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The resource utilization of marine-dredged sediment is considered a sustainable approach to its disposal. This paper investigates the preparation of non-sintered ceramsites from marine-dredged sediments and CSA cement via cold-bonded pelletization. The study examines the effects of various preparation conditions on the engineering properties, phase compositions and microstructures of non-sintered ceramsites. The results indicate that preparation conditions significantly influence the particle size distribution of non-sintered ceramsites. The early-strength development of non-sintered ceramsites prepared from CSA cement is remarkable, with the PCS achieving approximately 60% and 80% of the 28-day strength within 3 days and 7 days, respectively—a marked contrast to OPC. Response surface methodology analysis reveals significant interaction effects between the disc rotation angle, rotational speed, and duration of rotation on the PCS of non-sintered ceramsites. The open-ended porosity of non-sintered ceramsites exhibits greater sensitivity to changes in preparation parameters compared to closed-ended porosity and total porosity. The preparation conditions have negligible impact on the hydration process of CSA cement in non-sintered ceramsites. For both ellipsoidal and plate-like marine-dredged soil particles, ettringite and the AH3 phase provide effective pore-filling and binding effects in the microstructures of non-sintered ceramsites. These findings imply that low-carbon utilization of marine-dredged sediments through the preparation of non-sintered ceramsites offers a nature-based solution for sustainable management in coastal systems.

Background Studies have indicated that long non-coding RNAs (lncRNAs) play important regulatory roles in many biological processes. However, the regulation of seed oil biosynthesis by lncRNAs remains largely unknown. Results We comprehensively identified and characterized the lncRNAs from seeds in three developing stages in two accessions of Brassica napus ( B. napus ), ZS11 (high oil content) and WH5557 (low oil content). Finally, 8094 expressed lncRNAs were identified. LncRNAs MSTRG.22563 and MSTRG.86004 were predicted to be related to seed oil accumulation. Experimental results show that the seed oil content is decreased by 3.1–3.9% in MSTRG.22563 overexpression plants, while increased about 2% in MSTRG.86004 , compared to WT. Further study showed that most genes related to lipid metabolism had much lower expression, and the content of some metabolites in the processes of respiration and TCA (tricarboxylic acid) cycle was reduced in MSTRG.22563 transgenic seeds. The expression of genes involved in fatty acid synthesis and seed embryonic development (e.g., LEC1 ) was increased, but genes related to TAG assembly was decreased in MSTRG.86004 transgenic seeds. Conclusion Our results suggest that MSTRG.22563 might impact seed oil content by affecting the respiration and TCA cycle, while MSTRG.86004 plays a role in prolonging the seed developmental time to increase seed oil accumulation.

We propose, analyze, and test Anderson-accelerated Picard iterations for solving the incompressible Navier-Stokes equations (NSE). Anderson acceleration has recently gained interest as a strategy to accelerate linear and nonlinear iterations, based on including an optimization step in each iteration. We extend the Anderson acceleration theory to the steady NSE setting and prove that the acceleration improves the convergence rate of the Picard iteration based on the success of the underlying optimization problem. The convergence is demonstrated in several numerical tests, with particularly marked improvement in the higher Reynolds number regime. Our tests show it can be an enabling technology in the sense that it can provide convergence when both usual Picard and Newton iterations fail.

This paper considers the effect of Anderson acceleration (AA) on the convergence order of nonlinear solvers in fixed point form x k + 1 = g ( x k ) , that are looking for a fixed point x ∗ of g . While recent work has answered the fundamental question of how AA affects the convergence rate of linearly converging fixed point iterations (at a single step), no analytical results exist (until now) for how AA affects the convergence order of solvers that do not converge linearly. We first consider AA applied to general methods with convergence order r , and show that m = 1 AA changes the convergence order to (at least) r + 1 2 ; a more complicated expression for the order is found for the case of larger m . This result is valid for superlinearly converging methods and also locally for sublinearly converging methods where r < 1 locally but r → 1 as the iteration converges, revealing that AA slows convergence for superlinearly converging methods but (locally) accelerates it for sublinearly converging methods. We then consider AA-Newton, and find that it is a special case that fits in the framework of the recent theory for linearly converging methods which allows us to deduce that depth level m reduces the asymptotic convergence order from 2 to the largest positive real root of α m + 1 - α m - 1 = 0 (i.e. with m = 1 the order is 1.618, and decreases as m increases). Several numerical tests illustrate our theoretical results.

