pwc-archive/papers-with-abstracts huggingface dataset:
A Spatial Data Focusing and Generalized Time-invariant Frequency Diverse Array Approach for High Precision Range-angle-based Geocasting
Authors: Guylian Molineaux, Francois Horlin, Philippe De Doncker, Julien Sarrazin
Date: 2023-02-24 00:00:00

A novel unified frequency diverse array (FDA) and spatial data focusing (SDF) approach is proposed to simultaneously overcome time-variance and precision constraints of conventional FDA in geocasting, i.e., spatially confined broadcasting, scenarios. This paper describes a free space FDA-based SDF (FDA-SDF) system model for 2-dimensional range-angle-based focusing, including a generalized multi-purpose baseband approach for time-invariant FDA, complemented by SDF processing for improved spatial focusing precision and reduced array size. Comprehensive analytical derivations - general for any frequency offset configuration - describe the geographical FDA-SDF properties and design rules, such as geocast delivery zone steering, location, uniqueness, and size. Simulations of the proposed scheme validate theoretical derivations and demonstrate FDA-SDF's superior spatial precision and minimal design complexity. In particular, using novel alternating logarithmic frequency offsets, a 3-antenna FDA-SDF setup is shown to match the radial and azimuthal precision of its beamforming-based FDA counterpart using, respectively, 64 and 24 antennas.
Multi-RIS-Enabled 3D Sidelink Positioning
Authors: Hui Chen, Pinjun Zheng, Musa Furkan Keskin, Tareq Al-Naffouri, Henk Wymeersch
Date: 2023-02-24 00:00:00
Tasks: Autonomous Driving

Positioning is expected to be a core function in intelligent transportation systems (ITSs) to support communication and location-based services, such as autonomous driving, traffic control, etc. With the advent of low-cost reflective reconfigurable intelligent surfaces (RISs) to be deployed in beyond 5G/6G networks, extra anchors with high angular resolutions can boost signal quality and makes high-precision positioning with extended coverage possible in ITS scenarios. However, the passive nature of the RIS requires a signal source such as a base station (BS), which limits the positioning service in extreme situations, such as tunnels or dense urban areas, where 5G/6G BSs are not accessible. In this work, we show that with the assistance of (at least) two RISs and sidelink communication between two user equipments (UEs), these UEs can be localized even without any BSs involvement. A two-stage 3D sidelink positioning algorithm is proposed, benchmarked by the derived Cram\'er-Rao bounds. The effects of multipath and RIS profile designs on positioning performance are evaluated, and several scenarios with different RIS and UE locations are discussed for localizability analysis. Simulation results demonstrate the promising positioning accuracy of the proposed BS-free sidelink communication system in challenging ITS scenarios. Additionally, we propose and evaluate several solutions to eliminate potential blind areas where positioning performance is poor, such as removing clock offset via round-trip communication, adding geometrical prior or constraints, as well as introducing more RISs.
Graph signal processing with categorical perspective
Authors: Feng Ji, Xingchao Jian, Wee Peng Tay
Date: 2023-02-24 00:00:00

In this paper, we propose a framework for graph signal processing using category theory. The aim is to generalize a few recent works on probabilistic approaches to graph signal processing, which handle signal and graph uncertainties.
Cascaded ELM-based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections
Authors: Chaojin Qing, Chuangui Rao, Shuhai Tang, Na Yang, Jiafan Wang
Date: 2023-02-24 00:00:00

Due to the interdependency of frame synchronization (FS) and channel estimation (CE), joint FS and CE (JFSCE) schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems. Although traditional JFSCE schemes alleviate the influence between FS and CE, they show deficiencies in dealing with hardware imperfection (HI) and deterministic line-of-sight (LOS) path. To tackle this challenge, we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel. Specifically, the conventional JFSCE method is first employed to extract the initial features, and thus forms the non-Neural Network (NN) solutions for FS and CE, respectively. Then, the ELM-based networks, named FS-NET and CE-NET, are cascaded to capture the NN solutions of FS and CE. Simulation and analysis results show that, compared with the conventional JFSCE methods, the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error (NMSE) of CE, even against the impacts of parameter variations.
On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem
Authors: Hisham Muhammed, Ayotunde Ayorinde, Francis Okewole, Michael Adelabu, Ike Mowete
Date: 2023-02-23 00:00:00
Tasks: Prediction

