pwc-archive/papers-with-abstracts huggingface dataset:
What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?
Authors: Anthony Strittmatter
Date: 2018-12-16 00:00:00

Recent studies have proposed causal machine learning (CML) methods to estimate conditional average treatment effects (CATEs). In this study, I investigate whether CML methods add value compared to conventional CATE estimators by re-evaluating Connecticut's Jobs First welfare experiment. This experiment entails a mix of positive and negative work incentives. Previous studies show that it is hard to tackle the effect heterogeneity of Jobs First by means of CATEs. I report evidence that CML methods can provide support for the theoretical labor supply predictions. Furthermore, I document reasons why some conventional CATE estimators fail and discuss the limitations of CML methods.
Massive MIMO Antenna Selection: Asymptotic Upper Capacity Bound and Partial CSI
Date: 2018-12-17 00:00:00

Antenna selection (AS) is regarded as the key promising technology to reduce
hardware cost but keep relatively high spectral efficiency in multi-antenna
systems. By selecting a subset of antennas to transceive messages, AS greatly
alleviates the requirement on Radio Frequency (RF) chains. This paper studies
receive antenna selection in massive multiple-input multiple-output (MIMO)
systems. The receiver, equipped with a large-scale antenna array whose size is
much larger than that of the transmitter, selects a subset of antennas to
receive messages. A low-complexity asymptotic approximated upper capacity bound
is derived in the limit of massive MIMO systems over independent and identical
distributed (i.i.d.) Rayleigh flat fading channel, assuming that the channel
side information (CSI) is only available at the receiver. Furthermore,
numerical simulations are provided to demonstrate the approximation precision
of the asymptotic results and the tightness of the capacity bound. Besides the
asymptotic analysis of the upper bound, more discussions on the ergodic
capacity of the antenna selection systems are exhibited. By defining the number
of corresponding rows in the channel matrix as the amount of acquired CSI, the
relationship between the achievable channel capacity and the amount of acquired
CSI is investigated. Our findings indicate that this relationship approximately
follows the Pareto principle, i.e., most of the capacity can be achieved by
acquiring a small portion of full CSI. Finally, on the basis of this observed
law, an adaptive AS algorithm is proposed, which can achieve most of the
transmission rate but requires much less CSI and computation complexity
compared to state-of-the-art methods.
UWB Air-to-Ground Propagation Channel Measurements and Modeling using UAVs
Date: 2018-12-17 00:00:00

This paper presents an experimental study of the air-to-ground (AG)
propagation channel through ultrawideband(UWB) measurements in an open area
using unmanned-aerial-vehicles (UAVs). Measurements were performed using UWB
radios operating at a frequency range of 3.1 GHz - 4.8 GHz and UWB planar
elliptical dipole antennas having an omni-directional pattern in the azimuth
plane and typical donut shaped pattern in the elevation plane. Three scenarios
were considered for the channel measurements: (i)two receivers (RXs) at
different heights above the ground and placed close to each other in
line-of-sight (LOS) with the transmitter (TX) on the UAV and the UAV is
hovering; (ii) RXs are in obstructed line-of-sight (OLOS) with the UAV TX due
to foliage, and the UAV is hovering; and, (iii) UAV is moving in a circular
path. Different horizontal and vertical distances between the RXs and TX were
used in the measurements. In addition, two different antenna orientations were
used on the UAV antennas (vertical and horizontal) to analyze the effects of
antenna radiation patterns on the UWB AG propagation. From the empirical
results, it was observed that the received power depends mainly on the antenna
radiation pattern in the elevation plane when the antennas are oriented in the
same direction, as expected for these omni-azimuth antennas. Moreover, the
overall antenna gain at the TX and RX can be approximated using trigonometric
functions of the elevation angle.
How the network properties of shareholders vary with investor type and country
Date: 2019-09-26 00:00:00

