pwc-archive/papers-with-abstracts huggingface dataset:
Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes
Date: 2015-01-30 00:00:00
Tasks: Missing Values

Plant survival is a key factor in forest dynamics and survival probabilities
often vary across life stages. Studies specifically aimed at assessing tree
survival are unusual and so data initially designed for other purposes often
need to be used; such data are more likely to contain errors than data
collected for this specific purpose. We investigate the survival rates of ten
tree species in a dataset designed to monitor growth rates. As some individuals
were not included in the census at some time points we use
capture-mark-recapture methods both to allow us to account for missing
individuals, and to estimate relocation probabilities. Growth rates, size, and
light availability were included as covariates in the model predicting survival
rates. The study demonstrates that tree mortality is best described as constant
between years and size-dependent at early life stages and size independent at
later life stages for most species of UK hardwood. We have demonstrated that
even with a twenty-year dataset it is possible to discern variability both
between individuals and between species. Our work illustrates the potential
utility of the method applied here for calculating plant population dynamics
parameters in time replicated datasets with small sample sizes and missing
individuals without any loss of sample size, and including explanatory
covariates.
Foreign Exchange Market Microstructure and the WM/Reuters 4pm Fix
Date: 2016-02-29 00:00:00

A market fix serves as a benchmark for foreign exchange (FX) execution, and
is employed by many institutional investors to establish an exact reference at
which execution takes place. The currently most popular FX fix is the World
Market Reuters (WM/R) 4pm fix. Execution at the WM/R 4pm fix is a service
offered by FX brokers (normally banks), who deliver execution at the fix
provided they obtain the trade order until a certain time prior to 4pm. In this
paper, we study the market microstructure around 4pm. We demonstrate that
market dynamics can be distinguished from other times during the day through
increased volatility and size of movements. Our findings question the aggregate
benefit to the client base of using the 4pm fix in its current form.
Death ligand concentration and the membrane proximal signaling module regulate the type 1/ type 2 choice in apoptotic death signaling
Date: 2015-01-30 00:00:00
Tasks: Vocal Bursts Type Prediction

Apoptotic death pathways are frequently activated by death ligand induction
and subsequent activation of the membrane proximal signaling module. Death
receptors cluster upon binding to death ligands, leading to formation of a
membrane proximal death-inducing-signaling-complex (DISC). In this membrane
proximal signalosome, initiator caspases (caspase 8) are processed resulting in
activation of both type 1 and type 2 pathways of apoptosis signaling. How the
type 1/type 2 choice is made is an important question in the systems biology of
apoptosis signaling. In this study, we utilize a Monte Carlo based in silico
approach to elucidate the role of membrane proximal signaling module in the
type 1/type 2 choice of apoptosis signaling. Our results provide crucial
mechanistic insights into the formation of DISC signalosome and caspase 8
activation. Increased concentration of death ligands was shown to correlate
with increased type 1 activation. We also study the caspase 6 mediated system
level feedback activation of apoptosis signaling and its role in the type
1/type 2 choice. Our results clarify the basis of cell-to-cell stochastic
variability in apoptosis activation and ramifications of this issue is further
discussed in the context of therapies for cancer and neurodegenerative
disorders.
Kinetic Monte Carlo study of the type1/type 2 choice in apoptosis elucidates selective killing of cancer cells under death ligand induction
Date: 2015-01-30 00:00:00
Tasks: Vocal Bursts Type Prediction

