pwc-archive/papers-with-abstracts huggingface dataset:
Dynamic Carrier and Power Amplifier Mapping for Energy Efficient Multi-Carrier Wireless Communications
Date: 2019-01-18 00:00:00

The rapid increasing demand of wireless transmission has incurred mobile
broadband to continuously evolve through multiple frequency bands, massive
antennas and other multi-stream processing schemes. Together with the improved
data transmission rate, the power consumption for multi-carrier transmission
and processing is proportionally increasing, which contradicts with the energy
efficiency requirements of 5G wireless systems. To meet this challenge, multi
carrier power amplifier (MCPA) technology, e.g., to support multiple carriers
through a single power amplifier, is widely deployed in practical. With massive
carriers required for 5G communication and limited number of carriers supported
per MCPA, a natural question to ask is how to map those carriers into multiple
MCPAs and whether we shall dynamically adjust this mapping relation. In this
paper, we have theoretically formulated the dynamic carrier and MCPA mapping
problem to jointly optimize the traditional separated baseband and radio
frequency processing. On top of that, we have also proposed a low complexity
algorithm that can achieve most of the power saving with affordable
computational time, if compared with the optimal exhaustive search based
algorithm.
Centre-finding in E. coli and the role of mathematical modelling: past, present and future
Authors: Sean M. Murray, Martin Howard
Date: 2019-01-18 00:00:00

We review the key role played by mathematical modelling in elucidating two centre-finding patterning systems in E. coli: midcell division positioning by the MinCDE system and DNA partitioning by the ParABS system. We focus particularly on how, despite much experimental effort, these systems were simply too complex to unravel by experiments alone, and instead required key injections of quantitative, mathematical thinking. We conclude the review by analysing the frequency of modelling approaches in microbiology over time. We find that while such methods are increasing in popularity, they are still probably heavily under-utilised for optimal progress on complex biological questions.
Investigating Epithelial-To-Mesenchymal Transition with Integrated Computational and Experimental Approaches
Date: 2019-01-18 00:00:00

The transition between epithelial and mesenchymal (EMT) is a fundamental
cellular process that plays critical roles in development, cancer metastasis,
and tissue wound healing. EMT is not a binary process but involves multiple
partial EMT states that give rise to a high degree of cell state plasticity.
Here, we first reviewed several studies on theoretical predictions and
experimental verification of these intermediate states, the role of partial EMT
on kidney fibrosis development, and how quantitative signaling information
controls cell commitment to partial or full EMT upon transient signals. Next,
we summarized existing knowledge and open questions on the coupling between EMT
and other biological processes, such as the cell cycle, epigenetic regulation,
stemness, and apoptosis. Taken together, EMT is a model system that has
attracted increasing interests for quantitative experimental and theoretical
studies.
Personalized Visited-POI Assignment to Individual Raw GPS Trajectories
Authors: Suzuki Jun, Suhara Yoshihiko, Toda Hiroyuki, Nishida Kyosuke
Date: 2019-01-11 00:00:00

Knowledge discovery from GPS trajectory data is an important topic in several
scientific areas, including data mining, human behavior analysis, and user
modeling. This paper proposes a task that assigns personalized visited-POIs.
Its goal is to estimate fine-grained and pre-defined locations (i.e., points of
interest (POI)) that are actually visited by users and assign visited-location
information to the corresponding span of their (personal) GPS trajectories. We
also introduce a novel algorithm to solve this assignment task. First, we
exhaustively extract stay-points as candidates for significant locations using
a variant of a conventional stay-point extraction method. Then we select
significant locations and simultaneously assign visited-POIs to them by
considering various aspects, which we formulate in integer linear programming.
Experimental results conducted on an actual user dataset show that our method
achieves higher accuracy in the visited-POI assignment task than the various
cascaded procedures of conventional methods.
On a dividend problem with random funding
Date: 2019-01-18 00:00:00

