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This paper describes an end-to-end system implementation of a transactional memory (TM) programming model on top of the hardware transactional memory (HTM) of the Blue Gene/Q machine. The TM programming model supports most C/C++ programming constructs using a best-effort HTM and the help of a complete software stack including the compiler, the kernel, and the TM runtime. An extensive evaluation of the STAMP and the RMS-TM benchmark suites on BG/Q is the first of its kind in understanding characteristics of running TM workloads on real hardware TM. The study reveals several interesting insights on the overhead and the scalability of BG/Q HTM with respect to sequential execution, coarse-grain locking, and software TM.

From 1990-2005 at Ochsner Medical Center in New Orleans, LA, cardiopulmonary bypass (CPB) was used only when necessary during lung transplantation surgeries. Ochsner's lung transplant program was closed for more than 4 years after Hurricane Katrina, and since the program's reestablishment in 2010, the majority of lung transplantation surgeries have been performed with the patient on CPB and with a median sternotomy incision. The purpose of this study was to compare the outcomes of the CPB and non-CPB groups.After institutional review board approval, we conducted a retrospective review of the entire program using the Ochsner lung transplant database to identify patients in the non-CPB group from 1990-2005 and in the CPB group from 2010-2014. We calculated 1- and 3-year survival rates for each patient and reviewed medical records for evidence of stroke, the need for operative reexploration, and venous stenosis. We also performed a subgroup analysis of the first 20 consecutive patients undergoing lung transplantation on CPB with median sternotomy from February 2010 through April 2011 to examine intraoperative blood product use, the quantity of blood products administered, CPB cannulation and pump complications, ischemic time, and primary graft dysfunction.Of the 208 patients in the non-CPB group, 74% had 1-year graft survival and 55% had 3-year survival following transplantation. After February 2010, 79 patients underwent lung transplantation on CPB with median sternotomy, and 90% of those patients had 1-year graft survival. Of the 46 patients available for 3-year follow-up, 59% were alive with functional grafts. The difference in 1-year survival rates between the 2 cohorts was statistically significant. Two deaths, 3 strokes, and 5 reexplorations of the chest for bleeding occurred during the perioperative time period in the CPB group, but no mortality was associated with these perioperative events. One patient who had perioperative complications died within the first year; the death was attributable to gastric perforation.Patients' early outcomes appear to have improved with the use of CPB and median sternotomy; however, 3-year survival is similar to the non-CPB group. Technical benefits of CPB with median sternotomy include decreased warm ischemia time during graft implantation, controlled hemodynamics and reperfusion, avoidance of single-lung ventilation of a freshly implanted graft, and the option to open the left atrium for implantation of a venous cuff without using a clamp. The surgical exposure facilitated by CPB with median sternotomy for lung transplantation appears to be a safe and feasible approach for lung transplantations.

The primary goal of this research is to identify and examine the components of responsible drinking advertisements. We will examine industry and government related advertisements as we try to understand one of our major questions: does the source influence the validity of the message? The next group of major questions that we will be looking to answer is how are the vague quantifiers used in responsible drinking campaigns interpreted by the public? How many drinks do people consider “too much?” What does “drink responsibly” really mean? The third major question is whether or not an individual’s current consumption patterns of alcohol have any effect on how individuals assess responsible drinking campaigns. Our qualitative research has indicated that social influences can be strongly related with drinking patterns; this will be further examined in our quantitative research. Also, we will be looking into some of the psychology behind industry and government sponsored advertisements as well as gathering and interpreting information from a sample of our target demographic. Our target demographic consists of both male and females between the ages 18-24. Our literature review and qualitative analysis gave us good insight into some of the potential answers to our questions. We will use these potential answers from our previous research to guide us as we attempt to conduct conclusive research based on a sample data of 169 individuals. Our findings will aid us in developing conclusions and recommendations for Alberta Health Services.

Outlier detection and ensemble learning are well established research directions in data mining yet the application of ensemble techniques to outlier detection has been rarely studied. Here, we propose and study subsampling as a technique to induce diversity among individual outlier detectors. We show analytically and experimentally that an outlier detector based on a subsample per se, besides inducing diversity, can, under certain conditions, already improve upon the results of the same outlier detector on the complete dataset. Building an ensemble on top of several subsamples is further improving the results. While in the literature so far the intuition that ensembles improve over single outlier detectors has just been transferred from the classification literature, here we also justify analytically why ensembles are also expected to work in the unsupervised area of outlier detection. As a side effect, running an ensemble of several outlier detectors on subsamples of the dataset is more efficient than ensembles based on other means of introducing diversity and, depending on the sample rate and the size of the ensemble, can be even more efficient than just the single outlier detector on the complete data.