2,266 research outputs found
RLZAP: Relative Lempel-Ziv with Adaptive Pointers
Relative Lempel-Ziv (RLZ) is a popular algorithm for compressing databases of
genomes from individuals of the same species when fast random access is
desired. With Kuruppu et al.'s (SPIRE 2010) original implementation, a
reference genome is selected and then the other genomes are greedily parsed
into phrases exactly matching substrings of the reference. Deorowicz and
Grabowski (Bioinformatics, 2011) pointed out that letting each phrase end with
a mismatch character usually gives better compression because many of the
differences between individuals' genomes are single-nucleotide substitutions.
Ferrada et al. (SPIRE 2014) then pointed out that also using relative pointers
and run-length compressing them usually gives even better compression. In this
paper we generalize Ferrada et al.'s idea to handle well also short insertions,
deletions and multi-character substitutions. We show experimentally that our
generalization achieves better compression than Ferrada et al.'s implementation
with comparable random-access times
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A cortical-spinal prosthesis for targeted limb movement in paralyzed primate avatars
Motor paralysis is among the most disabling aspects of injury to the central nervous system. Here we develop and test a target-based cortical-spinal neural prosthesis that employs neural activity recorded from pre-motor neurons to control limb movements in functionally paralyzed primate avatars. Given the complexity by which muscle contractions are naturally controlled, we approach the problem of eliciting goal-directed limb movement in paralyzed animals by focusing on the intended targets of movement rather than their intermediate trajectories. We then match this information in real-time with spinal cord and muscle stimulation parameters that produce free planar limb movements to those intended target locations. We demonstrate that both the decoded activities of pre-motor populations and their adaptive responses can be used, after brief training, to effectively direct an avatar’s limb to distinct targets variably displayed on a screen. These findings advance the future possibility of reconstituting targeted limb movement in paralyzed subjects
A stochastic spectral analysis of transcriptional regulatory cascades
The past decade has seen great advances in our understanding of the role of
noise in gene regulation and the physical limits to signaling in biological
networks. Here we introduce the spectral method for computation of the joint
probability distribution over all species in a biological network. The spectral
method exploits the natural eigenfunctions of the master equation of
birth-death processes to solve for the joint distribution of modules within the
network, which then inform each other and facilitate calculation of the entire
joint distribution. We illustrate the method on a ubiquitous case in nature:
linear regulatory cascades. The efficiency of the method makes possible
numerical optimization of the input and regulatory parameters, revealing design
properties of, e.g., the most informative cascades. We find, for threshold
regulation, that a cascade of strong regulations converts a unimodal input to a
bimodal output, that multimodal inputs are no more informative than bimodal
inputs, and that a chain of up-regulations outperforms a chain of
down-regulations. We anticipate that this numerical approach may be useful for
modeling noise in a variety of small network topologies in biology
Exploring ecosystem markets for the delivery of public goods in the UK
Environmental restoration and conservation challenges go beyond what can be financed publicly. There are significant opportunities for private investment in the delivery of public goods, benefitting both commercial organisations whose business relies on ecosystem services, as well as landowners, land managers and the general public. Thus, public-private financing of natural capital improvement presents an opportunity to increase the availability of funding for payments for ecosystem services that provide environmental and societal benefits. Though public-private partnerships for the financing of ecosystem services is in its infancy in the UK.
This new report explores the voluntary ecosystem services market in the UK. This is achieved by developing an understanding of how key actors (schemes, stakeholder engagement initiatives, trading platforms and supporting modelling tools) operate, and by identifying possible synergies, examples of good practice and challenges to implementation. Topics covered include, understanding how the identified actors account for the social distribution of ecosystem services, how values are attributed to ecosystem services, and the legal obligations linked to ventures’ operation
A statistical method for revealing form-function relations in biological networks
Over the past decade, a number of researchers in systems biology have sought
to relate the function of biological systems to their network-level
descriptions -- lists of the most important players and the pairwise
interactions between them. Both for large networks (in which statistical
analysis is often framed in terms of the abundance of repeated small subgraphs)
and for small networks which can be analyzed in greater detail (or even
synthesized in vivo and subjected to experiment), revealing the relationship
between the topology of small subgraphs and their biological function has been
a central goal. We here seek to pose this revelation as a statistical task,
illustrated using a particular setup which has been constructed experimentally
and for which parameterized models of transcriptional regulation have been
studied extensively. The question "how does function follow form" is here
mathematized by identifying which topological attributes correlate with the
diverse possible information-processing tasks which a transcriptional
regulatory network can realize. The resulting method reveals one form-function
relationship which had earlier been predicted based on analytic results, and
reveals a second for which we can provide an analytic interpretation. Resulting
source code is distributed via http://formfunction.sourceforge.net.Comment: To appear in Proc. Natl. Acad. Sci. USA. 17 pages, 9 figures, 2
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Reconciling and Validating the Ashworth-Davies Doppler Shifts of a Translating Mirror
We simplify the Ashworth-Davies special relativistic theory of a uniformly
translating mirror with an arbitrary angle of incidence and direction of
propagation in the non-relativistic limit. We show that it is in good agreement
with a more intuitive derivation that only considers the constancy of the speed
of light. We confirm the theory with phase-insensitive frequency measurements
using a liquid crystal light valve
Dynamic Fluctuation Phenomena in Double Membrane Films
Dynamics of double membrane films is investigated in the long-wavelength
limit including the overdamped squeezing mode. We demonstrate that thermal
fluctuations essentially modify the character of the mode due to its nonlinear
coupling to the transversal shear hydrodynamic mode. The corresponding Green
function acquires as a function of the frequency a cut along the imaginary
semi-axis. Fluctuations lead to increasing the attenuation of the squeezing
mode it becomes larger than the `bare' value.Comment: 7 pages, Revte
Phase Retrieval of Vortices in Bose-Einstein Condensates
We propose and demonstrate numerically a measurement scheme for complete
reconstruction of the quantum wavefunctions of Bose-Einstein condensates,
amplitude and phase, from a time of flight measurement. We identify a
fundamental ambiguity present in the measurement of vortices and show how to
overcome it by augmenting the measurement to allow reconstruction of
matter-wave vortices and arrays of vortices
On the Inability of Markov Models to Capture Criticality in Human Mobility
We examine the non-Markovian nature of human mobility by exposing the
inability of Markov models to capture criticality in human mobility. In
particular, the assumed Markovian nature of mobility was used to establish a
theoretical upper bound on the predictability of human mobility (expressed as a
minimum error probability limit), based on temporally correlated entropy. Since
its inception, this bound has been widely used and empirically validated using
Markov chains. We show that recurrent-neural architectures can achieve
significantly higher predictability, surpassing this widely used upper bound.
In order to explain this anomaly, we shed light on several underlying
assumptions in previous research works that has resulted in this bias. By
evaluating the mobility predictability on real-world datasets, we show that
human mobility exhibits scale-invariant long-range correlations, bearing
similarity to a power-law decay. This is in contrast to the initial assumption
that human mobility follows an exponential decay. This assumption of
exponential decay coupled with Lempel-Ziv compression in computing Fano's
inequality has led to an inaccurate estimation of the predictability upper
bound. We show that this approach inflates the entropy, consequently lowering
the upper bound on human mobility predictability. We finally highlight that
this approach tends to overlook long-range correlations in human mobility. This
explains why recurrent-neural architectures that are designed to handle
long-range structural correlations surpass the previously computed upper bound
on mobility predictability
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