Collective Excitations of Supersymmetric Plasma

Collective excitations of N = 1 supersymmetric electromagnetic plasma are studied. Since the Keldysh-Schwinger approach is used, not only equilibrium but also non-equilibrium plasma, which is assumed to be ultrarelativistic, is under consideration. The dispersion equations of photon, photino, electron and selectron modes are written down and the self-energies, which enter the equations, are computed in the Hard Loop Approximation. The self-energies are discussed in the context of effective action which is also given. The photon modes and electron ones appear to be the same as in the usual ultrarelativistic plasma of electrons, positrons and photons. The photino modes coincide with the electron ones and the selectron modes are as of free relativistic massive particle.Comment: 14 pages, typos corrected, Phys. Rev. D in prin

Experimental analysis of waste tyres as a sustainable source of energy

© The Authors, published by EDP Sciences, 2019. Nowadays, the stability of energy supply that additionally should be sustainable is one of the most important global issues. Thus, many new potential energy sources are being investigated. Since automobile industry is growing, a huge amount of waste tyres (WT) occur each year. Pyrolysis of scrap tyres can be considered as a sustainable way to recover significant amounts of energy as well as the valuable materials. Potential of waste tyres in the energy sector is studied in this work. Proximate, ultimate and thermogravimetric (TG) analysis of mechanically grounded WT sample was done. Waste tyres feature high heating value combined with carbon content as high as 87.90 % (on dry ash-free basis). Additionally, TG analysis allows to choose optimal operating temperature for pyrolysis process which is between 350 and 500°C. However, the sulphur content is also relatively high - around 2 wt.% - and it is the most important challenge for utilizing this waste in a thermochemical way.The paper was financial supported by Department of Air Conditioning, Heating, Gas Engineering and Air Protection; Wroclaw University of Science and Technology (No. 0401/0055/18)

Fluorapatite Enhances Mineralization of Mesenchymal/Endothelial Cocultures

In addition to the widely used mesenchymal stem cells (MSCs), endothelial cells appear to be a favorable cell source for hard tissue regeneration. Previously, fluorapatite was shown to stimulate and enhance mineralization of MSCs. This study aims to investigate the growth of endothelial cells on synthesized ordered fluorapatite surfaces and their effect on the mineralization of adipose-derived stem cells (ASCs) through coculture. Endothelial cells were grown on fluorapatite surfaces and characterized by cell counting, flow cytometry, scanning electron microscopy, and enzyme-linked immunosorbent assay (ELISA). Cells were then cocultured with ASCs and stained for alkaline phosphatase and mineral formation. Fibroblast growth factor (FGF) pathway perturbation and basic FGF (bFGF) treatment of the ASCs were also conducted to observe their effects on differentiation and mineralization of these cells. Fluorapatite surfaces showed good biocompatibility in supporting endothelial cells. Without a mineralization supplement, coculture with endothelial cells induced osteogenic differentiation of ASCs, which was further enhanced by the fluorapatite surfaces. This suggested a combined stimulating effect of endothelial cells and fluorapatite surfaces on the enhanced mineralization of ASCs. Greater amounts of bFGF release by endothelial cells alone or cocultures with ASCs stimulated by fluorapatite surfaces, together with FGF pathway perturbation and bFGF treatment results, suggested that the FGF signaling pathway may function in this process.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140224/1/ten.tea.2013.0113.pd

In Vitro Differentiation and Mineralization of Dental Pulp Stem Cells on Enamel-Like Fluorapatite Surfaces

Our previous studies have shown good biocompatibility of fluorapatite (FA) crystal surfaces in providing a favorable environment for functional cell?matrix interactions of human dental pulp stem cells (DPSCs) and also in supporting their long-term growth. The aim of the current study was to further investigate whether this enamel-like surface can support the differentiation and mineralization of DPSCs, and, therefore, act as a potential model for studying the enamel/dentin interface and, perhaps, dentine/pulp regeneration in tooth tissue engineering. The human pathway-focused osteogenesis polymerase chain reaction (PCR) array demonstrated that the expression of osteogenesis-related genes of human DPSCs was increased on FA surfaces compared with that on etched stainless steel (SSE). Consistent with the PCR array, FA promoted mineralization compared with the SSE surface with or without the addition of a mineralization promoting supplement (MS). This was confirmed by alkaline phosphatase (ALP) staining, Alizarin red staining, and tetracycline staining for mineral formation. In conclusion, FA crystal surfaces, especially ordered (OR) FA surfaces, which mimicked the physical architecture of enamel, provided a favorable extracellular matrix microenvironment for the cells. This resulted in the differentiation of human DPSCs and mineralized tissue formation, and, thus, demonstrated that it may be a promising biomimetic model for dentin-pulp tissue engineering.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98483/1/ten%2Etec%2E2011%2E0624.pd

BayFlux: A Bayesian Method to Quantify Metabolic Fluxes and their Uncertainty at the Genome Scale.

