pwc-archive/papers-with-abstracts huggingface dataset:
Modeling of Sensory Characteristics Based on the Growth of Food Spoilage Bacteria
Date: 2016-09-23 00:00:00
Tasks: Open-Ended Question Answering

During last years theoretical works shed new light and proposed new
hypothesis on the mechanisms which regulate the time behaviour of biological
populations in different natural systems. Despite of this, the role of
environmental variables in ecological systems is still an open question.
Filling this gap of knowledge is a crucial task for a deeper comprehension of
the dynamics of biological populations in real ecosystems. In this work we
study how the dynamics of food spoilage bacteria influences the sensory
characteristics of fresh fish specimens. This topic is crucial for a better
understanding of the role played by the bacterial growth on the organoleptic
properties, and for the quality evaluation and risk assessment of food
products. We therefore analyze the time behaviour, in fresh fish specimens, of
sensory characteristics starting from the growth curves of two spoilage
bacterial communities. The theoretical study, initially based on a
deterministic model, exploits experimental temperature profiles. As a first
step, a model of predictive microbiology is used to reproduce the experimental
behaviour of the two bacterial populations. Afterwards, the theoretical
bacterial growths are converted, through suitable differential equations, into
"sensory" scores, based on the Quality Index Method (QIM), a scoring system for
freshness and quality sensory estimation of fishery products. As a third step,
the theoretical curves of QIM scores are compared with the experimental data
obtained by sensory analysis. Finally, the differential equations for QIM
scores are modified by adding terms of multiplicative white noise, which mimics
the effects of uncertainty and variability in sensory analysis. A better
agreement between experimental and theoretical QIM scores is observed, in some
cases, in the presence of suitable values of noise intensity respect to the
deterministic analysis.
Effect of gene-expression bursts on stochastic timing of cellular events
Date: 2016-09-23 00:00:00

Gene expression is inherently a noisy process which manifests as cell-to-cell
variability in time evolution of proteins. Consequently, events that trigger at
critical threshold levels of regulatory proteins exhibit stochasticity in their
timing. An important contributor to the noise in gene expression is translation
bursts which correspond to randomness in number of proteins produced in a
single mRNA lifetime. Modeling timing of an event as a first-passage time (FPT)
problem, we explore the effect of burst size distribution on event timing.
Towards this end, the probability density function of FPT is computed for a
gene expression model with burst size drawn from a generic non-negative
distribution. Analytical formulas for FPT moments are provided in terms of
known vectors and inverse of a matrix. The effect of burst size distribution is
investigated by looking at how the feedback regulation strategy that minimizes
noise in timing around a given time deviates from the case when burst is
deterministic. Interestingly, results show that the feedback strategy for
deterministic burst case is quite robust to change in burst size distribution,
and deviations from it are confined to about 20% of the optimal value. These
findings facilitate an improved understanding of noise regulation in event
timing.
Bone fusion in normal and pathological development is constrained by the network architecture of the human skull
Date: 2016-12-27 00:00:00
Tasks: Bayesian Inference

The premature fusion of cranial bones, craniosynostosis, affects the correct
development of the skull producing morphological malformations in newborns. To
assess the susceptibility of each craniofacial articulation to close
prematurely, we used a network model of the skull to quantify the link
reliability (an index based on stochastic block modeling and Bayesian
inference) of each articulation. We show that, of the 93 human skull
articulations at birth, the few articulations that are associated with
nonsyndromic craniosynostosis conditions have statistically significant lower
reliability scores than the others. In a similar way, articulations that close
during the normal postnatal development of the skull have also lower
reliability scores than those articulations that persist through adult live.
These results indicate a relationship between the architecture of the skull
network and the specific articulations that close during normal development and
in pathological conditions. Our findings suggest that the topological
arrangement of skull bones might act as an epigenetic factor, predisposing some
articulations to closure, both in normal and pathological development, and also
affecting the long-term evolution of the skull.
Discrete Sums of Geometric Brownian Motions, Annuities and Asian Options
Date: 2016-09-24 00:00:00

The discrete sum of geometric Brownian motions plays an important role in
modeling stochastic annuities in insurance. It also plays a pivotal role in the
pricing of Asian options in mathematical finance. In this paper, we study the
probability distributions of the infinite sum of geometric Brownian motions,
the sum of geometric Brownian motions with geometric stopping time, and the
finite sum of the geometric Brownian motions. These results are extended to the
discrete sum of the exponential L\'evy process. We derive tail asymptotics and
compute numerically the asymptotic distribution function. We compare the
results against the known results for the continuous time integral of the
geometric Brownian motion up to an exponentially distributed time. The results
are illustrated with numerical examples for life annuities with discrete
payments, and Asian options.
Short Maturity Asian Options in Local Volatility Models
Date: 2016-09-24 00:00:00

