A universal median quasi-Monte Carlo integration

We study quasi-Monte Carlo (QMC) integration over the multi-dimensional unit cube in several weighted function spaces with different smoothness classes. We consider approximating the integral of a function by the median of several integral estimates under independent and random choices of the underlying QMC point sets (either linearly scrambled digital nets or infinite-precision polynomial lattice point sets). Even though our approach does not require any information on the smoothness and weights of a target function space as an input, we can prove a probabilistic upper bound on the worst-case error for the respective weighted function space, where the failure probability converges to 0 exponentially fast as the number of estimates increases. Our obtained rates of convergence are nearly optimal for function spaces with finite smoothness, and we can attain a dimension-independent super-polynomial convergence for a class of infinitely differentiable functions. This implies that our median-based QMC rule is universal in the sense that it does not need to be adjusted to the smoothness and the weights of the function spaces and yet exhibits the nearly optimal rate of convergence. Numerical experiments support our theoretical results.Comment: Major revision, 32 pages, 4 figure

Electrochemical Synthesis of Graphite-Tetrafluoroaluminate Intercalation Compounds

Graphite tetrafluoroaluminate intercalation compounds (AlF₄-GICs) have been prepared by electrochemical oxidation of a natural graphite electrode in a 1.0 M nitromethane solution of tetraethylammmonium tetrafluoroaluminate ([TEA][AlF₄]). Galvanostatic electrolysis suggests that the intercalation reaction occurs above 0.8 V vs. Ag⁺/Ag. Powder X-ray diffraction measurements of the AlF₄-GIC obtained by potentiostatic electrolysis reveal that the most AlF₄-rich phase is the stage-3 GIC with a gallery height of 0.79 nm. This gallery height agrees with the theoretical value calculated from the size of AlF₄⁻ that locates its two-fold axis perpendicular to the graphite layers. Co-intercalation of the solvent is suggested by the composition of the stage-3 GIC (C₅₅AlF₄) and is confirmed by release of the solvent above 350 K during thermogravimetric analysis. Although the AlF₄-GIC shows the higher air stability than those of the GICs with typical inorganic complex anions, it slowly decomposes into GICs at higher stages after exposure to the air over 1000 h. Increase of gallery height was observed during this period, which possibly results from reorientation of AlF₄− between the layers. The thermodynamic stability of AlF₄-GIC is evaluated based on a Born-Harber cycle

Decision Diagrams for Solving a Job Scheduling Problem Under Precedence Constraints

We consider a job scheduling problem under precedence constraints, a classical problem for a single processor and multiple jobs to be done. The goal is, given processing time of n fixed jobs and precedence constraints over jobs, to find a permutation of n jobs that minimizes the total flow time, i.e., the sum of total wait time and processing times of all jobs, while satisfying the precedence constraints. The problem is an integer program and is NP-hard in general. We propose a decision diagram pi-MDD, for solving the scheduling problem exactly. Our diagram is suitable for solving linear optimization over permutations with precedence constraints. We show the effectiveness of our approach on the experiments on large scale artificial scheduling problems

Particle Swarm Optimization Combining Diversification and Intensification for Nonlinear Integer Programming Problems

In this research, focusing on nonlinear integer programming problems, we propose an approximate solution method based on particle swarm optimization proposed by Kennedy et al. And we developed a new particle swarm optimization method which is applicable to discrete optimization problems by incoporating a new method for generating initial search points, the rounding of values obtained by the move scheme and the revision of move methods. Furthermore, we showed the efficiency of the proposed particle swarm optimization method by comparing it with an existing method through the application of them into the numerical examples. Moreover we expanded revised particle swarm optimization method for application to nonlinear integer programming problems and showed more effeciency than genetic algorithm. However, variance of the solutions obtained by the PSO method is large and accuracy is not so high. Thus, we consider improvement of accuracy introducing diversification and intensification

Changes in the SF-8 scores among healthy non-smoking school teachers after the enforcement of a smoke-free school policy: a comparison by passive smoke status

