bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pattern of head circumference growth following bidirectional Glenn in infants with single ventricle heart disease
Authors: Tseng Stephanie Y , Anixt Julia , Meinzen-Derr Jareen , Thomas Cameron , Cooper David S , Heydarian Haleh C 
Published: December 2020

AbstractBackground:Infants with single ventricle congenital heart disease demonstrate increasing head growth after bidirectional Glenn; however, the expected growth trajectory has not been well described.Aims:1) We will describe the pattern of head circumference growth in the first year after bidirectional Glenn. 2) We will determine if head growth correlates with motor developmental outcomes approximately 12 months after bidirectional Glenn.Methods:Sixty-nine single ventricle patients underwent bidirectional Glenn between 2010 and 2016. Patients with structural brain abnormalities, grade III–IV intra-ventricular haemorrhage, significant stroke, or obstructive hydrocephalus were excluded. Head circumference and body weight measurements from clinical encounters were evaluated. Motor development was measured with Psychomotor Developmental Index of the Bayley Scales of Infant Development, Third Edition. Generalised estimating equations assessed change in head circumference z-scores from baseline (time of bidirectional Glenn) to 12 months post-surgery.Results:Mean age at bidirectional Glenn was 4.7 (2.3) months and mean head circumference z-score based on population-normed data was −1.13 (95% CI −1.63, −0.63). Head circumference z-score increased to 0.35 (95% CI −0.20, 0.90) (p < 0.0001) 12 months post-surgery. Accelerated head growth, defined as an increase in z-score of >1 from baseline to 12 months post-surgery, was present in 46/69 (66.7%) patients. There was no difference in motor Psychomotor Developmental Index scores between patients with and without accelerated head growth.Conclusion:Single ventricle patients demonstrated a significant increase in head circumference after bidirectional Glenn until 10–12 months post-surgery, at which time growth stabilised. Accelerated head growth did not predict sub-sequent motor developmental outcomes.
The Probabilistic Description Logic
Authors: BOTHA LEONARD , MEYER THOMAS , PEÑALOZA RAFAEL 
Published: December 2020

AbstractDescription logics (DLs) are well-known knowledge representation formalisms focused on the representation of terminological knowledge. Due to their first-order semantics, these languages (in their classical form) are not suitable for representing and handling uncertainty. A probabilistic extension of a light-weight DL was recently proposed for dealing with certain knowledge occurring in uncertain contexts. In this paper, we continue that line of research by introducing the Bayesian extension of the propositionally closed DL . We present a tableau-based procedure for deciding consistency and adapt it to solve other probabilistic, contextual, and general inferences in this logic. We also show that all these problems remain ExpTime-complete, the same as reasoning in the underlying classical .
Escape of CO2+ and Other Heavy Minor Ions From the Ionosphere of Mars
Authors: Maes Lukas , Fraenz Markus , McFadden James P. , Benna Mehdi 
Published: December 2020

AbstractIonospheric escape from Mars is an important process for the erosion of the Martian atmosphere. The heavy ion outflow is dominated by and O+, however, the Martian ionosphere consists of many more ion species. In the dayside ionosphere below roughly 220 km altitude, is the second most dominant ion, and higher up and in the nightside ionosphere other ions species with a mass near but below that of (28–30 Atomic Mass Unit [AMU], e.g., CO+, , HCO+, NO+, etc.) gain in importance. However, their contribution to the ionospheric outflow is often obscured by the dominant ions and O+. Therefore, we perform a peak fitting to the mass spectrum of SupraThermal and Thermal Ion Composition onboard Mars Atmosphere and Volatile EvolutioN. This method is validated against the mass spectrum given by Neutral Gas and Ion Mass Spectrometer, and results in the ionosphere agree qualitatively very well. A statistical study is then performed to study the low‐energy (<100 eV) heavy ion outflow. We find that can be seen throughout the Martian magnetosphere, but it escapes only in small amounts at a mean rate of less than 1% of the rate. On the other hand, we find that the ions with a mass from 28 to 30 AMU, which were previously unknown in the Martian ion escape, are an important part of the ionospheric outflow, with a mean escape rate that reaches 32% of the rate.
Characteristics of Frequent Dynamic Triggering of Microearthquakes in Southern California
Authors: Fan Wenyuan , Barbour Andrew J. , Cochran Elizabeth S. , Lin Guoqing 
Published: December 2020

