979 research outputs found
Low Reynolds number hydrodynamics of asymmetric, oscillating dumbbell pairs
Active dumbbell suspensions constitute one of the simplest model system for
collective swimming at low Reynolds number. Generalizing recent work, we derive
and analyze stroke-averaged equations of motion that capture the effective
hydrodynamic far-field interaction between two oscillating, asymmetric
dumbbells in three space dimensions. Time-averaged equations of motion, as
those presented in this paper, not only yield a considerable speed-up in
numerical simulations, they may also serve as a starting point when deriving
continuum equations for the macroscopic dynamics of multi-swimmer suspensions.
The specific model discussed here appears to be particularly useful in this
context, since it allows one to investigate how the collective macroscopic
behavior is affected by changes in the microscopic symmetry of individual
swimmers.Comment: 10 pages, to appear in EPJ Special Topic
SuperCYPsPred - a web server for the prediction of cytochrome activity
Cytochrome P450 enzymes (CYPs)-mediated drug metabolism influences drug pharmacokinetics and results in adverse outcomes in patients through drug-drug interactions (DDIs). Absorption, distribution, metabolism, excretion and toxicity (ADMET) issues are the leading causes for the failure of a drug in the clinical trials. As details on their metabolism are known for just half of the approved drugs, a tool for reliable prediction of CYPs specificity is needed. The SuperCYPsPred web server is currently focused on five major CYPs isoenzymes, which includes CYP1A2, CYP2C19, CYP2D6, CYP2C9 and CYP3A4 that are responsible for more than 80% of the metabolism of clinical drugs. The prediction models for classification of the CYPs inhibition are based on well-established machine learning methods. The models were validated both on cross-validation and external validation sets and achieved good performance. The web server takes a 2D chemical structure as input and reports the CYP inhibition profile of the chemical for 10 models using different molecular fingerprints, along with confidence scores, similar compounds, known CYPs information of drugs-published in literature, detailed interaction profile of individual cytochromes including a DDIs table and an overall CYPs prediction radar chart (http://insilico-cyp.charite.de/SuperCYPsPred/).The web server does not require log in or registration and is free to use
Discharging dynamics of topological batteries
Topological constraints have long been known to provide efficient mechanisms
for localizing and storing energy across a range of length scales, from knots
in DNA to turbulent plasmas. Despite recent theoretical and experimental
progress on the preparation of topological states, the role of topology in the
discharging dynamics is not well understood. Here, we investigate robust
topological energy release protocols in two archetypal soft systems through
simulations of 238 knotted elastic fibers and 3D liquid crystals across a range
of different topologies. By breaking the elastic fiber or switching the liquid
crystal surface anchoring, such topological batteries can perform mechanical
work or drive fluid flows. Our study reveals topologically resonant states for
which energy release becomes superslow or superfast. Owing to their intrinsic
stability we expect such tunable topological batteries to have broad
applications to storage and directed release of energy in soft matter.Comment: 8 pages, 5 figures; references added, discussion extende
Non-analytic microscopic phase transitions and temperature oscillations in the microcanonical ensemble: An exactly solvable 1d-model for evaporation
We calculate exactly both the microcanonical and canonical thermodynamic
functions (TDFs) for a one-dimensional model system with piecewise constant
Lennard-Jones type pair interactions. In the case of an isolated -particle
system, the microcanonical TDFs exhibit (N-1) singular (non-analytic)
microscopic phase transitions of the formal order N/2, separating N
energetically different evaporation (dissociation) states. In a suitably
designed evaporation experiment, these types of phase transitions should
manifest themselves in the form of pressure and temperature oscillations,
indicating cooling by evaporation. In the presence of a heat bath (thermostat),
such oscillations are absent, but the canonical heat capacity shows a
characteristic peak, indicating the temperature-induced dissociation of the
one-dimensional chain. The distribution of complex zeros (DOZ) of the canonical
partition may be used to identify different degrees of dissociation in the
canonical ensemble.Comment: version accepted for publication in PRE, minor additions in the text,
references adde
Stationarity, soft ergodicity, and entropy in relativistic systems
Recent molecular dynamics simulations show that a dilute relativistic gas
equilibrates to a Juettner velocity distribution if ensemble velocities are
measured simultaneously in the observer frame. The analysis of relativistic
Brownian motion processes, on the other hand, implies that stationary
one-particle distributions can differ depending on the underlying
time-parameterizations. Using molecular dynamics simulations, we demonstrate
how this relativistic phenomenon can be understood within a deterministic model
system. We show that, depending on the time-parameterization, one can
distinguish different types of soft ergodicity on the level of the one-particle
distributions. Our analysis further reveals a close connection between time
