Post-war economic policy and planning. Preliminary report of the Special committee on post-war economic policy and planning, pursuant to S.Res.102, a resolution creating a Special committee on post-war economic policy and planning ... [and Report[s]].

Submitted by Mr. George.

High-resolution dynamical downscaling products for the North Slope of Alaska and surrounding areas, links to model result files

Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic.

Quantifying ice-shelf basal melt and ice-stream dynamics using high-resolution DEM and GPS time series

Thesis (Ph.D.)--University of Washington, 2016-06

Influence of particle morphology on nanostructural feature and conducting property in Sm-doped CeO2 sintered body

Doped ceria (CeO2,) compounds are fluorite type oxides, which show oxide ionic conductivity higher than yttria stabilized zirconia (YSZ), in oxidizing atmospheres. As a consequence of this, considerable interest has been shown in application of these materials for 'low (500-650 degreesC)' or 'intermediate (650-800 degreesC)' temperature operation, solid oxide fuel cells (SOFCs). In this study, the authors prepared two kinds of nanosize Sm-doped CeO2 particles with different morphologies: one type was round and the other was elongated. Processing these powders with different morphology produced dense materials with very different ionic conducting properties and different nanoscale microstructures. Since both particles are very fine and well dispersed, sintered bodies with high density (relative density >95% of theoretical) could be prepared using both types of powder particles. The electrical conductivity of sintered bodies prepared from these powders with different starting morphologies was very different. Materials prepared from particles having a round shape were much higher than those produced using powders with an elongated morphology. Measured activation energies of the corresponding sintered samples showed a similar trend; round particles (60 kJ/mol), elongated particles (74 kJ/mol). While X-ray diffraction (XRD) profiles of these sintered materials were identical, diffuse scatter was observed in the back.-round of selected area electron diffraction pattern recorded from both sintered bodies. This indicated an underlying structure that appeared to have been influenced by the processing technology. Detailed observation using high-resolution transmission electron microscopy (HR-TEM) revealed that the size of microdomain with ordering of cations in the sintered body made from round shape particles was much smaller than that of the sintered body made from elongated particles. Accordingly, it is concluded that the morphology of doped CeO2 powders strongly influenced the microdomain size and electrolytic properties in the doped CeO2 sintered body. (C) 2004 Elsevier B.V. All rights reserved.

Can intellectual property rights impact directly on productivity: a case study in manufacturing industries

According to the institutional economics thesis the role of IPRs is one of the relevant determinants of economic growth in long run. Measures of IPRs have been limited and empirical studies have not been able to evaluate their impacts on productivity growth. The major conclusion that the author can be drawn from his estimations is that the extent to which patent rights and trademarks, ceteris paribus, positively correlated with output per capita depends on the intensity of technology.

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

The effects of intellectual property rights on knowledge spillovers and innovation: An empirical investigation

FDI is believed to be a conduit of new technologies between countries. The first chapter of this dissertation studies the advantages of outward FDI for the home country of multinationals conducting research and development abroad. We use patent citations as a proxy for technology spillovers and we bring empirical evidence that supports the hypothesis that a U.S. subsidiary conducting research and development overseas facilitates the flow of knowledge between its host and home countries.^ The second chapter examines the impact of intellectual property rights (IPR) reforms on the technology flows between the U.S. and host countries of U.S. affiliates. We again use patent citations to examine whether the diffusion of new technology between the host countries and the U.S. is accelerated by the reforms. Our results suggest that the reforms favor innovative efforts of domestic firms in the reforming countries rather than U.S. affiliates efforts. In other words, reforms mediate the technology flows from the U.S. to the reforming countries.^ The third chapter deals with another form of IPR, open source (OS) licenses. These differ in the conditions under which licensors and OS contributors are allowed to modify and redistribute the source code. We measure OS project quality by the speed with which programming bugs are fixed and test whether the license chosen by project leaders influences bug resolution rates. In initial regressions, we find a strong correlation between the hazard of bug resolution and the use of highly restrictive licenses. However, license choices are likely to be endogenous. We instrument license choice using (i) the human language in which contributors operate and (ii) the license choice of the project leaders for a previous project. We then find weak evidence that restrictive licenses adversely affect project success.^

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as "histogram binning" inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

If People Were Kaleidoscopes: Sharpening the Resolution on Patient Engagement in Safety

