pwc-archive/papers-with-abstracts huggingface dataset:
Optimization Algorithms for Improving the Performance of Permutation Trellis Codes
Authors: Oluwafemi Kolade, Mulundumina Shimaponda-Nawa, Daniel J. J. Versfeld, Ling Cheng
Date: 2020-04-19 00:00:00
Tasks: Decoder

In this paper, soft-decision (SD) decoders of permutation trellis code (PTC) with $M$-ary frequency shift keying are designed using three optimization algorithms and presented in four decoding schemes. In a concatenated code such as PTC, the Viterbi decoder for the outer convolutional code provides maximum likelihood decoding. Hence, the error correction performance is dependent on the decoding scheme used for the inner code. Due to the structure of the encoder with the modulation scheme, the channel output can be interpreted as an assignment problem. SD decoding can then be designed accordingly, using the presented, low-complexity optimization-based schemes. The bit error rate (BER) performance of the schemes are simulated in an additive white Gaussian noise (AWGN) and powerline communication (PLC) channel. The complexities of the schemes are also presented. The performance of the SD schemes are compared with the existing SD threshold detector, with BER results showing significant coding gain for certain codebooks. From the results, a reasonable trade-off between the complexity and coding gain is observed for a noisy channel such as the PLC channel.
Hispidin and Lepidine E: two Natural Compounds and Folic acid as Potential Inhibitors of 2019-novel coronavirus Main Protease (2019-nCoVMpro), molecular docking and SAR study
Authors: Talia Serseg, Khedidja Benarous, Mohamed Yousfi
Date: 2020-04-19 00:00:00
Tasks: Molecular Docking

2019-nCoV is a novel coronavirus was isolated and identified in 2019 in Wuhan, China. On 17th February and according to world health organization, a number of 71 429 confirmed cases worldwide, among them 2162 new cases recorded in the last 24 hours. There is no drug or vaccine for human and animal coronavirus. The inhibition of 3CL hydrolase enzyme provides a promising therapeutic principle for developing treatments against CoViD-19. The 3CLpro (Mpro) known for involving in counteracting the host innate immune response. This work presents the inhibitory effect of some natural compounds against 3CL hydrolase enzyme, and explain the main interactions in inhibitor-enzyme complex. Molecular docking study carried out using Autodock Vina. By screening several molecules, we identified three candidate agents that inhibit the main protease of coronavirus. Hispidin, lepidine E, and folic acid bound tightly in the enzyme, strong hydrogen bonds have been formed (1.69-1.80&[Aring]) with the active site residues. This study provides a possible therapeutic strategy for CoViD-19.
Postural control adaptation and habituation during vibratory proprioceptive stimulation: an HD-EEG investigation of cortical recruitment and kinematics
Date: 2020-04-19 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

The objective of the present work is to measure postural kinematics and power
spectral variation from HD-EEG to assess changes in cortical activity during
adaptation and habituation to postural perturbation. To evoke proprioceptive
postural perturbation, vibratory stimulation at 85 Hz was applied to the calf
muscles of 33 subjects over four 75-second stimulation periods. Stimulation was
performed according to a pseudorandom binary sequence. Vibratory impulses were
synchronized to high-density electroencephalography (HD-EEG, 256 channels).
Changes in absolute spectral power (ASP) were analyzed over four frequency
bands (Delta: 0.5-3.5 Hz; theta: 3.5-7.5 Hz; alpha: 7.5-12.5 Hz; beta:12.5-30
Hz). A force platform recorded torque actuated by the feet, and normalized sway
path length (SPL) was computed as a construct for postural performance during
each period. SPL values indicated improvement in postural performance over the
trial periods. Significant variation in absolute power values (ASP) was found
in assessing postural adaptation: an increase in theta band ASP in the
frontal-central region for closed-eyes trials, an increase in theta and beta
band ASP in the parietal region for open-eyes trials. In habituation, no
significant variations in ASP were observed during closed-eyes trials, whereas
an increase in theta, alpha, and beta band ASP was observed with open eyes.
Furthermore, open-eyed trials generally yielded a greater number of significant
ASP differences across all bands during both adaptation and habituation,
suggesting that following cortical activity during postural perturbation may be
up-regulated with the availability of visual feedback. Results provide deeper
insight into pathological postural control failure by exploring the dynamic
changes in both cortical activity and postural kinematics during adaptation and
habituation to proprioceptive postural perturbation.
Real-time Data-driven Quality Assessment for Continuous Manufacturing of Carbon Nanotube Buckypaper
Date: 2020-04-19 00:00:00

