Power attenuation from restricting range of motion is minimized in subjects with fast RTD and following isometric training

Time-dependent measures consisting of rate of torque development (RTD), rate of velocity development (RVD), and rate of neuromuscular activation can be used to evaluate explosive muscular performance, which becomes critical when performing movements throughout limited ranges of motion (ROM). Using a HUMAC NORM dynamometer, seven males (27 ± 7 years) and six females (22 ± 3 years) underwent 8 weeks of maximal isometric dorsiflexion training 3 days/week. One leg was trained at 0° (short-muscle tendon unit (MTU) length) and the other at 40° of plantar flexion (long-MTU length). RTD and rate of neuromuscular activation were evaluated during 'fast' maximal isometric contractions. Power, RVD, and rate of neuromuscular activation were assessed during maximal isotonic contractions in four conditions (small (40° to 30° of plantar flexion) ROM at 10 and 50% MVC; large (40° to 0° of plantar flexion) ROM at 10 and 50% MVC) for both legs, pre- and post-training. Despite no change in rate of neuromuscular activation following training, peak power, RTD, and RVD increased at both MTU lengths (p < 0.05). Strong relationships (R2=0.73) were observed between RTD and peak power in the small ROM, indicating that fast time-dependent measures are critical for optimal performance when ROM is constrained. Meanwhile, strong relationships (R2=0.90) between RVD and power were observed at the 50% load, indicating that RVD is critical when limited by load and ROM is not confined. Maximal isometric dorsiflexion training can be used to improve time-dependent measures (RTD, RVD) to minimize power attenuation when ROM is restricted.

Predictive Neuronal Adaptation as a Basis for Consciousness

Being able to correctly predict the future and to adjust own actions accordingly can offer a great survival advantage. In fact, this could be the main reason why brains evolved. Consciousness, the most mysterious feature of brain activity, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Similarly at a single neuron level, predicting future activity and adapting synaptic inputs accordingly was shown to be the best strategy to maximize the metabolic energy for a neuron. Following on these ideas, here we examined if surprise minimization by single neurons could be a basis for consciousness. First, we showed in simulations that as a neural network learns a new task, then the surprise within neurons (defined as the difference between actual and expected activity) changes similarly to the consciousness of skills in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of milliseconds) resulted in improved network performance. This improvement is likely because adapting activity based on the internal predictive model allows each neuron to make a more “educated” response to stimuli. Based on those results, we propose that the neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. Such adaptation allows neurons to exchange information about own predictions and thus to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this can allow testing directly our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational, and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.

Direct Determination of Reduced Models of a Class of Singularly Perturbed Nonlinear Systems on Three Time Scales in a Bond Graph Approach

One of the most important features in the analysis of the singular perturbation methods is the reduction of models. Likewise, the bond graph methodology in dynamic system modeling has been widely used. In this paper, the bond graph modeling of nonlinear systems with singular perturbations is presented. The class of nonlinear systems is the product of state variables on three time scales (fast, medium, and slow). Through this paper, the symmetry of mathematical modeling and graphical modeling can be established. A main characteristic of the bond graph is the application of causality to its elements. When an integral causality is assigned to the storage elements that determine the state variables, the dynamic model is obtained. If the storage elements of the fast dynamics have a derivative causality and the storage elements of the medium and slow dynamics an integral causality is assigned, a reduced model is obtained, which consists of a dynamic model for the medium and slow time scales and a stationary model of the fast time scale. By applying derivative causality to the storage elements of the fast and medium dynamics and an integral causality to the storage elements of the slow dynamics, the quasi-steady-state model for the slow dynamics is obtained and stationary models for the fast and medium dynamics are defined. The exact and reduced models of singularly perturbed systems can be interpreted as another symmetry in the development of this paper. Finally, the proposed methodology was applied to a system with three time scales in a bond graph approach, and simulation results are shown in order to indicate the effectiveness of the proposed methodology.

A Detailed Analysis of GW190521 with Phenomenological Waveform Models

In this paper we present an extensive analysis of the GW190521 gravitational wave event with the current (fourth) generation of phenomenological waveform models for binary black hole coalescences. GW190521 stands out from other events since only a few wave cycles are observable. This leads to a number of challenges, one being that such short signals are prone to not resolving approximate waveform degeneracies, which may result in multimodal posterior distributions. The family of waveform models we use includes a new fast time-domain model (IMRPhenomTPHM), which allows us to extensively test different priors and robustness with respect to variations in the waveform model, including the content of spherical harmonic modes. We clarify some issues raised in a recent paper, Nitz & Capano, associated with possible support for a high-mass-ratio source, but confirm their finding of a multimodal posterior distribution, albeit with important differences in the statistical significance of the peaks. In particular, we find that the support for both masses being outside the pair instability supernova mass gap, and the support for an intermediate-mass-ratio binary are drastically reduced with respect to what Nitz & Capano found. We also provide updated probabilities for associating GW190521 to the potential electromagnetic counterpart from the Zwicky Transient Facility (ZTF) Graham et al.

