Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydration, Ion Distribution, and Ionic Network Formation in Sulfonated Poly(arylene ether sulfones)

Britannia Vondrasek, Chengyuan Wen, 2 Shengfeng Cheng, 2, 3, ∗ Judy S. Riffle, 4 and John J. Lesko 3 Macromolecules Innovation Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA Department of Physics and Center for Soft Matter and Biological Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA Department of Chemistry, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA (Dated: January 15, 2021)
Plasma flows and sound-speed perturbations in the average supergranule

Context. Supergranules create a peak in the spatial spectrum of photospheric velocity features. Even though they have some properties of convection cells, their origin is still being debated in the literature. The time–distance helioseismology constitutes a method that is suitable for investigating the deep structure of supergranules. Aims. Our aim is to construct the model of the flows in the average supergranular cell using fully consistent time–distance inverse methodology. Methods. We used the Multi-Channel Subtractive Optimally Localised Averaging inversion method with regularisation of the cross-talk. We combined the difference and the mean travel-time averaging geometries. We applied this methodology to travel-time maps averaged over more than 104 individual supergranular cells. These cells were detected automatically in travel-time maps computed for 64 quiet days around the disc centre. The ensemble averaging method allows us to significantly improve the signal-to-noise ratio and to obtain a clear picture of the flows in the average supergranule. Results. We found near-surface divergent horizontal flows which quickly and monotonously weakened with depth; they became particularly weak at the depth of about 7 Mm, where they even apparently switched sign. The amplitude of the ‘reversed’ flow was comparable to the background flows. The inverted vertical flows and sound-speed perturbations were spoiled by unknown systematic errors. To learn about the vertical component, we integrated the continuity equation from the surface. The derived estimates of the vertical flow depicted a sub-surface increase from about 5 m s−1 at the surface to about 35 m s−1 at the depth of about 3 Mm followed by a monotonous decrease to greater depths. The vertical flow remained positive (an upflow) and became indistinguishable from the background at the depth of about 15 Mm. We further detected a systematic flow in the longitudinal direction. The course of this systematic flow with depth agrees well with the model of the solar rotation in the sub-surface layers.
Cluster synchronization on hypergraphs

We study cluster synchronization (a type of synchronization where different groups of oscillators in the system follow distinct synchronized trajectories) on hypergraphs, where hyperedges correspond to higher order interactions between the nodes. Specifically, we focus on how to determine admissible synchronization patterns from the hypergraph structure by clustering its nodes based on the input they receive from the rest of the system, and how the hypergraph structure together with the pattern of cluster synchronization can be used to simplify the stability analysis. We formulate our results in terms of external equitable partitions but show how symmetry considerations can also be used. In both cases, our analysis requires considering the partitions of hyperedges into edge clusters that are induced by the node clusters. This formulation in terms of node and edge clusters provides a general way to organize the analysis of dynamical processes on hypergraphs. Our analysis here enables the study of detailed patterns of synchronization on hypergraphs beyond full synchronization and extends the analysis of cluster synchronization to beyond purely dyadic interactions.
Thermal conduction in two-dimensional complex plasma layers

A simple vibrational model of heat transfer in two-dimensional (2D) fluids relates the heat conductivity coefficient to the longitudinal and transverse sound velocities, specific heat, and the mean interatomic separation. This model is demonstrated not to contradict the available experimental and numerical data on heat transfer in 2D complex plasma layers. Additionally, the heat conductivity coefficient of a 2D one-component plasma with a logarithmic interaction is evaluated.
COMPARISON OF EXTRACTANTS USED FOR EVALUATING THE BIOAVAILABILITY OF SOIL P AND K

