Vesiclepedia 2019 : a compendium of RNA, proteins, lipids and metabolites in extracellular vesicles

Extracellular vesicles (EVs) are membranous vesicles that are released by both prokaryotic and eukaryotic cells into the extracellular microenvironment. EVs can be categorised as exosomes, ectosomes or shedding microvesicles and apoptotic bodies based on the mode of biogenesis. EVs contain biologically active cargo of nucleic acids, proteins, lipids and metabolites that can be altered based on the precise state of the cell. Vesiclepedia (http://www.microvesicles.org) is a web-based compendium of RNA, proteins, lipids and metabolites that are identified in EVs from both published and unpublished studies. Currently, Vesiclepedia contains data obtained from 1254 EV studies, 38 146 RNA entries, 349 988 protein entries and 639 lipid/metabolite entries. Vesiclepedia is publicly available and allows users to query and download EV cargo based on different search criteria. The mode of EV isolation and characterization, the biophysical and molecular properties and EV-METRIC are listed in the database aiding biomedical scientists in assessing the quality of the EV preparation and the corresponding data obtained. In addition, FunRich-based Vesiclepedia plugin is incorporated aiding users in data analysis

Suffering from Vaccines or from Government? : Partisan Bias in COVID-19 Vaccine Adverse Events Coverage

Vaccine adverse events have been presumed to be a relatively objective measure that is immune to political polarization. The real-world data, however, shows the correlation between presidential disapproval ratings and the subjective severity of adverse events. This paper investigates the partisan bias in COVID vaccine adverse events coverage with language models that can classify the topic of vaccine-related articles and the political disposition of news comments. Based on 90K news articles from 52 major newspaper companies, we found that conservative media are inclined to report adverse events more frequently than their liberal counterparts, while the coverage itself was statistically uncorrelated with the severity of real-world adverse events. The users who support the conservative opposing party were more likely to write the popular comments from 2.3K random sampled articles on news platforms. This research implies that bipartisanship can still play a significant role in forming public opinion on the COVID vaccine even after the majority of the population's vaccinationComment: 5 pages, 5 figures, 2 table

Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws

Traditionally, classical numerical schemes have been employed to solve partial differential equations (PDEs) using computational methods. Recently, neural network-based methods have emerged. Despite these advancements, neural network-based methods, such as physics-informed neural networks (PINNs) and neural operators, exhibit deficiencies in robustness and generalization. To address these issues, numerous studies have integrated classical numerical frameworks with machine learning techniques, incorporating neural networks into parts of traditional numerical methods. In this study, we focus on hyperbolic conservation laws by replacing traditional numerical fluxes with neural operators. To this end, we developed loss functions inspired by established numerical schemes related to conservation laws and approximated numerical fluxes using Fourier neural operators (FNOs). Our experiments demonstrated that our approach combines the strengths of both traditional numerical schemes and FNOs, outperforming standard FNO methods in several respects. For instance, we demonstrate that our method is robust, has resolution invariance, and is feasible as a data-driven method. In particular, our method can make continuous predictions over time and exhibits superior generalization capabilities with out-of-distribution (OOD) samples, which are challenges that existing neural operator methods encounter.Comment: 39 pages, 16 figure

Modeling Freely Flying Monarch Butterflies Using a Strongly Coupled High Fidelity Numerical Framework

Flying insects are impressive creatures due in part to their small size and agile flight maneuvers. Additionally, butterflies can be highly efficient fliers, as evidenced by monarchs having the longest migration amongst insects. To begin uncovering the complex mechanisms enabling monarchs to migrate roughly 80 million times their average body length, high-fidelity modeling tools are required: These tools must consider the distinguishing features of monarchs ­ their low flapping frequency, high Reynolds number (amongst insects), large wings relative to their body, low wing loading, flexibility of their wings, and the highly coupled interplay between the instantaneous wing aerodynamics and dynamic body response. Many butterfly flight models to date have neglected the passive wing pitching arising from butterfly's flexible wings. Here, we propose a framework that tightly couples the effects of all three physics solvers using a dynamic relaxation scheme. As such, the highly nonlinear interplay between fluid, body, and passive wing dynamics is efficiently accounted for in each time step. We apply the model to the free flight of monarch butterflies, resulting in stable motion for many periods without any controllers

Marsbee - Swarm of Flapping Wing Flyers for Enhanced Mars Exploration

Mars exploration has received significant interest from academia, industry, government, and the general public. Despite continued interest, flying on Mars remains challenging, mainly due to the ultra-thin Martian atmospheric density. Although the gravitational acceleration on Mars is 38 percent of Earth's 9.8 meters per second squared, the Martian atmospheric density is only 1.3 percent of the air density on Earth. The aerodynamic forces are proportional to the ambient fluid density. Therefore, flying near the surface of Mars has been considered nearly impossible. The proposed mission architecture (Fig. 1) consists of a Mars rover (already existing) that serves as a mobile base for Marsbees - a deployable swarm of small bio-inspired flapping wing vehicles. In one ConOps scenario, each Marsbee would carry an integrated stereographic video camera and the swarm could construct a 3D topographic map of the local surface for rover path planning. These flying scouts would provide a "third-dimension" to the rover capabilities. In other scenarios, each part of the swarm of Marsbees could carry pressure and temperature sensors for atmospheric sampling, or small spectral analyzers for identification of mineral outcroppings. In each scenario, the rover acts as a recharging and deployment/return station and data and communication hub. Human exploration of Mars is one of the major objectives of NASA and commercial entities such as SpaceX and Boeing. The identified innovations unique to the bio-inspired flapping Marsbee provide viable multi-mode flying mobility for Martian atmospheric and terrain exploration. A swarm of Marsbees provides an enhanced reconfigurable Mars exploration system that is resilient to individual component failures. These Marsbees can carry sensors and wireless communication devices in combination with a Mars rover and helicopters. These enhanced sensing and information gathering abilities can contribute to the following NASA Mars mission objectives: i) "Determine the habitability of an environment", ii) "Obtain surface weather measurements to validate global atmospheric models", and iii) "Prepare for human exploration on Mars." Various commercial entities, e.g. SpaceX and Boeing, are investing in technologies to transport humans to Mars