pwc-archive/papers-with-abstracts huggingface dataset:
Developing Knowledge States: Technology and the Enhancement of National Statistical Capacity
Date: 2015-02-26 00:00:00

National statistical systems are the enterprises tasked with collecting,
validating and reporting societal attributes. These data serve many purposes -
they allow governments to improve services, economic actors to traverse
markets, and academics to assess social theories. National statistical systems
vary in quality, especially in developing countries. This study examines
determinants of national statistical capacity in developing countries, focusing
on the impact of general purpose technologies (GPTs). Just as technological
progress helps to explain differences in economic growth, states with markets
with greater technological attainment (specifically, general purpose
technologies) arguably have greater capacity for gathering and processing
quality data. Analysis using panel methods shows a strong, statistically
significant positive linear relationship between GPTs and national statistical
capacity. There is no evidence to support a non-linear function in this
relationship. Which is to say, there does not appear to be a marginal
depreciating National Statistical Capacity benefit associated with increases in
GPTs.
Gene-Mating Dynamic Evolution Theory II: Global stability of N-gender-mating polyploid systems
Date: 2020-01-13 00:00:00

Extending the previous 2-gender dioecious diploid gene-mating evolution model
[arXiv:1410.3456], we attempt to answer "whether the Hardy-Weinberg global
stability and the exact analytic dynamical solutions can be found in the
generalized N-gender N-polyploid gene-mating system with an arbitrary number of
alleles?" For a 2-gender gene-mating evolution model, a pair of male and female
determines the trait of their offspring. Each of the pair contributes one
inherited character, the allele, to combine into the genotype of their
offspring. Hence, for an N-gender N-polypoid gene-mating model, each of N
different genders contributes one allele to combine into the genotype of their
offspring. We exactly solve the analytic solution of N-gender-mating
$(n+1)$-alleles governing highly-nonlinear coupled differential equations in
the genotype frequency parameter space for any positive integer N and $n$. For
an analogy, the 2-gender to N-gender gene-mating equation generalization is
analogs to the 2-body collision to the N-body collision Boltzmann equations
with continuous distribution functions of "discretized" variables instead of
"continuous" variables. We find their globally stable solution as a continuous
manifold and find no chaos. Our solution implies that the Laws of Nature, under
our assumptions, provide no obstruction and no chaos to support an N-gender
gene-mating stable system.
Escape path complexity and its context dependency in Pacific blue-eyes (Pseudomugil signifer)
Date: 2015-02-26 00:00:00

The escape trajectories animals take following a predatory attack appear to
show high degrees of apparent 'randomness' - a property that has been described
as 'protean behaviour'. Here we present a method of quantifying the escape
trajectories of individual animals using a path complexity approach. When fish
(Pseudomugil signifer) were attacked either on their own or in groups, we find
that an individual's path rapidly increases in entropy (our measure of
complexity) following the attack. For individuals on their own, this entropy
remains elevated (indicating a more random path) for a sustained period (10
seconds) after the attack, whilst it falls more quickly for individuals in
groups. The entropy of the path is context dependent. When attacks towards
single fish come from greater distances, a fish's path shows less complexity
compared to attacks that come from short range. This context dependency effect
did not exist, however, when individuals were in groups. Nor did the path
complexity of individuals in groups depend on a fish's local density of
neighbours. We separate out the components of speed and direction changes to
determine which of these components contributes to the overall increase in path
complexity following an attack. We found that both speed and direction measures
contribute similarly to an individual's path's complexity in absolute terms.
Our work highlights the adaptive behavioural tactics that animals use to avoid
predators and also provides a novel method for quantifying the escape
trajectories of animals.
Phen-Gen: combining phenotype and genotype to analyze rare disorders
Date: 2015-02-27 00:00:00

We introduce Phen-Gen, a method which combines patient disease symptoms and
sequencing data with prior domain knowledge to identify the causative gene(s)
for rare disorders.
A Study of N-Acetyl aspartic acid/Creatine Ratio in the White Matter of HIV Positive Patients and Its Application
Date: 2015-02-27 00:00:00

