Time to flower Johansson, Mikael; Staiger, Dorothee
Journal of experimental botany,
02/2015, Letnik:
66, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Plants precisely time the onset of flowering to ensure reproductive success. A major factor in seasonal control of flowering time is the photoperiod. The length of the daily light period is measured ...by the circadian clock in leaves, and a signal is conveyed to the shoot apex to initiate floral transition accordingly. In the last two decades, the molecular players in the photoperiodic pathway have been identified in Arabidopsis thaliana. Moreover, the intricate connections between the circadian clockwork and components of the photoperiodic pathway have been unravelled. In particular, the molecular basis of time-of-day-dependent sensitivity to floral stimuli, as predicted by Bünning and Pittendrigh, has been elucidated. This review covers recent insights into the molecular mechanisms underlying clock regulation of photoperiodic responses and the integration of the photoperiodic pathway into the flowering time network in Arabidopsis. Furthermore, examples of conservation and divergence in photoperiodic flower induction in other plant species are discussed.
The alternating direction method of multipliers (ADMM) has emerged as a powerful technique for large-scale structured optimization. Despite many recent results on the convergence properties of ADMM, ...a quantitative characterization of the impact of the algorithm parameters on the convergence times of the method is still lacking. In this paper we find the optimal algorithm parameters that minimize the convergence factor of the ADMM iterates in the context of ℓ 2 -regularized minimization and constrained quadratic programming. Numerical examples show that our parameter selection rules significantly outperform existing alternatives in the literature.
Resource allocation plays a central role in networked systems such as smart grids, communication networks, and urban transportation systems. In these systems, many constraints have physical meaning ...and infeasible allocations can result in a system breakdown. Hence, algorithms with asymptotic feasibility guarantees can be insufficient since they cannot ensure that an implementable solution is found in finite time. This paper proposes a distributed feasible method (DFM) for resource allocation based on barrier functions. In DFM, every iterate is feasible and safe to implement since it does not violate the physical constraints. We prove that, under mild conditions, DFM converges to an arbitrarily small neighborhood of the optimum. Numerical experiments demonstrate the competitive performance of DFM.
The magnetically induced current density of an intriguing naphthalene-fused heteroporphyrin has been studied, using the quantum-chemical, gauge-including magnetically induced currents (GIMIC) method. ...The ring-current strengths and current-density pathways for the heteroporphyrin, its Pd complex, and the analogous quinoline-fused heteroporphyrin provide detailed information about their aromatic properties. The three porphyrinoids have similar current-density pathways and are almost as aromatic as free-base porphyrin. Notably, we show that the global ring current makes a branch at three specific points. Thus, the global current is composed of a total of eight pathways that include 22 π-electrons, with no contributions from 18-electron pathways.
18 or 22 π? 8 × 22! Quantum chemical calculations reveal the complex ring-current pathways of a new class of heteroporphyrinoids.
The barriers of internal rotation of the two phenyl groups in biphenyl are investigated using a combination of coupled cluster and density functional theory. The experimental barriers are for the ...first time accurately reproduced; our best estimates of the barriers are 8.0 and 8.3 kJ/mol around the planar and perpendicular conformations, respectively. The use of flexible basis sets of at least augmented quadruple-ζ quality is shown to be a crucial prerequisite. Further, to finally reconcile theory with experiment, extrapolations of both the basis set toward the basis set limit and electron correlation toward the full configuration-interaction limit are necessary. The minimum of the torsional angle is significantly increased by free energy corrections, which are needed to reach an agreement with experiment. The density functional B3LYP approach is found to perform well compared with the highest level ab initio results.
