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At least 973 records · Page 54

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here, in this work, we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO 2 exchange, soil CO 2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC i ), C translocation (dC i ), and the biomass production efficiency (BPE i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC i and BPE i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil–plant–climate interactions.

54 ENVIRONMENTAL SCIENCES↗

Comparison of reduced and sulfided C o M o/γ‐ A l 2 O 3 catalyst on hydroprocessing of pretreated bio‐oil in a continuous packed‐bed reactor

Pretreated bio‐oil was hydroprocessed with conventional sulfided CoMo/γ‐Al 2 O 3 catalyst in a continuous packed‐bed reactor. Hydroprocessing experiments were performed at a temperature of 350 to 400°C, 1500 psig hydrogen pressure, using a hydrogen flow rate of 500 mL/min at a liquid hourly space velocity of 0.2 h −1 . The results from sulfided catalytic experiments were compared with our prior studies on hydroprocessing pretreated bio‐oil with reduced CoMo/γ‐Al 2 O 3 catalyst. sulfided CoMo/γ‐Al 2 O 3 catalyst demonstrated higher catalytic activity and resulted in increased hydrocarbon fraction yields. Moreover, the quality of the hydrocarbon fraction, as determined by the acid value, higher heating value, and water content analysis, also improved. Sulfided CoMo/γ‐Al 2 O 3 catalyst produced a hydrocarbon fraction having a higher heating value of 44.4 MJ/kg, acid value of 0.5 mg KOH/g oil, and a total water content of 0.1%. Use of sulfided catalyst for hydroprocessing pretreated bio‐oil decreased the oxygen content from 47.8 wt % in the pretreated bio‐oil to nondetectable limits (∼0 wt %) in the hydrocarbon fraction. The hydrocarbon fraction was also analyzed by detailed hydrocarbon analysis and simulated distillation. © 2014 American Institute of Chemical Engineers Environ Prog, 34: 1174–1179, 2015

Parapati, Divya R.↗

Comparison of multigrid algorithms for high‐order continuous finite element discretizations

Summary We present a comparison of different multigrid approaches for the solution of systems arising from high‐order continuous finite element discretizations of elliptic partial differential equations on complex geometries. We consider the pointwise Jacobi, the Chebyshev‐accelerated Jacobi, and the symmetric successive over‐relaxation smoothers, as well as elementwise block Jacobi smoothing. Three approaches for the multigrid hierarchy are compared: (1) high‐order h ‐multigrid, which uses high‐order interpolation and restriction between geometrically coarsened meshes; (2) p ‐multigrid, in which the polynomial order is reduced while the mesh remains unchanged, and the interpolation and restriction incorporate the different‐order basis functions; and (3) a first‐order approximation multigrid preconditioner constructed using the nodes of the high‐order discretization. This latter approach is often combined with algebraic multigrid for the low‐order operator and is attractive for high‐order discretizations on unstructured meshes, where geometric coarsening is difficult. Based on a simple performance model, we compare the computational cost of the different approaches. Using scalar test problems in two and three dimensions with constant and varying coefficients, we compare the performance of the different multigrid approaches for polynomial orders up to 16. Overall, both h ‐multigrid and p ‐multigrid work well; the first‐order approximation is less efficient. For constant coefficients, all smoothers work well. For variable coefficients, Chebyshev and symmetric successive over‐relaxation smoothing outperform Jacobi smoothing. While all of the tested methods converge in a mesh‐independent number of iterations, none of them behaves completely independent of the polynomial order. When multigrid is used as a preconditioner in a Krylov method, the iteration number decreases significantly compared with using multigrid as a solver. Copyright © 2015 John Wiley & Sons, Ltd.

Sundar, Hari↗

A review of the fabrication methods and mechanical behavior of continuous thermoplastic polymer fiber–thermoplastic polymer matrix composites

