pwc-archive/papers-with-abstracts huggingface dataset:
What is the Contribution of Intra-household Inequality to Overall Income Inequality? Evidence from Global Data, 1973-2013
Date: 2016-08-29 00:00:00

Intra-household inequality continues to remain a neglected corner despite
renewed focus on income and wealth inequality. Using the LIS micro data, we
present evidence that this neglect is equivalent to ignoring up to a third of
total inequality. For a wide range of countries and over four decades, we show
that at least 30 per cent of total inequality is attributable to inequality
within the household. Using a simple normative measure of inequality, we
comment on the welfare implications of these trends.
On the Market-Neutrality of Optimal Pairs-Trading Strategies
Date: 2016-08-29 00:00:00

We consider the problem of optimal investment in a market with two
cointegrated stocks and an agent with CRRA utility. We extend the findings of
Liu and Timmermann [The Review of Financial Studies, 26(4):1048-1086, 2013] by
paying special attention to when/if the associated stochastic control problem
is well-posed and providing a verification result. Our new findings lead to a
sharp well-posedness condition which is, surprisingly, also the necessary and
sufficient condition for the optimal investment to be market-neutral (i.e.
having offsetting long/short positions in the stocks). Hence, we provide a
theoretical justification for market-neutral pairs-trading which, despite
having a strong practical relevance, has been lacking a theoretical ground.
Risk measures and Margining control
Date: 2016-08-29 00:00:00

This document constitutes the final report of the contractual activity
between Directa SIM and Dipartimento di Automatica e Informatica, Politecnico
di Torino, on the research topic titled "quantificazione del rischio di un
portafoglio di strumenti finanziari per trading online su device fissi e
mobili."
Cooperativity and modularity in protein folding
Date: 2016-08-30 00:00:00
Tasks: Protein Folding

A simple statistical mechanical model proposed by Wako and Sait$\hat{\rm o}$
has explained the aspects of protein folding surprisingly well. This model was
systematically applied to multiple proteins by Mu$\tilde{\rm n}$oz and Eaton
and has since been referred to as the Wako-Sait$\hat{\rm o}$-Mu$\tilde{\rm
n}$oz-Eaton (WSME) model. The success of the WSME model in explaining the
folding of many proteins has verified the hypothesis that the folding is
dominated by native interactions, which makes the energy landscape globally
biased toward native conformation. Using the WSME and other related models,
Sait$\hat{\rm o}$ emphasized the importance of the hierarchical pathway in
protein folding; folding starts with the creation of contiguous segments having
a native-like configuration and proceeds as growth and coalescence of these
segments. The $\phi$-values calculated for barnase with the WSME model
suggested that segments contributing to the folding nucleus are similar to the
structural modules defined by the pattern of native atomic contacts. The WSME
model was extended to explain folding of multi-domain proteins having a complex
topology, which opened the way to comprehensively understanding the folding
process of multi-domain proteins. The WSME model was also extended to describe
allosteric transitions, indicating that the allosteric structural movement does
not occur as a deterministic sequential change between two conformations but as
a stochastic diffusive motion over the dynamically changing energy landscape.
Statistical mechanical viewpoint on folding, as highlighted by the WSME model,
has been renovated in the context of modern methods and ideas, and will
continue to provide insights on equilibrium and dynamical features of proteins.
Breakdown of local information processing may underlie isoflurane anesthesia effects
Date: 2017-03-30 00:00:00

