pwc-archive/papers-with-abstracts huggingface dataset:
Spreading Code Optimization for Low-Earth Orbit Satellites via Mixed-Integer Convex Programming
Authors: Alan Yang, Tara Mina, Grace Gao
Date: 2024-04-19 00:00:00

Optimizing the correlation properties of spreading codes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes' correlation sidelobes, we can enhance navigation performance while minimizing the required spreading code lengths. In the case of low earth orbit (LEO) satellite navigation, shorter code lengths (on the order of a hundred) are preferred due to their ability to achieve fast signal acquisition. Additionally, the relatively high signal-to-noise ratio (SNR) in LEO systems reduces the need for longer spreading codes to mitigate inter-channel interference. In this work, we propose a two-stage block coordinate descent (BCD) method which optimizes the codes' correlation properties while enforcing the autocorrelation sidelobe zero (ACZ) property. In each iteration of the BCD method, we solve a mixed-integer convex program (MICP) over a block of 25 binary variables. Our method is applicable to spreading code families of arbitrary sizes and lengths, and we demonstrate its effectiveness for a problem with 66 length-127 codes and a problem with 130 length-257 codes.
Deep Reinforcement Learning-aided Transmission Design for Energy-efficient Link Optimization in Vehicular Communications
Authors: Zhengpeng Wang, Yanqun Tang, Yingzhe Mao, Tao Wang, Xiunan Huang
Date: 2024-04-19 00:00:00
Tasks: Decision Making, Deep Reinforcement Learning, valid

This letter presents a deep reinforcement learning (DRL) approach for transmission design to optimize the energy efficiency in vehicle-to-vehicle (V2V) communication links. Considering the dynamic environment of vehicular communications, the optimization problem is non-convex and mathematically difficult to solve. Hence, we propose scenario identification-based double and Dueling deep Q-Network (SI-D3QN), a DRL algorithm integrating both double deep Q-Network and Dueling deep Q-Network, for the joint design of modulation and coding scheme (MCS) selection and power control. To be more specific, we employ SI techique to enhance link performance and assit the D3QN agent in refining its decision-making processes. The experiment results demonstrate that, across various optimization tasks, our proposed SI-D3QN agent outperforms the benchmark algorithms in terms of the valid actions and link performance metrics. Particularly, while ensuring significant improvement in energy efficiency, the agent facilitates a 29.6% enhancement in the link throughput under the same energy consumption.
Elicitability and identifiability of tail risk measures
Authors: Tobias Fissler, Fangda Liu, Ruodu Wang, Linxiao Wei
Date: 2024-04-22 00:00:00

Tail risk measures are fully determined by the distribution of the underlying loss beyond its quantile at a certain level, with Value-at-Risk and Expected Shortfall being prime examples. They are induced by law-based risk measures, called their generators, evaluated on the tail distribution. This paper establishes joint identifiability and elicitability results of tail risk measures together with the corresponding quantile, provided that their generators are identifiable and elicitable, respectively. As an example, we establish the joint identifiability and elicitability of the tail expectile together with the quantile. The corresponding consistent scores constitute a novel class of weighted scores, nesting the known class of scores of Fissler and Ziegel for the Expected Shortfall together with the quantile. For statistical purposes, our results pave the way to easier model fitting for tail risk measures via regression and the generalized method of moments, but also model comparison and model validation in terms of established backtesting procedures.
Electroporation-mediated Metformin for effective anticancer treatment of triple-negative breast cancer cells
Authors: Praveen Sahu, Ignacio G. Camarillo, Pragatheiswar Giri, Raji Sundararajan
Date: 2024-04-22 00:00:00

