pwc-archive/papers-with-abstracts huggingface dataset:
Audio Features Affected by Music Expressiveness
Authors: Introini Alberto, Presti Giorgio, Boccignone Giuseppe
Date: 2016-05-17 00:00:00
Tasks: BIG-bench Machine Learning, Information Retrieval, Music Information Retrieval, Retrieval

Within a Music Information Retrieval perspective, the goal of the study
presented here is to investigate the impact on sound features of the musician's
affective intention, namely when trying to intentionally convey emotional
contents via expressiveness. A preliminary experiment has been performed
involving $10$ tuba players. The recordings have been analysed by extracting a
variety of features, which have been subsequently evaluated by combining both
classic and machine learning statistical techniques. Results are reported and
discussed.
Identification of conserved moieties in metabolic networks by graph theoretical analysis of atom transition networks
Date: 2016-05-17 00:00:00
Tasks: Network Identification

Conserved moieties are groups of atoms that remain intact in all reactions of
a metabolic network. Identification of conserved moieties gives insight into
the structure and function of metabolic networks and facilitates metabolic
modelling. All moiety conservation relations can be represented as nonnegative
integer vectors in the left null space of the stoichiometric matrix
corresponding to a biochemical network. Algorithms exist to compute such
vectors based only on reaction stoichiometry but their computational complexity
has limited their application to relatively small metabolic networks. Moreover,
the vectors returned by existing algorithms do not, in general, represent
conservation of a specific moiety with a defined atomic structure. Here, we
show that identification of conserved moieties requires data on reaction atom
mappings in addition to stoichiometry. We present a novel method to identify
conserved moieties in metabolic networks by graph theoretical analysis of their
underlying atom transition networks. Our method returns the exact group of
atoms belonging to each conserved moiety as well as the corresponding vector in
the left null space of the stoichiometric matrix. It can be implemented as a
pipeline of polynomial time algorithms. Our implementation completes in under
five minutes on a metabolic network with more than 4,000 mass balanced
reactions. The scalability of the method enables extension of existing
applications for moiety conservation relations to genome-scale metabolic
networks. We also give examples of new applications made possible by
elucidating the atomic structure of conserved moieties.
Statistical mechanics of ontology based annotations
Authors: Hoyle David C., Brass Andrew
Date: 2016-05-18 00:00:00

We present a statistical mechanical theory of the process of annotating an
object with terms selected from an ontology. The term selection process is
formulated as an ideal lattice gas model, but in a highly structured
inhomogeneous field. The model enables us to explain patterns recently observed
in real-world annotation data sets, in terms of the underlying graph structure
of the ontology. By relating the external field strengths to the information
content of each node in the ontology graph, the statistical mechanical model
also allows us to propose a number of practical metrics for assessing the
quality of both the ontology, and the annotations that arise from its use.
Using the statistical mechanical formalism we also study an ensemble of
ontologies of differing size and complexity; an analysis not readily performed
using real data alone. Focusing on regular tree ontology graphs we uncover a
rich set of scaling laws describing the growth in the optimal ontology size as
the number of objects being annotated increases. In doing so we provide a
further possible measure for assessment of ontologies.
An Introduction to Programming for Bioscientists: A Python-based Primer
Authors: Berk Ekmekci, Charles E. McAnany, Cameron Mura
Date: 2016-05-18 00:00:00
Tasks: Management

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.
Elections in Russia, 1991-2008
Date: 2016-05-18 00:00:00

In this paper, I review the main trends in voting in national elections in
Russia since 1991, discuss the evidence of manipulation or falsification by the
authorities, and use statistical techniques to examine the determinants of
voting trends.
Intrinsic noise profoundly alters the dynamics and steady state of morphogen-controlled bistable genetic switches
Date: 2016-05-18 00:00:00
Tasks: Position

During tissue development, patterns of gene expression determine the spatial
arrangement of cell types. In many cases, gradients of secreted signaling
molecules - morphogens - guide this process. The continuous positional
information provided by the gradient is converted into discrete cell types by
the downstream transcriptional network that responds to the morphogen. A
mechanism commonly used to implement a sharp transition between two adjacent
cell fates is the genetic toggle switch, composed of cross-repressing
transcriptional determinants. Previous analyses emphasize the steady state
output of these mechanisms. Here, we explore the dynamics of the toggle switch
and use exact numerical simulations of the kinetic reactions, the Chemical
Langevin Equation, and Minimum Action Path theory to establish a framework for
studying the effect of gene expression noise on patterning time and boundary
position. This provides insight into the time scale, gene expression
trajectories and directionality of stochastic switching events between cell
states. Taking gene expression noise into account predicts that the final
boundary position of a morphogen-induced toggle switch, although robust to
changes in the details of the noise, is distinct from that of the deterministic
system. Moreover, stochastic switching introduces differences in patterning
time along the morphogen gradient that result in a patterning wave propagating
away from the morphogen source. The velocity of this wave is influenced by
noise; the wave sharpens and slows as it advances and may never reach steady
state in a biologically relevant time. This could explain experimentally
observed dynamics of pattern formation. Together the analysis reveals the
importance of dynamical transients for understanding morphogen-driven
transcriptional networks and indicates that gene expression noise can
qualitatively alter developmental patterning.
Far from equilibrium: Wealth reallocation in the United States
Date: 2016-05-18 00:00:00

