Self-Stabilizing Token Distribution with Constant-Space for Trees

Self-stabilizing and silent distributed algorithms for token distribution in rooted tree networks are given. Initially, each process of a graph holds at most l tokens. Our goal is to distribute the tokens in the whole network so that every process holds exactly k tokens. In the initial configuration, the total number of tokens in the network may not be equal to nk where n is the number of processes in the network. The root process is given the ability to create a new token or remove a token from the network. We aim to minimize the convergence time, the number of token moves, and the space complexity. A self-stabilizing token distribution algorithm that converges within O(n l) asynchronous rounds and needs Theta(nh epsilon) redundant (or unnecessary) token moves is given, where epsilon = min(k,l-k) and h is the height of the tree network. Two novel ideas to reduce the number of redundant token moves are presented. One reduces the number of redundant token moves to O(nh) without any additional costs while the other reduces the number of redundant token moves to O(n), but increases the convergence time to O(nh l). All algorithms given have constant memory at each process and each link register

The basic K nuclear cluster K- pp and its enhanced formation in the p + p -> K+ + X reaction

We have studied the structure of K- pp nuclear cluster comprehensively by solving this three-body system exactly in a variational method starting from the Ansatz that the Lambda(1405) resonance (Lambda*) is a K-p bound state. We have found that our original prediction for the presence of K-pp as a compact bound system with M = 2322$MeV/c2, B = 48 MeV and Gamma = 60 MeV remains unchanged by varying the Kba-rN and NN interactions widely as far as they reproduce Lambda(1405). The structure of K- pp reveals a molecular feature, namely, the K- in Lambda* as an "atomic center" plays a key role in producing strong covalent bonding with the other proton. We have shown that the elementary process, p + p -> K+ + Lambda* + p, which occurs in a short impact parameter and with a large momentum transfer (Q ~ 1.6$ GeV/c), leads to unusually large self-trapping of Lambda* by the participating proton, since the Lambda*-p system exists as a compact doorway state propagating to K- pp (R{Lambda*-p} ~ 1.67 fm).Comment: 18 pages, 14 figures. Phys, Rev. C, in pres

Maximum Matching for Anonymous Trees with Constant Space per Process

We give a silent self-stabilizing protocol for computing a maximum matching in an anonymous network with a tree topology. The round complexity of our protocol is O(diam), where diam is the diameter of the network, and the step complexity is O(n*diam), where n is the number of processes in the network. The working space complexity is O(1) per process, although the output necessarily takes O(log(delta)) space per process, where delta is the degree of that process. To implement parent pointers in constant space, regardless of degree, we use the cyclic Abelian group Z_7

A Hardy's Uncertainty Principle Lemma in Weak Commutation Relations of Heisenberg-Lie Algebra

In this article we consider linear operators satisfying a generalized commutation relation of a type of the Heisenberg-Lie algebra. It is proven that a generalized inequality of the Hardy's uncertainty principle lemma follows. Its applications to time operators and abstract Dirac operators are also investigated

Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints

Biomimetic, dexterous robotic hands have the potential to replicate much of the tasks that a human can do, and to achieve status as a general manipulation platform. Recent advances in reinforcement learning (RL) frameworks have achieved remarkable performance in quadrupedal locomotion and dexterous manipulation tasks. Combined with GPU-based highly parallelized simulations capable of simulating thousands of robots in parallel, RL-based controllers have become more scalable and approachable. However, in order to bring RL-trained policies to the real world, we require training frameworks that output policies that can work with physical actuators and sensors as well as a hardware platform that can be manufactured with accessible materials yet is robust enough to run interactive policies. This work introduces the biomimetic tendon-driven Faive Hand and its system architecture, which uses tendon-driven rolling contact joints to achieve a 3D printable, robust high-DoF hand design. We model each element of the hand and integrate it into a GPU simulation environment to train a policy with RL, and achieve zero-shot transfer of a dexterous in-hand sphere rotation skill to the physical robot hand.Comment: for project website, see https://srl-ethz.github.io/get-ball-rolling/ . for video, see https://youtu.be/YahsMhqNU8o . Submitted to the 2023 IEEE-RAS International Conference on Humanoid Robot

Synchronization of spontaneous eyeblinks while viewing video stories

Blinks are generally suppressed during a task that requires visual attention and tend to occur immediately before or after the task when the timing of its onset and offset are explicitly given. During the viewing of video stories, blinks are expected to occur at explicit breaks such as scene changes. However, given that the scene length is unpredictable, there should also be appropriate timing for blinking within a scene to prevent temporal loss of critical visual information. Here, we show that spontaneous blinks were highly synchronized between and within subjects when they viewed the same short video stories, but were not explicitly tied to the scene breaks. Synchronized blinks occurred during scenes that required less attention such as at the conclusion of an action, during the absence of the main character, during a long shot and during repeated presentations of a similar scene. In contrast, blink synchronization was not observed when subjects viewed a background video or when they listened to a story read aloud. The results suggest that humans share a mechanism for controlling the timing of blinks that searches for an implicit timing that is appropriate to minimize the chance of losing critical information while viewing a stream of visual events

Slowing and Loss of Complexity in Alzheimer's EEG: Two Sides of the Same Coin?

Medical studies have shown that EEG of Alzheimer's disease (AD) patients is “slower” (i.e., contains more low-frequency power) and is less complex compared to age-matched healthy subjects. The relation between those two phenomena has not yet been studied, and they are often silently assumed to be independent. In this paper, it is shown that both phenomena are strongly related. Strong correlation between slowing and loss of complexity is observed in two independent EEG datasets: (1) EEG of predementia patients (a.k.a. Mild Cognitive Impairment; MCI) and control subjects; (2) EEG of mild AD patients and control subjects. The two data sets are from different patients, different hospitals and obtained through different recording systems. The paper also investigates the potential of EEG slowing and loss of EEG complexity as indicators of AD onset. In particular, relative power and complexity measures are used as features to classify the MCI and MiAD patients versus age-matched control subjects. When combined with two synchrony measures (Granger causality and stochastic event synchrony), classification rates of 83% (MCI) and 98% (MiAD) are obtained. By including the compression ratios as features, slightly better classification rates are obtained than with relative power and synchrony measures alone

Loosely-Stabilizing Leader Election with Polylogarithmic Convergence Time

A loosely-stabilizing leader election protocol with polylogarithmic convergence time in the population protocol model is presented in this paper. In the population protocol model, which is a common abstract model of mobile sensor networks, it is known to be impossible to design a self-stabilizing leader election protocol. Thus, in our prior work, we introduced the concept of loose-stabilization, which is weaker than self-stabilization but has similar advantage as self-stabilization in practice. Following this work, several loosely-stabilizing leader election protocols are presented. The loosely-stabilizing leader election guarantees that, starting from an arbitrary configuration, the system reaches a safe configuration with a single leader within a relatively short time, and keeps the unique leader for an sufficiently long time thereafter. The convergence times of all the existing loosely-stabilizing protocols, i.e., the expected time to reach a safe configuration, are polynomial in n where n is the number of nodes (while the holding times to keep the unique leader are exponential in n). In this paper, a loosely-stabilizing protocol with polylogarithmic convergence time is presented. Its holding time is not exponential, but arbitrarily large polynomial in n