Miracle-dz/UniFAR-FTUs huggingface dataset:
Competitive Adsorption of Pb(II), Cu(II), and Cd(II) Ions on Wheat-Residue Derived Black Carbon

The competitive adsorption properties of the heavy metal ions Pb(II), Cu(II), and Cd(II) ions in binary and ternary systems on black carbon (BC) isolated from the burning residue of wheat straw were studied in batch systems. The BC samples were characterized by Fourier transform infrared spectroscopy (FTIR). Equilibrium and kinetic adsorption data showed that the selectivity of metal ions on BC followed the order of Pb(II) > Cu(II) > Cd(II). Kinetic studies were performed, and the rate kinetics was fitted well with the pseudosecond-order model. The Freundlich adsorption isotherm was applicable to the adsorption process, and its constants were evaluated.
Particle Based Plasma Simulations for an Ion Engine Discharge Chamber

Mahalingam, Sudhakar. Ph.D. Department of Mechanical and Materials Engineering, Wright State University, 2007. Particle Based Plasma Simulation for an Ion Engine Discharge Chamber. Design of the next generation of ion engines can benefit from detailed computer simulations of the plasma in the discharge chamber. In this work a complete particle based approach has been taken to model the discharge chamber plasma.This is the first time that simplifying continuum assumptions on the particle motion have not been made in a discharge chamber model. Because of the long mean free paths of the particles in the discharge chamber continuum models are questionable. The PIC-MCC model developed in this work tracks following particles: neutrals, singly charged ions, doubly charged ions, secondary electrons, and primary electrons. The trajectories of these particles are determined using the Newton-Lorentz’s equation of motion including the effects of magnetic and electric fields. Particle collisions are determined using an MCC statistical technique. A large number of collision processes and particle wall interactions are included in the model. The magnetic fields produced by the permanent magnets are determined using Maxwell’s equations. The electric fields are determined using an approximate input electric field coupled with a dynamic determination of the electric fields caused by the charged particles. In this work inclusion of the dynamic electric field calculation is made possible by using an inflated plasma permittivity value in the Poisson solver. This allows dynamic electric field calculation with minimal computational requirements in terms of both computer memory and run time. In addition, a number of other numerical procedures such as parallel processing have been implemented to shorten the computational time. The primary results are those modeling the discharge chamber of NASA’s NSTAR ion engine at
Effect of leonurine on blood lipid in experimental hyperlipidemia rats

OBJECTIVE To study the effects of leonurine on blood lipid,hemorheology and auricle microcirculation in experimental hyperlipidemia rats.METHODS The rats were fed with the high-fat foods for 8 weeks to establish hyperlipidemia rats model,and then they were divided into Leonurine high-dose(10 mg·kg-1),middle-dose(5 mg·kg-1),low-dose(2.5 mg·kg-1),model group and Xuezhikang capsule group,and administered for 4 weeks.Then the concentration of serum triglyceride(TG),cholesterol(TC),high-density lipoprotein(HDL-C),low-density lipoprotein(LDL-C),abnormal hemorheological parameters and auricle microcirculation were assayed.RESULTS The serum levels of TG,TC and LDL-C in rats treated with Leonurine(10,5 mg·kg-1) were lowered significantly(P0.05). The abnormal hemorheological parameters were reduced and the auricle microcirculation was improved.CONCLUSION Leonurine can reduce the serum lipids and thermodynamics index while improve auricle microcirculation.
Collective wellbeing and posttraumatic growth during COVID-19: how positive psychology can help families, schools, workplaces and marginalized communities

ABSTRACT Positive psychology approaches have been shown to play a vital role in protecting mental health in times of challenge and are, therefore, important to include when studying the psychological outcomes of COVID-19. While existing research has focused on individual psychological health, this paper focuses on collective wellbeing and collective posttraumatic growth, with the aim of more clearly identifying the positive experiences and potential for positive growth for key institutions in our society during the pandemic. A range of positive psychology interventions for families, schools, workplaces, and clinical psychology are presented. The paper then considers how three broad-reaching phenomena existing in our wider society (i.e., arts and culture, eco-connection, and wellbeing literacy) can be used to boost collective wellbeing. A positive systems approach to understand civilian responses to the pandemic together with an examination of the role that positive psychology can play in supporting marginalized groups are also discussed.
Comparison between Cellulose Nanocrystal and Cellulose Nanofibril Reinforced Poly(ethylene oxide) Nanofibers and Their Novel Shish-Kebab-Like Crystalline Structures

