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Understanding the physics of strongly correlated electronic systems has been a central issue in condensed matter physics for decades. In transition metal oxides, strong correlations characteristic of narrow d bands are at the origin of remarkable properties such as the opening of Mott gap, enhanced effective mass, and anomalous vibronic coupling, to mention a few. SrVO3 with V4+ in a 3d1 electronic configuration is the simplest example of a 3D correlated metallic electronic system. Here, the authors' focus on the observation of a (roughly) quadratic temperature dependence of the inverse electron mobility of this seemingly simple system, which is an intriguing property shared by other metallic oxides. The systematic analysis of electronic transport in SrVO3 thin films discloses the limitations of the simplest picture of e–e correlations in a Fermi liquid (FL); instead, it is shown show that the quasi-2D topology of the Fermi surface (FS) and a strong electron–phonon coupling, contributing to dress carriers with a phonon cloud, play a pivotal role on the reported electron spectroscopic, optical, thermodynamic, and transport data. The picture that emerges is not restricted to SrVO3 but can be shared with other 3d and 4d metallic oxides.
The upcoming commissioning of the superconducting (SC) continuous wave Helmholtz linear accelerators first of series cryomodule is going to demand precise alignment of the four internal SC cavities and two SC solenoids. For optimal results, a beam-based alignment method is used to reduce the misalignment of the whole cryomodule, as well as its individual components. A symmetric beam of low transverse emittance is required for this method, which is to be formed by a collimation system. It consists of two separate plates with milled slits, aligned in the horizontal and vertical direction. The collimation system and alignment measurements are proposed, investigated, and realized. The complete setup of this system and its integration into the existing environment at the GSI High Charge State Injector are presented, as well as the results of the recent reference measurements.
Anti-inflammatory effects of low-dose irradiation often follow a non-linear dose–effect relationship. These characteristics were also described for the modulation of leukocyte adhesion to endothelial cells. Previous results further revealed a contribution of reactive oxygen species (ROS) and anti-oxidative factors to a reduced leukocyte adhesion. Here, we evaluated the expression of anti-oxidative enzymes and the transcription factor Nrf2 (Nuclear factor-erythroid-2-related factor 2), intracellular ROS content, and leukocyte adhesion in primary human microvascular endothelial cells (HMVEC) upon low-dose irradiation under physiological laminar shear stress or static conditions after irradiation with X-ray or Carbon (C)-ions (0–2 Gy). Laminar conditions contributed to increased mRNA expression of anti-oxidative factors and reduced ROS in HMVEC following a 0.1 Gy X-ray and 0.5 Gy C-ion exposure, corresponding to reduced leukocyte adhesion and expression of adhesion molecules. By contrast, mRNA expression of anti-oxidative markers and adhesion molecules, ROS, and leukocyte adhesion were not altered by irradiation under static conditions. In conclusion, irradiation of endothelial cells with low doses under physiological laminar conditions modulates the mRNA expression of key factors of the anti-oxidative system, the intracellular ROS contents of which contribute at least in part to leucocyte adhesion, dependent on the radiation source.
Some terms identify enigmata of today’s cosmology: “Inflation” is expected to explain the homogeneity and isotropy of the cosmic background. The repulsive force of a “dark energy” shall prevent a re-collapse of the cosmos. The additional gravitational effect of a “dark matter” was originally supposed to explain the deviations of the rotation curves of the galaxies from Kepler’s laws. Adopting a theory founded on the core notion of absolute quantum information–Protyposis–being a cosmological concept from the outset, the observed phenomena can be explained without postulating further unknown specific “particles” or “fields”. Moreover, this theory allows for a rationalization of the fact that huge black holes with their enormous jet structures, acting as “seeds” of the galaxies, are detected ever closer to the big bang. The problem of the rotation curves in the galaxies can be addressed outside of General Relativity within a Newtonian approximation: by an attenuation of the gravitational acceleration as in the modified Newtonian dynamics, or by the effect of additional invisible “particles of dark matter”, yet unknown and not yet established in natural sciences. Within the Protyposis theory, these problems are solved without having to invent a lot of parameters. The cosmology of the Protyposis causes the change of the gravitational acceleration in the vicinity of large (black hole) masses and, at the same time, avoids a recollapse of the cosmos for which a cosmological constant or “dark energy” was invented.
