pwc-archive/papers-with-abstracts huggingface dataset:
Nonlinear Multi-Carrier System with Signal Clipping: Measurement, Analysis, and Optimization
Authors: Yuyang Du, Liang Hao, Yiming Lei, Qun Yang, Shiqi Xu
Date: 2023-10-01 00:00:00

Signal clipping is a classic technique for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It has been widely applied in consumer electronic devices owing to its low complexity and high efficiency. Although clipping reduces the nonlinear distortion caused by power amplifiers (PAs), it induces additional clipping distortion. Optimizing the joint system performance with consideration of both PA nonlinearity and clipping distortion remains an open problem due to the complex PA modeling. In this paper, we analyze the PA nonlinearity through the Bessel-Fourier PA (BFPA) model and simplify its power expression using inter-modulation product (IMP) analysis. We derive expressions of the receiver signal-to-noise ratio (SNR) and system symbol error rate (SER) for the nonlinear clipped OFDM system. With the derivations, we investigate the optimal system setting to achieve the SER lower bound in a practical OFDM system that considers both PA nonlinearity and clipping distortion. The methods and results presented in this paper can serve as a useful reference for the system-level optimization of clipped OFDM systems with nonlinear PA.
An IRS-Assisted Secure Dual-Function Radar-Communication System
Authors: Yi-Kai Li, Athina Petropulu
Date: 2023-10-01 00:00:00

In dual-function radar-communication (DFRC) systems the probing signal contains information intended for the communication users, which makes that information vulnerable to eavesdropping by the targets. We propose a novel design for enhancing the physical layer security (PLS) of DFRC systems, via the help of intelligent reflecting surface (IRS) and artificial noise (AN), transmitted along with the probing waveform. The radar waveform, the AN jamming noise and the IRS parameters are designed to optimize the communication secrecy rate while meeting radar signal-to-noise ratio (SNR) constrains. Key challenges in the resulting optimization problem include the fractional form objective, the SNR being a quartic function of the IRS parameters, and the unit-modulus constraint of the IRS parameters. A fractional programming technique is used to transform the fractional form objective of the optimization problem into more tractable non-fractional polynomials. Numerical results are provided to demonstrate the convergence of the proposed system design algorithm, and also show the impact of the power assigned to the AN on the secrecy performance of the designed system.
An Experimental Prototype for Multistatic Asynchronous ISAC
Authors: Marco Canil, Jacopo Pegoraro, Jesus O. Lacruz, Marco Mezzavilla, Michele Rossi, Joerg Widmer, Sundeep Rangan
Date: 2023-10-01 00:00:00
Tasks: Diversity, ISAC

We prototype and validate a multistatic mmWave ISAC system based on IEEE802.11ay. Compensation of the clock asynchrony between each TX and RX pair is performed using the sole LoS wireless signal propagation. As a result, our system provides concurrent target tracking and micro-Doppler estimation from multiple points of view, paving the way for practical multistatic data fusion. Our results on human movement sensing, complemented with precise, quantitative GT data, demonstrate the enhanced sensing capabilities of multistatic ISAC, due to the spatial diversity of the receiver nodes.
Identifying Distribution Network Faults Using Adaptive Transition Probability
Authors: Xinliang Ma, Weihua Liu, Bingying Jin
Date: 2023-09-30 00:00:00
Tasks: Fault Detection

A novel approach is suggested for improving the accuracy of fault detection in distribution networks. This technique combines adaptive probability learning and waveform decomposition to optimize the similarity of features. Its objective is to discover the most appropriate linear mapping between simulated and real data to minimize distribution differences. By aligning the data in the same feature space, the proposed method effectively overcomes the challenge posed by limited sample size when identifying faults and classifying real data in distribution networks. Experimental results utilizing simulated system data and real field data demonstrate that this approach outperforms commonly used classification models such as convolutional neural networks, support vector machines, and k-nearest neighbors, especially under adaptive learning conditions. Consequently, this research provides a fresh perspective on fault detection in distribution networks, particularly when adaptive learning conditions are employed.
Bayesian Approach for Adaptive EMG Pattern Classification Via Semi-Supervised Sequential Learning
Authors: Seitaro Yoneda, Akira Furui
Date: 2023-09-30 00:00:00
Tasks: Classification

