pwc-archive/papers-with-abstracts huggingface dataset:
Patterns of mast fruiting - a stochastic approach
Date: 2016-01-24 00:00:00

Mast fruiting represents a synchronous population behaviour which can spread
on large landscape areas. This reproductive pattern is generally perceived as a
synchronous periodic production of large seed crops and has a significant
practical importance to forest natural regeneration in order to synchronize
cuttings. The mechanisms of masting are still argued and models of this
phenomenon are uncommon, so a stochastic approach can cast significant light on
some particular aspects. Trees manage to get synchronized and coordinate their
reproductive routines. But is it possible that trees get synchronized by
chance, absolutely random? Using a Monte Carlo simulation of seeding years and
a theoretical masting pattern, a stochastic analysis is performed in order to
assess the chance of random mast fruiting. Two populations of 100 trees, with
different fruiting periodicity of 2-3 years and 4-6 years, were set and the
fruition dynamic was simulated for 100 years. The results show that periodicity
itself cannot induce by chance the masting effect, but periodicity
mathematically influences the reproductive pattern.
Using runs of homozygosity to detect genomic regions associated with susceptibility to infectious and metabolic diseases in dairy cows under intensive farming conditions
Date: 2016-01-26 00:00:00

Runs of homozygosity (ROH) are contiguous stretches of homozygous genome
which likely reflect transmission from common ances- tors and can be used to
track the inheritance of haplotypes of interest. In the present paper, ROH were
extracted from 50K SNPs and used to detect regions of the genome associated
with susceptibility to diseases in a population of 468 Holstein-Frisian cows.
Diagnosed diseases were categorised as infectious diseases, metabolic
syndromes, mastitis, reproductive diseases and locomotive disorders. ROH
associated with infectious diseases, mastitis and locomotive disorders were
found on BTA 12. A long region of homozygosity linked with metabolic syndromes,
infectious and reproductive diseases was detected on BTA 15, disclosing complex
relationships between immunity, metabolism and functional disorders. ROH
associated with infectious and reproductive diseases, mastitis and metabolic
syndromes were observed on chromosomes 3, 5, 7, 13 and 18. Previous studies
reported QTLs for milk production traits on all of these regions, thus
substantiating the known negative relationship between selection for milk
production and health in dairy cattle.
Sequence assembly from corrupted shotgun reads
Date: 2016-01-26 00:00:00

The prevalent technique for DNA sequencing consists of two main steps:
shotgun sequencing, where many randomly located fragments, called reads, are
extracted from the overall sequence, followed by an assembly algorithm that
aims to reconstruct the original sequence. There are many different
technologies that generate the reads: widely-used second-generation methods
create short reads with low error rates, while emerging third-generation
methods create long reads with high error rates. Both error rates and error
profiles differ among methods, so reconstruction algorithms are often tailored
to specific shotgun sequencing technologies. As these methods change over time,
a fundamental question is whether there exist reconstruction algorithms which
are robust, i.e., which perform well under a wide range of error distributions.
  Here we study this question of sequence assembly from corrupted reads. We
make no assumption on the types of errors in the reads, but only assume a bound
on their magnitude. More precisely, for each read we assume that instead of
receiving the true read with no errors, we receive a corrupted read which has
edit distance at most $\epsilon$ times the length of the read from the true
read. We show that if the reads are long enough and there are sufficiently many
of them, then approximate reconstruction is possible: we construct a simple
algorithm such that for almost all original sequences the output of the
algorithm is a sequence whose edit distance from the original one is at most
$O(\epsilon)$ times the length of the original sequence.
On the fractional cell kill law governing the lysis of solid tumors
Date: 2016-08-29 00:00:00

