pwc-archive/papers-with-abstracts huggingface dataset:
An Empirical Study on Display Ad Impression Viewability Measurements
Authors: Zhang Weinan, Pan Ye, Zhou Tianxiong, Wang Jun
Date: 2015-05-21 00:00:00
Tasks: Position

Display advertising normally charges advertisers for every single ad
impression. Specifically, if an ad in a webpage has been loaded in the browser,
an ad impression is counted. However, due to the position and size of the ad
slot, lots of ads are actually not viewed but still measured as impressions and
charged. These fraud ad impressions indeed undermine the efficacy of display
advertising. A perfect ad impression viewability measurement should match what
the user has really viewed with a short memory. In this paper, we conduct
extensive investigations on display ad impression viewability measurements on
dimensions of ad creative displayed pixel percentage and exposure time to find
which measurement provides the most accurate ad impression counting. The
empirical results show that the most accurate measurement counts one ad
impression if more than 75% of the ad creative pixels have been exposed for at
least 2 continuous seconds.
Inference of Ancestral Recombination Graphs through Topological Data Analysis
Date: 2016-07-27 00:00:00
Tasks: Topological Data Analysis

The recent explosion of genomic data has underscored the need for
interpretable and comprehensive analyses that can capture complex phylogenetic
relationships within and across species. Recombination, reassortment and
horizontal gene transfer constitute examples of pervasive biological phenomena
that cannot be captured by tree-like representations. Starting from hundreds of
genomes, we are interested in the reconstruction of potential evolutionary
histories leading to the observed data. Ancestral recombination graphs
represent potential histories that explicitly accommodate recombination and
mutation events across orthologous genomes. However, they are computationally
costly to reconstruct, usually being infeasible for more than few tens of
genomes. Recently, Topological Data Analysis (TDA) methods have been proposed
as robust and scalable methods that can capture the genetic scale and frequency
of recombination. We build upon previous TDA developments for detecting and
quantifying recombination, and present a novel framework that can be applied to
hundreds of genomes and can be interpreted in terms of minimal histories of
mutation and recombination events, quantifying the scales and identifying the
genomic locations of recombinations. We implement this framework in a software
package, called TARGet, and apply it to several examples, including small
migration between different populations, human recombination, and horizontal
evolution in finches inhabiting the Gal\'apagos Islands.
Optimizing the Information Retrieval Trade-off in Data Visualization Using $\alpha$-Divergence
Authors: Amid Ehsan, Dikmen Onur, Oja Erkki
Date: 2016-03-29 00:00:00
Tasks: Data Visualization, Dimensionality Reduction, Information Retrieval, Retrieval

Data visualization is one of the major applications of nonlinear
dimensionality reduction. From the information retrieval perspective, the
quality of a visualization can be evaluated by considering the extent that the
neighborhood relation of each data point is maintained while the number of
unrelated points that are retrieved is minimized. This property can be
quantified as a trade-off between the mean precision and mean recall of the
visualization. While there have been some approaches to formulate the
visualization objective directly as a weighted sum of the precision and recall,
there is no systematic way to determine the optimal trade-off between these two
nor a clear interpretation of the optimal value. In this paper, we investigate
the properties of $\alpha$-divergence for information visualization, focusing
our attention on a particular range of $\alpha$ values. We show that the
minimization of the new cost function corresponds to maximizing a geometric
mean between precision and recall, parameterized by $\alpha$. Contrary to some
earlier methods, no hand-tuning is needed, but we can rigorously estimate the
optimal value of $\alpha$ for a given input data. For this, we provide a
statistical framework using a novel distribution called Exponential Divergence
with Augmentation (EDA). By the extensive set of experiments, we show that the
optimal value of $\alpha$, obtained by EDA corresponds to the optimal trade-off
between the precision and recall for a given data distribution.
Combination of genetic crossover and replica-exchange method for conformational search of protein systems
Date: 2015-05-21 00:00:00