We consider a modification of the dividend maximization problem from ruin
theory. Based on a classical risk process we maximize the difference of
expected cumulated discounted dividends and total expected discounted
additional funding (subject to some proportional transaction costs). For
modelling dividends we use the common approach whereas for the funding
opportunity we use the jump times of another independent Poisson process at
which we choose an appropriate funding height. In case of exponentially
distributed claims we are able to determine an explicit solution to the problem
and derive an optimal strategy whose nature heavily depends on the size of the
transaction costs.
Spatial clustering and common regulatory elements correlate with coordinated gene expression
Authors: Jingyu Zhang, HengYu Chen, Ruoyan Li, David A. Taft, Guang Yao, Fan Bai, Jianhua Xing
Date: 2019-01-18 00:00:00
Tasks: Clustering

Many cellular responses to surrounding cues require temporally concerted transcriptional regulation of multiple genes. In prokaryotic cells, a single-input-module motif with one transcription factor regulating multiple target genes can generate coordinated gene expression. In eukaryotic cells, transcriptional activity of a gene is affected by not only transcription factors but also the epigenetic modifications and three-dimensional chromosome structure of the gene. To examine how local gene environment and transcription factor regulation are coupled, we performed a combined analysis of time-course RNA-seq data of TGF-\b{eta} treated MCF10A cells and related epigenomic and Hi-C data. Using Dynamic Regulatory Events Miner (DREM), we clustered differentially expressed genes based on gene expression profiles and associated transcription factors. Genes in each class have similar temporal gene expression patterns and share common transcription factors. Next, we defined a set of linear and radial distribution functions, as used in statistical physics, to measure the distributions of genes within a class both spatially and linearly along the genomic sequence. Remarkably, genes within the same class despite sometimes being separated by tens of million bases (Mb) along genomic sequence show a significantly higher tendency to be spatially close despite sometimes being separated by tens of Mb along the genomic sequence than those belonging to different classes do. Analyses extended to the process of mouse nervous system development arrived at similar conclusions. Future studies will be able to test whether this spatial organization of chromosomes contributes to concerted gene expression.
Deep-Learning-based Millimeter-Wave Massive MIMO for Hybrid Precoding
Date: 2019-01-19 00:00:00
Tasks: Decoder, Deep Learning

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has
been regarded to be an emerging solution for the next generation of
communications, in which hybrid analog and digital precoding is an important
method for reducing the hardware complexity and energy consumption associated
with mixed signal components. However, the fundamental limitations of the
existing hybrid precoding schemes is that they have high computational
complexity and fail to fully exploit the spatial information. To overcome these
limitations, this paper proposes, a deep-learning-enabled mmWave massive MIMO
framework for effective hybrid precoding, in which each selection of the
precoders for obtaining the optimized decoder is regarded as a mapping relation
in the deep neural network (DNN). Specifically, the hybrid precoder is selected
through training based on the DNN for optimizing precoding process of the
mmWave massive MIMO. Additionally, we present extensive simulation results to
validate the excellent performance of the proposed scheme. The results exhibit
that the DNN-based approach is capable ofminimizing the bit error ratio (BER)
and enhancing spectrum efficiency of the mmWave massive MIMO, which achieves
better performance in hybrid precoding compared with conventional schemes while
substantially reducing the required computational complexity.
Optimal redeeming strategy of stock loans under drift uncertainty
Authors: Zuo Quan Xu, Fahuai Yi
Date: 2019-01-20 00:00:00

In practice, one must recognize the inevitable incompleteness of information while making decisions. In this paper, we consider the optimal redeeming problem of stock loans under a state of incomplete information presented by the uncertainty in the (bull or bear) trends of the underlying stock. This is called drift uncertainty. Due to the unavoidable need for the estimation of trends while making decisions, the related Hamilton-Jacobi-Bellman (HJB) equation is of a degenerate parabolic type. Hence, it is very hard to obtain its regularity using the standard approach, making the problem different from the existing optimal redeeming problems without drift uncertainty. We present a thorough and delicate probabilistic and functional analysis to obtain the regularity of the value function and the optimal redeeming strategies. The optimal redeeming strategies of stock loans appear significantly different in the bull and bear trends.
A Backward Simulation Method for Stochastic Optimal Control Problems
Date: 2019-01-20 00:00:00

