pwc-archive/papers-with-abstracts huggingface dataset:
Motion Ordering in Cellular Polar-polar and Polar-nonpolar Interactions
Authors: Katsuyoshi Matsushita, Taiko Arakaki, Koichi Fujimoto
Date: 2024-09-09 00:00:00

We examine the difference in motion ordering between cellular systems with and without information transfer to evaluate the effect of the polar--polar interaction through mutual guiding, which enables cells to inform other cells of their moving directions. We compare this interaction with the polar--nonpolar interaction through cell motion triggered by cellular contact, which cannot provide information on the moving directions. We model these interactions on the basis of the cellular Potts model. We calculate the order parameter of the polar direction in the interactions and examine the cell concentration and surface tension conditions of ordering. The results suggest that the polar--polar interaction through mutual guiding efficiently induces the motion ordering in comparison with the polar-nonpolar interaction for contact triggering, except in cases of weak driving. The results also show that the polar--polar interaction efficiently accelerates the collective motion compared with the polar--nonpolar interaction.
Quantitative Prediction of Protein-Polyelectrolyte Binding Thermodynamics: Adsorption of Heparin-Analog Polysulfates to the SARS-CoV-2 Spike Protein RBD
Authors: Lenard Neander, Cedric Hannemann, Roland R. Netz, Anil Kumar Sahoo
Date: 2024-08-30 00:00:00
Tasks: Drug Design, Friction

Interactions of polyelectrolytes (PEs) with proteins play a crucial role in numerous biological processes, such as the internalization of virus particles into host cells. Although docking, machine learning methods, and molecular dynamics (MD) simulations are utilized to estimate binding poses and binding free energies of small-molecule drugs to proteins, quantitative prediction of the binding thermodynamics of PE-based drugs presents a significant obstacle in computer-aided drug design. This is due to the sluggish dynamics of PEs caused by their size and strong charge-charge correlations. In this paper, we introduce advanced sampling methods based on a force-spectroscopy setup and theoretical modeling to overcome this barrier. We exemplify our method with explicit solvent all-atom MD simulations of interactions of anionic PEs that show antiviral properties, namely heparin and linear polyglycerol sulfate (LPGS), with the SARS-CoV-2 spike protein receptor binding domain (RBD). Our prediction for the binding free energy of LPGS to the wild-type RBD matches experimentally measured dissociation constants within thermal energy, kT, and correctly reproduces the experimental PE-length dependence. We find that LPGS binds to the Delta-variant RBD with an additional free-energy gain of 2.4 kT, compared to the wild-type RBD, in accord with electrostatic arguments. We show that the LPGS-RBD binding is solvent-dominated and enthalpy-driven, though with a large entropy-enthalpy compensation. Our method is applicable to general polymer adsorption phenomena and predicts precise binding free energies and re-configurational friction as needed for drug and drug-delivery design.
STAA: Spatio-Temporal Alignment Attention for Short-Term Precipitation Forecasting
Authors: Min Chen, Hao Yang, Shaohan Li, Xiaolin Qin
Date: 2024-09-06 00:00:00
Tasks: Precipitation Forecasting

There is a great need to accurately predict short-term precipitation, which has socioeconomic effects such as agriculture and disaster prevention. Recently, the forecasting models have employed multi-source data as the multi-modality input, thus improving the prediction accuracy. However, the prevailing methods usually suffer from the desynchronization of multi-source variables, the insufficient capability of capturing spatio-temporal dependency, and unsatisfactory performance in predicting extreme precipitation events. To fix these problems, we propose a short-term precipitation forecasting model based on spatio-temporal alignment attention, with SATA as the temporal alignment module and STAU as the spatio-temporal feature extractor to filter high-pass features from precipitation signals and capture multi-term temporal dependencies. Based on satellite and ERA5 data from the southwestern region of China, our model achieves improvements of 12.61\% in terms of RMSE, in comparison with the state-of-the-art methods.
Machine Learning Framework for High-Resolution Air Temperature Downscaling Using LiDAR-Derived Urban Morphological Features
Authors: Fatemeh Chajaei, Hossein Bagheri
Date: 2024-08-31 00:00:00