We combined the genetic crossover, which is one of the operations of genetic
algorithm, and replica-exchange method in parallel molecular dynamics
simulations. The genetic crossover and replica-exchange method can search the
global conformational space by exchanging the corresponding parts between a
pair of conformations of a protein. In this study, we applied this method to an
$\alpha$-helical protein, Trp-cage mini protein, which has 20 amino-acid
residues. The conformations obtained from the simulations are in good agreement
with the experimental results.
A Kolmogorov-Smirnov test for the molecular clock on Bayesian ensembles of phylogenies
Date: 2017-11-21 00:00:00
Tasks: Bayesian Inference

Divergence date estimates are central to understand evolutionary processes
and depend, in the case of molecular phylogenies, on tests of molecular clocks.
Here we propose two non-parametric tests of strict and relaxed molecular clocks
built upon a framework that uses the empirical cumulative distribution (ECD) of
branch lengths obtained from an ensemble of Bayesian trees and well known
non-parametric (one-sample and two-sample) Kolmogorov-Smirnov (KS)
goodness-of-fit test. In the strict clock case, the method consists in using
the one-sample Kolmogorov-Smirnov (KS) test to directly test if the phylogeny
is clock-like, in other words, if it follows a Poisson law. The ECD is computed
from the discretized branch lengths and the parameter $\lambda$ of the expected
Poisson distribution is calculated as the average branch length over the
ensemble of trees. To compensate for the auto-correlation in the ensemble of
trees and pseudo-replication we take advantage of thinning and effective sample
size, two features provided by Bayesian inference MCMC samplers. Finally, it is
observed that tree topologies with very long or very short branches lead to
Poisson mixtures and in this case we propose the use of the two-sample KS test
with samples from two continuous branch length distributions, one obtained from
an ensemble of clock-constrained trees and the other from an ensemble of
unconstrained trees. Moreover, in this second form the test can also be applied
to test for relaxed clock models. The use of a statistically equivalent
ensemble of phylogenies to obtain the branch lengths ECD, instead of one
consensus tree, yields considerable reduction of the effects of small sample
size and provides again of power.
Evolutionary graph theory revisited: general dynamics and the Moran process
Date: 2015-05-22 00:00:00

Evolution in finite populations is often modelled using the classical Moran
process. Over the last ten years this methodology has been extended to
structured populations using evolutionary graph theory. An important question
in any such population, is whether a rare mutant has a higher or lower chance
of fixating (the fixation probability) than the Moran probability, i.e. that
from the original Moran model, which represents an unstructured population. As
evolutionary graph theory has developed, different ways of considering the
interactions between individuals through a graph and an associated matrix of
weights have been considered, as have a number of important dynamics. In this
paper we revisit the original paper on evolutionary graph theory in light of
these extensions to consider these developments in an integrated way. In
particular we find general criteria for when an evolutionary graph with general
weights satisfies the Moran probability for the set of six common evolutionary
dynamics.
Genome-scale phylogenetic analysis finds extensive gene transfer among Fungi
Date: 2015-07-15 00:00:00

Although the role of lateral gene transfer is well recognized in the
evolution of bacteria, it is generally assumed that it has had less influence
among eukaryotes. To explore this hypothesis we compare the dynamics of genome
evolution in two groups of organisms: Cyanobacteria and Fungi. Ancestral
genomes are inferred in both clades using two types of methods. First, Count, a
gene tree unaware method that models gene duplications, gains and losses to
explain the observed numbers of genes present in a genome. Second, ALE, a more
recent gene tree-aware method that reconciles gene trees with a species tree
using a model of gene duplication, loss, and transfer. We compare their merits
and their ability to quantify the role of transfers, and assess the impact of
taxonomic sampling on their inferences. We present what we believe is
compelling evidence that gene transfer plays a significant role in the
evolution of Fungi.
Jarzynski-type equalities in gambling: role of information in capital growth
Date: 2015-08-18 00:00:00
Tasks: Vocal Bursts Type Prediction

