pwc-archive/papers-with-abstracts huggingface dataset:
Smart Resource Allocation: Beyond the Optimum
Authors: Pol Henarejos
Date: 2020-07-16 00:00:00
Tasks: Management, Scheduling

Dealing with broadcast scenarios has become a relevant topic in the scientific community. Because of interference, resource management presents a challenge, specially when spatial diversity is introduced. Many researches presented theoretical benchmarks, simplifications and low complex schemes, but in fact it is difficult the real implementation. The major part of current works propose iterative solutions, which are far away of feasible results. Since the problem is not convex, iterative solutions are prohibitive. Moreover, they always require the full knowledge of the channel state information. Hence, the feedback channel is often unaffordable and makes impossible to carry a huge amount of information. The present work aims to fill this gap presenting a novel scheme, from the theoretical framework to realistic scheme. It introduces the solution of the maximization of the sum rate in the broadcast scenario with multiple antennas at the transmitter. This solution aims to be realistic and to distribute the complexity between the base station and user equipment. Also, due to its construction, it opens the door to be compatible with LTE standards with no relevant changes. Thus, it allows to combine the resource allocation with scheduling tasks in a LTE environment, fulfilling the feedback requirements and maximizing the sum rate of the system.
Subcarrier-wise Backscatter Communications over Ambient OFDM for Low Power IoT
Authors: Mahyar Nemati, Morteza Soltani, Jie Ding, Jinho Choi
Date: 2020-07-16 00:00:00

Ambient backscatter communication (AmBC) over orthogonal-frequency-division-multiplexing (OFDM) signals has recently been proposed as an appealing technique for low power Internet-of-Things (IoT) applications. The special spectrum structure of OFDM signals provides a range of flexibility in terms of bit-error-rate (BER) performance, data rate, and power consumption. In this paper, we study subcarrier-wise backscatter communication over ambient OFDM signals. This new AmBC is to exploit the special spectrum structure of OFDM to transmit data over its squeezed orthogonal subcarriers. We propose a basis transmission scheme and its two modifications to support a higher data rate with superior BER performance compared to existing methods. The basis scheme can transmit one bit per subcarrier using on-off keying (OOK) modulation in the frequency domain. In the first modification, interleaved subcarrier block transmission model is employed to improve the BER performance of the system in frequency-selective channels. It results in a trade-off between the size of the blocks and data rate. Thus, in the second modification, interleaved index modulation (IM) is employed to mitigate the data rate decrementation of the former modification. It also stabilizes and controls the power of the signal to result in interference reduction for a legacy receiver. Analytical and numerical evaluations provide a proof to see the performance of the proposed method in terms of BER, data rate, and interference.
Gesture Recognition using Reflected Visible and Infrared Light Wave Signals
Authors: Li Yu, Hisham Abuella, Md Zobaer Islam, John F. O'Hara, Christopher Crick, Sabit Ekin
Date: 2020-07-16 00:00:00
Tasks: Gesture Recognition, Hand Gesture Recognition, Hand-Gesture Recognition

In this paper, we demonstrate the ability to recognize hand gestures in a non-contact, wireless fashion using only incoherent light signals reflected from a human subject. Fundamentally distinguished from radar, lidar and camera-based sensing systems, this sensing modality uses only a low-cost light source (e.g., LED) and sensor (e.g., photodetector). The light-wave-based gesture recognition system identifies different gestures from the variations in light intensity reflected from the subject's hand within a short (20-35 cm) range. As users perform different gestures, scattered light forms unique, statistically repeatable, time-domain signatures. These signatures can be learned by repeated sampling to obtain the training model against which unknown gesture signals are tested and categorized. Performance evaluations have been conducted with eight gestures, five subjects, different distances and lighting conditions, and with visible and infrared light sources. The results demonstrate the best hand gesture recognition performance of infrared sensing at 20 cm with an average of 96% accuracy. The developed gesture recognition system is low-cost, effective and non-contact technology for numerous Human-computer Interaction (HCI) applications.
Concept framework for the safety assessment of platooning trucks enabled by V2V communication
Date: 2020-07-16 00:00:00