We present a rigorous study of the short maturity asymptotics for Asian
options with continuous-time averaging, under the assumption that the
underlying asset follows a local volatility model. The asymptotics for
out-of-the-money, in-the-money, and at-the-money cases are derived, considering
both fixed strike and floating strike Asian options. The asymptotics for the
out-of-the-money case involves a non-trivial variational problem which is
solved completely. We present an analytical approximation for Asian options
prices, and demonstrate good numerical agreement of the asymptotic results with
the results of Monte Carlo simulations and benchmark test cases in the
Black-Scholes model for option parameters relevant in practical applications.
Associative Memory Impairments arising from Neurodegenerative Diseases and Traumatic Brain Injuries in a Hopfield Network Model
Date: 2016-09-24 00:00:00
Tasks: Diagnostic, Face Recognition

Neurodegenerative diseases and traumatic brain injuries (TBI) are among the
main causes of cognitive dysfunction in humans. Both manifestations exhibit the
extensive presence of focal axonal swellings (FAS). FAS compromises the
information encoded in spike trains, thus leading to potentially severe
functional deficits. Complicating our understanding of the impact of FAS is our
inability to access small scale injuries with non-invasive methods, the overall
complexity of neuronal pathologies, and our limited knowledge of how networks
process biological signals. Building on Hopfield's pioneering work, we extend a
model for associative memory to account for FAS and its impact on memory
encoding. We calibrate all FAS parameters from biophysical observations of
their statistical distribution and size, providing a framework to simulate the
effects of brain disorders on memory recall performance. A face recognition
example is used to demonstrate and validate the functionality of the novel
model. Our results link memory recall ability to observed FAS statistics,
allowing for a description of different stages of brain disorders within
neuronal networks. This provides a first theoretical model to bridge
experimental observations of FAS in neurodegeneration and TBI with compromised
memory recall, thus closing the large gap between theory and experiment on how
biological signals are processed in damaged, high-dimensional functional
networks. The work further lends new insight into positing diagnostic tools to
measure cognitive deficits.
Strategies for the Simulation of Sea Ice Organic Chemistry: Arctic Tests and Development
Date: 2016-09-25 00:00:00
Tasks: Geochemistry

A mechanism connecting ice algal ecodynamics with the buildup of organic
macromolecules in brine channels is tested offline in a reduced model of pack
geochemistry. Driver physical quantities are extracted from the global sea ice
dynamics code CICE, including snow height, column thickness and internal
temperature. The variables are averaged at the regional scale over ten Arctic
biogeographic zones and treated as input matrices at four vertical habitat
levels. Nutrient-light-salt limited ice algal growth is computed along with the
associated grazing plus mortality. Vertical transport is diffusive but responds
to pore structure. Simulated bottom layer chlorophyll maxima are reasonable,
though delayed by about a month relative to observations. This highlights major
uncertainties deriving from snow thickness variability. Upper level biota are
generated intermittently through flooding. Macromolecular injections are
represented by the compound classes humics, proteins, polysaccharides and
lipids. The fresh biopolymers behave in a successional manner and are removed
by bacteria. In baseline runs, organics are introduced solely through cell
disruption, and internal carbon is biased low. Continuous exudation is
therefore appended, and agreement with dissolved organic or individual
biopolymer measurements is achieved when strong release is coupled to light
availability. Detrital carbon then reaches hundreds of micromolar, sufficient
to support physical changes to the ice matrix. Through this optimized model
version we address the question, are high molecular weight organics added to
the brine network over and above background spillage? The mechanism is
configured for ready extension to the Antarctic, so that global ice organic
chemistry issues can be targeted.
Variance-corrected Michaelis-Menten equation predicts transient rates of single-enzyme reactions and response times in bacterial gene-regulation
Date: 2016-09-26 00:00:00

Many chemical reactions in biological cells occur at very low concentrations
of constituent molecules. Thus, transcriptional gene-regulation is often
controlled by poorly expressed transcription-factors, such as E.coli lac
repressor with few tens of copies. Here we study the effects of inherent
concentration fluctuations of substrate-molecules on the seminal
Michaelis-Menten scheme of biochemical reactions. We present a universal
correction to the Michaelis-Menten equation for the reaction-rates. The
relevance and validity of this correction for enzymatic reactions and
intracellular gene-regulation is demonstrated. Our analytical theory and
simulation results confirm that the proposed variance-corrected
Michaelis-Menten equation predicts the rate of reactions with remarkable
accuracy even in the presence of large non-equilibrium concentration
fluctuations. The major advantage of our approach is that it involves only the
mean and variance of the substrate-molecule concentration. Our theory is
therefore accessible to experiments and not specific to the exact source of the
concentration fluctuations.
A single predator charging a herd of prey: effects of self volume and predator-prey decision-making
Date: 2016-09-26 00:00:00
Tasks: Decision Making

