On the human taste perception: Molecular-level understanding empowered by computational methods

Background: The perception of taste is a prime example of complex signal transduction at the subcellular level, involving an intricate network of molecular machinery, which can be investigated to great extent by the tools provided by Computational Molecular Modelling. The present review summarises the current knowledge on the molecular mechanisms at the root of taste transduction, in particular involving taste receptors, highly specialised proteins driving the activation/deactivation of specific cell signalling pathways and ultimately leading to the perception of the five principal tastes: sweet, umami, bitter, salty and sour. The former three are detected by similar G protein-coupled receptors, while the latter two are transduced by ion channels. Scope and approach: The main objective of the present review is to provide a general overview of the molecular structures investigated to date of all taste receptors and the techniques employed for their molecular modelling. In addition, we provide an analysis of the various ligands known to date for the above-listed receptors, including how they are activated in the presence of their target molecule. Key findings and conclusions: In the last years, numerous advances have been made in molecular research and computational investigation of ligand-receptor interaction related to taste receptors. This work aims to outline the progress in scientific knowledge about taste perception and understand the molecular mechanisms involved in the transfer of taste information

Physics research on the TCV tokamak facility: from conventional to alternative scenarios and beyond

The research program of the TCV tokamak ranges from conventional to advanced-tokamak scenarios and alternative divertor configurations, to exploratory plasmas driven by theoretical insight, exploiting the device’s unique shaping capabilities. Disruption avoidance by real-time locked mode prevention or unlocking with electron-cyclotron resonance heating (ECRH) was thoroughly documented, using magnetic and radiation triggers. Runaway generation with high-Z noble-gas injection and runaway dissipation by subsequent Ne or Ar injection were studied for model validation. The new 1 MW neutral beam injector has expanded the parameter range, now encompassing ELMy H-modes in an ITER-like shape and nearly non-inductive H-mode discharges sustained by electron cyclotron and neutral beam current drive. In the H-mode, the pedestal pressure increases modestly with nitrogen seeding while fueling moves the density pedestal outwards, but the plasma stored energy is largely uncorrelated to either seeding or fueling. High fueling at high triangularity is key to accessing the attractive small edge-localized mode (type-II) regime. Turbulence is reduced in the core at negative triangularity, consistent with increased confinement and in accord with global gyrokinetic simulations. The geodesic acoustic mode, possibly coupled with avalanche events, has been linked with particle flow to the wall in diverted plasmas. Detachment, scrape-off layer transport, and turbulence were studied in L- and H-modes in both standard and alternative configurations (snowflake, super-X, and beyond). The detachment process is caused by power ‘starvation’ reducing the ionization source, with volume recombination playing only a minor role. Partial detachment in the H-mode is obtained with impurity seeding and has shown little dependence on flux expansion in standard single-null geometry. In the attached L-mode phase, increasing the outer connection length reduces the in–out heat-flow asymmetry. A doublet plasma, featuring an internal X-point, was achieved successfully, and a transport barrier was observed in the mantle just outside the internal separatrix. In the near future variable-configuration baffles and possibly divertor pumping will be introduced to investigate the effect of divertor closure on exhaust and performance, and 3.5 MW ECRH and 1 MW neutral beam injection heating will be added

Modeling and Control of Pipeline Networks Supplied by Automated Irrigation Channels

Abstract not availableBojan Mavkov, Timm Strecker, Aaron C. Zecchin, and Michael Canton

Experimental validation of a Lyapunov-based controller for the plasma safety factor and plasma pressure in the TCV tokamak

In this paper, model-based closed-loop algorithms are derived for distributed control of the inverse of the safety factor profile and the plasma pressure parameter β of the TCV tokamak. The simultaneous control of the two plasma quantities is performed by combining two different control methods. The control design of the plasma safety factor is based on an infinite-dimensional setting using Lyapunov analysis for partial differential equations, while the control of the plasma pressure parameter is designed using control techniques for single-input and single-output systems. The performance and robustness of the proposed controller is analyzed in simulations using the fast plasma transport simulator RAPTOR. The control is then implemented and tested in experiments in TCV L-mode discharges using the RAPTOR model predicted estimates for the q-profile. The distributed control in TCV is performed using one co-current and one counter-current electron cyclotron heating actuation

Fragmented blind docking: a novel protein–ligand binding prediction protocol

In the present paper we propose a novel blind docking protocol based on Autodock-Vina. The developed docking protocol can provide binding site identification and binding pose prediction at the same time, by a systematical exploration of the protein volume performed with several preliminary docking calculations. In our opinion, this protocol can be successfully applied during the first steps of the virtual screening pipeline, because it provides binding site identification and binding pose prediction at the same time without visual evaluation of the binding site. After the binding pose prediction, MM/GBSA re-scoring rescoring procedures has been applied to improve the accuracy of the protein–ligand bound state. The FRAD protocol has been tested on 116 protein–ligand complexes of the Heat Shock Protein 90–alpha, on 176 of Human Immunodeficiency virus protease 1, and on more than 100 protein–ligand system taken from the PDBbind dataset. Overall, the FRAD approach combined to MM/GBSA re-scoring can be considered as a powerful tool to increase the accuracy and efficiency with respect to other standard docking approaches when the ligand-binding site is unknown. Communicated by Ramaswamy H. Sarma

Real-time control of neoclassical tearing modes and its integration with multiple controllers in the TCV Tokamak

\u3cp\u3ePreliminary integrated control of NTMs, beta and model-estimated q profiles has been demonstrated experimentally in TCV for the first time. An upgrade of the supervision layer is foreseen. Dedicated NTM tests show that density affects the triggering of NTMs through global q profile modifications with central co-ECCD - too low or too high density will hinder the triggering. More detailed simulations are ongoing to further clarify these effects.\u3c/p\u3

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks

Profile control simulations and experiments on TCV: A controller test environment and results using a model-based predictive controller

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks

Real-time control of neoclassical tearing modes and its integration with multiple controllers in the TCV Tokamak

\u3cp\u3ePreliminary integrated control of NTMs, beta and model-estimated q profiles has been demonstrated experimentally in TCV for the first time. An upgrade of the supervision layer is foreseen. Dedicated NTM tests show that density affects the triggering of NTMs through global q profile modifications with central co-ECCD - too low or too high density will hinder the triggering. More detailed simulations are ongoing to further clarify these effects.\u3c/p\u3