In this research, we investigated the efficacy of Metformin, the most commonly administered type-2 diabetes drug for triple negative breast cancer (TNBC) treatment, due to its various anticancer properties. It is a plant-based bio-compound, synthesized as a novel biguanide, called dimethyl biguanide or metformin. One of the ways it operates is by hindering electron transport chain-complex I, in mitochondria, which causes a drop-in energy (ATP) generation. This eventually builds energetic stress and a decline in energy. Therefore, the natural cellular processes and proliferating tumor cells are obstructed. Here, we used electroporation, where, the MDA-MB-231, human TNBC cells were subjected to high intensity, short-duration electrical pulses (EP) in the presence of Metformin. The cell viability results indicate lower cell viability of 43.45% as compared to 85.20% with drug alone at 5mM concentration. This indicates that Metformin, the most common diabetes drug could also be explored for cancer treatment.
Theta oscillons in behaving rats
Authors: M. S. Zobaer, N. Lotfi, C. M. Domenico, C. Hoffman, L. Perotti, D. Ji, Y. Dabaghian
Date: 2024-04-22 00:00:00

Recently discovered constituents of the brain waves -- the oscillons -- provide high-resolution representation of the extracellular field dynamics. Here we study the most robust, highest-amplitude oscillons that manifest in actively behaving rats and generally correspond to the traditional theta-waves. We show that the resemblances between theta-oscillons and the conventional theta-waves apply to the ballpark characteristics -- mean frequencies, amplitudes, and bandwidths. In addition, both hippocampal and cortical oscillons exhibit a number of intricate, behavior-attuned, transient properties that suggest a new vantage point for understanding the theta-rhythms' structure, origins and functions. We demonstrate that oscillons are frequency-modulated waves, with speed-controlled parameters, embedded into a noise background. We also use a basic model of neuronal synchronization to contextualize and to interpret the observed phenomena. In particular, we argue that the synchronicity level in physiological networks is fairly weak and modulated by the animal's locomotion.
The emergence of subjective temporality: the self-simulational theory of temporal extension from the perspective of the free energy principle
Authors: Jan Erik Bellingrath
Date: 2024-04-19 00:00:00

The self-simulational theory of temporal extension describes an information-theoretically formalized mechanism by which the width of subjective temporality emerges from the architecture of self-modelling. In this paper, the perspective of the free energy principle will be assumed, to cast the emergence of subjective temporality, along with a Bayesian mechanism for hierarchical duration estimation, from first principles of the physics of self-organization. Using active inference, a deep parametric generative model of temporal inference is simulated, which realizes the described dynamics on a computational level. Two biases (i.e. variations) of time-perception naturally emerge from the simulated computational model. This concerns the intentional binding effect (i.e. the compression of the temporal interval between voluntarily initiated actions and subsequent sensory consequences) and empirically documented alterations of subjective time experience in deep states of meditative absorption (i.e. in minimal phenomenal experience). Generally, numerous systematic and domain-specific alterations of subjective temporal experience are computationally explained in a unified manner, as enabled by integration with current active inference accounts mapping onto the respective domains. This concerns - next to more general scale-invariant effects of explicit timing and central tendency effects - the temporality-modulating role of valence, impulsivity, boredom, flow-states, near death-experiences, and various psychopathologies, amongst others. The self-simulational theory of temporal extension, from the perspective of the free energy principle, explains how the subjective temporal Now emerges and varies from first principles, accounting for why sometimes, subjective time seems to fly, and sometimes, moments feel like eternities; with the computational mechanism being readily deployable synthetically.
The Length and the Width of the Human Brain Circuit Connections are Strongly Correlated
Authors: Dániel Hegedűs, Vince Grolmusz
Date: 2024-04-19 00:00:00

The correlations of several fundamental properties of human brain connections are investigated in a consensus connectome, constructed from 1064 braingraphs, each on 1015 vertices, corresponding to 1015 anatomical brain areas. The properties examined include the edge length, the fiber number, or edge width, meaning the number of discovered axon bundles forming the edge and the occurrence number of the edge, meaning the number of individual braingraphs where the edge exists. By using our previously published robust braingraphs at \url{https://braingraph.org}, we have prepared a single consensus graph from the data and compared the statistical similarity of the edge occurrence numbers, edge lengths, and fiber counts of the edges. We have found a strong positive Spearman correlation between the edge occurrence numbers and the fiber count numbers, showing that statistically, the most frequent cerebral connections have the largest widths, i.e., the fiber number. We have found a negative Spearman correlation between the fiber lengths and fiber counts, showing that, typically, the shortest edges are the widest or strongest by their fiber counts. We have also found a negative Spearman correlation between the occurrence numbers and the edge lengths: it shows that typically, the long edges are infrequent, and the frequent edges are short.
A neural network account to Kant's philosophical aesthetics
Authors: Peter beim Graben
Date: 2024-04-12 00:00:00
Tasks: Learning Theory