Climate models lack the necessary resolution for urban climate studies, requiring computationally intensive processes to estimate high resolution air temperatures. In contrast, Data-driven approaches offer faster and more accurate air temperature downscaling. This study presents a data-driven framework for downscaling air temperature using publicly available outputs from urban climate models, specifically datasets generated by UrbClim. The proposed framework utilized morphological features extracted from LiDAR data. To extract urban morphological features, first a three-dimensional building model was created using LiDAR data and deep learning models. Then, these features were integrated with meteorological parameters such as wind, humidity, etc., to downscale air temperature using machine learning algorithms. The results demonstrated that the developed framework effectively extracted urban morphological features from LiDAR data. Deep learning algorithms played a crucial role in generating three-dimensional models for extracting the aforementioned features. Also, the evaluation of air temperature downscaling results using various machine learning models indicated that the LightGBM model had the best performance with an RMSE of 0.352{\deg}K and MAE of 0.215{\deg}K. Furthermore, the examination of final air temperature maps derived from downscaling showed that the developed framework successfully estimated air temperatures at higher resolutions, enabling the identification of local air temperature patterns at street level. The corresponding source codes are available on GitHub: https://github.com/FatemehCh97/Air-Temperature-Downscaling.
Symmetries and synchronization from whole-neural activity in {\it C. elegans} connectome: Integration of functional and structural networks
Authors: Bryant Avila, Pedro Augusto, David Phillips, Tommaso Gili, Manuel Zimmer, Hernán A. Makse
Date: 2024-09-04 00:00:00

Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have been devised to extract network features like motifs, centrality, and modularity measures. It has previously been proposed that network symmetries are of particular importance since they are expected to underly the synchronization of a system's units, which is ubiquitously observed in nervous system activity patterns. However, perfectly symmetrical structures are difficult to assess in noisy measurements of biological systems, like neuronal connectomes. Here, we devise a principled method to infer network symmetries from combined connectome and neuronal activity data. Using nervous system-wide population activity recordings of the \textit{C.elegans} backward locomotor system, we infer structures in the connectome called fibration symmetries, which can explain which group of neurons synchronize their activity. Our analysis suggests functional building blocks in the animal's motor periphery, providing new testable hypotheses on how descending interneuron circuits communicate with the motor periphery to control behavior. Our approach opens a new door to exploring the structure-function relations in other complex systems, like the nervous systems of larger animals.
Fibration symmetry-breaking supports functional transitions in a brain network engaged in language
Authors: Tommaso Gili, Bryant Avila, Luca Pasquini, Andrei Holodny, David Phillips, Paolo Boldi, Andrea Gabrielli, Guido Caldarelli, Manuel Zimmer, Hernán A. Makse
Date: 2024-09-04 00:00:00

In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.
Terahertz Channels in Atmospheric Conditions: Propagation Characteristics and Security Performance
Authors: Jianjun Ma, Yuheng Song, Mingxia Zhang, Guohao Liu, Weiming Li, John F. Federici, Daniel M. Mittleman
Date: 2024-08-28 00:00:00

With the growing demand for higher wireless data rates, the interest in extending the carrier frequency of wireless links to the terahertz (THz) range has significantly increased. For long-distance outdoor wireless communications, THz channels may suffer substantial power loss and security issues due to atmospheric weather effects. It is crucial to assess the impact of weather on high-capacity data transmission to evaluate wireless system link budgets and performance accurately. In this article, we provide an insight into the propagation characteristics of THz channels under atmospheric conditions and the security aspects of THz communication systems in future applications. We conduct a comprehensive survey of our recent research and experimental findings on THz channel transmission and physical layer security, synthesizing and categorizing the state-of-the-art research in this domain. Our analysis encompasses various atmospheric phenomena, including molecular absorption, scattering effects, and turbulence, elucidating their intricate interactions with THz waves and the resultant implications for channel modeling and system design. Furthermore, we investigate the unique security challenges posed by THz communications, examining potential vulnerabilities and proposing novel countermeasures to enhance the resilience of these high-frequency systems against eavesdropping and other security threats. Finally, we discuss the challenges and limitations of such high-frequency wireless communications and provide insights into future research prospects for realizing the 6G vision, emphasizing the need for innovative solutions to overcome the atmospheric hurdles and security concerns in THz communications.
Spatial structure facilitates evolutionary rescue by drug resistance
Authors: Cecilia Fruet, Ella Linxia Müller, Claude Loverdo, Anne-Florence Bitbol
Date: 2024-09-11 00:00:00

