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Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory
Full text linkBecause of the intrinsic randomness of the evolutionary process, a mutant with a fitness advantage has some chance to be selected but no certainty. Any experiment that searches for advantageous mutants will lose many of them due to random drift. It is therefore of great interest to find population structures that improve the odds of advantageous mutants. Such structures are called amplifiers of natural selection: they increase the probability that advantageous mutants are selected. Arbitrarily strong amplifiers guarantee the selection of advantageous mutants, even for very small fitness advantage. Despite intensive research over the past decade, arbitrarily strong amplifiers have remained rare. Here we show how to construct a large variety of them. Our amplifiers are so simple that they could be useful in biotechnology, when optimizing biological molecules, or as a diagnostic tool, when searching for faster dividing cells or viruses. They could also occur in natural population structures
Design and characterization of methods and biological components to realize synthetic neurotransmission
No full textA major challenge in neuroscience research is to dissect the circuits that orchestrate behavior in health and disease. Proteins from a wide range of non-mammalian species, such as microbial opsins, have been successfully transplanted to specific neuronal targets to override their natural communication patterns. The goal of our work is to manipulate synaptic communication in a manner that closely incorporates the functional intricacies of synapses by preserving temporal encoding (i.e. the firing pattern of the presynaptic neuron) and connectivity (i.e. target specific synapses rather than specific neurons). Our strategy to achieve this goal builds on the use of non-mammalian transplants to create a synthetic synapse. The mode of modulation comes from pre-synaptic uptake of a synthetic neurotransmitter (SN) into synaptic vesicles by means of a genetically targeted transporter selective for the SN. Upon natural vesicular release, exposure of the SN to the synaptic cleft will modify the post-synaptic potential through an orthogonal ligand gated ion channel. To achieve this goal we have functionally characterized a mixed cationic methionine-gated ion channel from Arabidopsis thaliana, designed a method to functionally characterize a synthetic transporter in isolated synaptic vesicles without the need for transgenic animals, identified and extracted multiple prokaryotic uptake systems that are substrate specific for methionine (Met), and established a primary/cell line co-culture system that would allow future combinatorial testing of this orthogonal transmitter-transporter-channel trifecta.
Synthetic synapses will provide a unique opportunity to manipulate synaptic communication while maintaining the electrophysiological integrity of the pre-synaptic cell. In this way, information may be preserved that was generated in upstream circuits and that could be essential for concerted function and information processing
Ge hut wires - from growth to hole spin resonance
Full text linkNowadays, quantum computation is receiving more and more attention as an alternative to the classical way of computing. For realizing a quantum computer, different devices are investigated as potential quantum bits.
In this thesis, the focus is on Ge hut wires, which turned out to be promising candidates for implementing hole spin quantum bits. The advantages of Ge as a material system are
the low hyperfine interaction for holes and the strong spin orbit coupling, as well as the compatibility with the highly developed CMOS processes in industry. In addition, Ge can also be isotopically purified which is expected to boost the spin coherence times. The strong spin orbit interaction for holes in Ge on the one hand enables the full electrical control of the quantum bit and on the other hand should allow short spin manipulation times.
Starting with a bare Si wafer, this work covers the entire process reaching from growth over the fabrication and characterization of hut wire devices up to the demonstration
of hole spin resonance. From experiments with single quantum dots, a large g-factor anisotropy between the in-plane and the out-of-plane direction was found. A comparison to a theoretical model unveiled the heavy-hole character of the lowest energy states.
The second part of the thesis addresses double quantum dot devices, which were realized by adding two gate electrodes to a hut wire. In such devices, Pauli spin blockade was observed, which can serve as a read-out mechanism for spin quantum bits. Applying oscillating electric fields in spin blockade allowed the demonstration of continuous spin rotations and the extraction of a lower bound for the spin dephasing time. Despite the strong spin orbit coupling in Ge, the obtained value for the dephasing time is comparable
to what has been recently reported for holes in Si.
