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Dynamic Walking: Toward Agile and Efficient Bipedal Robots

control, Robotics, and Autonomous Systems 1000年第1期4卷 535-572页

作者： Jenna Reher Aaron D. Ames 1Department of Mechanical and Civil Engineering California Institute of Technology Pasadena California 91125 USA email: jreher@caltech.eduames@caltech.edu 2Control and Dynamical Systems Graduate Program California Institute of Technology Pasadena California 91125 USA

Dynamic walking on bipedal robots has evolved from an idea in science fiction to a practical reality. This is due to continued progress in three key areas: a mathematical understanding of locomotion, the computational ability to encode this mathematics through optimization, and the hardware capable of realizing this understanding in practice. In this context, this review outlines the end-to-end process of methods that have proven effective in the literature for achieving dynamic walking on bipedal robots. We begin by introducing mathematical models of locomotion, from reduced-order models that capture essential walking behaviors to hybrid dynamical systems that encode the full-order continuous dynamics along with discrete foot-strike dynamics. These models form the basis for gait generation via (nonlinear) optimization problems. Finally, models and their generated gaits merge in the context of real-time control, wherein walking behaviors are translated to hardware. The concepts presented are illustrated throughout in simulation, and experimental instantiations on multiple walking platforms are highlighted to demonstrate the ability to realize dynamic walking on bipedal robots that is both agile and efficient.

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Macroeconomic Models for Monetary Policy: A Critical Review from a Finance Perspective

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Financial Economics 1000年第1期12卷 95-140页

作者： Winston W. Dou Andrew W. Lo Ameya Muley Harald Uhlig 1Department of Finance The Wharton School University of Pennsylvania Philadelphia Pennsylvania 19104 USA email: wdou@wharton.upenn.edu 3Santa Fe Institute Santa Fe New Mexico 87501 USA 2Sloan School of Management Laboratory for Financial Engineering and Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge Massachusetts 02142 USA email: alo-admin@mit.edu 4Department of Economics Massachusetts Institute of Technology Cambridge Massachusetts 02142 USA email: ameyamuley@*** 5Department of Economics University of Chicago Chicago Illinois 60637 USA email: huhlig@uchicago.edu

We provide a critical review of macroeconomic models used for monetary policy at central banks from a finance perspective. We review the history of monetary policy modeling, survey the core monetary models used by major central banks, and construct an illustrative model for those readers who are unfamiliar with the literature. Within this framework, we highlight several important limitations of current models and methods, including the fact that local-linearization approximations omit important nonlinear dynamics, yielding biased impulse-response analysis and parameter estimates. We also propose new features for the next generation of macrofinancial policy models, including a substantial role for the financial sector, the government balance sheet, and unconventional monetary policies; heterogeneity, reallocation, and redistribution effects;the macroeconomic impact of large nonlinear risk premium dynamics; time-varying uncertainty; financial sector and systemic risks; imperfect product market and markups; and further advances in solution, estimation, and evaluation methods for dynamic quantitative structural models.

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Measuring the Functioning Human Brain

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Statistics and Its Application 1000年第1期12卷 283-309页

作者： Martin A. Lindquist Bonnie B. Smith Arunkumar Kannan Angela Zhao Brian Caffo 1Department of Biostatistics Johns Hopkins University Baltimore Maryland USA email: mlindqui@jhsph.edu 2Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland USA

The emergence of functional magnetic resonance imaging (fMRI) marked a significant technological breakthrough in the real-time measurement of the functioning human brain in vivo. In part because of their 4D nature (three spatial dimensions and time), fMRI data have inspired a great deal of statistical development in the past couple of decades to address their unique spatiotemporal properties. This article provides an overview of the current landscape in functional brain measurement, with a particular focus on fMRI, highlighting key developments in the past decade. Furthermore, it looks ahead to the future, discussing unresolved research questions in the community and outlining potential research topics for the future.

关键词： fMRI functional magnetic resonance imaging brain connectivity prediction resting-state fMRI statistics

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Nanoscale Electrokinetics and Microvortices: How Microhydrodynamics Affects Nanofluidic Ion Flux

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Fluid Mechanics 1000年第1期44卷 401-426页

作者： Hsueh-Chia Chang Gilad Yossifon Evgeny A. Demekhin 1Department of Chemical and Biomolecular Engineering Center for Microfluidics and Medical Diagnostics University of Notre Dame Notre Dame Indiana 46556 email: hchang@nd.edu 2Faculty of Mechanical Engineering Micro- and Nanofluidics Laboratory Technion – Israel Institute of Technology Technion City 32000 Israel email: yossifon@tx.technion.ac.il 3Department of Computational Mathematics and Computer Science Kuban State University Krasnodar 350040 Russia email: edemekhi@***

When a direct current (DC) electric field is applied across an ion-selective nanoporous membrane or a nanochannel with an overlapping Debye layer, a surprising microvortex instability occurs on the side of the membrane/channel through which counterions enter. Despite its micro and nano length scales, this instability exhibits all the hallmarks of other classical hydrodynamic instabilities—a subharmonic cascade, a wide-band fluctuation spectrum, and a coherent structure dominated by spatiotemporal dynamics. Moreover, the resulting convection enhances the ion flux into the ion-selective medium and gives rise to an overlimiting-current bifurcation in the current-voltage relationship. This hydrodynamically driven nonequilibrium ion flux does not seem to have any equivalent in cell membrane ion channels. Yet, by introducing asymmetric entrances to provide different polarized regions and/or viscous arrest of the vortex instability, one can fabricate a hydrodynamic nanofluidic diode. With other modifications, hysteretic, excitable, and oscillatory ion flux dynamics could also be elicited—all with strong hydrodynamic features.

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Extrachromosomal DNA in Cancer

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Genomics and Human Genetics 1000年第1期23卷 29-52页

作者： Vineet Bafna Paul S. Mischel 1Department of Computer Science and Engineering and Halıcıoğlu Data Science Institute University of California San Diego La Jolla California USA email: vbafna@cs.ucsd.edu 2Department of Pathology and ChEM-H Stanford University School of Medicine Stanford California USA email: pmischel@stanford.edu

In cancer, complex genome rearrangements and other structural alterations, including the amplification of oncogenes on circular extrachromosomal DNA (ecDNA) elements, drive the formation and progression of tumors. ecDNA is a particularly challenging structural alteration. By untethering oncogenes from chromosomal constraints, it elevates oncogene copy number, drives intratumoral genetic heterogeneity, promotes rapid tumor evolution, and results in treatment resistance. The profound changes in DNA shape and nuclear architecture generated by ecDNA alter the transcriptional landscape of tumors by catalyzing new types of regulatory interactions that do not occur on chromosomes. The current suite of tools for interrogating cancer genomes is well suited for deciphering sequence but has limited ability to resolve the complex changes in DNA structure and dynamics that ecDNA generates. Here, we review the challenges of resolving ecDNA form and function and discuss the emerging tool kit for deciphering ecDNA architecture and spatial organization, including what has been learned to date about how this dramatic change in shape alters tumor development, progression, and drug resistance.

关键词： ecDNA cancer homogeneously staining regions HSRs ecDNA evolution ecDNA hubs enhancer hijacking

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A Perspective on Incentive Design: Challenges and Opportunities

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control, Robotics, and Autonomous Systems 1000年第1期2卷 305-338页

作者： Lillian J. Ratliff Roy Dong Shreyas Sekar Tanner Fiez 1Department of Electrical Engineering University of Washington Seattle Washington 98195 USA email: ratliffl@uw.edu 2Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana Illinois 61801 USA

The increasingly tight coupling between humans and system operations in domains ranging from intelligent infrastructure to e-commerce has led to a challenging new class of problems founded on a well-established area of research: incentive design. There is a clear need for a new tool kit for designing mechanisms that help coordinate self-interested parties while avoiding unexpected outcomes in the face of information asymmetries, exogenous uncertainties from dynamic environments, and resource constraints. This article provides a perspective on the current state of the art in incentive design from three core communities—economics, control theory, and machine learning—and highlights interesting avenues for future research at the interface of these domains.

