bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data‐Driven Discovery of Fokker‐Planck Equation for the Earth's Radiation Belts Electrons Using Physics‐Informed Neural Networks
Authors: Camporeale E. , Wilkie George J. , Drozdov Alexander Y. , Bortnik Jacob 
Published: July 2022

AbstractWe use the framework of Physics‐Informed Neural Network (PINN) to solve the inverse problem associated with the Fokker‐Planck equation for radiation belts' electron transport, using 4 years of Van Allen Probes data. Traditionally, reduced models have employed a diffusion equation based on the quasilinear approximation. We show that the dynamics of “killer electrons” is described more accurately by a drift‐diffusion equation, and that drift is as important as diffusion for nearly‐equatorially trapped ∼1 MeV electrons in the inner part of the belt. Moreover, we present a recipe for gleaning physical insight from solving the ill‐posed inverse problem of inferring model coefficients from data using PINNs. Furthermore, we derive a parameterization for the diffusion and drift coefficients as a function of L only, which is both simpler and more accurate than earlier models. Finally, we use the PINN technique to develop an automatic event identification method that allows identifying times at which the radial transport assumption is inadequate to describe all the physics of interest.
Determination of Parameters Characteristic of Dynamic Weakening Mechanisms During Seismic Faulting in Cohesive Rocks
Authors: Cornelio C. , Spagnuolo E. , Aretusini S. , Nielsen S. , Passelègue F. , Violay M. , Cocco M. , Di Toro G. 
Published: July 2022

AbstractWhile sliding at seismic slip‐rates of ∼1 m/s, natural faults undergo an abrupt decrease of shear stress called dynamic weakening. Asperity‐scale (<<mm) processes related to flash heating and weakening and, meso‐scale (mm‐cm) processes involving shear across the bulk slip‐zone, related to frictional melting or viscous flow of minerals, have been invoked to explain pronounced velocity‐dependent weakening. Here we present a compilation of ∼100 experiments performed with two rotary shear apparatuses. Cohesive rock cylinders of basalt, gabbro, granitoid rocks and calcitic marble were sheared at various values of effective normal stress (σneff = 5–40 MPa), target slip‐rate (Vt = 0.1–6.5 m/s) and fluid pressure (Pf = 0–15 MPa). To account for the uncertainties of constitutive parameters, we introduce a norm‐based optimization procedure on a set of model parameters by comparing the shear stress evolution inferred from the proposed weakening models with the shear stress measured during the experiments. We analyze the fit to experimental data of each weakening model and we discuss a composite model in which two weakening mechanisms (namely flash heating and bulk melting, flash heating and dislocation/diffusion creep) are used to test the hypothesis that they match the shear stress evolution in different slip ranges. We found that for slip smaller than a slip‐switch distance δ0, the weakening is better described by mechanisms occurring at the asperity scale whereas for larger slip values the bulk model performs better. The inferred δ0 values decrease with normal stress suggesting that during earthquakes bulk mechanisms can govern shear stress evolution after a few centimeters of slip.
Quantifying the Effect of ICME Removal and Observation Age for in Situ Solar Wind Data Assimilation
Authors: Turner Harriet , Owens Mathew , Lang Matthew , Gonzi Siegfried , Riley Pete 
Published: July 2022

AbstractAccurate space weather forecasting requires advanced knowledge of the solar wind conditions in near‐Earth space. Data assimilation (DA) combines model output and observations to find an optimum estimation of reality and has led to large advances in terrestrial weather forecasting. It is now being applied to space weather forecasting. Here, we use solar wind DA with in‐situ observations to reconstruct solar wind speed in the ecliptic plane between 30 solar radii and Earth's orbit. This is used to provide solar wind speed hindcasts. Here, we assimilate observations from the Solar Terrestrial Relations Observatory and the near‐Earth data set, OMNI. Analysis of two periods of time, one in solar minimum and one in solar maximum, reveals that assimilating observations from multiple spacecraft provides a more accurate forecast than using any one spacecraft individually. The age of the observations also has a significant impact on forecast error, whereby the mean absolute error (MAE) sharply increases by up to 23% when the forecast lead time first exceeds the corotation time associated with the longitudinal separation between the observing spacecraft and the forecast location. It was also found that removing coronal mass ejections from the DA input and verification time series reduces the forecast MAE by up to 10% as it removes false streams from the forecast time series. This work highlights the importance of an L5 space weather monitoring mission for near‐Earth solar wind forecasting and suggests that an additional mission to L4 would further improve future solar wind DA forecasting capabilities.
Hypoxia-hindered methylation of PTGIS in endometrial stromal cells accelerates endometriosis progression by inducing CD16− NK-cell differentiation
Authors: Peng Haiyan , Weng Lichun , Lei Shating , Hou Shuhui , Yang Shaoliang , Li Mingqing , Zhao Dong 
Published: July 2022

