Manganese ferrite-polyaniline hybrid materials: Electrical and magnetic properties

Magnetic MnFe₂O₄ nanopowders were synthesized by an original solvothermal method in the absence and in the presence of tetra-n-butylammonium bromide (TBAB) and Tween 80 (TW) as surfactants. Manganese ferrite/polyaniline (PANI) hybrid materials were synthesized by in situ polymerization of aniline on the surface of MnFe₂O₄ using ammonium persulfate as oxidant. The purpose of the study was to investigate the influence of the two surfactants on the properties of the MnFe₂O₄ powders and of their composites with PANI. The specific surface area, the cumulative surface area of pores and the cumulative volume of pores are influenced by the nature of surfactant in case of MnFe₂O₄ powders and are higher by comparison to those of the MnFe₂O₄/PANI hybrid materials. The values of saturation magnetization in case of MnFe₂O₄ powders are higher than those of the hybrid materials and are not influenced by the surfactant nature. These features revealed that MnFe₂O₄ powders can be efficiently used as adsorbents for the purification of wastewaters. The values of the electrical conductivity of the composites exhibit a significant increase in comparison to the MnFe₂O₄ powders and depend on the surfactant nature. The highest value of electrical conductivity was achieved by the composite obtained using Tween 80 as surfactant (σ_DC = 54.5·10^?5S?m^?1) which was close to that of PANI (σ_DC = 61.2·10^?5 S?m^?1). The fact that the magnetic and electric properties of the synthesized MnFe₂O₄/PANI composites can be changed by design, demonstrate the high potential of these materials to be used in magneto-electric applications.     

Assessing students' conceptual understanding using an online three‐tier diagnostic test

When solving a mathematical problem, students who do not have sufficient conceptual understanding may perform poorly and exhibit misconceptions. This study was aimed to examine students' conceptual understanding and significant misconceptions when solving number sense‐related problems. An online three‐tier diagnostic test was administered to 125 fifth‐grade students with varied socio‐economic backgrounds in Hong Kong. Only 14.40% of the students exhibited high performance with high confidence, indicating that these students had a profound conceptual understanding of number sense. In addition, the majority of the students (66.40%) did not demonstrate number sense; these students exhibited several significant misconceptions and could solve the questions only by using a rule‐based method or guessing. Accordingly, most students performed unsatisfactorily on number sense‐related problems. This study is imperative in identifying early predictors and provides information for further compatible interventions in the teaching and learning of number sense in Hong Kong in particular and worldwide in general.     

Preliminary Evidence on the Diagnostic and Molecular Role of Circulating Soluble EGFR in Non-Small Cell Lung Cancer

Assessment of biological diagnostic factors providing clinically-relevant information to guide physician decision-making are still needed for diseases with poor outcomes, such as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a promising molecule in the clinical management of NSCLC. While the EGFR transmembrane form has been extensively investigated in large clinical trials, the soluble, circulating EGFR isoform (sEGFR), which may have a potential clinical use, has rarely been considered. This study investigates the use of sEGFR as a potential diagnostic biomarker for NSCLC and also characterizes the biological function of sEGFR to clarify the molecular mechanisms involved in the course of action of this protein. Plasma sEGFR levels from a heterogeneous cohort of 37 non-advanced NSCLC patients and 54 healthy subjects were analyzed by using an enzyme-linked immunosorbent assay. The biological function of sEGFR was analyzed in vitro using NSCLC cell lines, investigating effects on cell proliferation and migration. We found that plasma sEGFR was significantly decreased in the NSCLC patient group as compared to the control group (median value: 48.6 vs. 55.6 ng/mL respectively; p = 0.0002). Moreover, we demonstrated that sEGFR inhibits growth and migration of NSCLC cells in vitro through molecular mechanisms that included perturbation of EGF/EGFR cell signaling and holoreceptor internalization. These data show that sEGFR is a potential circulating biomarker with a physiological protective role, providing a first approach to the functional role of the soluble isoform of EGFR. However, the impact of these data on daily clinical practice needs to be further investigated in larger prospective studies.     

Modelling of effects of ultrastructural morphology on the hygroelastic properties of wood fibres

Wood fibres constitute the structural framework of e.g. wood, paper, board and composites, where stiffness and dimensional stability are of importance. An analytical modelling approach has been used for prediction of hygroelastic response, and assessment of the stresses in thick-walled cylinder models of wood fibres. A wood fibre was idealised as a multilayered hollow cylinder made of orthotropic material with helical orientation. The hygroelastic response of the layered assembly due to axisymmetric loading and moisture content changes was obtained by solving the corresponding boundary value problem of elasticity. A simple solution scheme based on the state space approach and the transfer matrix method was employed. This was combined with an analytical ultrastructural homogenisation method, used to link hygroelastic properties of constituent wood polymers to properties of each layer. Predicted hygroelastic response captured experimentally measured behaviour. Fibres that were constrained not to twist showed a stiffer response than fibres allowed twisting under uniaxial loading. It was also shown that the ultrastructure, i.e. the microfibril angle, will control the hygroexpansion in the same way as it controls the compliance of the cell wall. Qualitative failure trends comparable with experimental observations could be established with stress analysis and a simple plane-stress failure criterion.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

Analytical model of displacement amplification and stiffness optimization for a class of flexure-based compliant mechanisms

The paper formulates an analytical method for displacement and stiffness calculations of planar compliant mechanisms with single-axis flexure hinges. The procedure is based on the strain energy and Castigliano’s displacement theorem and produces closed-form equations that incorporate the compliances characterizing any analytically-defined hinge, together with the other geometric and material properties of the compliant mechanism. Displacement amplification, input stiffness and output stiffness calculations can simply be performed for any serial compliant mechanism. The class of amplifying compliant mechanisms that contain symmetric corner-filleted or circular flexure hinges is specifically addressed here. A parametric study of the mechanism performance is performed, based on the mathematical model, and an optimization procedure is proposed, based on Lagrange’s multipliers and Kuhn-Tucker conditions, which identifies the design vector that maximizes the performance of these flexure-based compliant mechanisms. Independent finite element simulation confirms the analytical model predictions.     

Rapid analysis of polymer homologues and additives with SFE/SFC-MS coupling

A rapid and easy analysis method for polymers is presented. The method involves sample preparation by SFE, separation of the extracted compounds by SFC and simultaneous quantitative detection by FID, as well as identification of unknowns by MS. The applications illustrate how structural research work and routine polymer analysis can be done with this time saving method.