Confinement in bilayer graphene via intra- and inter-layer interactions

We consider confinement of Dirac fermions in AB-stacked bilayer graphene by inhomogeneous on-site interactions, (pseudo-)magnetic field or inter-layer interaction. Working within the framework of four-band approximation, we focus on the systems where the stationary equation is reducible into two stationary equations with 2x2 Dirac-type Hamiltonians and auxiliary interactions. We show that the localized states are given in terms of solutions of an effective Schrodinger equation with energy-dependent potential. We consider several scenarios where bilayer graphene is subject to inhomogneous (pseudo-)magnetic field, on-site interactions or inter-layer coupling. In explicit examples, we provide analytical solutions for the states localized by local fluctuations or periodicity defects of the interactions.

Cooperative protein allosteric transition mediated by a fluctuating transmission network

Allosteric communication between distant protein sites represents a key mechanism of biomolecular regulation and signal transduction. Compared to other processes such as protein folding, however, the dynamical evolution of allosteric transitions is still not well understood. As example of allosteric coupling between distant protein regions, we consider the global open-closed motion of the two domains of T4 lysozyme, which is triggered by local motions in the hinge region. Combining extensive molecular dynamics simulations with machine learning of contact features, we identify a network of interresidue distances that move in a concerted manner. The cooperative process originates from a cogwheel-like motion of the hydrophobic core in the hinge region, which constitutes a flexible transmission network. Through rigid contacts and the protein backbone, the small local changes of the hydrophobic core are passed on to the distant terminal domains and lead to the emergence of a rare global conformational transition. As in an Ising-type model, the cooperativity of the allosteric transition can be explained via the interaction of local fluctuations.

Fast Directional Changes during Geomagnetic Transitions: Global Reversals or Local Fluctuations?

Paleomagnetic investigations from sediments in Central and Southern Italy found directional changes of the order of 10∘ per year during the last geomagnetic field reversal (which took place about 780,000 years ago). These values are orders of magnitudes larger than what is expected from the estimated millennial timescales for geomagnetic field reversals. It is yet unclear whether these extreme changes define the timescale of global dipolar change or whether they indicate a rapid, but spatially localised feature that is not indicative of global variations. Here, we address this issue by calculating the minimum amount of kinetic energy that flows at the top of the core required to instantaneously reproduce these two scenarios. We found that optimised flow structures compatible with the global-scale interpretation of directional change require about one order of magnitude more energy than those that reproduce local change. In particular, we found that the most recently reported directional variations from the Sulmona Basin, in Central Italy, can be reproduced by a core-surface flow with rms values comparable to, or significantly lower than, present-day estimates of about 8 to 22 km/y. Conversely, interpreting the observations as global changes requires rms flow values in excess of 77 km/y, with pointwise maximal velocities of 127 km/y, which we deem improbable. We therefore concluded that the extreme variations reported for the Sulmona Basin were likely caused by a local, transient feature during a longer transition.

Bispectral analysis of broadband turbulence and geodesic acoustic modes in the T-10 tokamak

Local fluctuations of electrostatic potential, poloidal electric field, magnetic potential and electron density are simultaneously measured in the T-10 tokamak by a heavy ion beam probe (HIBP) having a five-slit energy analyser, which allows an estimate of the turbulent particle flux and $\boldsymbol {E}\times \boldsymbol {B}$ rotation velocity in the off-minor-axis gradient zone of the toroidal plasma column. The high spatial and temporal resolution of the modern multichannel HIBP makes it an effective tool to study plasma oscillations. Motivated by previous work that has documented time-resolved interactions between measured plasma parameters using correlation analysis (coherence of $E_{\textrm {pol}}$ and density $n_e$ , and cross-phase), a new result from bicorrelation analysis (bicoherence of magnetic potential $A_\zeta$ and density $n_e$ , and biphase) is reported for documenting the evidence of wave–wave coupling and energy transfer associated with the interaction between geodesic acoustic modes (GAM) and broadband, quasi-coherent modes.

A Deep Learning Model to Forecast Solar Irradiance Using a Sky Camera

Solar irradiance fluctuates mainly due to clouds. A sky camera offers images with high temporal and spatial resolutions for a specific solar photovoltaic plant. The cloud cover from sky images is suitable for forecasting local fluctuations of solar irradiance and thereby solar power. Because no study applied deep learning for forecasting cloud cover using sky images, this study attempted to apply the long short-term memory algorithm in deep learning. Cloud cover data were collected by image processing of sky images and used for developing the deep learning model to forecast cloud cover 10 minutes ahead. The forecasted cloud cover data were plugged into solar radiation models as input in order to predict global horizontal irradiance. The forecasted results were grouped into three categories based on sky conditions: clear sky, partly cloudy, and overcast sky. By comparison with solar irradiance measurement at a ground station, the proposed model was evaluated. The proposed model outperformed the persistence model under high variability of solar irradiance such as partly cloudy days with relative root mean square differences for 10-minute-ahead forecasting are 25.10% and 39.95%, respectively. Eventually, this study demonstrated that deep learning can forecast the cloud cover from sky images and thereby can be useful for forecasting solar irradiance under high variability.

Dynamic Susceptibilities in Dense Soft Athermal Spheres Under a Finite-Rate Shear

The mechanical responses of dense packings of soft athermal spheres under a finite-rate shear are studied by means of molecular dynamics simulations. We investigate the volume fraction and shear rate dependence of the fluctuations in the shear stress and the interparticle contact number. In particular, we quantify them by defining the susceptibility as the ratio of the global to local fluctuations. The obtained susceptibilities form ridges on the volume fraction-shear rate plane, which are reminiscent of the Widom lines around the critical point in an equilibrium phase transition.

Feeding strategies for improving ruminant productivity in the post-COVID 19 pandemic era particularly for small holders

COVID-19 has highlighted the need for robust cattle supply chains using local feed resources. Higher Income Over Food Costs (IOFC) are usually achieved when live weight gains are high and the cost of the ingredients are low. There is a need to formulate rations with high metabolisable energy (ME) and crude protein (CP) to achieve the high live weight gain. Rations can be formulated locally by farmer co-operatives, entrepreneurs and local commercial enterprises to take advantage of cheaper prices for local ingredients. To do this, rations need to be altered quickly to take advantage of local fluctuations in prices and availability of ingredients. A recent ACIAR funded project has developed a least cost ration (ACIAR LCR) system to formulate rations to meet minimum ME and CP contents for beef cattle using locally available ingredients. The use of cassava and its various products in combination with protein sources, such as tree legumes and high protein by-products, have markedly improved IOFC.