Numerous extractants including strong and weak acids and their salts, alkaline solutions, water etc. are used to evaluate the phosphorus and potassium status of soils. In our study, two weak extractants, hot water[1] and ammonium lactate[2] were used for the analyses. Hot water percolation (HWP) procedure developed in Hungary, seems to be a promising extraction methodology for rapid soil tests. The main objective of our study was to compare the results obtained with the two extraction procedures and to evaluate their use in estimating the bioavailability of soil P (Hw-P and AL-P mg kg−1) and K (Hw-K and AL-K mg kg−1) in different soil types. Soil samples were collected from experiments carried out with several NPK fertilizer sources applied in different treatment combinations. Four soil types (an Eutric cambisol in FAO taxonomy and Ortic Eutrochrept in USA taxonomy), a Haplic luvisol (FAO), Typic Hapludalf, a Stagnic Luvisol (FAO), Typic Endoaqualf and a Chromic Luvisol (FAO), Arenic Hapludalf, respectively, were used in the study. Main characteristics of experimental soils showed considerable differences. Results obtained with the two extractants were compared to each other as well as to amounts of P and K (Pup and Kup, respectively) removed by young corn and sunflower plants. Nutrient uptake of plants showed a dramatic increase compared to the control with the application of fertilizer sources not causing acid forming reactions in soils. From the results of statistical analyses, it was evident that a good correlation was found between the values of soil P and K obtained with the two extractants (“r” values ranged between 0.974 and 0.612 for P and between 0.761 and 0.04 for K, respectively). Generally, a better relationship could be observed between Hw-P and AL-P values than Hw-K and AL-K values. Similar tendencies were found when plant P and K removal was correlated with soil P and K contents extracted either with hot water or AL solution. Plant removal of P showed a better correlation with AL-extractable phosphorus. Among soils, closest relationships were observed between plant removal and soil P contents using the two extractants on the Orthic Eutrochrept (r=0.925 and 0.932, respectively). On the other hand, a better correlation was obtained between Hw-K values and K removal for the Typic Hapludalf as well as for the Arenic Hapludalf than between the soil P extracted by AL solution and P removal by young plants. For the wider understanding of dominant factors influencing the effectiveness of these extractants, especially for HWP, and their relationships with plant removal in a variety of soil types in Hungary, further studies are needed.
Heavy metals in Phalaris arundinacea growing in a constructed wetland treating municipal sewage

Constructed wetlands with horizontal subsurface horizontal flow are commonly used for treatment of municipal sewage and are well monitored for removal of organics, suspended solids, nutrients and bacteria. However, the information on removal of heavy metals and their sequestration in plants growing there is very limited. The present study deals with sequestration of six heavy metals in Phalaris arundinacea growing in a constructed wetland treating municipal sewage in the Czech Republic during the period 2004–2008. The aboveground biomass of Phalaris arundinacea is higher that the average Phalaris biomass in other Czech constructed wetlands and also as compared to natural stands. Contrary to natural stands, the root to shoot (R/S) ratio is lower than 1.0 and varied between 0.34 and 0.68 with a mean value of 0.49. For all studied heavy metals the concentrations are the highest in the roots while in other parts, i.e. leaves, stems, rhizomes and flowers, the concentrations usually do not differ significantly. Because of low belowground biomass, the standings stocks are higher aboveground for Zn, Cd, Pb and Cu with copper standing stock being significantly higher than belowground. On the other hand, for Cr and Ni the belowground standing stocks were significantly higher than aboveground because of very high Cr and Ni concentrations in the roots. In most cases the concentrations found in our study are within the order of magnitude as compared to results from other constructed wetlands and natural stands. Heavy metal aboveground standing stocks represented between 1.6% (Cr) and 15.1% (Cd) of the annual metals inflow with an average value of 6.5%. The amount of heavy metals sequestered in the aboveground biomass accounted for between 3.7% (Zn) and 38.4% (Cd) of the heavy metal removal in the filtration beds with an average value of 13.2%.
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation

Deep ensembles perform better than a single network thanks to the diversity among their members. Recent approaches regularize predictions to increase diversity; however, they also drastically decrease individual members' performances. In this paper, we argue that learning strategies for deep ensembles need to tackle the trade-off between ensemble diversity and individual accuracies. Motivated by arguments from information theory and leveraging recent advances in neural estimation of conditional mutual information, we introduce a novel training criterion called DICE: it increases diversity by reducing spurious correlations among features. The main idea is that features extracted from pairs of members should only share information useful for target class prediction without being conditionally redundant. Therefore, besides the classification loss with information bottleneck, we adversarially prevent features from being conditionally predictable from each other. We manage to reduce simultaneous errors while protecting class information. We obtain state-of-the-art accuracy results on CIFAR-10/100: for example, an ensemble of 5 networks trained with DICE matches an ensemble of 7 networks trained independently. We further analyze the consequences on calibration, uncertainty estimation, out-of-distribution detection and online co-distillation.
Dissolution and Deagglomeration of Silicon Nitride in Aqueous Medium

Silicon nitride undergoes hydrolysis and dissolution when subjected to an aqueous environment. Molecular dynamics simulations suggest that hydrolysis proceeds through nucleophilic attack of water with the formation of an intermediate molecular complex involving a pentacoordinated silicon. We found that the dissolution of an oxidized silicon nitride powder resembles that of silica; the dissolution rate could be described using a simple kinetic equation with a dissolution activation energy of 52 kJ·mol−1. The deagglomeration of a fine silicon nitride powder under mild agitation was evaluated; we show that the peptization kinetics at room temperature is dominated by the breakup of particle–particle bonds due to hydrodynamic friction and cluster attrition. For breakup of hard agglomerates of small particles the dissolution of interparticle necks will play an important role.
VLA Resolves Unexpected Radio Structures in the Perseus Cluster of Galaxies

We present new deep, high-resolution, 1.5 GHz observations of the prototypical nearby Perseus galaxy cluster from the Karl G. Jansky Very Large Array. We isolate for the first time the complete tail of radio emission of the bent-jet radio galaxy NGC 1272, which had been previously mistaken to be part of the radio mini-halo. The possibility that diffuse radio galaxy emission contributes to mini-halo emission may be a general phenomenon in relaxed cool-core clusters, and should be explored. The collimated jets of NGC 1272 initially bend to the west, and then transition eastward into faint, 60 kpc long extensions with eddy-like structures and filaments. We suggest interpretations for these structures that involve bulk motions of intracluster gas, the galaxy’s orbit in the cluster including projection effects, and the passage of the galaxy through a sloshing cold front. Instabilities and turbulence created at the surface of this cold front and in the turbulent wake of the infalling host galaxy most likely play a role in the formation of the observed structures. We also discover a series of faint rings, southeast of NGC 1272, which are a type of structure that has never been seen before in galaxy clusters.
An underlying universal pattern in galaxy halo magnetic fields

Magnetic fields in galaxy halos are in general very difficult to observe. Most recently, the Continuum HAlos in Nearby Galaxies – an EVLA Survey (CHANG-ES) Collaboration investigated the radio halos of 35 nearby edge-on spiral galaxies in detail and detected large-scale magnetic fields in 16 of them. We used the CHANG-ES radio polarization data to create rotation measure maps for all galaxies in the sample and stack them with the aim of amplifying any underlying universal toroidal magnetic field pattern in the halo above and below the disk of the galaxy. We discovered a large-scale magnetic field in the central region of the stacked galaxy profile, which is attributable to an axial electric current that universally outflows from the center, both above and below the plane of the disk. A similar symmetry-breaking has also been observed in astrophysical jets, but never before in galaxy halos. This is an indication that galaxy halo magnetic fields are probably not generated by pure magnetohydrodynamic processes in the central regions of galaxies. One such promising physical mechanism is the Cosmic Battery operating in the innermost accretion disk around the central supermassive black hole. We anticipate that our discovery will stimulate a more general discussion on the origin of astrophysical magnetic fields.
Performance Enhancement by Blending an Electron Acceptor in TiO2/polyphenylenevinylene/Au Solid-state Solar Cells