Death ligand mediated apoptotic activation is a mode of programmed cell death
that is widely used in cellular and physiological situations. Interest in
studying death ligand induced apoptosis has increased due to the promising role
of recombinant soluble forms of death ligands (mainly recombinant TRAIL) in
anti-cancer therapy. A clear elucidation of how death ligands activate the type
1 and type 2 apoptotic pathways in healthy and cancer cells may help develop
better chemotherapeutic strategies. In this work, we use kinetic Monte Carlo
simulations to address the problem of type 1/ type 2 choice in death ligand
mediated apoptosis of cancer cells. Our study provides insights into the
activation of membrane proximal death module that results from complex
interplay between death and decoy receptors. Relative abundance of death and
decoy receptors was shown to be a key parameter for activation of the initiator
caspases in the membrane module. Increased concentration of death ligands
frequently increased the type 1 activation fraction in cancer cells, and, in
certain cases changes the signaling phenotype from type 2 to type 1. Results of
this study also indicate that inherent differences between cancer and healthy
cells, such as in the membrane module, may allow robust activation of cancer
cell apoptosis by death ligand induction. At the same time, large cell-to-cell
variability through the type 2 pathway was shown to provide protection for
healthy cells. Such elucidation of selective activation of apoptosis in cancer
cells addresses a key question in cancer biology and cancer therapy.
Worldwide clustering of the corruption perception
Date: 2015-01-31 00:00:00
Tasks: Clustering

We inspect a possible clustering structure of the corruption perception among
134 countries. Using the average linkage clustering, we uncover a well-defined
hierarchy in the relationships among countries. Four main clusters are
identified and they suggest that countries worldwide can be quite well
separated according to their perception of corruption. Moreover, we find a
strong connection between corruption levels and a stage of development inside
the clusters. The ranking of countries according to their corruption perfectly
copies the ranking according to the economic performance measured by the gross
domestic product per capita of the member states. To the best of our knowledge,
this study is the first one to present an application of hierarchical and
clustering methods to the specific case of corruption.
Role of dynamic capsomere supply for viral capsid self-assembly
Date: 2015-01-31 00:00:00

Many viruses rely on the self-assembly of their capsids to protect and
transport their genomic material. For many viral systems, in particular for
human viruses like hepatitis B, adeno or human immunodeficiency virus, that
lead to persistent infections, capsomeres are continuously produced in the
cytoplasm of the host cell while completed capsids exit the cell for a new
round of infection. Here we use coarse-grained Brownian dynamics simulations of
a generic patchy particle model to elucidate the role of the dynamic supply of
capsomeres for the reversible self-assembly of empty T1 icosahedral virus
capsids. We find that for high rates of capsomere influx only a narrow range of
bond strengths exists for which a steady state of continuous capsid production
is possible. For bond strengths smaller and larger than this optimal value, the
reaction volume becomes crowded by small and large intermediates, respectively.
For lower rates of capsomere influx a broader range of bond strengths exists
for which a steady state of continuous capsid production is established,
although now the production rate of capsids is smaller. Thus our simulations
suggest that the importance of an optimal bond strength for viral capsid
assembly typical for in vitro conditions can be reduced by the dynamic influx
of capsomeres in a cellular environment.
Stochastic dynamics of virus capsid formation: direct versus hierarchical self-assembly
Date: 2015-01-31 00:00:00

In order to replicate within their cellular host, many viruses have developed
self-assembly strategies for their capsids which are sufficiently robust as to
be reconstituted in vitro. Mathematical models for virus self-assembly usually
assume that the bonds leading to cluster formation have constant reactivity
over the time course of assembly (direct assembly). In some cases, however,
binding sites between the capsomers have been reported to be activated during
the self-assembly process (hierarchical assembly). In order to study possible
advantages of such hierarchical schemes for icosahedral virus capsid assembly,
we use Brownian dynamics simulations of a patchy particle model that allows us
to switch binding sites on and off during assembly. For T1 viruses, we
implement a hierarchical assembly scheme where inter-capsomer bonds become
active only if a complete pentamer has been assembled. We find direct assembly
to be favorable for reversible bonds allowing for repeated structural
reorganizations, while hierarchical assembly is favorable for strong bonds with
small dissociation rate, as this situation is less prone to kinetic trapping.
However, at the same time it is more vulnerable to monomer starvation during
the final phase. Increasing the number of initial monomers does have only a
weak effect on these general features. The differences between the two assembly
schemes become more pronounced for more complex virus geometries, as shown here
for T3 viruses, which assemble through homogeneous pentamers and heterogeneous
hexamers in the hierarchical scheme. In order to complement the simulations for
this more complicated case, we introduce a master equation approach that agrees
well with the simulation results.
Cultural and Demic Diffusion of First Farmers, Herders, and their Innovations Across Eurasia
Date: 2015-10-12 00:00:00

