Multi-Agent Reinforcement Learning for Railway Rescheduling

Malfunctions, congestions, and accidents occur in every railway system from time to time, which influences the railway traffic on a given section of the system. The disturbance may cause inconvenience for several passengers and disruption in rail freight. Both the schedule and route of the affected trains must be modified to avoid further congestion and minimalize delays. The rigidity of the railway system (e.g., single tracks, vast distances without a service station, no viable alternative in case of malfunction) poses restrictions, unlike other transportation systems. Replanning schedules and train routes (called the railway rescheduling problem) is complex and demanding, even for human operators, as one must consider numerous factors. Thus, finding a satisfying solution poses a significant challenge. This paper presents a MARL-base (Multi-Agent Reinforcement Learning) solution that shows great potential for tackling this problem, even in the case of multiple connected stations

NMR investigations of the interaction between the azo-dye sunset yellow and Fluorophenol

The interaction of small molecules with larger noncovalent assemblies is important across a wide range of disciplines. Here, we apply two complementary NMR spectroscopic methods to investigate the interaction of various fluorophenol isomers with sunset yellow. This latter molecule is known to form noncovalent aggregates in isotropic solution, and form liquid crystals at high concentrations. We utilize the unique fluorine-19 nucleus of the fluorophenol as a reporter of the interactions via changes in both the observed chemical shift and diffusion coefficients. The data are interpreted in terms of the indefinite self-association model and simple modifications for the incorporation of a second species into an assembly. A change in association mode is tentatively assigned whereby the fluorophenol binds end-on with the sunset yellow aggregates at low concentration and inserts into the stacks at higher concentrations

A novel epilepsy mutation in the sodium channel SCN1A identifies a cytoplasmic domain for {beta} subunit interaction

A mutation in the sodium channel SCN1A was identified in a small Italian family with dominantly inherited generalized epilepsy with febrile seizures plus (GEFS+). The mutation, D1866Y, alters an evolutionarily conserved aspartate residue in the C-terminal cytoplasmic domain of the sodium channel {alpha} subunit. The mutation decreased modulation of the {alpha} subunit by {beta}1, which normally causes a negative shift in the voltage dependence of inactivation in oocytes. There was less of a shift with the mutant channel, resulting in a 10 mV difference between the wild-type and mutant channels in the presence of {beta}1. This shift increased the magnitude of the window current, which resulted in more persistent current during a voltage ramp. Computational analysis suggests that neurons expressing the mutant channels will fire an action potential with a shorter onset delay in response to a threshold current injection, and that they will fire multiple action potentials with a shorter interspike interval at a higher input stimulus. These results suggest a causal relationship between a positive shift in the voltage dependence of sodium channel inactivation and spontaneous seizure activity. Direct interaction between the cytoplasmic C-terminal domain of the wild-type{alpha} subunit with the {beta}1or {beta}3 subunit was first demonstrated by yeast two-hybrid analysis. The SCN1A peptide K1846-R1886 is sufficient for {beta} subunit interaction. Coimmunoprecipitation from transfected mammalian cells confirmed the interaction between the C-terminal domains of the {alpha} and {beta}1 subunits. The D1866Y mutation weakens this interaction, demonstrating a novel molecular mechanism leading to seizure susceptibility

Characterizing environmentally assisted crack initiation and short crack growth

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Consistency and diversity of spike dynamics in the neurons of bed nucleus of Stria Terminalis of the rat: a dynamic clamp study

Neurons display a high degree of variability and diversity in the expression and regulation of their voltage-dependent ionic channels. Under low level of synaptic background a number of physiologically distinct cell types can be identified in most brain areas that display different responses to standard forms of intracellular current stimulation. Nevertheless, it is not well understood how biophysically different neurons process synaptic inputs in natural conditions, i.e., when experiencing intense synaptic bombardment in vivo. While distinct cell types might process synaptic inputs into different patterns of action potentials representing specific "motifs'' of network activity, standard methods of electrophysiology are not well suited to resolve such questions. In the current paper we performed dynamic clamp experiments with simulated synaptic inputs that were presented to three types of neurons in the juxtacapsular bed nucleus of stria terminalis (jcBNST) of the rat. Our analysis on the temporal structure of firing showed that the three types of jcBNST neurons did not produce qualitatively different spike responses under identical patterns of input. However, we observed consistent, cell type dependent variations in the fine structure of firing, at the level of single spikes. At the millisecond resolution structure of firing we found high degree of diversity across the entire spectrum of neurons irrespective of their type. Additionally, we identified a new cell type with intrinsic oscillatory properties that produced a rhythmic and regular firing under synaptic stimulation that distinguishes it from the previously described jcBNST cell types. Our findings suggest a sophisticated, cell type dependent regulation of spike dynamics of neurons when experiencing a complex synaptic background. The high degree of their dynamical diversity has implications to their cooperative dynamics and synchronization

Physics and chemistry of hydrogen in the vacancies of semiconductors

Hydrogen is well known to cause electrical passivation of lattice vacancies in semiconductors. This effect follows from the chemical passivation of the dangling bonds. Recently it was found that H in the carbon vacancy of SiC forms a three-center bond with two silicon neighbors in the vacancy, and gives rise to a new electrically active state. In this paper we examine hydrogen in the anion vacancies of BN, AlN, and GaN. We find that three-center bonding of H is quite common and follows clear trends in terms of the second-neighbor distance in the lattice, the typical (two-center) hydrogen-host-atom bond length, the electronegativity difference between host atoms and hydrogen, as well as the charge state of the vacancy. Three-center bonding limits the number of H atoms a nitrogen vacancy can capture to two, and prevents electric passivation in GaAs as well

Atomistic simulations of self-trapped exciton formation in silicon nanostructures: The transition from quantum dots to nanowires

Using an approximate time-dependent density functional theory method, we calculate the absorption and luminescence spectra for hydrogen passivated silicon nanoscale structures with large aspect ratio. The effect of electron confinement in axial and radial directions is systematically investigated. Excited state relaxation leads to significant Stokes shifts for short nanorods with lengths less than 2 nm, but has little effect on the luminescence intensity. The formation of self-trapped excitons is likewise observed for short nanostructures only; longer wires exhibit fully delocalized excitons with neglible geometrical distortion at the excited state minimum.Comment: 10 pages, 4 figure