pwc-archive/papers-with-abstracts huggingface dataset:
Mutation activity of Lonicera caerulea population in an active fault zone (the Altai Mountains)
Date: 2015-08-11 00:00:00

Geophysical and geochemical anomalies may have a mutagenic effect on plants
growing in active fault zones being the factors of evolutionary transformation
of plant populations. To test this assumption we evaluated the mutation
activity of a Lonicera caerulea natural population in one of the active fault
zones in the Altai Mountains. We derived principal cytogenetic indices (i.e.,
mitotic, prophase, metaphase, anaphase, and telophase indices as well as
proportion and range of abnormal mitoses) for meristematic cells of Lonicera
caerulea seedlings. We found that the local geological and geophysical
environment (i.e., mineralogical composition of rocks and anomalies of the
magnetic field) increases the mitotic activity and the number of abnormal
mitoses in the meristematic cells. The results may help to clarify the role of
environmental conditions of tectonically active regions in microevolutionary
processes.
Grand-canonical simulation of DNA condensation with two salts, affect of divalent counterion size
Date: 2016-02-13 00:00:00

The problem of DNA$-$DNA interaction mediated by divalent counterions is
studied using a generalized Grand-canonical Monte-Carlo simulation for a system
of two salts. The effect of the divalent counterion size on the condensation
behavior of the DNA bundle is investigated. Experimentally, it is known that
multivalent counterions have strong effect on the DNA condensation phenomenon.
While tri- and tetra-valent counterions are shown to easily condense free DNA
molecules in solution into toroidal bundles, the situation with divalent
counterions are not as clear cut. Some divalent counterions like Mg$^{+2}$ are
not able to condense free DNA molecules in solution, while some like Mn$^{+2}$
can condense them into disorder bundles. In restricted environment such as in
two dimensional system or inside viral capsid, Mg$^{+2}$ can have strong effect
and able to condense them, but the condensation varies qualitatively with
different system, different coions. It has been suggested that divalent
counterions can induce attraction between DNA molecules but the strength of the
attraction is not strong enough to condense free DNA in solution. However, if
the configuration entropy of DNA is restricted, these attractions are enough to
cause appreciable effects. The variations among different divalent salts might
be due to the hydration effect of the divalent counterions. In this paper, we
try to understand this variation using a very simple parameter, the size of the
divalent counterions. We investigate how divalent counterions with different
sizes can leads to varying qualitative behavior of DNA condensation in
restricted environments. Additionally a Grand canonical Monte-Carlo method for
simulation of systems with two different salts is presented in detail.
Balls, cups, and quasi-potentials: quantifying stability in stochastic systems
Date: 2015-10-23 00:00:00

When a system has more than one stable state, how can the stability of these
states be compared? This deceptively simple question has important consequences
for ecosystems, because systems with alternative stable states can undergo
dramatic regime shifts. The probability, frequency, duration, and dynamics of
these shifts will all depend on the relative stability of the stable states.
Unfortunately, the concept of stability in ecology has suffered from
substantial confusion and this is particularly problematic for systems where
stochastic perturbations can cause shifts between coexisting alternative stable
states. A useful way to visualize stable states in stochastic systems is with a
ball-in-cup diagram, in which the state of the system is represented as the
position of a ball rolling on a surface, and the random perturbations can push
the ball from one basin of attraction to another. The surface is determined by
a potential function, which provides a natural stability metric. However,
systems amenable to this representation, called gradient systems, are quite
rare. As a result, the potential function is not widely used and other
approaches based on linear stability analysis have become standard. Linear
stability analysis is designed for local analysis of deterministic systems and,
as we show, can produce a highly misleading picture of how the system will
behave under continual, stochastic perturbations. In this paper, we show how
the potential function can be generalized so that it can be applied broadly,
employing a concept from stochastic analysis called the quasi-potential. Using
three classic ecological models, we demonstrate that the quasi-potential
provides a useful way to quantify stability in stochastic systems.
A novel design of hidden web crawler using ontology
Authors: Manvi, Bhatia Komal Kumar, Dixit Ashutosh
Date: 2015-08-10 00:00:00