A number of optimal decision problems with uncertainty can be formulated into
a stochastic optimal control framework. The Least-Squares Monte Carlo (LSMC)
algorithm is a popular numerical method to approach solutions of such
stochastic control problems as analytical solutions are not tractable in
general. This paper generalizes the LSMC algorithm proposed in Shen and Weng
(2017) to solve a wide class of stochastic optimal control models. Our
algorithm has three pillars: a construction of auxiliary stochastic control
model, an artificial simulation of the post-action value of state process, and
a shape-preserving sieve estimation method which equip the algorithm with a
number of merits including bypassing forward simulation and control
randomization, evading extrapolating the value function, and alleviating
computational burden of the tuning parameter selection. The efficacy of the
algorithm is corroborated by an application to pricing equity-linked insurance
products.
Horizontal transfer between loose compartments stabilizes replication of fragmented ribozymes
Date: 2019-01-21 00:00:00

The emergence of replicases that can replicate themselves is a central issue
in the origin of life. Recent experiments suggest that such replicases can be
realized if an RNA polymerase ribozyme is divided into fragments short enough
to be replicable by the ribozyme and if these fragments self-assemble into a
functional ribozyme. However, the continued self-replication of such replicases
requires that the production of every essential fragment be balanced and
sustained. Here, we use mathematical modeling to investigate whether and under
what conditions fragmented replicases achieve continued self-replication. We
first show that under a simple batch condition, the replicases fail to display
continued self-replication owing to positive feedback inherent in these
replicases. This positive feedback inevitably biases replication toward a
subset of fragments, so that the replicases eventually fail to sustain the
production of all essential fragments. We then show that this inherent
instability can be resolved by small rates of random content exchange between
loose compartments (i.e., horizontal transfer). In this case, the balanced
production of all fragments is achieved through negative frequency-dependent
selection operating in the population dynamics of compartments. This selection
mechanism arises from an interaction mediated by horizontal transfer between
intracellular and intercellular symmetry breaking. The horizontal transfer also
ensures the presence of all essential fragments in each compartment, sustaining
self-replication. Taken together, our results underline compartmentalization
and horizontal transfer in the origin of the first self-replicating replicases.
Linking lineage and population observables in biological branching processes
Authors: Reinaldo García-García, Arthur Genthon, David Lacoste
Date: 2019-01-21 00:00:00

Using a population dynamics inspired by an ensemble of growing cells, a set of fluctuation theorems linking observables measured at the lineage and population levels are derived. One of these relations implies specific inequalities comparing the population doubling time with the mean generation time at the lineage or population levels. While these inequalities have been derived before for age controlled models with negligible mother-daughter correlations, we show that they also hold for a broad class of size-controlled models. We discuss the implications of this result for the interpretation of a recent experiment in which the growth of bacteria strains has been probed at the single cell level.
Tracking yeast pheromone receptor Ste2 endocytosis using fluorogen-activating protein tagging
Date: 2019-01-21 00:00:00

To observe internalization of the yeast pheromone receptor Ste2 by
fluorescence microscopy in live cells in real time, we visualized only those
molecules present at the cell surface at the time of agonist engagement (rather
than the total cellular pool) by tagging this receptor at its N-terminus with
an exocellular fluorogen-activating protein (FAP). A FAP is a single-chain
antibody engineered to bind tightly a nonfluorescent, cell-impermeable dye
(fluorogen), thereby generating a fluorescent complex. The utility of FAP
tagging to study trafficking of integral membrane proteins in yeast, which
possesses a cell wall, had not been examined previously. A diverse set of
signal peptides and propeptide sequences were explored to maximize expression.
Maintenance of the optimal FAP-Ste2 chimera intact required deletion of two,
paralogous, glycosylphosphatidylinositol (GPI)-anchored extracellular aspartyl
proteases (Yps1 and Mkc7). FAP-Ste2 exhibited a much brighter and distinct
plasma membrane signal than Ste2-GFP or Ste2-mCherry yet behaved quite
similarly. Using FAP-Ste2, new information was obtained about the mechanism of
its internalization, including novel insights about the roles of the
cargo-selective endocytic adaptors Ldb19/Art1, Rod1/Art4, and Rog3/Art7.
Phosphorylation by the stress-activated MAPK Slt2 down-regulates the yeast TOR complex 2
Date: 2019-01-21 00:00:00

