Waist Circumference predicting Cardiovascular Disease in Korean Men and Women

Objective: Obesity and cardiovascular disease (CVD) are closely related and have become increasingly prevalent in Korea. Asians are more prone to obesity-related co-morbidities than Caucasians, even at lower body mass index (BMI) and/or smaller waist circumference (WC) values. Nevertheless, little is known regarding the association of WC with the risk of CVD in non-Caucasian populations. The authors conducted a prospective cohort study of WC and the risk of CVD in the Korean Heart Study.Methods: We examined the association of WC to CVD incidence among 53,026 Korean adults (30,152 men, 22,874 women) with no history of CVD and/or cancer. During a mean follow-up of 8.6 years, 2,722 incident cases of atherosclerotic cardiovascular disease (ASCVD) including 1,383 cases of ischemic heart disease (IHD) and 1,012 cases of stroke were documented. Results: Average WC at baseline was 84.0±8.2 cm in men and 75.2±8.9 cm in women. After adjustment for age and BMI, WC was significantly associated with cardiovascular risk factors (P <.001). In men, a WC of ≥91 cm was associated with an ASCVD hazard ratio (HR) of 1.62 (95% confidence interval (CI): 1.25, 2.10) and an IHD HR of 1.70 (95% CI: 1.19, 2.42) in comparison with a WC of <78 cm even after further adjustment for BMI and traditional risk factors (P for trend = 0.0118, 0.0139 respectively). In women, the progressive associations of WC with ASCVD, IHD and stroke were observed. These associations were however attenuated after further adjustment for BMI and traditional risk factors. The multivariable HRs for ASCVD, IHD, and stroke increased with higher WC in both men and women. Conclusions: Central obesity significantly and independently contributes to cardiovascular outcomes in Korean men and women

Comment on "Non-Mean-Field Behavior of the Contact Process on Scale-Free Networks"

Recently, Castellano and Pastor-Satorras [1] utilized the finite size scaling (FSS) theory to analyze simulation data for the contact process (CP) on scale-free networks (SFNs) and claimed that its absorbing critical behavior is not consistent with the mean-field (MF) prediction. Furthermore, they pointed out large density fluctuations at highly connected vertices as a possible origin for non-MF critical behavior. In this Comment, we propose a scaling theory for relative density fluctuations in the spirit of the MF theory, which turns out to explain simulation data perfectly well. We also measure the value of the critical density decay exponent, which agrees well with the MF prediction. Our results strongly support that the CP on SFNs still exhibits a MF-type critical behavior.Comment: 1 page, 2 figures, typos are correcte

L2L_2 boosting in kernel regression

In this paper, we investigate the theoretical and empirical properties of $L_2$ boosting with kernel regression estimates as weak learners. We show that each step of $L_2$ boosting reduces the bias of the estimate by two orders of magnitude, while it does not deteriorate the order of the variance. We illustrate the theoretical findings by some simulated examples. Also, we demonstrate that $L_2$ boosting is superior to the use of higher-order kernels, which is a well-known method of reducing the bias of the kernel estimate.Comment: Published in at http://dx.doi.org/10.3150/08-BEJ160 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment

This paper addresses planning and control of robot motion under uncertainty that is formulated as a continuous-time, continuous-space stochastic optimal control problem, by developing a topology-guided path integral control method. The path integral control framework, which forms the backbone of the proposed method, re-writes the Hamilton-Jacobi-Bellman equation as a statistical inference problem; the resulting inference problem is solved by a sampling procedure that computes the distribution of controlled trajectories around the trajectory by the passive dynamics. For motion control of robots in a highly cluttered environment, however, this sampling can easily be trapped in a local minimum unless the sample size is very large, since the global optimality of local minima depends on the degree of uncertainty. Thus, a homology-embedded sampling-based planner that identifies many (potentially) local-minimum trajectories in different homology classes is developed to aid the sampling process. In combination with a receding-horizon fashion of the optimal control the proposed method produces a dynamically feasible and collision-free motion plans without being trapped in a local minimum. Numerical examples on a synthetic toy problem and on quadrotor control in a complex obstacle field demonstrate the validity of the proposed method.Comment: arXiv admin note: text overlap with arXiv:1510.0534