pwc-archive/papers-with-abstracts huggingface dataset:
A Low-Complexity Solution to Sum Rate Maximization for IRS-assisted SWIPT-MIMO Broadcasting
Authors: Vaibhav Kumar, Anastasios Papazafeiropoulos, Muhammad Fainan Hanif, Le-Nam Tran, Mark F. Flanagan
Date: 2023-02-28 00:00:00

This paper focuses on the fundamental problem of maximizing the achievable weighted sum rate (WSR) at information receivers (IRs) in an intelligent reflecting surface (IRS) assisted simultaneous wireless information and power transfer system under a multiple-input multiple-output (SWIPT-MIMO) setting, subject to a quality-of-service (QoS) constraint at the energy receivers (ERs). Notably, due to the coupling between the transmit precoding matrix and the passive beamforming vector in the QoS constraint, the formulated non-convex optimization problem is challenging to solve. We first decouple the design variables in the constraints following a penalty dual decomposition method, and then apply an alternating gradient projection algorithm to achieve a stationary solution to the reformulated optimization problem. The proposed algorithm nearly doubles the WSR compared to that achieved by a block-coordinate descent (BCD) based benchmark scheme. At the same time, the complexity of the proposed scheme grows linearly with the number of IRS elements while that of the benchmark scheme is proportional to the cube of the number of IRS elements.
Machine-learning Repurposing of DrugBank Compounds for Opioid Use Disorder
Authors: Hongsong Feng, Jian Jiang, Guo-Wei Wei
Date: 2023-03-01 00:00:00
Tasks: Drug Discovery

Opioid use disorder (OUD) is a chronic and relapsing condition that involves the continued and compulsive use of opioids despite harmful consequences. The development of medications with improved efficacy and safety profiles for OUD treatment is urgently needed. Drug repurposing is a promising option for drug discovery due to its reduced cost and expedited approval procedures. Computational approaches based on machine learning enable the rapid screening of DrugBank compounds, identifying those with the potential to be repurposed for OUD treatment. We collected inhibitor data for four major opioid receptors and used advanced machine learning predictors of binding affinity that fuse the gradient boosting decision tree algorithm with two natural language processing (NLP)-based molecular fingerprints and one traditional 2D fingerprint. Using these predictors, we systematically analyzed the binding affinities of DrugBank compounds on four opioid receptors. Based on our machine learning predictions, we were able to discriminate DrugBank compounds with various binding affinity thresholds and selectivities for different receptors. The prediction results were further analyzed for ADMET (absorption, distribution, metabolism, excretion, and toxicity), which provided guidance on repurposing DrugBank compounds for the inhibition of selected opioid receptors. The pharmacological effects of these compounds for OUD treatment need to be tested in further experimental studies and clinical trials. Our machine learning studies provide a valuable platform for drug discovery in the context of OUD treatment.
Spatial cancer systems biology resolves heterotypic interactions and identifies disruption of spatial hierarchy as a pathological driver event
Authors: Fabian V. Filipp
Date: 2023-03-02 00:00:00

Spatially annotated single-cell datasets provide unprecedented opportunities to dissect cell-cell communication in development and disease. Heterotypic signaling includes interactions between different cell types and is well established in tissue development and spatial organization. Epithelial organization requires several different programs that are tightly regulated. Planar cell polarity is the organization of epithelial cells along the planar axis orthogonal to the apical-basal axis. In this study, we investigate planar cell polarity factors and explore the implications of developmental regulators as malignant drivers. Utilizing cancer systems biology analysis, we derive gene expression network for WNT-ligands (WNT) and their cognate frizzled (FZD) receptors in skin cutaneous melanoma. The profiles supported by unsupervised clustering of multiple-sequence alignments identify ligand-independent signaling and implications for metastatic progression based on the underpinning developmental spatial program. Omics studies and spatial biology connect developmental programs with oncological events and explain key spatial features of metastatic aggressiveness. Dysregulation of prominent planar cell polarity factors such specific representative of the WNT and FZD families in malignant melanoma recapitulates the development program of normal melanocytes but in an uncontrolled and disorganized fashion.
Tuning to non-veridical features in attention and perceptual decision-making
Authors: Stefanie I. Becker, Zachary Hamblin-Frohman, Hongfeng Xia, Zeguo Qiu
Date: 2023-03-01 00:00:00
Tasks: Attribute, Decision Making, EEG, Electroencephalogram (EEG)

