Role of Stripes in Spin and Charge Dynamics of Underdoped La2−x Sr x CuO4

We investigate the electronic states of underdoped La _2–x Sr _x CuO ₄ (LSCO) by using a microscopic model, i.e., t-t-t-J model, containing charge stripes. The numerically exact diagonalization calculation is employed on small clusters. The physical properties observed in the angle-resolved photoemission and optical conductivity experiments are consistently explained in the model with vertical stripes, but not diagonal ones. These results demonstrate a crucial role of the vertical stripes in underdoped LSCO.     

Adaptive backstepping control of wheeled inverted pendulum with velocity estimator

In this paper, we introduce a backstepping control design of a wheeled inverted pendulum. Based on a second-order motion equation of the body angle, an adaptive integral backstepping controller is designed to stabilize the body angle. It is shown that the σ-modification rule in the adaptive update law guarantees the boundedness of the errors in estimating the time-varying signal that is an output of a linear system with every bounded input signal. Then, the stabilizing controller for the wheel angle is constructed by a PD-type positive feedback. The derived controller requires the full-state measurements. In the output feedback case, the K filter or the observer backstepping is needed. However, the structure of the controller becomes complicated. We propose a non-model-based differentiator based on the adaptive update law. Since the non-model-based differentiator does not require any knowledge of the dynamic structure of the signal, we can use it as a velocity estimator for unknown nonlinear systems. Therefore, we replaced the velocity measurement with the estimates by the non-model-based differentiator. Finally, simulation results for the proposed controller are presented.     

Design of a grid service-based platform for in silico protein-ligand screenings

Grid computing offers the powerful alternative of sharing resources on a worldwide scale, across different institutions to run computationally intensive, scientific applications without the need for a centralized supercomputer. Much effort has been put into development of software that deploys legacy applications on a grid-based infrastructure and efficiently uses available resources. One field that can benefit greatly from the use of grid resources is that of drug discovery since molecular docking simulations are an integral part of the discovery process. In this paper, we present a scalable, reusable platform to choreograph large virtual screening experiments over a computational grid using the molecular docking simulation software DOCK. Software components are applied on multiple levels to create automated workflows consisting of input data delivery, job scheduling, status query, and collection of output to be displayed in a manageable fashion for further analysis. This was achieved using Opal OP to wrap the DOCK application as a grid service and PERL for data manipulation purposes, alleviating the requirement for extensive knowledge of grid infrastructure. With the platform in place, a screening of the ZINC 2,066,906 compound "drug-like" subset database against an enzyme's catalytic site was successfully performed using the MPI version of DOCK 5.4 on the PRAGMA grid testbed. The screening required 11.56 days laboratory time and utilized 200 processors over 7 clusters.     

Estimation of a nonvisible field-of-view mobile target incorporating optical and acoustic sensors

This paper presents a nonvisible field-of-view (NFOV) target estimation approach that incorporates optical and acoustic sensors. An optical sensor can accurately localize a target in its field-of-view whereas the acoustic sensor could estimate the target location over a much larger space, but only with limited accuracy. A recursive Bayesian estimation framework where observations of the optical and acoustic sensors are probabilistically treated and fused is proposed in this paper. A technique to construct the observation likelihood when two microphones are used as the acoustic sensor is also described. The proposed technique derives and stores the interaural level difference of observations from the two microphones for different target positions in advance and constructs the likelihood through correlation. A parametric study of the proposed acoustic sensing technique in a controlled test environment, and experiments with an NFOV target in an actual indoor environment are presented to demonstrate the capability of the proposed technique.     

Mathematics based on incremental learning—Excluded middle and inductive inference

Learning theoretic aspects of mathematics and logic have been studied by many authors. They study how mathematical and logical objects are algorithmically “learned” (inferred) from finite data. Although they study mathematical objects, the objective of the studies is learning. In this paper, a mathematics whose foundation itself is learning theoretic will be introduced. It is called Limit-Computable Mathematics. It was originally introduced as a means for “Proof Animation”, which is expected to make interactive formal proof development easier. Although the original objective was not learning theoretic at all, learning theory is indispensable for our research. It suggests that logic and learning theory are related in a still unknown but deep new way.     