The disruption of coupling between brain areas has been suggested as the
mechanism underlying loss of consciousness in anesthesia. This hypothesis has
been tested previously by measuring the information transfer between brain
areas, and by taking reduced information transfer as a proxy for decoupling.
Yet, information transfer is a function of the amount of information available
in the information source-such that transfer decreases even for unchanged
coupling when less source information is available. Therefore, we asked whether
impaired local information processing leads to a loss of information transfer.
An important prediction of this alternative hypothesis is that changes in
locally available information (signal entropy) should be at least as pronounced
as changes in information transfer. We tested this prediction by recording
local field potentials in two ferrets after administration of isoflurane in
concentrations of 0.0 %, 0.5 %, and 1.0 %.
  We found strong decreases in the source entropy under isoflurane in area V1
and the prefrontal cortex (PFC)-as predicted by our alternative hypothesis. The
decrease in source entropy was stronger in PFC. Information transfer between V1
and PFC was reduced bidirectionally, but with a stronger decrease from PFC to
V1. This links the stronger decrease in information transfer to the stronger
decrease in source entropy, suggesting reduced source entropy reduces
information transfer. This conclusion fits the observation that the synaptic
targets of isoflurane are located in local cortical circuits rather than on the
synapses formed by interareal axonal projections. Thus, changes in information
transfer under isoflurane seem to be a consequence of changes in local
processing more than of decoupling between brain areas. We suggest that source
entropy changes must be considered whenever interpreting changes in information
transfer as decoupling.
Multi-period investment strategies under Cumulative Prospect Theory
Date: 2019-03-22 00:00:00
Tasks: Sensitivity

In this article, inspired by Shi, et al. we investigate the optimal portfolio
selection with one risk-free asset and one risky asset in a multiple period
setting under cumulative prospect theory (CPT). Compared with their study, our
novelty is that we consider a stochastic benchmark, and portfolio constraints.
We test the sensitivity of the optimal CPT-investment strategies to different
model parameters by performing a numerical analysis.
Systemic stability, cell differentiation, and evolution - A dynamical systems perspective
Date: 2016-08-30 00:00:00

Species or population that proliferate faster than others become dominant in
numbers. Catalysis allows catalytic sets within a molecular reaction network to
dominate the non catalytic parts of the network by processing most of the
available substrate. As a consequence one may consider a 'catalytic fitness' of
sets of molecular species. The fittest sets emerge as the expressed chemical
backbone or sub-network of larger chemical reaction networks employed by
organisms. However, catalytic fitness depends on the systemic context and the
stability of systemic dynamics. Unstable reaction networks would easily be
reshaped or destroyed by fluctuations of the chemical environment. In this
paper we therefore focus on recognizing systemic stability as an evolutionary
selection criterion. In fact, instabilities of regulatory systems dynamics
become predictive for associated evolutionary forces driving the emergence
large reaction networks that avoid or control inherent instabilities. Systemic
instabilities can be identified and analyzed using relatively simple
mathematical random networks models of complex regulatory systems. Using a
statistical ensemble approach one can identify fundamental causes of instable
dynamics, infer evolutionary preferred network properties, and predict
evolutionary emergent control mechanisms and their entanglement with cell
differentiation processes. Surprisingly, what systemic stability tells us here
is that cells (or other non-linear regulatory systems) never had to learn how
to differentiate, but rather how to avoid and control differentiation. For
example, in this framework we can predict that regulatory systems will
evolutionary favor networks where the number of catalytic enhancers is not
larger than the number of suppressors.
TLR-exosomes exhibit distinct kinetics and effector function
Date: 2016-08-10 00:00:00

The innate immune system is vital to rapidly responding to pathogens and
Toll-like receptors (TLRs) are a critical component of this response.
Nanovesicular exosomes play a role in immunity, but to date their exact
contribution to the dissemination of the TLR response is unknown. Here we show
that exosomes from TLR stimulated cells (TLR-exosomes) can largely recapitulate
TLR activation in distal cells in vitro. We can abrogate the
action-at-a-distance signaling of exosomes by UV irradiation, demonstrating
that RNA is crucial for their effector function. We are the first to show that
exosomes derived from poly(I:C) stimulated cells induce in vivo macrophage
M1-like polarization within murine lymph nodes. These TLR-exosomes demonstrate
enhanced trafficking to the node and preferentially recruit neutrophils as
compared to control-exosomes. This work definitively establishes the
differential effector function for TLR-exosomes in communicating the activation
state of the cell of origin.
The influence of the composition of tradeoffs on the generation of differentiated cells
Date: 2016-08-30 00:00:00