Large steps are being taken by the industry and R&D organizations in
automated driving technology development, as well as in setting up appropriate
scenario-based safety assessment methods. In this paper a concept framework is
proposed for a very specific group of vehicles: trucks in a platoon enabled by
vehicle-to-vehicle (V2V) communication. The basis is formed by previously
proposed scenario-based assessment methods for individual automated driving
vehicles. These methods however do not consider the inter-vehicle communication
component. It is shown how V2V communication interconnects vehicles in a
system-of-systems, and how to include V2V communication in the scenario
description. The paper also provides a vision to answer the basic question
whether safety assessment should consider the platoon as a whole, or the
individual vehicle in the platoon.
RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks
Authors: Mahyar Nemati, Jihong Park, Jinho Choi
Date: 2020-07-16 00:00:00

The use of millimeter-wave (mmWave) bandwidth is one key enabler to achieve the high data rates in the fifth-generation (5G) cellular systems. However, mmWave signals suffer from significant path loss due to high directivity and sensitivity to blockages, limiting its adoption within small-scale deployments. To enhance the coverage of mmWave communication in 5G and beyond, it is promising to deploy a large number of reconfigurable intelligent surfaces (RISs) that passively reflect mmWave signals towards desired directions. With this motivation, in this work we study the coverage of an RIS-assisted large-scale mmWave cellular network using stochastic geometry, and derive the peak reflection power expression of an RIS and the downlink signal-to-interference ratio (SIR) coverage expression in closed forms. These analytic results clarify the effectiveness of deploying RISs in the mmWave SIR coverage enhancement, while unveiling the major role of the density ratio between active base stations (BSs) and passive RISs. Furthermore, the results show that deploying passive reflectors is as effective as equipping BSs with more active antennas in the mmWave coverage enhancement. Simulation results confirm the tightness of the closed form expressions, corroborating our major findings based on the derived expressions.
Emergent Correlations in Gene Expression Dynamics as Footprints of Resource Competition
Authors: Priya Chakraborty, Sayantari Ghosh
Date: 2020-07-16 00:00:00

Genetic circuits need a cellular environment to operate in, which naturally couples the circuit function with the overall functionality of gene regulatory network. To execute their functions all gene circuits draw resources in the form of RNA polymerases, ribosomes, and tRNAs. Recent experiments pointed out that the role of resource competition on synthetic circuit outputs could be immense. However, the effect of complexity of the circuit architecture on resource sharing dynamics is yet unexplored. In this paper, we employ mathematical modelling and in-silico experiments to identify the sources of resource trade-off and to quantify its impact on the function of a genetic circuit, keeping our focus on regulation of immediate downstream proteins. We take the example of the fluorescent reporters, which are often used as protein read-outs. We show that estimating gene expression dynamics from readings of downstream protein data might be unreliable when the resource is limited and ribosome affinities are asymmetric. We focus on the impact of mRNA copy number and RBS strength on the nonlinear isocline that emerges with two regimes, prominently separated by a tipping point, and study how correlation and competition dominate each other depending on various circuit parameters. Focusing further on genetic toggle circuit, we have identified major effects of resource competition in this model motif, and quantified the observations. The observations are testable in wet-lab experiments, as all the parameters chosen are experimentally relevant.
eSampling: Energy Harvesting ADCs
Authors: Neha Jain, Nir Shlezinger, Bhawna Tiwari, Yonina C. Eldar, Anubha Gupta, Vivek Ashok Bohara, Pydi Ganga Bahubalindruni
Date: 2020-07-16 00:00:00
Tasks: Quantization

