Integration, heterochrony, and adaptation in pedal digits of syndactylous marsupials

Background. Marsupial syndactyly is a curious morphology of the foot found in all species of diprotodontian and peramelemorph marsupials. It is traditionally defined as a condition in which digits II and III of the foot are bound by skin and are reduced. Past treatments of marsupial syndactyly have not considered the implications of this unique morphology for broader issues of digit development and evolution, and the ongoing debate regarding its phylogenetic meaning lacks a broad empirical basis. This study undertakes the first interdisciplinary characterisation of syndactyly, using variance/covariance matrix comparisons of morphometric measurements, locomotor indices, ossification sequences, and re-assessment of the largely anecdotal data on the phylogenetic distribution of tarsal/metatarsal articulations and "incipient syndactyly". Results. Syndactylous digits have virtually identical variance/covariance matrices and display heterochronic ossification timing with respect to digits IV/V. However, this does not impact on overall locomotor adaptation patterns in the syndactylous foot as determined by analysis of locomotor predictor ratios. Reports of incipient syndactyly in some marsupial clades could not be confirmed; contrary to previous claims, syndactyly does not appear to impact on tarsal bone arrangement. Conclusion. The results suggest that marsupial syndactyly originates from a constraint that is rooted in early digit ontogeny and results in evolution of the syndactylous digits as a highly integrated unit. Although convergent evolution appears likely, syndactyly in Diprotodontia and Peramelemorpha may occur through homologous developmental processes. We argue that the term "syndactyly" is a misnomer because the marsupial condition only superficially resembles its name-giving human soft-tissue syndactyly

Enterprise Information Integration Using a Peer to Peer Approach

The integration of enterprise information systems has unique requirements and frequently posesproblems to business partners. We discuss specific integration issues for micro-sized enterprises onthe special case of independent sales agencies and their suppliers. We argue that the enterpriseinformation systems of those independent enterprises are technically best represented by equal peers.Therefore, we have designed the Peer-To-Peer (P2P) integration architecture VIANA for theintegration of enterprise information systems. Its architecture provides materializing P2P integrationusing optimistic replication. It is applicable to inter- and intraorganizational integration scenarios. Itis accomplished by the propagation of write operations between peers. We argue that this type ofintegration can be realized with no alteration of the participating information systems

Improving multifrontal solvers by means of algebraic Block Low-Rank representations

We consider the solution of large sparse linear systems by means of direct factorization based on a multifrontal approach. Although numerically robust and easy to use (it only needs algebraic information: the input matrix A and a right-hand side b, even if it can also digest preprocessing strategies based on geometric information), direct factorization methods are computationally intensive both in terms of memory and operations, which limits their scope on very large problems (matrices with up to few hundred millions of equations). This work focuses on exploiting low-rank approximations on multifrontal based direct methods to reduce both the memory footprints and the operation count, in sequential and distributed-memory environments, on a wide class of problems. We first survey the low-rank formats which have been previously developed to efficiently represent dense matrices and have been widely used to design fast solutions of partial differential equations, integral equations and eigenvalue problems. These formats are hierarchical (H and Hierarchically Semiseparable matrices are the most common ones) and have been (both theoretically and practically) shown to substantially decrease the memory and operation requirements for linear algebra computations. However, they impose many structural constraints which can limit their scope and efficiency, especially in the context of general purpose multifrontal solvers. We propose a flat format called Block Low-Rank (BLR) based on a natural blocking of the matrices and explain why it provides all the flexibility needed by a general purpose multifrontal solver in terms of numerical pivoting for stability and parallelism. We compare BLR format with other formats and show that BLR does not compromise much the memory and operation improvements achieved through low-rank approximations. A stability study shows that the approximations are well controlled by an explicit numerical parameter called low-rank threshold, which is critical in order to solve the sparse linear system accurately. Details on how Block Low-Rank factorizations can be efficiently implemented within multifrontal solvers are then given. We propose several Block Low-Rank factorization algorithms which allow for different types of gains. The proposed algorithms have been implemented within the MUMPS (MUltifrontal Massively Parallel Solver) solver. We first report experiments on standard partial differential equations based problems to analyse the main features of our BLR algorithms and to show the potential and flexibility of the approach; a comparison with a Hierarchically SemiSeparable code is also given. Then, Block Low-Rank formats are experimented on large (up to a hundred millions of unknowns) and various problems coming from several industrial applications. We finally illustrate the use of our approach as a preconditioning method for the Conjugate Gradient