Investigations in this paper focus on establishing the uniqueness properties of the Quasi Moment Method (QMM) solution to the problem of calibrating nominal radiowave propagation pathloss prediction models. Nominal (basic) prediction models utilized for the investigations, were first subjected to QMM calibrations with measurements from three different propagation scenarios. Then, the nominal models were recast in forms suitable for Singular Value Decomposition (SVD) calibration before being calibrated with both the SVD and QMM algorithms. The prediction performances of the calibrated models as evaluated in terms of Root Mean Square Prediction Error (RMSE), Mean Prediction Error (MPE), and Grey Relational Grade Mean Absolute Percentage Error (GRG MAPE) very clearly indicate that the uniqueness of QMM calibrations of basic pathloss models is more readily observable, when the basic models are recast in forms specific to SVD calibration. In the representative case of calibration with indoor to outdoor measurements, RMSE values were recorded for QMM calibrated nominal models as 5.2639dB for the ECC33 model, and 5.3218dB for the other nominal models. Corresponding metrics for the alternative (rearranged) nominal models emerged as 5.2663dB for the ECC33 model and 5.2591dB for the other models. A similar general trend featured in the GRG MAPE metrics, which for both SVD and QMM calibrations of all the alternative models, was recorded as 0.9131, but differed slightly (between 0.9138 and 0.9196) for the QMM calibration of the nominal models. The slight differences between these metrics (due to computational round off approximations) confirm that when the components of basic models are linearly independent, the QMM solution is unique.
On the Response of Basic Walfisch-Ikegami and Walfisch-Bertoni Models to QMM Calibration
Authors: Ayotunde Ayorinde, Hisham Muhammed, Ike Mowete
Date: 2023-02-23 00:00:00
Tasks: Attribute

This paper systematically examines the response to Quasi Moment Method (QMM) calibration, of the basic COST231 Walfisch Ikegami, ITUR Walfisch Ikegami, and Walfisch-Bertoni models. First, it is demonstrated that the component parameters of the models are suitable candidates for use as expansion or testing functions with QMM pathloss model calibration schemes; and thereafter, the basic models are subjected to calibration, using measurement data available in the open literature. Computational results reveal that the COST231 Walfisch Ikegami and ITU Walfisch Ikegami models have virtually identical QMM calibration root mean square error (RMSE) responses; and that the Walfisch Bertoni model has better RMSE responses than both of them. A particular attribute revealed by the simulation results is that all QMM calibrated Walfisch type basic models have excellent mean prediction error (MPE) metrics (in general, less than 0.001dB). In addition to pathloss prediction profiles, the paper also presents profiles of disaggregated net pathloss, in terms of contributions by component parameters, including roof-top-to-street diffraction and scatter loss and multiscreen diffraction loss.
Sleep Model -- A Sequence Model for Predicting the Next Sleep Stage
Authors: Iksoo Choi, Wonyong Sung
Date: 2023-02-17 00:00:00
Tasks: Classification, EEG, Electrocardiography (ECG), Electroencephalogram (EEG), Electromyography (EMG), model

As sleep disorders are becoming more prevalent there is an urgent need to classify sleep stages in a less disturbing way.In particular, sleep-stage classification using simple sensors, such as single-channel electroencephalography (EEG), electrooculography (EOG), electromyography (EMG), or electrocardiography (ECG) has gained substantial interest. In this study, we proposed a sleep model that predicts the next sleep stage and used it to improve sleep classification accuracy. The sleep models were built using sleep-sequence data and employed either statistical $n$-gram or deep neural network-based models. We developed beam-search decoding to combine the information from the sensor and the sleep models. Furthermore, we evaluated the performance of the $n$-gram and long short-term memory (LSTM) recurrent neural network (RNN)-based sleep models and demonstrated the improvement of sleep-stage classification using an EOG sensor. The developed sleep models significantly improved the accuracy of sleep-stage classification, particularly in the absence of an EEG sensor.
Wasserstein-Kelly Portfolios: A Robust Data-Driven Solution to Optimize Portfolio Growth
Authors: Jonathan Yu-Meng Li
Date: 2023-02-27 00:00:00
Tasks: Portfolio Optimization

