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While the wing kinematics of many flapping insects have been well characterized, understanding the underlying sensory, neural, and physiological mechanisms that determine these kinematics is still a challenge. Two main difficulties in understanding the physiological mechanisms arise from the complexity of the interaction between a flapping wing and its own unsteady flow, as well as the intricate mechanics of the insect wing hinge, which is among the most complicated joints in the animal kingdom. These difficulties call for the application of reduced-order approaches. Here this strategy is used to model the torques exerted by the wing hinge along the wing-pitch axis of maneuvering fruit flies as a damped torsional spring with elastic and damping coefficients as well as a rest angle. Furthermore, we model the air flows using simplified quasistatic aerodynamics. Our findings suggest that flies take advantage of the passive coupling between aerodynamics and the damped torsional spring to indirectly control their wing-pitch kinematics by modulating the spring parameters. The damped torsional-spring model explains the changes measured in wing-pitch kinematics during roll correction maneuvers through modulation of the spring damping and elastic coefficients. These results, in conjunction with the previous literature, indicate that flies can accurately control their wing-pitch kinematics on a sub-wing-beat time scale by modulating all three effective spring parameters on longer time scales.Gene expression is an inherently stochastic process that depends on the structure of the biochemical regulatory network in which the gene is embedded. Here we study the dynamical consequences of the interplay between stochastic gene switching and the widespread negative feedback regulatory loop in a simple model of a biochemical regulatory network. Using a simplified hybrid simulation approach, in which only the gene activation is modeled stochastically, we find that stochasticity in gene switching by itself can induce pulses in the system, providing also analytical insights into their origin. Furthermore, we find that this simple network is able to reproduce both exponential and peaked distributions of gene active and inactive times similar to those that have been observed experimentally. This simplified hybrid simulation approach also allows us to link these patterns to the dynamics of the system for each gene state.Transcriptional repression may cause transcriptional noise by a competition between repressor and RNA polymerase binding. Although promoter activity is often governed by a single limiting step, we argue here that the size of the noise strongly depends on whether this step is the initial equilibrium binding or one of the subsequent unidirectional steps. Overall, we show that nonequilibrium steps of transcription initiation systematically increase the cell-to-cell heterogeneity in bacterial populations. In particular, this allows also weak promoters to give substantial transcriptional noise.We propose a reaction-advection-diffusion model of epidermis consisting of two variables, the degree of differentiation and the calcium ion concentration, where calcium ions enhance differentiation. By analytically and numerically investigating this system, we show that a calcium localization layer formed beneath the stratum corneum helps reduce spatiotemporal fluctuations of the structure of the stratum corneum. In particular, spatially or temporally small-scale fluctuations in the lower structure are suppressed and do not affect the upper structure, due to acceleration of differentiation by calcium ions. Analytical expressions for the reduction rate of fluctuation amplitudes are shown.While several in vitro experiments on viral genome release have specifically studied the effects of external osmotic pressure and of the presence of polyvalent cations on the ejection of DNA from bacteriophages, few have systematically investigated how the extent of ejection is controlled by a combination of these effects. In this work we quantify the effect of osmotic pressure on the extent of DNA ejection from bacteriophage lambda as a function of polyvalent cation concentration (in particular, the tetravalent polyamine spermine). We find that the pressure required to completely inhibit ejection decreases from 38 to 17 atm as the spermine concentration is increased from 0 to 1.5 mM. Further, incubation of the phage particles in spermine concentrations as low as 0.15 mM--the threshold for DNA condensation in bulk solution-is sufficient to significantly limit the extent of ejection in the absence of osmolyte; for spermine concentrations below this threshold, the ejection is complete. In accord with recent investigations on the packaging of DNA in the presence of a condensing agent, we observe that the self-attraction induced by the polyvalent cation affects the ordering of the genome, causing it to get stuck in a broad range of nonequilibrated structures.Toroid formation is an important mechanism for DNA condensation in cells. The length change during DNA condensation was investigated in previous single-molecule experiments. However, DNA twist is key to understanding the topological kinetics of DNA condensation. In this study, DNA twist as well as DNA length was traced during the DNA condensation by the freely orbiting magnetic tweezers and the tilted magnetic tweezers combined with Brownian dynamics simulations. The experimental results disclose the complex relationship between DNA extension and backbone rotation. Brownian dynamics simulations show that the toroid formation follows a wiggling pathway which leads to the complex DNA backbone rotation as revealed in our experiments. These findings provide