ALBERT

Description: Previous work on the structural and thermal properties of various types of kaolinite have led to different conclusions, rendering comparison of analytical results difficult. The objectives of the present study were to investigate the thermal behaviour of kaolinite and to carry out a kinetic analysis of the decomposition of kaolinite at high temperatures. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetry-differential scanning calorimetry (TG-DSC) were used to study the mechanism of the thermal decomposition. The modified Coats–Redfern, Friedman, Flynn–Wall–Ozawa and Kissinger decomposition models were used to determine the decomposition mechanism of the kaolinite sample. The dehydroxylation of kaolinite occurred at ~600°C with the formation of metakaolin, which then transformed into either -alumina or aluminium-silicon spinel together with amorphous silica. The results of the XRD and FTIR analyses indicated that the -alumina, or aluminium-silicon spinel and amorphous silica phases, transformed into mullite and α-cristobalite, respectively, after decomposition at 900°C. Good linearity was observed with the modified Coats–Redfern, Flynn–Wall–Ozawa and Kissinger models from room temperature to 1400°C and the range of the activation energy determined was 120–180 kJ/mol.

Description: By using atomistic simulation and configurational statistics techniques, the thermodynamics of mixing for calcite-smithsonite solid solutions have been investigated. By employing a 2 x 2 x 1 supercell, the configuration with the lowest energy for the solid solution with a certain composition was determined. The incorporated Zn 2+ tends to occur at the sites neighboring to another substituted Zn 2+ within the (0001) layer, but the substituted layers are preferentially segregated by calcite layers, and vice versa. The supercells with compositions around the two end-members stand positive enthalpies at any temperatures, whereas those supercells with composition of about Ca 0.5 Zn 0.5 CO 3 prominently exhibit negative values in various temperatures of reality (e.g., 〈1000 K). The free energies are prominently negative at high temperatures (〉1500 K) for the whole range of compositions, only those around both end-members have positive values at some low temperatures (〈1200 K). In the derived phase relations of this solid solution system, the potential incorporation content of ZnCO 3 into calcite is only 0–2.5% mole fraction (i.e., Zn content of 0–1.6 wt%) in most geochemistry equilibrium processes, and vice versa.

Description: Different changes in the structural and thermal properties of various types of talc have been reported in the literature which have made comparison of analytical results difficult. The objective of the present study was to obtain some fundamental insights into the effects of the thermal behavior of talc and to carry out kinetic analyses of the decomposition of talc under high temperature. X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetry-differential scanning calorimetry (TG-DSC) were used to study the thermal decomposition mechanism. The Coats-Redfern decomposition model was used to determine the decomposition mechanism of talc samples. The results showed that the decomposition of talc commenced at ~800°C, peaking at ~895°C, with the formation of enstatite and amorphous silica. An isothermal treatment at 1000°C caused the complete dehydroxylation of talc. The XRD and FTIR results indicated that the enstatite and amorphous silica phases were transformed into clinoenstatite and paracrystalline opal phases, respectively, after the decomposition stage at 1200°C. Good linearity in the Coats-Redfern model was observed from room temperature to 1300°C and the activation energy was calculated to be 69 kcal/mol.

Description: We present deep spectroscopy of three Galactic planetary nebulae (PNe) with large abundance discrepancy factors: NGC 6153, M 1-42 and Hf 2-2. The spectra were obtained with Very Large Telescope/Ultraviolet and Visual Echelle Spectrograph and cover the whole optical range (3040–11 000 Å) with a spectral resolution of ~20 000. For all three PNe, several hundred emission lines were detected and identified, with more than 70 per cent of them as permitted lines. Most of these permitted lines are excited by recombination. Numerous weak optical recombination lines (ORLs) of O ii , C ii , N ii and Ne ii were detected in the spectra and accurate fluxes measured. Line flux tables were compiled and ready for use by the community of nebular astrophysics. These ORLs were critically analysed using the effective recombination coefficients recently calculated for the optical recombination spectrum of N ii and O ii under the physical conditions of photoionized gaseous nebulae. Plasma diagnostics based on the heavy element ORLs were carried out using the new atomic data. Elemental abundances derived from the ORLs were systematically higher than those derived from the collisionally excited lines (CELs) by a factor of ~11, 22 and 80 for NGC 6153, M 1-42 and Hf 2-2, respectively. The electron temperatures derived from the heavy element ORLs are systematically lower than those derived from the CELs. These ORL versus CEL abundance and temperature discrepancies, previously observed in the three PNe through deep spectroscopy with medium to low spectral resolution, are thus confirmed by our analysis of the deep echelle spectra using the new atomic data.