We propose new, efficient, and simple nonlinear iteration methods for the incompressible Navier-Stokes equations. The methods are constructed by applying Yosida-type algebraic splitting to the linear systems that arise from grad-div stabilized finite element implementations of incremental Picard and Newton iterations. They are efficient because at each nonlinear iteration, the same symmetric positive definite Schur complement system needs to be solved, which allows for CG to be used for inner and outer solvers, simple preconditioning, and the reusing of preconditioners. For the proposed incremental Picard-Yosida and Newton-Yosida iterations, we prove under small data conditions that the methods converge to the solution of the discrete nonlinear problem. Numerical tests are performed which illustrate the effectiveness of the method on a variety of test problems.

   Fatty acid exporter 1 (FAX1) is an initial transporter for fatty acid (FA), in charge of transporting FA from the inside of the plastid to the outside. Brassica napus ( B. napus ) has nineteen members in the FAX family, of which there are six FAX1 homologous genes. Here, we generated the BnaFAX1 CRISPR mutants ( BnaA09.FAX1 and BnaC08.FAX1 were both edited) and overexpression (OE) plants of BnaA09.FAX1 in B. napus . The results showed that the FA content was increased by 0.6–0.9% in OE plant leaves, and the seed oil content was increased by 1.4–1.7% in OE lines, compared to WT. Meanwhile, the content of triacylglycerol, diacylglycerol, and phosphatidylcholine was significantly increased in OE seeds. Moreover, seedling biomass and plant height of OE plants were increased compared to WT plants. However, the traits above had no significant difference between the mutants and WT. These results suggest that BnaA09.FAX1 plays a role in improving seed oil accumulation and plant growth, while the function of BnaFAX1 may be compensated by other homologous genes of BnaFAX1 and other BnaFAX genes in the mutants.

We propose, analyze, and test a penalty projection-based robust efficient and accurate algorithm for the Uncertainty Quantification (UQ) of the time-dependent Magnetohydrodynamic (MHD) flow problems in convection-dominated regimes. The algorithm uses the Elsässer variables formulation and discrete Hodge decomposition to decouple the stochastic MHD system into four sub-problems (at each time-step for each realization) which are much easier to solve than solving the coupled saddle point problems. Each of the sub-problems is designed in a sophisticated way so that at each time-step the system matrix remains the same for all the realizations but with different right-hand-side vectors which allows saving a huge amount of computer memory and computational time. Moreover, the scheme is equipped with Ensemble Eddy Viscosity (EEV) and grad-div stabilization terms. The unconditional stability with respect to the time-step size of the algorithm is proven rigorously. We prove the proposed scheme converges to an equivalent non-projection-based coupled MHD scheme for large grad-div stabilization parameter values. We examine how Stochastic Collocation Methods (SCMs) can be combined with the proposed penalty projection UQ algorithm. Finally, a series of numerical experiments are given which verify the predicted convergence rates, show the algorithm’s performance on benchmark channel flow over a rectangular step, a regularized lid-driven cavity problem with high random Reynolds number and high random magnetic Reynolds number, and the impact of the EEV stabilization in the MHD UQ algorithm.