Stammdatenmanagement: Datenqualität für Geschäftsprozesse

Zusammenfassung: Stammdatenmanagement ist eine Unternehmensfunktion, die sämtliche Planungs-, Überwachungs- und Bereitstellungsaktivitäten für Stammdaten umfasst und deren Ziel die Sicherung der Stammdatenqualität ist. Stammdaten von hoher Qualität sind die Voraussetzung, damit Unternehmen verschiedene strategische Anforderungen erfüllen können. Dieser Beitrag beschreibt diejenigen Bereiche, die beim Aufbau eines unternehmensweiten Stammdatenmanagements zu gestalten sin

An Architecture for Peer-to-Peer Integration of Interorganizational Information Systems

On the business case of independent sales agencies we discuss the requirements of tiny sized enterprises for data integration. If a multitude of independent enterprises need to be integrated, we argue that those are best represented by equal peers and describe the Architecture of VIANA: a Peer-to-Peer architecture for materialized integration of information systems, both in the interas well as the intraorganizational domain. VIANA propagates updates on data between peers and continuously monitors data quality. We argue that this type of integration can be accomplished with ideally no alteration of the participating information systems and that the integration may benefit substantially from existing data exchange formats. To this end we formulate the architecture in a way that existing XML technologies and standards may be utilized without the need for alterations

Amélioration des solveurs multifrontaux à l'aide de représentations algébriques rang-faible par blocs