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Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes

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Biomedical Data Science 1000年第1期7卷 369-389页

作者： Anthony Cesnik Leah V. Schaffer Ishan Gaur Mayank Jain Trey Ideker Emma Lundberg 1Department of Bioengineering Stanford University Stanford California USA email: emmalu@stanford.edu 2Department of Medicine University of California San Diego La Jolla California USA email: tideker@health.ucsd.edu 3Departments of Computer Science and Engineering and Bioengineering University of California San Diego La Jolla California USA 4Department of Pathology Stanford University Palo Alto California USA 5Science for Life Laboratory School of Engineering Sciences in Chemistry Biotechnology and Health KTH Royal Institute of Technology Stockholm Sweden 6Chan Zuckerberg Biohub San Francisco California USA

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

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control of Low-Inertia Power Systems

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control, Robotics, and Autonomous Systems 1000年第1期6卷 415-445页

作者： Florian Dörfler Dominic Groß 1Automatic Control Laboratory ETH Zurich Zurich Switzerland email: dorfler@ethz.ch 2Department of Electrical and Computer Engineering University of Wisconsin–Madison Madison Wisconsin USA email: dominic.gross@wisc.edu

Electric power systems are undergoing an unprecedented transition from fossil fuel–based power plants to low-inertia systems that rely predominantly on power electronics and renewable energy resources. This article reviews the resulting control challenges and modeling fallacies, at both the device and system level, and focuses on novel aspects or classical concepts that need to be revised in light of the transition to low-inertia systems. To this end, we survey the literature on modeling of low-inertia systems, review research on the control of grid-connected power converters, and discuss the frequency dynamics of low-inertia systems. Moreover, we discuss system-level services from a control perspective. Overall, we conclude that the system-theoretic mindset is essential to bridge different research communities and understand the complex interactions of power electronics, electric machines, and their controls in large-scale low-inertia power systems.

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Mixed Semiconductor Alloys for Optical Devices

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Chemical and Biomolecular engineering 1000年第1期4卷 187-209页

作者： Thomas F. Kuech Luke J. Mawst April S. Brown 1Department of Chemical and Biological Engineering 2Department of Electrical and Computer Engineering University of Wisconsin–Madison Madison Wisconsin 53706 email: kuech@engr.wisc.edu mawst@engr.wisc.edu abrown@ee.duke.edu 3Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708

There is an increasing technological need for a wider array of semiconducting materials that will allow greater control over the physical and electronic structure within multilayer heterostructures. This need has led to an expansion in the range of semiconducting alloys explored and used in new applications. These alloy semiconductors are often complicated by a limited range of miscibility. The current research has focused on the properties, stability, and detailed chemistry required to realize these materials. The use of synthetic conditions that permit the growth of these alloys to be dominated by kinetic rather than mass-transport considerations has allowed many of these nominally unstable materials to be grown and used in device structures. These materials have found important applications within optical communications as emitters and detectors and in solid-state lighting.

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Formal Methods for control Synthesis: An Optimization Perspective

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control, Robotics, and Autonomous Systems 1000年第1期2卷 115-140页

作者： Calin Belta Sadra Sadraddini 1Department of Mechanical Engineering Boston University Boston Massachusetts 02215 USA email: cbelta@bu.edu 2Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA email: sadra@mit.edu

In control theory, complicated dynamics such as systems of (nonlinear) differential equations are controlled mostly to achieve stability. This fundamental property, which can be with respect to a desired operating point or a prescribed trajectory, is often linked with optimality, which requires minimizing a certain cost along the trajectories of a stable system. In formal verification (model checking), simple systems, such as finite-state transition graphs that model computer programs or digital circuits, are checked against rich specifications given as formulas of temporal logics. The formal synthesis problem, in which the goal is to synthesize or control a finite system from a temporal logic specification, has recently received increased interest. In this article, we review some recent results on the connection between optimal control and formal synthesis. Specifically, we focus on the following problem: Given a cost and a correctness temporal logic specification for a dynamical system, generate an optimal control strategy that satisfies the specification. We first provide a short overview of automata-based methods, in which the dynamics of the system are mapped to a finite abstraction that is then controlled using an automaton corresponding to the specification. We then provide a detailed overview of a class of methods that rely on mapping the specification and the dynamics to constraints of an optimization problem. We discuss advantages and limitations of these two types of approaches and suggest directions for future research.

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