The Beta-Hyperbolic Secant (BHS) Distribution

The shape of a probability distribution is often summarized by the distribution's skewness and kurtosis. Starting from a symmetric parent density f on the real line, we can modify its shape (i.e. introduce skewness and in-/decrease kurtosis) if f is appropriately weighted. In particular, every density w on the interval (0; 1) is a specific weighting function. Within this work, we follow up a proposal of Jones (2004) and choose the Beta distribution as underlying weighting function w. Parent distributions like the Student-t, the logistic and the normal distribution have already been investigated in the literature. Based on the assumption that f is the density of a hyperbolic secant distribution, we introduce the Beta-hyperbolic secant (BHS) distribution. In contrast to the Beta-normal distribution and the to Beta-Student-t distribution, BHS densities are always unimodal and all moments exist. In contrast to the Beta-logistic distribution, the BHS distribution is more êexible regarding the range of skewness and leptokurtosis combinations. Moreover, we propose a generalization which nests both the Beta-logistic and the BHS distribution. Finally, the goodness-of-fit between all above-mentioned distributions is compared for glass fibre data and aluminium returns. --

Scanning Electron Microscopy of a Soil Fungus Gliocladium roseum

The paper describes the ultra-structural features of cryofixed and critical point-dried sporing cultures of a soil fungus Gliocladium roseum. Features described are Acrostalagmus-like conidiophores with spore masses in mucoid balls borne at the tips of branchlets and penicillate heads with conidia massed in rope-like formations. A particular feature of the aerial hyphae and conidiophores is the presence of blister-like swellings on their walls. These observations help to accurately characterize the organism in taxonomic studies

A modified Oster-Murray-Harris mechanical model of morphogenesis

There are two main modeling paradigms for biological pattern formation in developmental biology: chemical prepattern models and cell aggregation models. This paper focuses on an example of a cell aggregation model, the mechanical model developed by Oster, Murray, and Harris [Development, 78 (1983), pp. 83--125]. We revisit the Oster--Murray--Harris model and find that, due to the infinitesimal displacement assumption made in the original version of this model, there is a restriction on the types of boundary conditions that can be prescribed. We derive a modified form of the model which relaxes the infinitesimal displacement assumption. We analyze the dynamics of this model using linear and multiscale nonlinear analysis and show that it has the same linear behavior as the original Oster--Murray--Harris model. Nonlinear analysis, however, predicts that the modified model will allow for a wider range of parameters where the solution evolves to a bounded steady state. The results from both analyses are verified through numerical simulations of the full nonlinear model in one and two dimensions. The increased range of boundary conditions that are well-posed, as well as a wider range of parameters that yield bounded steady states, renders the modified model more applicable to, and more robust for, comparisons with experiments

Impacts from ice-nucleating bacteria on deep convection: implications for the biosphere-atmosphere interaction in climate change

International audienceA cloud modeling framework is described to simulate ice nucleation by biogenic aerosol particles, as represented by airborne ice-nucleation active (INA) bacteria. It includes the empirical parameterization of heterogeneous ice nucleation. The formation of cloud liquid by soluble material coated on such insoluble aerosols is represented and determines their partial removal from deep convective clouds by accretion onto precipitation. Preliminary simulations are performed for a case of deep convection over Oklahoma. If present at high enough concentrations, as might occur in proximity to land sources, INA bacteria are found to influence significantly: – (1) the average numbers and sizes of crystals in the clouds; (2) the horizontal cloud coverage in the free troposphere; and (3) precipitation and incident solar insolation at the surface, which influence rates of bacterial growth. At lower concentrations, the corresponding responses of cloud fields appear much lower or are ambiguous. In nature, the growth rates of INA bacteria on leaves prior to emission into the atmosphere are known to be highly dependent on temperature, precipitation and plant species. Consequently, the open question emerges of whether emissions of such ice-nucleating biogenic particles can then be modified by their own effects on clouds and atmospheric conditions, forming a weak feedback in climate or microclimate systems

