pwc-archive/papers-with-abstracts huggingface dataset:
The Energetics of Molecular Adaptation in Transcriptional Regulation
Date: 2019-05-15 00:00:00
Tasks: Diagnostic

Mutation is a critical mechanism by which evolution explores the functional
landscape of proteins. Despite our ability to experimentally inflict mutations
at will, it remains difficult to link sequence-level perturbations to
systems-level responses. Here, we present a framework centered on measuring
changes in the free energy of the system to link individual mutations in an
allosteric transcriptional repressor to the parameters which govern its
response. We find the energetic effects of the mutations can be categorized
into several classes which have characteristic curves as a function of the
inducer concentration. We experimentally test these diagnostic predictions
using the well-characterized LacI repressor of Escherichia coli, probing
several mutations in the DNA binding and inducer binding domains. We find that
the change in gene expression due to a point mutation can be captured by
modifying only a subset of the model parameters that describe the respective
domain of the wild-type protein. These parameters appear to be insulated, with
mutations in the DNA binding domain altering only the DNA affinity and those in
the inducer binding domain altering only the allosteric parameters. Changing
these subsets of parameters tunes the free energy of the system in a way that
is concordant with theoretical expectations. Finally, we show that the
induction profiles and resulting free energies associated with pairwise double
mutants can be predicted with quantitative accuracy given knowledge of the
single mutants, providing an avenue for identifying and quantifying epistatic
interactions.
Dynamic model of firms competitive interaction on the market with taxation
Date: 2019-05-15 00:00:00

In this article three models of firms interaction on the market are
described. One of these models is described by using a differential equation
and by Lotka-Volterra model, where the equation has a different form. Also,
there are models of non-competing and competing firms. The article presents an
algorithm for solving the interaction of competing firms in taxation and the
calculation of a compromise point. Besides, the article presents a compromise
between the interests of a state and an enterprise.
Area Optimization with Non-linear Models in Core Mapping for System-on-Chips
Date: 2019-05-13 00:00:00

Linear models are regularly used for mapping cores to tiles in a chip.
System-on-Chip (SoC) design requires integration of functional units with
varying sizes, but conventional models only account for identical-sized cores.
Linear models cannot calculate the varying areas of cores in SoCs directly and
must rely on approximations. We propose using non-linear models: Semi-definite
programming (SDP) allows easy model definitions and achieves approximately 20%
reduced area and up to 80% reduced white space. As computational time is
similar to linear models, they can be applied, practically.
Visualizations for Understanding SoC Behaviour
Date: 2019-05-10 00:00:00

This paper introduces a novel method of analysis for SoC development building
upon commonly used tools and techniques to approximate and automate the human
process of investigation. Knowledge of the interactions between components
within a SoC is essential for understanding how a system works so the presented
method provides a way of visualizing these interactions. The mathematical basis
for the method is explained and justified, then the method is demonstrated
using two representative case studies. Visualizations from the case studies are
used to exhibit the usefulness of the method for system optimization,
monitoring, and validation.
Getting a head start: the slime mold, Physarum polycephalum, tune foraging decision to motivational asymmetry when faced with competition
Authors: Eilidh Stirrup, David Lusseau
Date: 2019-05-16 00:00:00

Slime mould plasmodia can adjust their behaviour in response to chemical trails left by themselves and other Physarum plasmodia. This simple feedback process increases their foraging efficiency. We still do not know whether other factors influence plasmodium behaviour in realistic competition settings. Here we designed a competition experiment where two plasmodia had to find one food source in a common environment. As previously shown, the time it took plasmodia to find food depended on their hunger motivation. However, the time it took a plasmodium to start looking for food depended on its motivation and the motivation of its competitor. Plasmodia always initiated foraging quicker if they were in the presence of a competitor and the quickest if they were hungry and in the presence of a satiated competitor. The time it took to arrive to the food was not influenced by whether they were alone or with a competitor. Ultimately, this complex competition response benefited the hungry plasmodia as they had a 4:1 chance of finding the food first. The sensory ecology of Physarum polycephalum is more complex than previously thought and yields complex behaviour in a simple organism.
Improving Regression-based Event Study Analysis Using a Topological Machine-learning Method
Date: 2019-05-16 00:00:00
Tasks: BIG-bench Machine Learning, regression