Saccharomyces cerevisiae target of rapamycin (TOR) complex 2 (TORC2) is an
essential regulator of plasma membrane lipid and protein homeostasis. How TORC2
activity is modulated in response to changes in the status of the cell envelope
is unclear. Here we document that TORC2 subunit Avo2 is a direct target of
Slt2, the mitogen-activated protein kinase (MAPK) of the cell wall integrity
pathway. Activation of Slt2 by overexpression of a constitutively active allele
of an upstream Slt2 activator (Pkc1) or by auxin-induced degradation of a
negative Slt2 regulator (Sln1) caused hyperphosphorylation of Avo2 at its MAPK
phosphoacceptor sites in a Slt2-dependent manner and diminished TORC2-mediated
phosphorylation of its major downstream effector, protein kinase Ypk1. Deletion
of Avo2 or expression of a phosphomimetic Avo2 allele rendered cells sensitive
to two stresses (myriocin treatment and elevated exogenous acetic acid) that
the cell requires Ypk1 activation by TORC2 to survive. Thus, Avo2 is necessary
for optimal TORC2 activity, and Slt2-mediated phosphorylation of Avo2
down-regulates TORC2 signaling. Compared with wild-type Avo2, phosphomimetic
Avo2 shows significant displacement from the plasma membrane, suggesting that
Slt2 inhibits TORC2 by promoting Avo2 dissociation. Our findings are the first
demonstration that TORC2 function is regulated by MAPK-mediated
phosphorylation.
Consequences of delays and imperfect implementation of isolation in epidemic control
Date: 2019-01-21 00:00:00
Tasks: Management

For centuries isolation has been the main control strategy of unforeseen
epidemic outbreaks. When implemented in full and without delay, isolation is
very effective. However, flawless implementation is seldom feasible in
practice. We present an epidemic model called SIQ with an isolation protocol,
focusing on the consequences of delays and incomplete identification of
infected hosts. The continuum limit of this model is a system of Delay
Differential Equations, the analysis of which reveals clearly the dependence of
epidemic evolution on model parameters including disease reproductive number,
isolation probability, speed of identification of infected hosts and recovery
rates. Our model offers estimates on minimum response capabilities needed to
curb outbreaks,and predictions of endemic states when containment fails.
Critical response capability is expressed explicitly in terms of parameters
that are easy to obtain, to assist in the evaluation of funding priorities
involving preparedness and epidemics management.
Biogenic magnetic nanoparticles in plants
Authors: Svitlana Gorobets, Oksana Gorobets, Alona Magerman, Yuri Gorobets, Iryna Sharay
Date: 2019-01-22 00:00:00

The genetic programming of biosynthesis of biogenic magnetic nanoparticles (BMNs) in plants was revealed by methods of comparative genomics. The samples of leaves and the root of Nicotiana tabacum, the stems and tubers of Solanum tuberosum and the stems of pea Pisum sativum were examined by scanning probe microscopy (in atomic force and magnetic power modes), and it was found that the BMNs are located in the form of chains in the wall of the phloem sieve tubes (ie, the vascular tissue of plants). Such a localization of BMNs supports the idea that the chains of BMNs in different organs of plants have common metabolic functions. Stray gradient magnetic fields about several thousand Oe, which are created by chains of BMNs, can significantly affect the processes of mass transfer near the membrane of vesicles, granules, organelles, structural elements of the membrane, and others. This process is enhanced in plants when artificial magnetite is added to the soil.
Postoperative brain volumes are associated with one-year neurodevelopmental outcome in children with severe congenital heart disease
Date: 2019-01-22 00:00:00