AbstractDynamic triggering of earthquakes has been reported at various fault systems. The triggered earthquakes are thought to be caused either directly by dynamic stress changes due to the passing seismic waves, or indirectly by other nonlinear processes that are initiated by the passing waves. Distinguishing these physical mechanisms is difficult because of the general lack of high‐resolution earthquake catalogs and robust means to quantitatively evaluate triggering responses, particularly, delayed responses. Here we use the high‐resolution Quake Template Matching catalog in Southern California to systematically evaluate teleseismic dynamic triggering patterns in the San Jacinto Fault Zone and the Salton Sea Geothermal Field from 2008 to 2017. We develop a new statistical approach to identify triggered cases, finding that approximately 1 out of every 5 globalMw ≥ 6 earthquakes dynamically trigger microearthquakes in Southern California. The triggering responses include both instantaneous and delayed triggering, showing a highly heterogeneous pattern and indicating possible evolving triggering thresholds. We do not observe a clear peak ground velocity triggering threshold that can differentiate triggering earthquakes from nontriggering events, but there are subtle differences in the frequency content of the ground motion that may differentiate the earthquakes. In contrast to the depth distribution of background seismicity, the identified triggered earthquakes tend to concentrate at the edges of the seismogenic zones. Although instantaneously triggered earthquakes are likely a result of dynamic Coulomb stress changes, the cases of delayed‐dynamic triggering are best explained by nonlinear triggering processes, including cyclic material fatigue, accelerated transient creep, and stochastic frictional heterogeneities.
Revealing Sediment Transport Pathways and Geomorphic Change in Washover Fans by Combining Drone‐Derived Digital Elevation Models and Single Grain Luminescence Data
Authors: May Simon Matthias , Callow John Nikolaus , Brill Dominik , Hoffmeister Dirk , May Jan‐Hendrik 
Published: December 2020

AbstractChronostratigraphic investigations on coastal sedimentary records such as washover fans or beach‐ridge sequences may be used to reconstruct storm chronologies on centennial to millennial time scales. However, modern analogs are pivotal in interpreting depositional processes and reducing uncertainty in evaluating the complex chronostratigraphic architecture of these landforms. Such a modern analog was provided by category 3 tropical cyclone (TC) Olwyn in 2015, which caused a significant storm surge in the Exmouth Gulf (Western Australia). Pre‐ and post‐TC Olwyn geomorphological surveys and high‐resolution drone‐derived topographical data of a large washover fan document a detailed history of erosion and deposition during the event. The modern analog deposits provided an excellent opportunity to evaluate the use of luminescence‐based proxies (luminescence inventories) for tracing event‐related sediment source environments and understanding transport processes. Sediments deposited during Olwyn show a systematic relationship between luminescence characteristics and washover fan position. Seaward and central washover sections are indicated by well‐bleached deposits due to the beach as the dominant source and/or long transport distances. Lateral washover deposits are characterized by rather local source areas and short transport distances, resulting in higher remnant ages of 70–140 a. Our data show that the combination of sediment source environments and sediment transport length across the fan represents the main control in resetting the luminescence signal and enabling reliable depositional ages to be calculated. It documents the benefit of investigating luminescence inventories when establishing chronologies from complex sedimentary records, thereby demanding a careful consideration of local processes and source areas when interpreting sedimentary TC records.
Distortions of the Rain Distribution With Warming, With and Without Self‐Aggregation
Authors: Fildier Benjamin , Collins William D. , Muller Caroline 
Published: December 2020

AbstractWe investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative‐convective equilibrium states in a cloud‐resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative‐ and surface‐flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non‐trivial sensitivity to the degree of organization. Second, alternating Clausius‐Clapeyron and super‐Clausius‐Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges.The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self‐aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.
Histone acylation marks respond to metabolic perturbations and enable cellular adaptation
Authors: Jo Chanhee , Park Seokjae , Oh Sungjoon , Choi Jinmi , Kim Eun-Kyoung , Youn Hong-Duk , Cho Eun-Jung 
Published: December 2020