We present in silico simulations and mathematical analyses supporting several
hypotheses that explain the saturation expressed in the fractional cell kill
law that governs the lysis of tumor cells by cytotoxic CD8 + T cells (CTLs). In
order to give insight into the significance of the parameters appearing in such
law, a hybrid cellular automaton model describing the spatio-temporal evolution
of tumor growth and its interaction with the cell-mediated immune response is
used. When the CTLs eradicate efficiently the tumor cells, the model predicts a
correlation between the morphology of the tumors and the rate at which they are
lysed. As the effectiveness of the effector cells is decreased, the saturation
gradually disappears. This limit is thoroughly discussed and a new fractional
cell kill is proposed.
Probing the limits to microRNA-mediated control of gene expression
Date: 2016-01-26 00:00:00

According to the `ceRNA hypothesis', microRNAs (miRNAs) may act as mediators
of an effective positive interaction between long coding or non-coding RNA
molecules, carrying significant potential implications for a variety of
biological processes. Here, inspired by recent work providing a quantitative
description of small regulatory elements as information-conveying channels, we
characterize the effectiveness of miRNA-mediated regulation in terms of the
optimal information flow achievable between modulator (transcription factors)
and target nodes (long RNAs). Our findings show that, while a sufficiently
large degree of target derepression is needed to activate miRNA-mediated
transmission, (a) in case of differential mechanisms of complex processing
and/or transcriptional capabilities, regulation by a post-transcriptional
miRNA-channel can outperform that achieved through direct transcriptional
control; moreover, (b) in the presence of large populations of weakly
interacting miRNA molecules the extra noise coming from titration disappears,
allowing the miRNA-channel to process information as effectively as the direct
channel. These observations establish the limits of miRNA-mediated
post-transcriptional cross-talk and suggest that, besides providing a degree of
noise buffering, this type of control may be effectively employed in cells both
as a failsafe mechanism and as a preferential fine tuner of gene expression,
pointing to the specific situations in which each of these functionalities is
maximized.
A complex network analysis of hypertension-related genes
Date: 2016-01-27 00:00:00

In this paper, a network of hypertension-related genes is constructed by
analyzing the correlations of gene expression data among the Dahl
salt-sensitive rat and two consomic rat strains. The numerical calculations
show that this sparse and assortative network has small-world and scale-free
properties. Further, 16 key hub genes (Col4a1, Lcn2, Cdk4, etc.) are determined
by introducing an integrated centrality and have been confirmed by
biological/medical research to play important roles in hypertension.
The dengue fever in four municipalities of the Colima state, Mexico, from 2008 to 2015 and its relation with some climatological normals
Date: 2016-01-26 00:00:00

Although dengue fever is an ancient disease that should have been eradicated
since time ago, in Mexico as well as in other regions worldwide the cases of
classic and hemorrhagic dengue continue to be reported presently. Since 2002
(and before), a worrying outbreak of dengue was observed in several states of
Mexico, notably the case of Colima for which a "descacharrizacion" campaign was
implemented in 2009 to encourage the population to get rid of old objects
accumulated in their backyards and outdoors so as to prevent proliferation of
mosquitoes Aedes Aegypti. To understand the effect of such campaign, we studied
the incidence of dengue in four municipalities of the mentioned state, namely
Manzanillo, Armeria, Tecoman and Ixtlahuacan. In particular, we observed that
the incidence of dengue in these four municipalities had a strong relationship
with climatological normals, specifically precipitation and minimum
temperature. Furthermore, the results showed that the mentioned campaign helped
prevent mosquito eggs incubation and their development, thus leading to
reduction of the incidence of dengue in the human population.
A Method to Support Difficult Re-finding Tasks
Authors: Liu Gangli, Feng Ling
Date: 2016-01-27 00:00:00
Tasks: Math

