Steganography and authentication in image sharing without parity bits

Recently, a polynomial-based (k, n) steganography and authenticated image sharing (SAIS) scheme was proposed to share a secret image into n stego-images. At the same time, one can reconstruct a secret image with any k or more than k stego-images, but one cannot obtain any information about the secret from fewer than k stego-images. The beauty of a (k, n)-SAIS scheme is that it provides the threshold property (i.e., k is the threshold value), the steganography (i.e., stego-images look like cover images), and authentication (i.e., detection of manipulated stego-images). All existing SAIS schemes require parity bits for authentication. In this paper, we present a novel approach without needing parity bits. In addition, our (k, n)-SAIS scheme provides better visual quality and has higher detection ratio with respect to all previous (k, n)-SAIS schemes.     

Analysis of Biological Samples Using Paper Spray Mass Spectrometry: An Investigation of Impacts by the Substrates, Solvents and Elution Methods

Paper spray has been developed as a fast sampling ionization method for direct analysis of raw biological and chemical samples using mass spectrometry (MS). Quantitation of therapeutic drugs in blood samples at high accuracy has also been achieved using paper spray MS without traditional sample preparation or chromatographic separation. The paper spray ionization is a process integrated with a fast extraction of the analyte from the raw sample by a solvent, the transport of the extracted analytes on the paper, and a spray ionization at the tip of the paper substrate with a high voltage applied. In this study, the influence on the analytical performance by the solvent–substrate systems and the selection of the elution methods was investigated. The protein hemoglobin could be observed from fresh blood samples on silanized paper or from dried blood spots on silica-coated paper. The on-paper separation of the chemicals during the paper spray was characterized through the analysis of a mixture of the methyl violet 2B and methylene blue. The mode of applying the spray solvent was found to have a significant impact on the separation. The results in this study led to a better understanding of the analyte elution, on-paper separation, as well as the ionization processes of the paper spray. This study also helps in establishing a guideline for optimizing the analytical performance of paper spray for direct analysis of target analytes using mass spectrometry.     

多晶薄膜X-射线衍射

作者在普通X-射线衍射仪上实施了样品倾斜X-射线衍射(STD)技术,不需要专用薄膜附件(TFA)也能很好地进行薄膜结构的测定,并且给出其衍射能量方程和方位角方程,从而使理论、实验和结构解析结合为一体。目前,应用该技术已经成功地解决了一些其它简便方法所无法解决的诸如物相纵向分布变化测量等问题。本文还通过几种摩擦学用膜的测定结果阐明了该技术的应用及功能。     

悬链曲面上的点粒子动力学及扩展空间约束系统量子化

扩张型正则量子化方案的核心内容是位置、动量以及哈密顿量同时量子化. 通过分析悬链面上粒子的扩张型正则量子化方案, 并且与薛定谔理论进行比较, 发现内禀几何中二维悬链面给不出与薛定谔理论相一致的结果, 而考虑将二维悬链面嵌入在三维欧氏空间之后, 还需要将正则量子化方案进行扩张, 可以得到体系的几何势能和几何动量, 并与薛定谔理论相一致.     

Behaviour of silicon ointment for power-cable insulation under external heating

Journal of Thermal Analysis and Calorimetry - The burning process and typical fire parameters of power-cable silicon ointment were explored experimentally using a cone calorimeter, and the effects...     

Unpaired 3d Electrons on Atomically Dispersed Cobalt Centres in Coordination Polymers Regulate both Oxygen Reduction Reaction (ORR) Activity and Selectivity for Use in Zinc–Air Batteries

Reversible oxygen conversion is important for various green energy technologies. Herein we synthesize a series of bimetallic coordination polymers by varying the Ni/Co ratio and using HITP (HITP=2,3,6,7,10,11‐hexaiminotriphenylene) as the ligand, to interrogate the role of metal centres in modulating the activity of the oxygen reduction reaction (ORR). Co₃HITP₂ and Ni₃HITP₂ are compared. Unpaired 3d electrons in Co₃HITP₂ result in less coplanarity but more radical character. Thus, despite of a reduced crystallinity and conductivity, the best ORR activity, comparable to 20 % Pt/C, is obtained for Co₃HITP₂, showing the 3d orbital configuration of the metal centre promotes ORR. Experimental and DFT studies show a transition of ORR pathway from four‐electron for Co₃HITP₂ to two‐electron for Ni₃HITP₂. Rechargeable zinc–air batteries using Co₃HITP₂ as the air cathode catalyst demonstrate excellent energy efficiency and stability.     

Comparison of the active components of Aster tataricus from different regions and related processed products by ultra‐high performance liquid chromatography with tandem mass spectrometry

We investigated crude Aster tataricus, vinegar‐processed Aster tataricus, honey‐processed Aster tataricus, and steamed Aster tataricus as a case study and developed a comprehensive strategy integrating quantitative analysis and chemical pattern recognition methods for the evaluation and differentiation of Aster tataricus from different regions, as well as related processed products. In the study, 15 batches of raw Aster tataricus collected from seven provinces were analyzed. A sensitive and rapid ultra‐high performance liquid chromatography with tandem mass spectrometry method for simultaneous determination of 15 compounds was established to evaluate the quality of raw and processed Aster tataricus. Furthermore, multivariate statistical techniques were applied to compare the differences among Aster tataricus samples. As a result, the herbs collected from seven provinces were divided into two categories, and chlorogenic acid was the most important component distinguishing between the regions. Moreover, all of the raw and processed samples were classified by partial least squares discriminant analysis based on the 15 analyzed compounds. Results showed that raw Aster tataricus, vinegar‐processed Aster tataricus, honey‐processed Aster tataricus, and steamed Aster tataricus were clustered in four different areas. Shionone, chlorogenic acid and kaempferol were the significant constituents differentiating the raw and differently processed Aster tataricus samples.     

Machine-Learning Adsorption on Binary Alloy Surfaces for Catalyst Screening

Over the last few years, machine learning is gradually becoming an essential approach for the investigation of heterogeneous catalysis. As one of the important catalysts, binary alloys have attracted extensive attention for the screening of bifunctional catalysts. Here we present a holistic framework for machine learning approach to rapidly predict adsorption energies on the surfaces of metals and binary alloys. We evaluate different machine-learning methods to understand their applicability to the problem and combine a tree-ensemble method with a compressed-sensing method to construct decision trees for about 60000 adsorption data. Compared to linear scaling relations, our approach enables to make more accurate predictions lowering predictive root-mean-square error by a factor of two and more general to predict adsorption energies of various adsorbates on thousands of binary alloys surfaces, thus paving the way for the discovery of novel bimetallic catalysts.