We construct two examples of shareholder networks in which shareholders are
connected if they have shares in the same company. We do this for the
shareholders in Turkish companies and we compare this against the network
formed from the shareholdings in Dutch companies. We analyse the properties of
these two networks in terms of the different types of shareholder. We create a
suitable randomised version of these networks to enable us to find significant
features in our networks. For that we find the roles played by different types
of shareholder in these networks, and also show how these roles differ in the
two countries we study.
An Equivalent Circuit Formulation for Power System State Estimation including PMUs
Date: 2018-12-17 00:00:00
Tasks: State Estimation

In this paper, a novel formulation for the power system state estimation is
proposed, based on the recently introduced equivalent split-circuit formulation
of the power flow problem. The formulation models the conventional and time
synchronized measurements simultaneously and contains a significantly lower
level of nonlinearity compared to the available hybrid state estimators. The
appropriate circuit models are derived for different types of measurements and
integrated into the existing circuit framework for the power flow problem. A
constrained optimization problem is then formulated to estimate the states of
the system in rectangular coordinates, while satisfying the circuit equations
and bounds on the measurement data. To further prove the concept and validate
the accuracy of the proposed formulation, several test cases are solved and the
results are presented and discussed.
Fast and Accurate Depth Estimation from Sparse Light Fields
Date: 2018-12-17 00:00:00
Tasks: Depth Estimation, Superpixels

We present a fast and accurate method for dense depth reconstruction from
sparsely sampled light fields obtained using a synchronized camera array. In
our method, the source images are over-segmented into non-overlapping compact
superpixels that are used as basic data units for depth estimation and
refinement. Superpixel representation provides a desirable reduction in the
computational cost while preserving the image geometry with respect to the
object contours. Each superpixel is modeled as a plane in the image space,
allowing depth values to vary smoothly within the superpixel area. Initial
depth maps, which are obtained by plane sweeping, are iteratively refined by
propagating good correspondences within an image. To ensure the fast
convergence of the iterative optimization process, we employ a highly parallel
propagation scheme that operates on all the superpixels of all the images at
once, making full use of the parallel graphics hardware. A few optimization
iterations of the energy function incorporating superpixel-wise smoothness and
geometric consistency constraints allows to recover depth with high accuracy in
textured and textureless regions as well as areas with occlusions, producing
dense globally consistent depth maps. We demonstrate that while the depth
reconstruction takes about a second per full high-definition view, the accuracy
of the obtained depth maps is comparable with the state-of-the-art results.
Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks
Date: 2019-03-25 00:00:00

Neural activity exhibits a vast range of timescales that can be several fold
larger than the membrane time constant of individual neurons. Two types of
mechanisms have been proposed to explain this conundrum. One possibility is
that large timescales are generated by a network mechanism based on positive
feedback, but this hypothesis requires fine-tuning of the synaptic connections.
A second possibility is that large timescales in the neural dynamics are
inherited from large timescales of underlying biophysical processes, two
prominent candidates being adaptive ionic currents and synaptic transmission.
How the timescales of these processes influence the timescale of the network
dynamics has however not been fully explored. To address this question, we
analyze large networks of randomly connected excitatory and inhibitory units
with additional degrees of freedom that correspond to adaptation or synaptic
filtering. We determine the fixed points of the systems, their stability to
perturbations and the corresponding dynamical timescales. Furthermore, we apply
dynamical mean field theory to study the temporal statistics of the activity in
the fluctuating regime, and examine how the adaptation and synaptic timescales
transfer from individual units to the whole population. Our overarching finding
is that synaptic filtering and adaptation in single neurons have very different
effects at the network level. Unexpectedly, the macroscopic network dynamics do
not inherit the large timescale present in adaptive currents. In contrast, the
timescales of network activity increase proportionally to the time constant of
the synaptic filter. Altogether, our study demonstrates that the timescales of
different biophysical processes have different effects on the network level, so
that the slow processes within individual neurons do not necessarily induce
slow activity in large recurrent neural networks.
Resolving dynamics and function of transient states in single enzyme molecules
Date: 2018-12-17 00:00:00

