In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning, and decision-making...
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In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning, and decision-making for autonomous vehicles have led to great improvements in functional capabilities, with several prototypes already driving on our roads and streets. Yet challenges remain regarding guaranteed performance and safety under all driving circumstances. For instance, planning methods that provide safe and system-compliant performance in complex, cluttered environments while modeling the uncertain interaction with other traffic participants are required. Furthermore, new paradigms, such as interactive planning and end-to-end learning, open up questions regarding safety and reliability that need to be addressed. In this survey, we emphasize recent approaches for integrated perception and planning and for behavior-aware planning, many of which rely on machine learning. This raises the question of verification and safety, which we also touch upon. Finally, we discuss the state of the art and remaining challenges for managing fleets of autonomous vehicles.
We describe the magnetization reversal processes in multilayer elongated Ni80Fe20(10nm)/Au(t = 0 to 20 nm)/Co(20nm)/Si(001) nanorings. For a field applied in-plane along the long axis, the hysteresis loops display a t...
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We review the recent literature on financing biomedical innovation, with a specific focus on the drug development process and how it may be enhanced to improve outcomes. We begin by laying out stylized facts about the...
We review the recent literature on financing biomedical innovation, with a specific focus on the drug development process and how it may be enhanced to improve outcomes. We begin by laying out stylized facts about the structure of the drug development process and its associated costs and risks, and we present evidence that the rate of discovery for life-saving treatments has declined over time while costs have increased. We make the argument that these structural features require drug development (i.e., biopharmaceutical) firms to rely on external financing and at the same time amplify market frictions that may hinder the ability of these firms to obtain financing, especially for treatments that may have large societal value relative to the benefits going to the firms and their investors. We then provide an overview of the evidence for various types of market frictions to which these drug development firms are exposed and discuss how these frictions affect their incentive to invest in the development of new drugs, leading to underinvestment in valuable treatments. In light of this evidence, numerous studies have proposed ways to overcome this funding gap, including the use of financial innovation. We discuss the potential of these approaches to improve outcomes.
Proteolysis plays critical roles in normal and pathologic physiology; these enzymes are intricately involved in cancer progression and spread. Our understanding of protease function has advanced from nonspecific degra...
Proteolysis plays critical roles in normal and pathologic physiology; these enzymes are intricately involved in cancer progression and spread. Our understanding of protease function has advanced from nonspecific degrading enzymes to a modern appreciation of their diverse roles in posttranslational modification and signaling in a complex microenvironment. This new understanding has led to next-generation diagnostics and therapeutics that exploit protease activity in cancer. For diagnostics, protease activity may be measured as a biomarker of cancer, with wide-ranging utility from early detection to monitoring therapeutic response. Therapeutically, while broad inhibition of protease activity proved disappointing, new approaches that more specifically modulate proteases in concert with secondary targets might enable potent combination therapies. In addition, clinical evaluation is underway for tools that leverage protease activity to activate therapeutics, ranging from imaging agents that monitor surgical margins to immunotherapies with improved specificity. Technologies that interact with, measure, or modulate proteases are poised to improve cancer management on diagnostic and therapeutic fronts to realize the promise of precision medicine.
We review selected results related to the robustness of networked systems in finite and asymptotically large size regimes in static and dynamical settings. In the static setting, within the framework of flow over fini...
We review selected results related to the robustness of networked systems in finite and asymptotically large size regimes in static and dynamical settings. In the static setting, within the framework of flow over finite networks, we discuss the effect of physical constraints on robustness to loss in link capacities. In the dynamical setting, we review several settings in which small-gain-type analysis provides tight robustness guarantees for linear dynamics over finite networks toward worst-case and stochastic disturbances. We discuss network flow dynamic settings where nonlinear techniques facilitate understanding the effect, on robustness, of constraints on capacity and information, substituting information with control action, and cascading failure. We also contrast cascading failure with a representative contagion model. For asymptotically large networks, we discuss the role of network properties in connecting microscopic shocks to emergent macroscopic fluctuations under linear dynamics as well as for economic networks at equilibrium. Through this review, we aim to achieve two objectives: to highlight selected settings in which the role of the interconnectivity structure of a network in its robustness is well understood, and to highlight a few additional settings in which existing system-theoretic tools give tight robustness guarantees and that are also appropriate avenues for future network-theoretic investigations.
Die Übersetzung der bewährten Einführung in die Informatik, entstanden am Massachusetts Institute of Technology (mit), wird seit Jahren erfolgreich in der Lehre eingesetzt. Schritt für Schritt werd...
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ISBN:
(数字)9783642567063
ISBN:
(纸本)9783540423423
Die Übersetzung der bewährten Einführung in die Informatik, entstanden am Massachusetts Institute of Technology (mit), wird seit Jahren erfolgreich in der Lehre eingesetzt. Schritt für Schritt werden Konstruktion und Abstraktion von Daten und Prozeduren dargestellt. Von der Modularisierung bis zum Problemlösen mit Registermaschinen werden verschiedene Programmierparadigmen entwikckelt und die effektive Handhabung von Komplexität gezeigt. Als Programmiersprache wird SCHEME verwendet, ein Dialekt von LISP. Alle Programme laufen in jeder dem IEEE-Standard entsprechenden SCHEME-Implementierung.
The objective of a pulse-modulation (PM) system is to yield as high as possible an output signal-to-noise ratio (S/N)_{0} for a given channel signal-to-noise ratio (S/N)_{0} and bandwidth expansion factor β. In parti...
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The objective of a pulse-modulation (PM) system is to yield as high as possible an output signal-to-noise ratio (S/N)_{0} for a given channel signal-to-noise ratio (S/N)_{0} and bandwidth expansion factor β. In particular, one would like to design a modulation system in which the (S/N)_{0} approaches that of the Shannon bound (S/N)_{0} \leq [1 + (S/N)_{c}\beta^{-1}]^{\beta} . For a fixed system such as the pulse-position modulation (PPM), the relationship between (S/N)_{0} and (S/N)_{c} , must be linear above threshold. Thus to approach the β-power behavior of the Shannon bound, we must consider a family of PM systems. A class of systems is analyzed in which phase modulation of varying modulation indices is amplitude modulated by a PPM signal of fixed bandwidth. I t i s shown that when (S/N)_{c} , is large, the performance is proportional to the square of the modulation index which can be increased without changing the signal bandwidth. However, as the modulation index is increased, more sidelobes appear in the output of likelihood receiver which lead to large so-called anomolous errors. The effect of the sidelobes can be decreased significantly by redesigning the PPM signal since its autocorrelation function amplitude modulates the sidelobes. A new upper bound on the mean-squared error is derived which takes into account the effects of the noise at these sidelobe peaks. The bound depends functionally on the waveform which is used in the PPM modulator, and this raises the question as to which signal is the best one to use. An optimization problem is formulated using state-space techniques and solved numerically using a known algorithm. It is shown that it is possible to reduce the threshold significantly using optimally designed waveforms. The Barankin bounds are applied to the PPM/PM waveform to give lower bounds on the mean-squared error. It is therefore possible to bracket the actual performance region of the PPM/PM modulation system. The lower bounds lead to upp
Predicting the motion of superparamagnetic iron oxide nanoparticles (SPION) in biological systems is one of the most relevant parameters for the biomedical application of SPION. Recently, magnetic nanoparticles such a...
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