We study the degree of success of a single predator hunting a herd of prey on
a two dimensional square lattice landscape. We explicitly consider the self
volume of the prey restraining their dynamics on the lattice. The movement of
both predator and prey is chosen to include an intelligent, decision making
step based on their respective sighting ranges, the radius in which they can
detect the other species (prey cannot recognise each other besides the self
volume interaction): after spotting each other the motion of prey and predator
turns from a nearest neighbour random walk into direct escape or chase,
respectively. We consider a large range of prey densities and sighting ranges
and compute the mean first passage time for a predator to catch a prey as well
as characterise the effective dynamics of the hunted prey. We find that the
prey's sighting range dominates their life expectancy and the predator profits
more from a bad eyesight of the prey than from his own good eye sight. We
characterise the dynamics in terms of the mean distance between the predator
and the nearest prey. It turns out that effectively the dynamics of this
distance coordinate can be captured in terms of a simple Ornstein-Uhlenbeck
picture. Reducing the many-body problem to a simple two-body problem by
imagining predator and nearest prey to be connected by a Hookean bond, all
features of the model such as prey density and sighting ranges merge into the
effective binding constant.
Risk-Consistent Conditional Systemic Risk Measures
Date: 2016-09-26 00:00:00

We axiomatically introduce risk-consistent conditional systemic risk measures
defined on multidimensional risks. This class consists of those conditional
systemic risk measures which can be decomposed into a state-wise conditional
aggregation and a univariate conditional risk measure. Our studies extend known
results for unconditional risk measures on finite state spaces. We argue in
favor of a conditional framework on general probability spaces for assessing
systemic risk. Mathematically, the problem reduces to selecting a realization
of a random field with suitable properties. Moreover, our approach covers many
prominent examples of systemic risk measures from the literature and used in
practice.
The multiplicity of memory enhancement: Practical and ethical implications of the diverse neural substrates underlying human memory systems
Date: 2016-09-26 00:00:00
Tasks: Diversity, Fairness

The neural basis of human memory is incredibly complex. We argue that the
diversity of neural systems underlying various forms of memory suggests that
any discussion of enhancing 'memory' per se is too broad, thus obfuscating the
biopolitical debate about human enhancement. Memory can be differentiated into
at least four major (and several minor) systems with largely dissociable (i.e.,
non-overlapping) neural substrates. We outline each system, and discuss both
the practical and the ethical implications of these diverse neural substrates.
In practice, distinct neural bases imply the possibility, and likely the
necessity, of specific approaches for the safe and effective enhancement of
various memory systems. In the debate over the ethical and social implications
of enhancement technologies, this fine-grained perspective clarifies - and may
partially mitigate - certain common concerns in enhancement debates, including
issues related to safety, fairness, coercion, and authenticity. While many
researchers certainly appreciate the neurobiological complexity of memory, the
political debate tends to revolve around a monolithic one-size-fits-all
conception. The overall project - exploring how human enhancement technologies
affect society - stands to benefit from a deeper appreciation of memory's
neurobiological diversity.
Random-phase-approximation theory for sequence-dependent, biologically functional liquid-liquid phase separation of intrinsically disordered proteins
Date: 2016-09-26 00:00:00

Intrinsically disordered proteins (IDPs) are typically low in
nonpolar/hydrophobic but relatively high in polar, charged, and aromatic amino
acid compositions. Some IDPs undergo liquid-liquid phase separation in the
aqueous milieu of the living cell. The resulting phase with enhanced IDP
concentration can function as a major component of membraneless organelles
that, by creating their own IDP-rich microenvironments, stimulate critical
biological functions. IDP phase behaviors are governed by their amino acid
sequences. To make progress in understanding this sequence-phase relationship,
we report further advances in a recently introduced application of
random-phase-approximation (RPA) heteropolymer theory to account for
sequence-specific electrostatics in IDP phase separation. Here we examine
computed variations in phase behavior with respect to block length and charge
density of model polyampholytes of alternating equal-length charge blocks to
gain insight into trends observed in IDP phase separation. As a real-life
example, the theory is applied to rationalize/predict binodal and spinodal
phase behaviors of the 236-residue N-terminal disordered region of RNA helicase
Ddx4 and its charge-scrambled mutant for which experimental data are available.
Fundamental differences are noted between the phase diagrams predicted by RPA
and those predicted by mean-field Flory-Huggins and
Overbeek-Voorn/Debye-H\"uckel theories. In the RPA context, a physically
plausible dependence of relative permittivity on protein concentration can
produce a cooperative effect in favor of IDP-IDP attraction and thus a
significant increased tendency to phase separate. Ramifications of these
findings for future development of IDP phase separation theory are discussed.
Computer Folding of RNA Tetraloops: Identification of Key Force Field Deficiencies
Date: 2016-09-27 00:00:00