This paper introduces a new correction scheme to a conventional
regression-based event study method: a topological machine-learning approach
with a self-organizing map (SOM).We use this new scheme to analyze a major
market event in Japan and find that the factors of abnormal stock returns can
be easily can be easily identified and the event-cluster can be depicted.We
also find that a conventional event study method involves an empirical analysis
mechanism that tends to derive bias due to its mechanism, typically in an
event-clustered market situation. We explain our new correction scheme and
apply it to an event in the Japanese market --- the holding disclosure of the
Government Pension Investment Fund (GPIF) on July 31, 2015.
Low-Complexity OFDM Spectral Precoding
Date: 2019-05-16 00:00:00

This paper proposes a new large-scale mask-compliant spectral precoder
(LS-MSP) for orthogonal frequency division multiplexing systems. In this paper,
we first consider a previously proposed mask-compliant spectral precoding
scheme that utilizes a generic convex optimization solver which suffers from
high computational complexity, notably in large-scale systems. To mitigate the
complexity of computing the LS-MSP, we propose a divide-and-conquer approach
that breaks the original problem into smaller rank 1 quadratic-constraint
problems and each small problem yields closed-form solution. Based on these
solutions, we develop three specialized first-order low-complexity algorithms,
based on 1) projection on convex sets and 2) the alternating direction method
of multipliers. We also develop an algorithm that capitalizes on the
closed-form solutions for the rank 1 quadratic constraints, which is referred
to as 3) semi-analytical spectral precoding. Numerical results show that the
proposed LS-MSP techniques outperform previously proposed techniques in terms
of the computational burden while complying with the spectrum mask. The results
also indicate that 3) typically needs 3 iterations to achieve similar results
as 1) and 2) at the expense of a slightly increased computational complexity.
WMMSE resource allocation for NOMA-FD
Authors: Andrea Abrardo, Marco Moretti, Fabio Saggese
Date: 2019-05-16 00:00:00

Power and channel allocation in interference-limited systems is a key enabler for beyond 5G (B5G) technologies, such as multi-carrier full duplex non-orthogonal multiple access (FD-NOMA). In FD-NOMA systems power allocation is a very computationally intense non-convex problem due to the presence of strong interference and the integrality condition on channel allocation. In this paper, we propose an iterative power allocation algorithm based on the minimization of the weighted mean square error, which converges to a feasible allocation of the original problem. Experimental results show that the proposed algorithm has by far the lowest complexity among other state-of-the-art solutions. Moreover, they assess the validity of our approach showing performance close to the theoretical optimum.
Dynamics of Quadrotor UAVs for Aerial Networks: An Energy Perspective
Date: 2019-05-16 00:00:00

In this letter, we present a model for quadrotor unmanned aerial vehicles
(UAVs), including control, communication, and wireless charging. In so doing,
we investigate associated energy and battery dynamics. Indeed, energy and
battery expressions are derived by leveraging motors' and battery electrical
models. Through an experiment, their performances are evaluated for different
parameters. The objective is to provide a simple yet practical model of
quadrotor UAV consumed/harvested energy and battery dynamics for researchers
conducting work on energy-efficient aerial networks.
Options to Receive Retirement Gratuity
Date: 2019-05-27 00:00:00

Retirement gratuity is the money companies typically pay their employees at
the end of their contracts or at the time of leaving the company. It is a
defined benefit plan and is often given as an alternative to a pension plan. In
Botswana, there is now a new pattern whereby companies give their employees the
option to receive their gratuity at various stages before the end of their
contracts. In particular, some companies give their employees an option to
receive their gratuity on a monthly basis rather than having them wait for a
year or more. Many employees find this option attractive, but is it
economically sound? This paper sheds light on this question by quantifying the
economic benefits of the tax relief provided by government relative to
investing the monthly-received funds in a risk-free savings account or helping
repay a loan. The principles and methods used herein can be adapted and applied
to different taxation systems.
Identifying conversion efficiency as a key mechanism underlying food webs evolution : a step forward, or backward ?
Authors: Coralie Fritsch, Sylvain Billiard, Nicolas Champagnat
Date: 2019-05-15 00:00:00

