Separation of closely related structural isomers by inclusion complexation with tailor-made host compounds. Crystal structures of 2,2-di (p-hydroxyphenyl) propane and Its 1:1 complex withp-cresol

The crystal structures of the 2,2-di(p-hydroxyphenyl)propane host and its 1:1 adducts withm-andp-cresol guests have been studied. The preferential complexation of this host withp-cresol overm-cresol is related to the opposite trend exhibited by 1,1-di(p-hydroxyphenyl)cyclohexane; both hosts can separate effectively the two cresols from their liquid mixture by crystalline inclusion. A plausible explanation of the different inclusion features is provided by examining the intermolecular association in the corresponding solids. The analysed structures are stabilized by strong and continuous H-bonding between the constituent entities along two dimensions, and by weak van der Waals forces along the third axis. The p-cresol complex of the title host reveals a unique arrangement within and a more efficient packing of the layered structure, and thus represents a more stable and less soluble crystal lattice than itsm-cresol analog. Supplementary Data relating to this article are deposited with the British Library as Supplementary Publication No. SUP 82099 (8 pages).     

Multipoint recognition of catecholamines by hydrindacene-based receptors accompanied by the complexation-induced conformational switching

The molecular recognition of catecholamines by hydrindacene-based receptors 1 and 2, as well as the durene-based receptor 3, and the guest-induced conformational changes are reported. These receptors selectively bind adrenaline and dopamine salts through the guests' ammonium group and 3-hydroxyl group on the aromatic ring. In the case of adrenaline, an additional hydrogen bond with a benzylic hydroxyl group is formed. In 2 % CD3CN/CDCl3, the association constants are of the order of 10(4) M(-1), which is much larger than with guests without the 3-hydroxyl groups (10(3) M(-1)). The two amide groups of receptor 1 can rotate freely around the C(aromatic)--C(amide) bond, whereas the tert-amide in 2 changes between two stable conformations at a slow enough rate to allow detection by (1)H NMR spectroscopy. In the absence of a guest molecule, the syn-conformer is less stable than the anti-conformer. On complex formation with adrenaline, the syn-conformer becomes dominant due to an intramolecular dipole-reversal effect in addition to multipoint hydrogen bonding.     

Molecule-Responsive Fluorescent Sensors of α-Helix Peptides Bearing α-Cyclodextrin, Pyrene and Nitrobenzene Units in Their Side Chains

-Helix peptides bearing one unit of -cyclodextrin (-CD), one unit of pyrene and one unit of nitrobenzene (NB) in their side chains have been designed and synthesized as novel molecule-responsive devices.In both the CD-peptides, -PR17 and -PL17, the NB unit is separated from the CD unit by two turns of the helix. Two reference peptides (PL17, and -P17,) have also been synthesized. The circular dichroism studies in the peptide absorption region (200–250 nm)of -PR17 and -PL17 suggestthat the CD-peptides form stable-helixstructures (83–77%), which was destabilized by accommodating guest molecules (e.g., n-pentanol) into the CD cavity. It suggests that formation of intramolecular host–guest(CD–NB) complex stabilized thehelical structure and exogenous guest molecule excluded the appending NB moiety from inside to outside of the CD cavity, thereby causing destabilization of the helical structure and increasing the random coil content. The ICD spectra of the peptides in the pyrene and nitrobenzene absorption region (250–40 nm) suggest that NB forms inclusion complex with CD. The fluorescence studies revealed that the fluorescence of the pyrene unit is quenched by the NB unit in -PR17 and -PL17. The fluorescence intensity increases with increasing guest concentration for the CD-peptides.This guest-responsiveenhancement in the fluorescence intensity can be explained in terms of increased distance between the pyrene and NB moieties, which is caused by exclusion of the NB moiety from the CD cavity by guest accommodation. Using the guest-responsive fluorescence quenching properties of the CD-peptides, we have obtained binding constants for various short chain alkanols. -PL17 has higher binding affinity to the guest molecules than its isomer, -PR17, indicating that the location of functional groups on the peptide scaffold is important in molecule detection.     