Carbon nanotube (CNT) thin sheet, or buckypaper, has shown great potential as
a multifunctional platform material due to its desirable properties, including
its lightweight nature, high mechanical properties, and good conductivity.
However, their mass adoption and applications by industry have run into
significant bottlenecks because of large variability and uncertainty in quality
during fabrication. There is an urgent demand to produce high-quality,
high-performance buckypaper at an industrial scale. Raman spectroscopy provides
detailed nanostructure information within seconds, and the obtained spectra can
be decomposed into multiple effects associated with diverse quality
characteristics of buckypaper. However, the decomposed effects are
high-dimensional, and a systematic quantification method for buckypaper quality
assessment has been lacking. In this paper, we propose a real-time data-driven
quality assessment method, which fills in the blank of quantifying the quality
for continuous manufacturing processes of CNT buckypaper. The composite indices
derived from the proposed method are developed by analyzing in-line Raman
spectroscopy sensing data. Weighted cross-correlation and maximum margin
clustering are used to fuse the fixed effects into an inconsistency index to
monitor the long-term mean shift of the process and to fuse the normal effects
into a uniformity index to monitor the within-sample normality. Those
individual quality indices are then combined into a composite index to reflect
the overall quality of buckypaper. A case study indicates that our proposed
approach can determine the quality rank for ten samples, and can provide
quantitative quality indices for single-walled carbon nanotube buckypaper after
acid processing or functionalization. The quality assessment results are
consistent with evaluations from the experienced engineers.
OAM Mode-Group Generation Method: Partial Arc Transmitting Scheme
Date: 2020-04-19 00:00:00
Tasks: ARC

A partial slotted curved waveguide leaky-wave antenna which can generate
orbital angular momentum (OAM) mode-groups (MG) with high equivalent OAM order
negative and positive 40 at 60 GHz is proposed in this paper. The proposed
antenna with partial slotting is designed according to the circular
traveling-wave antenna which can generate single conventional OAM wave, so it
can be regarded as partial arc transmitting (PAT) scheme compared with the full
2pi aperture slotting of the circular traveling-wave antenna. The full-wave
simulation results show that the generated OAM MGs present a high gain beam
with a helical phase distribution. This method may lead to novel applications
for next generation communication and radar system.
A Semiempirical Dynamical Model to Forecast the Propagation of Epidemics: The Case of the Sars-Cov-2 in Spain
Date: 2020-04-19 00:00:00

A semiempirical model, based in the logistic map, has been succesfully
applied to forecast important quantities along the several phases of the
outbreak of the covid-19 for different countries. This paper shows how the
model was calibrated and applied to perform predictions of people needing to be
hospitalized, needs of ventilators, or the number of deaths which would be
produced. It is shown specifically the results obtained in the case of Spain,
showing a prediction of diagnosed infected and deaths which will be observed
after the ease of the total lockdown produced the 13th of March. Is also shown
how this model can provide an insight of what the level of infection in the
different regions of Spain is forecasted. The model predicts for Spain for the
end of May more than 400,000 diagnosed infected cases, number which will be
probably higher due to the change in the possibilities of performing massive
number of tests to the general population. The number of forecasted deaths for
that date is 46,000 +/- 15,000. The model also predicts the level of infection
at the different Spanish regions, providing a counterintuitive result in the
cases of Madrid and Catalonia as the result shows a higher the level of
infection at Catalonia than the level at Madrid, according with this model. All
of these results can be used to guide policy makers in order to optimize
resources and to avoid future outbreaks of the covid-19.
Consistent Calibration of Economic Scenario Generators: The Case for Conditional Simulation
Authors: Misha van Beek
Date: 2020-04-20 00:00:00
Tasks: Management, Portfolio Optimization