parameters and entropy in special relativity. A combination of different
time-parameterizations can potentially be useful in simulations that combine
molecular dynamics algorithms with randomized particle creation, annihilation,
or decay processes.Comment: 4 page
Design, Manufacture and Measurement of three Permanent Magnet Dipoles for FASER Experiment
FASER, the ForwArd Search ExpeRiment, is designed to search for new, yet undiscovered, light and weakly-interacting particles and study the interactions of high-energy neutrinos. Three dipoles, one 1.5 m-long and the other two 1.0 m-long each, installed upstream of the ATLAS experiment at CERN, are required to achieve sufficient separation of pairs of oppositely charged, high-energy Standard Model particles originating from decays of new physics particles. The dipoles have an aperture of 200 mm in diameter and a required magnetic field at the centre ≥ 0.55 T. Due to tight space constraints, a design based on permanent magnet technology was proposed. This paper describes the design, manufacturing, assembly and magnetic measurement of these large Halbach array dipoles
A System for Series Magnetic Measurements of the LHC Main Quadrupoles
More than 400 twin aperture lattice quadrupoles are needed for the Large Hadron Collider (LHC) which is under construction at CERN. The main quadrupole is assembled with correction magnets in a common cryostat called the Short Straight Section (SSS). We plan to measure all SSS's in cold conditions with an unprecedented accuracy: integrated gradient of the field within 150 ppm, harmonics in a range of 1 to 5 ppm, magnetic axis of all elements within 0.1 mm and their field direction within 0.2 mrad. In this paper we describe the automatic measurement system that we have designed, built and calibrated. Based on the results obtained on the two first prototypes of the SSS's (SSS3 and SSS4) we show that this system meets all above requirements
Establishing the substantive interpretation of the GFP by considering evidence from research on personality disorders and Animal Personality
In research on individual differences, various structural models aim at providing a comprehensive description of personality. These models assume multiple, mostly independent personality dimensions. More recently, the so-called General Factor of Personality (GFP) has become a proliferous, but contentious, topic. The notion of the GFP is based on the observations that personality dimensions are not independent, but in fact show consistent inter-correlations, leading to a relevant proportion of shared variance among them (Figueredo et al., 2006). The GFP seems to capture the socially desirable ends of personality scales, and, in terms of the Big Five model, high-GFP individuals score relatively high on openness, conscientiousness, extraversion (mainly the sociability-facet), agreeableness, and emotional stability (Rushton and Irwing, 2009; van der Linden et al., 2010a). Some authors have suggested that the GFP simply reflects methodological artifacts (Ashton et al., 2009; Backstrom et al., 2009; Hopwood et al., 2011b; Pettersson et al., 2012). However, much of this criticism has been addressed (Rushton and Erdle, 2010; Loehlin, 2012; Dunkel and van der Linden, 2014; van der Linden et al., 2014a). The objective of the present work is not to reiterate these issues, as they have been discussed extensively elsewhere (Irwing, 2013; van der Linden et al., 2016). Instead, we contend that criticism mostly offered within the specialty of personality psychology misses the bigger picture. More specific, evidence in favor of the GFP as a substantive and theoretically coherent construct has been provided in other research fields long before it became a contentious issue in personality psychology. Here we introduce two lines of evidence that may further corroborate the substantive interpretation of the GFP, specifically, findings from personality pathology as well as from animal personality. Looking at the GFP from a different perspective may help to overcome the current debates within personality psychology. In the following we will first briefly introduce work on the GFP and its theoretical foundation as social effectiveness. Afterwards we outline research from psychiatric nosology and animal ecology and discuss these in context
Learning dynamical information from static protein and sequencing data
Many complex processes, from protein folding to neuronal network dynamics, can be described as stochastic exploration of a high-dimensional energy landscape. While efficient algorithms for cluster detection in high-dimensional spaces have been developed over the last two decades, considerably less is known about the reliable inference of state transition dynamics in such settings. Here, we introduce a flexible and robust numerical framework to infer Markovian transition networks directly from time-independent data sampled from stationary equilibrium distributions. We demonstrate the practical potential of the inference scheme by reconstructing the network dynamics for several protein folding transitions, gene-regulatory network motifs and HIV evolution pathways. The predicted network topologies and relative transition time scales agree well with direct estimates from time-dependent molecular dynamics data, stochastic simulations and phylogenetic trees, respectively. Owing to its generic structure, the framework introduced here will be applicable to high-throughput RNA and protein sequencing datasets and future cryo-electronmicroscopy data
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