AbstractProstacyclin (PGI2) plays key roles in shaping the immune microenvironment and modulating vasodilation, whereas its contribution to endometriosis (EMs) remains largely unclear. Our study suggested that prostacyclin synthase (PTGIS)-dependent PGI2 signaling was significantly activated in EMs, which was involved in the hypoxic microenvironment of ectopic lesions and deficient methylation status of the PTGIS promoter. Notably, in vitro assays, hypoxia promoted PTGIS expression through DNA methyltransferase 1 (DNMT1)-mediated DNA methylation deficiency in endometrial stromal cells (ESCs); PTGIS overexpression enhanced the adhesive ability of ESCs and led to elevated PGI2 production, and PGI2 triggered CD16− (encoded by FCGR3, Fc fragment of IgG receptor IIIa) natural killer (NK)-cell differentiation through PGI2 receptor (IP, PTGIR) in an ESC/NK-cell coculture system. Our rodent model experiment suggested that treatment with the PGI2 analog iloprost and adoptive transfer of fcgr3 knockout (fcgr3−/−) NK cells aggravated EMs progression and that genetic ablation of ptgis (ptgis−/−) in ectopic lesions and treatment with the PTGIR antagonist RO1138452 partially rescued this outcome. Thus, our findings identified the contribution of PGI2 to EMs progression via enhancement of the adhesive ability of ESCs and inhibition of the activity of NK cells. We hypothesized that PGI2 is a target for EMs intervention and provide a rationale for studying pharmacological PTGIR inhibition and PTGIS genetic depletion therapies as therapeutic strategies for EMs.
LncRNAs in breast cancer: a link to future approaches
Authors: Sideris Nikolaos , Dama Paola , Bayraktar Salih , Stiff Thomas , Castellano Leandro 
Published: July 2022

AbstractBreast cancer affects millions of women each year. Despite recent advances in targeted treatments breast cancer remains a significant threat to women’s health. In recent years the development of high-throughput sequencing technologies has advanced the field of transcriptomics shedding light on the role of non-coding RNAs (ncRNAs), including long ncRNAs (lncRNAs), in human cellular function and disease. LncRNAs are classified as transcripts longer than 200nt with no coding potential. These transcripts constitute a diverse group of regulatory molecules essential to the modulation of crucial cellular processes, which dysregulation of leads to disease. LncRNAs exert their regulatory functions through their sequences and by forming complex secondary and tertiary structures that interact with other transcripts, chromatin and/or proteins. Numerous studies have provided evidence of the involvement of LncRNAs in tumor development and disease progression. They possess multiple characteristics that make them novel therapeutic and diagnostic targets. Indeed, the discovery of a novel mechanism by which lncRNAs associated with proteins can induce the formation of phase-separated droplets broadens our understanding of the spatiotemporal control of cellular processes and opens up developing a new treatment. Nevertheless, the role and the molecular mechanisms of many lncRNAs in the regulation of cellular processes and cancer still remain elusive. This is due to the absence of a thorough characterization of the regulatory role of their loci and the functional impact of their aberrations in cancer biology. Here, we present some of the latest advances concerning the role of LncRNAs in breast cancer.
Magnetic molecules as local sensors of topological hysteresis of superconductors
Authors: Serrano Giulia , Poggini Lorenzo , Cucinotta Giuseppe , Sorrentino Andrea Luigi , Giaconi Niccolò , Cortigiani Brunetto , Longo Danilo , Otero Edwige , Sainctavit Philippe , Caneschi Andrea , Mannini Matteo , Sessoli Roberta 
Published: July 2022

AbstractSuperconductors and magnetic materials, including molecules, are key ingredients for quantum computing and spintronics. However, only a little is known about how these materials interact in multilayer nanostructures like the hybrid architectures nowadays under development for such advanced applications. Here, we show that a single layer of magnetic molecules, Terbium(III) bis-phthalocyaninato (TbPc2) complexes, deposited under controlled UHV conditions on a superconducting Pb(111) surface is sensitive to the topology of the intermediate state of the superconductor, namely to the presence and evolution of superconducting and normal domains due to screening and penetration of an external magnetic field. The topological hysteresis of the superconducting substrate imprints a local evolution of the magnetisation of the TbPc2 molecules in the monolayer. Element and surface selective detection is achieved by recording the X-ray magnetic circular dichroism of the Tb atoms. This study reveals the impressive potential of magnetic molecules for sensing local magnetic field variations in molecular/superconductor hybrid devices, including spin resonators or spin injecting and spin filtering components for spintronics applications.
Design principles for water dissociation catalysts in high-performance bipolar membranes
Authors: Chen Lihaokun , Xu Qiucheng , Oener Sebastian Z. , Fabrizio Kevin , Boettcher Shannon W. 
Published: July 2022