We study the emergence of cell differentiation under the assumption of the
existence of a given number of tradeoffs between genes encoding different
functions. In the model the viability of colonies is determined by the
capability of their lower level units to perform different functions, which is
implicitly determined by external chemical stimuli. Due to the existence of
tradeoffs it can be evolutionarily advantageous to evolve the division of labor
whereby the cells can suppress their contributions to some of the activities
through the activation of regulatory genes, which in its turn inflicts a cost
in terms of fitness. Our simulation results show that cell differentiation is
more likely as the number of tradeoffs is increased but the outcome also
depends on their strength. We observe the existence of critical values for the
minimum number of tradeoffs and their strength beyond that maximum cell
differentiation can be attained. Remarkably, we observe the occurrence of a
maximum tradeoff strength beyond that the population is no longer viable
imposing an upper tolerable level of constraint at the system. This tolerance
is reduced as the number of tradeoffs grows.
LiRa: A New Likelihood-Based Similarity Score for Collaborative Filtering
Authors: Strnadova-Neeley Veronika, Buluc Aydin, Gilbert John R., Oliker Leonid, Ouyang Weimin
Date: 2017-03-20 00:00:00
Tasks: Collaborative Filtering, Missing Values, Recommendation Systems

Recommender system data presents unique challenges to the data mining,
machine learning, and algorithms communities. The high missing data rate, in
combination with the large scale and high dimensionality that is typical of
recommender systems data, requires new tools and methods for efficient data
analysis. Here, we address the challenge of evaluating similarity between two
users in a recommender system, where for each user only a small set of ratings
is available. We present a new similarity score, that we call LiRa, based on a
statistical model of user similarity, for large-scale, discrete valued data
with many missing values. We show that this score, based on a ratio of
likelihoods, is more effective at identifying similar users than traditional
similarity scores in user-based collaborative filtering, such as the Pearson
correlation coefficient. We argue that our approach has significant potential
to improve both accuracy and scalability in collaborative filtering.
Epidemic extinction in a generalized susceptible-infected-susceptible model
Date: 2016-11-29 00:00:00

We study the extinction of epidemics in a generalized
susceptible-infected-susceptible model, where a susceptible individual becomes
infected with the rate $\lambda$ when contacting $m$ infective individual(s)
simultaneously, and an infected individual spontaneously recovers with the rate
$\mu$. By employing the Wentzel-Kramers-Brillouin approximation for the master
equation, the problem is reduced to finding the zero-energy trajectories in an
effective Hamiltonian system, and the mean extinction time $\langle T\rangle$
depends exponentially on the associated action $\mathcal {S}$ and the size of
the population $N$, $\langle T\rangle \sim \exp(N\mathcal {S})$. Because of
qualitatively different bifurcation features for $m=1$ and $m\geq2$, we derive
independently the expressions of $\mathcal {S}$ as a function of the rescaled
infection rate $\lambda/\mu$. For the weak infection, $\mathcal {S}$ scales to
the distance to the bifurcation with an exponent $2$ for $m=1$ and $3/2$ for
$m\geq2$. Finally, a rare-event simulation method is used to validate the
theory.
The multilayer connectome of Caenorhabditis elegans
Date: 2016-08-31 00:00:00

Connectomics has focused primarily on the mapping of synaptic links in the
brain; yet it is well established that extrasynaptic volume transmission,
especially via monoamines and neuropeptides, is also critical to brain
function. Here we present a draft monoamine connectome, along with a partial
neuropeptide connectome, for the nematode C. elegans, based on new and
published expression data for biosynthetic genes and receptors. Thus, the
neuronal connectome can be represented as a multiplex network, with synaptic,
gap junction, and neuromodulatory layers representing alternative modes of
interneuronal interaction and with distinct network structures. In particular,
the monoamine network exhibits novel topological properties, with a highly
disassortative star-like structure and a rich-club of interconnected
broadcasting hubs. Despite the low degree of overlap between layers, we find
highly significant modes of interaction, pinpointing network locations and
multilink motifs where aminergic and neuropeptide signalling modulate synaptic
activity. The multilayer connectome of C. elegans represents a clear exemplar
of a biological multiplex network and provides a prototype for understanding
how extrasynaptic signalling can be integrated into the wired circuitry in
larger brains.
The Influence of Mobility Rate on Spiral Waves in Spatial Rock-Paper-Scissors Games
Date: 2016-09-12 00:00:00