Intuitive human-machine interfaces may be developed using pattern classification to estimate executed human motions from electromyogram (EMG) signals generated during muscle contraction. The continual use of EMG-based interfaces gradually alters signal characteristics owing to electrode shift and muscle fatigue, leading to a gradual decline in classification accuracy. This paper proposes a Bayesian approach for adaptive EMG pattern classification using semi-supervised sequential learning. The proposed method uses a Bayesian classification model based on Gaussian distributions to predict the motion class and estimate its confidence. Pseudo-labels are subsequently assigned to data with high-prediction confidence, and the posterior distributions of the model are sequentially updated within the framework of Bayesian updating, thereby achieving adaptive motion recognition to alterations in signal characteristics over time. Experimental results on six healthy adults demonstrated that the proposed method can suppress the degradation of classification accuracy over time and outperforms conventional methods. These findings demonstrate the validity of the proposed approach and its applicability to practical EMG-based control systems.
One-Bit Channel Estimation for IRS-aided Millimeter-Wave Massive MU-MISO System
Authors: Silei Wang, Qiang Li, Jingran Lin
Date: 2023-09-29 00:00:00
Tasks: Quantization

Recently, intelligent reflecting surface (IRS)-assisted communication has gained considerable attention due to its advantage in extending the coverage and compensating the path loss with low-cost passive metasurface. This paper considers the uplink channel estimation for IRS-aided multiuser massive MISO communications with one-bit ADCs at the base station (BS). The use of one-bit ADC is impelled by the low-cost and power efficient implementation of massive antennas techniques. However, the passiveness of IRS and the lack of signal level information after one-bit quantization make the IRS channel estimation challenging. To tackle this problem, we exploit the structured sparsity of the user-IRS-BS cascaded channels and develop three channel estimators, each of which utilizes the structured sparsity at different levels. Specifically, the first estimator exploits the elementwise sparsity of the cascaded channel and employs the sparse Bayesian learning (SBL) to infer the channel responses via the type-II maximum likelihood (ML) estimation. However, due to the one-bit quantization, the type-II ML in general is intractable. As such, a variational expectation-maximization (EM) algorithm is custom-derived to iteratively compute an ML solution. The second estimator utilizes the common row-structured sparsity induced by the IRS-to-BS channel shared among the users, and develops another type-II ML solution via the block SBL (BSBL) and the variational EM. To further improve the performance of BSBL, a third two-stage estimator is proposed, which can utilize both the common row-structured sparsity and the column-structured sparsity arising from the limited scattering around the users. Simulation results show that the more diverse structured sparsity is exploited, the better estimation performance is achieved, and that the proposed estimators are superior to state-of-the-art one-bit estimators.
Overview of Use Cases in Single Channel Full Duplex Techniques for Satellite Communication
Authors: Victor Monzon Baeza, Steven Kisseleff, Jorge Luis González Rios, Juan Andrés Vasquez-Peralvo, Carlos Mosquera, Roberto López Valcarce, Tomás Ramírez Parracho, Pablo Losada Sanisidro, Juan Carlos Merlano Duncan, Symeon Chatzinotas
Date: 2023-09-29 00:00:00

This paper provides an overview of the diverse range of applications and use cases for Single-Channel Full-Duplex (SCFD) techniques within the field of satellite communication. SCFD, allowing simultaneous transmission and reception on a single frequency channel, presents a transformative approach to enhancing satellite communication systems. We select eight potential use cases with the objective of highlighting the substantial potential of SCFD techniques in revolutionizing SatCom across a multitude of critical domains. In addition, preliminary results from the qualitative assessment are shown. This work is carried out within the European Space Agency (ESA) ongoing activity FDSAT: Single Channel Full Duplex Techniques for Satellite Communications.
Multistationarity questions in reduced vs extended biochemical networks
Authors: Alicia Dickenstein, Magalí Giaroli, Mercedes Pérez Millán, Rick Rischter
Date: 2023-10-03 00:00:00