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13C Metabolic Flux Analysis (13C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P-13C MOMA and P-13C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty

A concerted systems biology analysis of phenol metabolism in Rhodococcus opacus PD630

Rhodococcus opacus PD630 metabolizes aromatic substrates and naturally produces branched-chain lipids, which are advantageous traits for lignin valorization. To provide insights into its lignocellulose hydrolysate utilization, we performed 13C-pathway tracing, 13C-pulse-tracing, transcriptional profiling, biomass composition analysis, and metabolite profiling in conjunction with 13C-metabolic flux analysis (13C-MFA) of phenol metabolism. We found that 1) phenol is metabolized mainly through the ortho–cleavage pathway; 2) phenol utilization requires a highly active TCA cycle; 3) NADPH is generated mainly via NADPH-dependent isocitrate dehydrogenase; 4) active cataplerotic fluxes increase plasticity in the TCA cycle; and 5) gluconeogenesis occurs partially through the reversed Entner–Doudoroff pathway (EDP). We also found that phenol-fed R. opacus PD630 generally has lower sugar phosphate concentrations (e.g., fructose 1,6-bisphosphatase) compared to metabolite pools in 13C-glucose-fed Escherichia coli (set as internal standards), while its TCA metabolites (e.g., malate, succinate, and α-ketoglutarate) accumulate intracellularly with measurable succinate secretion. In addition, we found that phenol utilization was inhibited by benzoate, while catabolite repressions by other tested carbon substrates (e.g., glucose and acetate) were absent in R. opacus PD630. Three adaptively-evolved strains display very different growth rates when fed with phenol as a sole carbon source, but they maintain a conserved flux network. These findings improve our understanding of R. opacus’ metabolism for future lignin valorization

Physicochemical and Antibacterial Characterisation of a Novel Fluorapatite Coating

Peri-implantitis remains the major impediment to the long-term use of dental implants. With increasing concern over growing antibiotic resistance there is considerable interest in the preparation of antimicrobial dental implant coatings that also induce osseointegration. One such potential coating material is fluorapatite (FA). The aim of this study was to relate the antibacterial effectiveness of FA coatings against pathogens implicated in peri-implantitis to the physicochemical properties of the coating. Ordered and disordered FA coatings were produced on the under and upper surface of stainless steel (SS) discs respectively, using a hydrothermal method. Surface charge, surface roughness, wettability and fluoride release were measured for each coating. Surface chemistry was assessed by X-ray photoelectron spectroscopy and FA crystallinity by X-ray diffraction. Antibacterial activity against periodontopathogens was assessed in vitro using viable counts, confocal and scanning electron (SEM) microscopies. SEM showed that the hydrothermal method produced FA coatings predominately aligned perpendicular to the SS substrate or disordered FA coatings consisting of randomly aligned rod-like crystals. Both FA coatings significantly reduced the growth of all the examined bacterial strains in comparison to the control. The FA coatings, and especially the disordered ones, presented significantly lower charge, higher roughness and area when compared to the control, enhancing bacteria–material interactions and therefore bacterial deactivation by fluoride ions. The ordered FA layer reduced not only bacterial viability but adhesion too. Ordered FA crystals produced as a potential novel implant coating showed significant antibacterial activity against bacteria implicated in peri-implantitis which could be explained by a detailed understanding of their physicochemical properties

Phase transitions in the spinless Falicov-Kimball model with correlated hopping

The canonical Monte-Carlo is used to study the phase transitions from the low-temperature ordered phase to the high-temperature disordered phase in the two-dimensional Falicov-Kimball model with correlated hopping. As the low-temperature ordered phase we consider the chessboard phase, the axial striped phase and the segregated phase. It is shown that all three phases persist also at finite temperatures (up to the critical temperature $\tau_c$) and that the phase transition at the critical point is of the first order for the chessboard and axial striped phase and of the second order for the segregated phase. In addition, it is found that the critical temperature is reduced with the increasing amplitude of correlated hopping $t'$ in the chessboard phase and it is strongly enhanced by $t'$ in the axial striped and segregated phase.Comment: 17 pages, 6 figure

Novel techniques for automorphism group computation

Graph automorphism (GA) is a classical problem, in which the objective is to compute the automorphism group of an input graph. In this work we propose four novel techniques to speed up algorithms that solve the GA problem by exploring a search tree. They increase the performance of the algorithm by allowing to reduce the depth of the search tree, and by effectively pruning it. We formally prove that a GA algorithm that uses these techniques correctly computes the automorphism group of the input graph. We also describe how the techniques have been incorporated into the GA algorithm conauto, as conauto-2.03, with at most an additive polynomial increase in its asymptotic time complexity. We have experimentally evaluated the impact of each of the above techniques with several graph families. We have observed that each of the techniques by itself significantly reduces the number of processed nodes of the search tree in some subset of graphs, which justifies the use of each of them. Then, when they are applied together, their effect is combined, leading to reductions in the number of processed nodes in most graphs. This is also reflected in a reduction of the running time, which is substantial in some graph families