We consider a two-dimensional model of three species in rock-paper-scissors
competition and study the self-organisation of the population into fascinating
spiraling patterns. Within our individual-based metapopulation formulation, the
population composition changes due to cyclic dominance (dominance-removal and
dominance-replacement), mutations, and pair-exchange of neighboring
individuals. Here, we study the influence of mobility on the emerging patterns
and investigate when the pair-exchange rate is responsible for spiral waves to
become elusive in stochastic lattice simulations. In particular, we show that
the spiral waves predicted by the system's deterministic partial equations are
found in lattice simulations only within a finite range of the mobility rate.
We also report that in the absence of mutations and dominance-replacement, the
resulting spiraling patterns are subject to convective instability and
far-field breakup at low mobility rate. Possible applications of these
resolution and far-field breakup phenomena are discussed.
The dynamics of starvation and recovery
Date: 2017-11-10 00:00:00

The eco-evolutionary dynamics of species are fundamentally linked to the
energetic constraints of its constituent individuals. Of particular importance
is the interplay between reproduction and the dynamics of starvation and
recovery. To elucidate this interplay, we introduce a nutritional
state-structured model that incorporates two classes of consumer: nutritionally
replete, reproducing consumers, and undernourished, non-reproducing consumers.
We obtain strong constraints on starvation and recovery rates by deriving
allometric scaling relationships and find that population dynamics are
typically driven to a steady state. Moreover, these rates fall within a
'refuge' in parameter space, where the probability of population extinction is
minimized. We also show that our model provides a natural framework to predict
maximum mammalian body size by determining the relative stability of an
otherwise homogeneous population to a competing population with altered percent
body fat. This framework provides a principled mechanism for a selective driver
of Cope's rule.
Understanding the behavioural difference of PPCA among its homologs in C7 family towards recognition of DXCA
Date: 2015-09-17 00:00:00

Among all the proteins of Periplasmic C type cytochrome A (PPCA) family
obtained from cytochrome C7 found in Geobacter sulfurreducens, PPCA protein can
interact with Deoxycholate (DXCA), while its other homologs do not, as observed
from the crystal structures. Utilizing the concept of 'structure-function
relationship', an effort has been initiated towards understanding the driving
force for recognition of DXCA exclusively by PPCA among its homologs. Further,
a combinatorial analysis of the binding sequences (contiguous sequence of amino
acid residues of binding locations) is performed to build graph-theoretic
models, which show that PPCA differs from its homologues. Analysis of the
results suggests that the underlying impetus of recognition of DXCA by PPCA is
embedded in its primary sequence and 3D conformation.
Properties of low-dimensional collective variables in the molecular dynamics of biopolymers
Date: 2016-11-28 00:00:00

The description of the dynamics of a complex, high-dimensional system in
terms of a low-dimensional set of collective variables Y can be fruitful if the
low dimensional representation satisfies a Langevin equation with drift and
diffusion coefficients which depend only on Y. We present a computational
scheme to evaluate whether a given collective variable provides a faithful
low-dimensional representation of the dynamics of a high-dimensional system.
The scheme is based on the framework of finite-difference Langevin-equation,
similar to that used for molecular-dynamics simulations. This allows one to
calculate the drift and diffusion coefficients in any point of the
full-dimensional system. The width of the distribution of drift and diffusion
coefficients in an ensemble of microscopic points at the same value of Y
indicates to which extent the dynamics of Y is described by a simple Langevin
equation. Using a simple protein model we show that collective variables often
used to describe biopolymers display a non-negligible width both in the drift
and in the diffusion coefficients. We also show that the associated effective
force is compatible with the equilibrium free--energy calculated from a
microscopic sampling, but results in markedly different dynamical properties.
Species coexistence in a neutral dynamics with environmental noise
Date: 2016-11-15 00:00:00

