pwc-archive/papers-with-abstracts huggingface dataset:
Training-free Measures Based on Algorithmic Probability Identify High Nucleosome Occupancy in DNA Sequences
Date: 2018-10-16 00:00:00

We introduce and study a set of training-free methods of
information-theoretic and algorithmic complexity nature applied to DNA
sequences to identify their potential capabilities to determine nucleosomal
binding sites. We test our measures on well-studied genomic sequences of
different sizes drawn from different sources. The measures reveal the known in
vivo versus in vitro predictive discrepancies and uncover their potential to
pinpoint (high) nucleosome occupancy. We explore different possible signals
within and beyond the nucleosome length and find that complexity indices are
informative of nucleosome occupancy. We compare against the gold standard
(Kaplan model) and find similar and complementary results with the main
difference that our sequence complexity approach. For example, for high
occupancy, complexity-based scores outperform the Kaplan model for predicting
binding representing a significant advancement in predicting the highest
nucleosome occupancy following a training-free approach.
Exploring the context of visual information seeking
Authors: Sedghi Shahram, Shourmeij Zeinab, Tahamtan Iman
Date: 2018-05-17 00:00:00
Tasks: Information Retrieval, Retrieval

Information seeking is an interactive behaviour of the end users with
information systems, which occurs in a real environment known as context.
Context affects information-seeking behaviour in many different ways. The
purpose of this paper is to investigate the factors that potentially constitute
the context of visual information seeking. We used a Straussian version of
grounded theory, a qualitative approach, to conduct the study. Using a
purposive sampling method, 28 subjects participated in the study. The data were
analysed using open, axial and selective coding in MAXQDA software. The
contextual factors influencing visual information seeking were classified into
seven categories, including: user characteristics, general search features,
visual search features, display of results, accessibility of results, task type
and environmental factors. This study contributes to a better understanding of
how people conduct searches in and interact with visual search interfaces.
Results have important implications for the designers of information retrieval
systems. This paper is among the pioneer studies investigating contextual
factors influencing information seeking in visual information retrieval
systems.
Connectivity Inference from Neural Recording Data: Challenges, Mathematical Bases and Research Directions
Date: 2017-12-15 00:00:00
Tasks: Descriptive

This article presents a review of computational methods for connectivity
inference from neural activity data derived from multi-electrode recordings or
fluorescence imaging. We first identify biophysical and technical challenges in
connectivity inference along the data processing pipeline. We then review
connectivity inference methods based on two major mathematical foundations,
namely, descriptive model-free approaches and generative model-based
approaches. We investigate representative studies in both categories and
clarify which challenges have been addressed by which method. We further
identify critical open issues and possible research directions.
Constraint on the stem cell numbers and division rates posed by the risk of cancer
Authors: Augusto Gonzalez, Teresita Rodriguez, Rolando Perez
Date: 2017-08-08 00:00:00

Compiled data for the stem cell numbers, Ns, and division rates, ms, is reanalized in order to show that we can distinguish two groups of human tissues. In the first one, there is a relatively high fraction of maintenance (stem and transit) cells in the tissue, but the division rates are low. The second group, on the other hand, is characterized by very high transit cell division rates, of around one division per day. These groups do not have an embrionary origin. We argue that their properties arise from a combination of the needs of tissue homeostasis (in particular turnover rate) and a bound on cancer risk, which is roughly a linear function of the product Ns ms. The bound on cancer risk leads to a threshold at ms = 8/year, where the fraction of stem cells falls down two orders of magnitude.
Frequency-difference-dependent stochastic resonance in neural systems
Date: 2017-08-25 00:00:00

Biological neurons receive multiple noisy oscillatory signals, and their
dynamical response to the superposition of these signals is of fundamental
importance for information processing in the brain. Here we study the response
of neural systems to the weak envelope modulation signal, which is superimposed
by two periodic signals with different frequencies. We show that stochastic
resonance occurs at the beat frequency in neural systems at the single-neuron
as well as the population level. The performance of this
frequency-difference-dependent stochastic resonance is influenced by both the
beat frequency and the two forcing frequencies. Compared to a single neuron, a
population of neurons is more efficient in detecting the information carried by
the weak envelope modulation signal at the beat frequency. Furthermore, an
appropriate fine-tuning of the excitation-inhibition balance can further
optimize the response of a neural ensemble to the superimposed signal. Our
results thus introduce and provide insights into the generation and modulation
mechanism of the frequency-difference-dependent stochastic resonance in neural
systems.
Turbocharging Monte Carlo pricing for the rough Bergomi model
Date: 2018-03-16 00:00:00