Economic Scenario Generators (ESGs) simulate economic and financial variables forward in time for risk management and asset allocation purposes. It is often not feasible to calibrate the dynamics of all variables within the ESG to historical data alone. Calibration to forward-information such as future scenarios and return expectations is needed for stress testing and portfolio optimization, but no generally accepted methodology is available. This paper introduces the Conditional Scenario Simulator, which is a framework for consistently calibrating simulations and projections of economic and financial variables both to historical data and forward-looking information. The framework can be viewed as a multi-period, multi-factor generalization of the Black-Litterman model, and can embed a wide array of financial and macroeconomic models. Two practical examples demonstrate this in a frequentist and Bayesian setting.
On the integration of Shapley-Scarf housing markets
Authors: Rajnish Kunar, Kriti Manocha, Josue Ortega
Date: 2020-04-20 00:00:00
Tasks: All

We study the welfare consequences of merging Shapley--Scarf markets. Market integration can lead to large welfare losses and make the vast majority of agents worse-off, but is on average welfare-enhancing and makes all agents better off ex-ante. The number of agents harmed by integration is a minority when all markets are small or agents' preferences are highly correlated.
Low-Complexity Detection of Multiweight Permutation Modulation Space-Time Block Codes for Indoor Visible Light Communication
Authors: Oluwafemi Kolade, Ling Cheng
Date: 2020-04-20 00:00:00
Tasks: Decoder

In this paper, the spectral efficiency of permutation modulation-based multiple input multiple output (MIMO) visible light communication is improved using systematically designed, multiweight codeword matrices. Soft-decision, low-complexity detection schemes are then designed for the receiver and compared with the maximum likelihood (ML) detection method. Bit error rate (BER) results show the soft-decision detection algorithm is able to decode the transmitted information without knowledge of the channel state information. This enables the mobile receiver decode information while within the field of view of the transmitter unit. The BER results also show a close match with the ML detection in some codebooks and the performance of the soft-decision decoder is evaluated for different positions of the receiver in an indoor environment.
Experimental digital Gabor hologram rendering by a model-trained convolutional neural network
Date: 2020-04-20 00:00:00

Digital hologram rendering can be performed by a convolutional neural
network, trained with image pairs calculated by numerical wave propagation from
sparse generating images. 512-by-512 pixeldigital Gabor magnitude holograms are
successfully estimated from experimental interferograms by a standard UNet
trained with 50,000 synthetic image pairs over 70 epochs.
OCT4 expression in human embryonic stem cells: spatio-temporal dynamics and fate transitions
Authors: Laura E Wadkin, Sirio Orozco-Fuentes, Irina Neganova, Majlinda Lako, R A Barrio, A W Baggaley, Nicholas G Parker, Anvar Shukurov
Date: 2020-04-20 00:00:00

The improved in-vitro regulation of human embryonic stem cell (hESC) pluripotency and differentiation trajectories is required for their promising clinical applications. The temporal and spatial quantification of the molecular interactions controlling pluripotency is also necessary for the development of successful mathematical and computational models. Here we use time-lapse experimental data of OCT4-mCherry fluorescence intensity to quantify the temporal and spatial dynamics of the pluripotency transcription factor OCT4 in a growing hESC colony in the presence and absence of BMP4. We characterise the internal self-regulation of OCT4 using the Hurst exponent and autocorrelation analysis, quantify the intra-cellular fluctuations and consider the diffusive nature of OCT4 evolution for individual cells and pairs of their descendants. We find that OCT4 abundance in the daughter cells fluctuates sub-diffusively, showing anti-persistent self-regulation. We obtain the stationary probability distributions governing hESC transitions amongst the different cell states and establish the times at which pro-fate cells (which later give rise to pluripotent or differentiated cells) cluster in the colony. By quantifying the similarities between the OCT4 expression amongst neighbouring cells, we show that hESCs express similar OCT4 to cells within their local neighbourhood within the first two days of the experiment and before BMP4 treatment. Our framework allows us to quantify the relevant properties of proliferating hESC colonies and the procedure is widely applicable to other transcription factors and cell populations.
Multi-frequency-band tests for white noise under heteroskedasticity
Date: 2020-04-20 00:00:00