Analog-to-digital converters (ADCs) allow physical signals to be processed using digital hardware. The power consumed in conversion grows with the sampling rate and quantization resolution, imposing a major challenge in power-limited systems. A common ADC architecture is based on sample-and-hold (S/H) circuits, where the analog signal is being tracked only for a fraction of the sampling period. In this paper, we propose the concept of eSampling ADCs, which harvest energy from the analog signal during the time periods where the signal is not being tracked. This harvested energy can be used to supplement the ADC itself, paving the way to the possibility of zero-power consumption and power-saving ADCs. We analyze the tradeoff between the ability to recover the sampled signal and the energy harvested, and provide guidelines for setting the sampling rate in the light of accuracy and energy constraints. Our analysis indicates that eSampling ADCs operating with up to 12 bits per sample can acquire bandlimited analog signals such that they can be perfectly recovered without requiring power from the external source. Furthermore, our theoretical results reveal that eSampling ADCs can in fact save power by harvesting more energy than they consume. To verify the feasibility of eSampling ADCs, we present a circuit-level design using standard complementary metal oxide semiconductor (CMOS) 65 nm technology. An eSampling 8-bit ADC which samples at 40 MHZ is designed on a Cadence Virtuoso platform. Our experimental study involving Nyquist rate sampling of bandlimited signals demonstrates that such ADCs are indeed capable of harvesting more energy than that spent during analog-to-digital conversion, without affecting the accuracy.
Steady state running rate sets the speed and accuracy of accumulation of swimming bacterial populations
Authors: Margaritis Voliotis, Jerko Rosko, Teuta Pilizota, Tanniemola Liverpool
Date: 2020-07-16 00:00:00

We study the chemotaxis of a population of genetically identical swimming bacteria undergoing run and tumble dynamics driven by stochastic switching between clockwise and counterclockwise rotation of the flagellar rotary system. Understanding chemotaxis quantitatively requires that one links the switching rate of the rotary system in a gradient of chemoattractant/repellant to experimental measures of the efficiency of a population of bacteria in moving up/down the gradient. Here we achieve this by using a probabilistic model and show that the response of a population to the gradient is complex. We find the changes to a phenotype (the steady state switching rate in the absence of gradients) affects the average speed of the response as well as the width of the distribution and both must be taken into account to optimise the overall response of the population in complex environments. This is due to the behaviour of individuals in the 'tails' of the distribution. Hence we show that for chemotaxis, the behaviour of atypical individuals can have a significant impact on the fitness of a population.
Duality Theory for Robust Utility Maximisation
Authors: Daniel Bartl, Michael Kupper, Ariel Neufeld
Date: 2020-07-16 00:00:00

In this paper we present a duality theory for the robust utility maximisation problem in continuous time for utility functions defined on the positive real axis. Our results are inspired by -- and can be seen as the robust analogues of -- the seminal work of Kramkov & Schachermayer [18]. Namely, we show that if the set of attainable trading outcomes and the set of pricing measures satisfy a bipolar relation, then the utility maximisation problem is in duality with a conjugate problem. We further discuss the existence of optimal trading strategies. In particular, our general results include the case of logarithmic and power utility, and they apply to drift and volatility uncertainty.
Joint Trajectory and Passive Beamforming Design for Intelligent Reflecting Surface-Aided UAV Communications: A Deep Reinforcement Learning Approach
Authors: Liang Wang, Kezhi Wang, Cunhua Pan, Nauman Aslam
Date: 2020-07-16 00:00:00
Tasks: Deep Reinforcement Learning, Fairness

In this paper, the intelligent reflecting surface (IRS)-aided unmanned aerial vehicle (UAV) communication system is studied, where the UAV is deployed to serve the user equipment (UE) with the assistance of multiple IRSs mounted on several buildings to enhance the communication quality between UAV and UE. We aim to maximize the energy efficiency of the system, including the data rate of UE and the energy consumption of UAV via jointly optimizing the UAV's trajectory and the phase shifts of reflecting elements of IRS, when the UE moves and the selection of IRSs is considered for the energy saving purpose. Since the system is complex and the environment is dynamic, it is challenging to derive low-complexity algorithms by using conventional optimization methods. To address this issue, we first propose a deep Q-network (DQN)-based algorithm by discretizing the trajectory, which has the advantage of training time. Furthermore, we propose a deep deterministic policy gradient (DDPG)-based algorithm to tackle the case with continuous trajectory for achieving better performance. The experimental results show that the proposed algorithms achieve considerable performance compared to other traditional solutions.
5-HT2A mediated plasticity as a target in major depression: a narrative review connecting the dots from neurobiology to cognition and psychology
Date: 2020-07-16 00:00:00

