Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction

Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was computed in 50 patients ≥ age 60 before and during surgery. Average MSE was higher intra-operatively than pre-operatively (p = 0.0003). However, intraoperative EEG MSE was lower than preoperative MSE at smaller scales, but higher at larger scales (interaction p < 0.001), creating a crossover point where, by definition, preoperative, and intraoperative MSE curves met. Overall, EEG complexity was not associated with delirium or attention. In 42/50 patients with single crossover points, the scale at which the intraoperative and preoperative entropy curves crossed showed an inverse relationship with delirium-severity score change (Spearman ρ = −0.31, p = 0.054). Thus, average EEG complexity increases intra-operatively in older adults, but is scale dependent. The scale at which preoperative and intraoperative complexity is equal (i.e., the crossover point) may predict delirium. Future studies should assess whether the crossover point represents changes in neural control mechanisms that predispose patients to postoperative delirium.

CRITICAL SHIFTING WINDOW IN SWITCHABLE ROCKER FINGER FOLLOWER

A valvetrain including switchable rocker finger follower is capable of discrete switching between two modes (two cam profiles). The exact moment when switching occurs is called crossover point and this paper reviews the factors that cause the shift of the crossover point from its nominal design position. The range where crossover point can shift is called critical shifting window and its size and factors influencing it will be adressed.

Effectiveness of common water-reducing admixtures in alkali-activated slag pastes with different types of activator

Rheology of alkali-activated slag (AAS) is a very complex issue, where the activator nature as well as its dose play an important role. Moreover, the use of water-reducing admixtures in these systems is an issue, as they often do not work properly. This could be attributed to the high pH as well as to the surface chemistry of AAS. Therefore, lignosulfonate-, polynaphthalene- and polycarboxylate-based superplasticizers were used to modify AAS pastes with sodium waterglass, hydroxide and carbonate activator. These pastes were tested using a rotational rheometer in an oscillatory shear mode of increasing shear strain to observe the evolution of viscoelastic moduli and to determine the oscillatory stress corresponding to the linear viscoelastic region limit (“yield point”) and to the crossover point, where the storage modulus equals the loss modulus (“flow point”). In most cases, the used plasticizers did not improve the rheological properties; the only exception was the lignosulfonate one in sodium hydroxide-activated slag.

Crossover from BKT-Rough to KPZ-Rough Surfaces for Crystal Growth/Recession

We found a crossover from a Berezinskii-Kosterlitz-Thouless (BKT, logarithmic-rough surface to a Kardar-Parisi-Zhang (KPZ, algebraic)-rough surface for growing/recessing vicinal crystal surfaces in the non-equilibrium steady state using the Monte-Carlo method. We also found that the crossover point from a BKT-rough surface to a KPZ-rough surface is different from the kinetic roughening point for the (001) surface. Multilevel islands and negative islands (island-shaped holes) on the terrace formed by the two-dimensional nucleation process are found to block surface fluctuations, which contributes to making a BKT-rough surface.

Long-range vector models at large N

We calculate various CFT data for the O(N) vector model with the long-range interaction, working at the next-to-leading order in the 1/N expansion. Our results provide additional evidence for the existence of conformal symmetry at the long-range fixed point, as well as the continuity of the CFT data at the long-range to short-range crossover point s* of the exponent parameter s. We also develop the N > 1 generalization of the recently proposed IR duality between the long-range and the deformed short-range models, providing further evidence for its non-perturbative validity in the entire region d/2 < s < s*.

Crossover point of the field effect transistor and interconnect applications in turbostratic multilayer graphene nanoribbon channel

The electrical transport properties of a turbostratic multilayer graphene nanoribbon (GNR) with various number of layers (1–8 layers) were investigated using a field effect transistor with a single GNR channel. In the turbostratic multilayer GNR with 5 layers or less, the carrier mobility and Ion/Ioff ratio in the FETs were improved by slightly increasing the conductance with increasing the number of layers, meaning that the excellent semiconducting characteristic. The improvement of the carrier transport properties promotes by the turbostratic stacking structure. In the turbostratic multilayer GNR with 6 layers or more, although the Ion/Ioff ratio degraded, the conductance extremely improved with increasing the number of layers. This indicates that the turbostratic multilayer GNR with thicker number of layers becomes the significantly lower resistivity wire as a metallic characteristic. We revealed that the crossover point of the physical properties between the semiconducting and metallic characteristics is determined by the strength to screen the surrounding environment effects such as charged impurity on the substrate. Our comprehensive investigation provides a design guidance for the various electrical device applications of GNR materials.