The rough Bergomi model, introduced by Bayer, Friz and Gatheral [Quant.
Finance 16(6), 887-904, 2016], is one of the recent rough volatility models
that are consistent with the stylised fact of implied volatility surfaces being
essentially time-invariant, and are able to capture the term structure of skew
observed in equity markets. In the absence of analytical European option
pricing methods for the model, we focus on reducing the runtime-adjusted
variance of Monte Carlo implied volatilities, thereby contributing to the
model's calibration by simulation. We employ a novel composition of variance
reduction methods, immediately applicable to any conditionally log-normal
stochastic volatility model. Assuming one targets implied volatility estimates
with a given degree of confidence, thus calibration RMSE, the results we
demonstrate equate to significant runtime reductions - roughly 20 times on
average, across different correlation regimes.
Risk Constrained Trading Strategies for Stochastic Generation with a Single-Price Balancing Market
Date: 2017-06-23 00:00:00

Due to the limited predictability of wind power and other stochastic
generation, trading this energy in competitive electricity markets is
challenging. This paper derives revenue-maximising and risk-constrained
strategies for stochastic generators participating in electricity markets with
a single-price balancing mechanism. Starting from the optimal---and
impractical---strategy of offering zero or nominal power, which exposes the
participant to potentially large imbalance costs, we develop a number of
strategies that control risk by hedging against penalising balancing prices in
favour of rewarding ones. Trading strategies are formulated in a probabilistic
framework in order to address asymmetry in balancing prices. The large-scale
communication of system information characteristic of modern power systems is
utilised to inputs for electricity price forecasts and probabilistic system
length forecasts. A case study using data from the GB market in the UK is
presented and the ability of the proposed strategies to increase revenue and
reduce risk is demonstrated and analysed.
Crossing-effect in non-isolated and non-symmetric systems of patches
Date: 2017-08-10 00:00:00

The main result of this article is the determination of the minimal size for
the general case of problems with two identical patches. This solution is
presented in the explicit form, which allows to recuperate all the cases found
in the literature as particular cases, namely, one isolated fragment, one
single fragment communicating with its neighborhood, a system with two
identical fragments isolated from the matrix but mutually communicating and a
system of two identical fragments inserted in a homogeneous matrix. It is also
addressed the new problem of a single fragment communicating with the matrix,
with different life difficulty of each side. As application, it is found that
the internal condition $a_{0}$ can set which system is the worst to life. This
prediction confirms and extends the prediction already found in the literature
between isolated and non-isolated systems.
On the existence of sure profits via flash strategies
Authors: Claudio Fontana, Markus Pelger, Eckhard Platen
Date: 2017-08-10 00:00:00

We introduce and study the notion of sure profit via flash strategy, consisting of a high-frequency limit of buy-and-hold trading strategies. In a fully general setting, without imposing any semimartingale restriction, we prove that there are no sure profits via flash strategies if and only if asset prices do not exhibit predictable jumps. This result relies on the general theory of processes and provides the most general formulation of the well-known fact that, in an arbitrage-free financial market, asset prices (including dividends) should not exhibit jumps of a predictable direction or magnitude at predictable times. We furthermore show that any price process is always right-continuous in the absence of sure profits. Our results are robust under small transaction costs and imply that, under minimal assumptions, price changes occurring at scheduled dates should only be due to unanticipated information releases.
Reconciling cooperation, biodiversity and stability in complex ecological communities
Date: 2018-05-17 00:00:00

Empirical observations show that ecological communities can have a huge
number of coexisting species, also with few or limited number of resources.
These ecosystems are characterized by multiple type of interactions, in
particular displaying cooperative behaviors. However, standard modeling of
population dynamics based on Lotka-Volterra type of equations predicts that
ecosystem stability should decrease as the number of species in the community
increases and that cooperative systems are less stable than communities with
only competitive and/or exploitative interactions. Here we propose a stochastic
model of population dynamics, which includes exploitative interactions as well
as cooperative interactions induced by cross-feeding. The model is exactly
solved and we obtain results for relevant macro-ecological patterns, such as
species abundance distributions and correlation functions. In the large system
size limit, any number of species can coexist for a very general class of
interaction networks and stability increases as the number of species grows.
For pure mutualistic/commensalistic interactions we determine the topological
properties of the network that guarantee species coexistence. We also show that
the stationary state is globally stable and that inferring species interactions
through species abundance correlation analysis may be misleading. Our
theoretical approach thus show that appropriate models of cooperation naturally
leads to a solution of the long-standing question about complexity-stability
paradox and on how highly biodiverse communities can coexist.
Utilizing Embeddings for Ad-hoc Retrieval by Document-to-document Similarity
Authors: Yang Chenhao, He Ben, Ran Yanhua
Date: 2017-08-10 00:00:00
Tasks: Document Ranking, Information Retrieval, Retrieval

