Nonlinear Quantum Phenomena During the Polarization of Nanometer Layers of Proton Semiconductors and Dielectrics

This paper investigates the influence of the structure and parameters of the degenerate quasi-discrete energy spectrum of relaxers (protons) on the mechanism of nonlinear quantum diffusion polarization in nanoscale layers of hydrogen bonded crystals (HBC) in a wide range of parameters of fields (100 kV/m - 1000 MV/m) and temperatures (0-1550 K). The temperature dependence of the quantum transparency of the parabolic potential barrier for protons in HBC is calculated using the Gibbs quantum canonical distribution for the ensemble of non-interacting protons (ideal proton gas balanced with the ions of anion sub-lattice) moving in an onedimensional potential field of a crystalline lattice (in the field of hydrogen bonds) with a zone structure distributed by energy levels. The influence of "zero" oscillations of protons on the temperature dependences of the proton subsystem kinetic coefficients in HBC is considered. It is revealed that proton tunneling influences the nonlinear space-charge polarization kinetics in HBC at high (150-550 K) and ultrahigh (550-1550 K) temperatures when crystalline layer thickness ranges from 1 to 10 nm. The results of theoretical studies (based on earlier experiments) are bound to be prospective for the prediction of HBC-class (KDP, DKDP) ferroelectrics properties, studying the second-order nonlinear optical effects of femtosecond lasers, and the development of memory cells for non-volatile high-speed memory devices.

Poisson regression for linguists: A tutorial introduction to modeling count data with brms

Count data is prevalent in many different areas of linguistics, such as when counting words, syntactic constructions, discourse particles, case markers, or speech errors. The Poisson distribution is the canonical distribution for characterizing count data with no or unknown upper bound. Whereas logistic regression is very common in linguistics, Poisson regression is little known. This tutorial introduces readers to foundational concepts needed for Poisson regression, followed by a hands-on tutorial using the R package brms. We discuss a dataset where Catalan and Korean speakers change the frequency of their co-speech gestures as a function of politeness contexts. This dataset also involves exposure variables (the incorporation of time to deal with unequal intervals) and overdispersion (excess variance). Altogether, we hope that more linguists will consider Poisson regression for the analysis of count data.

Entropy minimization, convergence, and Gibbs ensembles (local and global)

We approach the subject of Statistical Mechanics from two different perspectives. In Part I we adopt the approach of Lanford and Martin-Lof. We examine the minimization of information entropy for measures on the phase space of bounded domains, subject to constraints that are averages of grand canonical distributions. We describe the set of all such constraints and show that it equals the set of averages of all probability measures absolutely continuous with respect to the standard measure on the phase space. We also investigate how the set of constrains relates to the domain of the microcanonical thermodynamic limit entropy. We then show that, for fixed constraints, the parameters of the corresponding grand canonical distribution converge, as volume increases, to the corresponding parameters (derivatives, when they exist) of the thermodynamic limit entropy. In Part II, we use the Banach manifold structure on the space of finite positive measures to show that the critical points of the Gibbs entropy are grand canonical equilibria when the constraints are scalar, and local equilibria when the constraints are integrable functions. This provides a rigorous justification of the derivation of the Gibbs measures that appears often in literature.

Differentiating Drosophila female germ cells initiate Polycomb silencing by regulating PRC2-interacting proteins

Polycomb silencing represses gene expression and provides a molecular memory of chromatin state that is essential for animal development. We show that Drosophila female germline stem cells (GSCs) provide a powerful system for studying Polycomb silencing. GSCs have a non-canonical distribution of PRC2 activity and lack silenced chromatin like embryonic progenitors. As GSC daughters differentiate into nurse cells and oocytes, nurse cells, like embryonic somatic cells, silence genes in traditional Polycomb domains and in generally inactive chromatin. Developmentally controlled expression of two Polycomb repressive complex 2 (PRC2)-interacting proteins, Pcl and Scm, initiate silencing during differentiation. In GSCs, abundant Pcl inhibits PRC2-dependent silencing globally, while in nurse cells Pcl declines and newly induced Scm concentrates PRC2 activity on traditional Polycomb domains. Our results suggest that PRC2-dependent silencing is developmentally regulated by accessory proteins that either increase the concentration of PRC2 at target sites or inhibit the rate that PRC2 samples chromatin.