We consider the solution of large sparse linear systems by means of direct factorization based on a multifrontal approach. Although numerically robust and easy to use (it only needs algebraic information: the input matrix A and a right-hand side b, even if it can also digest preprocessing strategies based on geometric information), direct factorization methods are computationally intensive both in terms of memory and operations, which limits their scope on very large problems (matrices with up to few hundred millions of equations). This work focuses on exploiting low-rank approximations on multifrontal based direct methods to reduce both the memory footprints and the operation count, in sequential and distributed-memory environments, on a wide class of problems. We first survey the low-rank formats which have been previously developed to efficiently represent dense matrices and have been widely used to design fast solutions of partial differential equations, integral equations and eigenvalue problems. These formats are hierarchical (H and Hierarchically Semiseparable matrices are the most common ones) and have been (both theoretically and practically) shown to substantially decrease the memory and operation requirements for linear algebra computations. However, they impose many structural constraints which can limit their scope and efficiency, especially in the context of general purpose multifrontal solvers. We propose a flat format called Block Low-Rank (BLR) based on a natural blocking of the matrices and explain why it provides all the flexibility needed by a general purpose multifrontal solver in terms of numerical pivoting for stability and parallelism. We compare BLR format with other formats and show that BLR does not compromise much the memory and operation improvements achieved through low-rank approximations. A stability study shows that the approximations are well controlled by an explicit numerical parameter called low-rank threshold, which is critical in order to solve the sparse linear system accurately. Details on how Block Low-Rank factorizations can be efficiently implemented within multifrontal solvers are then given. We propose several Block Low-Rank factorization algorithms which allow for different types of gains. The proposed algorithms have been implemented within the MUMPS (MUltifrontal Massively Parallel Solver) solver. We first report experiments on standard partial differential equations based problems to analyse the main features of our BLR algorithms and to show the potential and flexibility of the approach; a comparison with a Hierarchically SemiSeparable code is also given. Then, Block Low-Rank formats are experimented on large (up to a hundred millions of unknowns) and various problems coming from several industrial applications. We finally illustrate the use of our approach as a preconditioning method for the Conjugate Gradient.Nous considérons la résolution de très grands systèmes linéaires creux à l'aide d'une méthode de factorisation directe appelée méthode multifrontale. Bien que numériquement robustes et faciles à utiliser (elles ne nécessitent que des informations algébriques : la matrice d'entrée A et le second membre b, même si elles peuvent exploiter des stratégies de prétraitement basées sur des informations géométriques), les méthodes directes sont très coûteuses en termes de mémoire et d'opérations, ce qui limite leur applicabilité à des problèmes de taille raisonnable (quelques millions d'équations). Cette étude se concentre sur l'exploitation des approximations de rang-faible dans la méthode multifrontale, pour réduire sa consommation mémoire et son volume d'opérations, dans des environnements séquentiel et à mémoire distribuée, sur une large classe de problèmes. D'abord, nous examinons les formats rang-faible qui ont déjà été développé pour représenter efficacement les matrices denses et qui ont été utilisées pour concevoir des solveur rapides pour les équations aux dérivées partielles, les équations intégrales et les problèmes aux valeurs propres. Ces formats sont hiérarchiques (les formats H et HSS sont les plus répandus) et il a été prouvé, en théorie et en pratique, qu'ils permettent de réduire substantiellement les besoins en mémoire et opération des calculs d'algèbre linéaire. Cependant, de nombreuses contraintes structurelles sont imposées sur les problèmes visés, ce qui peut limiter leur efficacité et leur applicabilité aux solveurs multifrontaux généraux. Nous proposons un format plat appelé Block Rang-Faible (BRF) basé sur un découpage naturel de la matrice en blocs et expliquons pourquoi il fournit toute la flexibilité nécéssaire à son utilisation dans un solveur multifrontal général, en terme de pivotage numérique et de parallélisme. Nous comparons le format BRF avec les autres et montrons que le format BRF ne compromet que peu les améliorations en mémoire et opération obtenues grâce aux approximations rang-faible. Une étude de stabilité montre que les approximations sont bien contrôlées par un paramètre numérique explicite appelé le seuil rang-faible, ce qui est critique dans l'optique de résoudre des systèmes linéaires creux avec précision. Ensuite, nous expliquons comment les factorisations exploitant le format BRF peuvent être efficacement implémentées dans les solveurs multifrontaux. Nous proposons plusieurs algorithmes de factorisation BRF, ce qui permet d'atteindre différents objectifs. Les algorithmes proposés ont été implémentés dans le solveur multifrontal MUMPS. Nous présentons tout d'abord des expériences effectuées avec des équations aux dérivées partielles standardes pour analyser les principales propriétés des algorithms BRF et montrer le potentiel et la flexibilité de l'approche ; une comparaison avec un code basé sur le format HSS est également fournie. Ensuite, nous expérimentons le format BRF sur des problèmes variés et de grande taille (jusqu'à une centaine de millions d'inconnues), provenant de nombreuses applications industrielles. Pour finir, nous illustrons l'utilisation de notre approche en tant que préconditionneur pour la méthode du Gradient Conjugué

The Effects of a Rebound Tumbling Program Upon Body Weight, Body Measurements, Adipose Tissue, Leg Strength, Explosive Power of the Legs, and the Endurance of College Women

The purpose of this study was to determine the effects of a rebound tumbling program on body weight, body measurements, adipose tissue, leg strength, explosive power of the legs, and the endurance of college women. During a 12 week period, 39 girls participated in the rebound tumbling unit. Each girl spent a total of three hours on the trampoline during this 12 week period. Results of the initial and final tests should that there was significant gain in body weight. There was a significant loss in the girth of the right arm, waist, right thigh, left thigh, and hips. The loss in girth for the left arm, bust, right or left calf was no significant. The loss of adipose tissue at the waist was not significant. The loss of adipose tissue on the cheek, arm, chest, back, hip, and front thigh was significant. The increase in leg strength, explosive power of the legs, and endurance was significant. In the author’s opinion, trampolining does provide physiological benefits and could be justified as a part of the physical education program