4,713 research outputs found
Endpoint resolvent estimates for compact Riemannian manifolds
We prove bounds for the resolvent of the Laplace-Beltrami
operator on a compact Riemannian manifold of dimension in the endpoint case
. It has the same behavior with respect to the spectral
parameter as its Euclidean analogue, due to Kenig-Ruiz-Sogge, provided a
parabolic neighborhood of the positive half-line is removed. This is region is
optimal, for instance, in the case of a sphere.Comment: 14 page
DeepOBS: A Deep Learning Optimizer Benchmark Suite
Because the choice and tuning of the optimizer affects the speed, and
ultimately the performance of deep learning, there is significant past and
recent research in this area. Yet, perhaps surprisingly, there is no generally
agreed-upon protocol for the quantitative and reproducible evaluation of
optimization strategies for deep learning. We suggest routines and benchmarks
for stochastic optimization, with special focus on the unique aspects of deep
learning, such as stochasticity, tunability and generalization. As the primary
contribution, we present DeepOBS, a Python package of deep learning
optimization benchmarks. The package addresses key challenges in the
quantitative assessment of stochastic optimizers, and automates most steps of
benchmarking. The library includes a wide and extensible set of ready-to-use
realistic optimization problems, such as training Residual Networks for image
classification on ImageNet or character-level language prediction models, as
well as popular classics like MNIST and CIFAR-10. The package also provides
realistic baseline results for the most popular optimizers on these test
problems, ensuring a fair comparison to the competition when benchmarking new
optimizers, and without having to run costly experiments. It comes with output
back-ends that directly produce LaTeX code for inclusion in academic
publications. It supports TensorFlow and is available open source.Comment: Accepted at ICLR 2019. 9 pages, 3 figures, 2 table
Surveying the SO(10) Model Landscape: The Left-Right Symmetric Case
Grand Unified Theories (GUTs) are a very well motivated extensions of the
Standard Model (SM), but the landscape of models and possibilities is
overwhelming, and different patterns can lead to rather distinct
phenomenologies. In this work we present a way to automatise the model building
process, by considering a top to bottom approach that constructs viable and
sensible theories from a small and controllable set of inputs at the high
scale. By providing a GUT scale symmetry group and the field content, possible
symmetry breaking paths are generated and checked for consistency, ensuring
anomaly cancellation, SM embedding and gauge coupling unification. We emphasise
the usefulness of this approach for the particular case of a non-supersymmetric
SO(10) model with an intermediate left-right symmetry and we analyse how
low-energy observables such as proton decay and lepton flavour violation might
affect the generated model landscape.Comment: 36 pages, 6 figure
Perturbing and imaging nuclear compartments to reveal mechanisms of transcription regulation and telomere maintenance
The cell nucleus is organized into functional domains that form around chromatin, which
serves as a scaffold composed of DNA, proteins, and associated RNAs. On the 0.1-1 µm
mesoscale these domains can form spatially defined compartments with distinct composition
and properties that enrich specific genomic activities like transcription, chromatin modification
or DNA repair. In addition, extrachromosomal DNA elements and RNAs can separate from the
chromatin template and assemble with proteins into nuclear bodies. The resulting
accumulations of proteins and nucleic acids in the nucleus modulate chromatin-templated
processes and their organization. The assembly of these compartments occurs in a self-organizing manner via direct and indirect binding of proteins to DNA and/or RNA. Recently, it
has been proposed that multivalent interactions drive compartmentalization by inducing phase
separation with a non-stoichiometric accumulation of factors into biomolecular condensates.
Despite the importance of compartments for genome regulation, insights into their structure
and material properties and how these affect their function is limited. To address this issue, it
is important to devise approaches that can perturb nuclear compartments in a targeted
manner, while also measuring changes in genome activities within the same cell. In this thesis,
the methodology to reveal the underlying structure-function relationships of nuclear
compartments has been advanced and applied to compartments involved in activation and
silencing of chromatin, and telomere maintenance in cancer cells.