By analysing the properties of the electron density in the structurally simple perhalogenated ethanes, X3C-CY3 (X, Y = F, Cl), a previously overlooked non-covalent attraction between halogens ...attached to opposite carbon atoms is found. Quantum chemical calculations extrapolated towards the full solution of the Schrödinger equation reveal the complex nature of the interaction. When at least one of the halogens is a chlorine, the strength of the interaction is comparable to that of hydrogen bonds. Further analysis shows that the bond character is quite different from standard non-covalent halogen bonds and hydrogen bonds; no bond critical points are found between the halogens, and the σ-holes of the halogens are not utilised for bonding. Thus, the nature of the intramolecular halogen···halogen bonding studied here appears to be of an unusually strong van der Waals type.
Recent experiments and calculations have established the transition from two-dimensional (2D) to three-dimensional (3D) structures at a cluster size of 8 and 12 atoms for gold cluster cations and ...anions. For neutral gold clusters, however, experimental data are scarce, and existing theoretical studies disagree on the 2D–3D crossover point. We present the results of global structure optimizations of neutral gold clusters Au n for n = 9–13 using a genetic algorithm and meta-generalized density functional theory. The relative energies of the lowest-lying isomers are computed using the revTPSS functional and the random phase approximation (RPA). Thermal, scalar relativistic, and spin–orbit effects are included, and basis set extrapolations are performed for the RPA calculations. For the 2D–3D transition of gold cluster cations and anions, this methodology yields near-quantitative agreement with cross section and electron diffraction measurements. For neutral gold clusters, the 2D and 3D structures are predicted to be almost isoenergetic at n = 11 gold atoms, while clusters with n > 11 are manifestly 3D. Thus, neutral gold clusters turn 3D at an unusually large size of 11 gold atoms.
Acetylated oligosaccharides are common in nature. While they are involved in several biochemical and biological processes, the role of the acetyl groups and the complexity of their migration has ...largely gone unnoticed. In this work, by combination of organic synthesis, NMR spectroscopy and quantum chemical modeling, we show that acetyl group migration is a much more complex phenomenon than previously known. By use of synthetic oligomannoside model compounds, we demonstrate, for the first time, that the migration of acetyl groups in oligosaccharides and polysaccharides may not be limited to transfer within a single monosaccharide moiety, but may also involve migration over a glycosidic bond between two different saccharide units. The observed phenomenon is not only interesting from the chemical point of view, but it also raises new questions about the potential biological role of acylated carbohydrates in nature.
Predicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated statistical ...estimators suffer from underdetermination. While specific techniques have been proposed to overcome this deficiency, there still lacks a general approach. Here, we propose a deep neural network framework with gated recurrent units (DNNGRU) to address this gap. Our DNNGRU is network-free, as it is trained by supervised learning with time-series data on the volume of agents passing through edges. We use it to investigate how network topologies affect OD prediction accuracy, where performance enhancement is observed to depend on the degree of overlap between paths taken by different ODs. By comparing against methods that give exact results, we demonstrate the near-optimal performance of our DNNGRU, which we found to consistently outperform existing methods and alternative neural network architectures, under diverse data generation scenarios.
We study the evolution of opinions (or beliefs) over a social network modeled as a signed graph. The sign attached to an edge in this graph characterizes whether the corresponding individuals or end ...nodes are friends (positive links) or enemies (negative links). Pairs of nodes are randomly selected to interact over time, and when two nodes interact, each of them updates its opinion based on the opinion of the other node and the sign of the corresponding link. This model generalizes the DeGroot model to account for negative links: when two adversaries interact, their opinions go in opposite directions. We provide conditions for convergence and divergence in expectation, in mean-square, and in almost sure sense and exhibit phase transition phenomena for these notions of convergence depending on the parameters of the opinion update model and on the structure of the underlying graph. We establish a
no-survivor
theorem, stating that the difference in opinions of any two nodes diverges whenever opinions in the network diverge as a whole. We also prove a
live-or-die
lemma, indicating that almost surely, the opinions either converge to an agreement or diverge. Finally, we extend our analysis to cases where opinions have hard lower and upper limits. In these cases, we study when and how opinions may become asymptotically clustered to the belief boundaries and highlight the crucial influence of (strong or weak) structural balance of the underlying network on this clustering phenomenon.
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