12,444 research outputs found
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
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