All in all, the presented results point out the high potential of Ge hut wires as a platform for long-lived, fast and fully electrically tunable hole spin quantum bits
Metamolds: Computational Design of Silicone Molds
Full text linkWe propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds. Metamolds automatically define the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require changing the shape or topology of the input objects, and only requires off-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detail
A germanium hole spin qubit
Full text linkHoles confined in quantum dots have gained considerable interest in the past few years due to their potential as spin qubits. Here we demonstrate two-axis control of a spin 3/2 qubit in natural Ge. The qubit is formed in a hut wire double quantum dot device. The Pauli spin blockade principle allowed us to demonstrate electric dipole spin resonance by applying a radio frequency electric field to one of the electrodes defining the double quantum dot. Coherent hole spin oscillations with Rabi frequencies reaching 140 MHz are demonstrated and dephasing times of 130 ns are measured. The reported results emphasize the potential of Ge as a platform for fast and electrically tunable hole spin qubit devices
Crosstalk in concurrent repeated games impedes direct reciprocity and requires stronger levels of forgiveness
Full text linkDirect reciprocity is a mechanism for cooperation among humans. Many of our daily interactions are repeated. We interact repeatedly with our family, friends, colleagues, members of the local and even global community. In the theory of repeated games, it is a tacit assumption that the various games that a person plays simultaneously have no effect on each other. Here we introduce a general framework that allows us to analyze "crosstalk" between a player's concurrent games. In the presence of crosstalk, the action a person experiences in one game can alter the person's decision in another. We find that crosstalk impedes the maintenance of cooperation and requires stronger levels of forgiveness. The magnitude of the effect depends on the population structure. In more densely connected social groups, crosstalk has a stronger effect. A harsh retaliator, such as Tit-for-Tat, is unable to counteract crosstalk. The crosstalk framework provides a unified interpretation of direct and upstream reciprocity in the context of repeated games
Real time analysis of auxin response cell wall pH and elongation in Arabidopsis thaliana Hypocotyls
Full text linkThe rapid auxin-triggered growth of the Arabidopsis hypocotyls involves the nuclear TIR1/AFB-Aux/IAA signaling and is accompanied by acidification of the apoplast and cell walls (Fendrych et al., 2016). Here, we describe in detail the method for analysis of the elongation and the TIR1/AFB-Aux/IAA-dependent auxin response in hypocotyl segments as well as the determination of relative values of the cell wall pH
Multiple Covers with Balls
Full text linkWe describe arrangements of three-dimensional spheres from a geometrical
and topological point of view. Real data (fitting this setup) often consist of soft spheres
which show certain degree of deformation while strongly packing against each other. In this
context, we answer the following questions: If we model a soft packing of spheres by hard
spheres that are allowed to overlap, can we measure the volume in the overlapped areas?
Can we be more specific about the overlap volume, i.e. quantify how much volume is there
covered exactly twice, three times, or times? What would be a good optimization criteria
that rule the arrangement of soft spheres while making a \emph{good} use of the available
space? Fixing a particular criterion, what would be the optimal sphere configuration?
The first result of this thesis are short formulas for the computation of
volumes covered by at least of the balls. The formulas exploit information contained
in the order- Voronoi diagrams and its closely related Level- complex. The used complexes
lead to a natural generalization into \emph{poset diagrams}, a theoretical formalism that
contains the order- and degree- diagrams as special cases. In parallel, we define
different criteria to determine what could be considered an optimal arrangement from a
geometrical point of view. Fixing a criterion, we find optimal soft packing configurations in 2D
and 3D where the ball centers lie on a lattice. As a last step, we use tools from computational
topology on real physical data, to show the potentials of higher-order diagrams in the description
of melting crystals. The results of the experiments leaves us with an open window to apply
the theories developed in this thesis in real applications
Learning Three-Dimensional Flow for Interactive Aerodynamic Design
Full text linkWe present a data-driven technique to instantly predict how fluid flows around various three-dimensional objects. Such simulation is useful for computational fabrication and engineering, but is usually computationally expensive since it requires solving the Navier-Stokes equation for many time steps. To accelerate the process, we propose a machine learning framework which predicts aerodynamic forces and velocity and pressure fields given a threedimensional shape input. Handling detailed free-form three-dimensional shapes in a data-driven framework is challenging because machine learning approaches usually require a consistent parametrization of input and output. We present a novel PolyCube maps-based parametrization that can be computed for three-dimensional shapes at interactive rates. This allows us to efficiently learn the nonlinear response of the flow using a Gaussian process regression. We demonstrate the effectiveness of our approach for the interactive design and optimization of a car body