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99mTc-Labeled Straightener Oxide Nanoparticles for Dual-Contrast (T1/T2) Magnetic Resonance as well as Dual-Modality Image resolution associated with Tumour Angiogenesis.
We show how the competition between sensing and adaptation can result in a performance peak in Escherichia coli chemotaxis using extensive numerical simulations in a detailed theoretical model. Receptor clustering amplifies the input signal coming from ligand binding which enhances chemotactic efficiency. But large clusters also induce large fluctuations in total activity since the number of clusters goes down. The activity and hence the run-tumble motility now gets controlled by methylation levels which are part of adaptation module rather than ligand binding. This reduces chemotactic efficiency.We address the role of geometrical asymmetry in the occurrence of spin rectification in two-dimensional quantum spin chains subject to two reservoirs at the boundaries, modeled by quantum master equations. We discuss the differences in the rectification for some one-dimensional cases, and present numerical results of the rectification coefficient R for different values of the anisotropy parameter of the XXZ model, and different configurations of boundary drives, including both local and nonlocal dissipators. Our results also show that geometrical asymmetry, along with inhomogeneous magnetic fields, can induce spin current rectification even in the XX model, indicating that the phenomenon of rectification due to geometry may be of general occurrence in quantum spin systems.Neural systems process information in a dynamical regime between silence and chaotic dynamics. This has lead to the criticality hypothesis, which suggests that neural systems reach such a state by self-organizing toward the critical point of a dynamical phase transition. Here, we study a minimal neural network model that exhibits self-organized criticality in the presence of stochastic noise using a rewiring rule which only utilizes local information. For network evolution, incoming links are added to a node or deleted, depending on the node's average activity. Based on this rewiring-rule only, the network evolves toward a critical state, showing typical power-law-distributed avalanche statistics. The observed exponents are in accord with criticality as predicted by dynamical scaling theory, as well as with the observed exponents of neural avalanches. The critical state of the model is reached autonomously without the need for parameter tuning, is independent of initial conditions, is robust under stochastic noise, and independent of details of the implementation as different variants of the model indicate. We argue that this supports the hypothesis that real neural systems may utilize such a mechanism to self-organize toward criticality, especially during early developmental stages.This work extends the domain of vibrational mechanics to higher dimensions, with fast vibrations applied to different directions. selleck kinase inhibitor In particular, the presented analysis considers the case of a split biharmonic drive, where harmonics of frequency ω and 2ω are applied to orthogonal directions in a two-dimensional setting. It is shown, both numerically and with analytic calculations, that this determines a highly tunable effective potential with the same symmetry as the original one. The driving allows one not only to tune the amplitude of the potential, but also to introduce an arbitrary spatial translation in the direction corresponding to the 2ω driving. The setup allows for generalization to implement translations in an arbitrary direction within the two-dimensional landscapes. The same principles also apply to three-dimensional periodic potentials.We present a free-energy density functional theory (DFT)-based methodology for optical property calculations of warm dense matter to cover a wide range of thermodynamic conditions and photon energies including the entire x-ray range. It uses Mermin-Kohn-Sham density functional theory with exchange-correlation (XC) thermal effects taken into account via a fully temperature dependent generalized gradient approximation XC functional. The methodology incorporates a combination of the ab initio molecular dynamics (AIMD) snapshotted Kubo-Greenwood optic data with a single atom in simulation cell calculations to close the photon energy gap between the L and K edges and extend the K-edge tail toward many-keV photon energies. This gap arises in the standard scheme due to a prohibitively large number of bands required for the Kubo-Greenwood calculations with AIMD snapshots. Kubo-Greenwood data on snapshots provide an accurate description of optic properties at low photon frequencies slightly beyond the L edge and x-ray-principles opacity table (FPOT) for silicon in a wide range of material densities and temperatures.The Maier-Saupe-Zwanzig model for the nematic phase transitions in liquid crystals is investigated in a diamond hierarchical lattice. The model takes into account a parameter to describe the biaxiality of the microscopic units. Also, a suitably chosen external field is added to the Hamiltonian to allow the determination of critical parameters associated with the nematic phase transitions. Using the transfer-matrix technique, the free energy and its derivatives are obtained in terms of recursion relations between successive generations of the hierarchical lattice. In addition, a real-space renormalization-group approach is developed to obtain the critical parameters of the same model system. Results of both methods are in excellent agreement. There are indications of two continuous phase transitions. One of them corresponds to a uniaxial-isotropic transition, in the class of universality of the three-state Potts model on the diamond hierarchical lattice. The transition between the biaxial and the uniaxial phases is in the universality class of the Ising model on the same lattice.We consider the mutator model with unidirected transitions from the wild type to the mutator type, with different fitness functions for the wild types and mutator types. We calculate both the fraction of mutator types in the population and the surpluses, i.e., the mean number of mutations in the regular part of genomes for the wild type and mutator type, which have never been derived exactly. We identify the phase structure. Beside the mixed (ordinary evolution phase with finite fraction of wild types at large genome length) and the mutator phase (the absolute majority is mutators), we find another new phase as well-it has the mean fitness of the mixed phase but an exponentially small (in genome length) fraction of wild types. We identify the phase transition point and discuss its implications.
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