pwc-archive/papers-with-abstracts huggingface dataset:
Inequality in the use frequency of patent technology codes
Authors: José Alejandro Mendoza, Faustino Prieto, José María Sarabia
Date: 2021-11-22 00:00:00

Technology codes are assigned to each patent for classification purposes and to identify the components of its novelty. Not all the technology codes are used with the same frequency - if we study the use frequency of codes in a year, we can find predominant technologies used in many patents and technology codes not so frequent as part of a patent. In this paper, we measure that inequality in the use frequency of patent technology codes. First, we analyze the total inequality in that use frequency considering the patent applications filed under the Patent Co-operation Treaty at international phase, with the European Patent Office as designated office, in the period 1977-2018, on a yearly basis. Then, we analyze the decomposition of that inequality by grouping the technology codes by productive economic activities. We show that total inequality had an initial period of growth followed by a phase of relative stabilization, and that it tends to be persistently high. We also show that total inequality was mainly driven by inequality within productive economic activities, with a low contribution of the between-activities component.
Observing Actions in Global Games
Authors: Dominik Grafenhofer, Wolfgang Kuhle
Date: 2021-11-20 00:00:00

We study Bayesian coordination games where agents receive noisy private information over the game's payoffs, and over each others' actions. If private information over actions is of low quality, equilibrium uniqueness obtains in a manner similar to a global games setting. On the contrary, if private information over actions (and thus over the game's payoff coefficient) is precise, agents can coordinate on multiple equilibria. We argue that our results apply to phenomena such as bank-runs, currency crises, recessions, or riots and revolutions, where agents monitor each other closely.
Drewnowski's index to measure lifespan variation: Revisiting the Gini coefficient of the life table
Authors: José Manuel Aburto, Ugofilippo Basellini, Annette Baudisch, Francisco Villavicencio
Date: 2021-11-19 00:00:00

The Gini coefficient of the life table is a concentration index that provides information on lifespan variation. Originally proposed by economists to measure income and wealth inequalities, it has been widely used in population studies to investigate variation in ages at death. We focus on a complementary indicator, Drewnowski's index, which is as a measure of equality. We study its mathematical properties and analyze how changes over time relate to changes in life expectancy. Further, we identify the threshold age below which mortality improvements are translated into decreasing lifespan variation and above which these improvements translate into increasing lifespan inequality. We illustrate our theoretical findings simulating scenarios of mortality improvement in the Gompertz model. Our experiments demonstrate how Drewnowski's index can serve as an indicator of the shape of mortality patterns. These properties, along with our analytical findings, support studying lifespan variation alongside life expectancy trends in multiple species.
Light-weight Gesture Sensing Using FMCW Radar Time Series Data
Authors: Thomas Stadelmayer, Avik Santra, Robert Weigel, Fabian Lurz
Date: 2021-11-22 00:00:00
Tasks: Raspberry Pi 3, Time Series, Time Series Analysis

The paper proposes a novel feature extraction approach for FMCW radar systems in the field of short-range gesture sensing. A light-weight processing is proposed which reduces a series of 3D radar data cubes to four 1D time signals containing information about range, azimuth angle, elevation angle and magnitude. The processing is entirely performed in the time domain without using any Fourier transformation and enables the training of a deep neural network directly on the raw time domain data. It is shown experimentally on real world data, that the proposed processing retains the same expressive power as conventional radar processing to range-, Doppler- and angle-spectrograms. Further, the computational complexity is significantly reduced which makes it perfectly suitable for embedded devices. The system is able to recognize ten different gestures with an accuracy of about 95% and is running in real time on a Raspberry Pi 3 B. The delay between end of gesture and prediction is only 150 ms.
Joint Optimization for Secure Ambient Backscatter Communication in NOMA-enabled IoT Networks
Authors: Wali Ullah Khan, Furqan Jameel, Asim Ihsan, Omer Waqar, Manzoor Ahmed
Date: 2021-11-21 00:00:00

Non-orthogonal multiple access (NOMA) has emerged as a novel air interface technology for massive connectivity in sixth-generation (6G) era. The recent integration of NOMA in backscatter communication (BC) has triggered significant research interest due to its applications in low-powered Internet of Things (IoT) networks. However, the link security aspect of these networks has not been well investigated. This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system. Our system model takes into account the simultaneous operation of NOMA IoT users and the backscatter node (BN) in the presence of multiple eavesdroppers (EDs). The EDs in the surrounding area can overhear the communication of base station (BS) and BN due to the wireless broadcast transmission. Thus, the main objective is to enhance the link security by optimizing the BN reflection coefficient and BS transmit power. To gauge the performance of the proposed scheme, we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes. Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without BC and conventional orthogonal multiple access scheme in terms of system secrecy rate.
Orthogonal Delay Scale Space Modulation: A New Technique for Wideband Time-Varying Channels
Authors: Arunkumar K. P., Chandra R. Murthy
Date: 2021-11-21 00:00:00