We study the capital growth in gambling with (and without) side information
and memory effects. We derive several equalities for gambling, which are of
similar form to the Jarzynski equality and its extension to systems with
feedback controls. Those relations provide us with new measures to quantify the
effects of information on the statistics of capital growth in gambling. We
discuss the implications of the equalities and show that they reproduce the
known upper bounds of average capital growth rates.
Hydrogen bonds and asymmetrical heat diffusion in a-Helices. A Computational Analysis
Date: 2015-05-22 00:00:00

In this work, we report the heat rectifying capability of a-helices. Using
molecular dynamics simulations we show an increased thermal diffusivity in the
C-Terminal to N-Terminal direction of propagation. The origin of this effect
seems to be a function of the particular orientation of the hydrogen bonds
stabilizing these a-helices. Our results may be relevant for the design of
thermal rectification devices for materials science and lend support to the
role of normal length hydrogen bonds in the asymmetrical energy flow in
proteins.
Local Ranking Problem on the BrowseGraph
Authors: Trevisiol Michele, Aiello Luca Maria, Boldi Paolo, Blanco Roi
Date: 2015-05-23 00:00:00

The "Local Ranking Problem" (LRP) is related to the computation of a
centrality-like rank on a local graph, where the scores of the nodes could
significantly differ from the ones computed on the global graph. Previous work
has studied LRP on the hyperlink graph but never on the BrowseGraph, namely a
graph where nodes are webpages and edges are browsing transitions. Recently,
this graph has received more and more attention in many different tasks such as
ranking, prediction and recommendation. However, a web-server has only the
browsing traffic performed on its pages (local BrowseGraph) and, as a
consequence, the local computation can lead to estimation errors, which hinders
the increasing number of applications in the state of the art. Also, although
the divergence between the local and global ranks has been measured, the
possibility of estimating such divergence using only local knowledge has been
mainly overlooked. These aspects are of great interest for online service
providers who want to: (i) gauge their ability to correctly assess the
importance of their resources only based on their local knowledge, and (ii)
take into account real user browsing fluxes that better capture the actual user
interest than the static hyperlink network. We study the LRP problem on a
BrowseGraph from a large news provider, considering as subgraphs the
aggregations of browsing traces of users coming from different domains. We show
that the distance between rankings can be accurately predicted based only on
structural information of the local graph, being able to achieve an average
rank correlation as high as 0.8.
Cell-type-specific computational neuroanatomy, simulations from the sagittal and coronal Allen Brain Atlas
Date: 2015-05-24 00:00:00
Tasks: Specificity

The Allen Atlas of the adult mouse brain is a brain-wide, genome-wide data
set that has been made available online, triggering a renaissance in
neuroanatomy. In particular, it has been used to define brain regions in a
computational, data-driven way, and to estimate the region-specificity of cell
types characterized independently by their transcriptional activity. However,
these results were based on one series of co-registered (coronal) ISH image
series per gene, whereas the online ABA contains several image series per
genes, including sagittal ones. Since the sagittal series cover mostly the left
hemisphere, we can simulate the variability of results by repeatedly drawing a
random image series for each gene and restricting the computation to the left
hemisphere. This gives rise to an estimate of error bars on the results of
computational neuroanatomy.
Fundamental Limits to Cellular Sensing
Date: 2015-05-25 00:00:00