Body size or mass is one of the main factors underlying food webs structure. A large number of evolutionary models have shown that indeed, the adaptive evolution of body size (or mass) can give rise to hierarchically organised trophic levels with complex between and within trophic interactions. However, these models generally make strong arbitrary assumptions on how traits evolve, casting doubts on their robustness. In particular, biomass conversion efficiency is always considered independent of the predator and prey size, which contradicts with the literature. In this paper, we propose a general model encompassing most previous models which allows to show that relaxing arbitrary assumptions gives rise to unrealistic food webs. We then show that considering biomass conversion efficiency dependent on species size is certainly key for food webs adaptive evolution because realistic food webs can evolve, making obsolete the need of arbitrary constraints on traits' evolution. We finally conclude that, on the one hand, ecologists should pay attention to how biomass flows into food webs in models. On the other hand, we question more generally the robustness of evolutionary models for the study of food webs.
Modeling cell migration regulated by cell-ECM micromechanical coupling
Authors: Yu Zheng, Hanqing Nan, Qihui Fan, Xiaochen Wang, LiYu Liu, Ruchuan Liu, Fangfu Ye, Bo Sun, Yang Jiao
Date: 2019-05-16 00:00:00

Cell migration in fibreous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. During migration, individual cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers through focal adhesion complexes, remodel the ECM, and eventually propagate to and can be sensed by other cells in the system. The microstructure and physical properties of the ECM can also significantly influence cell migration, e.g., via durotaxis and contact guidance. Here, we develop a computational model for cell migration regulated by cell-ECM micro-mechanical coupling. Our model explicitly takes into account a variety of cellular level processes including focal adhesion formation and disassembly, active traction force generation and cell locomotion due to actin filament contraction, transmission and propagation of tensile forces in the ECM, as well as the resulting ECM remodeling. We validate our model by accurately reproducing single-cell dynamics of MCF-10A breast cancer cells migrating on collagen gels and show that the durotaxis and contact guidance effects naturally arise as a consequence of the cell-ECM micro-mechanical interactions considered in the model. Moreover, our model predicts strongly correlated multi-cellular migration dynamics, which are resulted from the ECM-mediated mechanical coupling among the migrating cell and are subsequently verified in {\it in vitro} experiments using MCF-10A cells. Our computational model provides a robust tool to investigate emergent collective dynamics of multi-cellular systems in complex {\it in vivo} micro-environment and can be utilized to design {\it in vitro} micro-environments to guide collective behaviors and self-organization of cells.
NANUQ: A method for inferring species networks from gene trees under the coalescent model
Date: 2019-05-16 00:00:00

Species networks generalize the notion of species trees to allow for
hybridization or other lateral gene transfer. Under the Network Multispecies
Coalescent Model, individual gene trees arising from a network can have any
topology, but arise with frequencies dependent on the network structure and
numerical parameters. We propose a new algorithm for statistical inference of a
level-1 species network under this model, from data consisting of gene tree
topologies, and provide the theoretical justification for it. The algorithm is
based in an analysis of quartets displayed on gene trees, combining several
statistical hypothesis tests with combinatorial ideas such as a quartet-based
intertaxon distance appropriate to networks, the NeighborNet algorithm for
circular split systems, and the Circular Network algorithm for constructing a
splits graph.
Cointegration in high frequency data
Authors: Simon Clinet, Yoann Potiron
Date: 2019-05-17 00:00:00
Tasks: Vocal Bursts Intensity Prediction

