Rethinking Presidential Eligibility

Many aspiring American Presidents have had their candidacies challenged for failing to meet the Constitution’s eligibility requirements. Although none of these challenges have ever been successful, they have sapped campaigns of valuable resources and posed a threat to several ambitious men. This Article examines several notable presidential eligibility challenges and explains why they have often been unsuccessful. The literature on presidential eligibility traditionally has focused on the Eligibility Clause, which enumerates the age, residency, and citizenship requirements that a President must satisfy before taking office. By contrast, very little of it examines how a challenge to one’s candidacy impacts a presidential campaign. This Article seeks to fill this gap. It also offers a modest proposal: Congress should pass legislation defining exactly who is eligible to be President and also implement procedural rules that would expedite presidential eligibility cases for review to the Supreme Court

Parametric versus nonparametric: the fitness coefficient

The fitness coefficient, introduced in this paper, results from a competition between parametric and nonparametric density estimators within the likelihood of the data. As illustrated on several real datasets, the fitness coefficient generally agrees with p-values but is easier to compute and interpret. Namely, the fitness coefficient can be interpreted as the proportion of data coming from the parametric model. Moreover, the fitness coefficient can be used to build a semiparamteric compromise which improves inference over the parametric and nonparametric approaches. From a theoretical perspective, the fitness coefficient is shown to converge in probability to one if the model is true and to zero if the model is false. From a practical perspective, the utility of the fitness coefficient is illustrated on real and simulated datasets

Decentralized event-triggered control over wireless sensor/actuator networks

In recent years we have witnessed a move of the major industrial automation providers into the wireless domain. While most of these companies already offer wireless products for measurement and monitoring purposes, the ultimate goal is to be able to close feedback loops over wireless networks interconnecting sensors, computation devices, and actuators. In this paper we present a decentralized event-triggered implementation, over sensor/actuator networks, of centralized nonlinear controllers. Event-triggered control has been recently proposed as an alternative to the more traditional periodic execution of control tasks. In a typical event-triggered implementation, the control signals are kept constant until the violation of a condition on the state of the plant triggers the re-computation of the control signals. The possibility of reducing the number of re-computations, and thus of transmissions, while guaranteeing desired levels of performance makes event-triggered control very appealing in the context of sensor/actuator networks. In these systems the communication network is a shared resource and event-triggered implementations of control laws offer a flexible way to reduce network utilization. Moreover reducing the number of times that a feedback control law is executed implies a reduction in transmissions and thus a reduction in energy expenditures of battery powered wireless sensor nodes.Comment: 13 pages, 3 figures, journal submissio

Isochronous Partitions for Region-Based Self-Triggered Control

In this work, we propose a region-based self-triggered control (STC) scheme for nonlinear systems. The state space is partitioned into a finite number of regions, each of which is associated to a uniform inter-event time. The controller, at each sampling time instant, checks to which region does the current state belong, and correspondingly decides the next sampling time instant. To derive the regions along with their corresponding inter-event times, we use approximations of isochronous manifolds, a notion firstly introduced in [1]. This work addresses some theoretical issues of [1] and proposes an effective computational approach that generates approximations of isochronous manifolds, thus enabling the region-based STC scheme. The efficiency of both our theoretical results and the proposed algorithm are demonstrated through simulation examples

Surface defects and temperature on atomic friction

We present a theoretical study of the effect of surface defects on atomic friction in the stick-slip dynamical regime of a minimalistic model. We focus on how the presence of defects and temperature change the average properties of the system. We have identified two main mechanisms which modify the mean friction force of the system when defects are considered. As expected, defects change locally the potential profile and thus affect the friction force. But the presence of defects also changes the probability distribution function of the tip slip length and thus the mean friction force. We corroborated both effects for different values of temperature, external load, dragging velocity and damping. We show also a comparison of the effects of surface defects and surface disorder on the dynamics of the system