As the world's first primary morbidity factor, depression has a considerable
impact on both an individual as well as a societal level. despite their
discovery several decades ago, classical antidepressants have been shown to
provide limited benefits against this condition. However, substances such as
ketamine and psychedelics have recently shown promising results and even
received the grade of Breakthrough therapy for this indication. The accurate
mechanisms of action underlying the efficacy of these substances are still to
be defined, but some similarities appear to be shared on different levels
across these substances. These include their structural, functional and
behavioral plasticity promoting abilities, as well as their capacity to promote
Brain-Derived Neurotrophic Factor overexpression, which seems to constitute a
key element underlying their immediate and long-lasting action. From this
observation, the present review aims to examine and connect the pharmacological
pathways involved in these therapies to the neurobiological, cognitive and
psychological responses that could be shared by both 5-HT2AR agonists and NMDA
antagonists. It is suggested that BDNF overexpression resulting from mTOR
activation mediates both structural and functional plasticity, resulting in
connectivity changes among high-level cognitive networks such as the Default
Mode Network, finally leading to an increased and long-lasting psychological
flexibility. Connecting these pieces of evidence could provide insights about
their precise mechanisms of action and help researchers to develop biomarkers
for antidepressant response. If the hypotheses suggested in this review are
verified by further trials, they could also constitute a starting point to
developing safer and more efficient antidepressants, as well as provide
information about the interactions that exist between different
neurotransmitters systems.
Effects of different feeding frequencies on growth, feed utilisation, digestive enzyme activities and plasma biochemistry of gilthead sea bream (Sparus aurata) fed with different fishmeal and fish oil dietary levels
Authors: S. Busti, A. Bonaldo, F. Dondi, D. Cavallini, M. Yufera, N. Gilannejad, F. J. Moyano, P. P Gatta, L. Parma
Date: 2020-07-14 00:00:00

In the context of Mediterranean aquaculture little attention has been paid to the manipulation of feeding frequency at the on-growing phase. The effects of different feeding frequencies: one meal per day, two meals per day, three meals per day on growth, digestive enzyme activity, feed digestibility and plasma biochemistry were studied in gilthead sea bream (Sparus aurata, L. 1758) fed with high and low fishmeal and fish oil levels. Isonitrogenous and isolipidic extruded diets were fed to triplicate fish groups by a fixed ration over 109 days. No significant effects of feeding frequency on overall performance, feed efficiency and feed digestibility during the on-growing of gilthead sea bream fed high or low fishmeal and fish oil dietary level were observed. Pepsin activity showed an apparent decrease in fish receiving more than one meal a day which was not compensated by an increased production of alkaline proteases particularly in fish fed on low FM. Although there were no effects on growth and feed utilisation at increasing feeding frequency, trypsin decreased significantly with an increasing number of meals only under low FMFO diet. Thus, it seemed that consecutive meals could have amplified the potential trypsin inhibitor effect of the vegetable meal-based diet adopted. Results of the plasma parameters related to nutritional and physiological conditions were not affected by feeding frequency. The higher level of plasma creatinine detected in fish fed a single daily meal with high FMFO level seems to be within physiological values in relation to the higher protein efficiency observed with this diet. According to the results, gilthead sea bream seems able to maximise feed utilisation regardless of the number of meals, and this could be a useful indicator for planning feeding activity at farm level to optimise growth of fish and costs of feeding procedures.
Symmetry and financial Markets
Authors: Jørgen Vitting Andersen, Andrzej Nowak
Date: 2020-07-16 00:00:00
Tasks: Decision Making