AbstractWater dissociation (WD, H2O → H+ + OH−) is the core process in bipolar membranes (BPMs) that limits energy efficiency. Both electric-field and catalytic effects have been invoked to describe WD, but the interplay of the two and the underlying design principles for WD catalysts remain unclear. Using precise layers of metal-oxide nanoparticles, membrane-electrolyzer platforms, materials characterization, and impedance analysis, we illustrate the role of electronic conductivity in modulating the performance of WD catalysts in the BPM junction through screening and focusing the interfacial electric field and thus electrochemical potential gradients. In contrast, the ionic conductivity of the same layer is not a significant factor in limiting performance. BPM water electrolyzers, optimized via these findings, use ~30-nm-diameter anatase TiO2 as an earth-abundant WD catalyst, and generate O2 and H2 at 500 mA cm−2 with a record-low total cell voltage below 2 V. These advanced BPMs might accelerate deployment of new electrodialysis, carbon-capture, and carbon-utilization technology.
Photovoltaphores: pharmacophore models for identifying metal-free dyes for dye-sensitized solar cells
Authors: Binyamin Hadar , Senderowitz Hanoch 
Published: July 2022

AbstractDye-sensitized solar cells (DSSCs) are cost-effective, sustainable, and versatile electricity producers, allowing them to be incorporated into a variety of devices. In this work, we explore the usage of pharmacophore modeling to identify metal-free dyes for DSSCs by means of virtual screening. Pharmacophore models were built based on experimentally tested sensitizers. Virtual screening was performed against a large dataset of commercially available compounds taken from the ZINC15 library and identified multiple virtual hits. A subset of these hits was subjected to DFT and time-dependent-DFT calculations leading to the identification of two compounds, TSC6 and ASC5, with appropriate molecular orbitals energies, favorable localization, and reasonable absorption UV–vis spectra. These results suggest that pharmacophore models, traditionally used in drug discovery and lead optimization, successfully predicted electronic properties, which are in agreement with the theoretical requirements for sensitizers. Such models may therefore find additional usages as modeling tools in materials sciences.
The use of viral vectors in vaccine development
Authors: Travieso Tatianna , Li Jenny , Mahesh Sneha , Mello Juliana Da Fonzeca Redenze E. , Blasi Maria 
Published: July 2022

AbstractVaccines represent the single most cost-efficient and equitable way to combat and eradicate infectious diseases. While traditional licensed vaccines consist of either inactivated/attenuated versions of the entire pathogen or subunits of it, most novel experimental vaccines against emerging infectious diseases employ nucleic acids to produce the antigen of interest directly in vivo. These include DNA plasmid vaccines, mRNA vaccines, and recombinant viral vectors. The advantages of using nucleic acid vaccines include their ability to induce durable immune responses, high vaccine stability, and ease of large-scale manufacturing. In this review, we present an overview of pre-clinical and clinical data on recombinant viral vector vaccines and discuss the advantages and limitations of the different viral vector platforms.
Human-centred mechanism design with Democratic AI
Authors: Koster Raphael , Balaguer Jan , Tacchetti Andrea , Weinstein Ari , Zhu Tina , Hauser Oliver , Williams Duncan , Campbell-Gillingham Lucy , Thacker Phoebe , Botvinick Matthew , Summerfield Christopher 
Published: July 2022

AbstractBuilding artificial intelligence (AI) that aligns with human values is an unsolved problem. Here we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used to design a social mechanism that humans prefer by majority. A large group of humans played an online investment game that involved deciding whether to keep a monetary endowment or to share it with others for collective benefit. Shared revenue was returned to players under two different redistribution mechanisms, one designed by the AI and the other by humans. The AI discovered a mechanism that redressed initial wealth imbalance, sanctioned free riders and successfully won the majority vote. By optimizing for human preferences, Democratic AI offers a proof of concept for value-aligned policy innovation.
Thermally induced magnetic order from glassiness in elemental neodymium
Authors: Verlhac Benjamin , Niggli Lorena , Bergman Anders , Kamber Umut , Bagrov Andrey , Iuşan Diana , Nordström Lars , Katsnelson Mikhail I. , Wegner Daniel , Eriksson Olle , Khajetoorians Alexander A. 
Published: July 2022

AbstractAt finite temperatures, fluctuations invariably introduce disorder and are responsible for ultimately destroying ordered phases. Here we present an unusual magnetic transition in elemental neodymium where, with increasing temperature, long-range multiply periodic ‘multi-Q’ magnetic order emerges from a self-induced spin glass. Using temperature-dependent spin-polarized scanning tunnelling microscopy, we characterize the local order of a previously reported spin glass phase, and quantify the emergence of long-range multi-Q order with increasing temperature. We develop two analysis tools that allow us to determine the glass transition temperature from measurements of the spatially dependent magnetization. We compare these observations with atomistic spin dynamics simulations, which reproduce the qualitative observation of a phase transition from a low-temperature spin glass phase to an intermediate ordered multi-Q phase. These simulations trace the origin of the unexpected high-temperature order in weakened frustration driven by temperature-dependent sublattice correlations. These findings constitute an example of order from disorder, and provide a platform to study the rich magnetization dynamics of a self-induced spin glass.
Self-regulation of phenotypic noise synchronizes emergent organization and active transport in confluent microbial environments
Authors: Dhar Jayabrata , Thai Anh L. P. , Ghoshal Arkajyoti , Giomi Luca , Sengupta Anupam 
Published: July 2022

