Universality Class of One-Dimensional Directed Sandpile Models

A general n-state directed `sandpile' model is introduced. The stationary properties of the n-state model are derived for n < infty, and analytical arguments based on a central limit theorem show that the model belongs to the universality class of the totally asymmetric Oslo model, with a crossover to uncorrelated branching process behavior for small system sizes. Hence, the central limit theorem allows us to identify the existence of a large universality class of one-dimensional directed sandpile models.Comment: 4 pages, 2 figure

The Temperature Evolution of the Out-of-Plane Correlation Lengths of Charge-Stripe Ordered La(1.725)Sr(0.275)NiO(4)

The temperature dependence of the magnetic order of stripe-ordered La(1.725)Sr(0.275)NiO(4) is investigated by neutron diffraction. Upon cooling, the widths if the magnetic Bragg peaks are observed to broaden. The degree of broadening is found to be very different for l = odd-integer and l = even-integer magnetic peaks. We argue that the observed behaviour is a result of competition between magnetic and charge order.Comment: 3 figure

Can the frequency-dependent specific heat be measured by thermal effusion methods?

It has recently been shown that plane-plate heat effusion methods devised for wide-frequency specific-heat spectroscopy do not give the isobaric specific heat, but rather the so-called longitudinal specific heat. Here it is shown that heat effusion in a spherical symmetric geometry also involves the longitudinal specific heat.Comment: Paper presented at the Fifth International Workshop on Complex Systems (Sendai, September, 2007), to appear in AIP Conference Proceeding

Nature-Inspired and Energy Efficient Route Planning

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KINEMATIC CHANGES AT BALL RELEASE IN BASEBALL PITCHING OVER A SIMULATED GAME OF BASEBALL

INTRODUCTION The defensive nature of baseball causes it to be dominated by the skill of the pitcher, who through speed of pitch or a combination of speed and guile in controlling the ball often determines the result of the game (Polk, 1982). Correct pitching mechanics enables a pitcher to throw the ball repeatedly at high velocities without undue risk of injury. Nowhere is this more important than in the late innings of a game. PURPOSES AND METHODS The purpose of this study was to kinematically describe and compare the changes in stride length, foot contact, ball release time, release height, ball velocity and knee, hip, and trunk angle at ball release over a simulated single game of baseball pitching in collegiate pitchers. Seven male collegiate pitchers were filmed pitching a simulated , 7inning baseball game. Each inning consisted of 14 pitches following the protocol as suggested by Potteiger, Blessing, and Wilson (1992). Every other pitch was to be thrown with 100% effort while the other pitches were to be thrown at 80% effort. The first, seventh, and thirteenth pitches of innings 1,4, and 7 were required to be fast balls and were filmed using the Peak5 2D video system. Film data were collected at 120 Hz. A Jugs radar gun was used to collect the velocity of the baseballs being pitched. A 3 x 3 analysis of variance with an alpha level set at

Higher-order temporal network effects through triplet evolution

We study the evolution of networks through ‘triplets’ — three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems