Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer

A single-celled amoeboid organism, the true slime mold Physarum polycephalum, exhibits rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. The authors previously created a biocomputer that incorporates the organism as a computing substrate to search for solutions to combinatorial optimization problems. With the assistance of optical feedback to implement a recurrent neural network model, the organism changes its shape by alternately growing and withdrawing its photosensitive branches so that its body area can be maximized and the risk of being illuminated can be minimized. In this way, the organism succeeded in finding the optimal solution to the four-city traveling salesman problem with a high probability. However, it remains unclear how the organism collects, stores, and compares information on light stimuli using the oscillatory dynamics. To study these points, we formulate an ordinary differential equation model of the amoeba-based neurocomputer, considering the organism as a network of oscillators that compete for a fixed amount of intracellular resource. The model, called the “Resource-Competing Oscillator Network (RCON) model,” reproduces well the organism’s experimentally observed behavior, as it generates a number of spatiotemporal oscillation modes by keeping the total sum of the resource constant. Designing the feedback rule properly, the RCON model comes to face a problem of optimizing the allocation of the resource to its nodes. In the problem-solving process, “greedy” nodes having the highest competitiveness are supposed to take more resource out of other nodes. However, the resource allocation pattern attained by the greedy nodes cannot always achieve a “socially optimal” state in terms of the public cost. We prepare four test problems including a tricky one in which the greedy pattern becomes “socially unfavorable” and investigate how the RCON model copes with these problems. Comparing problem-solving performances of the oscillation modes, we show that there exist some modes often attain socially favorable patterns without being trapped in the greedy one.     

A Linear-Time Algorithm for Symmetric Convex Drawings of Internally Triconnected Plane Graphs

We study a crossing minimization problem of drawing a bipartite graph with a radial drawing of two orbits. Radial drawings are one of well-known drawing conventions in social network analysis and visualization, in particular, displaying centrality indices of actors (Wasserman and Faust, Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge, 1994). The main problem in this paper is called the one-sided radial crossing minimization, if the positions of vertices in the outer orbit are fixed. The problem is known to be NP-hard (Bachmaier, IEEE Trans. Vis. Comput. Graph. 13, 583–594, 2007), and a number of heuristics are available (Bachmaier, IEEE Trans. Vis. Comput. Graph. 13, 583–594, 2007). However, there is no approximation algorithm for the crossing minimization problem in radial drawings. We present the first polynomial time constant-factor approximation algorithm for the one-sided radial crossing minimization problem.     

Optimal configuration for the self-identification of a two-dimensional variable geometry truss

This study addresses the optimal changes in geometry of a two-dimensional variable geometry truss (VGT) to identify the stiffness matrix of the truss using the concept of self-identification. The optimization of the geometry changing of the VGT is a problem of selecting the optimal combination of multiple design variables from a large number of candidate sets. This study proposes a simple optimization method for determining a set of optimal geometric parameters; in this method, the approximated mode shape matrix obtained using spline interpolation techniques is used to calculate the objective function for self-identification. The objective function used in this paper is a function of the condition number of the coefficient matrix of a linear matrix equation and a criterion for self-identification. The proposed algorithm can be used to reduce the number of actual vibration tests required for measuring the mode shapes and modal frequency while it maximizes the objective function. Numerical experiments are conducted to investigate the relationship between the convergence characteristics of the optimization and the target vibration modes. The effectiveness of the optimized geometry changing is verified by comparing the identification error for the uniform geometry changing, the optimized one for the three lower modes of the VGT, and the one found by a classical QR decomposition. Furthermore, the numerical results show that the identification sensitivity with respect to noisy data is reduced by the optimization.     

Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators

We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as a set of coupled chaotic oscillators.

Shape Reconstruction and Camera Self-Calibration Using Cast Shadows and Scene Geometries

Recently, various techniques of shape reconstruction using cast shadows have been proposed. These techniques have the advantage that they can be applied to various scenes, including outdoor scenes, without using special devices. Previously proposed techniques usually require calibration of camera parameters and light source positions, and such calibration processes limit the range of application of these techniques. In this paper, we propose a method to reconstruct 3D scenes even when the camera parameters or light source positions are unknown. The technique first recovers the shape with 4-DOF indeterminacy using coplanarities obtained by cast shadows of straight edges or visible planes in a scene, and then upgrades the shape using metric constraints obtained from the geometrical constraints in the scene. In order to circumvent the need for calibrations and special devices, we propose both linear and nonlinear methods in this paper. Experiments using simulated and real images verified the effectiveness of this technique.     

Ergonomic design and evaluation of the handle for an endoscopic dissector

The purpose of this study was to design an endoscopic dissector handle and objectively assess its usability. The handles were designed with increased contact area between the fingers and thumb and the eye rings, and the eye rings were modified to have a more perpendicular insertion angle to the finger midline. Four different handle models were compared, including a conventional product. Subjects performed dissection, exclusion, grasping, precision manipulation and precision handling tasks. Electromyography and subjective evaluations were measured. Compared to conventional handles, the designated handle reduced the muscle load in the extensor and flexor muscles of the forearm and increased subjective stability. The activity of the first dorsal interosseous muscle was sometimes influenced by the shape of the other parts. The ergonomically designed endoscopic dissector handle used in this study achieved high usability. Medical instrument designs based on ergonomic concepts should be assessed with objective indices.

Practitioner Summary: The endoscopic dissector handles were designed with increased contact area and more suitable insertion angle between the fingers and thumb and the eye rings. Compared to conventional handles, the designated handle reduced the muscle load in the extensor and flexor muscles of the forearm and increased subjective stability.     

Descent three-term conjugate gradient methods based on secant conditions for unconstrained optimization

The conjugate gradient method is an effective method for large-scale unconstrained optimization problems. Recent research has proposed conjugate gradient methods based on secant conditions to establish fast convergence of the methods. However, these methods do not always generate a descent search direction. In contrast, Y. Narushima, H. Yabe, and J.A. Ford [A three-term conjugate gradient method with sufficient descent property for unconstrained optimization, SIAM J. Optim. 21 (2011), pp. 212–230] proposed a three-term conjugate gradient method which always satisfies the sufficient descent condition. This paper makes use of both ideas to propose descent three-term conjugate gradient methods based on particular secant conditions, and then shows their global convergence properties. Finally, numerical results are given.     

Gender differences in hand stability of normal young people assessed at low force levels

To examine gender differences in hand stability, finger position and force holding tasks at low force levels were conducted with 30 male and 30 female young adults. Total fluctuation was defined as the standard deviation of measured data and fluctuation and the 10-Hz component of the physiological tremor were compared between maleand female subjects. In all tasks, the total fluctuation and the 10-Hz tremor were significantly larger in male subjects than females. On average, the fluctuation was 1.3 times larger and the 10-Hz tremor was 1.6 times larger. The results of this study suggest that women have superior hand stability compared with men at low force levels. Finger length, maximal voluntary contraction and surface electromyography were also measured and factors related to gender differences in hand stability are discussed. STATEMENT OF RELEVANCE: Hand stability is crucial for precise manual operations. This study demonstrated gender differences in hand steadiness at low force levels. Though hand dexterity cannot be explained only by hand stability, the results of this study are useful not only for occupational aptitude tests but also for neuropsychological tests.