Computationally Efficient Nonparametric Importance Sampling

The variance reduction established by importance sampling strongly depends on the choice of the importance sampling distribution. A good choice is often hard to achieve especially for high-dimensional integration problems. Nonparametric estimation of the optimal importance sampling distribution (known as nonparametric importance sampling) is a reasonable alternative to parametric approaches.In this article nonparametric variants of both the self-normalized and the unnormalized importance sampling estimator are proposed and investigated. A common critique on nonparametric importance sampling is the increased computational burden compared to parametric methods. We solve this problem to a large degree by utilizing the linear blend frequency polygon estimator instead of a kernel estimator. Mean square error convergence properties are investigated leading to recommendations for the efficient application of nonparametric importance sampling. Particularly, we show that nonparametric importance sampling asymptotically attains optimal importance sampling variance. The efficiency of nonparametric importance sampling algorithms heavily relies on the computational efficiency of the employed nonparametric estimator. The linear blend frequency polygon outperforms kernel estimators in terms of certain criteria such as efficient sampling and evaluation. Furthermore, it is compatible with the inversion method for sample generation. This allows to combine our algorithms with other variance reduction techniques such as stratified sampling. Empirical evidence for the usefulness of the suggested algorithms is obtained by means of three benchmark integration problems. As an application we estimate the distribution of the queue length of a spam filter queueing system based on real data.Comment: 29 pages, 7 figure

The Role of Attorney Fee Shifting in Public Interest Litigation

BACKGROUND: Brain tissue segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) are important in neuroradiological applications. Quantitative Mri (qMRI) allows segmentation based on physical tissue properties, and the dependencies on MR scanner settings are removed. Brain tissue groups into clusters in the three dimensional space formed by the qMRI parameters R1, R2 and PD, and partial volume voxels are intermediate in this space. The qMRI parameters, however, depend on the main magnetic field strength. Therefore, longitudinal studies can be seriously limited by system upgrades. The aim of this work was to apply one recently described brain tissue segmentation method, based on qMRI, at both 1.5 T and 3.0 T field strengths, and to investigate similarities and differences. METHODS: In vivo qMRI measurements were performed on 10 healthy subjects using both 1.5 T and 3.0 T MR scanners. The brain tissue segmentation method was applied for both 1.5 T and 3.0 T and volumes of WM, GM, CSF and brain parenchymal fraction (BPF) were calculated on both field strengths. Repeatability was calculated for each scanner and a General Linear Model was used to examine the effect of field strength. Voxel-wise t-tests were also performed to evaluate regional differences. RESULTS: Statistically significant differences were found between 1.5 T and 3.0 T for WM, GM, CSF and BPF (p<0.001). Analyses of main effects showed that WM was underestimated, while GM and CSF were overestimated on 1.5 T compared to 3.0 T. The mean differences between 1.5 T and 3.0 T were -66 mL WM, 40 mL GM, 29 mL CSF and -1.99% BPF. Voxel-wise t-tests revealed regional differences of WM and GM in deep brain structures, cerebellum and brain stem. CONCLUSIONS: Most of the brain was identically classified at the two field strengths, although some regional differences were observed

Collaborative Business Process Modeling Using 3D Virtual Environments

Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists involved in the process modeling. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. Some systems have been developed to support collaborative process modeling, all of which use traditional 2D interfaces. We present an environment for collaborative process modeling, using 3D virtual environment technology. We make use of avatar instantiations of user ego centres, to allow for the spatial embodiment of the user with reference to the process model. We describe an innovative prototype collaborative process modeling approach, implemented as a modeling environment in Second Life. This approach leverages the use of virtual environments to provide user context for editing and collaborative exercises. We present a positive preliminary report on a case study, in which a test group modelled a business process using the system in Second Life