Children with congenital heart disease (CHD) remain at risk for
neurodevelopmental impairment despite improved peri- and intraoperative care.
Our prospective cohort study aimed to determine the relationship between
perioperative brain volumes and neurodevelopmental outcome in neonates with
severe CHD. Pre- and postoperative cerebral MRI was acquired in term born
neonates with CHD undergoing neonatal cardiopulmonary bypass surgery. Brain
volumes were measured using an atlas prior based automated method. One-year
outcome was assessed with the Bayley-III. CHD infants (n=77) had lower pre- and
postoper-ative total and regional brain volumes compared to controls (n=44, all
p<0.01). CHD infants had poorer cognitive and motor outcome (p<=0.0001) and a
trend towards lower language composite score compared to controls (p=0.06). The
total and selected regional postoperative brain volumes predicted cognitive and
language outcome (all p<0.04). This association was independent of length of
intensive care unit stay for total, cortical, temporal, frontal and cerebellar
volumes. In CHD neonates undergoing cardiopulmonary bypass surgery, pre- and
postoperative brain volumes are reduced, and postoperative brain volumes
predict cognitive and language outcome at one year. Reduced cerebral volumes in
CHD patients could serve as a biomarker for im-paired outcome.
Design of Privacy-Preserving Dynamic Controllers
Date: 2020-04-16 00:00:00
Tasks: Privacy Preserving

As a quantitative criterion for privacy of "mechanisms" in the form of
data-generating processes, the concept of differential privacy was first
proposed in computer science and has later been applied to linear dynamical
systems. However, differential privacy has not been studied in depth together
with other properties of dynamical systems, and it has not been fully utilized
for controller design. In this paper, first we clarify that a classical concept
in systems and control, input observability (sometimes referred to as left
invertibility) has a strong connection with differential privacy. In
particular, we show that the Gaussian mechanism can be made highly
differentially private by adding small noise if the corresponding system is
less input observable. Next, enabled by our new insight into privacy, we
develop a method to design dynamic controllers for the classic tracking control
problem while addressing privacy concerns. We call the obtained controller
through our design method the privacy-preserving controller. The usage of such
controllers is further illustrated by an example of tracking the prescribed
power supply in a DC microgrid installed with smart meters while keeping the
electricity consumers' tracking errors private.
A Biomechanical Study on the Use of Curved Drilling Technique for Treatment of Osteonecrosis of Femoral Head
Date: 2019-01-14 00:00:00

Osteonecrosis occurs due to the loss of blood supply to the bone, leading to
spontaneous death of the trabecular bone. Delayed treatment of the involved
patients results in collapse of the femoral head, which leads to a need for
total hip arthroplasty surgery. Core decompression, as the most popular
technique for treatment of the osteonecrosis, includes removal of the lesion
area by drilling a straight tunnel to the lesion, debriding the dead bone and
replacing it with bone substitutes. However, there are two drawbacks for this
treatment method. First, due to the rigidity of the instruments currently used
during core decompression, lesions cannot be completely removed and/or
excessive healthy bone may also be removed with the lesion. Second, the use of
bone substitutes, despite its biocompatibility and osteoconductivity, may not
provide sufficient mechanical strength and support for the bone. To address
these shortcomings, a novel robot-assisted curved core decompression (CCD)
technique is introduced to provide surgeons with direct access to the lesions
causing minimal damage to the healthy bone. In this study, with the aid of
finite element (FE) simulations, we investigate biomechanical performance of
core decompression using the curved drilling technique in the presence of
normal gait loading. In this regard, we compare the result of the CCD using
bone substitutes and flexible implants with other conventional core
decompression techniques. The study finding shows that the maximum principal
stress occurring at the superior domain of the neck is smaller in the CCD
techniques (i.e. 52.847 MPa) compared to the other core decompression methods.