Healthcare is unacceptably error prone. The question remains why, with 20 years of evidence, is error and harm reduction not being effective? While precise numbers may be debated, all stakeholders recognize the frequency of healthcare errors is unacceptable, and greater efforts to ensure safety must occur. In recent years, one of these strategies has been the inclusion of the patient and their family as partners in safety, and has been a required organizational practice of Accreditation Canada in many of their standard sets. Existing patient advisories created to encourage engagement, have typically not included patient perspectives in their development or been comprehensively evaluated. There are no existing tools to determine if and how a patient wants to be involved in safety engagement. As such, a multi-phased study was undertaken to advance our knowledge about the client’s and family’s role in promoting safety. Phase 1 of the study was a scoping review to methodically review the existing literature about patients’ and families’ attitudes, beliefs and behaviours about their involvement in healthcare safety. Phase 2 was designed to inductively explore how a group of patients in an Ontario, Canada, community hospital, describe healthcare safety and see their role in preventing error. The study findings, which include the narratives of 30 patients and 4 family members, indicate that although there are shared themes that influence a patient’s engagement in patient safety, every individual has unique, changing beliefs, experiences and reasons for involvement. Five conceptual themes emerged from their narratives: Personal Capacity, Experiential Knowledge, Personal Character, Relationships, and Meaning of Safety. These study results will be used to develop and test a pragmatic, accessible tool to enable providers a way to collaborate with patients for determining their personal level and type of safety involvement. The most ethical and responsible approach to healthcare safety is to consider every facet and potential way for improvement. This exploratory study provides fundamental insights into the complexity of patient engagement in safety, and evidence for future steps.

Strategies for protecting intellectual property when using CUDA applications on graphics processing units

Recent advances in the massively parallel computational abilities of graphical processing units (GPUs) have increased their use for general purpose computation, as companies look to take advantage of big data processing techniques. This has given rise to the potential for malicious software targeting GPUs, which is of interest to forensic investigators examining the operation of software. The ability to carry out reverse-engineering of software is of great importance within the security and forensics elds, particularly when investigating malicious software or carrying out forensic analysis following a successful security breach. Due to the complexity of the Nvidia CUDA (Compute Uni ed Device Architecture) framework, it is not clear how best to approach the reverse engineering of a piece of CUDA software. We carry out a review of the di erent binary output formats which may be encountered from the CUDA compiler, and their implications on reverse engineering. We then demonstrate the process of carrying out disassembly of an example CUDA application, to establish the various techniques available to forensic investigators carrying out black-box disassembly and reverse engineering of CUDA binaries. We show that the Nvidia compiler, using default settings, leaks useful information. Finally, we demonstrate techniques to better protect intellectual property in CUDA algorithm implementations from reverse engineering.

Analytic and heuristic processes in the detection and resolution of conflict

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dualprocess models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and singleprocess accounts, which are discussed.

Software for Designing Custom Orbital-Craniofacial Implant Plans

Purpose: Custom cranio-orbital implants have been shown to achieve better performance than their hand-shaped counterparts by restoring skull anatomy more accurately and by reducing surgery time. Designing a custom implant involves reconstructing a model of the patient's skull using their computed tomography (CT) scan. The healthy side of the skull model, contralateral to the damaged region, can then be used to design an implant plan. Designing implants for areas of thin bone, such as the orbits, is challenging due to poor CT resolution of bone structures. This makes preoperative design time-intensive since thin bone structures in CT data must be manually segmented. The objective of this thesis was to research methods to accurately and efficiently design cranio-orbital implant plans, with a focus on the orbits, and to develop software that integrates these methods. Methods: The software consists of modules that use image and surface restoration approaches to enhance both the quality of CT data and the reconstructed model. It enables users to input CT data, and use tools to output a skull model with restored anatomy. The skull model can then be used to design the implant plan. The software was designed using 3D Slicer, an open-source medical visualization platform. It was tested on CT data from thirteen patients. Results: The average time it took to create a skull model with restored anatomy using our software was 0.33 hours ± 0.04 STD. In comparison, the design time of the manual segmentation method took between 3 and 6 hours. To assess the structural accuracy of the reconstructed models, CT data from the thirteen patients was used to compare the models created using our software with those using the manual method. When registering the skull models together, the difference between each set of skulls was found to be 0.4 mm ± 0.16 STD. Conclusions: We have developed a software to design custom cranio-orbital implant plans, with a focus on thin bone structures. The method described decreases design time, and is of similar accuracy to the manual method.

The'cave' mineral oxammite: a high resolution thermogravimetry and Raman spectroscopic study

The thermal decomposition of natural ammonium oxalate known as oxammite has been studied using a combination of high resolution thermogravimetry coupled to an evolved gas mass spectrometer and Raman spectroscopy coupled to a thermal stage. Three mass loss steps were found at 57, 175 and 188°C attributed to dehydration, ammonia evolution and carbon dioxide evolution respectively. Raman spectroscopy shows two bands at 3235 and 3030 cm-1 attributed to the OH stretching vibrations and three bands at 2995, 2900 and 2879 cm-1, attributed to the NH vibrational modes. The thermal degradation of oxammite may be followed by the loss of intensity of these bands. No intensity remains in the OH stretching bands at 100°C and the NH stretching bands show no intensity at 200°C. Multiple CO symmetric stretching bands are observed at 1473, 1454, 1447 and 1431cm-1, suggesting that the mineral oxammite is composed of a mixture of chemicals including ammonium oxalate dihydrate, ammonium oxalate monohydrate and anhydrous ammonium oxalate.