We used a hybrid fluorescence spectroscopic toolkit to monitor T4 Lysozyme
(T4L) in action. By unraveling the kinetic and dynamic interplay of the
conformational states, we sought to elucidate the dynamic structural biology of
T4L. In particular, by combining single-molecule and ensemble multiparameter
fluorescence detection, EPR spectroscopy, mutagenesis, and FRET-positioning and
screening, we characterized three short-lived conformational states within the
conformational landscape of the T4L over the ns-ms timescale. The use of 33
FRET-derived distance sets, to screen known T4L structures, revealed that T4L
in solution mainly adopts the known open and closed states in exchange at 4
$\mu$s. A newly found minor state, undisclosed by at present more than 500
crystal structures of T4L and sampled at 230 $\mu$s, may be actively involved
in the product release step in catalysis. The presented fluorescence
spectroscopic toolkit is anticipated to accelerate the development of dynamic
structural biology.
VLC Systems with CGHs
Date: 2018-11-12 00:00:00

The achievable data rate in indoor wireless systems that employ visible light
communication (VLC) can be limited by multipath propagation. Here, we use
computer generated holograms (CGHs) in VLC system design to improve the
achievable system data rate. The CGHs are utilized to produce a fixed broad
beam from the light source, selecting the light source that offers the best
performance. The CGHs direct this beam to a specific zone on the room's
communication floor where the receiver is located. This reduces the effect of
diffuse reflections. Consequently, decreasing the intersymbol interference
(ISI) and enabling the VLC indoor channel to support higher data rates. We
consider two settings to examine our propose VLC system and consider lighting
constraints. We evaluate the performance in idealistic and realistic room
setting in a diffuse environment with up to second order reflections and also
under mobility. The results show that using the CGHs enhances the 3dB bandwidth
of the VLC channel and improves the received optical power.
An Agent-Based Model for Bovine Viral Diarrhea
Date: 2018-12-14 00:00:00
Tasks: model

We present an exhaustive description of a stochastic, event-driven,
hierarchical agent-based model designed to reproduce the infectious state of
the cattle disease called Bovine Viral Diarrhea, for which the livestock-trade
network is the main route of spreading. For the farm-node dynamics, it takes
into account a vast number of breeding, infectious and animal movement
mechanisms via a susceptible-infected-recovered type of dynamics with an
additional permanently infectious class. The interaction between the farms is
described by a supply-demand farm manager mechanism governing the network
structure and dynamics. The model includes realistic disease and breeding
dynamics and allows to study numerous mitigation strategies of present and past
government regulations, including different testing and vaccination scenarios.
A minimal HIV-AIDS infection model with general incidence rate and application to Morocco data
Date: 2018-12-15 00:00:00
Tasks: Sensitivity

We study the global dynamics of a SICA infection model with general incidence
rate. The proposed model is calibrated with cumulative cases of infection by
HIV-AIDS in Morocco from 1986 to 2015. We first prove that our model is
biologically and mathematically well-posed. Stability analysis of different
steady states is performed and threshold parameters are identified where the
model exhibits clearance of infection or maintenance of a chronic infection.
Furthermore, we examine the robustness of the model to some parameter values by
examining the sensitivity of the basic reproduction number. Finally, using
numerical simulations with real data from Morocco, we show that the model
predicts well such reality.
Sample clock frequency offset (SCFO) Resolution Team 3 (RT-3) investigation
Date: 2018-12-18 00:00:00