In this paper, we consider a framework adapting the notion of cointegration when two asset prices are generated by a driftless It\^{o}-semimartingale featuring jumps with infinite activity, observed regularly and synchronously at high frequency. We develop a regression based estimation of the cointegrated relations method and show the related consistency and central limit theory when there is cointegration within that framework. We also provide a Dickey-Fuller type residual based test for the null of no cointegration against the alternative of cointegration, along with its limit theory. Under no cointegration, the asymptotic limit is the same as that of the original Dickey-Fuller residual based test, so that critical values can be easily tabulated in the same way. Finite sample indicates adequate size and good power properties in a variety of realistic configurations, outperforming original Dickey-Fuller and Phillips-Perron type residual based tests, whose sizes are distorted by non ergodic time-varying variance and power is altered by price jumps. Two empirical examples consolidate the Monte-Carlo evidence that the adapted tests can be rejected while the original tests are not, and vice versa.
A 300-500 MHz Tunable Oscillator Exploiting Ten Overtones in Single Lithium Niobate Resonator
Date: 2019-05-17 00:00:00

This paper presents the first voltage-controlled MEMS oscillator (VCMO) based
on a Lithium Niobate (LiNbO3) lateral overtone bulk acoustic resonator (LOBAR).
The VCMO consists of a LOBAR in a closed loop with 2 amplification stages and a
varactor-embedded tunable LC tank. By adjusting the bias voltage applied to the
varactor, the tank can be tuned to change the closed-loop gain and phase
responses of the oscillator so that Barkhausen conditions are satisfied for a
particular resonance mode. The tank is designed to allow the proposed VCMO to
lock to any of the ten overtones ranging from 300 to 500 MHz. Owing to the
high-quality factors of the LiNbO3 LOBAR, the measured VCMO shows a low
close-in phase noise of -100 dBc/Hz at 1 kHz offset from a 300 MHz carrier and
a noise floor of -153 dBc/Hz while consuming 9 mW. With further optimization,
this VCMO can lead to direct radio frequency (RF) synthesis for ultra-low-power
transceivers in multi-mode Internet-of-Things (IoT) nodes.
DSP Linearization for Millimeter-Wave All-Digital Receiver Array with Low-Resolution ADCs
Date: 2019-05-17 00:00:00
Tasks: All

Millimeter-wave (mmWave) communications and cell densification are the key
techniques for the future evolution of cellular systems beyond 5G. Although the
current mmWave radio designs are focused on hybrid digital and analog receiver
array architectures, the fully digital architecture is an appealing option due
to its flexibility and support for multi-user multiple-input multiple-output
(MIMO). In order to achieve reasonable power consumption and hardware cost, the
specifications of analog circuits are expected to be compromised, including the
resolution of analog-to-digital converter (ADC) and the linearity of
radio-frequency (RF) front end. Although the state-of-the-art studies focus on
the ADC, the nonlinearity can also lead to severe system performance
degradation when strong input signals introduce inter-modulation distortion
(IMD). The impact of RF nonlinearity becomes more severe with densely deployed
mmWave cells since signal sources closer to the receiver array are more likely
to occur. In this work, we design and analyze the digital IMD compensation
algorithm, and study the relaxation of the required linearity in the RF-chain.
We propose novel algorithms that jointly process digitized samples to recover
amplifier saturation, and relies on beam space operation which reduces the
computational complexity as compared to per-antenna IMD compensation.
A Nonlocal Approach to The Quantum Kolmogorov Backward Equation and Links to Noncommutative Geometry
Date: 2019-05-17 00:00:00

The Accardi-Boukas quantum Black-Scholes equation can be used as an
alternative to the classical approach to finance, and has been found to have a
number of useful benefits. The quantum Kolmogorov backward equations, and
associated quantum Fokker-Planck equations, that arise from this general
framework, are derived using the Hudson-Parthasarathy quantum stochastic
calculus. In this paper we show how these equations can be derived using a
nonlocal approach to quantum mechanics. We show how nonlocal diffusions, and
quantum stochastic processes can be linked, and discuss how moment matching can
be used for deriving solutions.
Single-shot non-invasive three-dimensional imaging through scattering media
Date: 2019-05-16 00:00:00
Tasks: Retrieval