Deep Web is content hidden behind HTML forms. Since it represents a large
portion of the structured, unstructured and dynamic data on the Web, accessing
Deep-Web content has been a long challenge for the database community. This
paper describes a crawler for accessing Deep-Web using Ontologies. Performance
evaluation of the proposed work showed that this new approach has promising
results.
Collective Properties of a Transcription Initiation Model under Varying Environment
Date: 2015-08-10 00:00:00

The dynamics of gene transcription is tightly regulated in eukaryotes. Recent
experiments have revealed various kinds of transcriptional dynamics, such as
RNA polymerase II pausing, that involves regulation at the transcription
initiation stage, and the choice of different regulation pattern is closely
related to the physiological functions of the target gene. Here we consider a
simplified model of transcription initiation, a process including the assembly
of transcription complex and the pausing and releasing of the RNA polymerase
II. Focusing on the collective behaviors on a population level, we explore
potential regulatory functions this model can offer. These functions include
fast and synchronized response to environmental change, or long-term memory
about the transcriptional status. As a proof of concept we also show that, by
selecting different control mechanisms cells can adapt to different
environments. These findings may help us better understand the design
principles of transcriptional regulation.
The Intrinsic Instability of Financial Markets
Date: 2015-08-10 00:00:00

In this paper we explain the wild fluctuations of financial prices from the
intrinsic amplifying feedback of speculative supply and demand. Formally, we
show that an asset return follows a multiplicative random growth with exogenous
input, which is well-known to be a generic power-law generating process, and
which could thus easily explain the well-established power-law distribution of
returns, and other related variables. Moreover, the theory we develop here is a
general framework where competing ideas can be discussed in a unified way. The
dominant random walk model, for instance, is easily derived in this framework
if we superimpose market clearing (central to neoclassical economics). It
corresponds to the case where the feedback in price dynamics is ignored in
favor of the external input, namely the random inflow of news from the real
economy.
Oscillatory dynamics in complex recurrent neural networks
Authors: Rakesh Sengupta, P V Raja Shekar
Date: 2015-08-10 00:00:00

Spontaneous oscillations measured by Local field potentials (LFPs), electroencephalograms and magnetoencephalograms exhibits variety of oscillations spanning frequency band ($1-100$ Hz) in animals and humans. Both instantaneous power and phase of these ongoing oscillations have commonly been observed to correlate with pre-stimulus processing in animals and humans. However, despite of numerous attempts it is not fully clear whether the same mechanisms can give rise to a range of oscillations as observed in vivo during resting state spontaneous oscillatory activity of the brain. In the current paper we show how oscillatory activity can arise out of general recurrent on-center off-surround neural network. The current work shows (a) a complex valued input to a class of biologically inspired recurrent neural networks can be shown to be mathematically equivalent to a combination of real-valued recurrent network with real-valued feed forward network, (b) such a network can give rise to oscillatory signatures. We also validate the conjecture with results of simulation of complex valued additive recurrent neural network.
Estimation of the Diffusion Constant from Intermittent Trajectories with Variable Position Uncertainties
Date: 2015-08-21 00:00:00
Tasks: Position

The movement of a particle described by Brownian motion is quantified by a
single parameter, $D$, the diffusion constant. The estimation of $D$ from a
discrete sequence of noisy observations is a fundamental problem in biological
single particle tracking experiments since it can report on the environment
and/or the state of the particle itself via hydrodynamic radius. Here we
present a method to estimate $D$ that takes into account several effects that
occur in practice, that are important for correct estimation of $D$, and that
have hitherto not been combined together for estimation of $D$. These effects
are motion blur from finite integration time of the camera, intermittent
trajectories, and time-dependent localization uncertainty. Our estimation
procedure, a maximum likelihood estimation, follows directly from the
likelihood expression for a discretely observed Brownian trajectory that
explicitly includes these effects. The manuscript begins with the formulation
of the likelihood expression and then presents three methods to find the exact
solution. Each method has its own advantages in either computational
robustness, theoretical insight, or the estimation of hidden variables. We then
compare our estimator to previously published estimators using a squared log
loss function to demonstrate the benefit of including these effects.
Archiving Deferred Representations Using a Two-Tiered Crawling Approach
Authors: Brunelle Justin F., Weigle Michele C., Nelson Michael L.
Date: 2015-08-10 00:00:00
Tasks: Vocal Bursts Valence Prediction