Latent semantic representations of words or paragraphs, namely the
embeddings, have been widely applied to information retrieval (IR). One of the
common approaches of utilizing embeddings for IR is to estimate the
document-to-query (D2Q) similarity in their embeddings. As words with similar
syntactic usage are usually very close to each other in the embeddings space,
although they are not semantically similar, the D2Q similarity approach may
suffer from the problem of "multiple degrees of similarity". To this end, this
paper proposes a novel approach that estimates a semantic relevance score (SEM)
based on document-to-document (D2D) similarity of embeddings. As Word or
Para2Vec generates embeddings by the context of words/paragraphs, the D2D
similarity approach turns the task of document ranking into the estimation of
similarity between content within different documents. Experimental results on
standard TREC test collections show that our proposed approach outperforms
strong baselines.
Topological limits to parallel processing capability of network architectures
Date: 2020-11-10 00:00:00

The ability to learn new tasks and generalize performance to others is one of
the most remarkable characteristics of the human brain and of recent AI
systems. The ability to perform multiple tasks simultaneously is also a
signature characteristic of large-scale parallel architectures, that is evident
in the human brain, and has been exploited effectively more traditional,
massively parallel computational architectures. Here, we show that these two
characteristics are in tension, reflecting a fundamental tradeoff between
interactive parallelism that supports learning and generalization, and
independent parallelism that supports processing efficiency through concurrent
multitasking. We formally show that, while the maximum number of tasks that can
be performed simultaneously grows linearly with network size, under realistic
scenarios (e.g. in an unpredictable environment), the expected number that can
be performed concurrently grows radically sub-linearly with network size.
Hence, even modest reliance on shared representation strictly constrains the
number of tasks that can be performed simultaneously, implying profound
consequences for the development of artificial intelligence that optimally
manages the tradeoff between learning and processing, and for understanding the
human brains remarkably puzzling mix of sequential and parallel capabilities.
Cell growth rate dictates the onset of glass to fluid-like transition and long time super-diffusion in an evolving cell colony
Date: 2018-02-14 00:00:00
Tasks: Quantization

Collective migration dominates many phenomena, from cell movement in living
systems to abiotic self-propelling particles. Focusing on the early stages of
tumor evolution, we enunciate the principles involved in cell dynamics and
highlight their implications in understanding similar behavior in seemingly
unrelated soft glassy materials and possibly chemokine-induced migration of
CD8$^{+}$ T cells. We performed simulations of tumor invasion using a minimal
three dimensional model, accounting for cell elasticity and adhesive cell-cell
interactions as well as cell birth and death to establish that cell growth
rate-dependent tumor expansion results in the emergence of distinct topological
niches. Cells at the periphery move with higher velocity perpendicular to the
tumor boundary, while motion of interior cells is slower and isotropic. The
mean square displacement, $\Delta(t)$, of cells exhibits glassy behavior at
times comparable to the cell cycle time, while exhibiting super-diffusive
behavior, $\Delta (t) \approx t^{\alpha}$ ($\alpha > 1$), at longer times. We
derive the value of $\alpha \approx 1.33$ using a field theoretic approach
based on stochastic quantization. In the process we establish the universality
of super-diffusion in a class of seemingly unrelated non-equilibrium systems.
Super diffusion at long times arises only if there is an imbalance between cell
birth and death rates. Our findings for the collective migration, which also
suggests that tumor evolution occurs in a polarized manner, are in quantitative
agreement with {\it in vitro} experiments. Although set in the context of tumor
invasion the findings should also hold in describing collective motion in
growing cells and in active systems where creation and annihilation of
particles play a role.
Two-locus clines on the real line with a step environment
Date: 2017-08-11 00:00:00
Tasks: Numerical Integration, Vocal Bursts Valence Prediction

The shape of allele-frequency clines maintained by migration-selection
balance depends not only on the properties of migration and selection, but also
on the dominance relations among alleles and on linkage to other loci under
selection. We investigate a two-locus model in which two diallelic, recombining
loci are subject to selection caused by an abrupt environmental change. The
habitat is one-dimensional and unbounded, selection at each locus is modeled by
step functions such that in one region one allele at each locus is advantageous
and in the other deleterious. We admit an environmentally independent,
intermediate degree of dominance at both loci, including complete dominance.
First, we derive an explicit expression for the single-locus cline with
dominance, thus generalizing classical results by Haldane (1948). We show that
the slope of the cline in the center (at the step) or, equivalently, the width
of the cline, is independent of the degree of dominance. Second, under the
assumption of strong recombination relative to selection and migration, the
first-order approximations of the allele-frequency clines at each of the loci
and of the linkage disequilibrium are derived. This may be interpreted as the
quasi-linkage-equilibrium approximation of the two-locus cline. Explicit
asymptotic expressions for the clines are deduced as $x\to\pm\infty$. For
equivalent loci, explicit expressions for the whole clines are derived. The
influence of dominance and of linkage on the slope of the cline in the center
and on a global measure of steepness are investigated. This global measure
reflects the influence of dominance. Finally, the accuracy of the
approximations and the dependence of the shape of the two-locus cline on the
full range of recombination rates is explored by numerical integration of the
underlying system of partial differential equations.
Technology networks: the autocatalytic origins of innovation
Date: 2018-04-19 00:00:00