Poly(ethylene oxide) (PEO) nanofiber mats were produced by electrospinning. Biobased cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs) as reinforcement nanofillers were also added to the polymer to produce composite nanofiber mats. The effects of the two cellulose nanofillers on the rheological properties of the PEO solutions and the microstructure, crystallization, and mechanical properties of the mats were systematically compared. The microstructural disparity between the CNCs and CNFs led to significant differences in the solution viscosity, nanofiber morphology and microstructure of the composite nanofiber mats. A unique shish-kebab-like crystalline structure was discovered in both pure and filled PEO nanofibers. Both CNCs and CNFs showed strong reinforcing effects on the nanofiber mats.
Studies on rhubarb (rhei rhizoma). VI. Isolation and characterization of stilbenes.

Nineteen stilbene derivatives (I-XIX), of which five are novel cis-stilbenes, have been obtained from a rhubarb of low quality (commercial name : ? , Imo-Daio). Based on chemical and spectroscopic evidence, these compounds have been characterized as rhapontigenin (I), rhaponticin (II), rhapontigenin 3'-O-β-D-glucopyranoside (III), rhaponticin 6"-O-gallate (IV), rhaponticin 2"-O-gallate (V), rhaponticin 2"-O-p-coumarate (VI), piceatannol (VII), piceatannol 3-O-β-D-glucopyranoside (VIII), piceatannol 3'-O-β-D-glucopyranoside (IX), piceatannol 3'-O-β-D-xylopyranoside (X), piceatannol 3-O-β-D-(6"-O-galloyl) glucopyranoside (XI), desoxyrhaponticin (XII), desoxyrhaponticin 6"-O-gallate (XIII), 3, 4', 5-trihydroxystilbene 4'-O-β-D-(6"-O-galloyl) glucopyranoside (XIV), cis-3, 3', 5-trihydroxy-4'-methoxystillbene 3-O-β-D-glucopyranoside (XV), cis-3, 3', 5-trihydroxy-4'-methoxystilbene 3-O-β-D-(6"-O-galloyl) glucopyranoside (XVI), cis-3, 5-dihydroxy-4'-methoxystibene 3-O-β-D-glucopyranoside (XVII), cis-3, 3', 5-trihydroxy-4'-methoxystilbene 3-O-β-D-(2"-O-galloyl) glucopyranoside (XVIII) and cis-3, 3', 5-trihydroxy-4'-methoxystibene (XIX).
Failed-transition outbursts in black hole low-mass X-ray binaries

Black hole low-mass X-ray binaries (BH LMXBs) evolve in a similar way during outburst. Based on the X-ray spectrum and variability, this evolution can be divided into three canonical states: low/hard, intermediate, and high/soft state. BH LMXBs evolve from the low/hard to the high/soft state through the intermediate state in some outbursts (here called ‘full outbursts’). However, in other cases, BH LMXBs undergo outbursts in which the source never reaches the high/soft state, here called ‘failed-transition outbursts’ (FT outbursts). From a sample of 56 BH LMXBs undergoing 128 outbursts, we find that 36 per cent of these BH LMXBs experienced at least one FT outburst, and that FT outbursts represent ∼33 per cent of the outbursts of the sample, showing that these are common events. We compare all the available X-ray data of full and FT outbursts of BH LMXBs from RXTE/PCA, Swift/BAT, and MAXI, and find that FT and full outbursts cannot be distinguished from their X-ray light curves, hardness–intensity diagrams, or X-ray variability during the initial 10–60 d after the outburst onset. This suggests that both types of outbursts are driven by the same physical process. We also compare the optical and infrared (O/IR) data of FT and full outbursts of GX 339−4. We found that this system is generally brighter in O/IR bands before an FT outburst, suggesting that the O/IR flux points to the physical process that later leads to a full or an FT outburst. We discuss our results in the context of models that describe the onset and evolution of outbursts in accreting X-ray binaries.
Ju l 2 02 1 Universal Velocity , Minimal Transport Coefficient , “ Collapse ” Times to Equilibrium States , and Other Bounds in Quantum Thermal Systems