According to Kant's (1724 -- 1804) philosophical aesthetics, laid down in his Critique of the Power of Judgement (1790), beauty is "subjective purposefulness", reflected by the "harmony of the cognitive faculties", which are "understanding" and "imagination". On the one hand, understanding refers to the mental capability to find regularities in sensory manifolds, while imagination refers to intuition, fantasy, and creativity of the mind, on the other hand. Inspired by the reinforcement learning theory of Schmidhuber, I present a neural network analogy for the harmony of the faculties in terms of generative adversarial networks (GAN) - also often employed for artificial music composition -- by identifying the generator module with the faculty of imagination and the discriminator module with the faculty of understanding. According to the GAN algorithm, both modules are engaged in an adversarial game, thereby optimizing a particular objective function. In my reconstruction, the convergence of the GAN algorithm during the reception of art, either music or fine, entails the harmony of the faculties and thereby a neural network analogue of subjective purposefulness, i.e., beauty.
Evaluating experiences in a digital nutrition education program for people with multiple sclerosis: a qualitative study
Authors: RD Russell, J He, LJ Black, A Begley
Date: 2024-04-22 00:00:00
Tasks: Nutrition

Background Multiple sclerosis (MS) is a complex immune-mediated disease with no currently known cure. There is growing evidence to support the role of diet in reducing some of the symptoms and disease progression in MS, and we previously developed and tested the feasibility of a digital nutrition education program for people with MS. Objective The aim of this study was to explore factors that influenced engagement in the digital nutrition education program, including features influencing capability, opportunity, and motivation to change their dietary behaviours. Methods Semi-structured interviews were conducted with people who MS who completed some or all of the program, until data saturation was reached. Interviews were analysed inductively using thematic analysis. Themes were deductively mapped against the COM-B behaviour change model. Results 16 interviews were conducted with participants who completed all (n=10) or some of the program (n=6). Four themes emerged: 1) Acquiring and validating nutrition knowledge; 2) Influence of time and social support; 3) Getting in early to improve health; and 4) Accounting for food literacy experiences. Discussion This is the first online nutrition program with suitable behavioural supports for people with MS. It highlights the importance of disease-specific and evidence-based nutrition education to support people with MS to make dietary changes. Acquiring nutrition knowledge, coupled with practical support mechanisms such as recipe booklets and goal-setting, emerged as crucial for facilitating engagement with the program. Conclusions When designing education programs for people with MS and other neurological conditions, healthcare professionals and program designers should consider flexible delivery and building peer support to address the needs and challenges faced by participants.
Feasibility of a co-designed online nutrition education program for people with multiple sclerosis
Authors: Rebecca D. Russell, Andrea Begley, Alison Daly, Eleanor Dunlop, Minh N. Pham, Lisa Grech, Lucinda J. Black
Date: 2024-04-22 00:00:00
Tasks: Nutrition