Studies of wealth inequality often assume that an observed wealth
distribution reflects a system in equilibrium. This constraint is rarely tested
empirically. We introduce a simple model that allows equilibrium but does not
assume it. To geometric Brownian motion (GBM) we add reallocation: all
individuals contribute in proportion to their wealth and receive equal shares
of the amount collected. We fit the reallocation rate parameter required for
the model to reproduce observed wealth inequality in the United States from
1917 to 2012. We find that this rate was positive until the 1980s, after which
it became negative and of increasing magnitude. With negative reallocation, the
system cannot equilibrate. Even with the positive reallocation rates observed,
equilibration is too slow to be practically relevant. Therefore, studies which
assume equilibrium must be treated skeptically. By design they are unable to
detect the dramatic conditions found here when data are analysed without this
constraint.
Recursive utility maximization under partial information
Date: 2016-05-19 00:00:00

This paper concerns the recursive utility maximization problem under partial
information. We first transform our problem under partial information into the
one under full information. When the generator of the recursive utility is
concave, we adopt the variational formulation of the recursive utility which
leads to a stochastic game problem and a characterization of the saddle point
of the game is obtained. Then, we study the K-ignorance case and explicit
saddle points of several examples are obtained. At last, when the generator of
the recursive utility is smooth, we employ the terminal perturbation method to
characterize the optimal terminal wealth.
Shear-Induced Nitric Oxide Production by Endothelial Cells
Date: 2016-05-19 00:00:00

We present a biochemical model of the wall shear stress (WSS)-induced
activation of endothelial nitric oxide synthase (eNOS) in an endothelial cell
(EC). The model includes three key mechanotransducers: mechanosensing ion
channels, integrins and G-protein-coupled receptors. The reaction cascade
consists of two interconnected parts. The first is rapid activation of calcium,
which results in formation of calcium-calmodulin complexes, followed by
recruitment of eNOS from caveolae. The second is phosphoryaltion of eNOS by
protein kinases PKC and AKT. The model also includes a negative feedback loop
due to inhibition of calcium influx into the cell by cyclic guanosine
monophosphate (cGMP). In this feedback, increased nitric oxide (NO) levels
cause an increase in cGMP levels, so that cGMP inhibition of calcium influx can
limit NO production. The model was used to predict the dynamics of NO
production by an EC subjected to a step increase of WSS from zero to a finite
physiologically relevant value. Among several experimentally observed features,
the model predicts a highly nonlinear, biphasic transient behavior of eNOS
activation and NO production: a rapid initial activation due to the very rapid
influx of calcium into the cytosol (occurring within 1 to 5 minutes) is
followed by a sustained period of activation due to protein kinases.
Some Mathematical Aspects of Price Optimisation
Date: 2016-05-19 00:00:00

Calculation of an optimal tariff is a principal challenge for pricing
actuaries. In this contribution we are concerned with the renewal insurance
business discussing various mathematical aspects of calculation of an optimal
renewal tariff. Our motivation comes from two important actuarial tasks, namely
a) construction of an optimal renewal tariff subject to business and technical
constraints, and b) determination of an optimal allocation of certain premium
loadings. We consider both continuous and discrete optimisation and then
present several algorithmic sub-optimal solutions. Additionally, we explore
some simulation techniques. Several illustrative examples show both the
complexity and the importance of the optimisation approach.
A Possible Mechanism of DNA to DNA Transcription in Eukaryotic Cells : Endonuclease Dependent Transcript Cutout
Date: 2016-06-19 00:00:00