Re-finding electronic documents from a personal computer is a frequent demand
to users. In a simple re-finding task, people can use many methods to retrieve
a document, such as navigating directly to the document's folder, searching
with a desktop search engine, or checking the Recent Files List. However, when
encountering a difficult re-finding task, people usually cannot remember the
attributes used by conventional re-finding methods, such as file path, file
name, keywords etc., the re-finding would fail. We propose a new method to
support difficult re-finding tasks. When a user is reading a document, we
collect all kinds of possible memory pieces of the user about the document,
such as number of pages, number of images, number of math formulas, cumulative
reading time, reading frequency, printing experiences etc. If the user wants to
re-find a document later, we use these collected attributes to filter out the
target document. To alleviate the user's cognitive burden, we use a question
and answer wizard interface and provide recommendations to the answers for the
user, the recommendations are generated by analyzing the collected attributes
of each document and the user's experiences about them.
Unified Growth Theory Contradicted by the Mathematical Analysis of the Historical Growth of Human Population
Date: 2016-04-20 00:00:00

Data describing the historical growth of human population global and regional
(Western Europe, Eastern Europe, Asia, former USSR, Africa and Latin America)
are analysed. Results are in harmony with the earlier analysis of the
historical growth of the world population in the past 12,000 years and with a
similar but limited study carried out over 50 years ago. This analysis is also
in harmony with the study of the historical economic growth. Within the range
of analysable data, there was no Malthusian stagnation. Takeoffs from
stagnation to growth, postulated by the Unified Growth Theory never happened.
There were no escapes from the Malthusian trap because there was no trap. This
analysis and the earlier studies of the Gross Domestic Product lead to the
conclusion that there were also no takeoffs in the income per capita
distributions, claimed by the Unified Growth Theory. Consequently, the claimed
in this theory differential timing in takeoffs never happened. Unified Growth
Theory is contradicted yet again by the mathematical analysis of the same data,
which were used, but never analysed, during the formulation of this theory.
However, this study, as well as the earlier publications on the related topics,
shows also that some fundamental postulates used in the economic and
demographic research are repeatedly contradicted by the mathematical analysis
of data.
Heterogeneous network epidemics: real-time growth, variance and extinction of infection
Date: 2017-01-20 00:00:00

Recent years have seen a large amount of interest in epidemics on networks as
a way of representing the complex structure of contacts capable of spreading
infections through the modern human population. The configuration model is a
popular choice in theoretical studies since it combines the ability to specify
the distribution of the number of contacts (degree) with analytical
tractability. Here we consider the early real-time behaviour of the Markovian
SIR epidemic model on a configuration model network using a multi-type
branching process. We find closed-form analytic expressions for the mean and
variance of the number of infectious individuals as a function of time and the
degree of the initially infected individual(s), and write down a system of
differential equations for the probability of extinction that are numerically
fast compared to Monte Carlo simulation. We show that these quantities are all
sensitive to the degree distribution - in particular we confirm that the mean
prevalence of infection depends on the first two moments of the degree
distribution and the variance in prevalence depends on the first three moments
of the degree distribution. In contrast to most existing analytic approaches,
the accuracy of these results does not depend on having a large number of
infectious individuals, meaning that in the large population limit they would
be asymptotically exact even for one initial infectious individual.
The leaky integrator with recurrent inhibition as a predictor
Date: 2016-07-27 00:00:00

It is shown that the leaky integrator, the basis for many neuronal models,
possesses a negative group delay when a time-delayed recurrent inhibition is
added to it. By means of this negative group delay, the leaky integrator
becomes a predictor for some frequency components of the input signal. The
prediction properties are derived analytically and an application to a local
field potential is provided.
Hierarchical organization of functional connectivity in the mouse brain: a complex network approach
Date: 2016-01-27 00:00:00
Tasks: Community Detection, Functional Connectivity