Was the spread of agropastoralism from the Eurasian founder regions dominated
by demic or by cultural diffusion? This study employs a mathematical model of
regional sociocultural development that includes different diffusion processes,
local innovation and societal adaptation. Simulations hindcast the emergence
and expansion of agropastoral life style in 294 regions of Eurasia and North
Africa. Different scenarios for demic and diffusive exchange processes between
adjacent regions are contrasted and the spatiotemporal pattern of diffusive
events is evaluated. This study supports from a modeling perspective the
hypothesis that there is no simple or exclusive demic or cultural diffusion,
but that in most regions of Eurasia a combination of demic and cultural
processes were important. Furthermore, we demonstrate the strong spatial and
temporal variability in the balance of spread processes. Each region shows
sometimes more demic, and at other times more cultural diffusion. Only few,
possibly environmentally marginal, areas show a dominance of demic diffusion.
This study affirms that diffusion processes should be investigated in a
diachronic fashion and not from a time-integrated perspective.
Neuronal calculus for the auditory pathway
Date: 2015-12-24 00:00:00

The first steps in the neural processing of sound are located in the auditory
nerve and in the cochlear nuclei. To model the signal processing efficiently,
we propose a simple mathematical tool that takes the minute timing of the
system into account. In contrast to the situation in the cortex, the number of
connections between neurons in auditory periphery is comparatively low. This
gives way to an accurate modeling of the connectivity of the neuronal network.
The timing is the all important feature in the peripheral neuronal auditory
pathway. The primary auditory neurons e.g. phase lock to periodic sounds with
important interactions with respect to both the refractory periods of the
neurons and to the time delays caused by traveling times along the basilar
membrane or through a synaptic connection. The mathematical tools provide a
solid basis to build models for peripheral auditory processes. In particular,
we study carefully a large class of refractory neurons, find analytical
formulas for the spiking activity, and prove that refractory neurons respond to
periodic signals by asymptotically periodic output. The methods rely on the
theory of positive operators and give a numerical scheme for finding fixed
points to an integral operator with geometric convergence rate. In addition, we
consider a perfect integrator neuron, mathematically equivalent to randomized
random walk, where the random walk is bounded from below, and solve the first
passage time problem using continuous time Markov chain techniques. In an
accompanying paper we set up the simulation framework as a counterpart to the
present mathematical model. By suitably adjusting the few parameters in the
model it is possible to reproduce the basic patterns of neural activity.
A 0.042 mm^2 programmable biphasic stimulator for cochlear implants suitable for a large number of channels
Date: 2015-01-29 00:00:00
Tasks: Blocking

This paper presents a compact programmable biphasic stimulator for cochlear
implants. By employing double-loop negative feedback, the output impedance of
the current generator is increased, while maximizing the voltage compliance of
the output transistor. To make the stimulator circuit compact, the stimulation
current is set by scaling a reference current using a two stage binary-weighted
transistor DAC (comprising a 3 bit high-voltage transistor DAC and a 4 bit
low-voltage transistor DAC). With this structure the power consumption and the
area of the circuit can be minimized. The proposed circuit has been implemented
in AMS 0.18um high-voltage CMOS IC technology, using an active chip area of
about 0.042mm^2. Measurement results show that proper charge balance of the
anodic and cathodic stimulation phases is achieved and a dc blocking capacitor
can be omitted. The resulting reduction in the required area makes the proposed
system suitable for a large number of channels.
An equilibrium model for spot and forward prices of commodities
Date: 2017-01-21 00:00:00

