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(Open) Linked Data in Bibliotheken
Get PDFThis book is an introduction to the subjects of linked data, open data and open linked data, and to their specific relevance for libraries. It illustrates these concepts through detailed descriptions of actual data projects. The volume will be useful to individuals involved in library practice and those in library management who have not yet become familiarized with these important contemporary fields
Optical control of ligand-gated ion channels
Get PDFIn the vibrant field of optogenetics, optics and genetic targeting are combined to commandeer cellular functions, such as the neuronal action potential, by optically stimulating light-sensitive ion channels expressed in the cell membrane. One broadly applicable manifestation of this approach are covalently attached photochromic tethered ligands (PTLs) that allow activating ligand-gated ion channels with outstanding spatial and temporal resolution. Here, we describe all steps towards the successful development and application of PTL-gated ion channels in cell lines and primary cells. The basis for these experiments forms a combination of molecular modeling, genetic engineering, cell culture, and electrophysiology. The light-gated glutamate receptor (LiGluR), which consists of the PTL-functionalized GluK2 receptor, serves as a model
The supervised IBP: Neighbourhood preserving infinite latent feature models
Get PDFWe propose a probabilistic model to infer
supervised latent variables in the Hamming
space from observed data. Our model allows simultaneous inference of the number
of binary latent variables, and their values.
The latent variables preserve neighbourhood
structure of the data in a sense that objects
in the same semantic concept have similar
latent values, and objects in di*erent concepts have dissimilar latent values. We formulate the supervised in*nite latent variable
problem based on an intuitive principle of
pulling objects together if they are of the
same type, and pushing them apart if they
are not. We then combine this principle with
a exible Indian Bu*et Process prior on the
latent variables. We show that the inferred
supervised latent variables can be directly
used to perform a nearest neighbour search
for the purpose of retrieval. We introduce
a new application of dynamically extending
hash codes, and show how to e*ectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving in*nite latent feature space
Can quantitative and population genetics help us understand evolutionary computation?
No full textEven though both population and quantitative genetics, and evolutionary computation, deal with the same questions, they have developed largely independently of each other. I review key results from each field, emphasising those that apply independently of the (usually unknown) relation between genotype and phenotype. The infinitesimal model provides a simple framework for predicting the response of complex traits to selection, which in biology has proved remarkably successful. This allows one to choose the schedule of population sizes and selection intensities that will maximise the response to selection, given that the total number of individuals realised, C = ∑t Nt, is constrained. This argument shows that for an additive trait (i.e., determined by the sum of effects of the genes), the optimum population size and the maximum possible response (i.e., the total change in trait mean) are both proportional to √C
Highly adaptive liquid simulations on tetrahedral meshes
Get PDFWe introduce a new method for efficiently simulating liquid with extreme amounts of spatial adaptivity. Our method combines several key components to drastically speed up the simulation of large-scale fluid phenomena: We leverage an alternative Eulerian tetrahedral mesh discretization to significantly reduce the complexity of the pressure solve while increasing the robustness with respect to element quality and removing the possibility of locking. Next, we enable subtle free-surface phenomena by deriving novel second-order boundary conditions consistent with our discretization. We couple this discretization with a spatially adaptive Fluid-Implicit Particle (FLIP) method, enabling efficient, robust, minimally-dissipative simulations that can undergo sharp changes in spatial resolution while minimizing artifacts. Along the way, we provide a new method for generating a smooth and detailed surface from a set of particles with variable sizes. Finally, we explore several new sizing functions for determining spatially adaptive simulation resolutions, and we show how to couple them to our simulator. We combine each of these elements to produce a simulation algorithm that is capable of creating animations at high maximum resolutions while avoiding common pitfalls like inaccurate boundary conditions and inefficient computation
Evolutionary interactions between haemagglutinin and neuraminidase in avian influenza
Get PDFBackground: Reassortment between the RNA segments encoding haemagglutinin (HA) and neuraminidase (NA), the major antigenic influenza proteins, produces viruses with novel HA and NA subtype combinations and has preceded the emergence of pandemic strains. It has been suggested that productive viral infection requires a balance in the level of functional activity of HA and NA, arising from their closely interacting roles in the viral life cycle, and that this functional balance could be mediated by genetic changes in the HA and NA. Here, we investigate how the selective pressure varies for H7 avian influenza HA on different NA subtype backgrounds. Results: By extending Bayesian stochastic mutational mapping methods to calculate the ratio of the rate of non-synonymous change to the rate of synonymous change (d N/d S), we found the average d N/d S across the avian influenza H7 HA1 region to be significantly greater on an N2 NA subtype background than on an N1, N3 or N7 background. Observed differences in evolutionary rates of H7 HA on different NA subtype backgrounds could not be attributed to underlying differences between avian host species or virus pathogenicity. Examination of d N/d S values for each subtype on a site-by-site basis indicated that the elevated d N/d S on the N2 NA background was a result of increased selection, rather than a relaxation of selective constraint. Conclusions: Our results are consistent with the hypothesis that reassortment exposes influenza HA to significant changes in selective pressure through genetic interactions with NA. Such epistatic effects might be explicitly accounted for in future models of influenza evolution
How Free is Your Linearizable Concurrent Data Structure?
Get PDFLinearizability requires that the outcome of calls by competing threads to a concurrent data structure is the same as some sequential execution where each thread has exclusive access to the data structure. In an ordered data structure, such as a queue or a stack, linearizability is ensured by requiring threads commit in the order dictated by the sequential semantics of the data structure; e.g., in a concurrent queue implementation a dequeue can only remove the oldest element.
In this paper, we investigate the impact of this strict ordering, by comparing what linearizability allows to what existing implementations do. We first give an operational definition for linearizability which allows us to build the most general linearizable implementation as a transition system for any given sequential specification. We then use this operational definition to categorize linearizable implementations based on whether they are bound or free. In a bound implementation, whenever all threads observe the same logical state, the updates to the logical state and the temporal order of commits coincide. All existing queue implementations we know of are bound. We then proceed to present, to the best of our knowledge, the first ever free queue implementation. Our experiments show that free implementations have the potential for better performance by suffering less from contention
Technical requirements and features
Get PDFThis document is created as a part of the project “Repository for Research Data at IST Austria”. It summarises the mandatory features, which need to be fulfilled to provide an institutional repository as a platform and also a service to the scientists at the institute. It also includes optional features, which would be of strong benefit for the scientists and would increase the usage of the repository, and hence the visibility of research at IST Austria
Automatic Generation of Alternative Starting Positions for Traditional Board Games
Get PDFBoard games, like Tic-Tac-Toe and CONNECT-4, play an important role not only in
development of mathematical and logical skills,
but also in emotional and social development. In this paper, we address the problem of generating
targeted starting positions for such games. This can facilitate new approaches
for bringing novice players to mastery, and also leads to discovery of interesting game variants.
Our approach generates starting states of varying hardness
levels for player~ in a two-player board game, given rules of the board game,
the desired number of steps required for player~ to win,
and the expertise levels of the two players.
Our approach leverages symbolic methods and iterative simulation to
efficiently search the extremely large state space.
We present experimental results that include discovery of states of varying hardness levels
for several simple grid-based board games. Also, the presence of such states for standard game variants like
Tic-Tac-Toe on board size opens up new games to be played
that have not been played for ages since the default start state is heavily biased