Web resources are increasingly interactive, resulting in resources that are
increasingly difficult to archive. The archival difficulty is based on the use
of client-side technologies (e.g., JavaScript) to change the client-side state
of a representation after it has initially loaded. We refer to these
representations as deferred representations. We can better archive deferred
representations using tools like headless browsing clients. We use 10,000 seed
Universal Resource Identifiers (URIs) to explore the impact of including
PhantomJS -- a headless browsing tool -- into the crawling process by comparing
the performance of wget (the baseline), PhantomJS, and Heritrix. Heritrix
crawled 2.065 URIs per second, 12.15 times faster than PhantomJS and 2.4 times
faster than wget. However, PhantomJS discovered 531,484 URIs, 1.75 times more
than Heritrix and 4.11 times more than wget. To take advantage of the
performance benefits of Heritrix and the URI discovery of PhantomJS, we
recommend a tiered crawling strategy in which a classifier predicts whether a
representation will be deferred or not, and only resources with deferred
representations are crawled with PhantomJS while resources without deferred
representations are crawled with Heritrix. We show that this approach is 5.2
times faster than using only PhantomJS and creates a frontier (set of URIs to
be crawled) 1.8 times larger than using only Heritrix.
A Model for Competition for Ribosomes in the Cell
Date: 2015-08-10 00:00:00
Tasks: Translation

Large-scale simultaneous mRNA translation and the resulting competition for
the available ribosomes has important implications to the cell's functioning
and evolution. Developing a better understanding of the intricate correlations
between these simultaneous processes, rather than focusing on the translation
of a single isolated transcript, should help in gaining a better understanding
of mRNA translation regulation and the way elongation rates affect organismal
fitness. A model of simultaneous translation is specifically important when
dealing with highly expressed genes, as these consume more resources. In
addition, such a model can lead to more accurate predictions that are needed in
the interconnection of translational modules in synthetic biology. We develop
and analyze a general model for large-scale simultaneous mRNA translation and
competition for ribosomes. This is based on combining several ribosome flow
models (RFMs) interconnected via a pool of free ribosomes. We prove that the
compound system always converges to a steady-state and that it always entrains
or phase locks to periodically time-varying transition rates in any of the mRNA
molecules. We use this model to explore the interactions between the various
mRNA molecules and ribosomes at steady-state. We show that increasing the
length of an mRNA molecule decreases the production rate of all the mRNAs.
Increasing any of the codon translation rates in a specific mRNA molecule
yields a local effect: an increase in the translation rate of this mRNA, and
also a global effect: the translation rates in the other mRNA molecules all
increase or all decrease. These results suggest that the effect of codon
decoding rates of endogenous and heterologous mRNAs on protein production is
more complicated than previously thought.
A Model for Tax Evasion with Some Realistic Properties
Date: 2015-08-11 00:00:00

We present a discrete-time dynamic model of income tax evasion. The model is
solved exactly in the case of a single taxpayer and shown to have some
realistic properties, including avoiding the Yitzhaki paradox. The extension to
an agent-based model with a network of taxpayers is also investigated.
Web Search Result Clustering based on Heuristic Search and k-means
Authors: Alam Mansaf, Sadaf Kishwar
Date: 2015-08-11 00:00:00
Tasks: Clustering, Heuristic Search, Information Retrieval, Retrieval