A total of 50 patients were enrolled in the study, and MRI brain with MR
spectroscopy was done. Tuberculosis was the most common neurologic disease
found in the HIV positive group, consisting of 9 patients. Seven of these
patients had tuberculous meningitis amongst which a further 2 had vasculitic
infarcts.PML was seen in 6 patients. NAA to Cr ratio was found to be reduced in
all the patients, and in fact the value was further reduced compared to the HIV
positive group as a whole. Raised choline and myoInositol peaks were also found
in all the patients. MR Spectroscopy showed lipid lactate peaks confirming the
diagnosis. 2 patients had HIV encephalopathy on the imaging study. Their
spectra also revealed lowered NAA peaks along with raised choline peaks. 2
patients with cryptococcosis showed characteristic imaging finding of enlarged
Virchow Robin (perivascular) spaces. They revealed elevated choline peaks in
addition to reduced NAA. The values of NAA to Cr ratio were determined after
duly processing the spectroscopic data from both cases and controls. Each group
(Cases and controls) were divided on the basis of age into two age groups:
Lesser than or equal to 40 years, and greater than 40 years. In all three
groups the values of the mean NAA to Cr ratio ratio was significantly (p-value
less than 0.05) reduced in comparison to controls. An ancillary finding was the
reduction of NAA to Cr ratio further in cases of PML. Combined use of both the
conventional and advanced MRI sequences is advisable as spectroscopy helps in
confirming the diagnosis of opportunistic infection of the CNS in HIV positive
patients. NAA to Cr ratio ratio is reduced in HIV positive patients and is a
marker for HIV infection of the brain even in the absence of imaging findings
of HIV encephalopathy or when the patient is symptomatic due to neurological
disease of other etiologies.
Closed Form Jitter Analysis of Neuronal Spike Trains
Date: 2015-02-27 00:00:00
Tasks: Form

Interval jitter and spike resampling methods are used to analyze the time
scale on which temporal correlations occur. They allow the computation of
jitter corrected cross correlograms and the performance of an associated
statistically robust hypothesis test to decide whether observed correlations at
a given time scale are significant. Currently used Monte Carlo methods
approximate the probability distribution of coincidences. They require
generating $N_{\rm MC}$ simulated spike trains of length $T$ and calculating
their correlation with another spike train up to lag $\tau_{\max}$. This is
computationally costly $O(N_{\rm MC} \times T \times \tau_{\max})$ and it
introduces errors in estimating the $p$ value. Instead, we propose to compute
the distribution in closed form, with a complexity of $O(C_{\max}
\log(C_{\max}) \tau_{\max})$, where $C_{\max}$ is the maximum possible number
of coincidences. All results are then exact rather than approximate, and as a
consequence, the $p$-values obtained are the theoretically best possible for
the available data and test statistic. In addition, simulations with realistic
parameters predict a speed increase over Monte Carlo methods of two orders of
magnitude for hypothesis testing, and four orders of magnitude for computing
the full jitter-corrected cross correlogram.
Document Clustering using K-Means and K-Medoids
Authors: Balabantaray Rakesh Chandra, Sarma Chandrali, Jha Monica
Date: 2015-02-27 00:00:00
Tasks: Clustering, Document Summarization, Sentence

With the huge upsurge of information in day-to-days life, it has become
difficult to assemble relevant information in nick of time. But people, always
are in dearth of time, they need everything quick. Hence clustering was
introduced to gather the relevant information in a cluster. There are several
algorithms for clustering information out of which in this paper, we accomplish
K-means and K-Medoids clustering algorithm and a comparison is carried out to
find which algorithm is best for clustering. On the best clusters formed,
document summarization is executed based on sentence weight to focus on key
point of the whole document, which makes it easier for people to ascertain the
information they want and thus read only those documents which is relevant in
their point of view.
Differential protein expression and peak selection in mass spectrometry data by binary discriminant analysis
Date: 2015-05-27 00:00:00
Tasks: Drug Discovery

