Minimal Set Of Constraints Research Articles

A conceptual framework for the dynamic modeling of time-resolved phenotypes for sets of genotype-environment-management combinations: a model library.

Dynamic crop growth models are an important tool to predict complex traits, like crop yield, for modern and future genotypes in their current and evolving environments, as those occurring under climate change. Phenotypic traits are the result of interactions between genetic, environmental, and management factors, and dynamic models are designed to generate the interactions producing phenotypic changes over the growing season. Crop phenotype data are becoming increasingly available at various levels of granularity, both spatially (landscape) and temporally (longitudinal, time-series) from proximal and remote sensing technologies. Here we propose four phenomenological process models of limited complexity based on differential equations for a coarse description of focal crop traits and environmental conditions during the growing season. Each of these models defines interactions between environmental drivers and crop growth (logistic growth, with implicit growth restriction, or explicit restriction by irradiance, temperature, or water availability) as a minimal set of constraints without resorting to strongly mechanistic interpretations of the parameters. Differences between individual genotypes are conceptualized as differences in crop growth parameter values. We demonstrate the utility of such low-complexity models with few parameters by fitting them to longitudinal datasets from the simulation platform APSIM-Wheat involving in silico biomass development of 199 genotypes and data of environmental variables over the course of the growing season at four Australian locations over 31 years. While each of the four models fits well to particular combinations of genotype and trial, none of them provides the best fit across the full set of genotypes by trials because different environmental drivers will limit crop growth in different trials and genotypes in any specific trial will not necessarily experience the same environmental limitation. A combination of low-complexity phenomenological models covering a small set of major limiting environmental factors may be a useful forecasting tool for crop growth under genotypic and environmental variation.

N=4 supersymmetric Schwarzian with D(1,2;α) symmetry

It was recently demonstrated that super-Schwarzian derivatives can be constructed from the Cartan forms of the superconformal supergroups $OSp(1|2)$, $SU(1,1|1)$, $OSp(3|2)$, $SU(1,1|2)$. Roughly speaking, the super-Schwarzian is just the component of the corresponding Cartan forms with the lowest dimension. In this paper, we apply the same approach to superalgebra $D(1,2;\ensuremath{\alpha})$. The minimal set of constraints we used includes: (a) introducing new superspace coordinates the Cartan forms depend on, which are completely invariant with respect to the corresponding group; (b) nullifying the form for dilatation. In contrast to the $SU(1,1|2)$ case, the new super-Schwarzian appears to be a $d{\ensuremath{\theta}}^{ia}$ component of the form for $su(2)$ automorphism.

Aggregate Constraints for Virtual Manipulation with Soft Fingers.

Interactive dexterous manipulation of virtual objects remains a complex challenge that requires both appropriate hand models and accurate physically-based simulation of interactions. In this paper, we propose an approach based on novel aggregate constraints for simulating dexterous grasping using soft fingers. Our approach aims at improving the computation of contact mechanics when many contact points are involved, by aggregating the multiple contact constraints into a minimal set of constraints. We also introduce a method for non-uniform pressure distribution over the contact surface, to adapt the response when touching sharp edges. We use the Coulomb-Contensou friction model to efficiently simulate tangential and torsional friction. We show through different use cases that our aggregate constraint formulation is well-suited for simulating interactively dexterous manipulation of virtual objects through soft fingers, and efficiently reduces the computation time of constraint solving.

A New Solution to the Structure Equation in Noncommutative Spacetime

In this paper, starting from the common foundation of Connes' noncommutative geometry ( NCG)\cite{Connes1, Connes2, CoLo, Connes3}, various possible alternatives in the formulation of atheory of gravity in noncommutative spacetime are discussed indetails. The diversity in the final physical content of the theory is shown to be the consequence of the arbitrary choices in each construction steps. As an alternative in the last step, when the structure equations are to be solved, a minimal set of constraints on the torsion and connection is found to determine all the geometric notions in terms of the metric. In the Connes-Lott model of noncommutative spacetime, in order to keep the full spectrum of the discretized Kaluza-Klein theory \cite{VW2}, it is necessary to include the torsion in the generalized Einstein-Hilbert-Cartan action.

A comparison of the computational efficiency of generalised function MPC using active set methods

This paper considers the computational efficiency of the recently developed generalised function parameterisations predictive control algorithms using active set methods. Alternative parameterisations have been shown to improve the volume of the feasible region when the number of degrees of freedom is limited. However, earlier work also demonstrates that some of the structure of optimisation problem is lost when using these parameterisations and thus requires more computation operations per step. This paper considers the dense problem structure arising from removing any redundant constraints and then considers the computational efficiency using the minimal constraint sets. Extensive simulation results suggest there can still be benefits from using more general parameterisations, although less significant then indicated by the number of degrees of freedom alone.

Asymptotic properties of keys and functional dependencies in random databases

Practical database applications give the impression that sets of constraints are rather small and that large sets are unusual and are caused by bad design decisions. Theoretical investigations, however, show that minimal constraint sets are potentially very large. Their size can be estimated to be exponential in terms of the number of attributes. The gap between observation in practice and theory results in the rejection of theoretical results. However, practice is related to average cases and is not related to worst cases. The theory used until now considered the worst-case complexity. This paper aims to develop a theory for the average-case complexity. Several probabilistic models and asymptotics of corresponding probabilities are investigated for random databases formed by independent random tuples with a common discrete distribution. Poisson approximations are studied for the distributions of some characteristics for such databases where the number of tuples is sufficiently large. We intend to prove that the exponential complexity of key sets and sets of functional dependencies is rather unusual and almost all minimal keys in a relation have a length which depends mainly on the size of the relation.

LOCAL SYMMETRIES STRUCTURE OF THE SUPERPARTICLE AND SUPERGRAVITY BACKGROUNDS

The classical (1,0) superparticle in a curved superspace is considered. The minimal set of constraints to be imposed on the background for correct inclusion of interaction is found. The most general form of Siegel-type local fermionic symmetry is presented. Gauge algebra of the model is shown to be closed off-shell (by means of adding one trivial symmetry) and deformed as compared to the flat one. The form and algebraic structure of local symmetries of the theory are shown not to be deformed (in comparing with the flat case) in the (1,0) supergravity background only.

On-line multiversion database concurrency control

This paper presents a new model for studying the concurrency vs. computation time tradeoffs involved in on-line multiversion database concur- rency control. The basic problem that is studied in our model is the following: Given: a current database system state which includes information such as which transaction previously read a version from which other transaction; which transaction has written which versions into the database; and the ordering of versions previously written; and a set of read and write requests of requesting transactions. Question: Does there exist a new database system state in which the request- ing transactions can be immediately put into execution (their read and write requests satisfied, or in the case of predeclared writeset transactions, write requests are guaranteed to be satisfied) while preserving consistency under a given set of additional constraints? (The amount of concurrency achieved is defined by the set of additional constraints). In this paper we derive "limits" of performance achievable by polynomial time concurrency control algorithms. Each limit is characterized by a minimal set of constraints that allow the on-line scheduling problem to be solved in polynomial time. If any one constraint in that minimal set is omitted, although it could increase the amount of concurrency, it would also have the dramatic negative effect of making the scheduling problem NP-complete; whereas if we do not omit any constraint in the minimal set, then the scheduling problem can be solved in polynomial time. With each of these limits, one can construct an efficient scheduling algorithm that achieves an optimal level of concurrency in polynomial computation time according to the constraints defined in the minimal set.