The (Lack of) Gender Dynamics of Gubernatorial Executive Orders

How do governors utilize state executive orders to effect policy changes? Are there differences between male and female governors? Though various works have examined the dynamics of presidential executive orders, few have examined how governors employ executive orders at the state level. We present results of a pilot study on how gender influences use of gubernatorial executive orders. Contrary to much of the literature on gender dynamics, we find minimal differences in the ways that female and male governors use gubernatorial executive orders. Female governors do not appear to rely more or less on unilateral orders than do their male colleagues. Although we do find some evidence that female governors are less likely to issue cultural and economic executive orders than socialissue and public-health executive orders, the difference between female and male governors across most issue areas is minimal. These results have important implications on studies of gender dynamics, the unilateral executive, and gubernatorial behavior

Strong and Confined Acids Enable a Catalytic Asymmetric Nazarov Cyclization of Simple Divinyl Ketones

We report a catalytic asymmetric Nazarov cyclization of simple, acylic, alkyl-substituted divinyl ketones using our recently disclosed strong and confined imidodiphosphorimidate Brønsted acids. The corresponding monocyclic cyclopentenones are formed in good yields and excellent regio-, diastereo-, and enantioselectivities. Further, the chemical utility of the obtained enantiopure cyclopentenones is demonstrated

On crack propagation in a nonlinear coupled thermo-mechanical system

AbstractThe crack propagation problem in a coupled thermo-mechanical system of nonlinear media have been considered and the related path-independent integrals are given. It is shown the dynamical crack extension force in a coupled thermo-mechanical system equals to this integral, thus it could consider such integrals as a nonlinear fracture criterion for coupled thermo-mechanical fracture dynamics

Performance Analysis of a Dual-Hop Cooperative Relay Network with Co-Channel Interference

This paper analyzes the performance of a dual-hop amplify-and-forward (AF) cooperative relay network in the presence of direct link between the source and destination and multiple co-channel interferences (CCIs) at the relay. Specifically, we derive the new analytical expressions for the moment generating function (MGF) of the output signal-to-interference-plus-noise ratio (SINR) and the average symbol error rate (ASER) of the relay network. Computer simulations are given to confirm the validity of the analytical results and show the effects of direct link and interference on the considered AF relay network

Cooling a mechanical resonator via coupling to a tunable double quantum dot

We study the cooling of a mechanical resonator (MR) that is capacitively coupled to a double quantum dot (DQD). The MR is cooled by the dynamical backaction induced by the capacitive coupling between the DQD and the MR. The DQD is excited by a microwave field and afterwards a tunneling event results in the decay of the excited state of the DQD. An important advantage of this system is that both the energy level splitting and the decay rate of the DQD can be well tuned by varying the gate voltage. We find that the steady average occupancy, below unity, of the MR can be achieved by changing both the decay rate of the excited state and the detuning between the transition frequency of the DQD and the microwave frequency, in analogy to the laser sideband cooling of an atom or trapped ion in atomic physics. Our results show that the cooling of the MR to the ground state is experimentally implementable.Comment: 10 pages, 5 figure

Parameter-Expanded ECME Algorithms for Logistic and Penalized Logistic Regression

Parameter estimation in logistic regression is a well-studied problem with the Newton-Raphson method being one of the most prominent optimization techniques used in practice. A number of monotone optimization methods including minorization-maximization (MM) algorithms, expectation-maximization (EM) algorithms and related variational Bayes approaches offer a family of useful alternatives guaranteed to increase the logistic regression likelihood at every iteration. In this article, we propose a modified version of a logistic regression EM algorithm which can substantially improve computationally efficiency while preserving the monotonicity of EM and the simplicity of the EM parameter updates. By introducing an additional latent parameter and selecting this parameter to maximize the penalized observed-data log-likelihood at every iteration, our iterative algorithm can be interpreted as a parameter-expanded expectation-condition maximization either (ECME) algorithm, and we demonstrate how to use the parameter-expanded ECME with an arbitrary choice of weights and penalty function. In addition, we describe a generalized version of our parameter-expanded ECME algorithm that can be tailored to the challenges encountered in specific high-dimensional problems, and we study several interesting connections between this generalized algorithm and other well-known methods. Performance comparisons between our method, the EM algorithm, and several other optimization methods are presented using a series of simulation studies based upon both real and synthetic datasets