Evaluation of the Primary Care Mental Health Specialist role: Final Report

This report details an evaluation to assess the impact of the new primary care mental health specialist (PCMHS) role in Kent and Medway. The evaluation was undertaken by the Centre for Health Services Studies (CHSS) at the University of Kent and was conducted June 2013 to December 2014. The evaluation was commissioned by NHS Kent and Medway and supported by Kent and Medway Commissioning Support. The evaluation encompasses six CCG areas across Kent and Medway, with 13 PCMHS employed in these areas (see Table 1-1 for breakdown). The number of posts per CCG is dependent on the amount CCGs invest (roughly equating to population size), rather than prevalence of illness. The PCMHS have been seconded from Kent and Medway NHS and Social Care Partnership Trust (KMPT) for the duration of the pilot, and are either community psychiatric nurses (CPN) or occupational therapists (OT) by profession. The majority of PCMHS are hosted by a voluntary organisation (mcch); three are hosted by GP practices and two by a community Interest Company, Invicta CIC. The main objectives of the evaluation are: 1. To assess the impact on patients by capturing their experience of the service; 2. To assess the impact by capturing experiences of those delivering the service (i.e., PCMHS); 3. To assess the impact by capturing experiences of other professions who work alongside the service (i.e., mental health professionals in secondary care, GPs); 4. To assess the economic cost of the new service via a unit cost analysis

Overstated carbon emission reductions from voluntary REDD+ projects in the Brazilian Amazon

Reduced Emissions from Deforestation and forest Degradation (REDD+) has gained international attention over the past decade, as manifested in both United Nations policy discussions and hundreds of voluntary projects launched to earn carbon-offset credits. There are on-going discussions about whether and how projects should be integrated into national efforts under the Paris Agreement. One consideration is whether these projects have generated additional impacts over and above national policies and other conservation measures. To help inform these discussions, we compare the crediting baselines established ex-ante by voluntary REDD+ projects in the Brazilian Amazon to counterfactuals constructed ex-post based on the quasi-experimental synthetic control method. We find that the crediting baselines assume consistently higher deforestation than counterfactual forest loss in synthetic control sites. This gap is partially due to decreased deforestation in the Brazilian Amazon during the early implementation phase of the REDD+ projects considered here. This suggests that forest carbon finance must strike a balance between controlling conservation investment risk and ensuring the environmental integrity of carbon emission offsets. Relatedly, our results point to the need to better align project- and national-level carbon accounting.German Federal Ministry of Education and Researc

Effect of Grade Retention in First Grade on Psychosocial Outcomes

In a 4-year longitudinal study, the authors investigated effects of retention in first grade on children’s externalizing and internalizing behaviors; social acceptance; and behavioral, cognitive, and affective engagement. From a large multiethnic sample (n = 784) of children below the median on literacy at school entrance, 124 retained children were matched with 251 promoted children on the basis of propensity scores (probability of being retained in first grade estimated from 72 baseline variables). Relative to promoted children, retained children were found to benefit from retention in both the short and longer terms with respect to decreased teacher-rated hyperactivity, decreased peer-rated sadness and withdrawal, and increased teacher-rated behavioral engagement. Retained children had a short-term increase in mean peer-rated liking and school belongingness relative to promoted children, but this advantage showed a substantial decrease in the longer term. Retention had a positive short-term effect on children’s perceived school belonging and a positive longer term effect on perceived academic self-efficacy. Retention may bestow advantages in the short-term, but longer term detrimental effects on social acceptance may lead to the documented longer term negative effects of retention

Innovation in Corporate Law

In most countries large business enterprises today are organized as corporations. The corporation with its key attributes of independent personality, limited liability and free tradeability of shares has played a key role in most developed market economies since the 19th century and has made major inroads in emerging markets. We suggest that the resilience of the corporate form is a function of the adaptability of the legal framework to a changing environment. We analyze a country\u27s capacity to innovate using the rate of statutory legal change, the flexibility of corporate law, and institutional change as indicators. Our findings suggest that origin countries are more innovative than transplant countries