Studies have indicated that long non-coding RNAs (lncRNAs) play important regulatory roles in many biological processes. However, the regulation of seed oil biosynthesis by lncRNAs remains largely unknown. We comprehensively identified and characterized the lncRNAs from seeds in three developing stages in two accessions of Brassica napus (B. napus), ZS11 (high oil content) and WH5557 (low oil content). Finally, 8094 expressed lncRNAs were identified. LncRNAs MSTRG.22563 and MSTRG.86004 were predicted to be related to seed oil accumulation. Experimental results show that the seed oil content is decreased by 3.1-3.9% in MSTRG.22563 overexpression plants, while increased about 2% in MSTRG.86004, compared to WT. Further study showed that most genes related to lipid metabolism had much lower expression, and the content of some metabolites in the processes of respiration and TCA (tricarboxylic acid) cycle was reduced in MSTRG.22563 transgenic seeds. The expression of genes involved in fatty acid synthesis and seed embryonic development (e.g., LEC1) was increased, but genes related to TAG assembly was decreased in MSTRG.86004 transgenic seeds. Our results suggest that MSTRG.22563 might impact seed oil content by affecting the respiration and TCA cycle, while MSTRG.86004 plays a role in prolonging the seed developmental time to increase seed oil accumulation.

This dissertation studies two classes of splitting methods, Yosida methods and projection methods, for simulating incompressible fluid flows. The former ones are algebraic splitting methods that split the system after discretization, while the latter ones split before. Both methods are more efficient than the exact solver as they decouple the system. Here we propose some variational forms of these methods that improve their accuracy and preserve the efficiency. Chapter 3 studies a new alteration of Yosida algebraic splitting methods for the Navier-Stokes equations. By applying the usual or pressure-corrected Yosida splitting techniques to discretizations written in terms of velocity and pressure updates (un+1 - un, p n+1- pn), we show that the accuracy is increased by one full order in Δt without any additional cost in the respective methods. Proofs of the convergence results are given both in linear algebraic and finite element frameworks. Several numerical tests are given which reveal the (sometimes dramatic) improvement in accuracy offered by the proposed fix. Chapter 4 analyzes the accuracy of the 'discretize-then-split' Yosida solver for incompressible flow problems, when divergence-free elements are used together with grad-div stabilization (with parameter γ). The Yosida method uses an inexact block LU factorization to create linear algebraic systems that are easier to solve, but at the expense of accuracy. We prove the difference between solutions of the exact and approximated linear algebraic systems is O(−2) in the natural norms of the associated finite element problems, and thus that full accuracy can be obtained by the Yosida method if large γ is used (γ ≥ 10 is sufficient in our numerical examples). The proof is based on transforming the Yosida inexact linear algebraic system into finite element problems, and analyzing these problems with finite element techniques based on pointwise divergence-free subspaces and their orthogonal complements. Chapter 5 studies and compares fully discrete numerical approximations for the Cahn-Hilliard-Navier-Stokes (CHNS) system of equations that enforce the divergence constraint in different ways, one method via penalization in a projection-type splitting scheme, and the other via strongly divergence-free elements in a fully coupled scheme. We prove a connection between these two approaches, and test the methods against standard ones with several numerical experiments. The tests reveal that CHNS system solutions can be efficiently and accurately computed with penalty-projection methods. Lastly, Chapter 6 investigates a flux-preserving enforcement of inhomogeneous Dirichlet boundary condition for velocity, u |δΩ = g for use with finite element methods for incompressible flow problems that strongly enforce mass conservation. Typical enforcement via nodal interpolation is not flux-preserving in general, and it can create divergence error even when divergence-free elements are used. We show with analysis and numerical tests that by slightly (and locally) changing nodal interpolation, the enforcement recovers flux-preservation, is optimally accurate, and delivers divergence-free solutions when used with divergence-free finite elements.

This paper studies the performance Newton's iteration applied with Anderson acceleration for solving the incompressible steady Navier-Stokes equations. We manifest that this method converges superlinearly with a good initial guess, and moreover, a large Anderson depth decelerates the convergence speed comparing to a small Anderson depth. We observe that the numerical tests confirm these analytical convergence results, and in addition, Anderson acceleration sometimes enlarges the domain of convergence for Newton's method.