We introduce a robust variant of the Kelly portfolio optimization model, called the Wasserstein-Kelly portfolio optimization. Our model, taking a Wasserstein distributionally robust optimization (DRO) formulation, addresses the fundamental issue of estimation error in Kelly portfolio optimization by defining a ``ball" of distributions close to the empirical return distribution using the Wasserstein metric and seeking a robust log-optimal portfolio against the worst-case distribution from the Wasserstein ball. Enhancing the Kelly portfolio using Wasserstein DRO is a natural step to take, given many successful applications of the latter in areas such as machine learning for generating robust data-driven solutions. However, naive application of Wasserstein DRO to the growth-optimal portfolio problem can lead to several issues, which we resolve through careful modelling. Our proposed model is both practically motivated and efficiently solvable as a convex program. Using empirical financial data, our numerical study demonstrates that the Wasserstein-Kelly portfolio can outperform the Kelly portfolio in out-of-sample testing across multiple performance metrics and exhibits greater stability.
Elicitability of Return Risk Measures
Authors: Mücahit Aygün, Fabio Bellini, Roger J. A. Laeven
Date: 2023-02-25 00:00:00

Informally, a risk measure is said to be elicitable if there exists a suitable scoring function such that minimizing its expected value recovers the risk measure. In this paper, we analyze the elicitability properties of the class of return risk measures (i.e., normalized, monotone and positively homogeneous risk measures). First, we provide dual representation results for convex and geometrically convex return risk measures. Next, we establish new axiomatic characterizations of Orlicz premia (i.e., Luxemburg norms). More specifically, we prove, under different sets of conditions, that Orlicz premia naturally arise as the only elicitable return risk measures. Finally, we provide a general family of strictly consistent scoring functions for Orlicz premia, a myriad of specific examples and a mixture representation suitable for constructing Murphy diagrams.
Reduced steroid activation of elephant shark glucocorticoid and mineralocorticoid receptors after inserting four amino acids from the DNA-binding domain of lamprey corticoid receptor-1
Authors: Yoshinao Katsu, Jiawen Zhang, Michael E. Baker
Date: 2023-02-25 00:00:00

Atlantic sea lamprey contains two corticoid receptors (CRs), CR1 and CR2, that are identical except for a four amino acid insert (Thr-Arg-Gln-Gly) in the CR1 DNA-binding domain (DBD). Steroids are stronger transcriptional activators of CR2 than of CR1 suggesting that the insert reduces the transcriptional response of lamprey CR1 to steroids. The DBD in elephant shark mineralocorticoid receptor (MR) and glucocorticoid receptor (GR), which are descended from a CR, lack these four amino acids, suggesting that a CR2 is their common ancestor. To determine if, similar to lamprey CR1, the presence of this insert in elephant shark MR and GR decreases transcriptional activation by corticosteroids, we inserted these four CR1-specific residues into the DBD of elephant shark MR and GR. Compared to steroid activation of wild-type elephant shark MR and GR, cortisol, corticosterone, aldosterone, 11-deoxycorticosterone and 11-deoxycortisol had lower transcriptional activation of these mutant MR and GR receptors, indicating that the absence of this four-residue segment in the DBD in wild-type elephant shark MR and GR increases transcriptional activation by corticosteroids.
Comparative Study of Lycopene Encapsulation Efficiency in Polycapprolactone Vs Poly Lactic Co-glycolic Acid
Authors: Mohammad Anwar Ul Alam, Lamin S. Kassama
Date: 2023-02-24 00:00:00

