Analysis of the DDˉ∗KD\bar{D}^*K system with QCD sum rules

In this article, we construct the color singlet-singlet-singlet interpolating current with $I\left(J^P\right)=\frac{3}{2}\left(1^-\right)$ to study the $D\bar{D}^*K$ system through QCD sum rules approach. In calculations, we consider the contributions of the vacuum condensates up to dimension-16 and employ the formula $\mu=\sqrt{M_{X/Y/Z}^{2}-\left(2{\mathbb{M}}_{c}\right)^{2}}$ to choose the optimal energy scale of the QCD spectral density. The numerical result $M_Z=4.71_{-0.11}^{+0.19}\,\rm{GeV}$ indicates that there exists a resonance state $Z$ lying above the $D\bar{D}^*K$ threshold to saturate the QCD sum rules. This resonance state $Z$ may be found by focusing on the channel $J/\psi \pi K$ of the decay $B\longrightarrow J/\psi \pi \pi K$ in the future.Comment: 9 pages, 4 figure

Complexity growth rates for AdS black holes in massive gravity and f(R)f(R) gravity

The "complexity = action" duality states that the quantum complexity is equal to the action of the stationary AdS black holes within the Wheeler-DeWitt patch at late time approximation. We compute the action growth rates of the neutral and charged black holes in massive gravity and the neutral, charged and Kerr-Newman black holes in $f(R)$ gravity to test this conjecture. Besides, we investigate the effects of the massive graviton terms, higher derivative terms and the topology of the black hole horizon on the complexity growth rate.Comment: 11 pages, no figur

Clinical and Genetic Risk Factors Associated with Psoriatic Arthritis among Patients with Psoriasis.

IntroductionPsoriatic arthritis (PsA) is a chronic, inflammatory arthritis that affects an estimated 30% of patients with psoriasis. PsA is underdiagnosed in primary care and dermatology clinics due to a variety of reasons, including failure of healthcare providers to ask about symptoms, overlap of symptoms and signs with other rheumatologic conditions, and lack of a specific diagnostic test. A delay in PsA diagnosis and treatment, even as short as 6 months, can lead to decreased quality of life, increased joint damage, and worse long-term physical function. In this study, we sought to identify the clinical and genetic factors that help discriminate patients with PsA from those with cutaneous psoriasis only.MethodsWe analyzed a cohort of 974 psoriasis patients at an academic medical center, of whom 175 had confirmed PsA, and performed univariate, multivariate, and predictive modeling to determine factors associated with PsA.ResultsThe univariate analysis revealed significant positive associations of PsA with age, nail involvement, scalp involvement, skin fold involvement, elbow/knee involvement, psoriasis severity, plaque subtype, erythrodermic subtype, hypertension, type 2 diabetes, and coronary artery disease, and a significant negative association of PsA with the human leukocyte antigen (HLA)-C*06:02 allele. In the multivariate analysis, nail involvement, type 2 diabetes, and pustular psoriasis remained significantly associated with PsA, while HLA-C*06:02 positivity remained protective. There was a trend towards an association of PsA with older age, younger age of psoriasis onset, and skin fold involvement, while there was protective trend for smoking. A predictive model including both clinical and genetic factors showed reasonable discriminative ability between psoriasis and PsA, with an area under the curve of 0.87 for a receiver operating characteristic curve.ConclusionThis study identified a number of clinical and genetic features that could help stratify patients who are at higher risk for having PsA and for whom rheumatology referral may be beneficial

A Mixture-Based Approach to Regional Adaptation for MCMC

Recent advances in adaptive Markov chain Monte Carlo (AMCMC) include the need for regional adaptation in situations when the optimal transition kernel is different across different regions of the sample space. Motivated by these findings, we propose a mixture-based approach to determine the partition needed for regional AMCMC. The mixture model is fitted using an online EM algorithm (see Andrieu and Moulines, 2006) which allows us to bypass simultaneously the heavy computational load and to implement the regional adaptive algorithm with online recursion (RAPTOR). The method is tried on simulated as well as real data examples

A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search

Sponsored search is an important monetization channel for search engines, in which an auction mechanism is used to select the ads shown to users and determine the prices charged from advertisers. There have been several pieces of work in the literature that investigate how to design an auction mechanism in order to optimize the revenue of the search engine. However, due to some unrealistic assumptions used, the practical values of these studies are not very clear. In this paper, we propose a novel \emph{game-theoretic machine learning} approach, which naturally combines machine learning and game theory, and learns the auction mechanism using a bilevel optimization framework. In particular, we first learn a Markov model from historical data to describe how advertisers change their bids in response to an auction mechanism, and then for any given auction mechanism, we use the learnt model to predict its corresponding future bid sequences. Next we learn the auction mechanism through empirical revenue maximization on the predicted bid sequences. We show that the empirical revenue will converge when the prediction period approaches infinity, and a Genetic Programming algorithm can effectively optimize this empirical revenue. Our experiments indicate that the proposed approach is able to produce a much more effective auction mechanism than several baselines.Comment: Twenty-third International Conference on Artificial Intelligence (IJCAI 2013

Masses and decay constants of the heavy tensor mesons with QCD sum rules

In this article, we calculate the contributions of the vacuum condensates up to dimension-6 in the operator product expansion, study the masses and decay constants of the heavy tensor mesons $D_2^*(2460)$, $D_{s2}^*(2573)$, $B_2^*(5747)$, $B_{s2}^*(5840)$ using the QCD sum rules. The predicted masses are in excellent agreement with the experimental data, while the ratios of the decay constants $\frac{f_{D_{s2}^*}}{f_{D_{2}^*}}\approx\frac{f_{B_{s2}^*}}{f_{B_{2}^*}}\approx\frac{f_{D_{s}}}{f_{D}}\mid_{\rm exp}$, where the exp denotes the experimental value.Comment: 13 pages, 13 figure