Orthogonal Time Frequency Space (OTFS) modulation is a recently proposed scheme for time-varying narrowband channels in terrestrial radio-frequency communications. Underwater acoustic (UWA) and ultra-wideband (UWB) communication systems, on the other hand, confront wideband time-varying channels. Unlike narrowband channels, for which time contractions or dilations due to Doppler effect can be approximated by frequency-shifts, the Doppler effect in wideband channels results in frequency-dependent non-uniform shift of signal frequencies across the band. In this paper, we develop an OTFS-like modulation scheme -- Orthogonal Delay Scale Space (ODSS) modulation -- for handling wideband time-varying channels. We derive the ODSS transmission and reception schemes from first principles. In the process, we introduce the notion of $\omega$-convolution in the delay-scale space that parallels the twisted convolution used in the time-frequency space. The preprocessing 2D transformation from the Fourier-Mellin domain to the delay-scale space in ODSS, which plays the role of inverse symplectic Fourier transform (ISFFT) in OTFS, improves the bit error rate performance compared to OTFS and Orthogonal Frequency Division Multiplexing (OFDM) in wideband time-varying channels. Furthermore, since the channel matrix is rendered near-diagonal, ODSS retains the advantage of OFDM in terms of its low-complexity receiver structure.
Design and Analysis of SWIPT with Safety Constraints
Authors: Constantinos Psomas, Minglei You, Kai Liang, Gan Zheng, Ioannis Krikidis
Date: 2021-11-20 00:00:00

Simultaneous wireless information and power transfer (SWIPT) has long been proposed as a key solution for charging and communicating with low-cost and low-power devices. However, the employment of radio frequency (RF) signals for information/power transfer needs to comply with international health and safety regulations. In this paper, we provide a complete framework for the design and analysis of far-field SWIPT under safety constraints. In particular, we deal with two RF exposure regulations, namely, the specific absorption rate (SAR) and the maximum permissible exposure (MPE). The state-of-the-art regarding SAR and MPE is outlined together with a description as to how these can be modeled in the context of communication networks. We propose a deep learning approach for the design of robust beamforming subject to specific information, energy harvesting and SAR constraints. Furthermore, we present a thorough analytical study for the performance of large-scale SWIPT systems, in terms of information and energy coverage under MPE constraints. This work provides insights with regards to the optimal SWIPT design as well as the potentials from the proper development of SWIPT systems under health and safety restrictions.
Delay Estimation for Ranging and Localization Using Multiband Channel State Information
Authors: Tarik Kazaz, Gerard J. M. Janssen, Jac Romme, Alle-Jan van der Veen
Date: 2021-11-20 00:00:00

In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth of the training signals used for channel probing. Considering that typical training signals have limited bandwidth, delay estimation using these algorithms often leads to poor localization performance. To mitigate these constraints, we exploit the multiband and carrier frequency switching capabilities of wireless transceivers and propose to acquire channel state information (CSI) in multiple bands spread over a large frequency aperture. The data model of the acquired measurements has a multiple shift-invariance structure, and we use this property to develop a high-resolution delay estimation algorithm. We derive the Cram\'er-Rao Bound (CRB) for the data model and perform numerical simulations of the algorithm using system parameters of the emerging IEEE 802.11be standard. Simulations show that the algorithm is asymptotically efficient and converges to the CRB. To validate modeling assumptions, we test the algorithm using channel measurements acquired in real indoor scenarios. From these results, it is seen that delays (ranges) estimated from multiband CSI with a total bandwidth of 320 MHz show an average RMSE of less than 0.3 ns (10 cm) in 90% of the cases.
Pre-scaling and Codebook Design for Joint Radar and Communication Based on Index Modulation
Authors: Shengyang Chen, Aryan Kaushik, Christos Masouros
Date: 2021-11-20 00:00:00
Tasks: Joint Radar-Communication

This paper develops an efficient index modulation (IM) approach for the joint radar-communication (JRC) system based on a multi-carrier multiple-input multiple-output (MIMO) radar. The communication information is embedded into the transmitted radar pulses by selecting the corresponding indices of the carrier frequencies and antenna allocations, providing two degrees of freedom. Our contribution involves the development of a novel codebook based minimum Euclidean distance (MED) maximization and a constellation randomization pre-scaling (CRPS) scheme for efficient IM-JRC transmission. It can be inferred that the IM approach integrating the CRPS scheme followed by the codebook design maximizes the signal-to-noise ratio gain. The numerical results support the effectiveness of the proposed approach and show enhanced bit error rate performance when compared to the existing baseline.
The best of both worlds: Combining population genetic and quantitative genetic models
Authors: Léonard Dekens, Sarah P. Otto, Vincent Calvez
Date: 2021-11-22 00:00:00

