Effect of film thickness on the electro-reduction of molecular oxygen on electropolymerized cobalt tetra-aminophthalocyanine films

We studied the electrocatalytic activity of cobalt tetra-aminophthalocyanine (CoTAPc) for the reduction of molecular oxygen (O₂) on adsorbed monomeric and on electropolymerized films of different thicknesses on glassy carbon (GC) electrode. The polymeric films, denoted poly-CoTAPc, were first characterized by electrochemical impedance spectroscopy and it appears that the types of phenomena revealed to be occurring depend less on the film thickness in basic than in acid media. For O₂ reduction, the results showed that poly-CoTAPc is more active than the monomeric CoTAPc adsorbed on GC. Indeed, rotating ring-disk electrode data showed that polymeric CoTAPc promotes the four-electron reduction of O₂ to water in parallel to a two-electron reduction to give peroxide. On monomeric and thin films of poly-CoTAPc, a two-electron reduction mechanism predominates. In basic media the activity increases very slightly with thickness, whereas in acid media this increase is more pronounced. This parallels the observed behavior revealed by electrochemical impedance spectroscopy.     

Sorption of uranium by non-living water hyacinth roots

Summary Many studies have shown that water hyacinth (Eichhornia crassipes) roots can be used to accumulate high concentrations of organic as well as inorganic pollutants. They are currently used to remediate aquatic environments and aqueous solutions. In the present study, sorption of uranium from aqueous solutions by using dried roots of water hyacinth has been investigated. The sorption of uranium was examined as a function of initial concentration, pH, weight of roots and contact time. Five different concentrations 20, 40, 60, 80, and 100 μg ^. ml^-1 were used. Sorption proves to be very rapid and depend on pH, weight of roots and concentration of uranium. Maximum sorption capacity of water hyacinth roots was 64,000 U⁶⁺ μg/g. The sorption of uranium by water hyacinth roots follows a Langmuir isotherm.     

Stabilization of γ‘ phase in Bi<Subscript>4</Subscript>V<Subscript>2-x</Subscript>Fe<Subscript>x</Subscript><Superscript>II</Superscript>O<Subscript>11-1.5x</Subscript> series

Summary This work reports the room-temperature stabilization of the Bi₄V_2-xFe_x^IIO_11-1.5x γ ‘ phase, a promising ionic conductive material that finds application in solid oxide fuel cell and oxygen sensor devices. The Fe(II) cation proved to be a better stabilizer than Fe(III), which was previously used, since a lower substitution degree of V⁵⁺ is needed for the former. Powder X-ray diffraction, Fourier-transform infrared spectroscopy and differential scanning calorimetry were used in these experiments.     

Trennung,Identifizierung und Bestimmung von Bactericiden auf der Basis von halogenierten Aromaten mittels Gas-Chromatographie

The separation of a mixture of 22 bactericides has been achieved by gas chromatography on columns with silicone rubber W-982 as stationary phase with temperatures between 100° and 300°C. The unchanged compounds as well as their silylation products have been used. The latter are more conveniently used especially for the quantitative determination. To be able to calculate the retention indices after Kovats gas chromatography has been performed isothermally at 180°C for the more volatile compounds and at 250°C for all other bactericides.The retention indices obtained under these conditions are tabulated together with the limits of detection.     

2-Amino-4-bromobutanoic Acid

(2S)- and (2R)-2-Amino-4-bromobutanoic acid were prepared starting from N-Boc-glutamic acid α tert-butyl ester. The double tert-butyl protection was necessary to prevent a partial racemisation during Barton’s radical decarboxylation used to transform the γ-carboxylic group into a bromide. This bromide reacted with different nitrogen, oxygen and sulphur nucleophiles to give nonnatural amino acids characterised by basic or heterocyclic side chains. The title compound was also used to prepare a conformationally constrained peptidomimetic.     

一种利用窗口结构提取红外弱小目标的方法

在分析红外弱小目标检测的检测概率和虚警率的基础上,引入了一种基于窗口结构的红外弱小目标检测方法.该方法无需进行图像差分,利用局部小范围内目标相对背景的灰度变化检测目标,可以在较低信噪比的情况下获得较高的检测概率和较低的虚警率.实验表明了该方法的有效性.     