Environmental fluctuations have important consequences in the organization of
ecological communities, and understanding how such a variability influences the
biodiversity of an ecosystem is a major question in ecology. In this paper, we
analyze the case of two species competing for the resources within the
framework of the neutral theory in the presence of environmental noise,
devoting special attention on how such a variability modulates species fitness.
The environment is dichotomous and stochastically alternates between periods
favoring one of the species while disfavoring the other one, preserving
neutrality on the long term. We study two different scenarios: in the first one
species fitness varies linearly with the environment, and in the second one the
effective fitness is re-scaled by the total fitness of the individuals
competing for the same resource. We find that, in the former case environmental
fluctuations always reduce the time of species coexistence, whereas such a time
can be enhanced or reduced in the latter case, depending on the correlation
time of the environment. This phenomenon can be understood as a direct
consequence of Chesson's storage effect.
Optimal Execution in a Multiplayer Model of Transient Price Impact
Date: 2019-03-10 00:00:00

Trading algorithms that execute large orders are susceptible to exploitation
by order anticipation strategies. This paper studies the influence of order
anticipation strategies in a multi-investor model of optimal execution under
transient price impact. Existence and uniqueness of a Nash equilibrium is
established under the assumption that trading incurs quadratic transaction
costs. A closed-form representation of the Nash equilibrium is derived for
exponential decay kernels. With this representation, it is shown that while
order anticipation strategies raise the execution costs of a large order
significantly, they typically do not cause price overshooting in the sense of
Brunnermeier and Pedersen.
Fast Online Deconvolution of Calcium Imaging Data
Date: 2017-03-16 00:00:00
Tasks: Time Series, Time Series Analysis

Fluorescent calcium indicators are a popular means for observing the spiking
activity of large neuronal populations, but extracting the activity of each
neuron from raw fluorescence calcium imaging data is a nontrivial problem. We
present a fast online active set method to solve this sparse non-negative
deconvolution problem. Importantly, the algorithm progresses through each time
series sequentially from beginning to end, thus enabling real-time online
estimation of neural activity during the imaging session. Our algorithm is a
generalization of the pool adjacent violators algorithm (PAVA) for isotonic
regression and inherits its linear-time computational complexity. We gain
remarkable increases in processing speed: more than one order of magnitude
compared to currently employed state of the art convex solvers relying on
interior point methods. Unlike these approaches, our method can exploit warm
starts; therefore optimizing model hyperparameters only requires a handful of
passes through the data. A minor modification can further improve the quality
of activity inference by imposing a constraint on the minimum spike size. The
algorithm enables real-time simultaneous deconvolution of $O(10^5)$ traces of
whole-brain larval zebrafish imaging data on a laptop.
On the quantum principles of cognitive learning
Date: 2016-08-14 00:00:00

Pothos & Busemeyer's (P&B's) query about whether quantum probability can
provide a foundation for the cognitive modeling embodies so many underlying
implications that the subject is far from exhausted. In this brief commentary,
however, I suggest that the conceptual thresholds of the meaningful learning
give rise to a typical Boltzmann's weighting measure, which indicates a
statistical verisimilitude of quantum behavior in the human cognitive ensemble.
Numerical solution of a semilinear parabolic degenerate Hamilton-Jacobi-Bellman equation with singularity
Date: 2016-09-22 00:00:00

We consider a semilinear parabolic degenerated Hamilton-Jacobi-Bellman (HJB)
equation with singularity which is related to a stochastic control problem with
fuel constraint. The fuel constraint translates into a singular initial
condition for the HJB equation. We first propose a transformation based on a
change of variables that gives rise to an equivalent HJB equation with
nonsingular initial condition but irregular coefficients. We then construct
explicit and implicit numerical schemes for solving the transformed HJB
equation and prove their convergences by establishing an extension to the
result of Barles and Souganidis (1991).