Realistic many-body models for Manganese Monoxide under pressure

In materials like transition metals oxides where electronic Coulomb correlations impede a description in terms of standard band-theories, the application of genuine many-body techniques is inevitable. Interfacing the realism of density-functional based methods with the virtues of Hubbard-like Hamiltonians, requires the joint ab initio construction of transfer integrals and interaction matrix elements (like the Hubbard U) in a localized basis set. In this work, we employ the scheme of maximally localized Wannier functions and the constrained random phase approximation to create effective low-energy models for Manganese monoxide, and track their evolution under external pressure. We find that in the low pressure antiferromagnetic phase, the compression results in an increase of the bare Coulomb interaction for specific orbitals. As we rationalized in recent model considerations [Phys. Rev. B 79, 235133 (2009)], this seemingly counter-intuitive behavior is a consequence of the delocalization of the respective Wannier functions. The change of screening processes does not alter this tendency, and thus, the screened on-site component of the interaction - the Hubbard U of the effective low-energy system - increases with pressure as well. The orbital anisotropy of the effects originates from the orientation of the orbitals vis-a-vis the deformation of the unit-cell. Within the high pressure paramagnetic phase, on the other hand, we find the significant increase of the Hubbard U is insensitive to the orbital orientation and almost exclusively owing to a substantial weakening of screening channels upon compression.Comment: 13 pages, 6 figure

Wind Forced Variability in Eddy Formation, Eddy Shedding, and the Separation of the East Australian Current

The East Australian Current (EAC), like many other subtropical western boundary currents, is believed to be penetrating further poleward in recent decades. Previous observational and model studies have used steady state dynamics to relate changes in the westerly winds to changes in the separation behavior of the EAC. As yet, little work has been undertaken on the impact of forcing variability on the EAC and Tasman Sea circulation. Here using an eddy‐permitting regional ocean model, we present a suite of simulations forced by the same time‐mean fields, but with different atmospheric and remote ocean variability. These eddy‐permitting results demonstrate the nonlinear response of the EAC to variable, nonstationary inhomogeneous forcing. These simulations show an EAC with high intrinsic variability and stochastic eddy shedding. We show that wind stress variability on time scales shorter than 56 days leads to increases in eddy shedding rates and southward eddy propagation, producing an increased transport and southward reach of the mean EAC extension. We adopt an energetics framework that shows the EAC extension changes to be coincident with an increase in offshore, upstream eddy variance (via increased barotropic instability) and increase in subsurface mean kinetic energy along the length of the EAC. The response of EAC separation to regional variable wind stress has important implications for both past and future climate change studies

Potassium channels in cell cycle and cell proliferation

Normal cell-cycle progression is a crucial task for every multicellular organism, as it determines body size and shape, tissue renewal and senescence, and is also crucial for reproduction. On the other hand, dysregulation of the cell-cycle progression leading to uncontrolled cell proliferation is the hallmark of cancer. Therefore, it is not surprising that it is a tightly regulated process, with multifaceted and very complex control mechanisms. It is now well established that one of those mechanisms relies on ion channels, and in many cases specifically on potassium channels. Here, we summarize the possible mechanisms underlying the importance of potassium channels in cell-cycle control and briefly review some of the identified channels that illustrate the multiple ways in which this group of proteins can influence cell proliferation and modulate cell-cycle progression

“Where’s the I-O?” Artificial Intelligence and Machine Learning in Talent Management Systems

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; and in addressing the issue of fairness, we present experimental evidence regarding the potential for AI/ML to evoke adverse reactions from job applicants during selection procedures. We close by emphasizing increased collaboration among I-O psychologists, computer scientists, legal scholars, and members of other professional disciplines in developing, implementing, and evaluating AI/ML applications in organizational contexts

Structured Random Matrices

Random matrix theory is a well-developed area of probability theory that has numerous connections with other areas of mathematics and its applications. Much of the literature in this area is concerned with matrices that possess many exact or approximate symmetries, such as matrices with i.i.d. entries, for which precise analytic results and limit theorems are available. Much less well understood are matrices that are endowed with an arbitrary structure, such as sparse Wigner matrices or matrices whose entries possess a given variance pattern. The challenge in investigating such structured random matrices is to understand how the given structure of the matrix is reflected in its spectral properties. This chapter reviews a number of recent results, methods, and open problems in this direction, with a particular emphasis on sharp spectral norm inequalities for Gaussian random matrices.Comment: 46 pages; to appear in IMA Volume "Discrete Structures: Analysis and Applications" (Springer

Downfolded Self-Energy of Many-Electron Systems

Starting from the full many-body Hamiltonian of interacting electrons the effective self-energy acting on electrons residing in a subspace of the full Hilbert space is derived. This subspace may correspond to, for example, partially filled narrow bands, which often characterize strongly correlated materials. The formalism delivers naturally the frequency-dependent effective interaction (the Hubbard U) and provides a general framework for constructing theoretical models based on the Green function language. It also furnishes a general scheme for first-principles calculations of complex systems in which the main correlation effects are concentrated on a small subspace of the full Hilbert space.Comment: 5 page

Bubble-Mediated Gas Transfer and Gas Transfer Suppression of DMS and CO2

Direct dimethyl sulfide (DMS) flux measurements using eddy covariance have shown a suppression of gas transfer at medium to high wind speed. However, not all eddy covariance measurements show evidence of this suppression. Processes, such as wave-wind interaction and surfactants, have been postulated to cause this suppression. We measured DMS and carbon dioxide eddy covariance fluxes during the Asian summer monsoon in the western tropical Indian Ocean (July and August 2014). Both fluxes and their respective gas transfer velocities show signs of a gas transfer suppression above 10 m/s. Using a wind-wave interaction, we describe a flow separation process that could be responsible for a suppression of gas transfer. As a result we provide a Reynolds number-based parameterization, which states the likelihood of a gas transfer suppression for this cruise and previously published gas transfer data. Additionally, we compute the difference in the gas transfer velocities of DMS and CO2 to estimate the bubble-mediated gas transfer using a hybrid model with three whitecap parameterizations