It is hard to overstate the importance that the concept of symmetry has had in every field of physics, a fact alluded to by the Nobel Prize winner P.W. Anderson, who once wrote that physics is the study of symmetry. Whereas the idea of symmetry is widely used in science in general, very few (if not almost no) applications has found its way into the field of finance. Still, the phenomenon appears relevant in terms of for example the symmetry of strategies that can happen in the decision making to buy or sell financial shares. Game theory is therefore one obvious avenue where to look for symmetry, but as will be shown, also technical analysis and long term economic growth could be phenomena which show the hallmark of a symmetry
Incorporating compositional heterogeneity into Lie Markov models for phylogenetic inference
Date: 2020-07-17 00:00:00

Phylogenetics uses alignments of molecular sequence data to learn about
evolutionary trees. Substitutions in sequences are modelled through a
continuous-time Markov process, characterised by an instantaneous rate matrix,
which standard models assume is time-reversible and stationary. These
assumptions are biologically questionable and induce a likelihood function
which is invariant to a tree's root position. This hampers inference because a
tree's biological interpretation depends critically on where it is rooted.
Relaxing both assumptions, we introduce a model whose likelihood can
distinguish between rooted trees. The model is non-stationary, with step
changes in the instantaneous rate matrix at each speciation event. Exploiting
recent theoretical work, each rate matrix belongs to a non-reversible family of
Lie Markov models. These models are closed under matrix multiplication, so our
extension offers the conceptually appealing property that a tree and all its
sub-trees could have arisen from the same family of non-stationary models.
  We adopt a Bayesian approach, describe an MCMC algorithm for posterior
inference and provide software. The biological insight that our model can
provide is illustrated through an analysis in which non-reversible but
stationary, and non-stationary but reversible models cannot identify a
plausible root.
Epidemic dynamics with homophily, vaccination choices, and pseudoscience attitudes
Authors: Matteo Bizzarri, Fabrizio Panebianco, Paolo Pin
Date: 2020-07-16 00:00:00

We interpret attitudes towards science and pseudosciences as cultural traits that diffuse in society through communication efforts exerted by agents. We present a tractable model that allows us to study the interaction among the diffusion of an epidemic, vaccination choices, and the dynamics of cultural traits. We apply it to study the impact of homophily between pro-vaxxers and anti-vaxxers on the total number of cases (the cumulative infection). We show that, during the outbreak of a disease, homophily has the direct effect of decreasing the speed of recovery. Hence, it may increase the number of cases and make the disease endemic. The dynamics of the shares of the two cultural traits in the population is crucial in determining the sign of the total effect on the cumulative infection: more homophily is beneficial if agents are not too flexible in changing their cultural trait, is detrimental otherwise.
Quantum Entanglement and Cryptography for Automation and Control of Dynamic Systems
Date: 2020-07-24 00:00:00

This paper addresses the application of quantum entanglement and cryptography
for automation and control of dynamic systems. A dynamic system is a system
where the rates of changes of its state variables are not negligible. Quantum
entanglement is realized by the Spontaneous Parametric Down-conversion process.
Two entangled autonomous systems exhibit correlated behavior without any
classical communication in between them due to the quantum entanglement
phenomenon. Specifically, the behavior of a system, Bob, at a distance, is
correlated with a corresponding system, Alice. In an automation scenario, the
'Bob Robot' is entangled with the 'Alice Robot' in performing autonomous tasks
without any classical connection between them. Quantum cryptography is a
capability that allows guaranteed security. Such capabilities can be
implemented in control of autonomous mechanical systems where, for instance, an
'Alice Autonomous System' can control a 'Bob Autonomous System' for
applications of automation and robotics. The applications of quantum
technologies to mechanical systems, at a scale larger than the atomistic scale,
for control and automation, is a novel contribution of this paper. Notably, the
feedback control transfer function of an integrated classical dynamic system
and a quantum state is proposed.