We present a method for single-shot three-dimensional imaging through
scattering media with a three-dimensional memory effect. In the proposed
computational process, a captured speckle image is two-dimensionally correlated
with different scales, and the object is three-dimensionally recovered with
three-dimensional phase retrieval. Our method was experimentally demonstrated
with a lensless setup and was compared with a multi-shot approach used in our
previous work [Y. Okamoto, et al., Opt. Lett. 44, 2526-2529 (2019)].
Quantification of the morphological characteristics of hESC colonies
Authors: Sirio Orozco-Fuentes, Irina Neganova, Laura E. Wadkin, Andrew W. Baggaley, Rafael A. Barrio, Majlinda Lako, Anvar Shukurov, Nicholas G. Parker
Date: 2019-05-17 00:00:00

The maintenance of the pluripotent state in human embryonic stem cells (hESCs) is critical for further application in regenerative medicine, drug testing and studies of fundamental biology. Currently, the selection of the best quality cells and colonies for propagation is typically performed by eye, in terms of the displayed morphological features, such as prominent/abundant nucleoli and a colony with a tightly packed appearance and a well-defined edge. Using image analysis and computational tools, we precisely quantify these properties using phase-contrast images of hESC colonies of different sizes (0.1 -- 1.1$\, \text{mm}^2$) during days 2, 3 and 4 after plating. Our analyses reveal noticeable differences in their structure influenced directly by the colony area $A$. Large colonies ($A > 0.6 \, \text{mm}^2$) have cells with smaller nuclei and a short intercellular distance when compared with small colonies ($A < 0.2 \, \text{mm}^2$). The gaps between the cells, which are present in small and medium sized colonies with $A \le 0.6 \, \text{mm}^2$, disappear in large colonies ($A > 0.6 \, \text{mm}^2$) due to the proliferation of the cells in the bulk. This increases the colony density and the number of nearest neighbours. We also detect the self-organisation of cells in the colonies where newly divided (smallest) cells cluster together in patches, separated from larger cells at the final stages of the cell cycle. This might influence directly cell-to-cell interactions and the community effects within the colonies since the segregation induced by size differences allows the interchange of neighbours as the cells proliferate and the colony grows. Our findings are relevant to efforts to determine the quality of hESC colonies and establish colony characteristics database.
Fidelity Imposed Network Edit (FINE) for Solving Ill-Posed Image Reconstruction
Date: 2019-05-17 00:00:00
Tasks: Image Reconstruction

Deep learning (DL) is increasingly used to solve ill-posed inverse problems
in imaging, such as reconstruction from noisy or incomplete data, as DL offers
advantages over explicit image feature extractions in defining the needed
prior. However, DL typically does not incorporate the precise physics of data
generation or data fidelity. Instead, DL networks are trained to output some
average response to an input. Consequently, DL image reconstruction contains
errors, and may perform poorly when the test data deviates significantly from
the training data, such as having new pathological features. To address this
lack of data fidelity problem in DL image reconstruction, a novel approach,
which we call fidelity-imposed network edit (FINE), is proposed. In FINE, a
pre-trained prior network's weights are modified according to the physical
model, on a test case. Our experiments demonstrate that FINE can achieve
superior performance in two important inverse problems in neuroimaging:
quantitative susceptibility mapping (QSM) and under-sampled reconstruction in
MRI.
A Fixed-Flexible BESS Allocation Scheme for Transmission Networks Considering Uncertainties
Authors: Malhar Padhee, Anamitra Pal, Chetan Mishra, Katelynn A. Vance
Date: 2019-05-18 00:00:00

Battery energy storage systems (BESSs) can play a key role in mitigating the intermittency and uncertainty associated with adding large amounts of renewable energy to the bulk power system (BPS). Two BESS technologies that have gained prominence in this regard are Lithium-ion (LI) BESS and Vanadium redox flow (VRF) BESS. This paper proposes a fixed-flexible BESS allocation scheme that exploits the complementary characteristics of LI and VRF BESSs to attain optimal techno-economic benefits in a wind-integrated BPS. Studies carried out on relatively large transmission networks demonstrate that benefits such as reduction in system operation cost, wind spillage, voltage fluctuations, and discounted payback period, can be realized by using the proposed scheme.