Description: Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically ‘small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as ‘large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency.

Description: The temporal and spatial evolution of a plasma jet generated by a spark discharge was observed. The electron temperature and density were obtained under different time and gas pressures by optical emission spectroscopy. Moreover, the discharge process of the plasma-jet triggered gas switch was recorded and analyzed at the lowest working coefficient. The results showed that the plasma jet moved forward in a bullet mode, and the advancing velocity increased with the decrease of pressure, and decreased with time growing. At initial time, the maximum velocity of a plasma jet could reach 3.68 × 10 6  cm/s. The electron temperature decreased from 2.0 eV to 1.3 eV, and the electron density increased from 3.1 × 10 15 /cm 3 to 6.3 × 10 15 /cm 3 at the initial moment as the gas pressure increases from 0.1 MPa to 0.32 MPa. For a two-gap gas switch, the discharge performances were more depended on the second discharge spark gap (gap 2). Because plasma jet promoted the discharge in Gap 2, the gas switch operating in mode II had better triggered discharge characteristics. In the discharge process, the plasma-jet triggering had the effect of non-penetrating inducing, which not only provided initial electrons for reducing statistical lag but also enhanced the local electric field. The discharge was initiated and accelerated from electron avalanche to streamer. Therefore, a fast discharge was occurred in the gas switch.

Description: We have reported a method to enhance the performance of graphene-Si (Gr/Si) Schottky junction solar cells by introducing Au nanoparticles (NPs) onto the monolayer graphene and few-layer graphene. The electron transfer between Au NPs and graphene leads to the increased work function and enhanced electrical conductivity of graphene, resulting in a remarkable improvement of device efficiency. By optimizing the initial thickness of Au layers, the power conversion efficiency of Gr/Si solar cells can be increased by more than three times, with a maximum value of 7.34%. These results show a route for fabricating efficient and stable Gr/Si solar cells.

Description: Regulation of magnetism and half-metallicity has attracted much attention because of its potential in spintronics. The magnetic properties and electronic structure of graphitic carbon nitride ( g -C 4 N 3 ) with external strain are determined theoretically based on the density function theory and many-body perturbation theory (G 0 W 0 ). Asymmetric deformation induced by uniaxial strain not only regulates the magnetic characteristics but also leads to a transformation from half-metallicity to metallicity. However, this transition cannot occur in the structure with symmetric deformation induced by biaxial strain. Our results suggest the use of strain engineering in metal-free spintronics applications.

Description: The Yuan-Agrawal (YA) memory-free approach is employed to study fractional dynamical systems with freeplay nonlinearities subjected to a harmonic excitation, by combining it with the precise integration method (PIM). By the YA method, the original equations are transformed into a set of first-order piecewise-linear ordinary differential equations (ODEs). These ODEs are further separated as three linear inhomogeneous subsystems, which are solved by PIM together with a predictor-corrector process. Numerical examples show that the results by the presented method agree well with the solutions obtained by the Runge-Kutta method and a modified fractional predictor-corrector algorithm. More importantly, the presented method has higher computational efficiency.

Description: Caspase-3 feedback loop enhances Bid-induced AIF/endoG and Bak activation in Bax and p53-independent manner Cell Death and Disease 6, e1919 (October 2015). doi:10.1038/cddis.2015.276 Authors: W Guo, Y Zhang, Z Ling, X Liu, X Zhao, Z Yuan, C Nie & Y Wei