Motivation: Proteomic mass spectrometry analysis is becoming routine in
clinical diagnostics, for example to monitor cancer biomarkers using blood
samples. However, differential proteomics and identification of peaks relevant
for class separation remains challenging.
  Results: Here, we introduce a simple yet effective approach for identifying
differentially expressed proteins using binary discriminant analysis. This
approach works by data-adaptive thresholding of protein expression values and
subsequent ranking of the dichotomized features using a relative entropy
measure. Our framework may be viewed as a generalization of the `peak
probability contrast' approach of Tibshirani et al. (2004) and can be applied
both in the two-group and the multi-group setting.
  Our approach is computationally inexpensive and shows in the analysis of a
large-scale drug discovery test data set equivalent prediction accuracy as a
random forest. Furthermore, we were able to identify in the analysis of mass
spectrometry data from a pancreas cancer study biological relevant and
statistically predictive marker peaks unrecognized in the original study.
  Availability: The methodology for binary discriminant analysis is implemented
in the R package binda, which is freely available under the GNU General Public
License (version 3 or later) from CRAN at URL
http://cran.r-project.org/web/packages/binda/ . R scripts reproducing all
described analyzes are available from the web page
http://strimmerlab.org/software/binda/ .
Measures of Systemic Risk
Date: 2016-10-13 00:00:00

Systemic risk refers to the risk that the financial system is susceptible to
failures due to the characteristics of the system itself. The tremendous cost
of systemic risk requires the design and implementation of tools for the
efficient macroprudential regulation of financial institutions. The current
paper proposes a novel approach to measuring systemic risk.
  Key to our construction is a rigorous derivation of systemic risk measures
from the structure of the underlying system and the objectives of a financial
regulator. The suggested systemic risk measures express systemic risk in terms
of capital endowments of the financial firms. Their definition requires two
ingredients: a cash flow or value model that assigns to the capital allocations
of the entities in the system a relevant stochastic outcome; and an
acceptability criterion, i.e. a set of random outcomes that are acceptable to a
regulatory authority. Systemic risk is measured by the set of allocations of
additional capital that lead to acceptable outcomes. We explain the conceptual
framework and the definition of systemic risk measures, provide an algorithm
for their computation, and illustrate their application in numerical case
studies.
  Many systemic risk measures in the literature can be viewed as the minimal
amount of capital that is needed to make the system acceptable after
aggregating individual risks, hence quantify the costs of a bail-out. In
contrast, our approach emphasizes operational systemic risk measures that
include both ex post bailout costs as well as ex ante capital requirements and
may be used to prevent systemic crises.
Multiscale metabolic modeling of C4 plants: connecting nonlinear genome-scale models to leaf-scale metabolism in developing maize leaves
Date: 2015-02-27 00:00:00

C4 plants, such as maize, concentrate carbon dioxide in a specialized
compartment surrounding the veins of their leaves to improve the efficiency of
carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and
oxygen levels and reaction rates are key to their physiology but cannot be
handled with standard techniques of constraint-based metabolic modeling. We
demonstrate that incorporating these relationships as constraints on reaction
rates and solving the resulting nonlinear optimization problem yields realistic
predictions of the response of C4 systems to environmental and biochemical
perturbations. Using a new genome-scale reconstruction of maize metabolism, we
build an 18000-reaction, nonlinearly constrained model describing mesophyll and
bundle sheath cells in 15 segments of the developing maize leaf, interacting
via metabolite exchange, and use RNA-seq and enzyme activity measurements to
predict spatial variation in metabolic state by a novel method that optimizes
correlation between fluxes and expression data. Though such correlations are
known to be weak in general, here the predicted fluxes achieve high correlation
with the data, successfully capture the experimentally observed base-to-tip
transition between carbon-importing tissue and carbon-exporting tissue, and
include a nonzero growth rate, in contrast to prior results from similar
methods in other systems. We suggest that developmental gradients may be
particularly suited to the inference of metabolic fluxes from expression data.
Error analysis in Fourier methods for option pricing
Date: 2015-11-29 00:00:00