Objective: Diet quality is important for people with multiple sclerosis (MS), but conflicting online information causes them confusion. People with MS want evidence-based MS-specific information to help them make healthy dietary changes, and we co-designed an asynchronous, online nutrition education program (Eating Well with MS) with the MS community. Our aim was to determine the feasibility of Eating Well with MS. Methods: We used a single-arm pre-post design. The feasibility trial was a nine-week intervention with adults with confirmed MS. Feasibility outcomes: 1) demand (recruitment); 2) practicality (completion); 3) acceptability (Intrinsic Motivation Inventory: interest/enjoyment and value/usefulness subscales); and 4) limited efficacy testing (Diet Habits Questionnaire (DHQ); Critical Nutrition Literacy Tool (CNLT); Food Literacy Behaviour Checklist (FLBC)). Results: The recruitment target (n=70) was reached. 87% completed at least one module and 57% completed the full program (five modules). The median interest/enjoyment rating was 5 out of 7 and median value/usefulness rating was 6 out of 7 (where 7 = very true). Compared to pre-program, participants who completed any of the program had statistically significantly improved DHQ, CNLT, and FLBC scores. Conclusion: Eating Well with MS was well received by the MS community and improved their dietary behaviours; demonstrating feasibility. Our findings support the use of co-design methods when developing resources to improve dietary behaviours.
Temporal genomics help in deciphering neutral and adaptive patterns in the contemporary evolution of kelp populations
Authors: Lauric Reynes, Louise Fouqueau, D. Aurelle, Stéphane Mauger, Christophe Destombe, Myriam Valero
Date: 2024-04-22 00:00:00

The impact of climate change on populations will be contingent upon their contemporary adaptive evolution. In this study, we investigated the contemporary evolution of four populations of the cold-water kelp Laminaria digitata by analysing their spatial and temporal genomic variation using ddRAD-sequencing. These populations were sampled from the center to the southern margin of its north-eastern Atlantic distribution at two-time points, spanning at least two generations. Through genome scans for local adaptation at a single time point, we identified candidate loci that showed clinal variation correlated with changes in sea surface temperature (SST) along latitudinal gradients. This finding suggests that SST may drive the adaptive response of these kelp populations, although factors such as species' demographic history should also be considered. Additionally, we performed a simulation approach to distinguish the effect of selection from genetic drift in allele frequency changes over time. This enabled the detection of loci in the southernmost population that exhibited temporal differentiation beyond what would be expected from genetic drift alone: these are candidate loci which could have evolved under selection over time. In contrast, we did not detect any outlier locus based on temporal differentiation in the population from the North Sea, which also displayed low and decreasing levels of genetic diversity. The diverse evolutionary scenarios observed among populations can be attributed to variations in the prevalence of selection relative to genetic drift across different environments. Therefore, our study highlights the potential of temporal genomics to offer valuable insights into the contemporary evolution of marine foundation species facing climate change.
Frequency-dependent returns in nonlinear public goods games
Authors: Christoph Hauert, Alex McAvoy
Date: 2024-04-21 00:00:00

When individuals interact in groups, the evolution of cooperation is traditionally modeled using the framework of public goods games. These models often assume that the return of the public good depends linearly on the fraction of contributors. In contrast, in real life public goods interactions, the return can depend on the size of the investor pool as well. Here, we consider a model in which the multiplication factor (marginal per capita return) for the public good depends linearly on how many contribute, which results in a nonlinear model of public goods. This simple model breaks the curse of dominant defection found in linear public goods interactions and gives rise to richer dynamical outcomes in evolutionary settings. We provide an in-depth analysis of the more varied decisions by the classical rational player in nonlinear public goods interactions as well as a mechanistic, microscopic derivation of the evolutionary outcomes for the stochastic dynamics in finite populations and in the deterministic limit of infinite populations. This kind of nonlinearity provides a natural way to model public goods with diminishing returns as well as economies of scale.
A minimal model of boosting and waning iin a recurrent seasonal epidemic
Authors: Siyu Chen, David Sankoff
Date: 2024-04-19 00:00:00

We propose a model of the immunity to a cyclical epidemic disease taking account not only of seasonal boosts during the infectious season, but also of residual immunity remaining from one season to the next. The focus is on the exponential waning process over successive cycles, imposed on the temporal distribution of infections or exposures over a season. This distribution, interacting with the waning function, is all that is necessary to reproduce, in mathematically closed form, the mechanical cycle of boosting and waning immunity characteristic of recurrent seasonal infectious disease. Distinct from epidemiological models predicting numbers of individuals moving between infectivity compartments, our result enables us to directly estimate parameters of waning and the infectivity distribution. We can naturally iterate the cyclical process to simulate immunity trajectories over many years and thus to quantify the strong relationship between residual immunity and the time elapsed between annual infectivity peaks.
The N-Gene Model for Evolutionary Games
Authors: Tyler Clark
Date: 2024-04-19 00:00:00
Tasks: model, Unity