When an electron acceptor, [2-[2-[4-(dimethylamino)phenyl]ethenyl]-6-methyl-4H-pyran-4-ylidene]propanedinitrile (DCM) was blended into poly[2-methoxy-5-(2′-ethylenehexyloxy)-1,4-phenylenevinylene] .
AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attention

Pedestrian trajectory prediction is a critical yet challenging task especially for crowded scenes. We suggest that introducing an attention mechanism to infer the importance of different neighbors is critical for accurate trajectory prediction in scenes with varying crowd size. In this work, we propose a novel method, AVGCN, for trajectory prediction utilizing graph convolutional networks (GCN) based on human attention (A denotes attention, V denotes visual field constraints). First, we train an attention network that estimates the importance of neighboring pedestrians, using gaze data collected as subjects perform a bird’s eye view crowd navigation task. Then, we incorporate the learned attention weights modulated by constraints on the pedestrian’s visual field into a trajectory prediction network that uses a GCN to aggregate information from neighbors efficiently. AVGCN also considers the stochastic nature of pedestrian trajectories by taking advantage of variational trajectory prediction. Our approach achieves state-of-the-art performance on several trajectory prediction benchmarks, and the lowest average prediction error over all considered benchmarks.
Field-scale Bioremediation of soil contaminated with crude oil

Field-scale remediation of oil-contaminated soils from the Liaohe Oil Fields in China was examined using composting biopiles in windrow technology. Micronutrient-enriched chicken excrement and rice husk were applied as nutrition and a bulking agent. The lipase activities of indigenous micro-organisms were analyzed, and three indigenous fungi with high lipase activities was identified. An inoculum consisting of the three indigenous fungi and one introduced (exotic) fungus was applied to four different types of oil-contaminated soils. The results showed that the inoculum of indigenous fungi increased both the total colony-forming units (TCFU) and increased the rate of degradation of total petroleum hydrocarbons (TPH) in all contaminated soils but at different rates. In sharp contrast to other studies, the introduction of exotic micro-organisms did not improve the remediation, and suggests that inoculation of oil-contaminated sites with nonindigenous species is likely to fail. On the other hand, indigenous genera of microbes were found to be very effective in increasing the rate of degradation of TPH. The degradation of TPH was mainly controlled by the compositions of aromatic hydrocarbons and asphaltene and resin. Between 38 to 57% degradation of crude oils (with densities ranging from 25,800 to 77,200 mg/kg dry weight) in contaminated soils was achieved after 53 days of operation. The degradation patterns followed typical first-order reactions. We demonstrate that the construction and operation of field-scale composting biopiles in windrows with passive aeration is a cost-effective bioremediation technology.
Relativistic effects of rotation in $\gamma$-ray pulsars -- Invited Review

In this paper we consider relativistic effects of rotation in the magnetospheres of γ-ray pulsars. The paper reviews the progress achieved in this field during the last three decades. For this purpose we examine direct centrifugal acceleration of particles and corresponding limiting factors: constraints due to the curvature radiation and the inverse Compton scattering of electrons against soft photons. Based on the obtained results generation of parametrically excited Langmuir waves and the corresponding Landau-Langmuir-centrifugal drive is studied.
On the logistic equation for the fractional p‐Laplacian

We consider a Dirichlet problem for a nonlinear, nonlocal equation driven by the degenerate fractional p‐Laplacian, with a logistic‐type reaction depending on a positive parameter. In the subdiffusive and equidiffusive cases, we prove existence and uniqueness of the positive solution when the parameter lies in convenient intervals. In the superdiffusive case, we establish a bifurcation result. A new strong comparison result, of independent interest, plays a crucial role in the proof of such bifurcation result.
BiGCN: A Bi-directional Low-Pass Filtering Graph Neural Network