This paper proposes a new family of multi-frequency-band (MFB) tests for the
white noise hypothesis by using the maximum overlap discrete wavelet packet
transform (MODWPT). The MODWPT allows the variance of a process to be
decomposed into the variance of its components on different equal-length
frequency sub-bands, and the MFB tests then measure the distance between the
MODWPT-based variance ratio and its theoretical null value jointly over several
frequency sub-bands. The resulting MFB tests have the chi-squared asymptotic
null distributions under mild conditions, which allow the data to be
heteroskedastic. The MFB tests are shown to have the desirable size and power
performance by simulation studies, and their usefulness is further illustrated
by two applications.
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences
Authors: Quentin Legros, Julian Tachella, Rachael Tobin, Aongus McCarthy, Sylvain Meignen, Gerald S. Buller, Yoann Altmann, Stephen McLaughlin, Michael E. Davies
Date: 2020-04-20 00:00:00
Tasks: 3D Reconstruction, Depth Estimation

In this paper, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon lidar in practical applications is the presence of strong ambient illumination which corrupts the data and can jeopardize the detection of peaks/surface in the signals. This background noise not only complicates the observation model classically used for 3D reconstruction but also the estimation procedure which requires iterative methods. In this work, we consider a new similarity measure for robust depth estimation, which allows us to use a simple observation model and a non-iterative estimation procedure while being robust to mis-specification of the background illumination model. This choice leads to a computationally attractive depth estimation procedure without significant degradation of the reconstruction performance. This new depth estimation procedure is coupled with a spatio-temporal model to capture the natural correlation between neighboring pixels and successive frames for dynamic scene analysis. The resulting online inference process is scalable and well suited for parallel implementation. The benefits of the proposed method are demonstrated through a series of experiments conducted with simulated and real single-photon lidar videos, allowing the analysis of dynamic scenes at 325 m observed under extreme ambient illumination conditions.
On the origin of the standard genetic code as a fusion of prebiotic single-base-pair codes
Authors: A. Nesterov-Mueller, R. Popov
Date: 2020-04-20 00:00:00
Tasks: Translation

The genesis of the stand genetic code is considered as a result of a fusion of two AU- and GC-codes distributed in two dominant and two recessive domains. The fusion of these codes is described with simple empirical rules. This formal approach explains the number of the proteinogenic amino acids and the codon assignment in the resulting standard genetic code. It shows how norleucine, pyrrolysine, selenocysteine and two other unknown amino acids, included into the prebiotic codes, disappeared after the fusion. The properties of these two missing amino acids were described. The ambiguous translation observed in mitochondria is explained. The internal structure of the codes allows a more detailed insights into molecular evolution in prebiotic time. In particular, the structure of the oldest single base-pair code is presented. The fusion concept reveals the appearance of the DNA machinery on the level of the single dominant AU-code. The time before the appearance of standard genetic code is divided into four epochs: pre-DNA, 2-code, pre-fusion, and after-fusion epochs. The prebiotic single-base-pair codes may help design novel peptide-based catalysts.
High-speed x-ray imaging with single-pixel detector
Date: 2020-04-20 00:00:00
Tasks: Vocal Bursts Intensity Prediction

We demonstrate experimentally the ability to use a single pixel detector for
two-dimensional high-speed and high-resolution x-ray imaging. We image the
rotation of a spinning chopper at 100-kHz at spatial resolution of about 15
microns by using the computational ghost imaging approach. The technique we
develop can be used for the imaging of high-speed periodic dynamics or
periodically stimulated effects with a large field of view and at low dose.
A Social Network Analysis of Occupational Segregation
Authors: I. Sebastian Buhai, Marco J. van der Leij
Date: 2020-04-20 00:00:00

