Pareto Smoothed Importance Sampling

Importance weighting is a general way to adjust Monte Carlo integration to account for draws from the wrong distribution, but the resulting estimate can be noisy when the importance ratios have a heavy right tail. This routinely occurs when there are aspects of the target distribution that are not well captured by the approximating distribution, in which case more stable estimates can be obtained by modifying extreme importance ratios. We present a new method for stabilizing importance weights using a generalized Pareto distribution fit to the upper tail of the distribution of the simulated importance ratios. The method, which empirically performs better than existing methods for stabilizing importance sampling estimates, includes stabilized effective sample size estimates, Monte Carlo error estimates and convergence diagnostics.Comment: Major revision: 1) proofs for consistency, finite variance, and asymptotic normality, 2) justification of k<0.7 with theoretical computational complexity analysis, 3) major rewrit

Computational polarimetric microwave imaging

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure

Structuring national and sub-national economic incentives to reduce emissions from deforestation in Indonesia

We estimate the impacts that alternative national and sub-national economic incentive structures for reducing emissions from deforestation (REDD+) in Indonesia would have had on greenhouse gas emissions and national and local revenue if they had been in place from 2000-2005. The impact of carbon payments on deforestation is calibrated econometrically from the pattern of observed deforestation and spatial variation in the benefits and costs of converting land to agriculture over that time period. We estimate that at an international carbon price of $10/tCO2e, a “basic voluntary incentive structure” modeled after a traditional payment-for-ecosystem-services (PES) program would have reduced emissions nationally by 62 MtCO2e/yr, or 8% below the without-REDD+ reference scenario (95% CI: 45-76 MtCO2e/yr; 6-9%), while generating a programmatic budget shortfall. By making four policy improvements—paying for net emission reductions at the scale of an entire district rather than site-by-site, paying for reductions relative to estimated business-as-usual levels rather than historical levels, sharing a portion of district-level revenues with the national government, and sharing a portion of the national government’s responsibility for costs with districts—an “improved voluntary incentive structure” would have reduced emissions by 175 MtCO2e/yr, or 22% below the reference scenario (95% CI: 136-207 MtCO2e/yr; 17-26%), while generating a programmatic budget surplus. A “regulatory incentive structure” such as a cap-and-trade or symmetric tax-and-subsidy program would have reduced emissions by 211/yr, or 26% below the reference scenario (95% CI: 163-247 MtCO2e/yr; 20-31%), and would not have required accurate predictions of business-as-usual emissions to guarantee a programmatic budget surplus.Climate change, land-use change, REDD+, reference levels, economic incentives

A task and performance analysis of endoscopic submucosal dissection (ESD) surgery

BACKGROUND: ESD is an endoscopic technique for en bloc resection of gastrointestinal lesions. ESD is a widely-used in Japan and throughout Asia, but not as prevalent in Europe or the US. The procedure is technically challenging and has higher adverse events (bleeding, perforation) compared to endoscopic mucosal resection. Inadequate training platforms and lack of established training curricula have restricted its wide acceptance in the US. Thus, we aim to develop a Virtual Endoluminal Surgery Simulator (VESS) for objective ESD training and assessment. In this work, we performed task and performance analysis of ESD surgeries. METHODS: We performed a detailed colorectal ESD task analysis and identified the critical ESD steps for lesion identification, marking, injection, circumferential cutting, dissection, intraprocedural complication management, and post-procedure examination. We constructed a hierarchical task tree that elaborates the order of tasks in these steps. Furthermore, we developed quantitative ESD performance metrics. We measured task times and scores of 16 ESD surgeries performed by four different endoscopic surgeons. RESULTS: The average time of the marking, injection, and circumferential cutting phases are 203.4 (σ: 205.46), 83.5 (σ: 49.92), 908.4 s. (σ: 584.53), respectively. Cutting the submucosal layer takes most of the time of overall ESD procedure time with an average of 1394.7 s (σ: 908.43). We also performed correlation analysis (Pearson's test) among the performance scores of the tasks. There is a moderate positive correlation (R = 0.528, p = 0.0355) between marking scores and total scores, a strong positive correlation (R = 0.7879, p = 0.0003) between circumferential cutting and submucosal dissection and total scores. Similarly, we noted a strong positive correlation (R = 0.7095, p = 0.0021) between circumferential cutting and submucosal dissection and marking scores. CONCLUSIONS: We elaborated ESD tasks and developed quantitative performance metrics used in analysis of actual surgery performance. These ESD metrics will be used in future validation studies of our VESS simulator

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor

Calculation of the absolute free energy of binding (ΔGbind) for a complex in solution is challenging owing to the need for adequate configurational sampling and an accurate energetic description, typically with a force field (FF). In this study, Monte Carlo (MC) simulations with improved side-chain and backbone sampling are used to assess ΔGbind for the complex of a druglike inhibitor (MIF180) with the protein macrophage migration inhibitory factor (MIF) using free energy perturbation (FEP) calculations. For comparison, molecular dynamics (MD) simulations were employed as an alternative sampling method for the same system. With the OPLS-AA/M FF and CM5 atomic charges for the inhibitor, the ΔGbind results from the MC/FEP and MD/FEP simulations, −8.80 ± 0.74 and −8.46 ± 0.85 kcal/mol, agree well with each other and with the experimental value of −8.98 ± 0.28 kcal/mol. The convergence of the results and analysis of the trajectories indicate that sufficient sampling was achieved for both approaches. Repeating the MD/FEP calculations using current versions of the CHARMM and AMBER FFs led to a 6 kcal/mol range of computed ΔGbind. These results show that calculation of accurate ΔGbind for large ligands is both feasible and numerically equivalent, within error limits, using either methodology

Waffles and Spaghetti: The Effects of Cognitive Processing Methods on Team Performance and Communication

The goal of this thesis is to shed light on a practical method for resolving conflicts in team environments that stem from miscommunications brought on by differing cognitive processes. Our brains use different cognitive processing techniques to make sense of and explore the vast amount of information the world presents them on a daily, even hourly basis. Each person has their own thinking style which influences how teams collaborate and problem solve. However, miscommunication can often arise when individuals fail to recognize and adapt to the varying processing methods, which can lead to frustration and inefficiency. This research seeks to address these challenges by defining the two main cognitive processing methods, linear and nonlinear processing, how brain physiology affects which method an individual primarily subscribes to, and practical solutions for overcoming frustrations and miscommunications. Secondly, the author will present a seven-minute animated short that takes the archetypes of linear and nonlinear processing to demonstrate the problems and solutions in a creative and entertaining way. The goal of the short is to present the complicated research using easy to understand symbols so that any organization or team can implement processes to help improve interpersonal communication