The Simulation of Traffic Signal Preemption using GPS and Dijkstra Algorithm for Emergency Fire Handling at Makassar City Fire Service

The Makassar City Fire Department often faces obstacles in handling fires. Problems that often hinder such as congestion at crossroads, panic residents, and others. The result of this research is a system that can assist firefighters when handling fire cases in terms of accelerating the firefighting team to the location of the fire. Dijkstra's algorithm will be used to find the shortest path to the fire location and the travel time. Then the traffic signal preemption simulation adjusts the color of the lights when the GPS vehicle approaches the traffic lights on the path to be traversed. The simulation results show that the use of traffic signal preemption in collaboration with Dijkstra's algorithm and GPS can help the performance of the Makassar City Fire Department, especially for handling fires that require fast time.

Ultrafast carrier dynamics at organic donor-acceptor interfaces - A quantum-based assessment of the hopping model

We investigate the charge transfer dynamics of photogenerated excitons at the donor-acceptor interface of an organic solar cell blend under the influence of molecular vibrations. This is examined using an effective Hamiltonian, parametrized by density functional theory calculations, to describe the full quantum behaviour of the relevant molecular orbitals, which are electronically coupled with each other and coupled to over one hundred vibrations (via Holstein coupling). This electron-phonon system is treated in a numerically quasi-exact fashion using the matrix-product-state ansatz. We provide insight into different mechanisms of charge separation and their relation to the electronic driving energy for the separation process. We find ultrafast electron transfer, which for small driving energy is dominated by kinetic processes and at larger driving energies by dissipative phonon emission connected to the prevalent vibration modes. Using this fully quantum mechanical model we perform a benchmark comparison to a recently developed semi-classical hopping approach, which treats the hopping and vibration time scales consistently. We find qualitatively and quantitatively good agreement between the results of the sophisticated matrix-product-state based quantum dynamics and the simple and fast time-consistent-hopping approach.

Radiometric analysis of digitized Z-scope records in archival radar sounding film

The earliest airborne geophysical campaigns over Antarctica and Greenland in the 1960s and 1970s collected ice penetrating radar data on 35 mm optical film. Early subglacial topographic and englacial stratigraphic analyses of these data were foundational to the field of radioglaciology. Recent efforts to digitize and release these data have resulted in geometric and ice-thickness analysis that constrain subsurface change over multiple decades but stop short of radiometric interpretation. The primary challenge for radiometric analysis is the poorly-characterized compression applied to Z-scope records and the sparse sampling of A-scope records. Here, we demonstrate the information richness and radiometric interpretability of Z-scope records. Z-scope pixels have uncalibrated fast-time, slow-time, and intensity scales. We develop approaches for mapping each of these scales to physical units (microseconds, seconds, and signal to noise ratio). We then demonstrate the application of this calibration and analysis approach to a flight in the interior of East Antarctica with subglacial lakes and to a reflight of an East Antarctic ice shelf that was observed by both archival and modern radar. These results demonstrate the potential use of Z-scope signals to extend the baseline of radiometric observations of the subsurface by decades.

Effort, success, and side of lesion determine arm choice in chronic stroke survivors with mild-to-moderate impairment

In neurotypical individuals, arm choice in reaching movements depends on expected biomechanical effort, expected success, and a handedness bias. Following a stroke, does arm choice change to account for the decreased motor performance, or does it follow a pre-injury habitual preference pattern? Participants with mild to moderate chronic stroke who were right-handed before stroke performed reaching movements in both spontaneous and forced-choice blocks, under no-time, medium-time, and fast-time constraint conditions designed to modulate reaching success. Mixed-effects logistic regression models of arm choice revealed that expected effort predicted choices. However, expected success only strongly predicted choice in left-hemiparetic individuals. In addition, reaction times decreased in left-hemiparetic individuals between the no-time and the fast-time constraint conditions but showed no changes in right-hemiparetic individuals. Finally, arm choice in the no-time constraint condition correlated with a clinical measure of spontaneous arm use for right-, but not for left-hemiparetic individuals. Our results are consistent with the view that right hemiparetic individuals show a habitual pattern of arm choice for reaching movements relatively independent of failures. In contrast, left hemiparetic individuals appear to choose their paretic left arm more optimally: that is, if a movement with the paretic arm is predicted to be not successful in the upcoming movement, the non-paretic right arm is chosen instead.