We consider a market model that consists of financial investors and producers
of a commodity. Producers optionally store some production for future sale and
go short on forward contracts to hedge the uncertainty of the future commodity
price. Financial investors take positions in these contracts in order to
diversify their portfolios. The spot and forward equilibrium commodity prices
are endogenously derived as the outcome of the interaction between producers
and investors. Assuming that both are utility maximizers, we first prove the
existence of an equilibrium in an abstract setting. Then, in a framework where
the consumers' demand and the exogenously priced financial market are
correlated, we provide semi-explicit expressions for the equilibrium prices and
analyze their dependence on the model parameters. The model can explain why
increased investors' participation in forward commodity markets and higher
correlation between the commodity and the stock market could result in higher
spot prices and lower forward premia.
The context-dependence of mutations: a linkage of formalisms
Date: 2015-04-22 00:00:00

Defining the extent of epistasis - the non-independence of the effects of
mutations - is essential for understanding the relationship of genotype,
phenotype, and fitness in biological systems. The applications cover many areas
of biological research, including biochemistry, genomics, protein and systems
engineering, medicine, and evolutionary biology. However, the quantitative
definitions of epistasis vary among fields, and its analysis beyond just
pairwise effects remains obscure in general. Here, we show that different
definitions of epistasis are versions of a single mathematical formalism - the
weighted Walsh-Hadamard transform. We discuss that one of the definitions, the
backgound-averaged epistasis, is the most informative when the goal is to
uncover the general epistatic structure of a biological system, a description
that can be rather different from the local epistatic structure of specific
model systems. Key issues are the choice of effective ensembles for averaging
and to practically contend with the vast combinatorial complexity of mutations.
In this regard, we discuss possible approaches for optimally learning the
epistatic structure of biological systems.
Predicting the extinction of Ebola spreading in Liberia due to mitigation strategies
Date: 2015-07-21 00:00:00

The Ebola virus is spreading throughout West Africa and is causing thousands
of deaths. In order to quantify the effectiveness of different strategies for
controlling the spread, we develop a mathematical model in which the
propagation of the Ebola virus through Liberia is caused by travel between
counties. For the initial months in which the Ebola virus spreads, we find that
the arrival times of the disease into the counties predicted by our model are
compatible with World Health Organization data, but we also find that reducing
mobility is insufficient to contain the epidemic because it delays the arrival
of Ebola virus in each county by only a few weeks. We study the effect of a
strategy in which safe burials are increased and effective hospitalisation
instituted under two scenarios: (i) one implemented in mid-July 2014 and (ii)
one in mid-August---which was the actual time that strong interventions began
in Liberia. We find that if scenario (i) had been pursued the lifetime of the
epidemic would have been three months shorter and the total number of infected
individuals 80\% less than in scenario (ii). Our projection under scenario (ii)
is that the spreading will stop by mid-spring 2015.
SBtab - Conventions for structured data tables in Systems Biology
Date: 2015-09-29 00:00:00

Data tables in the form of spreadsheets or delimited text files are the most
utilised data format in Systems Biology. However, they are often not
sufficiently structured and lack clear naming conventions that would be
required for modelling. We propose the SBtab format as an attempt to establish
an easy-to-use table format that is both flexible and clearly structured. It
comprises defined table types for different kinds of data; syntax rules for
usage of names, shortnames, and database identifiers used for annotation; and
standardised formulae for reaction stoichiometries. Predefined table types can
be used to define biochemical network models and the biochemical constants
therein. The user can also define own table types, adjusting SBtab to other
types of data. Software code, tools, and further information can be found at
www.sbtab.net.
Weighted Elastic Net Penalized Mean-Variance Portfolio Design and Computation
Date: 2015-10-15 00:00:00