We address several questions in reduced versus extended networks via the elimination or addition of intermediate complexes in the framework of chemical reaction networks with mass-action kinetics. We clarify and extend advances in the literature concerning multistationarity in this context. We establish general results about MESSI systems, which we use to compute the circuits of multistationarity for significant biochemical networks.
Some Remarks on a Non-Local Variable Carrying Capacity Model for Aphid Population Dynamics
Authors: Aniket Banerjee, Urvashi Verma, Rana D. Parshad
Date: 2023-10-04 00:00:00

Aphids are damaging insect pests on many crops. Their density can rapidly build up on a host plant to several thousand over one growing season. Occasionally, a competition-driven decline in population early in the season, followed by a build-up later, is observed in the field. Such dynamics cannot be captured via standard models, such as introduced in Kindlmann and Dixon, 2010. In Kindlmann et al., 2007, a logistic non-local population model with variable carrying capacity is proposed to capture these alternative dynamics. The proposed model has a rich dynamical structure and can predict multiple population peaks, as observed in the field. We show that additionally, this model also possesses solutions that can blow-up/explode in finite time. The blow-up is seen to occur for both large and small initial conditions and can occur both early and late in the season. We propose a model extension that, under certain parametric restrictions, has global time-bounded solutions. We discuss the ecological applications of our findings.
Analysis of the impact of fear in the presence of additional food and prey refuge with nonlocal predator-prey models
Authors: Sangeeta Saha, Swadesh Pal, Roderick Melnik
Date: 2023-10-02 00:00:00

There are many positive and negative factors present in the predator-prey interaction which affect the net growth of the species. Fear of predation is one such factor that creates psychological stress in a prey species, which causes a negative impact on their overall growth. This work considers a predator-prey model where the prey species faces a reduction in their growth out of fear, and the predator has an alternative food source that helps the prey to hide in a safer place. As an extension into the nonlocal spatio-temporal model, a nonlocal term is considered in the prey growth to incorporate a fear-effect range around their spatial location. Linear stability analysis helps to analyze the temporal model and produces a wide range of interesting results, including the presence of a certain amount of fear or even prey refuge, which helps in population coexistence. Furthermore, the numerical simulations of the local and nonlocal spatio-temporal models show different types of spatial-temporal patterns, such as Turing and non-Turing patterns. Nevertheless, an increase in fear level reduces the range of the Turing domain for the local model, whereas the opposite happens when the range of nonlocal interaction is increased.
Signature Methods in Stochastic Portfolio Theory
Authors: Christa Cuchiero, Janka Möller
Date: 2023-10-03 00:00:00

In the context of stochastic portfolio theory we introduce a novel class of portfolios which we call linear path-functional portfolios. These are portfolios which are determined by certain transformations of linear functions of a collections of feature maps that are non-anticipative path functionals of an underlying semimartingale. As main example for such feature maps we consider the signature of the (ranked) market weights. We prove that these portfolios are universal in the sense that every continuous, possibly path-dependent, portfolio function of the market weights can be uniformly approximated by signature portfolios. We also show that signature portfolios can approximate the growth-optimal portfolio in several classes of non-Markovian market models arbitrarily well and illustrate numerically that the trained signature portfolios are remarkably close to the theoretical growth-optimal portfolios. Besides these universality features, the main numerical advantage lies in the fact that several optimization tasks like maximizing (expected) logarithmic wealth or mean-variance optimization within the class of linear path-functional portfolios reduce to a convex quadratic optimization problem, thus making it computationally highly tractable. We apply our method also to real market data based on several indices. Our results point towards out-performance on the considered out-of-sample data, also in the presence of transaction costs.
Utility-based acceptability indices
Authors: Marcin Pitera, Miklós Rásonyi
Date: 2023-10-03 00:00:00
Tasks: Portfolio Optimization