Giving user a simple and well organized web search result has been a topic of
active information Retrieval (IR) research. Irrespective of how small or
ambiguous a query is, a user always wants the desired result on the first
display of an IR system. Clustering of an IR system result can render a way,
which fulfills the actual information need of a user. In this paper, an
approach to cluster an IR system result is presented.The approach is a
combination of heuristics and k-means technique using cosine similarity. Our
heuristic approach detects the initial value of k for creating initial
centroids. This eliminates the problem of external specification of the value
k, which may lead to unwanted result if wrongly specified. The centroids
created in this way are more specific and meaningful in the context of web
search result. Another advantage of the proposed method is the removal of the
objective means function of k-means which makes cluster sizes same. The end
result of the proposed approach consists of different clusters of documents
having different sizes.
Tissue fusion over non-adhering surfaces
Date: 2015-08-11 00:00:00
Tasks: Friction

Tissue fusion eliminates physical voids in a tissue to form a continuous
structure and is central to many processes in development and repair. Fusion
events in vivo, particularly in embryonic development, often involve the
purse-string contraction of a pluricellular actomyosin cable at the free edge.
However in vitro, adhesion of the cells to their substrate favors a closure
mechanism mediated by lamellipodial protrusions, which has prevented a
systematic study of the purse-string mechanism. Here, we show that monolayers
can cover well-controlled mesoscopic non-adherent areas much larger than a cell
size by purse-string closure and that active epithelial fluctuations are
required for this process. We have formulated a simple stochastic model that
includes purse-string contractility, tissue fluctuations and effective friction
to qualitatively and quantitatively account for the dynamics of closure. Our
data suggest that, in vivo, tissue fusion adapts to the local environment by
coordinating lamellipodial protrusions and purse-string contractions.
A note on convex characters, Fibonacci numbers and exponential-time algorithms
Date: 2016-07-27 00:00:00

Phylogenetic trees are used to model evolution: leaves are labelled to
represent contemporary species ("taxa") and interior vertices represent extinct
ancestors. Informally, convex characters are measurements on the contemporary
species in which the subset of species (both contemporary and extinct) that
share a given state, form a connected subtree. Given an unrooted, binary
phylogenetic tree T on a set of n >= 2 taxa, a closed (but fairly opaque)
expression for the number of convex characters on T has been known since 1992,
and this is independent of the exact topology of T. In this note we prove that
this number is actually equal to the (2n-1)th Fibonacci number. Next, we define
g_k(T) to be the number of convex characters on T in which each state appears
on at least k taxa. We show that, somewhat curiously, g_2(T) is also
independent of the topology of T, and is equal to to the (n-1)th Fibonacci
number. As we demonstrate, this topological neutrality subsequently breaks down
for k >= 3. However, we show that for each fixed k >= 1, g_k(T) can be computed
in O(n) time and the set of characters thus counted can be efficiently listed
and sampled. We use these insights to give a simple but effective exact
algorithm for the NP-hard maximum parsimony distance problem that runs in time
$\Theta( \phi^{n} \cdot n^2 )$, where $\phi \approx 1.618...$ is the golden
ratio, and an exact algorithm which computes the tree bisection and
reconnection distance (equivalently, a maximum agreement forest) in time
$\Theta( \phi^{2n}\cdot \text{poly}(n))$, where $\phi^2 \approx 2.619$.
Origins of Bipedalism
Date: 2015-10-17 00:00:00

The following manuscript reviews various theories of bipedalism and provides
a holistic answer to human evolution. There are two questions regarding
bipedalism: i) why were the earliest hominins partially bipedal? and ii) why
did hominins become increasingly bipedal over time and replace their less
bipedal ancestors? To answer these questions, the prominent theories in the
field, such as the savanna-based theory, the postural feeding hypotheses, and
the provisioning model, are collectively examined. Because biological evolution
is an example of trial and error and not a simple causation, there may be
multiple answers to the evolution of bipedalism. The postural feeding
hypothesis (reaching for food/balancing) provides an explanation for the
partial bipedalism of the earliest hominins. The savannah-based theory
describes how the largely bipedal hominins that started to settle on the ground
became increasingly bipedal. The provisioning model (food-gathering/monogamy)
explains questions arising after the postural feeding hypothesis and before the
savannah theory in an evolutionary timeline. Indeed, there are no straight
lines between the theories, and multiple forces could have pushed the evolution
of bipedalism at different points. Finally, this manuscript states that the
arboreal hominins that possessed ambiguous traits of bipedalism were eliminated
through choice and selection. Using the biological analogy of the okapi and
giraffe, I explain how one of the branches (Homo) became increasingly bipedal
while the other (Pan) adapted to locomotion for forest life by narrowing the
anatomical/biological focus in evolution.
Risk aggregation with empirical margins: Latin hypercubes, empirical copulas, and convergence of sum distributions
Date: 2015-08-11 00:00:00