This Resolution Team 3 (RT-3) report contains the results of the
investigation of key aspects of the proposed Sample Clock Frequency Offset
(SCFO) scheme for the Mid SKA1 telescope. This is a scheme, first proposed by
one author (Carlson) at a meeting at the SKAO 25-Jan-2013, to digitize the
analog signal at each antenna at a slightly different sample rate and transmit
the data to the CSP Mid.CBF for subsequent digital re-sampling to a common
sample clock frequency before channelization, correlation, and beamforming. The
primary purpose for doing this is to cause de-correlation of sample
clock-related self-interference to be able to improve correlated and beamformed
signal quality. This report includes an investigation of the efficacy of the
method, investigation of its implementation by SADT, DISH, and CSP,
presentation of further supporting modeling results augmenting the original
modeling work, a note on expansion to SKA-2, as well as possible draw-backs and
concerns. Finally, there are potential additional benefits in signal quality in
implementing the SCFO scheme, in particular de-correlation of aliased RFI
(particularly for Nyquist Zone-2 digitized signals) as well as relaxation of
signal-chain anti-aliasing filters transition band roll-off and reject band
attenuation prior to digitization in the antenna.
Systemic risk governance in a dynamical model of a banking system
Date: 2018-12-17 00:00:00

We consider the problem of governing systemic risk in a banking system model.
The banking system model consists in an initial value problem for a system of
stochastic differential equations whose dependent variables are the
log-monetary reserves of the banks as functions of time. The banking system
model considered generalizes previous models studied in [5], [4], [7] and
describes an homogeneous population of banks. Two distinct mechanisms are used
to model the cooperation among banks and the cooperation between banks and
monetary authority. These mechanisms are regulated respectively by the
parameters $\alpha$ and $\gamma$. A bank fails when its log-monetary reserves
go below an assigned default level. We call systemic risk or systemic event in
a bounded time interval the fact that in that time interval at least a given
fraction of the banks fails. The probability of systemic risk in a bounded time
interval is evaluated using statistical simulation. A method to govern the
probability of systemic risk in a bounded time interval is presented. The goal
of the governance is to keep the probability of systemic risk in a bounded time
interval between two given thresholds. The governance is based on the choice of
the log-monetary reserves of a kind of "ideal bank" as a function of time and
on the solution of an optimal control problem for the mean field approximation
of the banking system model. The solution of the optimal control problem
determines the parameters $\alpha$ and $\gamma$ as functions of time, that is
defines the rules of the borrowing and lending activity among banks and between
banks and monetary authority. Some numerical examples are discussed. The
systemic risk governance is tested in absence and in presence of positive and
negative shocks acting on the banking system.
Dynamic anticipation by Cdk2/Cyclin A-bound p27 mediates signal integration in cell cycle regulation
Authors: Maksym Tsytlonok, Hugo Sanabria, Yuefeng Wang, Suren Felekyan, Katherina Hemmen, Aaron Phillips, Mi-Kyung Yun, Brett Waddell, Cheon-Gil Park, Sivaraja Vaithiyalingam, Luigi Iconaru, Stephen W. White, Peter Tompa, Claus A. M. Seidel, Richard Kriwacki
Date: 2018-12-17 00:00:00

p27$^{Kip1}$ (p27) is an intrinsically disordered protein (IDP) that folds upon binding to cyclin-dependent kinase (Cdk)$/$cyclin complexes (e.g., Cdk2$/$cyclin A), inhibiting their catalytic activity and causing cell cycle arrest. However, cell division progresses when stably Cdk2$/$cyclin A-bound p27 is phosphorylated on one or two structurally occluded tyrosine residues $[$tyrosines 88 (Y88) and 74 (Y74)$]$ and a distal threonine residue $[$threonine 187 (T187)$]$. These events trigger ubiquitination and degradation of p27, fully activating Cdk2$/$cyclin A to drive cell division. Using an integrated approach comprising structural, biochemical, biophysical and single-molecule fluorescence methods, we show that Cdk2$/$cyclin A-bound p27 samples lowly-populated conformations that dynamically anticipate the sequential steps of this signaling cascade. "Dynamic anticipation" provides access to the non-receptor tyrosine kinases, BCR-ABL and Src, which sequentially phosphorylate Y88 and Y74 and promote intra-assembly phosphorylation (of p27) on distal T187. Tyrosine phosphorylation also allosterically relieves p27-dependent inhibition of substrate binding to Cdk2$/$cyclin A, a phenomenon we term "cross-complex allostery". Even when tightly bound to Cdk2$/$cyclin A, intrinsic flexibility enables p27 to integrate and process signaling inputs, and generate outputs including altered Cdk2 activity, p27 stability, and, ultimately, cell cycle progression. Intrinsic dynamics within multi-component assemblies may be a general mechanism of signaling by regulatory IDPs, which can be subverted in human disease, as exemplified by hyper-active BCR-ABL and Src in certain cancers.
Surface curvature guides early construction activity in mound-building termites
Date: 2018-12-17 00:00:00

