The aldol–annulation–fragmentation strategy toward the taxoid diterpene framework revisited. Instructive failures in the chemistry of medium ring containing systems

Central intermediate 5 for the taxoid diterpene framework, prepared by the aldol–annulation sequence, permitted the construction of A-secotaxane frameworks incorporating differentiatable olefin and oxygen functionalities suitable for further elaboration. The key BC-subunits 9 and 8 have proven amenable to efficient conversion into both oxa-bridged 7 and its central eight-membered B-ring analogue 6, providing two potential precursors for taxoid construction. Although their further elaboration into 4 was not progressed at this stage, 6 and 7 are potentially useful synthetic intermediates. Extensive structural studies that included 800 MHz ¹H (200 MHz ¹³C) NMR as well as X-ray crystallographic analyses of 7, 17, and 20 have contributed to the unambiguous elucidation of all the complex structures synthesized.     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.     

Structure and bonding in simple thiazyl compounds

The molcules NSF, NSO⁻, NSCl, HNSF⁺, HNSO, CH₃NSF⁺, CH₃NSO are investigated at the SCF level and partly with inclusion of electron correlation effects. Equilibrium geometries and relative stabilities of isomers and conformers are reported. Structure constants and relative energies are discussed in connection with the molecular electronic structure as characterized by the results of population analyses.     

The synthesis and stereoselective conjugate addition reactions of α-alkoxyorganocuprate reagents

α-Alkoxyorganocuprate reagents have been prepared from α-alkoxyorganostannanes. The cuprates undergo diastereoselective conjugate addition reactions with cyclohexenone with up to 8:92 selectivity. The effects of trimethylsilyl chloride on the chemical yields and the diastereoselectivity of the reaction are described.     

Rapid Detection of Five Estrogens Added Illegally to Dietary Supplements by Combining TLC with Raman Imaging Microscope

Estrogens added illegally to dietary supplements are hazardous to human health. Traditional detection and analysis methods have many limitations, and we have developed an assay that combines thin-layer chromatography with Raman imaging microscopy (TLC-RIM). The five estrogens (estrone, estradiol, estriol, ethinyl estradiol, and diethylstilbestrol) were initially separated by TLC, then detected by area scanning Raman imaging with a 532 nm laser under a microscope. Raman spectra were obtained for each estrogen, which were used for detecting estrogen illegally added to botanical dietary supplements. The LOD of each estrogen was 0.4, 1.0, 0.8, 0.2, and 0.2 mg/mL, respectively. The matrix in the real sample did not interfere with the detection of estrogens. The method was fast, sensitive, stable, specific, and reliable.     

一种锌配合物用于炭疽生物标志物的检测

采用溶剂热合成方法,合成了一种新型金属配位聚合物{[Zn₂(L)(H₂O)(DMA)]·DMA·2.3H₂O}_n (1),其中L^4-为完全脱去质子的N,N''-二(4-羧基苄基)-5-氨基间苯二甲酸,DMA为N,N-二甲基乙酰胺。单晶X射线衍射结果显示,该配合物属于三斜晶系,空间群为P$overline{1}$,a=0.989 6(5) nm,b=1.370 5(5) nm,c=1.382 1(5) nm,α=80.067(5)°,β=76.729(5)°,γ=76.611(5)°,结构是由二维金属有机层通过π…π相互作用而扩展成的三维超分子骨架。红外光谱验证了锌离子与L^4-配体成功配位。粉末X射线衍射(PXRD)实验证实了配合物1具有较高的纯度。热重分析结果显示配合物1在室温至416.9 ℃区间内具有较好的热稳定性。在273 nm的激发光下,配合物1在437 nm处有较强的荧光发射,可以在30 s内快速检测乙醇溶液中的炭疽生物标志物——吡啶-2,6-二甲酸,具有选择性高、抗干扰能力强、检测限低(约为15 μmol·L^-1)等特点。结合PXRD图和紫外可见吸收光谱揭示了其检测机理为晶体骨架坍塌而诱导的荧光猝灭。     

Photoluminescence of green nanophosphors Sr2MgSi2O7 doped with Tb3+ under 374-nm excitation

A series of Sr₂MgSi₂O₇:Tb³⁺ nanophosphors is prepared using a high-temperature solid-state reaction. The x-ray diffraction patterns show that the crystal structure of the sample is not significantly affected by Tb³⁺ ions. However, the images of the scanning electron microscope illustrate that the average size of nanoparticles becomes larger with the increase of Tb³⁺ concentration. Unlike earlier investigations on down-conversion emission of Tb³⁺ ion excited by deep ultraviolet light, in this work, the photoluminescence characteristics of Sr₂MgSi₂O₇ nanophosphors doped with different Tb³⁺ concentrations are analyzed under 374-nm excitations. The intense green emission at 545 nm is observed at an optimal doping concentration of 1.6 mol%. The main reason for the concentration quenching is due to the electric dipole-electric dipole interaction among Tb³⁺ ions.     

Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

Cryptographic algorithm is the most commonly used method of information security protection for many devices. The secret key of cryptographic algorithm is usually stored in these devices’ registers. In this paper, we propose an electromagnetic information leakage model to investigate the relationship between the electromagnetic leakage signal and the secret key. The registers are considered as electric dipole models to illustrate the source of the electromagnetic leakage. The equivalent circuit of the magnetic field probe is developed to bridge the output voltage and the electromagnetic leakage signal. Combining them, the electromagnetic information leakage model’s function relationship can be established. Besides, an electromagnetic leakage model based on multiple linear regression is proposed to recover the secret key and the model’s effectiveness is evaluated by guess entropy. Near field tests are conducted in an unshielded ordinary indoor environment to investigate the electromagnetic side-channel information leakage. The experiment result shows the correctness of the proposed electromagnetic leakage model and it can be used to recover the secret key of the cryptographic algorithm.