The RFQ direct injection project (RFQ-DIP) for the neutrino physics experiment IsoDAR aims at an efficient injection of a high-current H²⁺ beam into the dedicated 60 MeV driver cyclotron. Therefore, it is intended to use a compact 32.8 MHz RFQ structure of the split-coaxial type as a pre-buncher. To determine the thermal elongation of the 1.4 m long electrode rods as well as the thermal frequency detuning of the RF structure at a maximum nominal power load of 3.6 kW, an extensive thermal and structural mechanical analysis using COMSOL Multiphysics was conducted. The water heating along the cooling channels as well as the properties of heat transfer from the copper structure to the cooling water were taken into account, which required CFD simulations of the cooling water flow in the turbulent regime. Here we present the methods and results of the sophisticated thermal and structural mechanical simulations using COMSOL and provide a comparison to more simplistic simulations conducted with CST Studio Suite.
We show that the implementation of the 1/c2 transverse current–current interaction between electrons resulting from the non-relativistic QED into the standard self-consistent electron BCS model in bulk under thermal equilibrium in the stable superconductive phase ensures the full compensation of a constant external magnetic field by the internal magnetic field created by the electrons, i.e. one has an ideal diamagnet.
Mixing and magnetic fields in asymptotic giant branch stars in the framework of FRUITY models
(2021)
In the last few years, the modeling of asymptotic giant branch (AGB) stars has been much investigated, both focusing on nucleosynthesis and stellar evolution aspects. Recent advances in the input physics required for stellar computations made it possible to construct more accurate evolutionary models, which are an essential tool to interpret the wealth of available observational and nucleosynthetic data. Motivated by such improvements, the FUNS stellar evolutionary code has been updated. Nonetheless, mixing processes occurring in AGB stars’ interiors are currently not well-understood. This is especially true for the physical mechanism leading to the formation of the 13C pocket, the major neutron source in low-mass AGB stars. In this regard, post-processing s-process models assuming that partial mixing of protons is induced by magneto-hydrodynamics processes were shown to reproduce many observations. Such mixing prescriptions have now been implemented in the FUNS code to compute stellar models with fully coupled nucleosynthesis. Here, we review the new generation of FRUITY models that include the effects of mixing triggered by magnetic fields by comparing theoretical findings with observational constraints available either from the isotopic analysis of trace-heavy elements in presolar grains or from carbon AGB stars and Galactic open clusters.
Vibrational energy transfer (VET) is essential for protein function. It is responsible for efficient energy dissipation in reaction sites, and has been linked to pathways of allosteric communication. While it is understood that VET occurs via backbone as well as via non-covalent contacts, little is known about the competition of these two transport channels, which determines the VET pathways. To tackle this problem, we equipped the β-hairpin fold of a tryptophan zipper with pairs of non-canonical amino acids, one serving as a VET injector and one as a VET sensor in a femtosecond pump probe experiment. Accompanying extensive non-equilibrium molecular dynamics simulations combined with a master equation analysis unravel the VET pathways. Our joint experimental/computational endeavor reveals the efficiency of backbone vs. contact transport, showing that even if cutting short backbone stretches of only 3 to 4 amino acids in a protein, hydrogen bonds are the dominant VET pathway.
Experimental and theoretical studies of fluctuations in nucleus-nucleus interactions at high energies have started to play a major role in understanding of the concept of strong interactions. The elaborated procedures have been developed to disentangle different processes happening during nucleus-nucleus collisions. The fluctuations caused by a variation of the number of nucleons which participated in a collision are frequently considered the unwanted one. The methods to reduce the impact of these fluctuations in fixed-target experiments are reviewed and tested. They can be of key importance in the following ongoing fixed-target heavy-ion experiments: NA61/SHINE at the CERN SPS, STAR-FXT at the BNL RHIC, BMN at JINR Nuclotron, HADES at the GSI SIS18 and in future experiments such as NA60+ at the CERN SPS, CBM at the FAIR SIS100, JHITS at J-PARC-HI MR.
We review the properties of the strongly interacting quark-gluon plasma (QGP) at finite temperature T and baryon chemical potential µB as created in heavy-ion collisions at ultrarelativistic energies. The description of the strongly interacting (non-perturbative) QGP in equilibrium is based on the effective propagators and couplings from the Dynamical QuasiParticle Model (DQPM) that is matched to reproduce the equation-of-state of the partonic system above the deconfinement temperature Tc from lattice QCD. Based on a microscopic transport description of heavy-ion collisions, we discuss which observables are sensitive to the QGP creation and its properties.