In this study, we develop a novel evolutionary model that incorporates Mendelian genetics, continuous strategies, and the potential for multiple genes to contribute to a single phenotypic trait. The evolution of altruistic behavior, which confers benefits to others at a cost to the individual, remains a fundamental question in evolutionary biology. While previous models have investigated the conditions favoring the emergence and stability of altruism, they have often employed simplifying assumptions, such as single-gene inheritance and discrete strategies. We employ a modified dictator game as the framework for evolutionary interactions and explore the stability of altruistic behavior under various conditions. Our primary result demonstrates that when considering heterozygous genes, altruism can be evolutionarily stable at cost-to-benefit ratios exceeding unity, even with initially low frequencies of altruists in the population. This finding contrasts with the case of homozygous genes, where altruism is only stable at cost-to-benefit ratios greater than 2. The generality of our approach allows for its application to a diverse range of evolutionary games and interactions, providing a powerful tool for investigating the emergence and maintenance of social behaviors and personality traits. Our results contribute to the understanding of the evolutionary mechanisms underlying altruism and underscore the importance of incorporating genetic complexity in evolutionary models. This work has implications for the study of social evolution and the genetic architecture of complex behavioral phenotypes.
Modeling principles for a physiology-based whole-body model of human metabolism
Authors: Laura Hjort Blicher, Peter Emil Carstensen, Jacob Bendsen, Henrik Linden, Bjørn Hald, Kim Kristensen, John Bagterp Jørgensen
Date: 2024-04-22 00:00:00

Physiological whole-body models are valuable tools for the development of novel drugs where understanding the system aspects is important. This paper presents a generalized model that encapsulates the structure and flow of whole-body human physiology. The model contains vascular, interstitial, and cellular subcompartments for each organ. Scaling of volumes and blood flows is described to allow for investigation across populations or specific patient groups. The model equations and the corresponding parameters are presented along with a catalog of functions that can be used to define the organ transport model and the biochemical reaction model. A simple example illustrates the procedure.
A whole-body mathematical model of cholesterol metabolism and transport
Authors: Peter Emil Carstensen, Jacob Bendsen, Laura Hjort Blicher, Kim Kristensen, John Bagterp Jørgensen
Date: 2024-04-22 00:00:00
Tasks: Management

Cardiovascular diseases are the leading cause of death. Increased levels of plasma cholesterol are consistently associated with an increased risk of cardiovascular disease. As a result, it is imperative that studies are conducted to determine the best course of action to reduce whole-body cholesterol levels. A whole-body mathematical model for cholesterol metabolism and transport is proposed. The model can simulate the effects of lipid-lowering drugs like statins and anti-PCSK9. The model is based on ordinary differential equations and kinetic functions. It has been validated against literature data. It offers a versatile platform for designing personalized interventions for cardiovascular health management.
Joint Liability Model with Adaptation to Climate Change
Authors: Jiayue Zhang, Ken Seng Tan, Tony S. Wirjanto, Lysa Porth
Date: 2024-04-22 00:00:00
Tasks: model

This paper extends the application of ESG score assessment methodologies from large corporations to individual farmers' production, within the context of climate change. Our proposal involves the integration of crucial agricultural sustainability variables into conventional personal credit evaluation frameworks, culminating in the formulation of a holistic sustainable credit rating referred to as the Environmental, Social, Economics (ESE) score. This ESE score is integrated into theoretical joint liability models, to gain valuable insights into optimal group sizes and individual-ESE score relationships. Additionally, we adopt a mean-variance utility function for farmers to effectively capture the risk associated with anticipated profits. Through a set of simulation exercises, the paper investigates the implications of incorporating ESE scores into credit evaluation systems, offering a nuanced comprehension of the repercussions under various climatic conditions.