When searching for a lost item, we tune attention to the known properties of the object. Previously, it was believed that attention is tuned to the veridical attributes of the search target (e.g., orange), or an attribute that is slightly shifted away from irrelevant features towards a value that can more optimally distinguish the target from the distractors (e.g., red-orange; optimal tuning). However, recent studies showed that attention is often tuned to the relative feature of the search target (e.g., redder), so that all items that match the relative features of the target equally attract attention (e.g., all redder items; relational account). Optimal tuning was shown to occur only at a later stage of identifying the target. However, the evidence for this division mainly relied on eye tracking studies that assessed the first eye movements. The present study tested whether this division can also be observed when the task is completed with covert attention and without moving the eyes. We used the N2pc in the EEG of participants to assess covert attention, and found comparable results: Attention was initially tuned to the relative colour of the target, as shown by a significantly larger N2pc to relatively matching distractors than a target-coloured distractor. However, in the response accuracies, a slightly shifted, "optimal" distractor interfered most strongly with target identification. These results confirm that early (covert) attention is tuned to the relative properties of an item, in line with the relational account, while later decision-making processes may be biased to optimal features.
Thin Films on the Skin, but not Frictional Agents, Attenuate the Percept of Pleasantness to Brushed Stimuli
Authors: Merat Rezaei, Saad S. Nagi, Chang Xu, Sarah McIntyre, Hakan Olausson, Gregory J. Gerling
Date: 2023-02-28 00:00:00
Tasks: Friction

Brushed stimuli are perceived as pleasant when stroked lightly on the skin surface of a touch receiver at certain velocities. While the relationship between brush velocity and pleasantness has been widely replicated, we do not understand how resultant skin movements - e.g., lateral stretch, stick-slip, normal indentation - drive us to form such judgments. In a series of psychophysical experiments, this work modulates skin movements by varying stimulus stiffness and employing various treatments. The stimuli include brushes of three levels of stiffness and an ungloved human finger. The skin's friction is modulated via non-hazardous chemicals and washing protocols, and the skin's thickness and lateral movement are modulated by thin sheets of adhesive film. The stimuli are hand-brushed at controlled forces and velocities. Human participants report perceived pleasantness per trial using ratio scaling. The results indicate that a brush's stiffness influenced pleasantness more than any skin treatment. Surprisingly, varying the skin's friction did not affect pleasantness. However, the application of a thin elastic film modulated pleasantness. Such barriers, though elastic and only 40 microns thick, inhibit the skin's tangential movement and disperse normal force. The finding that thin films modulate affective interactions has implications for wearable sensors and actuation devices.
Disentangling Linkage and Population Structure in Association Mapping
Authors: Hanbin Lee, Moo Hyuk Lee
Date: 2023-03-02 00:00:00

Genome-wide association study (GWAS) tests single nucleotide polymorphism (SNP) markers across the genome to localize the underlying causal variant of a trait. Because causal variants are seldom observed directly, a surrogate model based on genotyped markers are widely considered. Although many methods estimating the parameters of the surrogate model have been proposed, the connection between the surrogate model and the true causal model is yet investigated. In this work, we establish the connection between the surrogate model and the true causal model. The connection shows that population structure is accounted in GWAS by modelling the variant of interest and not the trait. Such observation explains how environmental confounding can be partially corrected using genetic covariates and why the previously claimed connection between PC correction and linear mixed models is incorrect.
What Motivated Mitigation Policies? A Network-Based Longitudinal Analysis of State-Level Mitigation Strategies
Authors: William Fries
Date: 2023-03-02 00:00:00

Understanding which factors informed pandemic response can help create a more nuanced perspective on how each state of the United States handled the crisis. To this end, we create various networks linking states together based on their similarity in mitigation policies, politics, geographic proximity and COVID-19 case data. We use these networks to analyze the correlation between pandemic policies and politics, location and case-load from January 2020 through March 2022. We show that the best predictors of a state's response is an aggregate political affiliation rather than solely governor affiliation as others have shown. Further, we illustrate that political affiliation is heavily correlated with policy intensity from June 2020 through June 2021, but has little impact on policy after June 2021. In contrast, geographic proximity and daily incidence are not consistently correlated with state's having similar mitigation policies.
Overcompensation of transient and permanent death rate increases in age-structured models with cannibalistic interactions
Authors: Mingtao Xia, Xiangting Li, Tom Chou
Date: 2023-03-01 00:00:00

There has been renewed interest in understanding the mathematical structure of ecological population models that lead to overcompensation, the process by which a population recovers to a higher level after suffering a permanent increase in predation or harvesting. Here, we apply a recently formulated kinetic population theory to formally construct an age-structured single-species population model that includes a cannibalistic interaction in which older individuals prey on younger ones. Depending on the age-dependent structure of this interaction, our model can exhibit transient or steady-state overcompensation of an increased death rate as well as oscillations of the total population, both phenomena that have been observed in ecological systems. Analytic and numerical analysis of our model reveals sufficient conditions for overcompensation and oscillations. We also show how our structured population partial integrodifferential equation (PIDE) model can be reduced to coupled ODE models representing piecewise constant parameter domains, providing additional mathematical insight into the emergence of overcompensation.
Guidelines for the estimation and reporting of plasmid conjugation rates
Authors: Olivia Kosterlitz, Jana S. Huisman
Date: 2023-03-01 00:00:00