I first established a toolbox of chromatin effector constructs to probe and perturb properties of
nuclear compartments in living cells that comprised different combinations of DNA binding,
transcription activation and light-dependent interaction domains. In addition, I developed
workflows to quantitatively assess relevant compartment features by fluorescence
microscopy. These methods were employed to study the compaction mechanism of mouse
pericentric heterochromatin (PCH) foci and to investigate the interplay between transcriptional
co-activators, phase separation and transcription at an inducible reporter gene cluster. It
revealed determinants of PCH compaction and identified differential co-activator usage and
multivalent interactions as contributors to transcription factor (TF) strength. The results
furthermore challenged the model of TF phase separation as a general positive driver of gene
transcription. In the second part, I focused on exploiting the detection of compartments for
measuring activity of the alternative lengthening of telomeres (ALT) pathway used by cancer
cells to extend their telomeres in absence of telomerase. I developed ALT-FISH, a scalable
and quantitative imaging assay that detects ALT pathway-specific compartments containing
large amounts of single-stranded telomeric nucleic acids. I applied the method to cell line
models from different cancer entities and to tumor tissue from leiomyosarcoma and
neuroblastoma patients. By devising automated ALT-FISH data acquisition and analysis
IV
workflows, I implemented an approach, which enabled ALT activity measurements in hundreds
of thousands of single cells. These technological advancements provided a quantitative
description of ALT activity at single cell resolution and were used to characterize the spatial
distribution of ALT activity in relation to other biological features and in response to
perturbations. Finally, a novel approach for studying the regulation of ALT in tumors could be
established by integrating the method with the spatially resolved detection of single cell
transcriptomes.
In summary, this thesis introduced and utilized several methods to establish connections
between nuclear compartment organization, chromatin features, transcription regulation, and
telomere maintenance. These perturbation and imaging techniques are versatile and may be
applied to dissect nuclear activities related to other compartments and biological model
systems. Furthermore, the detection of ALT activity has demonstrated that compartments can
offer valuable biological insights into how phenotypic cellular heterogeneity is encoded and
linked to diseases such as cancer
Probing weak dipole-dipole interaction using phase-modulated non-linear spectroscopy
Phase-modulated non-linear spectroscopy with higher harmonic demodulation has
recently been suggested to provide information on many-body excitations. In the
present work we theoretically investigate the application of this method to
infer the interaction strength between two particles that interact via weak
dipole-dipole interaction. To this end we use full numerical solution of the
Schr\"odinger equation with time-dependent pulses. For interpretation purpose
we also derive analytical expressions in perturbation theory. We find one can
detect dipole-dipole interaction via peak intensities (in contrast to
line-shifts which typically are used in conventional spectroscopy). We provide
a detailed study on the dependence of these intensities on the parameters of
the laser pulse and the dipole-dipole interaction strength. Interestingly, we
find that there is a phase between the first and second harmonic demodulated
signal, whose value depends on the sign of the dipole-dipole interaction.Comment: 12 pages, 8 figures, Supporting information provided with the source
file
Coherent multidimensional spectroscopy in the gas phase
Recent work applying multidimentional coherent electronic spectroscopy at
dilute samples in the gas phase is reviewed. The development of refined
phase-cycling approaches with improved sensitivity has opened-up new
opportunities to probe even dilute gas-phase samples. In this context, first
results of 2-dimensional spectroscopy performed at doped helium droplets reveal
the femtosecond dynamics upon electronic excitation of cold, weakly-bound
molecules, and even the induced dynamics from the interaction with the helium
environment. Such experiments, offering well-defined conditions at low
temperatures, are potentially enabling the isolation of fundamental processes
in the excitation and charge transfer dynamics of molecular structures which so
far have been masked in complex bulk environments.Comment: Invited Review Articl
Efficient deep CNNs for cross-modal automated computer vision under time and space constraints
We present an automated computer vision architecture to handle video and image data using the same backbone networks. We show empirical results that lead us to adopt MOBILENETV2 as this backbone architecture. The paper demonstrates that neural architectures are transferable from images to videos through suitable preprocessing and temporal information fusion
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