In this short paper we introduce a new class of performance measures based on certainty equivalents defined via scaled utility functions. We analyse their properties, show that the corresponding portfolio optimization problem is well-posed under generic conditions, and analyse the link between portfolio dynamics, benchmark process, and utility function choice in the long-run setting.
Benzophenone Semicarbazones as Potential alpha-glucosidase and Prolyl Endopeptidase Inhibitor: In-vitro free radical scavenging, enzyme inhibition, mechanistic, and molecular docking studies
Authors: Qurat-ul-Ain Sidra Rafi, Khairullah, Saeedullah, Arshia Arshia, Reaz Uddin, Atia-ul-Wahab, Khalid Mohammed Khan, M. Iqbal Choudhary
Date: 2023-10-02 00:00:00
Tasks: Molecular Docking

$\alpha$-glucosidase and prolylendopeptidase has altered expression and activity patterns in neurological disease, type 2diabetes respectively and several cancers. Here we screened a series 1-29 benzophenone semicarbazone derivatives for in vitro free radical scavenging, alpha-glucosidase and prolylendopeptidase inhibition activities. Seven derivatives were identified as potential free radical scavengers, 14 as alpha-glucosidase, and 9 as prolylendopeptidase inhibitors. Kinetic studies on the most promising inhibitors were performed. Compounds 23, 27, 25 and 28 were found as inhibitor of alpha-glucosidase, while compound 26 inhibited both prolylendopeptidase and alpha-glucosidase. The binding modes and binding free energy of the multi targeted inhibitor 26 were predicted by molecular docking studies. These results provide insights on prolylendopeptidase and alpha-glucosidase inhibition of compound 26 for further development as therapeutic agents for neoplastic, neurological, and endocrine disorders.
Estimation of In-Vitro Free Radical Scavenging and Cytotoxic Activities of Thiocarbohydrazones Derivatives
Authors: Qurat-ul-Ain, Munira Taj Muhammad Khalid Mohammed Khan, M. Iqbal Choudhary
Date: 2023-10-02 00:00:00

Objective: To investigate free radical scavenging potential of thiocarbohydrazones derivatives for the discovery of antioxidant compounds of synthetic origin. Method: Eighteen thiocarbohydrazones derivatives were screened for antioxidant activities by using in vitro radical inhibition assay. Cytotoxicity all derivatives were evaluated using invitro cytotoxicity assay on mouse fibroblast cell line. Results: various compounds of the have shown significant radical scavenging activities as compared with the standard drug butylated hydroxytoluene. In addition in an in vitro cell cytotoxicity assay selected analogues were found to be non-cytotoxic against fibroblast 3T3 cell line. Conclusion: Taken together, these findings all compound this series could be further evaluated in in vivo model of oxidative stress to develop as a therapeutic agent against oxidative stress related disorders due to exhibiting excellent free radical scavenging properties and having their non cytotoxic nature against normal cells.
A biased random walk approach for modeling the collective chemotaxis of neural crest cells
Authors: Viktoria Freingruber, Kevin J. Painter, Mariya Ptashnyk, Linus Schumacher
Date: 2023-10-02 00:00:00

Collective cell migration is a multicellular phenomenon that arises in various biological contexts, including cancer and embryo development. "Collectiveness" can be promoted by cell-cell interactions such as co-attraction and contact inhibition of locomotion. These mechanisms act on cell polarity, pivotal for directed cell motility, through influencing the intracellular dynamics of small GTPases such as Rac1. To model these dynamics we introduce a biased random walk model, where the bias depends on the internal state of Rac1, and the Rac1 state is influenced by cell-cell interactions and chemoattractive cues. In an extensive simulation study we demonstrate and explain the scope and applicability of the introduced model in various scenarios. The use of a biased random walk model allows for the derivation of a corresponding partial differential equation for the cell density while still maintaining a certain level of intracellular detail from the individual based setting.
Sex-specific ultraviolet radiation tolerance across Drosophila
Authors: James E. Titus-McQuillan, Brandon A. Turner, Rebekah L. Rogers
Date: 2023-10-03 00:00:00