Graph convolutional networks (GCNs) have achieved great success on graph-structured data. Many graph convolutional networks can be thought of as low-pass filters for graph signals. In this paper, we propose a more powerful graph convolutional network, named BiGCN, that extends to bidirectional filtering. Specifically, we not only consider the original graph structure information but also the latent correlation between features, thus BiGCN can filter the signals along with both the original graph and a latent feature-connection graph. Compared with most existing GCNs, BiGCN is more robust and has powerful capacities for feature denoising. We perform node classification and link prediction in citation networks and co-purchase networks with three settings: noise-rate, noise-level and structure-mistakes. Extensive experimental results demonstrate that our model outperforms the state-of-the-art graph neural networks in both clean and artificially noisy data.
No-go Theorem for Acceleration in the Hyperbolic Plane

In recent years there has been significant effort to adapt the key tools and ideas in convex optimization to the Riemannian setting. One key challenge has remained: Is there a Nesterovlike accelerated gradient method for geodesically convex functions on a Riemannian manifold? Recent work has given partial answers and the hope was that this ought to be possible. Here we dash these hopes. We prove that in a noisy setting, there is no analogue of accelerated gradient descent for geodesically convex functions on the hyperbolic plane. Our results apply even when the noise is exponentially small. The key intuition behind our proof is short and simple: In negatively curved spaces, the volume of a ball grows so fast that information about the past gradients is not useful in the future. Department of Mathematics, Massachusetts Institute of Technology. Email: luh@mit.edu. This work was supported in part by a Fannie and John Hertz Foundation Fellowship. Department of Mathematics, Massachusetts Institute of Technology. Email: moitra@mit.edu. This work was supported in part by a Microsoft Trustworthy AI Grant, NSF CAREER Award CCF-1453261, NSF Large CCF1565235, a David and Lucile Packard Fellowship, an Alfred P. Sloan Fellowship and an ONR Young Investigator Award. 1 ar X iv :2 10 1. 05 65 7v 1 [ m at h. O C ] 1 4 Ja n 20 21
Optimal Energy Shaping via Neural Approximators

We introduce optimal energy shaping as an enhancement of classical passivity-based control methods. A promising feature of passivity theory, alongside stability, has traditionally been claimed to be intuitive performance tuning along the execution of a given task. However, a systematic approach to adjust performance within a passive control framework has yet to be developed, as each method relies on few and problem-specific practical insights. Here, we cast the classic energy-shaping control design process in an optimal control framework; once a task-dependent performance metric is defined, an optimal solution is systematically obtained through an iterative procedure relying on neural networks and gradient-based optimization. The proposed method is validated on state-regulation tasks.
Game-based Pricing and Task Offloading in Mobile Edge Computing Enabled Edge-Cloud Systems

As a momentous enabling of the Internet of things (IoT), mobile edge computing (MEC) provides IoT mobile devices (MD) with powerful external computing and storage resources. However, a mechanism addressing distributed task offloading and price competition for the open exchange marketplace has not been established properly, which has become a huge obstacle to MEC's application in the IoT market. In this paper, we formulate a distributed mechanism to analyze the interaction between OSPs and IoT MDs in the MEC enabled edge-cloud system by appling multi-leader multi-follower two-tier Stackelberg game theory. We first prove the existence of the Stackelberg equilibrium, and then we propose two distributed algorithms, namely iterative proximal offloading algorithm (IPOA) and iterative Stackelberg game pricing algorithm (ISPA). The IPOA solves the follower non-cooperative game among IoT MDs and ISPA uses backward induction to deal with the price competition among OSPs. Experimental results show that IPOA can markedly reduce the disutility of IoT MDs compared with other traditional task offloading schemes and the price of anarchy is always less than 150\%. Besides, results also demonstrate that ISPA is reliable in boosting the revenue of OSPs.