Termite colonies construct towering, complex mounds, in a classic example of
distributed agents coordinating their activity via interaction with a shared
environment. The traditional explanation for how this coordination occurs
focuses on the idea of a "cement pheromone", a chemical signal left with
deposited soil that triggers further deposition. Recent research has called
this idea into question, pointing to a more complicated behavioral response to
cues perceived with multiple senses. In this work, we explored the role of
topological cues in affecting early construction activity in Macrotermes. We
created artificial surfaces with a known range of curvatures, coated them with
nest soil, placed groups of major workers on them, and evaluated soil
displacement as a function of location at the end of one hour. Each point on
the surface has a given curvature, inclination, and absolute height; to
disambiguate these factors, we conducted experiments with the surface in
different orientations. Soil displacement activity is consistently correlated
with surface curvature, and not with inclination nor height. Early exploration
activity is also correlated with curvature, to a lesser degree. Topographical
cues provide a long-term physical memory of building activity in a manner that
ephemeral pheromone labeling cannot. Elucidating the roles of these and other
cues for group coordination may help provide organizing principles for swarm
robotics and other artificial systems.
Understanding Mobile Search Task Relevance and User Behaviour in Context
Authors: Aliannejadi Mohammad, Harvey Morgan, Costa Luca, Pointon Matthew, Crestani Fabio
Date: 2019-01-13 00:00:00
Tasks: Information Retrieval, Retrieval

Improvements in mobile technologies have led to a dramatic change in how and
when people access and use information, and is having a profound impact on how
users address their daily information needs. Smart phones are rapidly becoming
our main method of accessing information and are frequently used to perform
`on-the-go' search tasks. As research into information retrieval continues to
evolve, evaluating search behaviour in context is relatively new. Previous
research has studied the effects of context through either self-reported diary
studies or quantitative log analysis; however, neither approach is able to
accurately capture context of use at the time of searching. In this study, we
aim to gain a better understanding of task relevance and search behaviour via a
task-based user study (n=31) employing a bespoke Android app. The app allowed
us to accurately capture the user's context when completing tasks at different
times of the day over the period of a week. Through analysis of the collected
data, we gain a better understanding of how using smart phones on the go
impacts search behaviour, search performance and task relevance and whether or
not the actual context is an important factor.
Style Transfer and Extraction for the Handwritten Letters Using Deep Learning
Authors: Mohammed Omar, Bailly Gerard, Pellier Damien
Date: 2018-12-10 00:00:00
Tasks: Style Transfer

How can we learn, transfer and extract handwriting styles using deep neural
networks? This paper explores these questions using a deep conditioned
autoencoder on the IRON-OFF handwriting data-set. We perform three experiments
that systematically explore the quality of our style extraction procedure.
First, We compare our model to handwriting benchmarks using multidimensional
performance metrics. Second, we explore the quality of style transfer, i.e. how
the model performs on new, unseen writers. In both experiments, we improve the
metrics of state of the art methods by a large margin. Lastly, we analyze the
latent space of our model, and we see that it separates consistently writing
styles.