Conjugation is a central characteristic of plasmid biology and an important mechanism of horizontal gene transfer in bacteria. However, there is little consensus on how to accurately estimate and report plasmid conjugation rates, in part due to the wide range of available methods. Given the similarity between approaches, we propose general reporting guidelines for plasmid conjugation experiments. These constitute best practices based on recent literature about plasmid conjugation and methods to measure conjugation rates. In addition to the general guidelines, we discuss common theoretical assumptions underlying existing methods to estimate conjugation rates and provide recommendations on how to avoid violating these assumptions. We hope this will aid the implementation and evaluation of conjugation rate measurements, and initiate a broader discussion regarding the practice of quantifying plasmid conjugation rates.
Routine haematological markers can predict and discriminate health status and biological age even from noisy sources
Authors: Santiago Hernández-Orozco, Abicumaran Uthamacumaran, Francisco Hernández-Quiroz, Kourosh Saeb-Parsy, Hector Zenil
Date: 2023-03-02 00:00:00
Tasks: Blood Cell Count, CBC TEST, Nutrition, Survey

For more than two decades, advances in personalised medicine and precision healthcare have largely been based on genomics and other omics data. These strategies aim to tailor interventions to individual patient profiles, promising greater treatment efficacy and more efficient allocation of healthcare resources. Here, we show that widely collected common haematologic markers can reliably predict and discriminate individual chronological age and health status from even noisy sources. Our analysis includes synthetic and real retrospective patient data, including medically relevant and extreme cases, and draws on more than 100\,000 complete blood count records over 13 years from the United States Centers for Disease Control and Prevention's National Health and Nutrition Examination Survey (CDC NHANES). We combine fully explainable risk assessment scores with machine and deep learning techniques to focus on clinically significant patterns and characteristics without functioning purely as a ''black-box model allowing interpretation and control. We validated the results with the UK Biobank, a larger cohort independent of the CDC NHANES and with very different collection techniques, the former a survey and the second a longitudinal study. Unlike current biological ageing indicators, this approach may offer rapid, and scalable implementations of personalised, precision and predictive approaches to healthcare and medicine without or before requiring other specialised, uncommon or costly tests.
A systematic review of mechanistic models used to study avian influenza virus transmission and control
Authors: Sébastien Lambert, Billy Bauzile, Amélie Mugnier, Benoit Durand, Timothée Vergne, Mathilde C Paul
Date: 2023-03-01 00:00:00
Tasks: Articles

The global spread of avian influenza A viruses in domestic birds is causing dramatic economic and social losses. Various mechanistic models have been developed in an attempt to better understand avian influenza transmission and to evaluate the effectiveness of control measures. However, no comprehensive review of the mechanistic approaches used currently exists. To help fill this gap, we conducted a systematic review of mechanistic models applied to real-world epidemics to (1) describe the type of models and their epidemiological context, (2) synthetise estimated values of AIV transmission parameters and (3) review the control strategies most frequently evaluated and their outcome. Fourty-five articles qualified for inclusion, that fitted the model to data and estimated parameter values (n = 42) and/or evaluated the effectiveness of control strategies (n = 21). The majority were population-based models (n = 26), followed by individual-based models (n = 15) and a few metapopulation models (n = 4). Estimated values for the transmission rate varied substantially according to epidemiological settings, virus subtypes and epidemiological units. Other parameters such as the durations of the latent and infectious periods were more frequently assumed, limiting the insights brought by mechanistic models on these. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 7). According to the reviewed articles, optimal control strategies varied between virus subtypes and local conditions, and also depended on the objective. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks, while pre-emptive culling was preferred for reducing the epidemic size and duration. Earlier implementation of interventions consistently improved the efficacy of control strategies, highlighting the need for effective surveillance and epidemic preparedness. Potential improvements of mechanistic models include explicitly accounting for various transmission routes, and distinguishing poultry populations according to species and farm type. To provide insights to policy makers in a timely manner, aspects about the evaluation of control strategies that could deserve further attention include: economic evaluation, combination of strategies including vaccination, the use of optimization algorithm instead of comparing a limited set of scenarios, and real-time evaluation.
Investigating biomechanical determinants of endothelial permeability in a modified hollow fibre bioreactor
Authors: Stephen G Gray, Peter D Weinberg
Date: 2023-03-02 00:00:00