We propose an equilibrium interaction model of occupational segregation and labor market inequality between two social groups, generated exclusively through the documented tendency to refer informal job seekers of identical "social color". The expected social color homophily in job referrals strategically induces distinct career choices for individuals from different social groups, which further translates into stable partial occupational segregation equilibria with sustained wage and employment inequality -- in line with observed patterns of racial or gender labor market disparities. Supporting the qualitative analysis with a calibration and simulation exercise, we furthermore show that both first and second best utilitarian social optima entail segregation, any integration policy requiring explicit distributional concerns. Our framework highlights that the mere social interaction through homophilous contact networks can be a pivotal channel for the propagation and persistence of gender and racial labor market gaps, complementary to long studied mechanisms such as taste or statistical discrimination.
Confinement strategies in a simple SIR model
Date: 2020-04-20 00:00:00
Tasks: model

We propose a simple SIR model in order to investigate the impact of various
confinement strategies on a most virulent epidemic. Our approach is motivated
by the current COVID-19 pandemic. The main hypothesis is the existence of two
populations of susceptible persons, one which obeys confinement and for which
the infection rate does not exceed 1, and a population which, being non
confined for various imperatives, can be substantially more infective. The
model, initially formulated as a differential system, is discretised following
a specific procedure, the discrete system serving as an integrator for the
differential one. Our model is calibrated so as to correspond to what is
observed in the COVID-19 epidemic.
  Several conclusions can be reached, despite the very simple structure of our
model. First, it is not possible to pinpoint the genesis of the epidemic by
just analysing data from when the epidemic is in full swing. It may well turn
out that the epidemic has reached a sizeable part of the world months before it
became noticeable. Concerning the confinement scenarios, a universal feature of
all our simulations is that relaxing the lockdown constraints leads to a
rekindling of the epidemic. Thus we sought the conditions for the second
epidemic peak to be lower than the first one. This is possible in all the
scenarios considered (abrupt, progressive or stepwise exit) but typically a
progressive exit can start earlier than an abrupt one. However, by the time the
progressive exit is complete, the overall confinement times are not too
different. From our results, the most promising strategy is that of a stepwise
exit. And in fact its implementation could be quite feasible, with the major
part of the population (minus the fragile groups) exiting simultaneously but
obeying rigorous distancing constraints.
Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals
Date: 2020-04-16 00:00:00

The United Nations' ambitions to combat climate change and prosper human
development are manifested in the Paris Agreement and the Sustainable
Development Goals (SDGs), respectively. These are inherently inter-linked as
progress towards some of these objectives may accelerate or hinder progress
towards others. We investigate how these two agendas influence each other by
defining networks of 18 nodes, consisting of the 17 SDGs and climate change,
for various groupings of countries. We compute a non-linear measure of
conditional dependence, the partial distance correlation, given any subset of
the remaining 16 variables. These correlations are treated as weights on edges,
and weighted eigenvector centralities are calculated to determine the most
important nodes. We find that SDG 6, clean water and sanitation, and SDG 4,
quality education, are most central across nearly all groupings of countries.
In developing regions, SDG 17, partnerships for the goals, is strongly
connected to the progress of other objectives in the two agendas whilst,
somewhat surprisingly, SDG 8, decent work and economic growth, is not as
important in terms of eigenvector centrality.
High-Order Synchrosqueezing Transform for Multicomponent Signals Analysis -- With an Application to Gravitational-Wave Signal
Date: 2020-04-20 00:00:00

This study puts forward a generalization of the short-time Fourier-based
Synchrosqueezing Transform using a new local estimate of instantaneous
frequency. Such a technique enables not only to achieve a highly concentrated
time-frequency representation for a wide variety of AM-FM multicomponent
signals but also to reconstruct their modes with a high accuracy. Numerical
investigation on synthetic and gravitational-wave signals shows the efficiency
of this new approach.