We provide a bound for the error committed when using a Fourier method to
price European options when the underlying follows an exponential \levy
dynamic. The price of the option is described by a partial integro-differential
equation (PIDE). Applying a Fourier transformation to the PIDE yields an
ordinary differential equation that can be solved analytically in terms of the
characteristic exponent of the \levy process. Then, a numerical inverse Fourier
transform allows us to obtain the option price. We present a novel bound for
the error and use this bound to set the parameters for the numerical method. We
analyse the properties of the bound for a dissipative and pure-jump example.
The bound presented is independent of the asymptotic behaviour of option prices
at extreme asset prices. The error bound can be decomposed into a product of
terms resulting from the dynamics and the option payoff, respectively. The
analysis is supplemented by numerical examples that demonstrate results
comparable to and superior to the existing literature.
An investigation into inter- and intragenomic variations of graphic genomic signatures
Date: 2015-03-10 00:00:00

We provide, on an extensive dataset and using several different distances,
confirmation of the hypothesis that CGR patterns are preserved along a genomic
DNA sequence, and are different for DNA sequences originating from genomes of
different species. This finding lends support to the theory that CGRs of
genomic sequences can act as graphic genomic signatures. In particular, we
compare the CGR patterns of over five hundred different 150,000 bp genomic
sequences originating from the genomes of six organisms, each belonging to one
of the kingdoms of life: H. sapiens, S. cerevisiae, A. thaliana, P. falciparum,
E. coli, and P. furiosus. We also provide preliminary evidence of this method's
applicability to closely related species by comparing H. sapiens (chromosome
21) sequences and over one hundred and fifty genomic sequences, also 150,000 bp
long, from P. troglodytes (Animalia; chromosome Y), for a total length of more
than 101 million basepairs analyzed. We compute pairwise distances between CGRs
of these genomic sequences using six different distances, and construct
Molecular Distance Maps that visualize all sequences as points in a
two-dimensional or three-dimensional space, to simultaneously display their
interrelationships. Our analysis confirms that CGR patterns of DNA sequences
from the same genome are in general quantitatively similar, while being
different for DNA sequences from genomes of different species. Our analysis of
the performance of the assessed distances uses three different quality measures
and suggests that several distances outperform the Euclidean distance, which
has so far been almost exclusively used for such studies. In particular we show
that, for this dataset, DSSIM (Structural Dissimilarity Index) and the
descriptor distance (introduced here) are best able to classify genomic
sequences.
Role of word-of-mouth for programs of voluntary vaccination: A game-theoretic approach
Date: 2015-02-28 00:00:00

We propose a model describing the synergetic feedback between word-of-mouth
(WoM) and epidemic dynamics controlled by voluntary vaccination. We combine a
game-theoretic model for the spread of WoM and a compartmental model describing
$SIR$ disease dynamics in the presence of a program of voluntary vaccination.
We evaluate and compare two scenarios, depending on what WoM disseminates: (1)
vaccine advertising, which may occur whether or not an epidemic is ongoing and
(2) epidemic status, notably disease prevalence. Understanding the synergy
between the two strategies could be particularly important for organizing
voluntary vaccination campaigns. We find that, in the initial phase of an
epidemic, vaccination uptake is determined more by vaccine advertising than the
epidemic status. As the epidemic progresses, epidemic status become
increasingly important for vaccination uptake, considerably accelerating
vaccination uptake toward a stable vaccination coverage.
Colonization of a territory by a stochastic population under a strong Allee effect and a low immigration pressure
Date: 2016-09-29 00:00:00