In recent years experiments have demonstrated that living cells can measure
low chemical concentrations with high precision, and much progress has been
made in understanding what sets the fundamental limit to the precision of
chemical sensing. Chemical concentration measurements start with the binding of
ligand molecules to receptor proteins, which is an inherently noisy process,
especially at low concentrations. The signaling networks that transmit the
information on the ligand concentration from the receptors into the cell have
to filter this noise extrinsic to the cell as much as possible. These networks,
however, are also stochastic in nature, which means that they will also add
noise to the transmitted signal. In this review, we will first discuss how the
diffusive transport and binding of ligand to the receptor sets the receptor
correlation time, and then how downstream signaling pathways integrate the
noise in the receptor state; we will discuss how the number of receptors, the
receptor correlation time, and the effective integration time together set a
fundamental limit on the precision of sensing. We then discuss how cells can
remove the receptor noise while simultaneously suppressing the intrinsic noise
in the signaling network. We describe why this mechanism of time integration
requires three classes of resources---receptors and their integration time,
readout molecules, energy---and how each resource class sets a fundamental
sensing limit. We also briefly discuss the scheme of maximum-likelihood
estimation, the role of receptor cooperativity, and how cellular copy protocols
differ from canonical copy protocols typically considered in the computational
literature, explaining why cellular sensing systems can never reach the
Landauer limit on the optimal trade-off between accuracy and energetic cost.
Simulating leaky integrate and fire neuron with integers
Date: 2015-05-25 00:00:00

The leaky integrate and fire (LIF) neuron represents standard neuronal model
used for numerical simulations. The leakage is implemented in the model as
exponential decay of trans-membrane voltage towards its resting value. This
makes inevitable the usage of machine floating point numbers in the course of
simulation. It is known that machine floating point arithmetic is subjected to
small inaccuracies, which prevent from exact comparison of floating point
quantities. In particular, it is incorrect to decide whether two separate in
time states of a simulated system composed of LIF neurons are exactly
identical. However, decision of this type is necessary, e.g. to figure periodic
dynamical regimes in a reverberating network. Here we offer a simulation
paradigm of a LIF neuron, in which neuronal states are described by whole
numbers. Within this paradigm, the LIF neuron behaves exactly the same way as
does the standard floating point simulated LIF, although exact comparison of
states becomes correctly defined.
A Survey on Retrieval of Mathematical Knowledge
Authors: Guidi F., Coen C. Sacerdoti
Date: 2015-06-28 00:00:00
Tasks: Retrieval, Survey

We present a short survey of the literature on indexing and retrieval of
mathematical knowledge, with pointers to 72 papers and tentative taxonomies of
both retrieval problems and recurring techniques.
PopED lite: an optimal design software for preclinical pharmacokinetic and pharmacodynamic studies
Date: 2015-05-25 00:00:00
Tasks: Drug Discovery, Experimental Design

Optimal experimental design approaches are seldom used in pre-clinical drug
discovery. Main reasons for this lack of use are that available software tools
require relatively high insight in optimal design theory, and that the
design-execution cycle of in vivo experiments is short, making time-consuming
optimizations infeasible. We present the publicly available software PopED lite
in order to increase the use of optimal design in pre-clinical drug discovery.
PopED lite is designed to be simple, fast and intuitive. Simple, to give many
users access to basic optimal design calculations. Fast, to fit the short
design-execution cycle and allow interactive experimental design (test one
design, discuss proposed design, test another design, etc). Intuitive, so that
the input to and output from the software can easily be understood by users
without knowledge of the theory of optimal design. In this way, PopED lite is
highly useful in practice and complements existing tools. Key functionality of
PopED lite is demonstrated by three case studies from real drug discovery
projects.
The Compositional Nature of Event Representations in the Human Brain
Date: 2015-05-25 00:00:00
Tasks: Classification

How does the human brain represent simple compositions of constituents:
actors, verbs, objects, directions, and locations? Subjects viewed videos
during neuroimaging (fMRI) sessions from which sentential descriptions of those
videos were identified by decoding the brain representations based only on
their fMRI activation patterns. Constituents (e.g., "fold" and "shirt") were
independently decoded from a single presentation. Independent constituent
classification was then compared to joint classification of aggregate concepts
(e.g., "fold-shirt"); results were similar as measured by accuracy and
correlation. The brain regions used for independent constituent classification
are largely disjoint and largely cover those used for joint classification.
This allows recovery of sentential descriptions of stimulus videos by composing
the results of the independent constituent classifiers. Furthermore,
classifiers trained on the words one set of subjects think of when watching a
video can recognise sentences a different subject thinks of when watching a
different video.
Seasonal Floquet states in a game-driven evolutionary dynamics
Date: 2015-08-12 00:00:00

