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At the cutting edge of materials science, matter is designed to self-organize into structures that perform a wide range of functions. The past two decades have witnessed major innovations in the versatility of building blocks, ranging from…

Soft Condensed Matter · Physics 2022-09-26 Angus McMullen , Maitane Muñoz Basagoiti , Zorana Zeravcic , Jasna Brujic

The mechanics of an oriented point (point with "spin") based on 3D and 4D Frenet equations is considered. In such mechanics there is an opportunity to describe formally any physical trajectory of a particle with own rotation. We use…

General Relativity and Quantum Cosmology · Physics 2017-02-09 Trukhanova Mariya , Shipov Gennady

The generation of unidirectional motion has been a long-standing challenge in engineering of molecular motors and, more generally, machines. A molecular motor is characterized by a set of low energy states that differ in their…

Mixed order phase transitions (MOT), which display discontinuous order parameter and diverging correlation length, appear in several seemingly unrelated settings ranging from equilibrium models with long-range interactions to models far…

Statistical Mechanics · Physics 2015-06-22 Amir Bar , David Mukamel

In this paper, we study the machine learning elements which we are interested in together as a machine learning system, consisting of a collection of machine learning elements and a collection of relations between the elements. The…

Machine Learning · Computer Science 2025-02-05 Xiuzhan Guo

An oblivious mobile robot is a stateless computational entity located in a spatial universe, capable of moving in that universe. When activated, the robot observes the universe and the location of the other robots, chooses a destination,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-11 Paola Flocchini , Nicola Santoro , Giovanni Viglietta , Masafumi Yamashita

Robotic manipulation of slender objects is challenging, especially when the induced deformations are large and nonlinear. Traditionally, learning-based control approaches, such as imitation learning, have been used to address deformable…

Robotics · Computer Science 2024-02-21 Andrew Choi , Dezhong Tong , Demetri Terzopoulos , Jungseock Joo , M. Khalid Jawed

Here we report on the translocation of folded polymers through nano-pores using molecular dynamic simulations. Two cases are studied; one in which a folded molecule unfolds upon passage and one in which the folding remains intact as the…

Soft Condensed Matter · Physics 2016-03-23 Narges Nikoofard , Alireza Mashaghi

This paper introduces a simulation study of fluid actuated multi-driven closed system as spherical mobile robot called "RollRoller". Robot's mechanism design consists of two essential parts: tubes to lead a core and mechanical controlling…

Robotics · Computer Science 2016-10-21 Seyed Amir Tafrishi , Sandor M. Veres , Esmaeil Esmaeilzadeh , Mikhail Svinin

In topological quantum computation the geometric details of a particle trajectory are irrelevant; only the topology matters. Taking this one step further, we consider a model of computation that disregards even the topology of the particle…

Quantum Physics · Physics 2011-06-03 Stephen P. Jordan

Humanoid robots are machines built with an anthropomorphic shape. Despite decades of research into the subject, it is still challenging to tackle the robot locomotion problem from an algorithmic point of view. For example, these machines…

Robotics · Computer Science 2020-04-28 Stefano Dafarra

We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is…

Neural and Evolutionary Computing · Computer Science 2014-12-11 Alex Graves , Greg Wayne , Ivo Danihelka

Natural filaments, such as proteins, plant tendrils, octopus tentacles, and elephant trunks, can transform into arbitrary three-dimensional shapes that carry out vital functions. Their shape-morphing behavior arises from intricate…

A hallmark of biological intelligence and control is combinatorial generalization: animals are able to learn various things, then piece them together in new combinations to produce appropriate outputs for new tasks. Inspired by the ability…

Neurons and Cognition · Quantitative Biology 2022-10-07 Sunny Duan , Mikail Khona , Adrian Bertagnoli , Sarthak Chandra , Ila Fiete

Molecular modeling, a central topic in quantum mechanics, aims to accurately calculate the properties and simulate the behaviors of molecular systems. The molecular model is governed by physical laws, which impose geometric constraints such…

Machine Learning · Computer Science 2024-06-25 Tianlang Chen , Shengjie Luo , Di He , Shuxin Zheng , Tie-Yan Liu , Liwei Wang

Linear bio-molecular motors move unidirectionally along a track by coordinating several different processes, such as fuel (ATP) capture, hydrolysis, conformational changes, binding and unbinding from a track, and center-of-mass diffusion. A…

Statistical Mechanics · Physics 2015-05-18 Nathan J. Kuwada , Gerhard A. Blab , Heiner Linke

Moving a module in a modular robot is a very complex and error-prone process. Unlike in swarm, in the modular robots we are targeting, the moving module must keep the connection to, at least, one other module. In order to miniaturize each…

Robotics · Computer Science 2020-05-08 Benoit Piranda , Julien Bourgeois

Understanding how monomeric proteins fold under in vitro conditions is crucial to describing their functions in the cellular context. Significant advances both in theory and experiments have resulted in a conceptual framework for describing…

Soft Condensed Matter · Physics 2010-07-20 D. Thirumalai , Edward P. O'Brien , Greg Morrison , Changbong Hyeon

In this paper, we study a discrete system of entities residing on a two-dimensional square grid. Each entity is modelled as a node occupying a distinct cell of the grid. The set of all $n$ nodes forms initially a connected shape $A$.…

Data Structures and Algorithms · Computer Science 2019-04-30 Abdullah Almethen , Othon Michail , Igor Potapov

Kernel methods are powerful machine learning techniques which implement generic non-linear functions to solve complex tasks in a simple way. They Have a solid mathematical background and exhibit excellent performance in practice. However,…

Machine Learning · Computer Science 2021-01-27 J. Emmanuel Johnson , Valero Laparra , Adrián Pérez-Suay , Miguel D. Mahecha , Gustau Camps-Valls