763 research outputs found

    Note on group distance magic graphs G[C4]G[C_4]

    Get PDF
    A \emph{group distance magic labeling} or a \gr-distance magic labeling of a graph G(V,E)G(V,E) with ∣V∣=n|V | = n is an injection ff from VV to an Abelian group \gr of order nn such that the weight w(x)=∑y∈NG(x)f(y)w(x)=\sum_{y\in N_G(x)}f(y) of every vertex x∈Vx \in V is equal to the same element \mu \in \gr, called the magic constant. In this paper we will show that if GG is a graph of order n=2p(2k+1)n=2^{p}(2k+1) for some natural numbers pp, kk such that \deg(v)\equiv c \imod {2^{p+1}} for some constant cc for any v∈V(G)v\in V(G), then there exists an \gr-distance magic labeling for any Abelian group \gr for the graph G[C4]G[C_4]. Moreover we prove that if \gr is an arbitrary Abelian group of order 4n4n such that \gr \cong \zet_2 \times\zet_2 \times \gA for some Abelian group \gA of order nn, then exists a \gr-distance magic labeling for any graph G[C4]G[C_4]

    Bax/Bak promote sumoylation of DRP1 and its stable association with mitochondria during apoptotic cell death

    Get PDF
    Dynamin-related protein 1 (DRP1) plays an important role in mitochondrial fission at steady state and during apoptosis. Using fluorescence recovery after photobleaching, we demonstrate that in healthy cells, yellow fluorescent protein (YFP)–DRP1 recycles between the cytoplasm and mitochondria with a half-time of 50 s. Strikingly, during apoptotic cell death, YFP-DRP1 undergoes a transition from rapid recycling to stable membrane association. The rapid cycling phase that characterizes the early stages of apoptosis is independent of Bax/Bak. However, after Bax recruitment to the mitochondrial membranes but before the loss of mitochondrial membrane potential, YFP-DRP1 becomes locked on the membrane, resulting in undetectable fluorescence recovery. This second phase in DRP1 cycling is dependent on the presence of Bax/Bak but independent of hFis1 and mitochondrial fragmentation. Coincident with Bax activation, we detect a Bax/Bak-dependent stimulation of small ubiquitin-like modifier-1 conjugation to DRP1, a modification that correlates with the stable association of DRP1 with mitochondrial membranes. Altogether, these data demonstrate that the apoptotic machinery regulates the biochemical properties of DRP1 during cell death

    Spectroscopic properties of halite from KÅ‚odawa salt mine, central Poland

    Get PDF
    The dynamics of colour centre transformation was investigated in blue halite single crystals from KÅ‚odawa Salt Mine, Central Poland, using UV-vis spectroscopy. The following colour centres were considered: F, R_{1}, R_{2}, as well as plasmons and M centres. The R_{2} centres predominated in navy blue (A) and pale blue (B) halites. Other relatively large populations were plasmons found in all examined samples. In purple (C) halite samples the plasmon population is the highest one among others and R_{1} centres appeared to be equally significant, whereas M centres were almost absent. For A and C samples unidentified bands were observed at 26,500 to 26,200 cm^{-1}, respectively. The bleaching process of the blue halites was investigated using temperature dependent UV-vis and micro-Raman spectroscopies. In micro-Raman 300-100 cm^{-1} region three very intense sharp bands were attributed to the colour centres and colloidal Na precipitation in A and B halites. The one broad band in the range 3,500 to 500 cm^{-1}, which was characteristic even for the colourless sample D but absent in the spectra of colourless NaCl obtained after recrystallization of sample A, requires further study

    Towards retrieving dispersion profiles using quantum-mimic Optical Coherence Tomography and Machine Learnin

    Full text link
    Artefacts in quantum-mimic Optical Coherence Tomography are considered detrimental because they scramble the images even for the simplest objects. They are a side effect of autocorrelation which is used in the quantum entanglement mimicking algorithm behind this method. Interestingly, the autocorrelation imprints certain characteristics onto an artefact - it makes its shape and characteristics depend on the amount of dispersion exhibited by the layer that artefact corresponds to. This unique relationship between the artefact and the layer's dispersion can be used to determine Group Velocity Dispersion (GVD) values of object layers and, based on them, build a dispersion-contrasted depth profile. The retrieval of GVD profiles is achieved via Machine Learning. During training, a neural network learns the relationship between GVD and the artefacts' shape and characteristics, and consequently, it is able to provide a good qualitative representation of object's dispersion profile for never-seen-before data: computer-generated single dispersive layers and experimental pieces of glass.Comment: 11 pages, 5 figure
    • …
    corecore