Efficient Bayesian inference under the structured coalescent

Motivation: Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and subpopulation sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo (MCMC) sampling algorithms (samplers) capable of efficiently exploring the state space. Results: In this article, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylogenetic trees in which lineages are associated with the distinct subpopulation in which they lie. The sampler includes a set of MCMC proposal functions that offer significant mixing improvements over a previously published method. Furthermore, its implementation as a BEAST 2 package ensures maximum flexibility with respect to model and prior specification. We demonstrate the usefulness of this new sampler by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly available hemagglutinin (HA) gene sequences under the structured coalescent. Availability and implementation: The sampler has been implemented as a publicly available BEAST 2 package that is distributed under version 3 of the GNU General Public License at http://compevol.github.io/MultiTypeTree. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Accelerating Self-Assembly of Crisscross Slat Systems

We present an abstract model of self-assembly of systems composed of "crisscross slats", which have been experimentally implemented as a single-stranded piece of DNA [Minev et al., 2021] or as a complete DNA origami structure [Wintersinger et al., 2022]. We then introduce a more physically realistic "kinetic" model and show how important constants in the model were derived and tuned, and compare simulation-based results to experimental results [Minev et al., 2021; Wintersinger et al., 2022]. Using these models, we show how we can apply optimizations to designs of slat systems in order to lower the numbers of unique slat types required to build target structures. In general, we apply two types of techniques to achieve greatly reduced numbers of slat types. Similar to the experimental work implementing DNA origami-based slats, in our designs the slats oriented in horizontal and vertical directions are each restricted to their own plane and sets of them overlap each other in square regions which we refer to as macrotiles. Our first technique extends their previous work of reusing slat types within macrotiles and requires analyses of binding domain patterns to determine the potential for errors consisting of incorrect slat types attaching at undesired translations and reflections. The second technique leverages the power of algorithmic self-assembly to efficiently reuse entire macrotiles which self-assemble in patterns following designed algorithms that dictate the dimensions and patterns of growth. Using these designs, we demonstrate that in kinetic simulations the systems with reduced numbers of slat types self-assemble more quickly than those with greater numbers. This provides evidence that such optimizations will also result in greater assembly speeds in experimental systems. Furthermore, the reduced numbers of slat types required have the potential to vastly reduce the cost and number of lab steps for crisscross assembly experiments

Naringenin inhibits adipogenesis and reduces insulin sensitivity and adiponectin expression in adipocytes

Adipose tissue development and function are widely studied to examine the relationship between obesity and the metabolic syndrome. It is well documented that the inability of adipose tissue to properly increase its lipid storage capacity during the obese state can lead to metabolic dysfunction. In a blind screen of 425 botanicals, we identified naringenin as an inhibitor of adipocyte differentiation. Naringenin is one of the most abundant citrus flavonoids, and recent studies have demonstrated antihyperlipidemic capabilities. These studies have largely focused on the effects of naringenin on the liver. Our biochemical studies clearly demonstrate that naringenin inhibits adipogenesis and impairs mature fat cell function. Naringenin specifically inhibited adipogenesis in a dose-dependent fashion as judged by examining lipid accumulation and induction of adipocyte marker protein expression. In mature 3T3-L1 adipocytes, naringenin reduced the ability of insulin to induce IRS-1 tyrosine phosphorylation and substantially inhibited insulin-stimulated glucose uptake in a dose-dependent manner and over a time frame of 1.5 to 24 hours. Exposure to naringenin also inhibited adiponectin protein expression in mature murine and human adipocytes. Our studies have revealed that naringenin may have a negative impact on adipocyte-related diseases by limiting differentiation of preadipocytes, by significantly inducing insulin resistance, and by decreasing adiponectin expression in mature fat cells. © 2013 Allison J. Richard et al

Mineralogy of sulfides

Metal sulphides are the most important group of ore minerals. As shown in this brief introduction, much is known about their compositions, crystal structures, phase relations and paragenesis. Much less is known about their surface chemistry and, in particular, about their biogeochemistry, and about the formation and behaviour of ‘nanoparticle’ sulphides, whether formed abiotically or biogenically. These are large and complex topics which can only be touched upon in this article which also serves to direct readers to more comprehensive accounts