Abstract Thermoplastic polymer fiber–thermoplastic polymer matrix composites (PPCs or PRFPs), often recognized as self‐reinforced or single polymer composites, are potential candidates for future advanced polymer composites because of various advantages ( e.g., recyclability, formability, low‐cost, ultra‐lightweight, environmental friendliness, etc.). The manufacturability and mechanical behavior of these composites compared to conventional carbon‐/glass‐/aramid‐fiber‐reinforced polymers is of great interest to the composites community, but there are a limited number of studies in this area. To this end, this paper reviewed fabrication methods with different processing parameters and mechanical behavior of uni‐/multi‐directional thermoplastic PPCs featuring continuous thermoplastic polymer fibers from limited data in the literature. It was shown that most specific behaviors (normalized by density) of these materials in various loading conditions (e.g., quasi‐static tension/shear/flexure, tension‐tension fatigue, and out‐of‐plane impacting, etc.) are comparable to or better than glass‐/aramid‐fiber‐reinforced polymers. Particularly, the specific ductility in the foregoing conditions outperforms all the carbon‐/glass‐/aramid‐fiber‐reinforced polymers. Thermoplastic PPCs with remarkable performance can be achieved through several uncomplicated methods (e.g., film stacking, hot compaction, powder and solution impregnations, matrix infusion and injection molding, additive manufacturing, etc.), which have some similarities to the methods used for carbon‐/glass‐/aramid‐fiber‐reinforced polymers. Moreover, several opportunities and challenging problems of thermoplastic PPCs were summarized at the end of this review paper. Efficient solutions may require countless efforts in the composites community to further strengthen the performance and understanding of thermoplastic PPCs for wide applications in various engineering fields in the future.

36 MATERIALS SCIENCE↗

Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions

Abstract The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical, and experimental explorations will most likely be required to understand its power. There have been different algorithms proposed to exploit the probabilistic nature of variational quantum circuits for generative modeling. In this paper, a hybrid architecture for quantum generative adversarial networks (QGANs) is employed and their robustness in the presence of noise is studied. A simple way of adding different types of noise to the quantum generator circuit is devised, and the noisy hybrid QGANs (HQGANs) are simulated numerically to learn continuous probability distributions, and to show that the performance of HQGANs remains unaffected. The effect of different parameters on the training time is also investigated to reduce the computational scaling of the algorithm and simplify its deployment on a quantum computer. The training on Rigetti's Aspen‐4‐2Q‐A quantum processing unit is then performed, and the results from the training are presented. The authors' results pave the way for experimental exploration of different quantum machine learning algorithms on noisy intermediate‐scale quantum devices.

Anand, Abhinav↗

Decoding α-MoC 1− x Nanoparticle Formation in Continuous Flow via Machine Learning

Molybdenum carbide nanoparticles (α-MoC 1−x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1−x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitoring and machine learning (ML)-based analysis to quantify precursor conversion and product formation in real time. A multilayer perceptron ML model was found to accurately deconvolute complex, nonlinear spectral patterns, enabling identification of a two-step reaction pathway, involving precursor conversion to an amorphous intermediate followed by intraparticle crystallization to α-MoC 1−x NPs, with the first step being rate limiting. Ex situ small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) validation confirm the predicted concentration profiles and crystallization behavior. This integrated approach showcases how ML can empower insights into NP nucleation and growth, paving the way for self-driving, flow-based platforms for NP synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuous Flavor Symmetries and the Stability of Asymmetric Dark Matter

Generically, the asymmetric interactions in asymmetric dark matter (ADM) models could lead to decaying DM. We show that, for ADM that carries nonzero baryon number, continuous flavor symmetries that generate the flavor structure in the quark sector also imply a looser lower bound on the mass scale of the asymmetric mediators between the dark and visible sectors. Furthermore, the mediators for B = 2 ADM that can produce a signal in the future indirect dark matter searches can thus also be searched for at the LHC. For two examples of the mediator models, with either the MFV or Froggatt-Nielsen flavor breaking pattern, we derive the FCNC constraints and discuss the search strategies at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pileup and Infrared Radiation Annihilation (PIRANHA): a paradigm for continuous jet grooming

Jet grooming is an important strategy for analyzing relativistic particle collisions in the presence of contaminating radiation. Most jet grooming techniques introduce hard cutoffs to remove soft radiation, leading to discontinuous behavior and associated experimental and theoretical challenges. In this paper, we introduce Pileup and Infrared Radiation Annihilation (Piranha), a paradigm for continuous jet grooming that overcomes the discontinuity and infrared sensitivity of hard-cutoff grooming procedures. We motivate Piranha from the perspective of optimal transport and the Energy Mover’s Distance and review Apollonius Subtraction and Iterated Voronoi Subtraction as examples of Piranha-style grooming. We then introduce a new tree-based implementation of Piranha, Recursive Subtraction, with reduced computational costs. Finally, we demonstrate the performance of Recursive Subtraction in mitigating sensitivity to soft distortions from hadronization and detector effects, and additive contamination from pileup and the underlying event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic Games for Continuous-Time Jump Processes Under Finite-Horizon Payoff Criterion

In this paper we study two-person nonzero-sum games for continuous-time jump processes with the randomized history-dependent strategies under the finite-horizon payoff criterion. The state space is countable, and the transition rates and payoff functions are allowed to be unbounded from above and from below. Under the suitable conditions, we introduce a new topology for the set of all randomized Markov multi-strategies and establish its compactness and metrizability. Then by constructing the approximating sequences of the transition rates and payoff functions, we show that the optimal value function for each player is a unique solution to the corresponding optimality equation and obtain the existence of a randomized Markov Nash equilibrium. Furthermore, we illustrate the applications of our main results with a controlled birth and death system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach

In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ppb-level mid-infrared ethane detection based on three measurement schemes using a 3.34-μm continuous-wave interband cascade laser

A ppb-level mid-infrared ethane (C 2 H 6 ) sensor was developed using a continuous-wave, thermoelectrically cooled, distributed feedback interband cascade laser emitting at 3.34 μm and a miniature dense patterned multipass gas cell with a 54.6-m optical path length. The performance of the sensor was investigated using two different techniques based on the tunable interband cascade laser: direct absorption spectroscopy (DAS) and second-harmonic wavelength modulation spectroscopy (2f-WMS). Three measurement schemes, DAS, WMS and quasi-simultaneous DAS and WMS, were realized based on the same optical sensor core. A detection limit of ~7.92 ppbv with a precision of ±30 ppbv for the separate DAS scheme with an averaging time of 1 s and a detection limit of ~1.19 ppbv with a precision of about ±4 ppbv for the separate WMS scheme with a 4-s averaging time were achieved. An Allan–Werle variance analysis indicated that the precisions can be further improved to 777 pptv @ 166 s for the separate DAS scheme and 269 pptv @ 108 s for the WMS scheme, respectively. For the quasi-simultaneous DAS and WMS scheme, both the 2f signal and the direct absorption signal were simultaneously extracted using a LabVIEW platform, and four C 2 H 6 samples (0, 30, 60 and 90 ppbv with nitrogen as the balance gas) were used as the target gases to assess the sensor performance. A detailed comparison of the three measurement schemes is reported. Here, atmospheric C 2 H 6 measurements on the Rice University campus and a field test at a compressed natural gas station in Houston, TX, were conducted to evaluate the performance of the sensor system as a robust and reliable field-deployable sensor system.

47 OTHER INSTRUMENTATION↗

A continuation multilevel Monte Carlo algorithm

Here, we propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. Moreover, the actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Our numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients.

97 MATHEMATICS AND COMPUTING↗

One-Sided Continuity Properties for the Schonmann Projection

We consider the plus-phase of the two-dimensional Ising model below the critical temperature. In 1989 Schonmann proved that the projection of this measure onto a one-dimensional line is not a Gibbs measure. After many years of continued research which have revealed further properties of this measure, the question whether or not it is a Gibbs measure in an almost sure sense remains open. In this paper we study the same measure by interpreting it as a temporal process. One of our main results is that the Schonmann projection is almost surely a regular g-measure. That is, it does possess the corresponding one-sided notion of almost Gibbsianness. We further deduce strong one-sided mixing properties which are of independent interest. Our proofs make use of classical coupling techniques and some monotonicity properties which are known to hold for one-sided, but not two-sided conditioning for FKG measures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Semirings of Continuous (0,∞]-Valued Functions

The semiring C{sup ∞}(X) of all continuous functions on an arbitrary topological space X with values in the topological semiring (0,∞] is studied. General properties of semirings C{sup ∞}(X) are considered. Properties of lattices of ideals and congruences of semirings C{sup ∞}(X) over the P-spaces X, the F-spaces X, and the finite discrete spaces are proved.

97 MATHEMATICS AND COMPUTING↗

Continuous Dependence on Translations of the Independent Variable for Solutions of Boundary-Value Problems for Differential-Difference Equations

We consider boundary-value problems for differential-difference operators with perturbations in translations of the independent variable. We prove that the family of differential-difference operators is positive definite uniformly with respect to translations of the independent variable. Solutions of such problems depend continuously on these translations. We consider the coercivity problem for differential-difference operators with incommensurable translations of the independent variable and study the approximation of such operators by rational operators.

97 MATHEMATICS AND COMPUTING↗

On Justification of the Asymptotics of Eigenfunctions of the Absolutely Continuous Spectrum in the Problem of Three One-Dimensional Short-Range Quantum Particles with Repulsion

The present paper offers a new approach to the construction of the coordinate asymptotics of the kernel of the resolvent of the Schrödinger operator in the scattering problem of three onedimensional quantum particles with short-range pair potentials. Within the framework of this approach, the asymptotics of eigenfunctions of the absolutely continuous spectrum of the Schrödinger operator can be constructed. In the paper, the possibility of a generalization of the suggested approach to the case of the scattering problem of N particles with arbitrary masses is discussed.

97 MATHEMATICS AND COMPUTING↗