AbstractAcetylation is the most studied histone acyl modification and has been recognized as a fundamental player in metabolic gene regulation, whereas other short-chain acyl modifications have only been recently identified, and little is known about their dynamics or molecular functions at the intersection of metabolism and epigenetic gene regulation. In this study, we aimed to understand the link between nonacetyl histone acyl modification, metabolic transcriptional regulation, and cellular adaptation. Using antibodies specific for butyrylated, propionylated, and crotonylated H3K23, we analyzed dynamic changes of H3K23 acylation upon various metabolic challenges. Here, we show that H3K23 modifications were highly responsive and reversibly regulated by nutrient availability. These modifications were commonly downregulated by the depletion of glucose and recovered based on glucose or fatty acid availability. Depletion of metabolic enzymes, namely, ATP citrate lyase, carnitine acetyltransferase, and acetyl-CoA synthetase, which are involved in Ac-CoA synthesis, resulted in global loss of H3K23 butyrylation, crotonylation, propionylation, and acetylation, with a profound impact on gene expression and cellular metabolic states. Our data indicate that Ac-CoA/CoA and central metabolic inputs are important for the maintenance of histone acylation. Additionally, genome-wide analysis revealed that acyl modifications are associated with gene activation. Our study shows that histone acylation acts as an immediate and reversible metabolic sensor enabling cellular adaptation to metabolic stress by reprogramming gene expression.
A novel multistage antiplasmodial inhibitor targeting Plasmodium falciparum histone deacetylase 1
Authors: Huang Zhenghui , Li Ruoxi , Tang Tongke , Ling Dazheng , Wang Manjiong , Xu Dandan , Sun Maoxin , Zheng Lulu , Zhu Feng , Min Hui , Boonhok Rachasak , Ding Yan , Wen Yuhao , Chen Yicong , Li Xiaokang , Chen Yuxi , Liu Taiping , Han Jiping , Miao Jun , Fang Qiang , Cao Yaming , Tang Yun , Cui Jie , Xu Wenyue , Cui Liwang , Zhu Jin , Wong Gary , Li Jian , Jiang Lubin 
Published: December 2020

AbstractAlthough artemisinin combination therapies have succeeded in reducing the global burden of malaria, multidrug resistance of the deadliest malaria parasite, Plasmodium falciparum, is emerging worldwide. Innovative antimalarial drugs that kill all life-cycle stages of malaria parasites are urgently needed. Here, we report the discovery of the compound JX21108 with broad antiplasmodial activity against multiple life-cycle stages of malaria parasites. JX21108 was developed from chemical optimization of quisinostat, a histone deacetylase inhibitor. We identified P. falciparum histone deacetylase 1 (PfHDAC1), an epigenetic regulator essential for parasite growth and invasion, as a molecular target of JX21108. PfHDAC1 knockdown leads to the downregulation of essential parasite genes, which is highly consistent with the transcriptomic changes induced by JX21108 treatment. Collectively, our data support that PfHDAC1 is a potential drug target for overcoming multidrug resistance and that JX21108 treats malaria and blocks parasite transmission simultaneously.
Multipurpose self-configuration of programmable photonic circuits
Authors: Pérez-López Daniel , López Aitor , DasMahapatra Prometheus , Capmany José 
Published: December 2020

AbstractProgrammable integrated photonic circuits have been called upon to lead a new revolution in information systems by teaming up with high speed digital electronics and in this way, adding unique complementary features supported by their ability to provide bandwidth-unconstrained analog signal processing. Relying on a common hardware implemented by two-dimensional integrated photonic waveguide meshes, they can provide multiple functionalities by suitable programming of their control signals. Scalability, which is essential for increasing functional complexity and integration density, is currently limited by the need to precisely control and configure several hundreds of variables and simultaneously manage multiple configuration actions. Here we propose and experimentally demonstrate two different approaches towards management automation in programmable integrated photonic circuits. These enable the simultaneous handling of circuit self-characterization, auto-routing, self-configuration and optimization. By combining computational optimization and photonics, this work takes an important step towards the realization of high-density and complex integrated programmable photonics.
Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data
Authors: Nelson Christopher T. , Vasudevan Rama K. , Zhang Xiaohang , Ziatdinov Maxim , Eliseev Eugene A. , Takeuchi Ichiro , Morozovska Anna N. , Kalinin Sergei V. 
Published: December 2020

AbstractThe physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the corresponding parameters. The preexisting materials knowledge naturally folds in the Bayesian framework in the form of prior distributions, with the different order parameters forming competing (or hierarchical) models. Here, we explore the physics of the ferroelectric domain walls in BiFeO3 using this method, and derive the posterior estimates of relevant parameters. More generally, this inference approach both allows learning materials physics from experimental data with associated uncertainty quantification, and establishing guidelines for instrumental development answering questions on what resolution and information limits are necessary for reliable observation of specific physical mechanisms of interest.
Bidirectional mid-infrared communications between two identical macroscopic graphene fibres
Authors: Fang Bo , Bodepudi Srikrishna Chanakya , Tian Feng , Liu Xinyu , Chang Dan , Du Sichao , Lv Jianhang , Zhong Jie , Zhu Haiming , Hu Huan , Xu Yang , Xu Zhen , Gao Weiwei , Gao Chao 
Published: December 2020