AbstractThe variation associated with different observable characteristics—phenotypes—at the cellular scale underpins homeostasis and the fitness of living systems. However, if and how these noisy phenotypic traits shape properties at the population level remains poorly understood. Here we report that phenotypic noise self-regulates with growth and coordinates collective structural organization, the kinetics of topological defects and the emergence of active transport around confluent colonies. We do this by cataloguing key phenotypic traits in bacteria growing under diverse conditions. Our results reveal a statistically precise critical time for the transition from a monolayer biofilm to a multilayer biofilm, despite the strong noise in the cell geometry and the colony area at the onset of the transition. This reveals a mitigation mechanism between the noise in the cell geometry and the growth rate that dictates the narrow critical time window. By uncovering how rectification of phenotypic noise homogenizes correlated collective properties across colonies, our work points at an emergent strategy that confluent systems employ to tune active transport, buffering inherent heterogeneities associated with natural cellular environment settings.
An 8-year record of phytoplankton productivity and nutrient distributions from surface waters of Saanich Inlet
Authors: Kafrissen Sile M. , Giesbrecht Karina E. , McNabb Brandon J. , Long Jennifer E. , Martin Curtis , Wyatt Shea N. , Lagunas Marcos G. , Varela Diana E. 
Published: July 2022

AbstractPhytoplankton are the base of nearly all marine food webs and mediate the interactions of biotic and abiotic components in marine systems. Understanding the spatial and temporal changes in phytoplankton growth requires comprehensive biological, physical, and chemical information. Long-term datasets are an invaluable tool to study these changes, but they are rare and often include only a small set of measurements. Here, we present biological, physical and chemical oceanographic data measured periodically between March 2010 and November 2017 from the euphotic zone of Saanich Inlet, a temperate fjord on the west coast of British Columbia, Canada. The dataset includes measurements of dissolved macronutrients, total and size-fractionated chlorophyll-a, particulate carbon, nitrogen and biogenic silica, and carbon and nitrate uptake rates. This collection describes phytoplankton dynamics and the distribution of biologically-available macronutrients over time in the upper water column of Saanich Inlet. We establish a baseline for future investigations in Saanich Inlet and provide a data collection protocol that can be applied to similar productive coastal regions.
Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy
Authors: Blum Leonore , Hofmann Anna , Rosenbaum David , Elshehabi Morad , Suenkel Ulrike , Fallgatter Andreas J. , Ehlis Ann-Christine , Metzger Florian G. 
Published: July 2022

AbstractChanges in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.
Sesamin protects against neurotoxicity via inhibition of microglial activation under high glucose circumstances through modulating p38 and JNK signaling pathways
Authors: Kongtawelert Prachya , Kaewmool Chayanut , Phitak Thanyaluck , Phimphilai Mattabhorn , Pothacharoen Peraphan , Shwe Thuzar Hla 
Published: July 2022

AbstractDiabetes mellitus (DM), one of the principal causes of morbidity and mortality worldwide, is implicated in the progression of age-related neurodegenerative diseases (NDDs), in which microglial activation is a crucial mediator. Sesamin, a kind of phytochemical, shows inhibitory effects on microglial activation. The present study studied whether sesamin protects against neurotoxicity triggered by high glucose-induced microglial activation. We firstly demonstrated that high doses of glucose, which mimics hyperglycemia in DM, did induce the activation of murine BV2 microglial cells, increasing inflammatory responses such as the production of ROS or inflammatory mediators like IL-1β, TNF-⍺, and nitric oxide, through activation of p38 and JNK signaling pathways. Next, conditioned medium (CM) collected from high glucose-activated BV2 cell culture was used to show aggravated neurotoxicity in differentiated PC12 cells, indicating that high glucose-activated microglia could induce neurotoxicity. Interestingly, pretreatment of BV2 cells with sesamin diminished high glucose-induced microglia activation and inflammatory responses. Moreover, neurotoxicity in PC12 cells was found to be decreased in the group treated with CM from the sesamin-pretreated BV2 cell culture, suggesting sesamin inhibited microglial activation, thereby protecting neurons from activated microglia-mediated neurotoxicity. Thus, sesamin might be a potential compound to use in the prevention of diabetic-induced NDDs.