This paper represents a contribution to the study of the brain functional
connectivity from the perspective of complex networks theory. More
specifically, we apply graph theoretical analyses to provide evidence of the
modular structure of the mouse brain and to shed light on its hierarchical
organization. We propose a novel percolation analysis and we apply our approach
to the analysis of a resting-state functional MRI data set from 41 mice. This
approach reveals a robust hierarchical structure of modules persistent across
different subjects. Importantly, we test this approach against a statistical
benchmark (or null model) which constrains only the distributions of empirical
correlations. Our results unambiguously show that the hierarchical character of
the mouse brain modular structure is not trivially encoded into this
lower-order constraint. Finally, we investigate the modular structure of the
mouse brain by computing the Minimal Spanning Forest, a technique that
identifies subnetworks characterized by the strongest internal correlations.
This approach represents a faster alternative to other community detection
methods and provides a means to rank modules on the basis of the strength of
their internal edges.
Trading-profit attribution for the size factor
Date: 2016-01-28 00:00:00

An algorithm was recently introduced by INTECH for the purposes of estimating
the trading-profit contribution of systematic rebalancing to the relative
return of rules-based investment strategies. We apply this methodology to
analyze the size factor through the use of equal-weighted portfolios. These
strategies combine a natural exposure to the size factor with a simple
understanding within the framework of Stochastic Portfolio Theory, furnishing a
natural test subject for the attribution algorithm.
Portfolio Optimization in the Stochastic Portfolio Theory Framework
Date: 2016-01-28 00:00:00
Tasks: Portfolio Optimization

I discuss some theoretical results with a view to motivate some practical
choices in portfolio optimization. Even though the setting is not completely
general (for example, the covariance matrix is assumed to be non-singular), I
attempt to highlight the features that have practical relevance. The
mathematical setting is Stochastic Portfolio Theory, which is flexible enough
to describe most realistic assets, and it has been successfully employed for
managing equity portfolios since 1987.
A pathway-based network analysis of hypertension-related genes
Date: 2016-01-28 00:00:00

Complex network approach has become an effective way to describe
interrelationships among large amounts of biological data, which is especially
useful in finding core functions and global behavior of biological systems.
Hypertension is a complex disease caused by many reasons including genetic,
physiological, psychological and even social factors. In this paper, based on
the information of biological pathways, we construct a network model of
hypertension-related genes of the salt-sensitive rat to explore the
interrelationship between genes. Statistical and topological characteristics
show that the network has the small-world but not scale-free property, and
exhibits a modular structure, revealing compact and complex connections among
these genes. By the threshold of integrated centrality larger than 0.71, seven
key hub genes are found: Jun, Rps6kb1, Cycs, Creb3l2, Cdk4, Actg1 and RT1-Da.
These genes should play an important role in hypertension, suggesting that the
treatment of hypertension should focus on the combination of drugs on multiple
genes.
Fractional diffusion emulates a human mobility network during a simulated disease outbreak
Date: 2016-01-28 00:00:00

From footpaths to flight routes, human mobility networks facilitate the
spread of communicable diseases. Control and elimination efforts depend on
characterizing these networks in terms of connections and flux rates of
individuals between contact nodes. In some cases, transport can be
parameterized with gravity-type models or approximated by a diffusive random
walk. As a alternative, we have isolated intranational commercial air traffic
as a case study for the utility of non-diffusive, heavy-tailed transport
models. We implemented new stochastic simulations of a prototypical
influenza-like infection, focusing on the dense, highly-connected United States
air travel network. We show that mobility on this network can be described
mainly by a power law, in agreement with previous studies. Remarkably, we find
that the global evolution of an outbreak on this network is accurately
reproduced by a two-parameter space-fractional diffusion equation, such that
those parameters are determined by the air travel network.
Micro-foundation using percolation theory of the finite-time singular behavior of the crash hazard rate in a class of rational expectation bubbles
Date: 2016-01-28 00:00:00