Bacterial populations often have complex spatial structures, which can impact their evolution. Here, we study how spatial structure affects the evolution of antibiotic resistance in a bacterial population. We consider a minimal model of spatially structured populations where all demes (i.e., subpopulations) are identical and connected to each other by identical migration rates. We show that spatial structure can facilitate the survival of a bacterial population to antibiotic treatment, starting from a sensitive inoculum. Specifically, the bacterial population can be rescued if antibiotic resistant mutants appear and are present when drug is added, and spatial structure can impact the fate of these mutants and the probability that they are present. Indeed, the probability of fixation of neutral or deleterious mutations providing drug resistance is increased in smaller populations. This promotes local fixation of resistant mutants in the structured population, which facilitates evolutionary rescue by drug resistance in the rare mutation regime. Once the population is rescued by resistance, migrations allow resistant mutants to spread in all demes. Our main result that spatial structure facilitates evolutionary rescue by antibiotic resistance extends to more complex spatial structures, and to the case where there are resistant mutants in the inoculum.
When lowering temperature, the in vivo circadian clock in cyanobacteria follows and surpasses the in vitro protein clock trough the Hopf bifurcation
Authors: I. Mihalcescu, H. Kaji, H. Maruyama, J. Giraud, M. Van-Melle Gateau, B. Houchmandzadeh, H. Ito
Date: 2024-09-09 00:00:00

The in vivo circadian clock in single cyanobacteria is studied here by time-lapse fluorescence microscopy when the temperature is lowered below 25{\deg}C . We first disentangle the circadian clock behavior from the bacterial cold shock response by identifying a sequence of "death steps" based on cellular indicators. By analyzing only "alive" tracks, we show that the dynamic response of individual oscillatory tracks to a step-down temperature signal is described by a simple Stuart-Landau oscillator model. The same dynamical analysis applied to in vitro data (KaiC phosphorylation level following a temperature step-down) allows for extracting and comparing both clock's responses to a temperature step down. It appears, therefore, that both oscillators go through a similar supercritical Hopf bifurcation. Finally, to quantitatively describe the temperature dependence of the resulting in vivo and in vitro Stuart-Landau parameters $\mu(T)$ and $\omega_c(T)$, we propose two simplified analytical models: temperature-dependent positive feedback or time-delayed negative feedback that is temperature compensated. Our results provide strong constraints for future models and emphasize the importance of studying transitory regimes along temperature effects in circadian systems.
Adaptive cross-country optimisation strategies in thermal soaring birds
Authors: Göksel Keskin, Olivier Duriez, Pedro Lacerda, Andrea Flack, Máté Nagy
Date: 2024-09-05 00:00:00

Thermal soaring enables birds to perform cost-efficient flights during foraging or migration trips. Yet, although all soaring birds exploit vertical winds effectively, this group contains species that vary strongly in their morphologies. Aerodynamic rules dictate the costs and benefits of flight, but, depending on their ecological needs, species may use different behavioural strategies. To quantify these morphology-related differences in behavioural cross-country strategies, we compiled and analysed a large dataset, which includes data from over a hundred individuals from 12 soaring species recorded with high frequency tracking devices. We quantified the performance during thermalling and gliding flights, and the overall cross-country behaviour that is the combination of both. Our results confirmed aerodynamic theory across the 12 species; species with higher wing loading typically flew faster, and consequently turned on a larger radius, than lighter ones. Furthermore, the combination of circling radius and minimum sink speed determines the maximum benefits soaring birds can obtain from thermals. Also, we observed a spectrum of strategies regarding the adaptivity to thermal strength and uncovered a universal rule for cross-country strategies for all analysed species. Finally, our newly described behavioural rules can provide inspirations for technical applications, like the development of autopilot systems for autonomous robotic gliders.
Simple measures to capture the robustness and the plasticity of soil microbial communities
Authors: Takashi Shimada, Kazumori Mise, Kai Morino, Shigeto Otsuka
Date: 2024-09-05 00:00:00
Tasks: Nutrition

Soil microbial communities are known to be robust against perturbations such as nutrition inputs, which appears as an obstacle for the soil improvement. On the other hand, its adaptable aspect has been also reported. Here we propose simple measures for these seemingly contradicting features of soil microbial communities, robustness and plasticity, based on the distribution of the populations. The first measure is the similarity in the population balance, i.e. the shape of the distribution function, which is found to show resilience against the nutrition inputs. The other is the similarity in the composition of the species measured by the rank order of the population, which shows an adaptable response during the population balance is recovering. These results clearly show that the soil microbial system is robust (or, homeostatic) in its population balance, while the composition of the species is rather plastic and adaptable.
Procedural Synthesis of Synthesizable Molecules
Authors: Michael Sun, Alston Lo, Minghao Guo, Jie Chen, Connor Coley, Wojciech Matusik
Date: 2024-08-24 00:00:00
Tasks: Evolutionary Algorithms, Program Synthesis

Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize both problems using ideas from program synthesis. Drawing inspiration from syntax-guided synthesis approaches, we decouple the syntactic skeleton from the semantics of a synthetic tree to create a bilevel framework for reasoning about the combinatorial space of synthesis pathways. Given a molecule we aim to generate analogs for, we iteratively refine its skeletal characteristics via Markov Chain Monte Carlo simulations over the space of syntactic skeletons. Given a black-box oracle to optimize, we formulate a joint design space over syntactic templates and molecular descriptors and introduce evolutionary algorithms that optimize both syntactic and semantic dimensions synergistically. Our key insight is that once the syntactic skeleton is set, we can amortize over the search complexity of deriving the program's semantics by training policies to fully utilize the fixed horizon Markov Decision Process imposed by the syntactic template. We demonstrate performance advantages of our bilevel framework for synthesizable analog generation and synthesizable molecule design. Notably, our approach offers the user explicit control over the resources required to perform synthesis and biases the design space towards simpler solutions, making it particularly promising for autonomous synthesis platforms. Code is at https://github.com/shiningsunnyday/SynthesisNet.
Why aphids are not pests in cacao? An approach based on a predator-prey model with aging
Authors: Vladimir R. V. Assis, Nazareno G. F. Medeiros, Evandro N. Silva, Alexandre Colato, Ana T. C. Silva
Date: 2024-09-10 00:00:00

We studied a mean-field predator-prey model with aging to simulate the \mbox{interaction} between aphids (\textit{Toxoptera aurantii}) and syrphid larvae in \mbox{cacao} farms in Ilheus, Bahia. Based on the classical predator-prey model, we \mbox{propose} a system of differential equations with three rate equations. \mbox{Unlike} the original Lotka-Volterra model, our model includes two aphid population classes: juveniles (non-breeding) and adult females (asexually breeding). We obtained steady-state solutions for juvenile and adult populations by \mbox{analyzing} the stability of the fixed points as a function of model \mbox{parameters}. The results show that the absorbing state (zero prey population) is always possible, but not consistently stable. A nonzero stationary solution is achievable with appropriate parameter values. Using phase diagrams, we analyzed the \mbox{stationary} solution, providing a comprehensive understanding of the \mbox{dynamics} involved. Simulations on complete graphs yielded \mbox{results} closely matching the differential equations. We also \mbox{performed} simulations on \mbox{random} networks to highlight the influence of \mbox{network} topology on \mbox{system} behavior. Our findings highlight the critical role of life-stage structure, \mbox{predation}, and spatial variation in stabilizing predator-prey \mbox{systems}. This emphasizes the importance of network effects in population dynamics and refines the framework for biological pest control in agriculture. Ultimately, our research contributes to sustainable agricultural practices.
Quantum panprotopsychism and the structure and subject-summing combination problem
Authors: Rodolfo Gambini, Jorge Pullin
Date: 2024-09-02 00:00:00

In a previous paper, we have shown that an ontology of quantum mechanics in terms of states and events with internal phenomenal aspects, that is, a form of panprotopsychism, is well suited to explaining the phenomenal aspects of consciousness. We have proved there that the palette and grain combination problems of panpsychism and panprotopsychism arise from implicit hypotheses based on classical physics about supervenience that are inappropriate at the quantum level, where an exponential number of emergent properties and states arise. In this article, we address what is probably the first and most important combination problem of panpsychism: the subject-summing problem originally posed by William James. We begin by identifying the physical counterparts of the subjects of experience within the quantum panprotopsychic approach presented in that article. To achieve this, we turn to the notion of subject of experience inspired by the idea of prehension proposed by Whitehead and show that this notion can be adapted to the quantum ontology of objects and events. Due to the indeterminacy of quantum mechanics and its causal openness, this ontology also seems to be suitable for the analysis of the remaining aspects of the structure combination problem, which shows how the structuration of consciousness could have evolved from primitive animals to humans. The analysis imposes conditions on possible implementations of quantum cognition mechanisms in the brain and suggests new problems and strategies to address them. In particular, with regard to the structuring of experiences in animals with different degrees of evolutionary development.