We previously proposed the existence of DNA to DNA transcription in
eukaryotic cells, but the mechanism by which single-stranded DNA (ssDNA)
transcript is produced and released from the genome remains unknown. We once
speculated that the mechanism of DNA to DNA transcription might be similar to
that of DNA to RNA transcription, but now we propose that endonuclease
dependent transcript cutout may be a possible mechanism of DNA to DNA
transcription, in which a copy of ssDNA fragment (transcript) between two nicks
produced by nicking endonuclease is released from double-stranded DNA (dsDNA)
region in the genome by an unknown ssDNA fragment releasing enzyme. The gap in
the dsDNA will be filled through DNA repair mechanism. Occasionally, multiple
copies of ssDNA transcripts could be produced through multiple rounds of
cutout-repair-cutout cycle.
Nonlinear trend removal should be carefully performed in heart rate variability analysis
Date: 2016-05-19 00:00:00
Tasks: Heart Rate Variability, Rhythm, Time Series Analysis

$\bullet$ Background : In Heart rate variability analysis, the rate-rate time
series suffer often from aperiodic non-stationarity, presence of ectopic beats
etc. It would be hard to extract helpful information from the original signals.
10 $\bullet$ Problem : Trend removal methods are commonly practiced to reduce
the influence of the low frequency and aperiodic non-stationary in RR data.
This can unfortunately affect the signal and make the analysis on detrended
data less appropriate. $\bullet$ Objective : Investigate the detrending effect
(linear \& nonlinear) in temporal / nonliear analysis of heart rate variability
of long-term RR data (in normal sinus rhythm, atrial fibrillation, 15
congestive heart failure and ventricular premature arrhythmia conditions).
$\bullet$ Methods : Temporal method : standard measure SDNN; Nonlinear methods
: multi-scale Fractal Dimension (FD), Detrended Fluctuation Analysis (DFA) \&
Sample Entropy (Sam-pEn) analysis. $\bullet$ Results : The linear detrending
affects little the global characteristics of the RR data, either 20 in temporal
analysis or in nonlinear complexity analysis. After linear detrending, the
SDNNs are just slightly shifted and all distributions are well preserved. The
cross-scale complexity remained almost the same as the ones for original RR
data or correlated. Nonlinear detrending changed not only the SDNNs
distribution, but also the order among different types of RR data. After this
processing, the SDNN became indistinguishable be-25 tween SDNN for normal sinus
rhythm and ventricular premature beats. Different RR data has different
complexity signature. Nonlinear detrending made the all RR data to be similar ,
in terms of complexity. It is thus impossible to distinguish them. The FD
showed that nonlinearly detrended RR data has a dimension close to 2, the
exponent from DFA is close to zero and SampEn is larger than 1.5 -- these
complexity values are very close to those for 30 random signal. $\bullet$
Conclusions : Pre-processing by linear detrending can be performed on RR data,
which has little influence on the corresponding analysis. Nonlinear detrending
could be harmful and it is not advisable to use this type of pre-processing.
Exceptions do exist, but only combined with other appropriate techniques to
avoid complete change of the signal's intrinsic dynamics. 35 Keywords $\bullet$
heart rate variability $\bullet$ linear / nonlinear detrending $\bullet$
complexity analysis $\bullet$ mul-tiscale analysis $\bullet$ detrended
fluctuation analysis $\bullet$ fractal dimension $\bullet$ sample entropy;
Geometric Near-neighbor Access Tree (GNAT) revisited
Authors: Fredriksson Kimmo
Date: 2016-05-20 00:00:00

Geometric Near-neighbor Access Tree (GNAT) is a metric space indexing method
based on hierarchical hyperplane partitioning of the space. While GNAT is very
efficient in proximity searching, it has a bad reputation of being a memory
hog. We show that this is partially based on too coarse analysis, and that the
memory requirements can be lowered while at the same time improving the search
efficiency. We also show how to make GNAT memory adaptive in a smooth way, and
that the hyperplane partitioning can be replaced with ball partitioning, which
can further improve the search performance. We conclude with experimental
results showing the new methods can give significant performance boost.
Antibiotic resistance: a physicist's view
Date: 2016-05-19 00:00:00

The problem of antibiotic resistance poses challenges across many
disciplines. One such challenge is to understand the fundamental science of how
antibiotics work, and how resistance to them can emerge. This is an area where
physicists can make important contributions. Here, we highlight cases where
this is already happening, and suggest directions for further physics
involvement in antimicrobial research.
Collective migration under hydrodynamic interactions -- a computational approach
Date: 2016-05-19 00:00:00