β—环糊精对D／L—酪氨酸对映体的手性识别及超分子包合物的合成

利用圆二色谱研究了β－环糊精（β－ＣＤ）对Ｄ／Ｌ酪氨酸的手性识别行为，制备出了β－ＣＤ与Ｌ－酪氨酸（Ｌ－Ｔｙｒ）的固体超分子化合物，并用元素分析、薄层分析、Ｘ射线粉末衍射及热分析对包合物进行了表征，用荧光光谱法测定了包合物的形成常数．实验结果表明，β－ＣＤ具有选择包结Ｌ－酪氨酸的特性；主客体形成１１的包合物，其组成为Ｌ－Ｔｙｒ／β－ＣＤ·１２Ｈ２Ｏ；稳定常数为５．１３×１０３Ｌ／ｍｏｌ；包合物的热稳定性比主客体皆有改善     

Preparation of Saccharide-Silica Composites by a Sol-Gel Method and the Application for Optical Resolution of Metal Chelate Compounds

A novel organic-inorganic composite was prepared by a sol-gel process using hydrolysis and condensation of tetraethoxysilane (TEOS) reacted with a saccharide. During the process, ethoxy groups of the TEOS were replaced with hydroxyl groups of the saccharide and, consequently, saccharide molecules were combined with silica through their hydroxyl groups. Samples obtained under different reaction conditions were used for optical resolution of a metal chelate compound. The resolution ability of the composites was affected by the amount of water added for hydrolysis and of the saccharide. In particular, the amount of water drastically influenced the optical resolution performance. Composites obtained at the lower H2O/TEOS ratio gave the metal chelate compound a higher optical rotation. Three types of composites with the same composition were prepared by kneading, impregnation and by the sol-gel method, and were compared. The sol-gel composite showed the best optical resolution ability. It was concluded that the optical resolution ability was closely related to dispersibility of saccharide in the silica matrix.     

Should I scan my face? The influence of perceived value and trust on Chinese users’ intention to use facial recognition payment

While China has seen the widespread adoption of facial recognition payment, concerns over the potential risks impede the further growth of user acceptance. Drawing on the perspectives of perceived value and trust, we developed a research model to explore how the Chinese users’ trade-off between perceived benefits (perceived convenience and perceived novelty) and perceived risks (perceived privacy risk and perceived financial risk) influences their usage intention. Based on survey data from 1,200 Chinese mobile payment users, this study uses structural equation modeling to examine the hypotheses. Our results show that perceived convenience positively influences perceived value, while privacy risk and financial risk negatively influence perceived value and trust. Although perceived novelty has no significant effect on perceived value and trust, perceived value positively influences trust, and both of them have a positive effect on the intention to use. Furthermore, our moderation analysis indicates that the influence of perceived value on the intention to use is stronger among users who consider facial information to be more sensitive. The theoretical implications for research as well as the practical implications for practitioners are also discussed.     

“模式识别”课程线上线下混合教学模式探索与实践

在模式识别课程教学中,针对传统线下课程短板,开展线上与线下相结合的混合教学模式教学改革探索。阐述了本课程教学改革的教学环节设计、教学实施方法、考核方式等,以思维导图和综合案例串联庞杂知识点,采用多样化手段,加强对学生创新思维和能力的培养。教学实践证明,该课程教学改革调动了学生主动性,培育了其创新能力与科学精神,丰富了线上线下混合教学改革的理论研究。     

基于transformer自适应特征向量融合的图像分类

针对目前基于transformer的图像分类模型直接应用在小数据集上性能较差的问题,本文提出了transformer自适应特征向量融合网络,该网络在特征提取器中将不同阶段的特征进行融合,减少特征信息丢失的同时获得更多不同感受野下的信息,同时利用最大池化来去除特征中的冗余信息,从而使提取的特征更具有判别性。此外,为了充分利用图像的各级特征信息来进行分类预测,本文将网络各阶段产生的特征向量进行融合,使融合后的特征向量更具有表征能力,从而减少网络对大数据集的依赖,使网络在小数据集中也能获得很好的性能。实验表明,本文提出的 算法在数据集Mini-ImageNet-100、CIFAR-100和ImageNet-1k上的TOP-1准确率分别达到了74.22%、85.86%和81.4%。在没有增加计算量的情况下,在baseline上分别提高了6.0%、3.0%和0.1%,且参数量减少了18.3%。本文代码开源在“https://github.com/xhutongxue/afvf”。     

Deep ensemble-based hard sample mining for food recognition

Deep neural networks represent a compelling technique to tackle complex real-world problems, but are over-parameterized and often suffer from over- or under-confident estimates. Deep ensembles have shown better parameter estimations and often provide reliable uncertainty estimates that contribute to the robustness of the results. In this work, we propose a new metric to identify samples that are hard to classify. Our metric is defined as coincidence score for deep ensembles which measures the agreement of its individual models. The main hypothesis we rely on is that deep learning algorithms learn the low-loss samples better compared to large-loss samples. In order to compensate for this, we use controlled over-sampling on the identified ”hard” samples using proper data augmentation schemes to enable the models to learn those samples better. We validate the proposed metric using two public food datasets on different backbone architectures and show the improvements compared to the conventional deep neural network training using different performance metrics.     

Joint frame rate adaptation and object recognition model selection for stabilized unmanned aerial vehicle surveillance

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.