Lycopene contributes to the red-colored pigmentation of fruits and vegetables, and it is a fat-soluble carotenoid with antioxidant properties. Epidemiological studies have shown the significant health benefits associated to the consumption of lycopene rich foods, because of the anti-cancer properties. Degradative losses of lycopene during processing is a grave concern, hence encapsulation provides a remedy. The objective of this study is to evaluate the encapsulation efficiency of two biodegradable polymers (PLGA and PCL) as for controlled release of lycopene in the gastrointestinal (GI) system. The nanoparticles (NP) were synthesized by emulsion evaporation method and physicochemical properties was determined using a Dynamic Light Scattering spectroscopy. The results show the hydrodynamic diameter of the lycopene NP synthesized in PCL (200 mg) and 3500 mg surfactant and sonicated for 15 min was 79.23+0.85 nm (Lowest). PLGA (500 mg) and 500 mg surfactant with 15 min sonication was observed to have the lowest NP diameter (108.2+2.66 nm) among the others. Significant difference result found in PDI value (0.12+0.07) when PCL of 200mg dissolve in 3500 mg of surfactant. On the other hands the zeta potential values were much smaller in case of PCL NP ranged between -1.3+0.046 and -4.21+0.08 mV compared to the PLGA NP -72.36+2.17 to 107.66+3.15 mV in all experiments. Thus, NP synthesized with PCL and surfactant provide a smaller sized nano-solution than PLGA and surfactant. As the degradation rate for PCL is lower than PLGA so PCL can be considered as a potential biodegradable polymer than PLGA to encapsulate lycopene.
A new twist on PIFE: photoisomerisation-related fluorescence enhancement
Authors: Evelyn Ploetz, Benjamin Ambrose, Anders Barth, Richard Börner, Felix Erichson, Achillefs N. Kapanidis, Harold D. Kim, Marcia Levitus, Timothy M. Lohman, Abhishek Mazumder, David S. Rueda, Fabio D. Steffen, Thorben Cordes, Steven W. Magennis, Eitan Lerner
Date: 2023-02-24 00:00:00

PIFE was first used as an acronym for protein-induced fluorescence enhancement, which refers to the increase in fluorescence observed upon the interaction of a fluorophore, such as a cyanine, with a protein. This fluorescence enhancement is due to changes in the rate of cis/trans photoisomerisation. It is clear now that this mechanism is generally applicable to interactions with any biomolecule and, in this review, we propose that PIFE is thereby renamed according to its fundamental working principle as photoisomerisation-related fluorescence enhancement, keeping the PIFE acronym intact. We discuss the photochemistry of cyanine fluorophores, the mechanism of PIFE, its advantages and limitations, and recent approaches to turn PIFE into a quantitative assay. We provide an overview of its current applications to different biomolecules and discuss potential future uses, including the study of protein-protein interactions, protein-ligand interactions and conformational changes in biomolecules.
Russel and Rao Coefficient is a Suitable Substitute for Dice Coefficient in Studying Restriction Mapped Genetic Distances of Escherichia coli
Authors: Zhu En Chay, Chin How Lee, Kun Cheng Lee, Jack SH Oon, Maurice HT Ling
Date: 2023-02-19 00:00:00

Escherichia coli is one of many bacterial inhabitants found in human intestines and any adaptation as a result of mutations may affect its host. A commonly used technique employed to study these mutations is Restriction Fragment Length Polymorphism (RFLP) and is proceeded with a suitable distance coefficient to quantify genetic differences between 2 samples. Dice is considered a suitable distance coefficient in RFLP analyses, while others were left unstudied in its suitability for use. Hence, this study aims to identify substitutes for Dice. Experimental data was obtained by subculturing E. coli for 72 passages in 8 different adaptation media and RFLP profiles analyzed using 20 distance coefficients. Our results suggest that Dennis, Fossum, Matching and Russel and Rao to work as well or better than Dice. Dennis, Matching and Fossum coefficients had highest discriminatory abilities but are limited by the lack of upper or lower boundaries. Russel and Rao coefficient is highly correlated with Dice coefficient (r2 = 0.998), with both higher and lower boundaries, suggesting that Russel and Rao coefficient can be used to substitute Dice coefficient in studying genetic distances in E. coli.
New GO-based Measures and Their Statistical Significance in Multiple Network Alignment
Authors: Reza Mousapour, Kimia Yazdani, Wayne B. Hayes
Date: 2023-02-26 00:00:00

Protein-protein interaction (PPI) networks provide valuable insights into the function of biological systems, and aligning multiple PPI networks can reveal important functional relationships between different species. However, assessing the quality of multiple network alignments is a challenging problem. In this paper, we propose two new measures, the Squared GO Score (SGS) and the Exposed G Score, to evaluate the quality of multiple network alignments while using functional information from Gene Ontology (GO) terms. We also introduce a $p$-value measure, the Statistical Exposed G Score, to compute the exact significance of a multiple network alignment based on its revealed GO terms. We also show that our measures are highly correlated with the recovered Ortholog count, providing further evidence for their effectiveness. Our work contributes to the development of more reliable and accurate measures for evaluating multiple network alignments and has potential applications in predicting gene function and identifying evolutionary relationships between different species using multiple network alignment.
Comparison and Analysis of Cognitive Load under 2D/3D Visual Stimuli
Authors: Yu Liu, Chen Song, Yunpeng Yin, Herui Shi, Jinglin Sun, Han Wang, Peiguang Jing
Date: 2023-02-25 00:00:00
Tasks: EEG, Electroencephalogram (EEG), Experimental Design