Numerous traits under migration-selection balance are shown to exhibit complex patterns of genetic architecture with large variance in effect sizes. However, the conditions under which such genetic architectures are stable have yet to be investigated, because studying the influence of a large number of small allelic effects on the maintenance of spatial polymorphism is mathematically challenging, due to the high complexity of the systems that arise. In particular, in the most simple case of a haploid population in a two-patch environment, while it is known from population genetics that polymorphism at a single major-effect locus is stable in the symmetric case, there exists no analytical predictions on how this polymorphism holds when a polygenic background also contributes to the trait. Here we propose to answer this question by introducing a new eco-evo methodology that allows us to take into account the combined contributions of a major-effect locus and of a quantitative background resulting from small-effect loci, where inheritance is encoded according to an extension to the infinitesimal model. In a regime of small variance contributed by the quantitative loci, we justify that traits are concentrated around the major alleles, according to a normal distribution, using new convex analysis arguments. This allows a reduction in the complexity of the system using a separation of time scales approach. We predict an undocumented phenomenon of loss of polymorphism at the major-effect locus despite strong selection for local adaptation, because the quantitative background slowly disrupts the rapidly established polymorphism at the major-effect locus, which is confirmed by individual-based simulations. Our study highlights how segregation of a quantitative background can greatly impact the dynamics of major-effect loci by provoking migrational meltdowns.
A lattice structure for ancestral configurations arising from the relationship between gene trees and species trees
Authors: Egor Lappo, Noah A. Rosenberg
Date: 2021-11-19 00:00:00

To a given gene tree topology $G$ and species tree topology $S$ with leaves labeled bijectively from a fixed set $X$, one can associate a set of ancestral configurations, each of which encodes a set of gene lineages that can be found at a given node of the species tree. We introduce a lattice structure on ancestral configurations, studying the directed graphs that provide graphical representations of lattices of ancestral configurations. For a matching gene tree topology and species tree topology $G=S$, we present a method for defining the digraph of ancestral configurations from the tree topology by using iterated cartesian products of graphs. We show that a specific set of paths on the digraph of ancestral configurations is in bijection with the set of labeled histories -- a well-known phylogenetic object that enumerates possible temporal orderings of the coalescences of a tree. For each of a series of tree families, we obtain closed-form expressions for the number of labeled histories by using this bijection to count paths on associated digraphs. Finally, we prove that our lattice construction extends to nonmatching tree pairs, and we use it to characterize pairs $(G,S)$ having the maximal number of ancestral configurations for a fixed $G$. We discuss how the construction provides new methods for performing enumerations of combinatorial aspects of gene and species trees.
Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences
Authors: Andonis Gerardos, Nicola Dietler, Anne-Florence Bitbol
Date: 2021-11-22 00:00:00

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families. Does successful inference mainly rely on correlations from structural contacts or from phylogeny, or both? Do these two types of signal combine constructively or hinder each other? To address these questions, we generate and analyze synthetic data produced using a minimal model that allows us to control the amounts of structural constraints and phylogeny. We show that correlations from these two sources combine constructively to increase the performance of partner inference by DCA or MI. Furthermore, signal from phylogeny can rescue partner inference when signal from contacts becomes less informative, including in the realistic case where inter-protein contacts are restricted to a small subset of sites. We also demonstrate that DCA-inferred couplings between non-contact pairs of sites improve partner inference in the presence of strong phylogeny, while deteriorating it otherwise. Moreover, restricting to non-contact pairs of sites preserves inference performance in the presence of strong phylogeny. In a natural data set, as well as in realistic synthetic data based on it, we find that non-contact pairs of sites contribute positively to partner inference performance, and that restricting to them preserves performance, evidencing an important role of phylogeny.
Divergent Evolution of Progesterone and Mineralocorticoid Receptors in Terrestrial Vertebrates and Fish Influences Endocrine Disruption
Authors: Michael E. Baker
Date: 2021-11-20 00:00:00

There is much concern about disruption of endocrine physiology regulated by steroid hormones in humans, other terrestrial vertebrates and fish by industrial chemicals, such as bisphenol A, and pesticides, such as DDT. These endocrine-disrupting chemicals influence steroid-mediated physiology in humans and other vertebrates by competing with steroids for receptor binding sites, disrupting diverse responses involved in reproduction, development and differentiation. Here I discuss that due to evolution of the progesterone receptor (PR) and mineralocorticoid receptor (MR) after ray-finned fish and terrestrial vertebrates diverged from a common ancestor, each receptor evolved to respond to different steroids in ray-finned fish and terrestrial vertebrates. In elephant shark, a cartilaginous fish, ancestral to ray-finned fish and terrestrial vertebrates, both progesterone and 17,20dihydroxyprogesterone activate the PR. During the evolution of ray-finned fish and terrestrial vertebrates, the PR in terrestrial vertebrates continued responding to progesterone and evolved to weakly respond to 17,20dihydroxyprogesterone. In contrast, the physiological progestin for the PR in zebrafish and other ray-finned fish is 17,20dihydroxyprogesterone, and ray-finned fish PR responds weakly to progesterone. The MR in fish and terrestrial vertebrates also diverged to have different responses to progesterone.
Clustering based method for finding spikes in insect neurons
Authors: Smith Gupta
Date: 2021-11-22 00:00:00
Tasks: Clustering