A deep convolutional neural network (CNN) is developed to study symmetry energy (Esym(ρ)) effects by learning the mapping between the symmetry energy and the two-dimensional (transverse momentum and rapidity) distributions of protons and neutrons in heavy-ion collisions. Supervised training is performed with labeled data-set from the ultrarelativistic quantum molecular dynamics (UrQMD) model simulation. It is found that, by using proton spectra on event-by-event basis as input, the accuracy for classifying the soft and stiff Esym(ρ) is about 60% due to large event-by-event fluctuations, while by setting event-summed proton spectra as input, the classification accuracy increases to 98%. The accuracies for 5-label (5 different Esym(ρ)) classification task are about 58% and 72% by using proton and neutron spectra, respectively. For the regression task, the mean absolute errors (MAE) which measure the average magnitude of the absolute differences between the predicted and actual L (the slope parameter of Esym(ρ)) are about 20.4 and 14.8 MeV by using proton and neutron spectra, respectively. Fingerprints of the density-dependent nuclear symmetry energy on the transverse momentum and rapidity distributions of protons and neutrons can be identified by convolutional neural network algorithm.
The deuteron coalescence parameter 𝐵2 in proton+proton and nucleus+nucleus collisions in the energy range of √s N N = 900–7000 GeV for proton + proton and √s N N = 2–2760 GeV for nucleus + nucleus collisions is analyzed with the Ultrarelativistic Quantum Molecular Dynamics (UrQMD) transport model, supplemented by an event-by-event phase space coalescence model for deuteron and anti-deuteron production. The results are compared to data by the E866, E877, PHENIX, STAR and ALICE experiments. The 𝐵2 values are calculated from the final spectra of protons and deuterons. At lower energies, √s N N ≤ 20 GeV, B2 drops drastically with increasing energy. The calculations confirm that this is due to the increasing freeze-out volume reflected in B2 ∼ 1/V . At higher energies, √s N N ≥ 20 GeV, B2 saturates at a constant level. This qualitative change and the vanishing of the volume suppression is shown to be due to the development of strong radial flow with increasing energy. The flow leads to strong space-momentum correlations which counteract the volume effect.
The β-barrel assembly machinery (BAM) consisting of the central β-barrel BamA and four other lipoproteins mediates the folding of the majority of the outer membrane proteins. BamA is placed in an asymmetric bilayer and its lateral gate is suggested to be the functional hotspot. Here we used in situ pulsed electron-electron double resonance spectroscopy to characterize BamA in the native outer membrane. In the detergent micelles, the data is consistent with mainly an inward-open conformation of BamA. The native membrane considerably enhanced the conformational heterogeneity. The lateral gate and the extracellular loop 3 exist in an equilibrium between different conformations. The outer membrane provides a favorable environment for occupying multiple conformational states independent of the lipoproteins. Our results reveal a highly dynamic behavior of the lateral gate and other key structural elements and provide direct evidence for the conformational modulation of a membrane protein in situ.
Geometrical frustration among interacting spins combined with strong quantum fluctuations destabilize long-range magnetic order in favor of more exotic states such as spin liquids. By following this guiding principle, a number of spin liquid candidate systems were identified in quasi-two-dimensional (quasi-2D) systems. For 3D, however, the situation is less favorable as quantum fluctuations are reduced and competing states become more relevant. Here we report a comprehensive study of thermodynamic, magnetic and dielectric properties on single crystalline and pressed-powder samples of PbCuTe2O6, a candidate material for a 3D frustrated quantum spin liquid featuring a hyperkagome lattice. Whereas the low-temperature properties of the powder samples are consistent with the recently proposed quantum spin liquid state, an even more exotic behavior is revealed for the single crystals. These crystals show ferroelectric order at TFE ≈ 1 K, accompanied by strong lattice distortions, and a modified magnetic response—still consistent with a quantum spin liquid—but with clear indications for quantum critical behavior.
Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments
(2021)
Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation–maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient. We test how well a dataset conforms to the assumptions of a diffusion model and determine the optimal number of subpopulations with the help of a quality factor of known analytical distribution. To facilitate use by practitioners, we provide a fast open-source implementation of the theory for the efficient analysis of multiple trajectories in arbitrary dimensions simultaneously.