This paper studies convergence properties of multivariate distributions
constructed by endowing empirical margins with a copula. This setting includes
Latin Hypercube Sampling with dependence, also known as the Iman--Conover
method. The primary question addressed here is the convergence of the component
sum, which is relevant to risk aggregation in insurance and finance.
  This paper shows that a CLT for the aggregated risk distribution is not
available, so that the underlying mathematical problem goes beyond classic
functional CLTs for empirical copulas. This issue is relevant to Monte-Carlo
based risk aggregation in all multivariate models generated by plugging
empirical margins into a copula.
  Instead of a functional CLT, this paper establishes strong uniform
consistency of the estimated sum distribution function and provides a
sufficient criterion for the convergence rate $O(n^{-1/2})$ in probability.
These convergence results hold for all copulas with bounded densities. Examples
with unbounded densities include bivariate Clayton and Gauss copulas. The
convergence results are not specific to the component sum and hold also for any
other componentwise non-decreasing aggregation function. On the other hand,
convergence of estimates for the joint distribution is much easier to prove,
including CLTs.
  Beyond Iman--Conover estimates, the results of this paper apply to
multivariate distributions obtained by plugging empirical margins into an exact
copula or by plugging exact margins into an empirical copula.
The short-cut network within protein residue networks
Date: 2015-08-12 00:00:00
Tasks: Protein Folding

A protein residue network (PRN) is a network of interacting amino acids
within a protein. We describe characteristics of a sparser, highly central and
more volatile sub-network of a PRN called the short-cut network (SCN), as a
protein folds under molecular dynamics (MD) simulation with the goal of
understanding how proteins form navigable small-world networks within
themselves. The edges of an SCN are found via a local greedy search on a PRN.
SCNs grow in size and transitivity strength as a protein folds, and SCNs from
successful MD trajectories are better formed in these terms. Findings from an
investigation on how to model the formation of SCNs using dynamic graph theory,
and suggestions to move forward are presented. A SCN is enriched with
short-range contacts and its formation correlates positively with secondary
structure formation. Thus our approach to modeling PRN formation, in essence
protein folding from a graph theoretic view point, is more in tune with the
notion of increasing order to a random graph than the other way around, and
this increase in order coincides with improved navigability of PRNs.
Asyptotic Normality for Maximum Likelihood Estimation and Operational Risk
Date: 2016-08-25 00:00:00
Tasks: valid

Operational risk models commonly employ maximum likelihood estimation (MLE)
to fit loss data to heavy-tailed distributions. Yet several desirable
properties of MLE (e.g. asymptotic normality) are generally valid only for
large sample-sizes, a situation rarely encountered in operational risk. In this
paper, we study how asymptotic normality does--or does not--hold for common
severity distributions in operational risk models. We then apply these results
to evaluate errors caused by failure of asymptotic normality in constructing
confidence intervals around the MLE fitted parameters.
Convergence of random walks to Brownian motion on cubical complexes
Date: 2019-05-22 00:00:00

Cubical complexes are metric spaces constructed by gluing together unit cubes
in an analogous way to the construction of simplicial complexes. We construct
Brownian motion on such spaces, define random walks, and prove that the
transition kernels of the random walks converge to that for Brownian motion.
The proof involves pulling back onto the complex the distribution of Brownian
sample paths on the standard cube, and combining this with a distribution on
walks between cubes in the complex. The main application lies in analysing sets
of evolutionary trees: several tree spaces are cubical complexes and we briefly
describe our results and some applications in this context. Our results extend
readily to a class of polyhedral complex in which every cell of maximal
dimension is isometric to a given fixed polyhedron.