We present a plausible micro-founded model for the previously postulated
power law finite time singular form of the crash hazard rate in the
Johansen-Ledoit-Sornette model of rational expectation bubbles. The model is
based on a percolation picture of the network of traders and the concept that
clusters of connected traders share the same opinion. The key ingredient is the
notion that a shift of position from buyer to seller of a sufficiently large
group of traders can trigger a crash. This provides a formula to estimate the
crash hazard rate by summation over percolation clusters above a minimum size
of a power sa (with a > 1) of the cluster sizes s, similarly to a generalized
percolation susceptibility. The power sa of cluster sizes emerges from the
super-linear dependence of group activity as a function of group size,
previously documented in the literature. The crash hazard rate exhibits
explosive finite-time singular behaviors when the control parameter (fraction
of occupied sites, or density of traders in the network) approaches the
percolation threshold pc. Realistic dynamics are generated by modelling the
density of traders on the percolation network by an Ornstein-Uhlenbeck process,
whose memory controls the spontaneous excursion of the control parameter close
to the critical region of bubble formation. Our numerical simulations recover
the main stylized properties of the JLS model with intermittent explosive
super-exponential bubbles interrupted by crashes.
A computational model describing the interplay of basal ganglia and subcortical background oscillations during working memory processes
Date: 2016-01-28 00:00:00

Working memory is responsible for the temporary manipulation and storage of
information to support reasoning, learning and comprehension in the human
brain. Background oscillations from subcortical structures may drive a gating
or switching mechanism during working memory computations, and different
frequency bands may be associated with different processes while working memory
tasks are performed. There are three well-known relationships between working
memory processes and specific frequency bands of subcortical oscillations,
namely: the storage of new information which correlates positively with
beta/gamma-frequency band oscillations, the maintenance of information while
ignoring irrelevant stimulation which is directly linked to theta-frequency
band oscillations, and the clearance of memory which is associated with
alpha-frequency band oscillations. Although these relationships between working
memory processes and subcortical background oscillations have been observed, a
full explanation of these phenomena is still needed. This paper will aid
understanding of the working memory's operation and phase switching by
proposing a novel and biophysical realistic mathematical-computational
framework which unifies the generation of subcortical background oscillations,
the role of basal ganglia-thalamo-cortical circuits and the influence of
dopamine in the selection of working memory operations and phases: this has
never been attempted before.
Deep Learning Based Semantic Video Indexing and Retrieval
Authors: Podlesnaya Anna, Podlesnyy Sergey
Date: 2016-01-28 00:00:00
Tasks: Deep Learning, Retrieval, Video Retrieval

We share the implementation details and testing results for video retrieval
system based exclusively on features extracted by convolutional neural
networks. We show that deep learned features might serve as universal signature
for semantic content of video useful in many search and retrieval tasks. We
further show that graph-based storage structure for video index allows to
efficiently retrieving the content with complicated spatial and temporal search
queries.
Prediction Errors Drive UCS Revaluation and not Classical Conditioning: Evidence and Neurophysiological Consequences
Date: 2016-01-28 00:00:00

Nowadays, the experimental study of emotional learning is commonly based on
classical conditioning paradigms and models, which have been thoroughly
investigated in the last century. On the contrary, limited attention has been
paid to the revaluation of an unconditioned stimulus (UCS), which, as
experimentally observed by various researchers in the last four decades, occurs
out of classical conditioning. For this reason, no analytical or quantitative
theory has been developed for this phenomenon and its dynamics. Unluckily,
models based on classical conditioning are unable to explain or predict
important psychophysiological phenomena, such as the failure of the extinction
of emotional responses in certain circumstances. In this manuscript an
analytical representation of UCS revaluation learning is developed; this allows
us to identify the conditions determining the "inextinguishability" (or
resistant-to-extinction) property of emotional responses and reactions (such as
those observed in evaluative conditioning, in the nonreinforcement presentation
of a conditioned inhibitor, in post-traumatic stress disorders and in panic
attacks). Furthermore, an analysis of the causal relation existing between
classical conditioning and UCS revaluation is provided. Starting from this
result, a theory of implicit emotional learning and a novel interpretation of
classical conditioning are derived. Moreover, we discuss how the proposed
theory can lead to the development of new methodologies for the detection and
the treatment of undesired or pathological emotional responses, and can inspire
animal models for resistant-to-extinction responses and reactions.