With the increasing prevalence of 3D videos, investigating the differences of viewing experiences between 2D and 3D videos has become an important issue. In this study, we explored the cognitive load induced by 2D and 3D video stimuli under various cognitive tasks utilizing electroencephalogram (EEG) data. We also introduced the Cognitive Load Index (CLI), a metric which combines {\theta} and {\alpha} oscillations to evaluate the cognitive differences. Four video stimuli, each associated with typical cognitive tasks were adopted in our experiments. Subjects were exposed to both 2D and 3D video stimuli, and the corresponding EEG data were recorded. Then, we analyzed the power within the 0.5-45 Hz frequency of EEG data, and CLI was utilized to evaluate the brain activity of different subjects. According to our experiments and analysis, videos that involve simple observational tasks (P <0.05) consistently induced a higher cognitive load in subjects when they were viewing 3D videos. However, for videos that involve calculation tasks (P >0.05), the differences in cognitive load induced by 2D and 3D video were not obvious. Thus, we concluded that 3D videos could generally induce a higher cognitive load, but the extent of the differences also depended on the contents of the video stimuli and the viewing purpose.
Characterize the non-Gaussian diffusion property of cerebrospinal fluid using Diffusion Kurtosis Imaging and explore its diagnostic efficacy for Alzheimer's disease
Authors: Yingnan Xue, Min Wen, Qiong Ye
Date: 2023-02-24 00:00:00
Tasks: Diagnostic

Differentiating Alzheimer's disease (AD) patients from healthy controls (HCs) remains a challenge. The changes of protein level in cerebrospinal fluid (CSF) of AD patients have been reported in the literature. Macromolecules will hinder the movement of water in CSF and lead to non-Gaussian diffusion. Diffusion kurtosis imaging (DKI) is a commonly used technique for quantifying non-Gaussian diffusivity. In this study, we used DKI to evaluate the non-Gaussian diffusion of CSF in AD patients and HC. Between-group difference was explored. In addition, we have built a prediction model using cross-validation Support Vector Machines (SVM), and achieved excellent performance. The validated area under the receiver operating characteristic curve(AUC) is in the range of 0.96-1.00, and the correct prediction is in the range of 87.1% - 90.0%.
Optimal interruption of P. vivax malaria transmission using mass drug administration
Authors: Md Nurul Anwar, Roslyn I. Hickson, Somya Mehra, David J. Price, James M. McCaw, Mark B. Flegg, Jennifer A. Flegg
Date: 2023-02-24 00:00:00

\textit{Plasmodium vivax} is the most geographically widespread malaria-causing parasite resulting in significant associated global morbidity and mortality. One of the factors driving this widespread phenomenon is the ability of the parasites to remain dormant in the liver. Known as hypnozoites, they reside in the liver following an initial exposure, before activating later to cause further infections, referred to as relapses. As around 79-96$\%$ of infections are attributed to relapses, we expect it will be highly impactful to apply treatment to target the hypnozoite reservoir to eliminate \textit{P. vivax}. Treatment with a radical cure to target the hypnozoite reservoir is a potential tool to control or eliminate \textit{P. vivax}. We have developed a multiscale mathematical model as a system of integro-differential equations that captures the complex dynamics of \textit{P. vivax} hypnozoites and the effect of hypnozoite relapse on disease transmission. Here, we use our model to study the anticipated effect of radical cure treatment administered via a mass drug administration (MDA) program. We implement multiple rounds of MDA with a fixed interval between rounds, starting from different steady-state disease prevalences. We then construct an optimisation model to obtain the optimal MDA interval. We also incorporate mosquito seasonality in our model to study its effect on the optimal treatment regime. We find that the effect of MDA interventions is temporary and depends on the pre-intervention disease prevalence (and choice of model parameters) as well as the number of MDA rounds under consideration. We find radical cure alone may not be enough to lead to \textit{P. vivax} elimination under our mathematical model (and choice of model parameters) since the prevalence of infection eventually returns to pre-MDA levels.