m点边值共振问题解的存在性

利用Mawhin延拓定理考察了一类分数阶微分方程m点边值共振问题解的存在性.得到了解的存在性的一个充分性条件,并且举出实例用以说明主要结果.     

Copper‐Catalyzed Aerobic Oxidative C?C Bond Cleavage for C?N Bond Formation: From Ketones to Amides

A novel copper‐catalyzed aerobic oxidative C(CO) C(alkyl) bond cleavage reaction of aryl alkyl ketones for C N bond formation is described. A series of acetophenone derivatives as well as more challenging aryl ketones with long‐chain alkyl substituents could be selectively cleaved and converted into the corresponding amides, which are frequently found in biologically active compounds and pharmaceuticals.