AbstractAmong light-based free-space communication platforms, mid-infrared (MIR) light pertains to important applications in biomedical engineering, environmental monitoring, and remote sensing systems. Integrating MIR generation and reception in a network using two identical devices is vital for the miniaturization and simplification of MIR communications. However, conventional MIR emitters and receivers are not bidirectional due to intrinsic limitations of low performance and often require cryogenic cooling. Here, we demonstrate that macroscopic graphene fibres (GFs) assembled from weakly-coupled graphene layers allow room-temperature MIR detection and emission with megahertz modulation frequencies due to the persistence of photo-thermoelectric effect in millimeter-length and the ability to rapidly modulate gray-body radiation. Based on the dual-functionality of GFs, we set up a system that conducts bidirectional data transmission by switching modes between two identical GFs. The room-temperature operation of our systems and the potential to produce GFs on industrial textile-scale offer opportunities for simplified and wearable optical communications.
Learning grain boundary segregation energy spectra in polycrystals
Authors: Wagih Malik , Larsen Peter M. , Schuh Christopher A. 
Published: December 2020

AbstractThe segregation of solute atoms at grain boundaries (GBs) can profoundly impact the structural properties of metallic alloys, and induce effects that range from strengthening to embrittlement. And, though known to be anisotropic, there is a limited understanding of the variation of solute segregation tendencies across the full, multidimensional GB space, which is critically important in polycrystals where much of that space is represented. Here we develop a machine learning framework that can accurately predict the segregation tendency—quantified by the segregation enthalpy spectrum—of solute atoms at GB sites in polycrystals, based solely on the undecorated (pre-segregation) local atomic environment of such sites. We proceed to use the learning framework to scan across the alloy space, and build an extensive database of segregation energy spectra for more than 250 metal-based binary alloys. The resulting machine learning models and segregation database are key to unlocking the full potential of GB segregation as an alloy design tool, and enable the design of microstructures that maximize the useful impacts of segregation.
A meta-learning approach for genomic survival analysis
Authors: Qiu Yeping Lina , Zheng Hong , Devos Arnout , Selby Heather , Gevaert Olivier 
Published: December 2020

AbstractRNA sequencing has emerged as a promising approach in cancer prognosis as sequencing data becomes more easily and affordably accessible. However, it remains challenging to build good predictive models especially when the sample size is limited and the number of features is high, which is a common situation in biomedical settings. To address these limitations, we propose a meta-learning framework based on neural networks for survival analysis and evaluate it in a genomic cancer research setting. We demonstrate that, compared to regular transfer-learning, meta-learning is a significantly more effective paradigm to leverage high-dimensional data that is relevant but not directly related to the problem of interest. Specifically, meta-learning explicitly constructs a model, from abundant data of relevant tasks, to learn a new task with few samples effectively. For the application of predicting cancer survival outcome, we also show that the meta-learning framework with a few samples is able to achieve competitive performance with learning from scratch with a significantly larger number of samples. Finally, we demonstrate that the meta-learning model implicitly prioritizes genes based on their contribution to survival prediction and allows us to identify important pathways in cancer.
Sample spinning to mitigate polarization artifact and interstitial-vacancy imbalance in ion-beam irradiation
Authors: Ren Cui-Lan , Yang Yang , Li Yong-Gang , Huai Ping , Zhu Zhi-Yuan , Li Ju 
Published: December 2020

AbstractAccelerator-based ion-beam irradiation has been widely used to mimic the effects of neutron radiation damage in nuclear reactors. However, ion radiation is most often monodisperse in the incoming ions’ momentum direction, leading to excessive polarization in defect distribution, while the scattering under neutron irradiation is often more isotropic and has less radiation-induced polarization. Mitigation of the excess-polarization as well as the damage non-uniformity artifact might be crucial for making the simulation of neutron radiation by ion-beam radiation more realistic. In this work, a general radiation polarization theory in treating radiation as external polar stimuli is established to understand the natural material responses in different contexts, and the possibility to correct the defect polarization artifact in ion-beam irradiation. Inspired by Magic Angle Spinning in Nuclear Magnetic Resonance, we present a precise sample spinning strategy to reduce the point-defect imbalance effect in ion-beam irradiation. It can be seen that with optimized surface inclination angle and the axis of sample rotation, the vacancy-interstitial population imbalance, as well as the damage profile non-uniformity in a designated region in the target are both reduced. It is estimated that sample spinning frequency on the order of kHz should be sufficient to scramble the ion momentum monodispersity for commonly taken ion fluxes and dose rates, which is experimentally feasible.