Substrate-based cell motility is essential for fundamental biological
processes, such as tissue growth, wound healing and immune response. Even if a
comprehensive understanding of this motility mode remains elusive, progress has
been achieved in its modeling using a whole cell physical model. The model
takes into account the main mechanisms of cell motility - actin polymerization,
substrate mediated adhesion and actin-myosin dynamics and combines it with
steric cell-cell and hydrodynamic interactions. The model predicts the onset of
collective cell migration, which emerges spontaneously as a result of inelastic
collisions of neighboring cells. Each cell here modeled as an active polar gel,
is accomplished with two vortices if it moves. Open collision of two cells the
two vortices which come close to each other annihilate. This leads to a
rotation of the cells and together with the deformation and the reorientation
of the actin filaments in each cell induces alignment of these cells and leads
to persistent translational collective migration. The effect for low Reynolds
numbers is as strong as in the non-hydrodynamic model, but it decreases with
increasing Reynolds number.
The genealogy of Maria de Aguilar: evidence of admixture in the early Spanish Colony in Costa Rica
Date: 2016-05-19 00:00:00

During long time, historians and genealogists have interpreted that the elite
that emerged during the Spanish Conquest was almost exclusively European. We
reconstructed a deep matrilineal genealogy which includes recent Costa Rican
ex-presidents and religious authorities back to their ancestors at the early
17th century, and compared their historic ethnic affinities with genetic
mitochondrial evidence of some living descendents. The observed DNA lineage has
an Amerindian ancestry. Such results point out that an Amerindian gene flow had
occurred into the Spanish group during the first generations of colonial
society. This conclusion do not support the current idea that the Spanish elite
avoided interethnic marriages.
Mitochondrial genealogy of Maria Mercedes Cairol Antunez, footprint of recent immigration to Costa Rica / La genealogia mitocondrial de Maria Mercedes Cairol Antunez, huella de la inmigracion reciente a Costa Rica
Date: 2016-05-20 00:00:00
Tasks: Diversity

The technological advances in Genetics have given rise to the science of
Molecular Genealogy, by giving us the opportunity to approach the study of
pedigrees from a new perspective, examining alive people at the same time than
collating records from their ancestors. A four generations matrilineal
genealogy is presented from Da. Angela Antunez (b. a. 1881 in Barcelona, Spain)
to their descendants in Cuba and Costa Rica. The observed mitochondrial lineage
has a substitution in the region HVR1 respect to the reference sequence (CRS)
and belongs to H haplogroup. This is consistent -as expected, with the recent
documented European lineage. This is an example of differential female
migration, in which women move to the husband's place of origin. Because of
patrilocal marriages are practiced in most societies, such migration mechanism
has had a major impact since the arrival of immigrant women bring new and
different lineages of mtDNA, which together with the admixture process
contributed to enrich the diversity and regionalization of the gene pool of
human populations in the Americas.
The genealogy of Da. Isabel de Jimenez. An approach to the first phase of admixture in Costa Rica / La genealogia de Da. Isabel de Jimenez. Una aproximacion a la primera fase del mestizaje en Costa Rica
Date: 2016-05-20 00:00:00

Traditionally the Costa Rican historians and genealogists have interpreted
that the Spanish ruling elite emerged after the conquest was exclusively of
European origin. On the other side, recent technological advances in Genetics
give us the opportunity to approach the study of pedigrees from a new
perspective, examining alive people and simultaneously collating the historical
information of their ancestors. In this paper, a complete matrilineal genealogy
was reconstructed from nowadays "white" Costa Ricans to their ancestors in the
early Colonial society (XVI century). It was compared the correlation between
ethnic affiliations deduced from historical records with the genetic
inheritance from maternal lineages. The MtDNA lineage observed corresponds to a
Native American ancestry. These results show that some Amerindian gene flow
into the Spanish group must have occurred since the first generation of
Colonial society, a finding that contrasts with the prevailing ideas that the
Spanish elite avoided the intermarriage with other ethnic groups. Examples like
this one confirm that miscegenation began early in Costa Rica. So, those who
considered themselves "Spaniards" in the late colonial era, were actually
biologically mestizos. It is widely accepted, that the general Costa Rican
population is the result of an admixture process between Europeans, Amerindians
and Africans.
Fisher-Wright model with deterministic seed bank and selection
Date: 2016-07-28 00:00:00
Tasks: Diversity

Seed banks are a common characteristics to many plant species, which allow
storage of genetic diversity in the soil as dormant seeds for various periods
of time. We investigate an above-ground population following a Fisher-Wright
model with selection coupled with a deterministic seed bank assuming the length
of the seed bank is kept constant and the number of seeds is large. To assess
the combined impact of seed banks and selection on genetic diversity, we derive
a general diffusion model. The applied techniques outline a path of
approximating a stochastic delay differential equation by an appropriately
rescaled stochastic differential equation, which is a common issue in
statistical physics. We compute the equilibrium solution of the site-frequency
spectrum and derive the times to fixation of an allele with and without
selection. Finally, it is demonstrated that seed banks enhance the effect of
selection onto the site-frequency spectrum while slowing down the time until
the mutation-selection equilibrium is reached.