We study the dynamics of colonization of a territory by a stochastic
population at low immigration pressure. We assume a sufficiently strong Allee
effect that introduces, in deterministic theory, a large critical population
size for colonization. At low immigration rates, the average pre-colonization
population size is small thus invalidating the WKB approximation to the master
equation. We circumvent this difficulty by deriving an exact zero-flux solution
of the master equation and matching it with an approximate non-zero-flux
solution of the pertinent Fokker-Planck equation in a small region around the
critical population size. This procedure provides an accurate evaluation of the
quasi-stationary probability distribution of population sizes in the
pre-colonization state, and of the mean time to colonization, for a wide range
of immigration rates. At sufficiently high immigration rates our results agree
with WKB results obtained previously. At low immigration rates the results can
be very different.
Diversity waves in collapse-driven population dynamics
Date: 2015-07-14 00:00:00
Tasks: Diversity

Populations of species in ecosystems are often constrained by availability of
resources within their environment. In effect this means that a growth of one
population, needs to be balanced by comparable reduction in populations of
others. In neutral models of biodiversity all populations are assumed to change
incrementally due to stochastic births and deaths of individuals. Here we
propose and model another redistribution mechanism driven by abrupt and severe
collapses of the entire population of a single species freeing up resources for
the remaining ones. This mechanism may be relevant e.g. for communities of
bacteria, with strain-specific collapses caused e.g. by invading
bacteriophages, or for other ecosystems where infectious diseases play an
important role.
  The emergent dynamics of our system is cyclic "diversity waves" triggered by
collapses of globally dominating populations. The population diversity peaks at
the beginning of each wave and exponentially decreases afterwards. Species
abundances are characterized by a bimodal time-aggregated distribution with the
lower peak formed by populations of recently collapsed or newly introduced
species, while the upper peak - species that has not yet collapsed in the
current wave. In most waves both upper and lower peaks are composed of several
smaller peaks. This self-organized hierarchical peak structure has a long-term
memory transmitted across several waves. It gives rise to a scale-free tail of
the time-aggregated population distribution with a universal exponent of 1.7.
We show that diversity wave dynamics is robust with respect to variations in
the rules of our model such as diffusion between multiple environments,
species-specific growth and extinction rates, and bet-hedging strategies.
Leveraging the network: a stress-test framework based on DebtRank
Date: 2016-02-22 00:00:00

We develop a novel stress-test framework to monitor systemic risk in
financial systems. The modular structure of the framework allows to accommodate
for a variety of shock scenarios, methods to estimate interbank exposures and
mechanisms of distress propagation. The main features are as follows. First,
the framework allows to estimate and disentangle not only first-round effects
(i.e. shock on external assets) and second-round effects (i.e. distress induced
in the interbank network), but also third-round effects induced by possible
fire sales. Second, it allows to monitor at the same time the impact of shocks
on individual or groups of financial institutions as well as their
vulnerability to shocks on counterparties or certain asset classes. Third, it
includes estimates for loss distributions, thus combining network effects with
familiar risk measures such as VaR and CVaR. Fourth, in order to perform
robustness analyses and cope with incomplete data, the framework features a
module for the generation of sets of networks of interbank exposures that are
coherent with the total lending and borrowing of each bank. As an illustration,
we carry out a stress-test exercise on a dataset of listed European banks over
the years 2008-2013. We find that second-round and third-round effects dominate
first-round effects, therefore suggesting that most current stress-test
frameworks might lead to a severe underestimation of systemic risk.
Capturing a phylogenetic tree when the number of character states varies with the number of leaves
Date: 2015-08-26 00:00:00

We show that for any two values $\alpha, \beta >0 $ for which
$\alpha+\beta>1$ then there is a value $N$ so that for all $n \geq N$ the
following holds. For any binary phylogenetic tree $T$ on $n$ leaves there is a
set of $\lfloor n^\alpha \rfloor$ characters that capture $T$, and for which
each character takes at most $\lfloor n^\beta \rfloor$ distinct states. Here
`capture' means that $T$ is the unique perfect phylogeny for these characters.
Our short proof of this combinatorial result is based on the probabilistic
method.