Fabrication and characterization of Grass pea (Lathyrus sativus) protein isolate-Alyssum homolocarpum seed gum complex coacervate

The present work was carried out to fabricate Grass pea (Lathyrus sativus) protein isolate (GPPI) and Alyssum homolocarpum seed gum (AHSG) complex coacervate and investigate its morphological and structural properties. Formation of complex coacervates were studied by zeta potentiometry and turbidimetric analysis as function of different pHs (7.0–2.0) and GPPI to AHSG ratios (3:1 to 1:3). The critical pH values associated with the formation of soluble (pH_c) and insoluble (pH_φ1) complexes, and complete dissociation (pH_φ2) at GPPI to AHSG ratio (1:1) were found to be 4.8, 4.0, and 2.5, respectively. Formation of insoluble complex coacervate was maximum at pH 3.2 and GPPI to AHSG ratio of 1:1, where the highest yield (69%) was observed. Scanning electron microscopic (SEM) demonstrated that GPPI-AHSG complex had a rough branched-like structure. Results also showed that the complexation between GPPI and AHSG were formed through the electrostatic interaction and hydrogen bonding. Circular dichroism spectroscopy (CD) indicated that the β-sheet and random coil content in GPPI increased when AHSG molecules were added to protein solution. The fading of pure peaks of GPPI and AHSG in X-Ray diffraction (XRD) patterns of GPPI-AHSG complexes confirmed the alterations in the physical state of mixture from crystalline to amorphous. GPPI-AHSG complex coacervates had lower weight loss compared to individual GPPI and AHSG.     

金属配合物和一氧化碳的反应

一氧化碳是发展可持续化学经济的重要原料。人们希望能够将一氧化碳催化转变成高附加值化学品,从而减少石油等化石资源对人类的束缚。研究均相金属配合物与一氧化碳的反应能够使人们了解一氧化碳转变及利用机理,并开发新催化剂高效地利用一氧化碳资源。本文从金属配合物与一氧化碳反应的活性点出发,分别讨论不同类型的金属配合物与一氧化碳的反应,以求让人们在分子水平上了解一氧化碳的基本反应原理;并总结了该领域存在的难点问题,展望了未来,希望更多的科研工作者投入其中,从而实现利用一氧化碳合成出各种各样的化学品和材料。     

Analysis of large experimental datasets in electrochemical impedance spectroscopy

An approach for the analysis of large experimental datasets in electrochemical impedance spectroscopy (EIS) has been developed. The approach uses the idea of successive Bayesian estimation and splits the multidimensional EIS datasets into parts with reduced dimensionality. Afterwards, estimation of the parameters of the EIS-models is performed successively, from one part to another, using complex nonlinear least squares (CNLS) method. The results obtained on the previous step are used as a priori values (in the Bayesian form) for the analysis of the next part. To provide high stability of the sequential CNLS minimisation procedure, a new hybrid algorithm has been developed. This algorithm fits the datasets of reduced dimensionality to the selected EIS models, provides high stability of the fitting and allows semi-automatic data analysis on a reasonable timescale. The hybrid algorithm consists of two stages in which different zero-order optimisation strategies are used, reducing both the computational time and the probability to overlook the global optimum. The performance of the developed approach has been evaluated using (i) simulated large EIS dataset which represents a possible output of a scanning electrochemical impedance microscopy experiments, and (ii) experimental dataset, where EIS spectra were acquired as a function of the electrode potential and time. The developed data analysis strategy showed promise and can be further extended to other electroanalytical EIS applications which require multidimensional data analysis.     

CM newforms with rational coefficients

We classify newforms with rational Fourier coefficients and complex multiplication for fixed weight up to twisting. Under the extended Riemann hypothesis for odd real Dirichlet characters, these newforms are finite in number. We produce tables for weights 3 and 4, where finiteness holds unconditionally. I am indepted to K. Hulek for his continuous interest and encouragement. Partial support by the DFG Schwerpunkt 1094 “Globale Methoden in der komplexen Geometrie” is gratefully acknowledged. My thanks go also to the referee for helpful comments. Part of the revising took place while I enjoyed the hospitality of the Dipartimento di Matematica “Frederico Enriques” of Milano University. Funding from the network Arithmetic Algebraic Geometry, a Marie Curie Research Training Network, is gratefully acknowledged. I particularly thank M. Bertolini and B. van Geemen. The final version was prepared while I was funded by DFG under grant Schu 2266/2-2.     

Induced polarization forward modelling using finite element method and the fractal model

The modeling of induced polarization data from 2D and 3D geological medium was developed. We applied the finite element method and the fractal model to complex resistivity of rocks as an intrinsic electrical property of geological medium. The LU factorization and pre-conditioned complex bi-conjugated gradient method were applied to solve the complex linear equation system. The modeling implemented in this work was efficient and prompt. In addition, the induced polarization survey using the fractal model as intrinsic property of the medium is a promising method for environmental investigation.     

Inhomogeneity in structure of MgPb liquid alloy

The concentration dependent asymmetry in mixing properties of MgPb liquid alloys at 973 K has been investigated on the basis of regular associated solution model. The analysis suggests that heterocoordination leading to the formation of chemical complex Mg₂Pb is likely to exist in the melt.     

Analyzing complex networks evolution through Information Theory quantifiers

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.     

Attack structural vulnerability of power grids: A hybrid approach based on complex networks

Power grids have been studied as a typical example of real-world complex networks. Different from previous methods, this paper proposes a hybrid approach for structural vulnerability analysis of power transmission networks, in which a DC power flow model with hidden failures is embedded into the traditional error and attack tolerance methodology to form a new scheme for power grids vulnerability assessment and modeling. The new approach embodies some important characteristics of power transmission networks. Furthermore, the simulation on the standard IEEE 118 bus system demonstrates that a critical region might exist and when the power grid operates in the region, it is vulnerable to both random and intentional attacks. Finally, a brief theoretical analysis is presented to explain the new phenomena.