Using “local uncertainty relations” in thermal many body systems, we illustrate that there exist universal speed limit (regardless of interaction range), bounds on acceleration or force/stress, acceleration or material stress rates, diffusion constant, viscosity, other transport coefficients, electromagnetic or other gauge field strengths, correlation functions of arbitrary spatio-temporal derivatives, Lyapunov exponents, thermalization times, and transition times between orthogonal states in non-relativistic quantum thermal systems, and derive analogs of the Ioffe-Regel limit. In the ~ → 0 limit, all of our bounds either diverge (e.g., our speed and acceleration limit) or vanish (as in, e.g., our viscosity and diffusion constant bounds). Our inequalities hold at all temperatures and, as corollaries, imply general power law bounds on response functions at both asymptotically high and low temperatures. Our results shed light on measurements and on how apparent nearly instantaneous effective “collapse” to an eigenstate may arise in macroscopic interacting many body quantum systems.
Sampling from Potts on random graphs of unbounded degree via random-cluster dynamics

We consider the problem of sampling from the ferromagnetic Potts and random-cluster models on a general family of random graphs via the Glauber dynamics for the random-cluster model. The random-cluster model is parametrized by an edge probability $p \in (0,1)$ and a cluster weight $q>0$. We establish that for every $q\ge 1$, the random-cluster Glauber dynamics mixes in optimal $\Theta(n\log n)$ steps on $n$-vertex random graphs having a prescribed degree sequence with bounded average branching $\gamma$ throughout the full high-temperature uniqueness regime $p<p_u(q,\gamma)$. The family of random graph models we consider includes the Erd\H{o}s--R\'enyi random graph $G(n,\gamma/n)$, and so we provide the first polynomial-time sampling algorithm for the ferromagnetic Potts model on Erd\H{o}s--R\'enyi random graphs for the full tree uniqueness regime. We accompany our results with mixing time lower bounds (exponential in the largest degree) for the Potts Glauber dynamics, in the same settings where our $\Theta(n \log n)$ bounds for the random-cluster Glauber dynamics apply. This reveals a novel and significant computational advantage of random-cluster based algorithms for sampling from the Potts model at high temperatures.
Using Adversarial Debiasing to Remove Bias from Word Embeddings

Word Embeddings have been shown to contain the societal biases present in the original corpora. Existing methods to deal with this problem have been shown to only remove superficial biases. The method of Adversarial Debiasing was presumed to be similarly superficial, but this is was not verified in previous works. Using the experiments that demonstrated the shallow removal in other methods, I show results that suggest Adversarial Debiasing is more effective at removing bias and thus motivate further investigation on the utility of Adversarial Debiasing.
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise

Annealed importance sampling (AIS) and related algorithms are highly effective tools for marginal likelihood estimation, but are not fully differentiable due to the use of Metropolis-Hastings correction steps. Differentiability is a desirable property as it would admit the possibility of optimizing marginal likelihood as an objective using gradient-based methods. To this end, we propose Differentiable AIS (DAIS), a variant of AIS which ensures differentiability by abandoning the Metropolis-Hastings corrections. As a further advantage, DAIS allows for mini-batch gradients. We provide a detailed convergence analysis for Bayesian linear regression which goes beyond previous analyses by explicitly accounting for the sampler not having reached equilibrium. Using this analysis, we prove that DAIS is consistent in the full-batch setting and provide a sublinear convergence rate. Furthermore, motivated by the problem of learning from large-scale datasets, we study a stochastic variant of DAIS that uses mini-batch gradients. Surprisingly, stochastic DAIS can be arbitrarily bad due to a fundamental incompatibility between the goals of last-iterate convergence to the posterior and elimination of the accumulated stochastic error. This is in stark contrast with other settings such as gradient-based optimization and Langevin dynamics, where the effect of gradient noise can be washed out by taking smaller steps. This indicates that annealing-based marginal likelihood estimation with stochastic gradients may require new ideas.
Determining a nonlinear hyperbolic system with unknown sources and nonlinearity

This paper is devoted to some inverse boundary problems associated with a time‐dependent semilinear hyperbolic equation, where both nonlinearity and sources (including initial displacement and initial velocity) are unknown. It is shown in several generic scenarios that one can uniquely determine the nonlinearity and/or the sources by using passive or active boundary observations. In order to exploit the nonlinearity and the sources simultaneously, we develop a new technique, which combines the observability for linear wave equations and an approximation property with higher order linearization for the semilinear hyperbolic equation.
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision

Recent work has shown success in incorporating pre-trained models like BERT to improve NLP systems. However, existing pre-trained models lack of causal knowledge which prevents today's NLP systems from thinking like humans. In this paper, we investigate the problem of injecting causal knowledge into pre-trained models. There are two fundamental problems: 1) how to collect various granularities of causal pairs from unstructured texts; 2) how to effectively inject causal knowledge into pre-trained models. To address these issues, we extend the idea of CausalBERT from previous studies, and conduct experiments on various datasets to evaluate its effectiveness. In addition, we adopt a regularization-based method to preserve the already learned knowledge with an extra regularization term while injecting causal knowledge. Extensive experiments on 7 datasets, including four causal pair classification tasks, two causal QA tasks and a causal inference task, demonstrate that CausalBERT captures rich causal knowledge and outperforms all pre-trained models-based state-of-the-art methods, achieving a new causal inference benchmark.
Hydrogenation of Nitrile and Olefinic Groups in Butadiene Rubbers

Nowadays, traditional diene-based polymers cannot meet the demand for robust elastomers in many industries. Acrylonitrile butadiene rubber (NBR) is a widely used diene-based polymer as an oilresistant elastomer and is produced via copolymerization of acrylonitrile (AN or ACN) and butadiene (BD). When dealing with aggressive environments, NBR’s performance decreases rapidly due to the residual carbon-carbon double bonds in the polymer backbone. By selectively hydrogenating these unsaturated bonds to yield its more stable counterpart, hydrogenated NBR (HNBR), the mechanical, thermo-oxidative and chemical resistant properties of a material are greatly improved. The ACN content of NBR and HNBR also determines a number of properties including oil and solvent resistance, compatibility with polar solvent and abrasion resistance etc. HNBR with lower ACN content can be cured without sulfur which improves heat resistance and is much more environmentally friendly. In the present research project, a rhodium hydrido complex was screened and synthesized; a corresponding catalytic system was successfully established to produce HNBR with a certain amount of ACN. It is worthwhile to point out that this thesis is the first development in establishing a system that is able to reduce nitrile content of the macromolecular polymers (NBR and HNBR), and to achieve tandem hydrogenation of both nitrile groups and olefinic groups in the macromolecular polymer (NBR). In both HNBR and NBR systems, the nitrile content can be reduced from 40% to less than 10% within 5 hours at 60C and 500 psig H2. The nitrile groups have been converted to primary amines without any side products such as the formation of secondary amines. A possible mechanism for nitrile reduction has been proposed for the first time. The causes for gel formation during nitrile reduction have been investigated and a possible mechanism is proposed. Several additives have been tested and some of them are found to be effective to slow down or terminate gel formation, and tryphenylphosphine (TPP) was found to be the most effective additive. In the NBR system, tandem hydrogenation of nitrile and olefinic groups has been successfully achieved. The nitrile reduction process is similar to that of the HNBR system. The olefinic groups were reduced from 100% to lower than 5% simultaneously under the same reaction conditions. A possible mechanism for tandem hydrogenation has also been proposed for the first time.
Fast convergence of generalized forward-backward algorithms for structured monotone inclusions

In this paper, we develop rapidly convergent forward-backward algorithms for computing zeroes of the sum of finitely many maximally monotone operators. A modification of the classical forward-backward method for two general operators is first considered, by incorporating an inertial term (closed to the acceleration techniques introduced by Nesterov), a constant relaxation factor and a correction term. In a Hilbert space setting, we prove the weak convergence to equilibria of the iterates (xn), with worst-case rates of o(n) in terms of both the discrete velocity and the fixed point residual, instead of the classical rates of O(n) established so far for related algorithms. Our procedure is then adapted to more general monotone inclusions and a fast primal-dual algorithm is proposed for solving convex-concave saddle point problems.
Long-term tillage and synthetic fertilization affect soil functioning and crop yields in a corn—soybean rotation in eastern Canada