It is well known that the out-of-sample performance of Markowitz's
mean-variance portfolio criterion can be negatively affected by estimation
errors in the mean and covariance. In this paper we address the problem by
regularizing the mean-variance objective function with a weighted elastic net
penalty. We show that the use of this penalty can be motivated by a robust
reformulation of the mean-variance criterion that directly accounts for
parameter uncertainty. With this interpretation of the weighted elastic net
penalty we derive data driven techniques for calibrating the weighting
parameters based on the level of uncertainty in the parameter estimates. We
test our proposed technique on US stock return data and our results show that
the calibrated weighted elastic net penalized portfolio outperforms both the
unpenalized portfolio and uniformly weighted elastic net penalized portfolio.
  This paper also introduces a novel Adaptive Support Split-Bregman approach
which leverages the sparse nature of $\ell_{1}$ penalized portfolios to
efficiently compute a solution of our proposed portfolio criterion. Numerical
results show that this modification to the Split-Bregman algorithm results in
significant improvements in computational speed compared with other techniques.
The search for candidate relevant subsets of variables in complex systems
Date: 2015-01-27 00:00:00
Tasks: Time Series Analysis

In this paper we describe a method to identify "relevant subsets" of
variables, useful to understand the organization of a dynamical system. The
variables belonging to a relevant subset should have a strong integration with
the other variables of the same relevant subset, and a much weaker interaction
with the other system variables. On this basis, extending previous works on
neural networks, an information-theoretic measure is introduced, i.e. the
Dynamical Cluster Index, in order to identify good candidate relevant subsets.
The method does not require any previous knowledge of the relationships among
the system variables, but relies on observations of their values in time. We
show its usefulness in several application domains, including: (i) random
boolean networks, where the whole network is made of different subnetworks with
different topological relationships (independent or interacting subnetworks);
(ii) leader-follower dynamics, subject to noise and fluctuations; (iii)
catalytic reaction networks in a flow reactor; (iv) the MAPK signaling pathway
in eukaryotes. The validity of the method has been tested in cases where the
data are generated by a known dynamical model and the Dynamical Cluster Index
method is applied in order to uncover significant aspects of its organization;
however it is important to stress that it can also be applied to time series
coming from field data without any reference to a model. Given that it is based
on relative frequencies of sets of values, the method could be applied also to
cases where the data are not ordered in time. Several indications to improve
the scope and effectiveness of the Dynamical Cluster Index to analyze the
organization of complex systems are finally given.
Convex duality with transaction costs
Date: 2015-10-17 00:00:00

Convex duality for two two different super--replication problems in a
continuous time financial market with proportional transaction cost is proved.
In this market, static hedging in a finite number of options, in addition to
usual dynamic hedging with the underlying stock, are allowed. The first one the
problems considered is the model--independent hedging that requires the
super--replication to hold for every continuous path. In the second one the
market model is given through a probability measure P and the inequalities are
understood P almost surely. The main result, using the convex duality, proves
that the two super--replication problems have the same value provided that P
satisfies the conditional full support property. Hence, the transaction costs
prevents one from using the structure of a specific model to reduce the
super--replication cost.
Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study
Date: 2015-07-30 00:00:00
Tasks: parameter estimation

The last decade has seen an explosion in models that describe phenomena in
systems medicine. Such models are especially useful for studying signaling
pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to
showcase current mathematical and statistical techniques that enable modelers
to gain insight into (models of) gene regulation, and generate testable
predictions. We introduce a range of modeling frameworks, but focus on ordinary
differential equation (ODE) models since they remain the most widely used
approach in systems biology and medicine and continue to offer great potential.
We present methods for the analysis of a single model, comprising applications
of standard dynamical systems approaches such as nondimensionalization, steady
state, asymptotic and sensitivity analysis, and more recent statistical and
algebraic approaches to compare models with data. We present parameter
estimation and model comparison techniques, focusing on Bayesian analysis and
coplanarity via algebraic geometry. Our intention is that this (non exhaustive)
review may serve as a useful starting point for the analysis of models in
systems medicine.