Spikes can be easily detected inmostintracellular recordings as sharp peaks. However, insome experimental preparations,because of unipolar morphology or other characteristicsof the recorded neurons, the sizes of the spikes recorded from the soma can be much smaller. The experimental settings and the quality of the recording can also affect the observed amplitudes of the spikes. Whole-cell patch-clamp recordings from the somata of projection neurons of the antennal lobe in Drosophila or mosquitoes can show spikes with amplitudes as small as 2 mV. Moreover, the observed spikes often ride on relatively large depolarizations, which makes it difficult for the standard thresholding-based approaches to distinguish them from noise or sharp EPSPs present in the signal. For spike detection in such neuronal recordings, we propose a clustering-based algorithm that separates peaks corresponding to action potentials from those corresponding to noise. Candidate peaks, including many noise peaks, are first selected according to their sharpness, and then a feature vector is extracted for each peak. The 3-dimensional feature vector contains the absolute value of the peak voltage, height of the spike, and the magnitude of the second derivative minima attained during the spike. In most recordings, this 3D space reveals two natural clusters, separating the noise peaks from the true action potentials. Some parameters of the algorithm can be optionally altered by the user to improve detection, which comes handy in the few recordings where the default parameters do not work well. In summary, the algorithm facilitates accurate spike detection to enable the interpretation and analysis of patch-clamp data from neuronal recordings in invertebrates. The algorithm is implemented as an freely available open-source tool.
A Neural Network Model of the Entorhinal Cortex and Hippocampus for Event-order Memory Processing
Authors: Hiroki Nakagawa, Katsumi Tateno, Kensuke Takada, Takashi Morie
Date: 2021-11-20 00:00:00
Tasks: Autonomous Navigation, Hippocampus, Retrieval

To solve a navigation task based on experiences, we need a mechanism to associate places with objects and to recall them along the course of action. In a reward-oriented task, if the route to a reward location is simulated in mind after experiencing it once, it might be possible that the reward is gained efficiently. One way to solve it is to incorporate a biologically plausible mechanism. In this study, we propose a neural network that stores a sequence of events associated with a reward. The proposed network recalls the reward location by tracing them in its mind in order. We simulated a virtual mouse that explores a figure-eight maze and recalls the route to the reward location. During the learning period, a sequence of events relating to firing along a passage was temporarily stored in the heteroassociative network, and the sequence of events is consolidated in the synaptic weight matrix when a reward is fed. For retrieval, the sequential activation of conjunctive cue-place cells toward the reward location is internally generated by an impetus input. In the figure-eight maze task, the location of the reward was estimated by mind travel, irrespective of whether the reward is in the counterclockwise or distant clockwise route. The mechanism of efficiently reaching the goal by mind travel in the brain based on experiences is beneficial for mobile service robots that perform autonomous navigation.
Sensitivity analysis in an Immuno-Epidemiological Vector-Host Model
Authors: Hayriye Gulbudak, Zhuolin Qu, Fabio Milner, Necibe Tuncer
Date: 2021-11-22 00:00:00
Tasks: Sensitivity

Sensitivity Analysis (SA) is a useful tool to measure the impact of changes in model parameters on the infection dynamics, particularly to quantify the expected efficacy of disease control strategies. SA has only been applied to epidemic models at the population level, ignoring the effect of within-host virus-with-immune-system interactions on the disease spread. Connecting the scales from individual to population can help inform drug and vaccine development. Thus the value of understanding the impact of immunological parameters on epidemiological quantities. Here we consider an age-since-infection structured vector-host model, in which epidemiological parameters are formulated as functions of within-host virus and antibody densities, governed by an ODE system. We then use SA for these immuno-epidemiological models to investigate the impact of immunological parameters on population-level disease dynamics such as basic reproduction number, final size of the epidemic or the infectiousness at different phases of an outbreak. As a case study, we consider Rift Valley Fever Disease (RFVD) utilizing parameter estimations from prior studies. SA indicates that 1% increase in within-host pathogen growth rate can lead up to 8% increase in R0; up to 1% increase in steady-state infected host abundance, and up to 4% increase in infectiousness of hosts when the reproduction number R0 is larger than one. These significant increases in population-scale disease quantities suggest that control strategies that reduce the within-host pathogen growth can be important in reducing disease prevalence.