72 research outputs found
Note on Discrete Gauge Anomalies
We consider the probem of gauging discrete symmetries. All valid constraints
on such symmetries can be understood in the low energy theory in terms of
instantons. We note that string perturbation theory often exhibits global
discrete symmetries, which are broken non-perturbatively.Comment: 9 page
Orthogonal Light-Dependent Membrane Adhesion Induces Social Self-Sorting and Member-Specific DNA Communication in Synthetic Cell Communities
Developing orthogonal chemical communication pathways in diverse synthetic cell communities is a considerable challenge due to the increased crosstalk and interference associated with large numbers of different types of sender-receiver pairs. Herein, the authors control which sender-receiver pairs communicate in a three-membered community of synthetic cells through red and blue light illumination. Semipermeable protein-polymer-based synthetic cells (proteinosomes) with complementary membrane-attached protein adhesion communicate through single-stranded DNA oligomers and synergistically process biochemical information within a community consisting of one sender and two different receiver populations. Different pairs of red and blue light-responsive protein-protein interactions act as membrane adhesion mediators between the sender and receivers such that they self-assemble and socially self-sort into different multicellular structures under red and blue light. Consequently, distinct sender-receiver pairs come into the signaling range depending on the light illumination and are able to communicate specifically without activation of the other receiver population. Overall, this work shows how photoswitchable membrane adhesion gives rise to different self-sorting protocell patterns that mediate member-specific DNA-based communication in ternary populations of synthetic cells and provides a step towards the design of orthogonal chemical communication networks in diverse communities of synthetic cells
Industry-scale application and evaluation of deep learning for drug target prediction
Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.Web of Science121art. no. 2
Dynamic scaling in the vicinity of the Luttinger liquid fixed point
We calculate the single-particle spectral function A (k, omega) of a
one-dimensional Luttinger liquid by means of a functional renormalization group
(RG) approach. Given an infrared energy cutoff Lambda = Lambda_0 e^{- l}, our
approach yields the spectral function in the scaling form, A_{\Lambda} (k_F +
p, omega) = tau Z_l tilde{A}_l (p xi, omega tau), where k_F is the Fermi
momentum, Z_l is the wave-function renormalization factor, tau = 1 / \Lambda is
the time scale and xi = v_F / \Lambda is the length scale associated with
Lambda. At the Luttinger liquid fixed point (l rightarrow infty) our RG result
for A (k, omega) exhibits the correct anomalous scaling properties, and for k =
\pm k_F agrees exactly with the well-known bosonization result at weak
coupling. Our calculation demonstrates that the field rescaling is essential
for obtaining the crossover from Fermi liquid behavior to Luttinger liquid
behavior from a truncation of the hierarchy of exact RG flow equations as the
infrared cutoff is reduced.Comment: 15 pages, 5 figure
Exact renormalization group flow equations for non-relativistic fermions: scaling towards the Fermi surface
We construct exact functional renormalization group (RG) flow equations for
non-relativistic fermions in arbitrary dimensions, taking into account not only
mode elimination but also the rescaling of the momenta, frequencies and the
fermionic fields. The complete RG flow of all relevant, marginal and irrelevant
couplings can be described by a system of coupled flow equations for the
irreducible n-point vertices. Introducing suitable dimensionless variables, we
obtain flow equations for generalized scaling functions which are continuous
functions of the flow parameter, even if we consider quantities which are
dominated by momenta close to the Fermi surface, such as the density-density
correlation function at long wavelengths. We also show how the problem of
constructing the renormalized Fermi surface can be reduced to the problem of
finding the RG fixed point of the irreducible two-point vertex at vanishing
momentum and frequency. We argue that only if the degrees of freedom are
properly rescaled it is possible to reach scale-invariant non-Fermi liquid
fixed points within a truncation of the exact RG flow equations.Comment: 20 Revtex pages, with 4 figures; final version to appear in Phys.
Rev. B; references and some explanations adde
Willing suspension of disbelief: a study in online learning through simulation, and its potential for deeper learning in Higher Education
This article describes the replacement of a 'traditionally taught' law of probate course (lectures and workshops/tutorials) with an on-line collaborative learning exercise using simulation and role-play which is referred to hereafter as the Transactional Learning Project ('TLP'). The article considers the theory that the emotional engagement that comes about through role play in simulation leads to deeper learning, a process Maharg (2010) has dubbed as the 'integration of the cognitive and the affective'. The article includes statistical analysis of student feedback on the TLP in an attempt to measure how easy it is to carry students predisposed to expect information to be 'given' rather than 'acquired' along the journey leading away from traditional didactic teaching. The project was motivated partly by the dearth of such learning practices on the Legal Practice Course. It is suggested that the findings of the project add to the body of research which tends to illustrate the success in terms of student learning from working in leaderless (i.e. where the tutor is absent from the collaborative group) groups engaged in practical tasks involving simulation
The BCN Challenge to Compatibilist Free Will and Personal Responsibility
Many philosophers ignore developments in the behavioral, cognitive, and neurosciences that purport to challenge our ideas of free will and responsibility. The reason for this is that the challenge is often framed as a denial of the idea that we are able to act differently than we do. However, most philosophers think that the ability to do otherwise is irrelevant to responsibility and free will. Rather it is our ability to act for reasons that is crucial. We argue that the scientific findings indicate that it is not so obvious that our views of free will and responsibility can be grounded in the ability to act for reasons without introducing metaphysical obscurities. This poses a challenge to philosophers. We draw the conclusion that philosophers are wrong not to address the recent scientific developments and that scientists are mistaken in formulating their challenge in terms of the freedom to do otherwise
The Electron Capture in Ho Experiment - a Short Update
The definition of the absolute neutrino mass scale is one of the main goals of the Particle Physics today. The study of the end-point regions of the ÎČ- and electron capture (EC) spectrum offers a possibility to determine the effective electron (anti-)neutrino mass in a completely model independent way, as it only relies on the energy and momentum conservation.
The ECHo (Electron Capture in 163Ho) experiment has been designed in the attempt to measure the effective mass of the electron neutrino by performing high statistics and high energy resolution measurements of the 163 Ho electron capture spectrum. To achieve this goal, large arrays of low temperature metallic magnetic calorimeters (MMCs) implanted with with 163Ho are used. Here we report on the structure and the status of the experiment
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