The genetic basis of phenotypic differences between species is among the most longstanding questions in evolutionary biology. How new genes form and the processes selection acts to produce differences across species are fundamental to understand how species persist and evolve in an ever-changing environment. Adaptation and genetic innovation arise in the genome by a variety of sources. Functional genomics requires both intrinsic genetic discoveries, as well as empirical testing to observe adaptation between lineages. Here we explore two species of Drosophila on the island of Sao Tome and mainland Africa, D. santomea and D. yakuba. These two species both inhabit the island, but occupy differing species distributions based on elevation, with D. yakuba also having populations on mainland Africa. Intrinsic evidence shows genes between species may have a role in adaptation to higher UV tolerance with DNA repair mechanisms (PARP) and resistance to humeral stress lethal effects (Victoria). We conducted empirical assays between island D. santomea, D. yakuba, and mainland D. yakuba. Flies were shocked with UVB radiation (@ 302 nm) at 1650-1990 mW/cm2 for 30 minutes on a transilluminator apparatus. Custom 5-wall acrylic enclosures were constructed for viewing and containment of flies. All assays were filmed. Island groups did show significant differences between fall-time under UV stress and recovery time post-UV stress test between regions and sex. This study shows evidence that mainland flies are less resistant to UV radiation than their island counterparts. Further work exploring the genetic basis for UV tolerance will be conducted from empirical assays. Understanding the mechanisms and processes that promote adaptation and testing extrinsic traits within the context of the genome is crucially important to understand evolutionary machinery.
A comprehensive comparison of tools for fitting mutational signatures
Authors: Matúš Medo, Charlotte K. Y. Ng, Michaela Medová
Date: 2023-10-02 00:00:00
Tasks: Prognosis

Mutational signatures connect characteristic mutational patterns in the genome with biological or chemical processes that take place in cancers. Analysis of mutational signatures can help elucidate tumor evolution, prognosis, and therapeutic strategies. Although tools for extracting mutational signatures de novo have been extensively benchmarked, a similar effort is lacking for tools that fit known mutational signatures to a given catalog of mutations. We fill this gap by comprehensively evaluating twelve signature fitting tools on synthetic mutational catalogs with empirically-driven signature weights corresponding to eight cancer types. On average, SigProfilerSingleSample and SigProfilerAssignment/MuSiCal perform best for small and large numbers of mutations per sample, respectively. We further show that ad hoc constraining the list of reference signatures is likely to produce inferior results. Evaluation of real mutational catalogs suggests that the activity of signatures that are absent in the reference catalog poses considerable problems to all evaluated tools.
Numerical modeling of hydrogel scaffold anisotropy during extrusion-based 3D printing for tissue engineering
Authors: V. T. Mai, R. Chatelin, E. -J. Courtial, C. Boulocher, R. Rieger
Date: 2023-10-04 00:00:00

Extrusion-based 3D printing is a widely utilized tool in tissue engineering, offering precise 3D control of bioinks to construct organ-sized biomaterial objects with hierarchically organized cellularized scaffolds. The internal organization of scaffold constituents must replicate the structural anisotropy of the targeted tissue to effectively promote cellular behavior during 3D cell culture. The choice of polymers in the bioink and extrusion process topological properties significantly impact tissue engineering constructs' structural anisotropy and cellular response. Our study employed a hydrogel bioink consisting of fibrinogen, alginate, and gelatin, providing biocompatibility, printability, and shape retention post-printing. Topological properties in flowing polymers are determined by macromolecule conformation, namely orientation and stretch degree. We utilized the micro-macro approach to describe hydrogel macromolecule orientation during extrusion, offering a two-scale fluid behavior description. The study aimed to use the Fokker-Planck equation to represent constituent population (polymer chain) state within a hydrogel's representative elementary volume during extrusion-based 3D printing. Our findings indicate that a high shear rate drives constituent orientation in tubular nozzle syringe setups, overcoming fluid rheological behavior. Additionally, the interaction coefficient (C_i), representing microscopic fluid particle interaction, surpasses hydrogel behavior for constituent orientation prediction. This approach provides an initial but robust framework to model scaffold anisotropy, enabling optimization of the extrusion process while maintaining computational feasibility.