Study on fabrication of 3-D microstructures by synchrotron radiation based on pixels exposed lithography

We report research on the development of a method of fabricating three-dimensional microstructures that uses synchrotron radiation light. Some research on three-dimensional processing methods using SR lithography has already been reported. They have involved techniques of applying exposure energy distributions to resist surfaces. Complicated energy distributions need to be applied to resist surfaces to fabricate arbitrary three-dimensional structures. However, we devised a new method that made it possible to fabricate arbitrary three-dimensional microstructures by using a mask with pattern created function. The advantages of this method are that it is suitable for rapid prototyping and it reduces the fabrication time and cost since it is not necessary to fabricate conventional photolithographic masks. Our research involved a basic experiment on this method of fabrication where we succeeded in fabricating a free-form surface by exposing it through an overlapping array of pixels that created a single aperture. Moreover, the pixel size could be made smaller than the aperture size by overlapping adjoining pixels.     

Network coding-based reliable multicast in wireless networks

Reliable multicast, the lossless dissemination of data from one sender to a group of receivers, has a wide range of important applications. Recently, network coding has been applied to the reliable multicast in wireless networks, where multiple lost packets with distinct intended receivers are XOR-ed together as one packet and forwarded via single retransmission, resulting in a significant reduction of bandwidth consumption. However, the simple XOR operation cannot fully exploit the potential coding opportunities and finding the optimal set of lost packets for XOR-ing is a complex NP-complete optimization problem. In this work, we intend to move beyond the simple XOR to more general coding operations. Specifically, we propose two new schemes (a static scheme which repeatedly retransmits one coding packet until all intended receivers receive it and a dynamic scheme which updates the coding packet once one or more receivers receive it) to encode packets with more general coding operations, which not only can encode lost packets with common intended receivers together to fully exploit the potential coding opportunities but also have polynomial-time complexity. We demonstrate, through both analytical and simulation results, that the proposed schemes can more greatly reduce the bandwidth requirement than the available coding-based schemes, especially in the case of high packet loss probabilities and a larger number of receivers. This reduction can vary from a few percents to over 15% depending on the packet loss probabilities and the number of receivers.     

Nonlinear control for rotational movement of cart-pendulum system using homoclinic orbit

In this paper, we deal with the control method for rotational movements of a pendulum using a separatrix. We design a controller that attains a homoclinic motion or a heteroclinic motion of the pendulum and the asymptotic stability of the cart by using a kind of forwarding control design. First, we derive a controller that converges to a homoclinic orbit via a Lyapunov function of the pendulum subsystem. Next, we give a nonlinear stabilizing controller via another Lyapunov function of the cart subsystem. Moreover, using the third Lyapunov function and adding a complementary control input, we guarantee that the pendulum converges to the homoclinic orbit and the cart is stabilized. Finally, the simulation and the experiment using the rapid controller prototyping system based on MATLAB/Simulink are performed to demonstrate the forward upward circling and the giant swing of the pendulum.     

Development of anthropomorphic multi-D.O.F. master-slave arm for mutual telexistence

We developed a robotic arm for a master-slave system to support "mutual telexistence", which realizes remote dexterous manipulation tasks and close physical communication with other people using gestures. In this paper, we describe the specifications of the experimental setup of the master-slave arm to demonstrate the feasibility of the mutual telexistence concept. We developed the master arm of a telexistence robot for interpersonal communication. The last degree of the 7-degree-of-freedom slave arm is resolved by placing a small orientation sensor on the operator's arm. This master arm is made light and impedance control is applied in order to grant the operator as much freedom of movement as possible. For this development stage, we compared three control methods and confirmed that the impedance control method is the most appropriate to this system.     

Probabilistic enhancement of approximate indexing in metric spaces

Some approximate indexing schemes have been recently proposed in metric spaces which sort the objects in the database according to pseudo-scores. It is known that (1) some of them provide a very good trade-off between response time and accuracy, and (2) probability-based pseudo-scores can provide an optimal trade-off in range queries if the probabilities are correctly estimated. Based on these facts, we propose a probabilistic enhancement scheme which can be applied to any pseudo-score based scheme. Our scheme computes probability-based pseudo-scores using pseudo-scores obtained from a pseudo-score based scheme. In order to estimate the probability-based pseudo-scores, we use the object-specific parameters in logistic regression and learn the parameters using MAP (Maximum a Posteriori) estimation and the empirical Bayes method. We also propose a technique which speeds up learning the parameters using pseudo-scores. We applied our scheme to the two state-of-the-art schemes: the standard pivot-based scheme and the permutation-based scheme, and evaluated them using various kinds of datasets from the Metric Space Library. The results showed that our scheme outperformed the conventional schemes, with regard to both the number of distance computations and the CPU time, in all the datasets.