The computer-aided folding of biomolecules, particularly RNAs, is one of the
most difficult challenges in computational structural biology. RNA tetraloops
are fundamental RNA motifs playing key roles in RNA folding and RNA-RNA and
RNA-protein interactions. Although state-of-the-art Molecular Dynamics (MD)
force fields correctly describe the native state of these tetraloops as a
stable free-energy basin on the microsecond time scale, enhanced sampling
techniques reveal that the native state is not the global free energy minimum,
suggesting yet unidentified significant imbalances in the force fields. Here,
we tested our ability to fold the RNA tetraloops in various force fields and
simulation settings. We employed three different enhanced sampling techniques,
namely, temperature replica exchange MD (T-REMD), replica exchange with solute
tempering (REST2), and well-tempered metadynamics (WT-MetaD). We aimed to
separate problems caused by limited sampling from those due to force-field
inaccuracies. We found that none of the contemporary force fields is able to
correctly describe folding of the 5'-GAGA-3' tetraloop over a range of
simulation conditions. We thus aimed to identify which terms of the force field
are responsible for this poor description of TL folding. We showed that at
least two different imbalances contribute to this behavior, namely,
overstabilization of base-phosphate and/or sugar-phosphate interactions and
underestimated stability of the hydrogen bonding interaction in base pairing.
The first artifact stabilizes the unfolded ensemble, while the second one
destabilizes the folded state. The former problem might be partially alleviated
by reparametrization of the van der Waals parameters of the phosphate oxygens
suggested by Case et al., while in order to overcome the latter effect we
suggest local potentials to better capture hydrogen bonding interactions.
The accuracy of biochemical interactions is ensured by endothermic stepwise kinetics
Date: 2016-09-27 00:00:00
Tasks: Specificity

The discerning behavior of living systems relies on accurate interactions
selected from the lot of molecular collisions occurring in the cell. To ensure
the reliability of interactions, binding partners are classically envisioned as
finely preadapted molecules, evolutionarily selected on the basis of their
affinity in one-step associations. But the counterselection of inappropriate
interactions can in fact be much more efficiently obtained through difficult
multi-step adjustment, whose final high energy state is locked by a fluctuation
ratchet. The progressive addition of molecular bonds during stereo-adjustment
can be modeled as a predominantly backward random walk whose first arrival is
frozen by a micro-irreversible transition. A new criterion of ligand
specificity is presented, that is based on the ratio rejection/incorporation.
In addition to its role in the selectivity of interactions, this generic recipe
can underlie other important biological phenomena such as the regular synthesis
at low level of supramolecular complexes, monostable kinetic bimodality,
substrate concentration thresholds or the preparation of rapidly
depolymerizable structureswith stored energy, like microtubules.
Conformational selection or induced fit? New insights from old principles
Date: 2016-09-27 00:00:00

A long standing debate in biochemistry is to determine whether the
conformational changes observed during biomolecular interactions proceed
through conformational selection (of preexisting isoforms) or induced fit
(ligand-induced 3D reshaping). The latter mechanism had been invoked in certain
circumstances, for example to explain the non-Michaelian activity of monomeric
enzymes like glucokinase. But the relative importance of induced fit has been
recently depreciated in favor of conformational selection, assumed to be always
sufficient, predominant in general and in particular for glucokinase. The
relative contributions of conformational selection and induced fit are
reconsidered here in and out of equilibrium, in the light of earlier concepts
such as the cyclic equilibrium rule and the turning wheel of Wyman, using
single molecule state probability, one way fluxes and net fluxes. The
conditions for a switch from conformational selection to induced fit at a given
ligand concentration are explicitly determined. Out of equilibrium, the
inspection of the enzyme states circuit shows that conformational selection
alone would give a Michaelian reaction rate but not the established nonlinear
behaviour of glucokinase. Moreover, when induced fit and conformational
selection coexist and allow kinetic cooperativity, the net flux emerging in the
linkage cycle necessarily corresponds to the induced fit path.
Drawing a Waddington landscape to capture dynamic epigenetics
Date: 2016-09-27 00:00:00

Epigenetics is most often reduced to chromatin marking in the current
literature, whereas this notion was initially defined in a more general
context. This restricted view ignores that epigenetic memories are in fact more
robustly ensured in living systems by steady state mechanisms with permanent
molecule renewal. This misconception is likely to result from misleading
intuitions and insufficient dialogues between traditional and quantitative
biologists. To demystify dynamic epigenetics, its most famous image, a
Waddington landscape and its attractors, are explicitly drawn. The simple
example provided is sufficient to highlight the main requirements and
characteristics of dynamic gene networks, underlying cellular differentiation,
de-differentiation and trans-differentiation.