Ziadi, N. , Angers, D. A. , Gagnon, B. , Lalande, R. , Morel, C. , Rochette, P. and Chantigny, M. H. 2014. Long-term tillage and synthetic fertilization affect soil functioning and crop yields in a corn-soybean rotation in eastern Canada. Can. J. Soil Sci. 94: 365-376. Adoption of conservation practices can induce beneficial changes to soil properties and related crop yields in which magnitude varies according to soil and climatic conditions but usually increases with time. A long-term field experiment was initiated in 1992 at L'Acadie in southern Quebec on a clay loam soil to evaluate the effect of tillage [mouldboard plow (MP) vs. conservation (CT)], synthetic N fertilization (0, 80, and 160 kg N ha-1) and synthetic P fertilization (0, 17.5, and 35 kg P ha-1) on soil functioning and grain yields of a corn-soybean rotation. Soil tillage was performed every year while synthetic fertilizers were applied only to the corn. Results obtained 12 to 20 yr after initiation of the study indicated that CT enhanced organic C accumulation, NO3-N, P and K availability, microbial biomass and activity, and microbial community structure in the upper soil layer, likely due to leaving crop residues at the soil surface. The MP practice resulted in greater organic C content deeper, near the bottom of the plow layer, which promoted soil microbial activity at that depth. However, soil N2O emissions were not affected by tillage. The N and P fertilization increased the availability of these nutrients, but had no significant effect on the soil microbial biomass, activity, and structure. Linear relationships were established between soil available P and cumulative P budgets obtained under MP or 0 kg P ha-1 under CT. Crop yields varied by year in this study but on average, MP yielded 10% more corn and 13% more soybeans than CT. Corn yield increased linearly with added synthetic N each year, whereas soybean yield was little affected by residual N, and both crops did not respond to fertilizer P. Response to N fertilization did not differ due to tillage or P. Despite higher costs associated with plowing, the profitability of MP was greater than CT on this clay loam soil due to greater yields. Specialized management practices (e.g., delayed planting, better herbicide selection, fall cover crop, in-row tillage) might help to improve CT performance on these cool, humid fine-textured soils.
Variations of the Martian Thermospheric Gravity-wave Activity during the Recent Solar Minimum as Observed by MAVEN

Atmospheric gravity (buoyancy) waves (GWs) are of great importance for the energy and momentum budget of all planetary atmospheres. Propagating upward waves carry energy and momentum from the lower atmosphere to thermospheric altitudes and re-distribute them there. On Mars, GWs dominate the variability of the thermosphere and ionosphere. We provide a comprehensive climatology of Martian thermospheric GW activity at solar minimum (end of solar cycle 24) inferred from measurements by the Neutral Gas and Ions Mass Spectrometer on board the Mars Atmosphere and Volatile EvolutioN. The results are compared and interpreted using a one-dimensional spectral nonlinear GW model. Monthly mean GW activity varies strongly as a function of altitude (150–230 km) between 6% and 25%, reaching a maximum at ∼170 km. GW activity systematically exhibits a local time variability with nighttime values exceeding those during daytime, in accordance with previous studies. The analysis suggests that the day–night difference is primarily caused by a competition between dissipation due to molecular diffusion and wave growth due to decreasing background density. Thus, the convective instability mechanism is likely to play a less important role in limiting GW amplitudes in the upper thermosphere, which explains their local time behavior.
Finite-memory strategies in two-player infinite games

We study infinite two-player win/lose games $(A,B,W)$ where $A,B$ are finite and $W \subseteq (A \times B)^\omega$. At each round Player 1 and Player 2 concurrently choose one action in $A$ and $B$, respectively. Player 1 wins iff the generated sequence is in $W$. Each history $h \in (A \times B)^*$ induces a game $(A,B,W_h)$ with $W_h := \{\rho \in (A \times B)^\omega \mid h \rho \in W\}$. We show the following: if $W$ is in $\Delta^0_2$ (for the usual topology), if the inclusion relation induces a well partial order on the $W_h$'s, and if Player 1 has a winning strategy, then she has a finite-memory winning strategy. Our proof relies on inductive descriptions of set complexity, such as the Hausdorff difference hierarchy of the open sets. Examples in $\Sigma^0_2$ and $\Pi^0_2$ show some tightness of our result. Our result can be translated to games on finite graphs: e.g. finite-memory determinacy of multi-energy games is a direct corollary, whereas it does not follow from recent general results on finite memory strategies.