<p>Abstract</p> <p>Background</p> <p>The effects of the enforcement of a smoke-free workplace policy on health-related quality of life (HRQOL) among a healthy population are poorly understood. The present study was undertaken to examine the effects of the enforcement of a smoke-free school policy on HRQOL among healthy non-smoking schoolteachers with respect to their exposure to passive smoke.</p> <p>Methods</p> <p>Two self-reported questionnaire surveys were conducted, the first before and the second after the enforcement of a total smoke-free public school policy in Nara City. A total of 1534 teachers were invited from 62 schools, and their HRQOL was assessed using six domains extracted from the Medical Outcomes Survey Short Form-8 questionnaire (SF-8): general health perception (GH), role functioning-physical (RP), vitality (VT), social functioning (SF), mental health (MH), and role functioning-emotional (RE). The participants were divided into two groups according to their exposure to environmental tobacco smoke (ETS) at baseline: participants not exposed to ETS at school (non-smokers), and participants exposed to ETS at school (passive smokers). Changes in each SF-8 score were evaluated using paired t-tests for each group, and their inter-group differences were evaluated using multiple linear regression analyses adjusted for sex, age, school type, managerial position, and attitude towards a smoke-free policy.</p> <p>Results</p> <p>After ineligible subjects were excluded, 689 teachers were included in the analyses. The number of non-smokers and passive smokers was 447 and 242, respectively. Significant changes in SF-8 scores were observed for MH (0.9; 95% confidence interval [CI], 0.2-1.5) and RE (0.7; 95% CI, 0.0-1.3) in non-smokers, and GH (2.2; 95% CI, 1.2-3.1), VT (1.8; 95% CI, 0.9-2.7), SF (2.7; 95% CI, 1.6-3.8), MH (2.0; 95% CI, 1.0-2.9), and RE (2.0; 95% CI, 1.2-2.8) in passive smokers. In the multiple linear regression analyses, the net changes in the category scores of GH (1.8; 95% CI, 0.7-2.9), VT (1.4, 95% CI, 0.3-2.5), SF (2.5; 95% CI, 1.1-3.9), MH (1.2; 95% CI, 0.1-2.4) and RE (1.6; 95% CI, 0.5-2.7) in passive smokers significantly exceeded those in non-smokers.</p> <p>Conclusions</p> <p>A smoke-free school policy would improve the HRQOL of healthy non-smoking teachers who are exposed to ETS.</p

Particle Swarm Optimization Combining Diversification and Intensification for Nonlinear Integer Programming Problems

Abstract-In this research, focusing on nonlinear integer programming problems, we propose an approximate solution method based on particle swarm optimization proposed by Kennedy et al. And we developed a new particle swarm optimization method which is applicable to discrete optimization problems by incoporating a new method for generating initial search points, the rounding of values obtained by the move scheme and the revision of move methods. Furthermore, we showed the efficiency of the proposed particle swarm optimization method by comparing it with an existing method through the application of them into the numerical examples. Moreover we expanded revised particle swarm optimization method for application to nonlinear integer programming problems and showed more effeciency than genetic algorithm. However, variance of the solutions obtained by the PSO method is large and accuracy is not so high. Thus, we consider improvement of accuracy introducing diversification and intensification

CT fluoroscopy-guided percutaneous intervertebral drain insertion for cervical pyogenic spondylodiscitis

A 79-year-old man was admitted to our hospital with C6-C7 pyogenic spondylodiscitis with an epidural abscess. Since the cervical intervertebral space is narrower than the thoracolumbar intervertebral space, drain insertion into the cervical intervertebral space requires a more accurate procedure. Moreover, the specific anatomy of cervical vertebrae, which includes the transverse foramen through which the vertebral artery passes and the uncinate process on the side edges of the top surface of the bodies, makes it impossible to perform computed tomography (CT)-guided percutaneous intervertebral drain insertion through the posterolateral approach. Therefore, CT fluoroscopy-guided percutaneous cervical intervertebral drain insertion using a lateral approach, in which the needle is advanced between the carotid sheath and scalene muscle, and simultaneous intravenous contrast enhancement might be a safe and useful technique. There have been no papers on CT fluoroscopy-guided percutaneous intervertebral drain insertion for cervical pyogenic spondylodiscitis, while successful CT fluoroscopy-guided percutaneous intervertebral drain insertion for thoracolumbar pyogenic spondylodiscitis has been reported. Here, we successfully performed CT fluoroscopy-guided percutaneous intervertebral drain insertion for cervical pyogenic spondylodiscitis