Crystal structure of (2,3-bis((2R,5R)-2,5-dimethylphosphonalyl)maleic anhydride)-(η4-norbornadiene)-rhodium(I) tetrafluoroborate, [Rh(C7H8)(C16H24O3P 2)] [BF4]

C23H32BF4O3P2Rh, orthorhombic, P212121 (no. 19), a = 10.147(2) Å, b = 13.246(3) Å, c = 18.827(4) Å, V = 2530.5 Å3, Z = 4, Rgt(F) = 0.025, wRref(F 2) = 0.067, T = 200 K. © by Oldenbourg Wissenschaftsverlag,

On the Connection between Temperature and Volatility in Ideal Agent Systems

Models for spin systems known from statistical physics are applied by analogy in econometrics in the form of agent-based models. Researchers suggest that the state variable temperature $T$ corresponds to volatility $\sigma$ in capital market theory problems. To the best of our knowledge, this has not yet been theoretically derived, for example, for an ideal agent system. In the present paper, we derive the exact algebraic relation between $T$ and $\sigma$ for an ideal agent system and discuss implications and limitations.Comment: Theoretical Contributio

A closer look at the chemical potential of an ideal agent system

Models for spin systems known from statistical physics are used in econometrics in the form of agent-based models. Econophysics research in econometrics is increasingly developing general market models that describe exchange phenomena and use the chemical potential $\mu$ known from physics in the context of particle number changes. In statistical physics, equations of state are known for the chemical potential, which take into account the respective model framework and the corresponding state variables. A simple transfer of these equations of state to problems in econophysics appears difficult. To the best of our knowledge, the equation of state for the chemical potential is currently missing even for the simplest conceivable model of an ideal agent system. In this paper, this research gap is closed and the equation of state for the chemical potential is derived from the econophysical model assumptions of the ideal agent system. An interpretation of the equation of state leads to fundamental relationships that could also have been guessed, but are shown here by the theory.Comment: 11 Pages, 0 Figures, Working Paper, Theoretical Contributio

Genome-based selection and application of food-grade microbes for chickpea milk fermentation towards increased L-lysine content, elimination of indigestible sugars, and improved flavour

Background Plant-based milk alternatives are more popular than ever, and chickpea-based milks are among the most commercially relevant products. Unfortunately, limited nutritional value because of low levels of the essential amino acid L-lysine, low digestibility and unpleasant taste are challenges that must be addressed to improve product quality and meet consumer expectations. Results Using in-silico screening and food safety classifications, 31 strains were selected as potential L-lysine producers from approximately 2,500 potential candidates. Beneficially, 30% of the isolates significantly accumulated amino acids (up to 1.4 mM) during chickpea milk fermentation, increasing the natural level by up to 43%. The best-performing strains, B. amyloliquefaciens NCC 156 and L. paracasei subsp. paracasei NCC 2511, were tested further. De novo lysine biosynthesis was demonstrated in both strains by 13C metabolic pathway analysis. Spiking small amounts of citrate into the fermentation significantly activated L-lysine biosynthesis in NCC 156 and stimulated growth. Both microbes revealed additional benefits in eliminating indigestible sugars such as stachyose and raffinose and converting off-flavour aldehydes into the corresponding alcohols and acids with fruity and sweet notes. Conclusions B. amyloliquefaciens NCC 156 and L. paracasei subsp. paracasei NCC 2511 emerged as multi-benefit microbes for chickpea milk fermentation with strong potential for industrial processing of the plant material. Given the high number of L-lysine-producing isolates identified in silico, this concept appears promising to support strain selection for food fermentation

Social inertia in collaboration networks

This work is a study of the properties of collaboration networks employing the formalism of weighted graphs to represent their one-mode projection. The weight of the edges is directly the number of times that a partnership has been repeated. This representation allows us to define the concept of "social inertia" that measures the tendency of authors to keep on collaborating with previous partners. We use a collection of empirical datasets to analyze several aspects of the social inertia: 1) its probability distribution, 2) its correlation with other properties, and 3) the correlations of the inertia between neighbors in the network. We also contrast these empirical results with the predictions of a recently proposed theoretical model for the growth of collaboration networks.Comment: 7 pages, 5 figure

A cosmological model in Weyl-Cartan spacetime

We present a cosmological model for early stages of the universe on the basis of a Weyl-Cartan spacetime. In this model, torsion $T^{\alpha}$ and nonmetricity $Q_{\alpha \beta}$ are proportional to the vacuum polarization. Extending earlier work of one of us (RT), we discuss the behavior of the cosmic scale factor and the Weyl 1-form in detail. We show how our model fits into the more general framework of metric-affine gravity (MAG).Comment: 19 pages, 5 figures, typos corrected, uses IOP style fil