the complete description of multivalent cation-dependent DNA toroid formation under tension.In medical imaging and porous media research, NMR diffusion measurements are extensively used to investigate the structure of diffusion restrictions such as cell membranes. Recently, several methods have been proposed to unambiguously determine the shape of arbitrary closed pores or cells filled with an NMR-visible medium by diffusion experiments. The first approach uses a combination of a long and a short diffusion-weighting gradient pulse, while the other techniques employ short gradient pulses only. this website While the eventual aim of these methods is to determine pore-size and shape distributions, the focus has been so far on identical pores. Thus, the aim of this work is to investigate the ability of these different methods to resolve pore-size and orientation distributions. Simulations were performed comparing the various pore imaging techniques employing different distributions of pore size and orientation and varying timing parameters. The long-narrow gradient profile is most advantageous to investigate pore distributions, because average pore images can be directly obtained. The short-gradient methods suppress larger pores or induce a considerable blurring. Moreover, pore-shape-specific artifacts occur; for example, the central part of a distribution of cylinders may be largely underestimated. Depending on the actual pore distribution, short-gradient methods may nonetheless yield good approximations of the average pore shape. Furthermore, the application of short-gradient methods can be advantageous to differentiate whether pore-size distributions or intensity distributions, e.g., due to surface relaxation, are predominant.We study the influence of driver mutations on the spatial evolutionary dynamics of solid tumors. We start with a cancer clone that expands uniformly in three dimensions giving rise to a spherical shape. We assume that cell division occurs on the surface of the growing tumor. Each cell division has a chance to give rise to a mutation that activates an additional driver gene. The resulting clone has an enhanced growth rate, which generates a local ensemble of faster growing cells, thereby distorting the spherical shape of the tumor. We derive formulas for the abundance and diversity of additional driver mutations as function of time. Our model is semi-deterministic the spatial growth of cancer clones is deterministic, while mutants arise stochastically.Positioning of nucleosomes along a eukaryotic genome plays an important role in its organization and regulation. There are many different factors affecting the location of nucleosomes. Some can be viewed as preferential binding of a single nucleosome to different locations along the DNA and some as interactions between neighboring nucleosomes. In this study, we analyze positioning of nucleosomes and derive conditions for their good positioning. Using analytic and numerical approaches we find that, if the binding preferences are very weak, an interplay between the interactions and the binding preferences is essential for a good positioning of nucleosomes, especially on correlated energy landscapes. Analyzing the empirical energy landscape, we conclude that good positioning of nucleosomes in vivo is possible only if they strongly interact. In this case, our model, predicting long-length-scale fluctuations of nucleosomes' occupancy along the DNA, accounts well for the empirical observations.Free-living biofilms have been subject to considerable attention, and basic physical principles for them are generally accepted. Many host-biofilm systems, however, consist of heterogeneous mixtures of aggregates of microbes intermixed with host material and are much less studied. Here we analyze a key property, namely reactive depletion, in such systems and argue that two regimes are possible (1) a homogenizable mixture of biofilm and host that in important ways acts effectively like a homogeneous macrobiofilm and (2) a distribution of separated microbiofilms within the host with independent local microenvironments.The formation of dynamic patterns such as localized propagating waves is a fascinating self-organizing phenomenon that happens in a wide range of spatially extended systems including neural systems, in which they might play important functional roles. Here we derive a type of two-dimensional neural-field model with refractoriness to study the formation mechanism of localized waves. After comparing this model with existing neural-field models, we show that it is able to generate a variety of localized patterns, including stationary bumps, localized waves rotating along a circular path, and localized waves with longer-range propagation. We construct explicit bump solutions for the two-dimensional neural field and conduct a linear stability analysis on how a stationary bump transitions to a propagating wave under different spatial eigenmode perturbations. The neural-field model is then partially solved in a comoving frame to obtain localized wave solutions, whose spatial profiles are in good agreement with those obtained from simulations. We demonstrate that when there are multiple such propagating waves, they exhibit rich propagation dynamics, including propagation along periodically oscillating and irregular trajectories; these propagation dynamics are quantitatively characterized. In addition, we show that these waves can have repulsive or merging collisions, depending on their collision angles and the refractoriness parameter. Due to its analytical tractability, the two-dimensional neural-field model provides a modeling framework for studying localized propagating waves and their interactions.
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