We analyse the autocatalytic structure of technological networks and evaluate
its significance for the dynamics of innovation patenting. To this aim, we
define a directed network of technological fields based on the International
Patents Classification, in which a source node is connected to a receiver node
via a link if patenting activity in the source field anticipates patents in the
receiver field in the same region more frequently than we would expect at
random. We show that the evolution of the technology network is compatible with
the presence of a growing autocatalytic structure, i.e. a portion of the
network in which technological fields mutually benefit from being connected to
one another. We further show that technological fields in the core of the
autocatalytic set display greater fitness, i.e. they tend to appear in a
greater number of patents, thus suggesting the presence of positive spillovers
as well as positive reinforcement. Finally, we observe that core shifts take
place whereby different groups of technology fields alternate within the
autocatalytic structure; this points to the importance of recombinant
innovation taking place between close as well as distant fields of the
hierarchical classification of technological fields.
Quantitative predictions from competition theory with incomplete information on model parameters tested against experiments across diverse taxa
Date: 2017-08-11 00:00:00

We derive an analytical approximation for making quantitative predictions for
ecological communities as a function of the mean intensity of the
inter-specific competition and the species richness. This method, with only a
fraction of the model parameters (carrying capacities and competition
coefficients), is able to predict accurately empirical measurements covering a
wide variety of taxa (algae, plants, protozoa).
iTrace: An Implicit Trust Inference Method for Trust-aware Collaborative Filtering
Authors: He Xu, Liu Bin, Chen Ke-Jia
Date: 2017-08-15 00:00:00
Tasks: Collaborative Filtering, Recommendation Systems

The growth of Internet commerce has stimulated the use of collaborative
filtering (CF) algorithms as recommender systems. A collaborative filtering
(CF) algorithm recommends items of interest to the target user by leveraging
the votes given by other similar users. In a standard CF framework, it is
assumed that the credibility of every voting user is exactly the same with
respect to the target user. This assumption is not satisfied and thus may lead
to misleading recommendations in many practical applications. A natural
countermeasure is to design a trust-aware CF (TaCF) algorithm, which can take
account of the difference in the credibilities of the voting users when
performing CF. To this end, this paper presents a trust inference approach,
which can predict the implicit trust of the target user on every voting user
from a sparse explicit trust matrix. Then an improved CF algorithm termed
iTrace is proposed, which takes advantage of both the explicit and the
predicted implicit trust to provide recommendations with the CF framework. An
empirical evaluation on a public dataset demonstrates that the proposed
algorithm provides a significant improvement in recommendation quality in terms
of mean absolute error (MAE).
Attention but not musical training affects auditory streaming
Date: 2017-08-11 00:00:00
Tasks: Rhythm

While musicians generally perform better than non-musicians in various
auditory discrimination tasks, effects of specific instrumental training have
received little attention. The effects of instrument-specific musical training
on auditory grouping in the context of stream segregation are investigated here
in three experiments. In Experiment 1a, participants listened to sequences of
ABA tones and indicated when they heard a change in rhythm. This change is
caused by the manipulation of the B tones' timbre and indexes a change in
perception from integration to segregation, or vice versa. While it was
expected that musicians would detect a change in rhythm earlier when their own
instrument was involved, no such pattern was observed. In Experiment 1b,
designed to control for potential expectation effects in Experiment 1a,
participants heard sequences of static ABA tones and reported their initial
perceptions, whether the sequence was integrated or segregated. Results show
that participants tend to initially perceive these static sequences as
segregated, and that perception is influenced by similarity between the timbres
involved. Finally, in Experiment 2 violinists and flautists located mistuned
notes in an interleaved melody paradigm containing a violin and a flute melody.
Performance did not depend on the instrument the participant played but rather
which melody their attention was directed to. Taken together, results from the
three experiments suggest that the specific instrument one practices does not
have an influence on auditory grouping, but attentional mechanisms are
necessary for processing auditory scenes.