I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.

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Design, fabrication and control of soft robots

http://www.cs.unibo.it/~montesi/CBD/Articoli/SurvyBigData2.pdf

Data-intensive applications, challenges, techniques and technologies: A survey on Big Data

‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and, drawing on a number of examples, details how cities are being instrumented with digital devices and infrastructure that produce ‘big data’. Such data, smart city advocates argue enables real-time analysis of city life, new modes of urban governance, and provides the raw material for envisioning and enacting more efficient, sustainable, competitive, productive, open and transparent cities. The final section of the paper provides a critical reflection on the implications of big data and smart urbanism, examining five emerging concerns: the politics of big urban data, technocratic governance and city development, corporatisation of city governance and technological lock-ins, buggy, brittle and hackable cities, and the panoptic city.

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The real-time city? Big data and smart urbanism

This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology.

https://journals.sagepub.com/doi/pdf/10.1177/2053951714528481

Big Data, new epistemologies and paradigm shifts:

Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database As scale and demand increase, so does Complexity Fortunately, scalability and simplicity are not mutually exclusiverather than using some trendy technology, a different approach is needed Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning Also available is all code from the book

Big Data: Principles and best practices of scalable realtime data systems

With the increasing complexity of humanoid mechanisms and their desired capabilities, there is a pressing need for a generalized framework where a desired whole-body motion behavior can be easily specified and controlled. Our hypothesis is that human motion results from simultaneously performing multiple objectives in a hierarchical manner, and we have analogously developed a prioritized, multiple-task control framework. The operational space formulation10 provides dynamic models at the task level and structures for decoupled task and posture control.13 This formulation allows for posture objectives to be controlled without dynamically interfering with the operational task. Achieving higher performance of posture objectives requires precise models of their dynamic behaviors. In this paper we complete the picture of task descriptions and whole-body dynamic control by establishing models of the dynamic behavior of secondary task objectives within the posture space. Using these models, we present a whole-body control framework that decouples the interaction between the task and postural objectives and compensates for the dynamics in their respective spaces.

/pdf/whole-body-dynamic-behavior-and-control-of-human-like-robots-7urz3atv55.pdf

Whole-body dynamic behavior and control of human-like robots

A task-level control framework is proposed for providing feedback control in the simulation of goal-directed human motion. An operational space approach, adapted from the field of robotics, is used for this purpose. This approach is augmented by a significant new extension directed at addressing the control of muscle-driven systems. Task/posture decomposition is intrinsically exploited, allowing human musculoskeletal properties to direct postural behavior during the performance of a task. This paper also describes a simulation architecture for generating musculoskeletal simulations of human characters. The evolving capabilities of the collective environment are directed toward autonomously generating realistic motion control for virtual actors in interactive computer graphics applications, as well as synthesizing the control of human-like motion in robotic systems.

/pdf/simulating-the-task-level-control-of-human-motion-a-1l5ko0aikp.pdf

Simulating the task-level control of human motion: a methodology and framework for implementation

Generating coordinated natural motion in human-like robotic structures has proved to be a challenging task. Given that humans easily solve this problem, we propose a methodology to devise the underlying strategies of human movement and apply them for robotic control. We use this approach to examine how humans utilize their muscles while performing positioning tasks. This analysis suggests an effort potential that is shown to characterize human postural motion. By applying this methodology to other criteria, we seek to establish a basis of human motion characteristics.

/pdf/human-like-motion-from-physiologically-based-potential-4er1kglrwv.pdf

Human-Like Motion from Physiologically-Based Potential Energies

A question of some interest in computational statistical mechanics is whether macroscopic quantities can be accurately computed without detailed resolution of the fastest scales in the problem. To address this question a simple model for a distinguished particle immersed in a heat bath is studied (due to Ford and Kac). The model yields a Hamiltonian system of dimension 2N+2 for the distinguished particle and the degrees of freedom describing the bath. It is proven that, in the limit of an infinite number of particles in the heat bath (N→∞), the motion of the distinguished particle is governed by a stochastic differential equation (SDE) of dimension 2. Numerical experiments are then conducted on the Hamiltonian system of dimension 2N+2 (N≫1) to investigate whether the motion of the distinguished particle is accurately computed (i.e., whether it is close to the solution of the SDE) when the time step is small relative to the natural time scale of the distinguished particle, but the product of the fastest frequency in the heat bath and the time step is not small—the underresolved regime in which many computations are performed. It is shown that certain methods accurately compute the limiting behavior of the distinguished particle, while others do not. Those that do not are shown to compute a different, incorrect, macroscopic limit.

/pdf/analysis-and-experiments-for-a-computational-model-of-a-heat-2dxktigofn.pdf

James Warren

Papers

Big Data: Principles and best practices of scalable realtime data systems

Whole-body dynamic behavior and control of human-like robots

Simulating the task-level control of human motion: a methodology and framework for implementation

Human-Like Motion from Physiologically-Based Potential Energies

Analysis and Experiments for a Computational Model of a Heat Bath