Mating preferences of many biological species are not constant but
season-dependent. Within the framework of evolutionary game theory this can be
modeled with two finite opposite-sex populations playing against each other
following the rules that are periodically changing. By combining Floquet theory
and the concept of quasi-stationary distributions, we reveal existence of
metastable time-periodic states in the evolution of finite game-driven
populations. The evolutionary Floquet states correspond to time-periodic
probability flows in the strategy space which cannot be resolved within the
mean-field framework. The lifetime of metastable Floquet states increases with
the size $N$ of populations so that they become attractors in the limit $N
\rightarrow \infty$.
Seeing the Forest through the Trees: Adaptive Local Exploration of Large Graphs
Authors: Pienta Robert, Lin Zhiyuan, Kahng Minsuk, Vreeken Jilles, Talukdar Partha P., Abello James, Parameswaran Ganesh, Chau Duen Horng
Date: 2016-07-22 00:00:00

Visualization is a powerful paradigm for exploratory data analysis.
Visualizing large graphs, however, often results in a meaningless hairball. In
this paper, we propose a different approach that helps the user adaptively
explore large million-node graphs from a local perspective. For nodes that the
user investigates, we propose to only show the neighbors with the most
subjectively interesting neighborhoods. We contribute novel ideas to measure
this interestingness in terms of how surprising a neighborhood is given the
background distribution, as well as how well it fits the nodes the user chose
to explore. We introduce FACETS, a fast and scalable method for visually
exploring large graphs. By implementing our above ideas, it allows users to
look into the forest through its trees. Empirical evaluation shows that our
method works very well in practice, providing rankings of nodes that match
interests of users. Moreover, as it scales linearly, FACETS is suited for the
exploration of very large graphs.
Modulation of transforming growth factor beta signalling pathway genes by transforming growth factor beta in human osteoarthritic chondrocytes: involvement of Sp1 in both early and late response cells to transforming growth factor beta
Date: 2015-05-26 00:00:00

Transforming growth factor beta (TGF$\beta$) plays a central role in
morphogenesis, growth, and cell differentiation. This cytokine is particularly
important in cartilage where it regulates cell proliferation and extracellular
matrix synthesis. While the action of TGF$\beta$ on chondrocyte metabolism has
been extensively catalogued, the modulation of specific genes that function as
mediators of TGF$\beta$ signalling is poorly defined. In the current study,
elements of the Smad component of the TGF$\beta$ intracellular signalling
system and TGF$\beta$ receptors were characterised in human chondrocytes upon
TGF$\beta$1 treatment. Human articular chondrocytes were incubated with
TGF$\beta$1. Then, mRNA and protein levels of TGF$\beta$ receptors and Smads
were analysed by RT-PCR and western blot analysis. The role of specific protein
1 (Sp1) was investigated by gain and loss of function (inhibitor, siRNA,
expression vector). We showed that TGF$\beta$1 regulates mRNA levels of its own
receptors, and of Smad3 and Smad7. It modulates TGF$\beta$ receptors
post-transcriptionally by affecting their mRNA stability, but does not change
the Smad-3 and Smad-7 mRNA half-life span, suggesting a potential
transcriptional effect on these genes. Moreover, the transcriptional factor
Sp1, which is downregulated by TGF$\beta$1, is involved in the repression of
both TGF$\beta$ receptors but not in the modulation of Smad3 and Smad7.
Interestingly, Sp1 ectopic expression permitted also to maintain a similar
expression pattern to early response to TGF$\beta$ at 24 hours of treatment. It
restored the induction of Sox9 and COL2A1 and blocked the late response
(repression of aggrecan, induction of COL1A1 and COL10A1). These data help to
better understand the negative feedback loop in the TGF$\beta$ signalling
system, and enlighten an interesting role of Sp1 to regulate TGF$\beta$
response.