Enantioselective Hydrogenation of Endocyclic Enones:the Solution to a Historical Problem

The enantioselective hydrogenation of endocyclic enones has been a historical problem for homogeneous catalysis.We herein report an efficient method to reduce e...     

水中硝酸盐氮稳定同位素比值测定前处理方法的优化

水体中过量的硝酸盐导致会严重的水生生态恶化和环境污染问题。氮稳定同位素技术为水体污染来源的判断及水生系统氮素转化机理研究提供了强有力的工具。在前人基础上,通过开发Cu2+-Cd复合催化结合超声波辅助加速反应,优化硝酸盐氮同位素比值测定前处理方法。考察了Cu2+添加量,超声功率以及反应时间变化对NO3--N转化生成N2O气体及其氮同位素比值的影响,在单因素实验基础上采用正交实验优化得到了最佳反应条件,并采用不同15N同位素比值的KNO3标准溶液结合气体预浓缩装置与稳定同位素质谱仪联用系统对新方法进行了验证。新方法单次反应体系中氮最低量为1.0 μg,其中自然丰度和高丰度样品δ15N分析精度小于1‰,富集样品的15N分析精度可达0.1 atom%以内(CV<1%);且所有标准样品的15N测定值与参考值基本一致。将优化后的方法应用于不同来源水样中硝酸盐氮稳定同位素比值测定,均可获得较好的精度,较原方法提高了前处理效率,且精度更优。综上,建立的方法准确可靠,操作简单,耗时短,适用于水中硝酸盐氮稳定同位素比值测定的批量、快速前处理。     

Semi-Supervised Cross-Subject Emotion Recognition Based on Stacked Denoising Autoencoder Architecture Using a Fusion of Multi-Modal Physiological Signals

In recent decades, emotion recognition has received considerable attention. As more enthusiasm has shifted to the physiological pattern, a wide range of elaborate physiological emotion data features come up and are combined with various classifying models to detect one’s emotional states. To circumvent the labor of artificially designing features, we propose to acquire affective and robust representations automatically through the Stacked Denoising Autoencoder (SDA) architecture with unsupervised pre-training, followed by supervised fine-tuning. In this paper, we compare the performances of different features and models through three binary classification tasks based on the Valence-Arousal-Dominance (VAD) affection model. Decision fusion and feature fusion of electroencephalogram (EEG) and peripheral signals are performed on hand-engineered features; data-level fusion is performed on deep-learning methods. It turns out that the fusion data perform better than the two modalities. To take advantage of deep-learning algorithms, we augment the original data and feed it directly into our training model. We use two deep architectures and another generative stacked semi-supervised architecture as references for comparison to test the method’s practical effects. The results reveal that our scheme slightly outperforms the other three deep feature extractors and surpasses the state-of-the-art of hand-engineered features.     

A Comprehensive Review of Rosmarinic Acid: From Phytochemistry to Pharmacology and Its New Insight

Polyphenolic acids are the widely occurring natural products in almost each herbal plant, among which rosmarinic acid (RA, C₁₈H₁₆O₈) is well-known, and is present in over 160 species belonging to many families, especially the Lamiaceae. Aside from this herbal ingredient, dozens of its natural derivatives have also been isolated and characterized from many natural plants. In recent years, with the increasing focus on the natural products as alternative treatments, a large number of pharmacological studies have been carried out to demonstrate the various biological activities of RA such as anti-inflammation, anti-oxidation, anti-diabetes, anti-virus, anti-tumor, neuroprotection, hepatoprotection, etc. In addition, investigations concerning its biosynthesis, extraction, analysis, clinical applications, and pharmacokinetics have also been performed. Although many achievements have been made in various research aspects, there still exist some problems or issues to be answered, especially its toxicity and bioavailability. Thus, we hope that in the case of natural products, the present review can not only provide a comprehensive understanding on RA covering its miscellaneous research fields, but also highlight some of the present issues and future perspectives worth investigating later, in order to help us utilize this polyphenolic acid more efficiently, widely, and safely.