Abstract
The primary immunological target of COVID-19 vaccines is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface and mediates viral entry into the host cell. To identify possible antibody binding sites, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation, and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for structure-based vaccine design. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics. The protective glycan shield and the high flexibility of its hinges give the stalk overall low epitope scores. Our computational epitope-mapping procedure is general and should thus prove useful for other viral envelope proteins whose structures have been characterized.
Author summary
The SARS-CoV-2 virus has caused a global health crisis. The spike protein exposed at its surface is key for infection and the primary antibody target. However, spike is covered by highly mobile glycan molecules that could impair antibody binding. To identify accessible epitopes, we performed molecular dynamics simulations of an atomistic model of glycosylated spike embedded in a membrane. By combining extensive simulations with bioinformatics analyses, we recovered known antibody binding sites and identified several epitope candidates as targets for further vaccine development.
As part of the research for this thesis, a momentum spectrometer was set up and initial measurements on accelerated ions were performed. For this purpose, the necessary hardware for the operation of the spectrometer and for high-precision measurements was were assembled. A control system for remote operation was developed and the spectrometer was installed at the used beamline.
There, measurements of low-energy ion beams in superposition with electrons confined in a Gabor lens can be carried out.
Investigations were made on both the Gabor lens-generated ions and the beam ions, leading to first results regarding the charge changes of beam ions during propagation through an electron atmosphere.
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150–350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma’s final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
During infection the SARS-CoV-2 virus fuses its viral envelope with cellular membranes of its human host. Initial contact with the host cell and membrane fusion are both mediated by the viral spike (S) protein. Proteolytic cleavage of S at the S2′ site exposes its 40 amino acid long fusion peptide (FP). Binding of the FP to the host membrane anchors the S2 domain of S in both the viral and the host membrane. The reorganization of S2 then pulls the two membranes together. Here we use molecular dynamics (MD) simulations to study the two core functions of the SARS-CoV-2 FP: to attach quickly to cellular membranes and to form an anchor strong enough to withstand the mechanical force during membrane fusion. In eight 10 μs-long MD simulations of FP in proximity to endosomal and plasma membranes, we find that FP binds spontaneously to the membranes and that binding proceeds predominantly by insertion of two short amphipathic helices into the membrane interface. Connected via a flexible linker, the two helices can bind the membrane independently, yet binding of one promotes the binding of the other by tethering it close to the target membrane. By simulating mechanical pulling forces acting on the C-terminus of the FP we then show that the bound FP can bear forces up to 250 pN before detaching from the membrane. This detachment force is more than ten-fold higher than an estimate of the force required to pull host and viral membranes together for fusion. We identify a fully conserved disulfide bridge in the FP as a major factor for the high mechanical stability of the FP membrane anchor. We conclude, first, that the sequential binding of two short amphipathic helices allows the SARS-CoV-2 FP to insert quickly into the target membrane, before the virion is swept away after shedding the S1 domain connecting it to the host cell receptor. Second, we conclude that the double attachment and the conserved disulfide bridge establish the strong anchoring required for subsequent membrane fusion. Multiple distinct membrane-anchoring elements ensure high avidity and high mechanical strength of FP-membrane binding.
Transport of lipids across membranes is fundamental for diverse biological pathways in cells. Multiple ion-coupled transporters participate in lipid translocation, but their mechanisms remain largely unknown. Major facilitator superfamily (MFS) lipid transporters play central roles in cell wall synthesis, brain development and function, lipids recycling, and cell signaling. Recent structures of MFS lipid transporters revealed overlapping architectural features pointing towards a common mechanism. Here we used cysteine disulfide trapping, molecular dynamics simulations, mutagenesis analysis, and transport assays in vitro and in vivo, to investigate the mechanism of LtaA, a proton-dependent MFS lipid transporter essential for lipoteichoic acids synthesis in the pathogen Staphylococcus aureus. We reveal that LtaA displays asymmetric lateral openings with distinct functional relevance and that cycling through outward- and inward-facing conformations is essential for transport activity. We demonstrate that while the entire amphipathic central cavity of LtaA contributes to lipid binding, its hydrophilic pocket dictates substrate specificity. We propose that LtaA catalyzes lipid translocation by a ‘trap-and-flip’ mechanism that might be shared among MFS lipid transporters.