Effects of mechanical stress on the permeability of vascular endothelium are important to normal physiology and may be critical in the development of atherosclerosis, where they can account for the patchy arterial distribution of the disease. Such properties are frequently investigated in vitro. Here we evaluate and use the hollow fibre bioreactor for this purpose; in this system, endothelial cells form a confluent monolayer lining numerous plastic capillaries with porous walls, contained in a cartridge. The capillaries were perfused with a near-aortic waveform by an external pump, and permeability was assessed by the movement of rhodamine-labelled albumin from the intracapillary space to the extracapillary space. Confluence and quiescence of the cells was confirmed by electron microscopy and measurements of glucose consumption and permeability. The system was able to detect previously established influences on permeability: tracer transport was increased by acute application of shear stress and decreased by chronic shear stress compared to a static control, and was increased by thrombin or an NO synthase inhibitor under chronic shear. Increasing viscosity by addition of xanthan gum reduced permeability under both acute and chronic shear. Addition of damping chambers to reduce flow pulsatility increased permeability. Modifying the cartridge to allow chronic convection across the monolayer increased effective permeability more than could be explained the addition of convective transport alone, indicating that it caused an increase in permeability. The off-the-shelf hollow fibre bioreactor provides an excellent system for investigating the biomechanics of endothelial permeability and its potential is increased by simple modifications.
Strat{é}gies de gestion de la chaleur et performances sportives de haut niveau: {é}clairage psychophysiologique et recommandations appliqu{é}es
Authors: Nicolas Robin, E. Hermand, V. Hatchi, O. Hue
Date: 2023-03-01 00:00:00
Tasks: Management

Objectives: This article sheds light on the different heat stress management strategies, common or innovative, in order to analyze those that would be the most suitable and effective for athletes who have to compete in humid and/or hot environments.News: The Paris summer Olympics Games in 2024 will take place from July 26th to September 8th with a high risk for athletes to practice their sport at high temperatures, thereby imposing physiological (cardiovascular, ventilatory, thermoregulatory, etc.) and psychological (early mental fatigue, decreased motivation, discomfort, etc.) which can have a major negative impact on their performance.Prospects and projects: To perform in a hot environment, it is now recommended to use strategies, in particular active acclimatization which promotes physiological but also psychological adaptations. Similarly, fluid management and cooling techniques have potentially beneficial effects on physiological factors but their psychological consequences are still poorly understood and need to be investigated. Finally, mental strategies (goal setting, mental imagery, positive self-talk, music, etc.) or cognitive training in the heat can limit poor performance in this condition. The effects of combining physical and mental techniques, as well as innovative strategies such as cold suggestion, are also being investigated.Conclusion: For each strategies presented, the scientific work has enabled the development of practical recommendations for athletes, coaches and mental trainers in order to allow them to physiologically and psychologically anticipate the effects of high relative humidity and/or high temperature.
Robust portfolio selection under Recovery Average Value at Risk
Authors: Cosimo Munari, Justin Plückebaum, Stefan Weber
Date: 2023-03-02 00:00:00

We study mean-risk optimal portfolio problems where risk is measured by Recovery Average Value at Risk, a prominent example in the class of recovery risk measures. We establish existence results in the situation where the joint distribution of portfolio assets is known as well as in the situation where it is uncertain and only assumed to belong to a set of mixtures of benchmark distributions (mixture uncertainty) or to a cloud around a benchmark distribution (box uncertainty). The comparison with the classical Average Value at Risk shows that portfolio selection under its recovery version enables financial institutions to exert better control on the recovery on liabilities while still allowing for tractable computations.
Bayesian Optimization of ESG Financial Investments
Authors: Eduardo C. Garrido-Merchán, Gabriel González Piris, Maria Coronado Vaca
Date: 2023-02-10 00:00:00
Tasks: Bayesian Optimization

Financial experts and analysts seek to predict the variability of financial markets. In particular, the correct prediction of this variability ensures investors successful investments. However, there has been a big trend in finance in the last years, which are the ESG criteria. Concretely, ESG (Economic, Social and Governance) criteria have become more significant in finance due to the growing importance of investments being socially responsible, and because of the financial impact companies suffer when not complying with them. Consequently, creating a stock portfolio should not only take into account its performance but compliance with ESG criteria. Hence, this paper combines mathematical modelling, with ESG and finance. In more detail, we use Bayesian optimization (BO), a sequential state-of-the-art design strategy to optimize black-boxes with unknown analytical and costly-to compute expressions, to maximize the performance of a stock portfolio under the presence of ESG criteria soft constraints incorporated to the objective function. In an illustrative experiment, we use the Sharpe ratio, that takes into consideration the portfolio returns and its variance, in other words, it balances the trade-off between maximizing returns and minimizing risks. In the present work, ESG criteria have been divided into fourteen independent categories used in a linear combination to estimate a firm total ESG score. Most importantly, our presented approach would scale to alternative black-box methods of estimating the performance and ESG compliance of the stock portfolio. In particular, this research has opened the door to many new research lines, as it has proved that a portfolio can be optimized using a BO that takes into consideration financial performance and the accomplishment of ESG criteria.