599 research outputs found
The Hosoya polynomial decomposition for catacondensed benzenoid graphs
AbstractFor a graph G with the vertex set V(G), we denote by d(u,v) the distance between vertices u and v in G, by d(u) the degree of vertex u. The Hosoya polynomial of G is H(G)=∑{u,v}⊆V(G)xd(u,v). The partial Hosoya polynomials of G are Hmn(G)=∑{u,v}⊆V(G)d(u)=m,d(v)=nxd(u,v) for positive integer numbers m and n. It is shown that H(G1)−H(G2)=x2(x+1)2(H33(G1)−H33(G2)),H22(G1)−H22(G2)=(x2+x−1)2(H33(G1)−H33(G2)) and H23(G1)−H23(G2)=2(x2+x−1)(H33(G1)−H33(G2)) for arbitrary catacondensed benzenoid graphs G1 and G2 with equal number of hexagons. As an application, we give an affine relationship between H(G) with two other distance-based polynomials constructed by Gutman [I. Gutman, Some relations between distance-based polynomials of trees, Bulletin de l’Académie Serbe des Sciences et des Arts (Cl. Math. Natur.) 131 (2005) 1–7]
On effects of regular S=1 dilution of S=1/2 antiferromagnetic Heisenberg chains by a quantum Monte Carlo simulation
The effects of regular S=1 dilution of S=1/2 isotropic antiferromagnetic
chain are investigated by the quantum Monte Carlo loop/cluster algorithm. Our
numerical results show that there are two kinds of ground-state phases which
alternate with the variation of concentration. When the effective spin
of a unit cell is half-integer, the ground state is ferrimagnetic with gapless
energy spectrum and the magnetism becomes weaker with decreasing of the
concentration . While it is integer, a non-magnetic ground state
with gaped spectrum emerges and the gap gradually becomes narrowed as fitted by
a relation of .Comment: 6 pages, 9 figure
Higher phagocytic activity of thioglycollate-elicited peritoneal macrophages is related to metabolic status of the cells
BACKGROUND: Peritoneal macrophages are widely used in immunological studies. The cells can be collected under non-elicited (resident) or elicited (e.g., with Brewer thioglycollate broth injection) conditions, and their phenotype and functions differ. Recent studies have shown that macrophage phenotype and function are related to their metabolic states, and metabolic reprogramming has been an emerging concept for controlling macrophage function. In this study, we examined the metabolic state of resident and elicited macrophages and investigated how their metabolic state may affect cell function, including phagocytosis. FINDINGS: Flow cytometry showed that elicited macrophages expressed higher levels of MHC-II, LFA-1 and CD64 but lower levels of F4/80 compared to naïve resident peritoneal macrophages, suggesting a more mature and active phenotype. Elicited macrophages had significantly higher levels of phagocytic activity compared to that of resident macrophages. Metabolic studies showed that the Extracellular Acidification Rates (ECAR) and Oxygen Consumption Rates (OCR) were both significantly higher in elicited macrophages than those in resident macrophages. The treatment of macrophages with 2-Deoxy-D-glucose suppressed glycolysis and reduced phagocytosis, whereas treatment with oligomycin enhanced glycolysis and increased phagocytosis in elicited macrophages. CONCLUSION: Naïve resident peritoneal macrophages are less metabolically active compared to elicited macrophages. Elicited macrophages had higher levels of glycolysis and oxidative phosphorylation, which may be related to their increased phagocytic capacity and higher levels of maturation and activation. Further understanding of the molecular links between metabolic pathways and cell function would be crucial to develop strategies to control macrophage function through metabolic reprogramming
A Research on Maximum Symbolic Entropy from Intrinsic Mode Function and Its Application in Fault Diagnosis
Empirical mode decomposition (EMD) is a self-adaptive analysis method for nonlinear and nonstationary signals. It has been widely applied to machinery fault diagnosis and structural damage detection. A novel feature, maximum symbolic entropy of intrinsic mode function based on EMD, is proposed to enhance the ability of recognition of EMD in this paper. First, a signal is decomposed into a collection of intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal, and then IMFs are transformed into a serious of symbolic sequence with different parameters. Second, it can be found that the entropies of symbolic IMFs are quite different. However, there is always a maximum value for a certain symbolic IMF. Third, take the maximum symbolic entropy as features to describe IMFs from a signal. Finally, the proposed features are applied to evaluate the effect of maximum symbolic entropy in fault diagnosis of rolling bearing, and then the maximum symbolic entropy is compared with other standard time analysis features in a contrast experiment. Although maximum symbolic entropy is only a time domain feature, it can reveal the signal characteristic information accurately. It can also be used in other fields related to EMD method
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